Freshwater and estuarine radioecology: proceedings of an international seminar, Lisbon, Portugal, 21-25 March 1994

Studies in Environmental Science 68

FRESHWATER AND ESTUARINE RADIOECOLOGY Proceedings of an International Seminar, Lisbon, Portugal, 21-25 March 1994

Editors:

G. Desmet

European Commission,Directorate General XXII-F-6, Rue de Treves 61, 1049 6russels, Belgium

R.J. Blust

Department of Biology, University of Antwerp, Groenenborgerlaan 171,2020 Antwerp, Belgium

R.N.J. Comans

ECN, Petten, The Netherlands

J.A. Fernandez

Universidad de Malaga, Campus de Teatinos sln, 29071, Malaga, Spain

J. Hilton

Institute of Freshwater Ecology, River Laboratory, East Stoke, Wareham, Dorset 6H20 666, UK

A. de Bettencourt

Departmento de Protecpio e Seguranqa Radiologica, DirecqBo Geral do Ambiente, Estrada NacionalIO, 2686 Sacavem, Portugal Assistant Editors:

P.G. Appleby, P. BeneS, U. Bergstrom and J. Remacle

1997 ELSEVIER Amsterdam - Lausanne - New York Oxford Shannon - Tokyo

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ELSEVIER SCIENCE B.V. Sara Burgerhnrtstraat 25 P.O.Box 21 I , lo00 AE Amsterdam, The Netherlands

Library o f C o n g r e s s Cataloging-in-Publication

Data

Freshwaxer and estuarine radioecology : proceedings o f an international seminar, Lisbon, Portugal, 21-25 March 1994 / editors, G. Desmet let al.1. p. cm. -- (Studies in environmental science ; 68) Includes bibliographical references and index. I S B N 0-444-82533-9 1. Freshwater radioecology. 2. Estuarine radloecology. I. Desmet. G. 11. Series. 0H543.9.F74 1997 577.6'277--dc21 97-20761 CIP

...

ISBN 0-444-82533-9 0 1997 ELSEVIER SCIENCE B.V. All rights reserved.

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International Seminar on Freshwater and Estuarine Radioecology Program Committee B.G. Blaylock J . Brittain

A. Cremers A. de Bettencourt G. Desmet

L. Foulquier J.M. Godoy

J. Hilton A. Janssens

F. Mingot Buades E. Schulte 0. Vanderborght 0. Voitsekhovitch

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List of contributors J.M. Abril Dpto. Fisica Aplicada, E. U.Ingenieria Tecnica Agricola, Universidad de Sevilla, Ctra. Utrera km. 1, 41014-Seville, Spain P.G. Appleby Department of Applied Mathematics and Theoretical Physics, University of Liverpool, Liverpool L69 3BX, UK 0. Bashkov Institute of Hydrobiology, Academy of Sciences of Ukraine, Geroev Stalingrada Prosp., 12,254210 Kiev, Ukraine

J.-P. Baudin Institut de Protection et de Suretk Nucleaire, Departement de Protection de 1,Environnement et des Installations, Laboratoire des Eaux Continentales, IPSNICEA, 13108 St-Paul-122-Durance, France, and Centre National de la Recherche Scientifique A. Bayer Bundesamt f i r Strahlenschutz, Institut f i r Strahlenhygiene, Postfach 1108, 0-85762 Oberschleipheim, Germany

K. Beaugelin Institut de Protection et de Surete Nucleaire, Dkpartement de Protection de I’Environnement et des Installations, Laboratoire des Eaux Continentales, IPSNI CEA, 13108 St-Paul-lez-Durance,France M. Belli m P A , Via Vitaliano Brancati 48, 00144 Rome, Italy

N. Belova Moscow University, Faculty of Biology, Department of Ichthyology, Kosinskaja str. 28-1-135, Moscow 111538, Russia V. Belyaev Institute of Hydrobiology, Academy of Sciences of Ukraine, Geroev Stalingrada Prosp., 12,25421 0 Kiev, Ukraine

P. Beneg

Department of Nuclear Chemistry, Czech Technical University, 11519 Prague 1, Bwhova 7, Czech Republic

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U. Bergstrom Studsvik Eco & Safety AB, S-61182 Nykoping, Sweden V. Berkovsky Ukrainian Centre of Radiation Medicine, 53 Melnikov St., UA-252050, Kiev, Ukraine I.Ya. Bilyi Ukrainian Hydro-Meteorological Institute, Nauka Ave. 37, Kiev, 252028, Ukraine

H.E. Bjgrnstad Laboratory of Analytical Chemistry, Agricultural University of Norway, As, Norway (Present address: Solberg, Sand, N-1440 Drgbak, Norway)

R. Blust

Department of Biology, University of Antwerp (RUCA), Groenenborgerlaun 171,2020 Antwerp, Belgium

J. Boardman AEA, Warrington, Cheshire WA3 6AT, UK L. Braf Institute of Limnology, Uppsala University, Norbyvtigen 20, 75236 Uppsala, Sweden

J.E. Brittain Freshwater Ecology and Inland Fisheries Laboratory (LFI), University of Oslo, Sarsgt. 1, 0562 Oslo, Norway A. Bulgakov Institute of Experimental Meteorology, S P A “Typhoon”,Lenin av. 82,249020 Obninsk, Kaluga Region, Russian Federation C.V. Carreiro DGAIDPSR, 2685 Sacave‘m, Portugal F.P. Carvalho Direccao Geral do Ambiente, Departamento de Proteccao e Seguranca Radiologica, E N 10, P-2685 Sacavem, Portugal (Present address: International Atomic Energy Agency, Marine Environment Laboratory, P.O. Box 800, MC 98012, Monaco Cedex)

M.C e m i

Department of Nuclear Chemistry, Czech Technical University, 11519 Prague 1, Bgehovci 7, Czech Republic

L. Chant Environmental Research Branch, Chalk River Laboratories, Chalk River, Ontario KOJ 1JO, Canada

...

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P. Ciffroy Electricite' de France, Environment Department 6, quai Watier, 78401 Chatou, France B. Claveri Centre de Recherches Ecologiques, Universite' de Metz, Laboratoire d'Ecotoxicologie, B.P. 4116, 57040 Metz, France E. Colizza Istituto di Geologia e Paleontologia, Universita di Trieste, via Edoardo Weiss, Comprensorio d i S. Giovanni, 34127 Trieste, Italy

R.N.J. Comans Netherlands Energy Research Foundation (ECN), P.O. Box 1, 1755 ZG Petten, The Netherlands S. Comhaire Department of Biology, University of Antwerp (RUCA), Groenenborgerlaun 171,2020 Antwerp, Belgium

J.A. Corisco Dpto. de Protecpio e Seguranga Radiologica, D.G.A., Estrada Nacional 10, 2685 Sacave'm, Portugal A. Cremers, Laboratory for Colloid Chemistry, Katholieke Universiteit Leuven, Kardinaal Mercierlaan 92, B-3030, Heverlee, Leuven, Belgium F. D'haeseleer Department of Biology, University of Antwerp (RUCA), Groenenborgerlaan 171,2020 Antwerp, Belgium H. Dahlgaard Ris@National Laboratory, DK-4000 Roskilde, Denmark M.E.M. De Luca Instituto de Biofisica Carlos Chagas Filhol UFRJIIlha do Fundcio, RJ, Brazil R. Delfanti Centro Ricerche Ambiente Marino, ENEA, CP 316,19100 L a Spezia, Italy G . Desmet Directorate-General XII, Science, Research and Development, Rue de la Loi, 200, B - 1049 Brussels, Belgium A. Diez de 10s Rios Dpto. de Fisica Me'dica, Universidad de Malaga, Campus de Teatinos s l n . 29071, Malaga, Spain A.M. Dowdall Radiological Protection Institute of Ireland, 3 Clonskeagh Square, Clonskeagh Road, Dublin 14, Ireland

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M. Eckerle Fachhochschule Ravensburg-Weingarten, P.O. Box 1261, 0-88241 Weingarten, Germany G.P. Fanzutti Istituto di Geologia e Paleontologia, Universita di Trieste, via Edoardo Weiss, Comprensorio di S. Giovanni, 34127 Trieste, Italy J.A. Fernhdez Dpto. de Biologia Vegetal, Universidad de Malaga, Campus de Teatinos s l n . 29071, Malaga, Spain E.S.B. Ferraz Centro de Energia Nuclear Agricultura, Universidade de ScZo Paulo, 13400970 Piracicaba, S6o Paulo, Brazil F. Finocchiaro Istituto di Geologia e Paleontologia, Universita d i Trieste, via Edoardo Weiss, Comprensorio d i S. Giovanni, 34127 Trieste, Italy M.A. Fomovsky Institute of Hydrobiology, Academy of Sciences of Ukraine, Geroev Stalingrada Prosp. 12,254210 Kiev, Ukraine L. Foulquier Institut de Protection et de Surete' Nucle'aire, Service djEtudes et de Recherche sur les transferts dans l%nvironnement, IPSNI CEA, Cadarache, B.P. 1, 13108,Saint -Paul -Lez -Durance, France M . Frignani Istituto per la Geologia Marina del CNR, Via Gobetti 101, 40129 Bologna, Italy M . Fukui Division of Fuel Cycle and Environment, Kyoto University, Noda, Kumatoricho, Osaka 590-04, Japan M.R. Garcia CIEMAT-IMA. Avda. de la Complutense 22, Madrid 28040, Spain M. Garcia-Lebn Dpto. Fisica Atdmica, Molecular y Nuclear, Universidad de Sevilla, Apdo. 1065, 41080-Seville, Spain M.J. Garcia-Shchez Dpto. de Biologia Vegetal, Universidad de Mcilaga, Campus de Teatinos s In., 29071, Malaga, Spain C. Gasc6 CIEMAT-IMA. Avda. de la Complutense 22, Madrid 28040, Spain P.A. Geelhoed-Bonouvrie Netherlands Energy Research Foundation (ECN), P.O. Box 1, 1755 ZG Petten, The Netherlands

J.A. Gil Corisco DGAIDPSR, E.N. 10,2685 Sacave'm, Portugal C. Giovani Servizio di Fisica Sanitaria, Lab. Reg. Rad. Ambientale USL, Udine, Italy J.M. Godoy Instituto ale Radioproteqbo e Dosimetria IIRD-CNEN, Av. Salvador Allende s l n Jacarepagua, Rio de Janeiro, R J , Brazil CP 37750 (Present address: Pontificia Universidade Catdlica do Rio de Janeiro, Depto. de Quimica, Rua Marqugs de Sbo Vincente 225, Gavea, R J , Brazil, CEP 22453-900) R.H. Hadderingh KEMA, Environmental Services, P.O. Box 9035, 6800 E T Arnhem, The Netherlands L. H a a n s o n Institute of Earth Sciences, Uppsala University, Norbyv. 18B, 752 36 Uppsala, Sweden A. Hambuckers University of Liege, Plant World Observatory, B77 Sart Tilman, B-4000 Liege, Belgium F. Hambuckers-Berhin University of Liege, Microbial Ecology, B22 Sart Tilman, B-4000 Liege, Belgium R. Heling KEMA, Utrechtseweg 310, 6812 AR Arnhem, The Netherlands M.A. Heredia Dpto. de Biologia Vegetal, Universidad de Malaga, Campus de Teatinos sln., 29071 Malaga, Spain J. Hilton Institute of Freshwater Ecology, The River Laboratory, East Stoke, Wareham, Dorset BH20 2BB, UK T.G. Hinton Savannah River Ecology Laboratory, Drawer E, Aiken, SC 29802, U S A H. Hofer ABB Reaktor GmbH, Abteilung Strahlenschutz, Postfach 100563, 0-68140 Mannheim, Germany (Present address: Hofer & Bechtel GmbH, Postfach 1068, 0-63527 Mainhausen, Germany) H. Hummel KNAW-NIOOI CEMO Vierstraat 28, 4401 E A Yerseke, The Netherlands M.P.M. Janssen National Institute of Public Health and Environmental Protection, Laboratory of Radiation Research (RNM-LSO),P.O. Box 1,3720 BA Bilthoven, The Netherlands

J. John Department of Nuclear Chemistry, Czech Technical University, 115 19 Praha 1, Brehova 7,Czech Republic L. Jurchuk Institute of Hydrobiology, Academy of Sciences of Ukraine, Geroev Stalingrada Prosp., 12,254210Kiev, Ukraine

S. Kaminski Fachhochschule Ravensburg-Weingarten, P.O. Box 1261, 0-88241 Weingarten, Germany V. Kanivetc Ukrainian Hydrometeorological Research Institute, Kiev, Ukraine T. Klenk Fachhochschule Ravensburg-Weingarten, P.0. Box 1261, 0-88241 Weingarten, Germany

K. Konitzer Institute of Earth Sciences, Uppsala University, Norbyviigen 18B, 752 36 Uppsala, Sweden A. Konoplev Institute of Experimental Meteorology, SPA “Typhoon”,Lenin av. 82,249020 Obninsk, Kaluga Region, Russian Federation

H.W. Kiister National Institute of Public Health and Environmental Protection, Laboratory of Radiation Research (RIVM-LSO),P.O. Box 1,3720B A Bilthoven, The Netherlands A.O. Koulikov Institute of Evolutionary Morphology and Ecology of Animals, Leninsky Prospect 33,Moscow 11 7071,Russia A. Kudelsky Institute of Geological Sciences, Academy of Sciences of Belarus, Minsk, 7 Zhodinskaya str., Belarus A. Lambrechts

Institut de Protection et de Surete‘ Nuclbaire, Service d’Etudes et de Recherche sur les transferts dans l%nvironnement, IPSNI CEA, Cadarache, B.P. 1, 13108,Saint-Paul-Lez-Durance, France

L. Langone Istituto per la Geologia Marina del CNR, Via Gobetti 101,40129 Bologna, Italy

G. Laptev Ukrainian Hydrometeorological Research Institute, Kiev, Ukraine

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J.F.M.M. Lembrechts National Institute of Public Health and Environmental Protection, Laboratory of Radiation Research (RNM-LSO),P.O. Box 1,3720 B A Bilthoven, The Netherlands

G. Lindner Fachhochschule Coburg, P.O. Box 1652,D-96406 Coburg, Germany

I. Los'y Ukrainian Centre of Radiation Medicine, 53 Melnikov St., UA-252050, Kiev, Ukraine M.J. Madruga Laboratory for Colloid Chemistry, K. U. Leuven, Kardinaul Mercierlaan 92, 3001 Heverlee, Belgium (Present Address: DGAIDPSR, E.N. 10, 2685 Sacave'm, Portugal) M.J. Madruga DGAIDPSR, 2685 Sacave'm, Portugal

F.J. Maringer Bundesforschungs- und Priifzentrum Arsenal, Faradaygasse 3, A-1030 Vienna, Austria A. Martinez-Aguirre Facultad de Fisica, Universidad de Sevilla, Apdo. 1065, 41080 Sevilla, Spain

G. Mattassi Servizio di Igiene Ambientale, USL, Palmanova, Italy

A.T. McGarry Radiological Protection Institute of Ireland, 3 Clonskeagh Square, Clonskeagh Road, Dublin 14, Ireland M. Meili Institute of Earth Sciences, Uppsala University, Norbyvagen 18 B, 752 36 Uppsala, Sweden

R. Melis

Istituto di Geologia e Paleontologia, Universita di Trieste, via Edoardo Weiss, Comprensorio di S. Giovanni, 34127 Trieste, Italy L. Monte ENEA, CP 2400,00100 Roma AD, Italy 0.1. Nasvit Institute of Hydrobiology, Academy of Sciences of Ukraine, Geroev Stalingrada Prosp. 12,254210 Kiev, Ukraine D.J. Niquette Savannah River Ecology Laboratory, Drawer E, Aiken, SC 29802, U S A

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S . Ovsyannikova Belarussian State University, Minsk, 14 Leningradskaya str., Belarus

R. Padovani Servizio di Fisica Sanitaria, Lab. Reg. Rad. Ambientale USL,Udine, Italy J. Palomares CIEMAT-IMA.Avda. de la Complutense 22, Madrid 28040, Spain C. Papucci Centro Ricerche Ambiente Marino, ENEA, CP 316, 19100 L a Spezia, Italy

V. Pashkevich Institute of Geological Sciences, Academy of Sciences of Belarus, Minsk, 7 Zhodinskaya str., Belarus

R.M.J. Pennders National Institute of Public Health and Environmental Protection, Laboratory ofRadiation Research (RWM-LSO),P.O. Box 1,3720 BA Bilthoven, The Netherlands L. P6rez del Villar CIEMAT-IMA.Avda. de la Complutense 22, Madrid 28040, Spain

R. Periaiiez Dpto. Fisica Aplicada, E. U.Ingenieria Tkcnica Agricola, Universidad de Sevilla, Ctra. Utrera km. 1, 41014-Seville, Spain Ye. Petryayev Belarussian State University, Minsk, 14 Leningradskaya str., Belarus

R. Piani Istituto di Geologia e Paleontologia, Universita di Trieste, via Edoardo Weiss, Comprensorio di S. Giovanni, 34127 Trieste, Italy

v. Popov

Institute of Experimental Meteorology, SPA “Typhoon”,Lenin av. 82,249020 Obninsk, Kaluga Region, Russian Federation A. Popov S P A Typhoon, Leninstr 82, Obninsk, Kaluga Region, 249020 Russia M. Pozuelo CIEMAT-IMA.Avda. de la Complutense 22, Madrid 28040, Spain D. Rank Bundesforschungs- und Prufzentrum Arsenal, Faradaygasse 3, A-1030 Vienna, Austria W. Raskob Forschungszentrum Karlsruhe GmbH, INR, P.O. Box 3640, 0-76021 Karlsruhe, Germany, and D.T.I. Dr. Trippe Ingenieurgesellschaft m.b.H., Amalienstr. 6 3 f 65, 76133 Karlsruhe, Germany

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J.B. Rasussen Department of Biology, McGIll University, 1205 Dr. Penfield Ave., Montreal, Quebec H3A l B 1 , Canada

M . Ravaioli

Istituto per la Geologia Marina del CNR, Via Gobetti 101, 40129 Bologna, Italy

J. Remacle University of Liege, Microbial Ecology, B22 Sart Tilman, B-4000 LiGge, Belgium

M . Riccardi ANPA, Via Vitaliano Brancati 48, 00144 Rome, Italy T. Richter Fachhochschule Ravensburg-Weingarten, P.O. Box 1261, 0-88241 Weingarten, Germany

V. Romanenko Institute of Hydrobiology, Academy of Sciences of Ukraine, Geroev Stalingrada Prosp., 12,254210 Kiev, Ukraine

D.J. Rowan Environmental Research Branch, Chalk River Laboratories, Chalk River, Ontario KOJ 1JO, Canada (Present address: Department of Radiological Health Sciences, Colorado State University, Fort Collins, CO 80523-1673, USA) I.N. Ryabov Institute of Evolutionary Morphology and Ecology of Animals, Leninsky prospect 33, Moscow 11 7071, Russia T.P. Ryan Radiological Protection Institute of Ireland, 3 Clonskeagh Square, Clonskeagh Road, Dublin 14, Ireland U. Sansone ANPA, Via Vitaliano Brancati 48, 00144 Rome, Italy R. Saxen Finnish Centre for Radiation and Nuclear Safety, P.O. Box 268, 00101 Helsinki, Finland B. Schink Fakultat fur Biologie, Universitat Konstanz, P.O. Box 5560, 0-78434 Konstanz, Germany P.G. Schout KNAW-NIOOI CEMO Vierstraat 28, 4401 E A Yerseke, The Netherlands G. Schroder Institut f i r Seenforschung, Landesanstalt f u r Umweltschutz Baden- Wurttemberg, P.O. Box 4146,D-88081 Langenargen, Germany

F. gebesta Department of Nuclear Chemistry, Czech Technical University, 115 19 Praha I , Brehova 7, Czech Republic F. Siclet Electricite' de France, Environment Department 6, quai Watier, 78401 Chatou, France

J.T. Smith Institute of Freshwater Ecology, River Laboratory, East Stoke, Wareham, Dorset BH20 6BB, UK G. Sokolik Belarussian State University, Minsk, 14 Leningradskaya str., Belarus V.D. Solomatina Institute of Hydrobiology, Academy of Sciences of Ukraine, Geroev Stalingrada Prosp. 12,254210 Kiev, Ukraine B. Sundblad Studsvik Ecology & Safety, 611 82 Nykoping, Sweden B.M.H. Timmermans KNAW-NIOOI CEMO Vierstraat 28,4401 E A Yerseke, The Netherlands P. Tkalich Institute of Cybernetics, Prospect Glushkova 42, Kiev, 252 207 Ukraine A. Travesi CIEMAT-IMA. Avda. de la Complutense 22, Madrid 28040, Spain M. Tschurlovits Atominstitute of Austrian Universities, Schiittelstrasse 115, A-1020 Vienna, Austria G.H.F.M. van Aerssen KEMA, Environmental Services, P.O. Box 9035, 6800 ET Arnhem, The Netherlands J. van der Steen KEMA, Utrechtseweg 310, 6812 AR Arnhem, The Netherlands L. Van Ginneken Department of Biology, University of Antwerp (RUCA), Groenenborgerlaan 171,2020 Antwerp, Belgium 0.Vanderborght Department of Biology, University of Antwerp (RUCA), Groenenborgerlaan 171,2020 Antwerp, Belgium M.C. Vaz Carreiro Dpto. de Protecch e Seguranca Radioldgica, D.G.A., Estrada Nacional 10, 2685 Sacave'm, Portugal

D. Vazelle

Electricit6 de France, Environment Department 6, quai Watier, 78401 Chatou, France

J. Vesely Czech Geological Survey, 118 21 Praha 1, Malostranske namesti 19, Czech Republic M. Vidal DGAIDPSR, 2685 Sacavem, Portugal

O.V. Voitsekhovitch Ukrainian Hydro-Meteorological Institute, Nauka Ave. 37, Kiev, 252028, Ukraine M. Walser Fachhochschule Ravensburg- Weingarten, P.O. Box 1261, 0-88241 Weingarten, Germany

J. Wauters Laboratory of Colloid Chemistry, Katholieke Universiteit Leuven, Kardinaal Mercierlaan 92, 3001 Heverlee, Belgium F.W. Whicker Savannah River Ecology Laboratory, Drawer E, Aiken, SC 29802, U S A A. Zanello Servizio di Igiene Ambientale, USL, Palmanova, Italy S. Zanini Servizio di Fisica Sanitaria, Lab. Reg. Rad. Ambientale USL, Udine, Italy

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Preface G. Desmet Directorate-General XU,Science, Research and Development, Rue de la hi, 200, B-1049 Brussels, Belgium

The Chernobyl accident raised the profile of radioecology throughout the world. It stimulated many scientists, who were previously not associated with radioecology, to redirect their work and make use of the multiple opportunities for large scale “field experiments” to further particular areas of biological and earth sciences. In return they have brought new ideas which have helped our understanding of radioecological processes. Concurrently, the interpretation by established radioecologists of field data, collected under the dynamic conditions of the Chernobyl accident, has widened our appreciation of the complexity of the transport processes. As a result of these studies, significant steps have been made in our understanding of the transport of radionuclides through, and the accumulation of radionuclides in aquatic systems. The second reason for having this Seminar is to describe the consequences of the Chernobyl accident for water reservoirs and eventually to come with advice for safeguarding or improving the water quality. At present in radiological research the emphasis is now much more directed towards an integral research of complex ecosystems where the dynamic interaction between the ecosphere and the radiocontaminants is investigated. This change was bound to happen due to changed scientific insights after the large accidents and due to a changed coordination approach of the EC, aiming at more Added Scientific Value for Member State research. The objectives of radioecology thence are closely connected to this definition; they have although of course been very much influenced by the evaluation of the major nuclear events altering the quality and useability of the affected environment. These objectives then can be summarized as follows: - to understand and quantify the factors which determine the fate of radionuclides at short, medium and long term afier the deposition of released radionuclides; - to allow the calculation of the dose man can incur from using its environment;

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- t o provide methods for the mitigation of the consequences of an accident - to mitigate but maintaining the ecological and economic ”value” of the affected area. This Seminar allowed a rather precise evaluation of the research situation and needs in this particular field of fresh and estuarine water radioecology and guided the Commission’s services in the preparation of its specific work programme and its reflections how to work towards an environmental management structure and package for safeguarding of river water quality and of its derived food products or for mitigating the consequences of a nuclear accident. I invite therefore the experts assembled, be they from the European Union, the countries of European Economic Area or the former Soviet Union, not to dwell only on explicit and distinct scientific issues, but also to draw firm conclusions with respect to the scientific and technical requirements for the effective environmental management of aquatic systems, bearing in mind the three general objectives of radioecology as outlined above. It is therefore desirable that at the end of this seminar senior scientists have already delineated a draft concept of the works that would deserve or need further EC support in this field, and specified the skills needed to have fulfilled the projected tasks at the end of the contract period. I realise that this is a rather tough message, although it is obvious that such an important meeting with such an outstanding occupation of highly qualified experts should not disband without a clear concept of their field of research and of its future organisation in the context of subsidiarity and thus the requirements of their individual Member States. Hereby the European Commission wants to provide the framework wherein the generic parameters can be investigated and included in a site-specific package of operational parameters. This is, in its turn, the renowned Added Scientific Value of research in the context of the R&D efforts of the European Union.

Freshwuter und E.vtuurine Rudiwcolr,xy Edited by C. Desmet et d.

0 1997 Elsevier Science B.V. All rights reserved

3

Modelling of radiocesium in lakes - on predictive power and lessons for the future L. HAkanson Institute of Earth Sciences, Uppsula University, Norbyu. 18B, 752 36 Uppsulu,Sweden

ABSTRACT

A general definition of the predictive power (PP) of a model has been proposed and tested, where PP = RV((1.1- slope)-CV).R2 is the mean ?-value of several validations, and (1.1- slope) is the mean slope factor in such validations, i.e., regressions of independent empirical data versus model-predicted values. CV is the coefficient of variation for ? in these validations (regressions). Using this definition, it can be shown that: (a) within the range of application, empirical models (for radiocesium in lakes) seem to give higher P P than dynamic models; and (b) the highest PP is not necessarily given by the most complex dynamic model. This generally results from inclusion of model variables with a high variability and/or uncertainty. The predictive power of a model is governed by the weakness of its weakest part. 1.AIM

The results presented in this paper emanate from the VAMP project, where VAMP is an acronym for d i d a t i o n of model gredidions. The VAMP project was a large international project run by the UN’s International Atomic Energy Agency (IAEA) in Vienna. This project was initiated aRer the Chernobyl accident and the models used in the project are the state-of-the-art in modelling of radiocesium in lakes. A great deal of information about fluxes, rates and biomasses can be learned from the Chernobyl accident, and the transport of this pulse (radiotracer) through ecosystems. The VAMP models are intended to incorporate the most fundamental processes affecting radiocesium in lake water and predatory fish. The models should provide reasonable predictions if the “unthinkable” accident should happen again. They are meant to be general models applicable for most types of lakes driven by readily accessible environmental variables (lake-specificvariables). These models will be presented

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in a technical report from IAEA, scheduled for September 1997. The objective here is to use three of these models to illustrate some important principles in all types of modelling, namely predictive power and some technical tools to increase predictive power. In short, this paper aims to: - present a quantitative, general definition of the predictive power of a model; - discuss predictive power for empirical and dynamical models in general terms, but to illustrate these principles with data for radiocesium in lakes; - address the very important question of optimal size of predictive models; - discuss three modelling tools that can increase the predictive power of models for radiocesium in lakes, namely (1) a potassium moderator, accounting for the fact (see, e.g., Refs. [1-31) that the K-concentration influences the bio-uptake rate of radiocesium in lakes, (2) a seasonal variability moderator (see Ref. [4])accounting for seasonal variabilities in tributary water discharge, and a water retention rate moderator (see Ref. [4]) accounting for differences among lakes in water retention rate. It should be noted that this is not a literature review. The aim is to discuss and define predictive power and to illustrate that this is important. 2. DEFINING PREDICTIVE POWER

Predictive power should not just be two empty words. A scientific definition of the concept is necessary so the meaning is clear. The aim of the first section is to give a definition of predictive power and the rationale for that definition. Figure 1A illustrates two hypothetical curves, one based on empirical data, the other on modelled values. We can see that there is an almost perfect agreement between the two curves. So, the model provides a very good prediction for this particular y-variable in this particular lake. One way t o quantify the fit between empirical and modelled y is to do a regression. The r2-value, the intercept and the slope of the regression line will reveal the fit. The ?-value and the slope should be as close to one as possible (Fig. 1B) and the intercept should ideally cross the origin. Would this model work also for other lakes or ecosystems? If the answer is yes, then we may have a very useful predictive model. One can, however, safely assume that the r2-value and the slope will not be equally good in all cases. There will be situations when the model will yield a poor prediction, a low r2 and a slope much lower or higher than one. Such a spread of values indicates the uncertainty of the model in predictions. This is illustrated in Table 1. In this example, we have tested a given (hypothetical) model in 15 situations. For each validation, we can determine the ?-value and the slope between empirical and modelled y. We can also determine the coefficient of variation (CV= standard deviatiodmean value) for r2,If the model generally has a high predictive power, then the CV should be small. It is 0.19 in Table 1.

5 TABLE 1 Illustration and definition of predictive power (PP) from mean ?, mean slope factor and CV after 15 model validations Test no.

r2

Slope (a)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

0.95 0.82 0.77 0.96 0.66 0.55 0.88 0.46 0.92 0.91 0.68 0.86 0.88 0.92 0.79

0.90 0.85 2.10 1.50 1.20 1.00 1.30 0.60 0.80 1.50 1.20 2.00 0.95 0.67 0.80

MV(=R2) SD

0.80 0.15 0.19

cv

If slope > 1 than l/slope

0.48 0.67 0.83 1.00 0.77

0.67 0.83 0.50

1,l-a 0.20 0.25 0.62 0.43 0.27 0.10 0.33 0.50 0.30 0.43 0.27 0.60 0.15 0.43 0.30 0.35

Predictive power, PP = 0.80/(0.35.0.19)= 12.0. PP = R2/((1,1-slope)CV)

From these arguments on r2,slope and CV, we may give a general definition of predictive power (PP): PP = R2/((1.1- a) CV)

(1)

where R2 is the mean rz of all model validations: the higher R2the higher PP. One could also use the median r2-value.This is a matter of definition, and here we used the mean value. The slope,a,of the regression line may be smaller and larger than 1. If the slope is smaller than 1,we quantify the influence on PP by means of the factor 1.1- a.Since a may be equal to 1, and since division by zero is not allowed, we use 1.1instead of just 1. Other constants than 1.1 may be used, but 1.1will cause PP-values to vary between 0 and 100 (see Fig. 2). This means that the slope factor is always larger than 0.1. If the slope is larger than 1,we simply set a to Uslope, and use the same factor. This means that a slope of 0.5 will give the same factor as a slope of 2, namely 1.1 - 0.5 = 0.6 or 1.1- 1/2 = 0.6. One could also account for the intercept in this approach, but that would add very little since the slope and the r2-value are already used. CV is the coefficient of variation for the r2-valuesobtained in the empirical tests (Table 1).

6 + Emp. data

181

04

0

o Mc.yielled values

'

.

5

10 15 20 25 30 35 40 45 Time

1 t

50

Modelled values

Fig. 1. (A) Illustration of a very good correspondence between empirical data and modelled values. (B) The same data illustrated by regression analysis. The fit is almost perfect, the r2-valueis 1.00, but the slope is 1.11, which is higher then the ideal 1.00.

The predictive power of the given model is 12. This is a rather high value since the mean r2(i.e., R2)is as high as 0.80, the uncertainty linked to the slope is 0.35 and the CV is 0.19. In this case, we determine the CV-value from the spread around the ?-values. It is a measure of model uncertainty. Similar CV-values may be determined in other ways, e.g., by Monte Car10 simulations, which we will illustrate later on. Figure 2 gives two nomograms illustrating how R2,slope and CV influence PP. One can safely assume that CV in practice will never be zero for models of aquatic ecosystems, neither are models likely to yield r2-values of 1.00. Very good models may give r2-values of about 0.95. CV values lower than 0.1 ought t o be rare. From Fig. 2, we can note that with this definition, PP will generally be lower than 100. Models yielding PP higher than 10 would be very good. Models giving PP lower than 1 would be useless for all practical purposes. Such models have a poor fit (a low r2and/or a slope much diverging from 1)and great uncertainties (i.e., a high CV). Verbal models do not give any PP values at all! This expression of predictive power (Eq. (1))should be regarded like most models for complex systems: a tool which accounts, not for every conceivable situation and factor, but for the most important factors in a simple and useful manner. The fit between modelled values and empirical data is here

7

A: 100

T

R2

Nomogram f o r CV=O, 1

t ‘r PP=

R2 (1,1 -d*CV

i f a t l then 1 , l - a

i f w l then 1.1 -I/u

L

&

90

--

80-

Nomogram l o r slope=0,8

given by the r2-value and the slope factor. The fit may, however, be expressed in many alternative ways. Instead of the mean or median rz one could use the adjusted r2. All expressions related to such r2-values would depend on the number of data-pairs (n),the range and the transformation of the x- and y-variables. Logarithmic x- and y-variables will give different rz-values than non-transformed variables. Instead of using this definition of the slope factor, one could use other alternatives and also include the intercept. It should be stressed that the uncertainty (CV) is determined independently of the fit. One should not use, e.g., expressions related to the confidence interval of the regression line for the uncertainty since such measures are directly related to the r2-value [41. In this approach, the model uncertainty is expressed in two ways, either by Monte Carlo simulations or from repeated validations which enable the determination of CV from the obtained ?-values between modelled values and empirical data. There may be other approaches to express model uncertainty.

8

This is, as far as the author is aware, the first general definition of predictive power for ecosystem models. This definition should not be used in an uncritical manner and PP-values determined for different models for different purposes may not be directly comparable. In all modelling situations, it is the responsibility of the modeller to define and explain the presuppositions of the models and its applicability, so that the net result is more clarity and less confusion, not the other way around. Since predictive power is such an important concept in ecosystem and environmental modelling and research, we hope that by presenting this approach, this would stimulate endeavours to further discussions and tests on this topic. 3. PREDICTIVE POWER OF EMPIRICAL MODELS

Figure 3 illustrates an important message: limnetic ecosystems are extremely complex and any lake is characterized by many complicated interactions among biological, chemical, and physical variables. The components in Fig. 3 are fundamental. They include: - The relationship between lake pH, alkalinity and colour 151. - A load diagram relating a load (the input of total-P to a lake) and lake sensitivity (a function of theoretical lake water retention time, T) to their net effects - lake total-P concentration and lake trophic status [6]. - The relationship between the ratio of lake total-P concentration to mean depth, and the lake type as reflected by the bottom fauna [7]. - The effect of effective fetch and water depth on the potential dynamic conditions on the bottom (i.e., the bottom areas where erosion dominates are covered with coarse sediments, those where transportation dominates are covered with mixed sediments, and those where accumulation occurs are covered with fine sediments). In the resulting erosion-transportation-accumulation (ETA) diagram, the water content of surficial sediments defines a standard limit (WW= 50%)between the areas of erosion and transportation. WTIA is the limit between areas of transportation and accumulation [81, - The relationship between the load of organic matter, the oxygen levels and the benthic communities [9]. It is quite easy to produce a diagram like this, illustrating the complexities of natural ecosystems, but that alone is insufficient. One of the important tasks of predictive modelling is to describe such complicated relationships quantitatively and to rank the relative importance of different x-variables in predicting a given y-variable. It is important to use a hierarchical mode of thinking (Fig. 4). In lake radioecology, one would generally like to predict concentrations of radionuclides in water (because this can be a threat to the people using lake water for drinking, irrigation, swimming, fishing, etc.), and in fish eaten by man. These are the target y-variables to be predicted by the VAMP models.

9

0 5 10

c,

e

P

s c

1

15 20 25

30 35 40

lcml

45

50

Inwrascd conlarn~nel~on by orgaruc mauer U e c r r a s d oxygen cunmnUaUon

Fig. 3. “Everythingdepends on everything else”.An illustration of the complex interactions among various chemical, biological ind physical factors that may be used to characterize a lake ecosystem. From Ref. (41.

Then one needs to study the fluxes to, within and from these compartments (lake water and predatory fish). Everything in the lake could, potentially, influence such fluxes, but everything can not be of equal importance for these two specific predictions. Good predictive models are based on the most important processes - no more, no less. This is schematically illustrated by the hierarchical, tree-structure in Fig. 4. So, one needs reliable empirical data on the most important rates and model variables. But all empirical data from natural ecosystems are more or less uncertain. Two main approaches to address the problem of uncertainty analysis

10

Hierarchical, tree-structure starting with target y-variables to be predicted and a quantitative ranking of the most important model variables (XI. y h C s in fish eaten by man

y2= CS in lake water M

i 5

5

L a

0

x!2

x3

x4

x’2

n

!i

x-3

x6 7

xa

Fig. 4. Schematic illustration of a hierarchical, “top-t-Jwn’’ mode of thinking in predictive modelling. The target y-variables in this example are radiocesium in fish eaten by man and Cs in lake water.

exist: analytical methods [10-121 and statistical methods, like Monte Carlo techniques 113-151. In this section, we will only discuss Monte Carlo simulations. Figure 5 illustrates schematically why it is important to consider uncertainty. When working with mean values and frequency distributions of empirical data at the ecosystem level, there is always uncertainty about any model variable (x). This uncertainty is illustrated by the frequency distributions (the “gates”) in Fig. 5 . It should be noted that many variables are not initially normally distributed and only some of these variables may be transformed to normal distributions. The uncertainty in x is reflected in almost all descriptions of the observations. The regression parameters and the regression line they describe are uncertain, as are the mean y-value and the predicted y-value. In short, uncertainty dogs all ecological descriptions so it is important that we learn to look at this uncertainty, to describe it and to assess its effects with uncertainty tests. For example, all descriptions of a central tendency should be accompanied by a measure of dispersion, we may describe the uncertainty in regression with confidence bands, or we may calculate an uncertainty ellipse. If we have a predictive empirical model, y = o l l . x ~+ 0 1 2 . ~ 2+ 0 1 3 . ~ 3+ ~ x + 40 1 5 . ~ 5 + PI, based on five, more or less uncertain, empirical x-variables, then the

11 Slope

Predlctlve power Degrae of PP-rA2/(1 , l - l ) ’ C V explrnetlon

Model uncertainty

-I

a1

*

xl

+

@I

y2

= a2

*

xl

+

x2

+

p2

y3

= a3

’

xl

+

x2

+

x3

yl

+

p3

Fig. 5. Illustration of predictive power for three regression models. The model uncertainty (CV) is determined from Monte Carlo simulations. CV depends on uncertainties in model variables ( x ) and slope coefficients (a). The highest predictive power is obtained for two x-variables in this hypothetical example.

2-value (the degree of explanation obtained when empirical data are compared to modelled values in regression) would increase for each model variable added to the model. However, the model uncertainty might also increase, especially for the last x-variables in the model, and especially if these x-variables are uncertain. Large empirical models based on many such unreliable x-variables carry an accumulated uncertainty. This cumulative uncertainty may be quantified by Monte Carlo simulations, a technique to forecast the entire range of likely observations in a given situation; it can also give confidence limits to describe the likelihood of a given event. Let us assume that we would like to know the uncertainties associated with the simple model y = a l . x l + PI in Fig. 5. This is an empirical, statistical model derived for a certain number of lakes. The r2-valueis assumed to be 0.40. The simulated uncertainty in the xl-variable and the slope a1are given by the two frequency curves (the “gates”)showing the probabilities (or the frequencies) of

12

the values. The program generates individual estimates or “shots” through these two “gates”, and the result of doing this 10,000 times is the uncertainty curve for the predicted y-variable. The first CV in Fig. 5 is 0.2. The +95% confidence interval for the predicted y could also be determined (see Fig. 12 later on) but that measure of model uncertainty can be derived directly from rz and n, and it does not add any more information. This measure of model uncertainty, on the other hand, is produced by an independent method, Monte Carlo simulations. The next step uses a model with two x-variables. The ?-value has increased from 0.4 to 0.65. How about the model uncertainty? Adding one model variable does not alter the uncertainty of the first model variable, only the uncertainty of the slope of the first model variable, a2,which is reduced. This is illustrated by a smaller uncertainty “gate” in Fig. 5. We must also account for the uncertainty of the new model variable, xz. This is shown by the new uncertainty “gate”. A new Monte Carlo simulation will give a new coefficient of variation for y, 0.25, as compared to 0.2 for the first model. The predictive power connected to these two steps may now be determined. It is assumed that the slope in regressions is close to 1.The PP-value is 20 for step 1and 26 for step 2. So, PP has increased. In the next example, we add one more model variable, x3. In this case, rz increases from 0.65 to 0.85, the model uncertainty increases from 0.25 t o 0.35, and the predictive power decreases from 26 to 24. This may seem paradoxical, but it has to do with the fact that model uncertainty accumulates as more and more uncertain x-variables are included in the model. Note that this is just a pedagogical example. We will soon substantiate the argument by real lake data for cesium. To the extent that uncertainty increases with the number of variables, there is a problem of optimization between the generality of the model, which will increase with the number of x-variables, and the model uncertainty. We will discuss this theme in the following sections. The first focus is on the relationship between the ?-value and the uncertainty of the slope coefficient of the regression line. Table 2 gives (based on data from 14 Swedish lakes; see [61) an r-rank table (based on linear correlation coefficients of absolute values) for one of our target y-variables, the concentration of radiocesium in pike (Cs-pi88) in 1988 in relation to: (1) Cs-concentrations in pike (Bq k g ’ ww) caught in 1986 and 1987 and in fish eaten by pike, namely perch fry (Cs-pe86 and Cs-pe87). (2) Fallout, Cs-soil in Bq m-2. (3) Variables indicating the load of cesium to the lake, Cs-wat87 (Cs in lake water in 1987 in Bq 1-9, cesium in surface sediments (Cs-sed86 and Cs-sed87 in Bq kg-l dw) and cesium concentrations in material collected by sediments traps placed 2 m above the bed of the lakes (Cs-bo86 and Cs-bo87 in Bq kg-’ dw).

13

TABLE 2 An r-rank (linear correlation coefficient, r) matrix based on data from 14 Swedish lakes on cesium in pike 1988 (&-pi88 in Bq k g ' ww) versus (1) different cesium variables (Cs-pe87 is Cs in perch fry in 1987 in Bq kg' ww, Cs-soil in fallout in Bq m-', Cs-wat87 is cesium in lake water in 1987 in Bq l-l, Cs-sed86 is cesium in surface sediments in 1986 in Bq kg' dw, Cs-bo86 is Cs in near-bottom sediment traps in 1986 in Bq kg' dw), (2) different lake variables (mean values for 19871, (3)lake morphologic parameters (Dm = mean depth, Q = theoretical water discharge, Vol = lake volume, BA = areas of fine sediment accumulation, DR = dynamic ratio), and (4) different watershed parameters. The table also gives a small r-rank matrix illustrating correlations among the water chemical cluster variables linked to Kconcentration. The column called CV gives mean coefficients of variations for the given variables. r-rank (n=14)

Cs-pl88

cv

Other fish

Cs-pi88 Cs-pi87 Cs-pe87 Cs-pe86

1.00 0.91 0.80 0.91

0.22 0.33 0.28 0.59

Fallout

Cs-soil

0.70

0.10

Lake load

Cs-wat87 Cs-sed86 CS-bO87 Cs-sed89 Cs-bo86 Colour Fe cond K alk CaMg Ca PH totP

0.88 0.85 0.76 0.71 0.66 -0.20 -0.20 -0.31 -0.31 -0.37 -0.37 -0.38

0.26 0.62

Water variables

Morphometry

Watershed

0.62

-0.48

0.19 0.28 0.09 0.12 0.39 0.14 0.12 0.02 0.38

Vol T Area BA DR

0.53 0.38 0.27 0.23 0.05 -0.47 -0.64

0.01 0.10 0.01 0.10 0.01 0.05 0.02

Rock% ADA Basic rock% RDA Mire% Fine sed% Forest% Lake% Coarse sed% Open land% Till%

0.40 0.37 0.25 0.12 0.09 0.05 -0.02 -0.04 -0.08 -0.11 -0.18

0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01

Dm

Q

-0.42

Cluster variables K 1.00 cond 0.94 CaMg 0.92 alk 0.90 PH 0.57

14

(4) Different lake variables (mean annual values for 1987)for colour (mg Pt

1-I), Fe (pg l-l), conductivity (cond in mS m-9, K-concentration (in meq 1-I), alkalinity (alk in meq l-l),hardness (CaMg in meq 1-9, Ca-concentration (meq 1-I), pH and total-P-concentration (totP in 1.181-l). (5) Various lake morphological parameters, Dm = mean depth in m, Q = theoretical water discharge in m3s-1, lake volume (Vol) in m3,theoretical water retention time, Tin years, lake area in m*,percentage of the lake bed dominated by accumulation processes and fine sediments, BA in % of lake area, and dynamic ratio, DR (= S l D m ) . (6) Different parameters describing the catchment area, Rock% is the percentage of bare rocks in the watershed, ADA = the area of the drainage area in m2,Bas%= the percentage of basic rocks, RDA = the relief of the catchment area, etc. It is evident that all the Cs-variables are related to one another and to the fallout (Cs-soil) after the Chernobyl accident, and all the water variables could, potentially, influence the bio-availability and bio-uptake of radiocesium as well as the biomasses, and hence the concentration in the biomasses of radiocesium. The morphological parameters could, potentially, influence the retention of radiocesium in lakes, the resuspension and the internal loading of Cs, and the watershed parameters could, potentially, all influence the runoff of cesium from land to water, i.e., the secondary load of radiocesium to the lakes. But all these factors cannot be of equal importance to predict Cs-pi88. One simple way to quantitatively rank such dependencies is to make a correlation analysis (Table 2). We can note that the some of the potential factors appear with high r-values vs Cs-pi88, like Cs-wat87 (r = OM), totalP ( r = 0.481, dynamic ratio (r = -0.64) and Rock% ( r = 0.401, and some with low r-values. We should also remember that many, if not all, of the variables are related to one another. This is stressed by the small r-rank matrix for the water chemical variables related to the K-concentration. From this small table, we can note that very high and expected correlations exist between K, conductivity, hardness and alkalinity (r > 0.9). Such inter-related variables can replace one another in predictive models without causing any major loss in predictive power. Note also that there exist great differences in the representativeness and reliability of these potential model variables. All water chemical variables vary with time and sampling location in a lake. The CV-values given in Table 2 have been determined from frequent within lake samplings during one year. From such analyses one can determine a lake-specific mean value ( M V ) ,the spread around the mean (the standard deviation, SD) and the relative standard deviation (or coefficient of variation, CV = SD/MV). The data in this table are from HtSkanson et al. [161 and Andersson et al. [17]. We can note the small uncertainty (CV = 0.01) for the map parameters, CV is higher or about 10%(or 0.1) for variables like Q and Cs-soil, and much higher for many variables, like 0.38 for tota1-P (a very variable variable). We can also note that the variability decreases with time for cesium in small perch (from 0.69 in 1986, to 0.28 in

15

1987). These uncertainties are very important indeed in predictive modelling. The next example illustrates a simple regression model with real data for a given y-variable, the concentration of radiocesium in pike in 1988 (2 years after the Chernobyl fallout), Cs-pi88 in Bqkg ww. Many lake variables (like K-concentration, pH, total-P and colour) could, as stressed in Table 2, influence the bio-uptake of radiocesium and the Cs-concentration in pike. The result of a stepwise multiple regression is illustrated in the table in Fig. 6. Note that the concentration of Cs-137 in water in 1987 is the most important x-variable. It explains statistically about 78%(r2= 0.778) of the variability in the y-variable (Cs-pi88) among these 14 Swedish lakes. The F-value is 4. The next factor is the potassium concentration of the lake water (the mean annual K-value for 1987 is used). At the second step, the r2-value has increased to 0.885. The third x-variable is the Open land percent (OL%,a measure of the cultivated land) of the catchment. Accounting for OL% increases F' to 0.917. The fourth and last x-variable (for F = 1) is lake total-P (mean value for 1987).It increases 3 to 0.929. y=Cs-piW; n=l4 Step F-value Variable r A2-value Model

1 2 3 4

Cs-wa187 0.778 K 0.885

4 4 2 1

a%

Step rAi-value

1

2 3 4

0.917 0.929

toll'

0.778 0,885 0.917 0,929

Variable Value

Cs-wale7 K asb tolP

y=9479'xl+769 y=9559'~1-170.6'~2+2524 ~=9685'x1-249.5'~2+172'~3+2804 ~=9259'~1-226.4'X2+191.6'X3-224.6'~4+4939

0.01

Modelled value Cs-pi88. Bqlkg ww 5509 5598 6528

0.38

6368

CV for variable

0.5 Bq/l

0.26

10 peqll 6% 1 1 Fgll

0.12

Uncercainty i n y CV from MC-sim. 0.219 0,223 0,190 0,239

PP

36 40 48 39

Cs-pi@& maximum PP for n-3

0

5

10

Model size (n)

15

20

25

Fig. 6. Predictive power for empirical models derived by stepwisemultiple regressionanalysis using cesium in pike in 1988 (Cs-pi88in Bq kg-' ww) as y-variable, and cesium in lake water in 1987 (Cs-wat871,lake K-concentration, Open land%of the watershed, and lake total-P as r-variables.The graph illustrates the relationshipbetween PP and model size (n)for the data given in the table. The other curve illustrates another situation. The main point here is to highlight the fact that different models will yield different curves.

16

Lake total-P is, as already pointed out, a very variable variable. Its coefficient of variation (CV) is, on average, 38%, or 0.38.The corresponding CV for K is only about 0.12;for cesium in water it is about 0.26 [171.The uncertainty associated with the determination of the Open land% is much smaller -in the order of 1%(CV = 0.01;[MI). With this information, we can use Monte Carlo simulations to estimate the uncertainty (CV) in our y-variable. The results are given in the table in Fig. 6. We can note that CV is 0.219at step 1,0.223at step 2, 0.190at step 3 and 0.239at step 4.PP attains a maximum value for n = 3. So, by accounting for total-P in this stepwise regression analysis, we increase r2, but decrease PP. The reason for this is that we add an uncertain variable which contributes more to the model uncertainty (CV) than to the r2-value.The net result is a model with a lower PP. We should also note that empirical regression analysis automatically yields a slope close to 1. The PP-value of these empirical models are very high, PP > 35 for all four models. From the graph in Fig. 6, we can see that the maximum PP is not obtained for the largest model size. For other models, the highest PP may very well be obtained for other model sizes. This is illustrated by the other curve in the graph. It should be remembered that empirical models can only be used within given ranges of applicability. These models only apply to small, forest lakes of glacial origin. 4. PREDICTIVE POWER OF DYNAMIC MODELS

Dynamic models derive from a causal analysis of ecological and biological fluxes, and are based on calculations using differential equations. Dynamic models are mostly used to study complex interactions and time-dependent variations within defined ecosystems. If dynamic models are to be used in practice, e.g., to quantify fluxes, amounts and concentrations of energy, carbon or contaminants in lakes, the rates that govern the transport among the various compartments in the lake ecosystem have to be known, simulated or guessed. In dynamic modelling, dimensional analysis (of each parameter) is very important. Dynamic models are often difficult to calibrate and validate, and they tend to grow indefinitely. If dynamic models are not validated, they may yield absolutely worthless predictions. As is the case for any model, the presuppositions (“trafficrules”) of the model must always be clearly stated. Figure 7A illustrates a typical compartmental model, giving the biotic compartments of a lake ecosystem (top predator, two types of small fish, zooplankton, phytoplankton, algae and benthos), the abiotic compartments (active sediments, passive sediments and water), and the processes and mechanisms regulating fluxes among these compartments for our type substance, radiocesium. The figure also gives the fluxes to the lake (direct lake load and river input related to catchment load) and from the lake (outflow and sedimentation to the passive sediment layer). This general model can apply to any substance, not just radiocesium.

17 Catchment load River Input

pshing

t

Direct lake load

outflow

Fig. 7. (A) Compartmental model illustrating the fluxes (arrows; mass per unit time) in a traditional dynamic model for the type substance radiocesium in a lake ecosystem with compartments (mass units) for top predator, two types of small fish, zooplankton,phytoplankton, algae, benthos, water and sediments. (B) Illustration of a “mixed model, i.e., a model based on mass-balance and an empirical dimensionless moderator expressing the impad of environmental factors on the uptake of radiocesium from water to small fish. From Ref. [4].

Figure 7B gives a simplified model where the fluxes to the top predator, the y-parameter to be predicted, can be estimated from a few compartments (small fish and lake water) and empirical knowledge of the factors regulating the Cs-uptake by small fish. The uptake by small fish can be described as a k c t i o n of lake pH, theoretical water retention (T> and the dynamic ratio of the lake (DR), Hikanson [61 and HAkanson and Peters [41 discuss many basic problems with traditional mass-balance models like Fig. 7A and methods to derive predictive mixed models of the type in Fig. 7B. To use the model in Fig. 7A,one would need reliable, quantitative data on many rates describing the fluxes (in mass per unit time) among the compartments and the characteristics of each compartment. Appendix 1 gives a list of all the rates and variables linked to the three dynamic models which will be discussed in this paper. Moreover, “rates” are not constants, they vary in time and space. The rates are variables, like most of the variables describing the system and its compartments (e.g., weight and age of the animals).

18

Mixed model cs c o n c c n ~ o nin A

I

Water retention time T

/.-)

Li K moderator

0

Bioconccnuauon faclol

Resuspension facior

G

Retention rate for fish

f") L.,

Rcrenlion in lake water

0

Retation r a ~ for e Prey

(3

Lakearea

(3 Ef

('-) \ 9

Fallout of Cs

L4

'-a>

~cmcm~i~ion

0 :%on

time T

nl=6

n2=5

Fig. 8. Illustration of the small mixed model to predict concentrations of radiocesium in fish. The panel of driving variables gives the model variables, which preferably should not be altered for different lakes to minimizethe componentof "tuningand art", and the lake-specific or environmental variables, which must be altered for different lakes.

19 The V A M P model

Mode! varlsbles

Panel of drivine variables

Fnvironmat.l vwiabler

Fig. 9. “he first version of the VAMP model for radiocesium inlakes. Sub-modelsfor biomass and the seasonal moderator for Q and T,and the panel of driving variable are also shown. This panel is divided into two parts: “model variables” and “environmental variables”. “he environmental variables (or lake-specific variables) change for every lake, but ideally the model variables do not change, unless there are excellent reasons to do 60. This conservative rigour about ad hoc adjustments maximizes the science in building predictive models.

20

In this section, we discuss the relationship between predictive power (PP) and model size (n),i.e., the optimal size problem, for dynamic predictive models. We will test three models for cesium in lakes, and compare these results with the results in Fig. 6. (1)A small, mixed model (of the type illustrated in Fig. 7B;for a further presentation of this approach, see Ref. [6l).It has only three compartments: Water, prey and predatory fish, 6 model variables and 5 lake-speciiic variables (Fig. 8).The total number of driving variables (z)is thus 11.Note that there is no catchment area, no sediments, no food-web and no partition coefficient (Kd) in this model. (2) The VAMP model (Fig. 9).It has 10 compartments, 21 model variables and 13 lake-specific variables. The model size is given by n = 34. (3)The generic model. It is a traditional model (like that illustrated in Fig. 7A)with 9 compartments, 27 model variables and 9 lake-specific variables, which gives n = 36. These models will be tested using the data for the VAMP lakes (see Fig, 10 and Table 3). Since the six VAMP lakes vary in size (fmm 0.042to 1147 km2), mean depth (from 1.7to 89.5m), precipitation (from 600 to 1840 mm year-’), pH (from 5.1 to 8.5),K-concentration (from 0.4to 40 mg 1-’1, primary productivity (from 0.8to 350 g C m-2 year-’) and in food-web characteristics, it is a great challenge to try to model the effects of the Chernobyl “spike” on the cesium concentrations in water and biota.

r

Fig. 10.The location of the VAMP lakes.

Bracciano 0vre Helmdalsvatn IJsselmeer Hillesjon Devoke Water Esthwaite Water

Is0 Valkjarvi

0.4 40 0.4 7 3 0.55 0.9

350

25 0.8 27 350 100

Prim. prod. Susp. load ( g c/m' year) (mgfl)

(mg/l)

K

0.5 0.5 0.3 40 5 0.1 1

0.042 57 0.78 1147 1.6 0.34 1

61 42 61 52 61 54 54

126 164 1090 0 10 233 66

Is0 Valkjarvi, Finland Bracciano, Italy 0vre Helmdalsvatn, Norway IJsselmeer, Holland Hillesjon, Sweden Devoke Water, UK Esthwaite Water, UK

Lake area (km')

Altitude (ma.s.1.)

Lake

Lat. "N

300 700

60 500

70

Sed. rate (g/m2 year)

3.1 89.5 4.7 4.3 1.7 4.0 6.4

Mean depth (m)

70 0.9 130 2.2 100 17 2

Ca-dep. (kBq/m2)

0.168 91.2 23.4 114700 19.2 3.06 14.0

(km2)

Catchment

3 137 0.17 0.41 0.36 0.24 0.19

(years)

T

Whitefish and perch Whitefish Minnow and trout Smelt, mch and perch Roach and perch Perch and trout

Prey fish

600 900 800 750 650 1840 1800

(dyear)

Prec.

11650 14 5250 21 4750 1750

5.1 8.5 6.8 8.5 7.3 6.5 8.0

PH

Data for the seven "VAMP lakes". All lakes are oligo-humic except Is0 Valkjarvi and Hillesjon which are meso-humic. IJsselmeer, Hillesjon and Esthwaite water are eutrophic and the remainder are oligotrophic

TABLE 3

22

5. UNCERTAINTY IN EMPIRICAL DATA Before comparing empirical data to modelled values, it seems appropriate to discuss the uncertainty in the empirical data. There exist several approaches to this problem, and the aim here it to illustrate that results and interpretations could, in fact, depend very much on the method selected. We will illustrate this by using three different methods. Table 4 illustrates available data for one on the VAMP lakes, Devoke water. Month 1is January 1986. There exist data (available to the author) from month 8 till month 64 for cesium-137 in lake water, small perch (perch <20 g, SP), large perch (>20 g, LP) and trout. Since it is very interesting to predict “the peak and the tail”, i.e., the maximum values and the recovery process, we will look at the uncertainties of the empirical data for: (1)Uncertainties related to individual analysis of water samples and fish from the same sampling occasion. This method is, probably, the most common and straightforward one to address uncertainty in empirical values. (2) The maximum values (the “peak”), i.e., the correspondence between empirical maximum values and modelled values for the same month. (3) The temporal data (the “tail”),i.e., the correspondencebetween empirical data and modelled values for a given period. This is illustrated in Table 4. The empirical uncertainties are given by the SD-values and mean values, in italics, like SD = 398 for MV = 1167 for large perch for month 10. The emboldened rectangles give the empirical maximum values, like 0.24 Bq 1-’ for month 8 for Cs in water. The modelled value for month 8 will be compared with this value. The same principles apply to the value 2092 Bq kg-’ ww for lake perch for month 14 and 1383 Bq kg-’ ww for trout for month 14. This comparison will be called method 2, max. values. The set-up for the “tail”test, method 3, is also given in Table 4. The column of empirical data for trout, starting with 779 Bq kg-’ ww for month 9 and ending with 120 Bq kg-’ ww for month 64 will be compared to modelled values. We can test the uncertainty of this series of data if we copy the column and paste it in so that data for April are compared to data from March, etc. By doing so we obtain two empirical sets of data, Empl and Emp2. They should be similar. Note, however, (1)that all data from the first half year after the Chernobyl accident (ie., data up to September 1986)have been excluded in this test since the conditions then were most variable, and significant changes took place, especially in lake water and plankton-eating fish from one month t o the next, and (2) that to get enough data for this comparison we have for 1986 and 1987 only accepted data from adjacent months, but for 1988 we have accepted data two months apart (but not more), like 235 Bq kg-’ ww for month 34 and 380 Bq kg-’ ww for month 36, and for 1989 and the following years, we have accepted data three months apart (but not more), like 325 Bq kg-’ ww for month 38 and 344 Bq kg-’ ww for month 41. This gives data for a very interesting

23 TABLE 4 Compilation of empirical data for radiocesium in water, small perch, large perch and trout in Devoke water Monlh 1rJan-86

n

Walw Bq11 MV

Parch -20 Bqlkg ww n UV

Parch 20Bqlkg ww n MV

SO

2'CV lor 1'124

n

I==

8 9 10 11 12 13 14

15 16 17

1

4

5 12

1312

0.15

I573 1122 1466 I457 1610 I637 1663

0.08

7

0.08

7

0.06 1 2

9

64 1 443

517

0.25 0.66

17 1 12

84 63 21 67 67 120 37 65 47 42

239 473 371 761 560

1279

50

2'CV 101 n24

449

1.15

351

0,68

555 356 526 230 120 435 31 8 221 375 209

0.80 0.85 1.66 2.13 0.35 1.28 0.53 1.18 1.15 0.89

175

0.83

141

0.75

0.06

1476 3

6

359

)0911258

0.10

18

19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35

1502 1167 398

1375

MV

0.05

14

9 12 8 3

f34 42 34

1361 797 540 981 549 860

11

43 23 38

6

0.04

36

6

0.04

8

380

32

37 38 39

6

0.03

9

325

34

6 6

0.02

3 3

344 179

17 27

41

19

9

278 239 195

1

120

40

41 42 43 44

47 53 56 64

4

356

4

832

0.04

6

0.03

1

0 02

6

0.03

I330 1334 6

91

672

Mv:

0.59

'

1.02

comparison since this is the manner in which modelled values are often compared to empirical data. We cannot expect that the models should yield better correlations with the empirical data than obtained from this comparison between Empl and Emp2. Figure 11 gives the results related to method 1, uncertainty in empirical data. Figure 11A first gives the direct results for trout in Devoke water. This is a graphical display of the information given in Table 4, except that we have used 2 S D and not 1SD. The reason for this is simply that f2.SD corresponds

24

L

lkJokc~tzr.~tmut M

MV*2*SD

5 2000 If 9 1500 e

500

0 ~ ".o Q.......o .... o "............... o o"0................................................................ ~ 0 ................

e

-500

B.

x x

3000.

Y

c

3

X X

X

Ii

.

.

L

2500: c2000

REi 6

ya0.008x + 0.47: r2-0,015:p=O.29. MV=0,55;S D=0,35

X

21,75. AUflehdata 1.5. X > 1.25. ! ! 1. f3

M

.

p

[I&

500..-..o...""............ 0."

Depokewater,brrrwrtrout

MV+,2*SD

mq.jbPr!

..._.-........................".* ..... "*....................................................................... $9 H B

"

........ 0 --*..-...

"

25 to k95% confidence limits. From this figure, we can note that the mean values vary very much. The peak value, 1383 Bq kg-' ww, is attained during month 14, and after this there is an unsteady general decrease with time. The spread around the mean value is very large initially, but it is reduced with time. This is the result for one species of fish in one lake. Figure 11B gives the results for all fish data for all VAMP lakes. In this figure, the relative standard deviations (2CV) are compared to the number of fish analysed (N). The assumption was that there might exist a negative correlation such that greater uncertainties might be at hand if N was small. That does not seem to be the case. The most important factor for the uncertainty is the time after the fallout - the uncertainty decreases with time. The mean CV is 0.55 with a large standard deviation (0.35). If we apply this mean, standardized empirical uncertainty to the data on trout for Devoke water, we get the graph in Fig. 11C. This figure can be compared with Fig. 11A. We can note that Fig. 11C is quite similar to Fig. 11A in this case. This approach gives a crude, standardized method to describe the uncertainty of all these empirical fish data, also in cases when only bulk samples of many fishes have been determined, and not individual fish samples, which enable determinations of SD, MV and CV. Next, we will compare these empirical uncertainties to modelled uncertainties. Figure 12A gives a comparison between peak values for the VAMP model and empirical peak values (for the same month; according to method 2) for cesium in water (for the 7 VAMP lakes) and in fish (Fig. 12B, for the 18 available data-pairs). The figure also gives the regression lines and the statistics. We can note that the VAMP model generally predicts the maximum values better in fish than in water (r2= 0.95 and 0.86, respectively, and the slope is 0.921 and 0.805,respectively). The figure also gives the 95%confidence interval for the predicted y . The confidence intervals are not exactly parallel to the regression line, but almost. We can determine one approximate figure for each water and fish, defining the 95% confidence intervals as 2 S D [from the mean value log(VAMP-mod)= 0 and 2.5, respectively)], i.e., 0.81 for the VAMP model for water and 0.60 for fish. We can then compare this expression for model uncertainty (2SD from Fig. 12) with the empirical uncertainty (2CV) from Fig. 11). This is a simple method to validate this model (it could, of course, also be used for any model) and to express the uncertainty of the predicted maximum values. One result for trout in Devoke water is given in Fig. 13. Here, we can see (Fig. 13A) that the standardized empirical uncertainty (2CV = 0.55) gives rather narrow uncertainty limits around the empirical mean values. In Fig. 13B, we can make a direct comparison to the model uncertainty, as expressed We can note that, with this approach, we by the limits given by 2SD (= get what one would anticipate: The model predictions provide wider uncertainty limits than the empirical data. Figure 14 gives a more comprehensive comparison between predicted peak values and empirical peak values (according to method 2). The plots include

26 2.0

log(cmp)-0.805*log(mod)-O.O94: r2-0.86; n-7: p-0.0026 I

5

Fig. 12. Comparison between maximum empirical data and correspondingvalues predicted by the VAMP model for (A) Cs in lake water and (B)Cs in all types of fish. Statistics and 96% confidence limits for the predicted y. The values for 2.SD (0.81 for water and 0.60 for fish) describe the smallest distance (in y-direction) between the regression line and the 95% confidence interval as a simple measure of model uncertainty determined by these validations.

27

Fig. 13. Comparison between uncertainties in (A) empirical data (from the results given in Fig. 11B),and (B)uncertaintiesrelated to the prediction by the VAMP model (from the results presented in Fig. 12B).

comparisons of both water and fish on the same graph. Figure 14A shows that the VAMP model can, in fact, predict maximum values of cesium in water and fish very accurately. The /'-value is 0.97 for the 25 data-pairs (for logarithmic values). The mixed model (Fig. 14B)also gives similar fine predictions; the r2-valueis 0.97 also for this model. This is somewhat surprising since the mixed model is very small. It does not account for many processes perceived to be important. The largest generic model (Fig. 14C)gives the lowest ?-value (0.91), but this is mainly due to one outlier, namely large perch in Devoke water. If this point is omitted, the r2-valueis 0.97. Figure 14D gives the results when the two empirical data-sets are compared in the same way. We can note an expected very high r2-value (0.987). It is also interesting to look at how the different models predict in individual lakes and for different species of fish, and especially to study how various processes and model components affect the predictions. It is, however, far beyond the objective of this paper to address such issues in detail. We will just give a few examples. The first example is given in Fig. 15. It concerns the Finnish lake, Is0 Valkjarvi. Figure 15A shows that there exists a good correspondence between the two data series, Empl and Emp2 for Cs in water in this

28 5

-8

3-

2

0-

w, M

4-

2-

1-1

-

-2

-2

-

4-

I

I

-1

0

B-

'

I

I

I

I

1 2 log(Vamp-mod)

4

3

Mixed

3-

;2-

s

M

2

1-

0-

-1-2

.I

I

I

I

I

I

Dev, LP (outlier excluded gives r2-0.97

.-

-2

-2

I

I

-1

0

I

I

I

2 log (Qen-mod)

1

I

4

3

5

-3 -3

l

-2

'

~

-1

'

l

'

l

0 1 2 log(emp -2)

'

l

3

'

l

~

l

.

4

Fig. 14.A compilation of validation tests (empiricaldata venue modelled values) for (A) the VAMP model, (B)the Mixed model,(C)the Generic model, and (D) the test of the two empirical data-sets called Empl and Emp2. Note that this figure gives logarithmic data.

29

--.-

23

- A.

Lake I s 0 V a l k j a r v i

tlixed model

U

m

r2-0.95 1

r2=0.874; slope=O. 1 2 4

Y

w i t h retention rate moderator& internal loading w i t h o u t seconday loading & seasonal v a r i a b i l i t y m o d e r a t o r

Modelled values Empirical data 0

u

31

Months

-.

15

0. V A t l P model r*=0.889: slope=0.370

h

CT

m

Y

L

c

P

.E c

w i t h r e t e n t i o n r a t e moderator, internal loading secondary loading a seasonal v a r i a b i l i t y moderator

75

.-

d

0 L

d

c U Iu

c

u -1-2

I

0

61

'

91

Months

-

l

1 2-2

c. Generic model r2-0.777; slope=0.0 14

-

h

\ D

m al L

c

P

E c

w i t h internal loading secondary loedlng

? 5 -

a

w i t h o u t retention r a t e m o d e r a t o r & seasonal v a r i a b i l i t y moderator

0 c c 0

+ c U W

0

u

31

,U4k2-l-

2

61

91 0

2

1

1

2

1

Months

Fig. 15. Validation results for cesium in water in Lake Is0 Valkjiirvi. (A) the Mixed model, (B) the VAMP model, and (C)the Generic model. The figure also gives a list of processes influencing the recovery accounted for (and not accounted for) in the three models, and the results from the comparison between the two empirical data-sets, Empl and Emp2.

30

lake, r2= 0.951. The slope is 0.692, which is expected - the values should be lower for Emp2 since these data are from a month aRer the data given by Empl. We can note that the small mixed model gives rather poor predictions in this case; 4 is 0.874, which is not so bad, but the slope is very low, just 0.124. This is also clear from the graph (Fig. 15A),which shows that the mixed model provides very poor predictions for the “tail” values: The empirical data are much higher than the modelled values. This model accounts for the water retention rate moderator (see Ref. [41 and a following section), and internal loading, but it does not account for secondary loading (from the catchment) or for seasonal variability in water discharge. The VAMP model gives the best predictions in this example. The r2-valueis highest 0.889 and the slope is closest to 1(0.370).This model accounts for all the given four processes affecting the recovery process, i.e., the “tail” values, and we can note a much better correspondence between modelled values and empirical data. But also in this case, we can note that the slope is far from the ideal value of 1.0.The generic model gives very poor predictions indeed. The slope is 0.014. It should be stressed that this example on Cs in water in Is0 Valkjkvi has been selected to illustrate the importance of the factors included in the definition of predictive power, the r2-value,the slope and the coefficient of variation. The idea has not been to evaluate the given models, but to discuss predictive power in a general way. The next example concerns predictions of Cs in whitefish in the Italian lake Bracciano and Is0 Valkjiirvi. Figures 16A, B and C gives the results for the three models for Bracciano in the same way as Fig. 15 gave the results for water in Is0 Valkjmi. We can first note that the correspondence between the two empirical data-set is rather poor in this case, 2 = 0.808 and the slope is 1.208, indicating that, on average, the values from the latest month (Emp2) are higher than the values from Empl. This indicates that something is “strange” in lake Bracciano: This lake has, in fact, high concentrations of old cesium [191. These models assume that all cesium emanates from the Chernobyl fallout, and there is no factor accounting for old cesium from the weapon tests during the 1950s and 60s. Figures 16A, B and C illustrate that all three models provide a low predictive power in Bracciano. The best model is the VAMP model which gives an 3 of 0.409, but the slope is very far from 1;it is 0.079. The generic model gives an 9 of 0. All this illustrates, in fact, not the weakness of these models, but the strength of modelling. All models provide very good to adequate predictions in most lakes for water and most species of fish (which we will see later on), and when this is NOT the case then the difference between the model prediction and the empirical value could be discussed in quantitative terms. The model would provide a hypothesis, which is tested against independent empirical data. In the case of Bracciano, it is evident that models which do not account for old fallout should provide poor predictions. If these models were t o give good predictions, it would be for the wrong reason!

31 A. Lake Bracciano

D. Lake Is0 Valkjarvi

. -

lSoo07

m

Empirical

m

-

Y

r2-0.027 slope=O. 15 1

5

e a?

z

7.5

s I ope=O.956

-c -

c

-c

C

0

e

e

0

a L e

L

e C

C W

u

0

s

o

U

$

slope=0.348

Y

m 0

Modelled values

L

5

r2 =0.309 H l X B d model

31

I

R _.

”1

.

61

u 0

Months

,

VAHPmodel

Ul Y

VAHP model

U

m

Y

-In S

=

slope=0.079

+ al L

3

slope:0.758

75

-c

-

0 C

0 C

.-

c L a

e L 10

e W C

ac2

C 0

6

U

0

u

61

I

31

tlonths

C.

Months

Generic model r2-0.777 s l o pe = 1.943

f

2

0

U

/

slope=-0.375

,

0 I

Months

31

r\n”

”

, 61

nl\

I

31

61

Months

Fig. 16. Validations for cesium in whitefish in Lake Bracciano and Lake Is0 Valkjiirvi for the Mixed model, the VAMP model, and the Generic model. The figure also gives the results from the comparison between the two empirical data-sets, Empl and Emp2.

Figures 16D, E and F for lake Is0 Valkjarvi give another interesting story: the r2-value and the slope for the two empirical data-sets are: 0.309 and 0.348, respectively. This indicates great uncertainties in the empirical data for whitefish in this lake. And all three models actually give much higher r2-values and much better slopes than obtained from the comparison between Empl and Emp2: the mixed model gives ?= 0.874 and slope = 0.956, and from Fig. 18A we

32 TABLE 5 Empirical r2-values obtained in comparisons between empirical and modelled y for the VAMP model, the Mixed model, the Generic model and for the test series between the two empirical samples (Empl vs Emp2) for different lakes, Cs-concentrations in water and in different species of fish ~~

~

Lake

VAMP r2

Mixed r2

Generic

1.2

Empl vs Emp2 r2

Water Water Water Water Water Water

IJsselmeer Is0 Valkjarvi Devoke water Esthwaite water Hillesjon Bracciano

0.89 0.84 0.79 0.66 0.52 0.31

0.81 0.80 0.81 0.61 0.39 0.44

0.76 0.04 0.95 0.74 0.64 0.92

0.88 0.95 0.11 0.40 0.02 0.99

Whitefish Whitefish

Is0 Valkjiirvi Bracciano

0.89 0.41

0.87 0.03

0.78 0.00

0.31 0.81

Trout Trout

Heimdalsvatn Devoke water

0.86 0.39

0.90 0.58

0.83 0.50

0.86 0.27

Smelt

IJsselmeer

0.81

0.73

0.81

0.92

Small perch Small perch Small perch Small perch

Hillesjon Is0 Valkjarvi IJsselmeer Devoke water

0.88 0.84 0.77 0.01

0.86 0.85 0.85 0.08

0.87 0.65 0.74 0.03

0.95 0.72 0.85 0.02

Roach Roach

IJsselmeer Hillesjon

0.79 0.64

0.72 0.89

0.79 0.62

0.65

Pike Pike

Hillesjon Is0 Valkjarvi

0.94 0.69

0.88 0.60

0.94 0.00

0.85 0.44

Large perch Large perch Large perch Large perch

Is0 Valkjarvi Hillesjon IJsselmeer Devoke water

0.98 0.55 0.30 0.08

0.94 0.68 0.57 0.06

0.18 0.61 0.32 0.11

0.87 0.00

can note the very good correspondence between modelled values and empirical data both for the peak and the tail. The VAMP model also gives good predictions, although the modelled peak is too high. The generic model gives values that are about 2 times higher (slope = 1.943)than the empirical data. These are some selected results to highlight how the different models behave. Table 5 gives a compilation of many model runs for the three models,

33

for the seven VAMP lakes and for Cs-concentrations in water, whitefish, trout, small perch, large perch, roach, and pike. The table gives the ?-values when empirical data are compared to modelled values for the corresponding periods (months). The results are summarized in Fig. 17. We can note from this figure that the mean ?-value from all these validation tests (n = 23) is, in fact, highest for the simplest model, the mixed model, and lowest for the largest model, the generic one, We can also note that the mean ?-value between the two empirical data-sets, Empl vs Emp2, is about 0.6. This indicates the uncertainty in the empirical data and gives an analogous comparison to the comparison between modelled values and empirical data. Figure 18 summarizes the corresponding results for the slope. Figure 18A gives the mean values and the standard deviations, and Fig. 18B the median values, the quartiles, the 90%values and the outliers. We can note that also in this case the comparison between the two empirical data sets gives the largest divergence from 1. The median and the mean value is about 0.6. It is, of course, also logical that this slope should be somewhat smaller than 1. The results concerning predictive power of the dynamic models are summarized in Fig. 19. The table in this figure gives the mean r2,the CV related to the given r2-values, the mean slope and the predictive power (PP) for the three models and the corresponding data for the comparison between the two empirical samples (Empl vs Emp2). We can note that the smallest model, the mixed model, yields the highest PP, the biggest model, the generic model, the lowest PP. So, also in this case, one obtains best predictive power for small models accounting for the most important processes, no more, no less. Large models with many uncertain rates and model variables give lower PP. We can also note that the lowest PP-value is obtained when comparing the two empirical samples. This indicates the empirical uncertainties associated with the VAMP data. We should also note that the PP-values obtained by these dynamic models are much lower than the PP-values from the empirical models in Fig. 16. That is an important indication and a lesson: Within the range of applicability,

1-

9

'

+SD

-

.8.

.7. 47 .6..5-

N L

-

.

.-

__

I

+MV

,4.-3.-.2.--. .1 -. 0

._-

Fig. 17. Compilation of validation results for r2-valuesobtained for water and all species of fish for the three models (VAMP, Mixed and Generic) and results from the comparison between the two empirical data-sets, Empl and Emp2.

34 2 .............

"

".._XI,

Ideal

Slope-VAMP Slope-Mix

Slope-Cen

Slope-Emp

.................................

Fig. 18. Compilation of validation results for slopes obtained for water and all species of fish (n = 18) for the three models (VAMP,Mixed and Generic) and results from the comparison between the two empirical data-sets, Empl and Emp2. (A) gives the mean slopes and the standard deviations (B)gives the median (= 50%), quartiles, percentiles and outliers.

empirical models often provide better predictive power than dynamic models in ecosystem contexts. The VAMP report presents three dimensionless moderators that have proven to increase the predictive power of these models. 6.THE K-MODEPATOR

The K-moderator expresses the fact that the bio-uptake of radiocesium by plankton (here mainly phytoplankton) depends on the K-concentration of the lake water: The lower K, the higher the uptake, and vice versa. In the VAMP model, the moderator operates on the phytoplankton bio-uptake rate, which is set to 0.005 (month-'). In the mixed model, it operates on the bio-concentration factor. The default value for the bio-concentration factor is 150 for lakes with very low K-concentration (el mg 1-'1. For lakes with high K-concentration the actual bio-concentration factor is given by the ratio 150/K-moderator.

35 Model Lake-pedfic rdmblsa vuhblss nl n2 Mlxed model VAMP model

Generic model

[Empl versus Emp2

6 21 27

5 13

9

ne nl+n2

R”2

CV

Slope, b W

1.1-a

PP

11 34 36

0.65 0.65 0.56

0,427

1.12 0.85 1.15

0.21 0.25 0.23

7.42

0.428 0.602

0.59

0.603

0.59

0.51

1.93

6.12 3.99

1

lo’ 6 9.

.% 8.

c

7. SEASONAL VARIABILITY MODERATORS FOR WATER DISCHARGE AND THEORETICAL WATER RETENTION TIME

Many ecological variables vary greatly with the season of the year (e.g., related to temperature, precipitation and runoff).It is often at least as hard to predict such seasonal variation as it is to forecast the weather. The VAMP report describes the construction of a “seasonal variability moderator”, which is a simple sub-model meant to increase the predictive power of larger ecosystem models by accounting for seasonal variability. This moderator accounts for variation in the discharge of water from tributary streams (&).The model has also been presented in detail by Ref. [41. Traditional process-oriented hydrological models for Q, or series of empirical data [20-241, would, naturally, be preferable to this moderator technique, which is meant to be used when such alternatives could not be used for practical or economical reasons. This approach assumes that the following five factors are vital: - Latitude (Lath The higher the latitude, the larger the potential seasonal variability (in Q and T; T = VoVQ) if everything else is constant. - Altitude (Alt, in m above sea level). The higher the altitude, the larger the potential seasonal variability (in Q and T ) if everything else is constant.

36

- Precipitation (Prec; usually given in mm year'). The greater the precipitation, the larger the potential seasonal variability (in Q and T )if everything else is constant - Area of drainage area (ADA, in m2).The larger the size of the catchment, the larger the potential seasonal variability in Q and T,if everything else is constant. - Lake volume (Vol in m3).The larger the volume of the lake, the smaller the potential seasonal variability (in T, but not in Q). To construct a seasonal variability moderator for Q and T this approach uses two features: - A seasonal variability norm. This norm is a curve constructed to illustrate extreme seasonal variability in mean monthly water discharge, relative to the annual mean discharge. The curve has several specificfeatures. The annual mean value of the norm should be 1.00 (this is a dimensionless proportionality), but the mean value for each month can vary widely around the annual mean. The range between the lowest (0.001for January) and the highest values (7.0 for April) should be high, and is 7000 for this particular seasonal variability norm. - A smoothing function is used to average out seasonal variability. The seasonal variability norm is defined to yield extreme values for Q and T . However, the extremes can be moderated by taking running mean values of the seasonal variability norm over periods of different length - the longer the period, the smoother the curve. The equation that specifies this calculation is a smoothing or averaging function. The smoothing function is based on the five, easily accessible factors given above. Accessibility is an important criterion in this context. Several techniques exist to smooth n temporal pattern, like the seasonal variability norm for Q and T , e.g., one-sided running means, two-sided running means (this means that the value for a given month, e.g., July, is represented by the average value for May, June, July, August and September), or any other smoothing function, like first-order exponential equations. 8. A SEASONAL VARIABILITY MODERATOR FOR LAKE WATER RETENTION RATE

In the basic mass-balance model, the retention in the lake of any given substance X i s related to T, the theoretical lake water retention time (see Ref. 181). The retention rate would be 1/T or some variant of 1/T, like: (1) l/T(t),where T(t) is a time-dependent function of T; this could be either derived from empirical data or obtained by using the seasonal moderator for

Q;

(2) 0.693/[0.5-T(t)], which is linked to the half-life, where 0.695= -ln(0.5); or (3) l / F m ,where YDm is a dimensional moderator for the mean depth (see [4]1.

37

To describe variation of the retention rate (RR)with time, one might use the seasonal moderator for Q (Ye),instead of the mean average water retention, which is a constant. For example, we could define the retention rate as:

According to this equation, when the seasonal moderator for Q has a low value (as it does during the winter), the theoretical water retention time would be long and the retention rate low, and vice versa. If T is 1year, and the seasonal moderator for Q takes the value 2.0 in April and 0.2 in October, then the retention rate for April is 2/1= 2; all the water would be flushed out of the lake twice in that month. For October, the rate is 0.2/1 = 0.2, so much of the water in the lake at the beginning of the month is still there on November 1. In large, well stratified lakes, the water is not well mixed, and turnover depends on other processes besides tributary flow, Q [25-291. For such lakes, some of the water turns over more quickly than the value suggested by the theoretical water retention rate, 1/T, and other parts turn over much more slowly. This has been demonstrated in many contexts (e.g., Ref. [301). In lake eutrophication modelling, where both the water and phosphorus in the superficial strata turn over faster than those in deeper water, equations using often predict the retention of water or total-P retention in lakes better than do equations using T'. The rationale for the sub-model for retention rates for lakes is further explained in the VAMP report. The idea is to provide a general expression for the exponent, TXp. The exponent (exp) should be about 1 for small, shallow lakes with large catchments, i.e., for lakes with a short theoretical water retention time (T),and the exp-value should be small for lakes with very long theoretical retention times. The following algorithm for retention rate has been calibrated with the empirical data for the VAMP lakes (Table 3): Retentionjn-lake-water = l/~3"'(T+29'+0

(3)

With this approach, T must always be equal to or smaller than 1, so the lake with the shortest T-value is used to establish the appropriate units for T. If T is extremely short as it is in Lake 0vre Heimdalsvatn, Norway where T = 2 months, then the calculation time, dt, should be 1 month, rather than 1 year. If T = 1 unit of time, then the retention rate estimated by Eq. (3) is 1,as it is in previous calculations where retention rate is estimated as 1/T. But if T = 10, the retention rate with this approach is 0.14, instead of 0.1 as it would be with the traditional approach (l/T). For T = 100, retention rate estimated by Eq. (3) is 0.11, not 0.01. Next, we will demonstrate how this sub-model works in a larger ecosystem model.

38 9. USING THESE SUB-MODELS

The sub-models to predict seasonal variability for Q and T,and lake water retention rate may be used in many different contexts. For example, they allow one to reconstruct or to predict the seasonal pattern of lake variables given only the annual or super-annual means. Such annual mean values may in turn be predicted from simple characteristics of the catchment or the lake (e.g., lake total-P, colour, pH, and Secchi depth from map parameters, and many important lake biological variables from mean annual total-P, see Ref. [4]). The VAMP model for radiocesium in lakes is presented in Fig. 9. The VAMP model is based on many of the concepts presented in this paper. It is of utmost importance that the model accounts for seasonal differences, since we cannot expect the next accident to happen at the same time of the year and under the same weather conditions. Figure 20 shows the curves for radiocesium in predatory fish (trout) in Lake 0vre Heimdalsvatn that would have been

$ M

6ooo- A.

/

Fallout month

tr

m Y

0

3000’ Y

a

c

With seasonal moderators

31

5 tr m

z

U

Y

I

61 Months

I

91

1

121

s

-E

Y

3000-

k c

.d

V

I//I/:/,..

1’

Without seasonal moderators 31

61 Months

91

1

121

Fig. 20. Sensitivityanalyses of the effect of the timing ofthe acute fallout on Cs-concentrations in predatory fish (trout) for Lake h e Heimdalsvatn predicted using the VAMP model with (A) and without (B)the seasonal variabilitymoderator for Q and T.Curve 1 gives the results if 130 kBq m-2 occurs as an acute dose in January, curve 3 represents March, etc.

39

observed had the accident happened in another season. The simulation in Fig. 20 is therefore a sensitivity analysis of the VAMP model, with (Fig. 20A)and without (Fig. 20B) the seasonal moderator for Q and T,where the month of the fallout changes while all else remains the same. The question of interest is whether the timing of the event afTects the peak value and the shape of the recovery ”tail”. The model indicates that May, just at the very start of the growing season, was the worst possible month for an accident of this type. Lower peak values would have been obtained had the accident occurred in January (curve l), March (curve 3) or in the fall. In winter, a significant part of the fallout would have quickly escaped the lake in the spring flood. In late summer and fall, the plankton would have accumulated less fallout than they did just &r the spring flood. The predicted peak for predatory fish with the seasonal moderator is 5300 Bq kg-’ ww; without the moderator the result is 2900 Bq kg’ ww. The empirical peak value is 4600. The timing of the peak is little affected by the presence or absence of the moderator for Q and T.However, when the month of the fallout is changed, the model without this seasonal variability moderator transposes the same curve in simple steps depending on the month of the fallout. This does not seem very probable. These predictions concerning different fallout months have not been validated, and one hopes they will never be tested. Nevertheless, they meet the weaker criterion that the predictions of the VAMP model seem plausible. 10.CONCLUSIONS

In this paper, many statements and comments about models in general and predictive models in particular have been given. Some of those statements are compiled below. - If the aim is to quantify, rank, predict and simulate, there are few, if any, alternative approaches to models in complex ecosystems. “Verbal models”, “qualitative explanations”, and “logical reasoning” often deteriorate into ”Environmental theology“, rather than environmental science. - Dynamic models are logical constructs. But logical reasoning depends on one’s personal knowledge and some of that knowledge may be subjective. What is logical for one person may be illogical for another. Logic in ecology is not objective, but subjective - it is in the mind of the beholder. - Big models are often “prescriptive” not predictive. Big models may look more objective than small, but this may be self-deception. Their complexity hides the deception as a deodorant hides a bad smell. - Models are built and validated with empirical data. Empiricism enters at many steps from start to finish in modelling. But empirical data, and any knowledge based on empirical data, are uncertain.Accumulated uncertainties in the models will cause accumulateduncertainties in model predictions.

40

- The predictive power of a model is not governed by the strength of the model's strongest part, but by the weakness of its weakest part. - Big models are simple to build, but hard to validate. Small models are hard to build, and simple to validate. - Small size is necessary, but not sufficient, for utility and predictive power; so useful models must be small. Small models should be based on the most fundamental processes, but that is far easier to say than it is to accomplish. - Scientific knowledge does not lie in the model alone, nor in the empirical data alone, but in their overlap as validated, predictive models. - The key issue is not to verify, but to falsify a model, and thereby to determine its limitations. - It is important to predict mean values, but it is equally important to predict the confidence interval around the mean. 11. REFERENCES 1. Black, V.S., 1957. Excretion and osmoregulation. In: The Physiology of Fishes, Brown, M.E. (ed.). Academic Press, New York, Vol. 1, pp. 163-205. 2. Fleishman, D.G., 1963. Accumulation of artificial radionuclides in freshwater fish. In: Radioecology, Klechkovskii, V.M., Polikarpov, G.G. and Aleksakhin, R.M. (editors).John Wiley, New York, pp. 347-370. 3. Carlsson, S., 1978. A model for the turnover of Cs-137 and potassium in pike (Esox Lucius). Health Phys., 35: 549-554. 4. H&anson, L. and Peters, R.H., 1995. Predictive Limnology - Methods for Predictive Modelling. SPB Academic Publishing, Amsterdam, 464 pp. 5. Nilsson, A., Andersson, T., Hikanson, L. and Andersson, A., 1989. Mercury in lake fish - linkages to mercury and selenium in mor and historical emissions (in Swedish with English summary). SNV Report 3593,117 p. 6. HAkanson, L., 1991. Ecometric and dynamic modelling- exemplified by cesium in lakes after Chernobyl. Springer-Verlag, Berlin, 158 p. 7. Saether, O.A., 1979. Chironomid communities as water quality indicators. Holarctic Ecol., 2: 65-74. 8. Hbkanson, L. and Jansson, M., 1983. Principles of Lake Sedimentology. SpringerVerlag, Berlin, 316 p. 9. Pearson, T.H. and Rosenberg, R., 1976. A comparative study on the effects on the marine environment of wastes from cellulose industries in Scotland and Sweden. Ambio, 5: 77-79. 10. Cox, D.C. and Baybutt, P., 1981. Methods for uncertainty analysis: a comparative survey. Risk Analysis, 1(4), 251-258. 11. Beck, M.B. and Van Straten, G., 1983 (eds). Uncertainty, System Identification and the Prediction of Water Quality. Springer-Verlag, Heidelberg, 387 p. 12. Worley, B.A., 1987. Deterministic Uncertainty Analysis. Oak Ridge National Laboratory Report ORNL-6428, Oak Ridge, USA, 53 p. 13. Tiwari, J.L. and Hobbie, J.E., 1976. Random differential equations as models of ecosystems. Monte Carlo simulation approach. Math. Biosci., 28: 25-44. 14. Rose, K.A., McLean, R.I. and Summers, J.K., 1989. Development and Monte Carlo

41

15. 16.

17. 18. 19. 20.

21.

22. 23. 24. 25. 26.

27. 28. 29. 30.

analysis of an oyster bio-accumulation model applied to bio-monitoring. Ecol. Mod., 45: 111-132. M A , 1989. Evaluating the reliability of predictions made using environmental transfer models. Safety Series No. 100. International Atomic Energy Agency, Vienna. Hiikanson, L., Andersson, P., Andersson, T., Bengtsson, A.,Grahn, P., Johansson, J-A., Kvarnas, H., Lindgren, G. and Nilsson, A., 1990. Measures to reduce mercury in lake fish. Final report from the Liming-mercury-cesium project. Nat. Environ. Prot. Agency, S-17125 Solna, Sweden, SNV PM 3818,189 p. Andersson, T., Hlkanson, L., Kvarnas, H. och Nilsson, A., 1991. Remedial measures against high levels of radioactive cesium in Swedish lake fish (in Swedish). SSI Rapport 91-07,114 p. Nilsson, A., 1992. Statistical modelling of regional variations in lake water chemistry and mercury distribution. Thesis, Umel univ. Monte, L., Fratarcangeli, F., Pompei, F., Quaggia, S. and Battella, C., 1993. Bio-accumulation of Cs-137 in the main species of fishes in lakes of central Italy. Radiochimica Acta, 60: 219-222. Roberts, D.J., Lindell, T. and Kvarnas, H., 1982. Environmental factors governing regional lake water quality differences. SNV Report 1621,32 p. Knoechel, R. and Campbell, C.E., 1988. Physical, chemical, watershed and planktun characteristics of lakes on the Avalon Peninsula, Newfoundland, Canada: a multivariate analysis of interrelationships. Verh. Int. Verein. Limnol., 23: 282296. Rochelle, B., Liff, C., Campbell, W., Cassell, D., Church, R. and NUSZ,R., 1989. Regional relationships between geomorphidhydrologic parameters and surface water chemistry relative to acidic deposition. J. Hydrol., 112: 103-120. Newton, R.M., Weintraub, J. and April, R., 1987. The relationship between surface water chemistry and geology in the North Branch of the Moose River. Biogeochem., 3: 21-35. RosBn, K. (ed.), 1991. Chemical weathering under field conditions. Swedish University of Agricultural Sciences, Uppsala, Report 63, 185 p. Hutchinson, G.E., 1957. A Treatise on Limnology. I. Geography, Physics, and Chemistry. Wiley, New York, 1015 p. Lerman, A. (ed.), 1979. Lakes - Chemistry, Geology, Physics. Springer-Verlag. Heidelberg, 363 p. Csanady, G.T., 1978. Water circulation and dispersal mechanisms. In: Lerman, A. (ed.). Lakes - Chemistry, Geology, Physics. Springer-Verlag, Heidelberg, pp. 21-64. Graf, W.H. and Mortimer, C.H. (eds.), 1979. Hydrodynamics of Lakes. Elsevier, Amsterdam, 360 p. Simons, T.J., 1980. Circulation models of lakes and inland seas. Can. Bull. Fish. Aquat. Sci., 203: 1-146. Vollenweider, R.A., 1968. The scientific basis of lake eutrophication, with particular reference to phosphorus and nitrogen as eutrophication factors. Tech. Rep. DASAISV68.27, OECD, Paris, 159 pp.

42

APPENDM: MODEL CHARACTERISTICS(COMPARTMENTS,MODEL VARIABLES AND LAKE-SPECIFIC VARIABLES) 1. Mixed model

A. Compartments: 1. Lake water 2. Fish 3. Prey B. Model variables (rates in 1 /month, area etc. in m2): 1. Bio-accumulation factor = 150K moderator 2. Resuspension factor, RF = (DR)o.2 3. Retention in lake water = 1/(RF.(T>((3"(11+2gh0,6)/(1.5))) 4. Retention rate for fish = 0.693/(2.X.12),where Xis set to: 3 years for pike and large predatory perch; 1.5years for trout and minnow; 1year for char and perch (= 20 g); 0.75 year for roach; 0.5 year for smelt 5. Retention rate for prey = Retention rate for fish.2 6. K moderator = GRAPH(K concentration) C, Lake-specific variables (examples for Lake Ovre Heimdalsvatn): 1. K-concentration = 0.4 mg 1-' 2 . Lake area = 0.78.106 3. Mean depth = 4.7 4. Water retention time T = (63130) 5. Fallout = 130000 Bq/m2month 5 1986 2. VAMP model

A. Compartments: 1. Dissolved in water 2. Active sediments 3. Lake water first week after fallout 4. Lake water 5. Outflow areas of the catchment 6. Passive sediments 7. Phytoplankton 8. Predator 9. Prey 10. Particulate in water

43

B. Model variables (rates in 1 /month, area etc. in m2): . (Altitude . Latitude . 1. Averaging function = (50.Vol~me("~))/(Precipitation Catchment 2. Benthic uptake rate = 0.00000025 . (Dynamic ratio) 3. Bio-accumulation rate plankton to prey = 0.25/12 4. Bio-accumulation rate prey to predator = Bio-accumul. rate plankton to prey = 0.25/12 5. Direct uptake rate = YpH plus K . 0.0004 6. Initial Kd = 0.5 7. Outflow areas OA = 0.1 8. Outflow rate from catchment = Seasonal moderator. 0.04412 . (ddelay time, Month of fallout,l)))) 9. Partition coefficient Kd = 1/(1.04+(1.75.((~W4)-')~)) 10. Phytoplankton outflow rate = 1 11. Phytoplanktonic uptake rate = YpH plus K.0.005 12. Predator biomass = Prey biomassl(24Transfer C O ~ ~ V ~ . ~ ) 13. Prey and predator outflow rate = 1/(X.12),whereXis: 3 years for large pike and large, predatory perch (> 20 g); 1.5 year for minnow, trout, etc.; 1year for perch (10-20 g ) , etc.; 0.75 year in whitefish, roach, etc.; 0.5 year for smelt, perch fry (c 10 g), etc. 14. Prey biomass = (Phytoplankton biomassflransfer coem 15. Retention in lake water = Seasonal moderator/F30~~T+zs~+o~5~ / (1.5)) 16. Retention rate in active sediments = Sedimentation rate of suspended matterflhickness of active sediments 17. Sedimentation rate of Cs = l/Mean depth 18. Thickness of active sediments = 2 cm 19. Transfer coefficient = (Prim production+ 1)o.66 20. Seasonal variability norm = GRAPH(T1ME) 2 1. YpH plus K = GRAPH(pH plus K) C . Lake-specific variables (examples for Lake 0vre Heimdalsuatn): 1. Altitude = (1090+1) m.a.s.1. 2. Atmospheric load = 130 kBq m2 3. Catchment area = 23.4,106m2 4. Lake volume = 3.7.106m3 5. Water retention time = 63/30 months 6. K concentration= 0.4 mg 1-' 7. Lake area = 0.78.106m 2 8. Latitude = 61 iN 9. Month of fallout = 5 10. p H = 6.8 11. Precipitation = 800 mm y e a r' 12. Primary production = 27.5 g C m-' y e a r' 13. Sedimentation rate of suspended matter = 60 g m-2 y ear'

44

3. Generic model

A. Compartments: 1. Active sediments 2. Lake water 3. Passive sediments 4. Dissolved phase; 5. Suspended particulate phase 6. Catchment 7. Benthos 8. Plankton 9. Predator 10. Prey

B. Model variables (rates in 1 /month, area etc. in m2): 1. Accumulation rate sediment to benthos = 0.00001 2. Accumulation rate suspended particulate phase to (phyto- and zoo-) plankton = 0,00001 3. Accumulation rate water to plankton = O.O02/K moderator 4. Thickness of active sediment layer = 0.02 5 . Bio-accumulation rate benthos to predator = 0.02 6. Bio-accumulation rate benthos t o prey = 0.001 7. Bio-accumulation rate plankton to prey = 0.001 8. Bio-accumulation rate prey to predator = 0.01 9. Bioturbation coefficient = 1+14Mass of benthos/lO-') 10. Direct uptake rate = 0.00001K moderator 11. Mass of benthos = Total bio-production.0.1 12. Mass of predator = Total bio-production/(lO.Transfer coefficient) 13. Mass of prey = Total bio-production/Transfer coefficient 14. Outflow area = 0.1 15. Rate of Cs sedimentation = l/(Lake volumeLake area) 16. Resuspension factor = 0.01 . 17. Retention coefficient of active layer = Sedimentation rate of suspended materialPThickness of active layer 18. Retention coefficient of benthos = 0.5 19. Retention coefflcient of plankton = 1 20. Retention coefficient of predator = 0.693/(X.12),where X i s set to: 3 years for pike and large predatory perch; 1.5 years for trout and minnow; 1year for char and perch (= 20 g) 21. Retention coefficient of prey = 0.693/(0.Y.12),where Y is set to: 0.25 year for zooplankton; 0.5 year for smelt; 0.75 year for roach; 1year for small perch 22. Transfer rate from inflow areas = 0.001/12 23. Water retention coefficient = 0.693/(0.5.Theoreticalwater retention time)

45

24. 25. 26. 27.

K moderator = GRAPH(K concentration) Partition coefficient Kd = GRAPH(T1ME)

Transfer coefficient = GRAPH(Primaryproduction) Transfer rate from outflow areas = GRAPH(T1ME)

C. Lake-specific variables (examples for Lake 0vre Heimdalsvatn) 1. Catchment area = 23.4.106 2. K-concentration = 0.4 3. Lake area = 0.78.106 4. Lake volume = 3.7.106 5. Precipitation factor = 800/600 6. Primary production = 27.5 7. Sedimentation rate of suspended particulate matter = 60.(1/13200) 8. Theoretical water retention time = (63/30) 9. Fallout = 130000 Bq/m2month 5 1986

Freshwuter und Estuurine Rudioeecolrigy Edited by G . Desmet et d. 0 1997 Elsevier Science B.V.All rights reserved

47

Aquatic radioecology post Chernobyl - a review of the past and a look to the future J. Hilton Institute of Freshwater Ecology, The Riuer Laboratory, East Stoke, Wareham, Dorset BH20 2BB, UK

ABSTRACT The dynamic nature of environmental pollution following the Chernobyl accident has highlighted a number of limitations to the models of radionuclide transport in aquatic systems which were developed under the pseudo-equilibrium conditions following the atmospheric testing of atomic weapons. Much of the work has concentrated on caesium and has highlighted the importance of specifying the chemical form of the caesium and the rate of transfer between different physico-chemical forms. Ion exchange theory models have made a significant contribution to our understanding of these processes and have be applied directly to models for predicting the storage and run-off of radionuclides from catchments. A number models, which combine hydrodynamic properties with chemical behaviour, have been developed to explain and predict the transport of radionuclides in lakes and rivers. Uptake of radionuclides by biota was originally modelled using the steady-state concentration factor approach. The requirement to understand the dynamics of uptake and loss by biota has led to the development of complex box models which are extremely helpful in understanding specific situations. However, their requirement for large, amounts of data for calibration is leading to the development of new models based on an understanding of the processes involved in transporting radionuclides across membranes, both in unicellular and multicellular animals. 1. INTRODUCTION

It is now many years since the last international seminar on aquatic radioecology. At that time almost all our knowledge of radioactivity in the natural environment was gathered from experience gained with the atmospheric deposition of radionuclides derived from the testing of atomic weapons in the atmosphere. As a result much of the work from that time was based on pseudo steady-state criteria. In 1986 the accident at the Chernobyl power station

TABLE 1 Groups involved in the framework I11 and Chernobyl programmes 19861994

ENEA (Italy) Institute of Experimental Meteorology (Russia) Institute of Freshwater Ecology (UK) (coordinator) Institute of Geochemistry and Geophysicsof the BSSR Academy of Sciences(Belorussia) Katholic University, Leuven (Belgium) LNETI (Portugal) Stichting Energieonderzoek Centrum Nederland (The Netherlands) Ukrainian HydrometeorologicalInstitute (Ukraine) Biological uptake: CEA, Cadarache (France) Institute of Hydrobiology, Kiev (Ukraine) Keuring van ElectrotechnischeMaterialen (The Netherlands) LNETI (Portugal) Norwegian Institute for Nature Research (Norway) Severtzov Institute of Evolutionary Morphology and Ecology of Animals (Russia) University of Antwerp (Belgium) University of Liege (Belgium) University of Malaga (Spain) University of Nantes (France)

occurred and the pulsed input of radionuclides into the environment has focused our attention much more on dynamic situations. In addition the effects of deposition from this accident highlighted gaps in our understanding particularly with respect to the interaction of radionuclides with upland soils. In response to these new challenges aquatic radioecology has moved on significantly since the last meeting. As a result I would like to review the state of radioecology today using examples from the work of two European Community research programmes in aquatic radioecology and, from this base, to identify requirements for future research. Although this review is based on research from European Community programmes it is nonetheless a personal view. However I am indebted to colleagues from the research groups listed in Table 1without whom this paper would have been impossible, The essence of most aquatic radioecology post-Chernobyl has been the emphasis on the processes which transport radionuclides through the environment. The main objectives of this more fundamental, process-based work is three-fold (1) to improve models, particularly in reducing the degrees of freedom in fitting data during calibration exercises; (2) to develop scientificallybased countermeasures;and (3) to interpret site specific problems in terms of dominant processes so that appropriate mixes of countermeasuresfor local solutions can be devised.

49

Because of its dominance in Western European studies, the majority of the work outlined here focuses on radiocaesium. However, the approach developed can usefully serve as a model for other radionuclides since the processes discussed are common to all elements, only the balance in the relative importance of different processes changes for different radionuclides. Figure 1shows a conceptual model of radionuclide transport in the aquatic environment after an atmospheric deposition event. The stippled circles show those process steps where the distribution of radionuclide between the solid and liquid is a major parameter. It is generally described by the adsorption coefficient, &, which is defined at equilibrium as:

Kd =

concentration of radioactivity in solid (Bqkg) concentration of radioactivity in liquid (BqA)

(1)

This parameter can be used to describe the distribution of radioactivity between particles in dilute suspension and the water; and between particles in sediments and interstitial (pore) water. It has also been applied to settling solids in sediment traps and the surrounding water. In this situation the assumption of equilibrium is more risky but may be acceptable. However it is not applicable to sediments and the overlying water where equilibrium is not a reasonable assumption. Kd is usually regarded as a constant, but values ranging from 10' to lo7 (for Cs) have been reported in the literature. Immediately prior to the Chernobyl accident it was becoming clear from the work of Evans et al. 111, in particular, that layered clay mineral particles, particularly the mineral illite, played an important role in the sorption of radiocaesium in lake sediments. Brouwer et al. [21 measured the Kd over a range of different radiocaesium concentrations. At very low caesium concentrations he observed that the Kd was very high, but with a small increase in caesium concentrations the Kd rapidly dropped and then maintained essentially a constant value irrespective of further increases in caesium concentration. They interpreted this behaviour in terms of two major types of site on the illite mineral which can be visualised as shown in Fig. 2. In diagrammatic form, a layered illite clay mineral particle can be likened to a stack of plates. Each plate is made up of silicon and oxygen atoms. In between these plates are potassium atoms which act as glue holding the silicon-oxygen plates together. The large number of sorption sites which Brouwer [2] identified at higher caesium concentrations are located on the top and bottom faces of the pile of plates. These sites have no real preference, in terms of shape, between one atom and another. Hence they are completely unselective. The second, much smaller number of sites, are located on the edge of the stack of plates identified by arrow B in Fig. 2. At the edge of the pile of plates the spaces between the plates tend to fan out slightly creating openings which can accommodate atoms with a small atomic radius but which will not accommodate large atoms (or hydrated ions). Because caesium can easily lose any

50

WET AND DRY

ATlOl

\

\

\

LI -1 r1 INVERTEBRATES

INGESTION

CARNIVORES, INVERTEBRATES AND FISH

INGESTION

A

EXCRETION

A

\

f

f

z 0

I-

S

9

3 W

p: Y

0 u I l

0

ln

-

Fig. 1. A conceptual model of the transfer of radioactivity from atmospheric deposition into fish.

51

A

silicate sheet

B

A Fig. 2. A diagrammatic representation of an illite mineral. Arrows A indicates the planar, unselective sites and arrows B indicate the highly selective, frayed edge sites.

water attracted to it by its positive charge it has a very small ionic size and can enter these spaces easily. However, other ions which are very similar such as potassium or ammonium have much more difficulty entering these sites making them much more selective for caesium. The parameter which describes the relative selectivity of sorption sites is called the selectivity coefficient, K,, and for the unselective sites on the top and bottom of the plates has a value of about 1for all ions of the same charge. At the selective sites K, is about 1,000 potassium and about 200 for ammonium compared to caesium [31. As a result of the very high selectivity for caesium of this small number of sites it has been hypothesised that the sorption of radiocaesium on to soil and sediment particles is dominated by these, so called, frayed (= broken) edge sites. Hence if we can describe these sites accurately we should be able to predict the sorption properties of soils and sediments and they should be related to the illite content of the soil. The selectivity of the frayed edge sites can be determined from experimental measurements on pure illite minerals 131. However, attempts to measure the number of frayed edge sorption sites in soil and sediment samples are complicated by the sorption of ions onto the unselective or planar sites on the rest of the soil matrix. For this reason Cremers [41 developed a technique in which the unselective sites in the soil matrix, including the planar sites on illite clay minerals, are filled by a very large molecule, in their case silver thio-urea, which is too big to enter the frayed edge sites. As a result only the frayed edge sites are exposed and measurements of their numbers and other properties can be made in the presence of a large number of non selective sites. On the assumption of simple ion exchange at both sites, it is possible to define the Kds of the planar and frayed edge sites in terms of the two following equations:

52 plan= d

=

e

[CECI . [majorcompetitor]

where [CECI is the cation exchange capacity of th solid in mE/k and [major competitor] is the concentration (mmol) of the major competitor. is the selectivity coefficient of caesium relative to the major competitor; and

e

e

= 1000 (K') where [FESI = the frayed edge site concentration (mE/kg) and o r e "= 200 (NH;) for frayed edge sites. From these equations it is clear that the Kd should be inversely related to the concentration of the major competitor. For the planar sites, where the cation exchange capacity is the dominant property, all the major ions (Ca, Mg, Na, K) in the water are competitors, whereas at the frayed edge sites only K+and NH: are the main competitors. At the frayed edge sites under oxic conditions potassium will be the main competitor and for anoxic conditions it will be ammonium. Figure 3 shows a plot of the Kd in sediments from Ketelmere versus 1200

1000

800

600

400

200

0 0

0.2

0.4

0.6

0.8

1.0

1.2

NH:(~M) Fig. 3. A plot of Kd versus ammonium ion concentration in the pore waters of Ketelmere [5].

53

the ammonium concentration in the pore water [51. A good straight line is obtained on a plot of log Kd v log[NH;] with a slope very similar t o the value of -1 predicted by the theory. There is one further complication with the sorption of radiocaesium to illite. As time progresses, caesium on the frayed edge sites can migrate between the lattice sheets and replace potassium there. In so doing it becomes unavailable for normal exchange [61. Comans and HocMey 171 modelled experimental data using a four component model and the assumption of a Freundlich sorption isotherm. The four components are the water; a proportion of the frayed edge sites at which instantaneous equilibrium of caesium between the water and the sites occurs; a second proportion of the FES over which the maintenance of equilibrium is kinetically controlled; a component into which caesium can slowly migrate from the FES and become unavailable (or migrate out again much more slowly). / .

Y

Frayed Edge y,

\

k

Water X

\

Unavailable 2

I

r \

,

r

Frayed Edge y*

,

/

The reaction kinetics are described by the equations: [Yll = f k

[XI"

-din- k([YlI + [Yzl)

dt

(4a)

(4c)

f i n = Freundlich isotherm constants

These equations can be solved by including the mass balance equation:

subscript 0 denotes concentrations at time zero. They showed that diffusion into unavailable positions is much faster in the presence of calcium saturated illite compared to potassium saturated illite.

54

They also showed that the half time for the reaction rate of immobilisation is about of the order tens of days. Konoplev et al. [81, during this conference, have presented work to show that the reverse rate is about an order of magnitude lower with a half time approximately hundreds of days. Hence, although the radiocaesium is partially immobilised it is still available for remobilisation over very long time scales. As a result of all this work our understanding of radiocaesium sorption is almost sufficient for our purposes. However, a few outstanding problems still remain, In particular we cannot quantify the variability in the rate of immobilisation which can cover the range of more than 80%of the caesium immobilised within 24 hours, t o significantly less than 30% immobilised over a period of several months [9]. In addition, although our understanding of the behaviour of radiocaesium in mineral soils is now quite good the application of this theory to upland soils, where illite is relatively scarce, still requires more work t o allow predictions to be made of the length of time for which radiocaesium will remain recycling within these systems. As a result some further work is still required on caesium sorption but our knowledge should be at an appropriate level within about 5 years. Having established the fundamental properties controlling the variation at Kd it now becomes easier to understand and predict runoff of radionuclide from catchments. 2. CATCHMENT PROCESSES

Within a few months after the Chernobyl accident it became clear that the concentration of radiocaesium in some lakes in the English Lake District, (which was heavily contaminated by Chernobyl fallout), remained much higher than in nearby lakes [lo]. Two years after the accident some lakes retained concentrations as high as 100 mBq 1-' whereas others were significantly less than 10 mBq 1-I. An analysis of this data suggested that the lakes which retained high concentrations had significant quantities of peat bogs within their catchments [lo]. Figure 4 shows a plot of the caesium radioactivity in stream waters in one of these lakes. Two distinct patterns can be seen; streams 1 and 2 which show very high concentrations which are highly variable and streams 3 , 4 , 5 and 6 which are much lower and much more stable. The lake concentration lies in between. A detailed analysis 1111 of these stream concentrations showed that the streams with high concentrations emanated from sub-catchments with high proportions of peat and that loss rates were of the order of 2-3% per annum whereas in other non peat sub-catchments loss rates were an order of magnitude lower. Hence, it becomes clear that the soil in the sub-catchment type is an important factor particularly with respect to the presence or absence of sphagnum peat bogs. Carlsson [121 presented a general equation for the change in radioactivity in a catchment with time as follows:

55 Devoke Water 1987

I

1988

1989

Inlets

Days from 61h May 1986

Fig. 4. C s activity in streams of Devoke water 1111.

Ft is the amount of radioactivity remaining on the whole catchment at time t after a deposition event; At is the total catchment area; h, is the fraction of the initial deposition which is lost rapidly from the whole catchment; 6 is the deposition flux (Bq/m2/unittime); his the decay constant for the radionuclide in question; hi is the fraction of the cumulative deposit which is lost per unit time by erosion of soil particles from the ith soil type; is the fraction of the cumulative deposit which is lost per unit time by desorption of weakly sorbed radionuclides from the ith soil type; A, is the area of the ith soil type within the catchment; F, is the

cumulative activity (Bq/m2)retained in the ith soil type of the catchment; the summation sign indicates summation over all soil types in the catchment. Tipping et al. [131 has shown that ha,i.e. the fraction of initial deposition which is lost rapidly from the whole catchment, depends on the saturation level of the soil at the time of deposition such that a saturated soil will lose much more than an unsaturated soil. In order to estimate these proportions Tipping [13] utilised a complex model involving water movement as well as chemical properties. However, if the proportion of rapidly lost radionuclide can be estimated from a soil core soon after deposition then the rate of change over longer time periods can be estimated from Konoplev et al.’s [81 calculations. They proposed that hb,the erosive loss of solid particles containing radioactivity is given by the following equation [ 14,151.

56

where Li is the proportion of the inventory removed in particulate form in time period, t (time-'); C, is the time averaged mean concentration of radioactivity on soil particles; C,is the time averaged mean inventory in the top 3 mm of soil (Bq m-'); M is the total amount of suspended solids removed over the time period of interest (g m-' time-') estimated from universal soil loss equation [ 161; A is the area of the drainage basin (m'). They also showed that &, the fraction lost in dissolved form can be given by 1141,

where: h, is the proportion of the radionuclide in the top 3 mm of soil removed in solution (time-'); C,is the time averaged mean inventory in the top 3 mm of soil (Bq m-'1; V is the volume of run-off over the time period of interest (I); A is the area of the drainage basin (m'); Cl is the time averaged mean concentration of radioactivity in the soil water over the time period of interest (Bq 1 3 and can be estimated from:

where C1 is the concentration of radioactivity in the soil solution; Rexis the amount of exchangeable radioactivity on the solid; MI is the concentration of an appropriate competing major cation (e.g K' for Cs; Ca'' for Sr) in the soil solution; M,,is the amount of exchangeable competing major cation on the solid; KE is the selectivity coefficient for R with respect to M Ke., the strength of binding to R compared to the strength of binding to M). 3. LAKE PROCESSES

In deep lakes there are three potential processes by which radionuclides in the water column can be lost. These are the hydraulic flushing of water through the outflow, the sorption of radionuclide to particles which subsequently settle to the bottom sediments taking the radionuclide with them and thirdly the molecular diffusion of dissolved radionuclide across a, so-called,boundary layer again for storage within the sediment. The basic equation [171 is given below: z

57 where: Co= initial activity; F = outflow rate (m3d-'); A = surface area of lake (m'); u = bulk settling velocity of particles; kd = sorption coefficient (m3kg-l); S = suspended solids concentration (kg ma); D = diffusion constant (m2d?; z = boundary layer thickness (m). The equation assumes that the amount of radioactivity in the outflow in particulate form is small compared to the amount of radioactivity in dissolved forms. The particle settlement component is dependent on four variables: the cross sectional area of the lake, the settling velocity of particles in a lake, the sorption coefficient and the suspended solids concentration. It is still not clear whether the cross sectional area should be the total lake area or the area of accumulating sediment, and arguments can be made for either of these but since they seldom differ by a factor of 2 the argument is probably academic. Settling velocities usually vary between 0.1 to 1 m per day, although the presence of large calenoid zooplankton can create faecal pellets which settle between 15 and 20 m per day (181. However, a value of about 0.5 m per day is generally a good starting point. &s, of radiocaesium in particular, have been discussed above and will not be discussed further here. However, the Kd will vary depending on the proportion of organic mattedalgae in the suspended particles [ 191. This is produced within the lake at different rates at different times of the year. Suspended solids concentrations generally vary in deep lakes from a few mg 1-' up to a few 10s mg 1-'. The third component, the boundary layer transport, is potentially simple t o calculate but generally there are significant problems. In reality there is a region, up to several metres thick, in which an exponential reduction in turbulence from the turbulence levels in the open water to zero at the sediment interface takes place. However in this form it is rather difficult to model and so from a physicalkhemical point of view the concept of the boundary layer is introduced [20],which is a thin layer of static water next to the sediment, across which molecules and ions can travel by molecular diffusion (Fig. 5). The rate of transport across this boundary is given as follows:

-dC - D . ( C , - C J dt

z

where D is the diffusion constant which, for many ions, is tabulated by Li and Gregory [21];C , is the concentration of radionuclide in the open water; C, is the concentration of radionuclide in the interstitial water, and z is the boundary layer thickness. One difficulty is that there are very few measurements of boundary layer thickness at present, but a figure of about 350 pm is probably a reasonable value, at least for hypolimnetic waters. A further complication is that the concentration in the interstitial water is only zero at the start. As the sorption sites in the sediment fill up an equilibrium establishes itself between radioactivity in the interstitial water and on the solid sediment so that C,tends to increase with time [22].Although it is possible to calculate this after making

58

Concentration (open water)

7

Boundary layer

concentration gradient

1

'CoAcen;rot.:on

/

1

1

[interstitial water)/

Diffusion

/ / /' /

Fig. 5. The boundary layer.

some assumptions it does complicate models significantly. In the first instance it is a reasonable assumption to set Ci = 0 but it should be recognised that this will overestimate the importance of this component. It should be noted that under anaerobic conditions the concentration in the interstitial water can rise, due to the presence of reducing conditions creating high NHt concentrations in the pore water which displaces caesium so that concentrations become much higher than those in the water column. On these occasions radioactivity will be released from the sediment at a rate again determined by this equation but with Ci and C , reversed. Work is in progress to improve the ease of measurement of z and extend the range of locations for which measurements are available. 4. TURBULENT SYSTEMS

The previous equations are applicable in deep lakes where turbulence is relatively small but in rivers and shallow lakes turbulence is such that resuspension can become a major transport mechanism for bringing radioactivity on sediment particles back into the water column. This is given by the following equation which can be extended to give information on two-dimen-

59

sional transport with time if the appropriate equations for the advective transport term are included 1231.

_dC_ - A + D - R f P - qc+ S dt

(11)

where C = activity of radionuclide in water; A = advective transport term; D = dispersion term; R = resuspension-sorptioddesorption-sedimentation term; P = exchange across sediment boundary; qc = radioactivity decay; S = source or sink term. Using this series of equations it is possible to obtain reasonable estimates of the rate of change of radioactivity in different components of the catchment and lake/river systems with the minimum of calibration a n d o r measurement of input parameters. The main difficulty in the use of Eqs. (9) and (11) lies in the fact that not all lakes appear to require all components. For example, [17] showed that transport across the boundary layer was a dominant process in a Canadian shield lake, whereas Davison et al. [241 and Robbins et al. [19] showed that boundary layer transport was likely to be a small component of the total transport to the sediment. Similarly, it is not clear when sedimentary release is likely to be important or when resuspension in lakes will dominate. Further work is required to develop an expert system to guide modellers. 5. THE UPTAKE OF RADIOACTIVITY BY BIOTA

As a result of the growth of radioecology from mainly pseudo steady-state

systems prior to Chernobyl, uptake of radioactivity by biota was normally described by the equilibrium parameters, the concentration factor (CF) and the trophic transfer factor (TTF), defined as follows:

CF =

concentration in organism co n c e n tr a t i a n water

TFF =

concentration in trophic level n + 1 concentration in tr o p hideve In

(12) (13)

The parameters are only applicable under equilibrium conditions. However, as with Kd,even when CF and ?r'F values reported in rivers are excluded (as the equilibrium condition is not met) CF and TTF still vary over several orders of magnitude for a given species. As a result of these observations and comparisons with other pollutants it was becoming clear that a dynamic description was required even before the Chernobyl accident. Typical of these is the Thomman [251 model. dC dt

-= input

from water

+ input food - excretion - growth dilution

60

kWF= transfer rate from water to organism; kZF= transfer rate from food to organism; kFW = excretion rate; Cw = concentration of radionuclide in water; Cz = concentration of radionuclide in food; CF = concentration of radionuclide in organism; M = weight of fish. By making the assumption that no growth takes place over the period of interest and that uptake occurs only from the water Eq. (14) can be simplified to give [261:

This can be integrated to give:

assuming CF= 0 at t = 0; at t = w; i.e. at equilibrium

which is Eq. (12). A similar equation to Eq. (14) can be used for zooplankton [26] where Cz would be the concentration of radionuclide in algae and again an equivalent equation would be available for predatory fish where C, would be the concentration in the prey fish.Hence dynamic trophic chain systems can be built up from a number of these equations. Again, for the simplifying situation of steady state they reduce t o Eq. (13). However, in dynamic situations a large number of rate constants are required to make predictions. At the present time, the rate constants can only be obtained by carrying out laboratory experiments. An elegant example from the work is shown in Fig. 6 [27-44,46-481. As can be seen for complex trophic chains the number of experiments which are required to calibrate the systems is very large. Because it is known that to some extent the uptake and loss rate contents are species specific, food specific and dependent upon the chemical properties of both the water and the sediment, it is not possible to use data collected from one system to calibrate models for use at another site. For example uptake rates and excretion rates measured in hard water laboratory systems applicable to French rivers would not be applicable to soft water systems such as those in Scandinavia. As a result studies are now taking place to try and predict the rate constants from a knowledge of the underlying physiology and chemistry of the processes involved in uptake and excretion.

61

Fig. 6. Kinetic parameter for a simple trophic chain model (from Ref. [27]).

A study of the concentration factors given for algae in the literature shows that a wide range of values covering up to three orders of magnitude is quite common. An algal cell cannot differentiate between a caesium ion and a potassium ion. Hence a study of potassium uptake mechanisms for algae will give information on the uptake mechanisms involved in radiocaesium accumulation. Figure 7 shows the uptake rate of potassium versus the concentration of

62

Uptake rate of Kf

EXTERNAL

1

INTERNAL

+ I -

K' H+

H+

channel

L

Rb' Cs' I

\

T-

Fig. 7. (a)The uptake rate of potassium as a function of [K'l in the medium. (b) Active uptake pumps for K', H ' and Cs'. (c)Passive uptake channel for K+and Cs', after Ref. [501.

potassium in the medium. As can be seen there are two different regions in the plot. Above about 0.1 mmol the rate of uptake of potassium increases linearly with the increased concentration in the water, whereas below this level, the uptake rate is zero at zero concentration and increases quite rapidly to approach an asymptote when concentrations in the water approach 0.1 mmol. It is now recognised 1491 that at high concentrations, the linear relationship is due to passive uptake by the cell through the cell membrane. Whereas the increase to an asymptotic value occurs due to active uptake in waters where potassium in the water is low and the cell has to do work to concentrate the potassium, and accompanying caesium, into the cell [501. Over the last few

63

years new techniques have shown that the difference in the concentration of positively charged ions within the cell and outside the cell creates a voltage drop across the cell wall so that the inside wall is negatively charged and the outside wall is positively charged. This voltage drop across the cell membrane is known as the membrane potential. The work done in travelling down this electro-chemical potential allows small positive ions, like potassium, rubidium and caesium to pass through specific channels in the cell wall into the interior of the cell and accumulate. The channel itself is selective for monovalent ions but is relatively unselective between them. Hence the uptake efficiency decreased in the order: (100%)K ' > Rb' > NHt > Na' 1 Li' > Cs' (60%).From his knowledge of the processes involved in passive uptake across an open channel, Fernandez et al. [491 have shown that the uptake rate is a function of the external concentrations of monovalent ions such as potassium, ammonium and sodium, with potassium being the most important. The Ca2' ion concentration is also important since this defines the probabilities of channels being open, ie the calcium concentration affects the rate of uptake but not the final equilibrium value. In addition the algal species itself determines the number of channels etc. which defines the base uptake rate under a given set of conditions. Caesium concentration factors at potassium concentrations in the water greater than 0.1 mmol are typically in the range 5-30. Because the driving force in this process is an electro chemical potential the uptake rate is a function of the chemical potential (Ap) such that

where F = Faraday constant, z = ion charge (in the case of caesium and potassium = l), Em = membrane potential and EN = Nernst potential. The Nernst potential for any ion is given by

RT external concentration EN = x In ZF internal concentration

(19)

The internal concentration divided by the external concentration = the concentration factor (CF). From Eq. (18) it can be seen that at equilibrium, Em= EE = E$. Hence the concentration factor for caesium

This is Vanderpleogh's relationship 1511 where [KLJ = a constant = membrane potential = fn (species). At low potassium concentrations the membrane potential voltage drop is not sufficient to force the potassium and caesium from a low concentration in the

64

medium to a high concentration within the cell itself. In these situations it has been shown [50]that so-called ion pumps in the cell wall actively move molevalent ions from the external medium into the cell. The pump in question allows both potassium and other molevalent ions through and also protons. If potassium is considered to be 100% efficient then rubidium is slightly less efficient, caesium is slightly less efficient again at approximately 50%, lithium is slightly less efficient and sodium is very much less efficient at about 1% efficiency. Because hydrogen ions are also brought into the cell via the proton pump, a mechanism is required to remove the positively charged protons and stop the cell from becoming very acid internally. Hence a pump working the opposite way driven by the ATP metabolism forces protons from the inside of the cell back out to the external medium. From this reasoning, it is known that the control variables must be the external ions particularly potassium, but also the pH since the hydrogen ion concentration has a major effect. Because of the need to expel protons the metabolic rate, which is a function of temperature, will also be important and there is speculation that the algal species will show differences in the rates of transport through these active uptake channels which come into play when potassium is scarce. As a result of active uptake, concentration factors for radiocaesium when this mechanism is dominant are much higher than for the passive uptake and range from about 300 to 1000. Although this fundamental approach is still in its infancy it is encouraging to see that empirical formulae, like Vanderpleogh's equation [51]can be derived and that a systematic understanding of variations can be developed. Further work is now required to systematically make measurements of internal Cs+and K+ concentrations under known conditions of the fundamental parameters in order that CF of any algal species can be predicted, given the potassium concentration (for [K'I > 0.1 Mm at present). The uptake of radionuclides by multicellular animals is more complex still. In this case the fundamental processes are less well understood although presumably channels exist to transport ions through the cell wall. For uptake through the gill it is possible to interpret laboratory experiments using pharmacokinetic analysis [521.The fish is treated as a one-compartment open model for uptake of radionuclides, where complexation and loss to container walls modify the rate of radionuclide uptake. The model developed can be used to analyse data involving non-constant exposure to radionuclides in natural environments. The clearance from the water of radionuclides depends on a number of factors which can be related to (1)the concentration and chemical speciation of the radionuclide in the water and other sources, and (2) the kinetics and selectivity of the transport systems involved in the uptake and elimination of the radionuclide in the organisms. A convenient model to describe these effects and incorporate them in the pharmacokinetic model is the Michaelis-Menten model for enzyme kinetics. With this approach the uptake rate from water to fish in the general inputloutput Eq. (14)can be substituted as follows:

66

where: CF= concentration of the ion of interest in the fish; Cw = concentration of the ion of interest in the water; Sw = activity of the form of the ion in the water which is taken up by the animal; and K , and V,, are constants. The activity is a property derived from the concentration by correcting for differences in ionic strength of the test solutions. The Michaelis-Menten equation has the typical form shown in Fig. 8, where V,, is the maximum rate of uptake at high substrate concentrations and K,, the binding constant, is the activity of substrate which produces a rate half the maximum. Experiments [53] have shown that three factors are important. The chemistry of the acclimation water, the chemistry of the exposure water and the form of the substrate. If the animal is acclimatised in water of a certain chemistry then ancillary ions such as, say calcium, will change the number of channels which are open and will have some physiological effect on the animal [531.These effects may drastically change V, and K,. In effect, the acclimation water chemistry may change the transport system entirely. The chemistry of the exposure water, particularly calcium, pH and temperature, also affect both K, and V-. Typically, if the exposure water concentrations are not very different from the acclimation water then different exposure conditions will tend to scale V, and K,, rather than make gross changes since the same transport processes will be operating as in the acclimation condition. The form of the substrate is also important. It is generally one specific form, normally the free ion, which is taken up through the channel [541.Hence the total substrate amount is not a useful measure. The proportion of the total substrate which is in the relevant form for uptake is directly affected by the chemistry of the exposure water and can be calculated

Fig. 8. General Michaelis-Menten type curves.

66

from speciation models. Inhibition effects such as the influence of calcium competition on cobalt uptake can be incorporated by adding extra parameters to modify V,, and K,. So far, quantitative relations have been obtained to model the effect of chemical speciation, ionic strength and water hardness on the uptake of radio-cobalt by the fish. The models that have been constructed make it possible to predict the effect of changes in these conditions on the uptake of radio-cobalt by the carp in a variable environment 1551. The integration of this concept to uptake models is in its infancy and most work to date has been carried out on transport across the gill membrane. However, it is not inconceivable that the same approach could be used for uptake from the gut where the pH may be more important and calculation of the speciation of the substrate may be more difficult. The main benefits of this type of work are that properties (channels) of the gill or gut membrane are probably similar for all fish. Therefore it should be possible to measure the effect of say calcium, pH and temperature once in a laboratory and these values could then be incorporated into any model reducing the requirement for multiple laboratory experiments to calibrate inputloutput trophic level models. Recently it has been shown that ecological effects can also have a major role in determining the radioactivity of fish within the same lakes. Forseth et al. [561showed that in Lake H~ysjaenin Norway, charr were normally found in the deeper pelagic water whereas brown trout were normally found in the shallower littoral zone (Fig. 9a). As a result the mean annual temperature experienced by the trout was 3°C higher than the mean annual temperature experienced by the charr. By examining the stomach contents it also showed that charr almost exclusively fed on zooplankton whereas brown trout fed mainly on zoobenthos and surface insects (Fig. 9b). By back calculation they also showed that the daily ration size for trout, particularly over the mid and late summer,was significantly higher than the daily ration size for charr so that the total food consumption from June to October 1987 was estimated at 860 mg dry weight g-' of trout fresh weight and 233 mg dry weight g-' of cham fresh weight. They also showed that trout both accumulated radiocaesium faster and reached a higher maximum of 16,340 Bq kg-' wet weight compared to a maximum of 5,460 Bq kg-' wet weight in charr. However trout also lost radioactivity faster than charr so that the ecological half lives were 357 days and 550 days respectively. By combining data on the radiocaesium content of the food articles and the food input, the net intake of radiocaesium by trout and charr over the observation period were estimated at 4,800Bq kg-' fresh weight and 1,500 Bq kg-' fresh weight respectively. By combining all these data they concluded that the food intake for trout was greater than for charr. Hence the higher peak activity levels and earlier time of occurrence of the peak in trout. However, because charr lived at a lower temperature they were more efficient in their utilisation of food and assimilated more radioactivity compared to trout. This effect was increased because cham fed for much longer during the year and hence continued to accumulate radiocaesium as opposed to the trout

67 a) Catch per unit effort

b)

Dominant prey types

100,

0-3

1987

80

3-7

May June

6O

7-15

4o

June

20

15-23

Trout Chor

0

0-3.

July *u9 Sept eorly Ocl

3-7. 7-15 15-23.

loo80 'O

40 20

0

Daily ration rng dw/g wet w

I

=

=

6.5 mg/g 1.5 mg/g

July Trout Char

= 14 = 2.3

mg/g mg/g

Sept Trout = 2 mg/g Chor = 1.6 rng/g

100

0-3 3-7 7-15

October

15-23

20

10

0

10

20

Trout Char

= =

1.4 mg/g 1.0 mg/g

CPUE

Trout

Char

Fig. 9. (a) Catch per unit effort of trout and charr at different depths and at different t i e s of the year; from Ref. [561. (b) Food preferences of trout and charr at different times of the year: 1. Zooplankton; 2. Molluscs; 3. Surface insects; 4. Chironomid zoobenthos; 5. Other zoobenthos;from Ref. [561.

which did not feed over much of the winter and lost radiocaesium during this period. In addition, as a result of the habitat temperature difference trout excreted radioactivity faster than charr. Hence charr lost activity much slower than trout so that by 1988 the concentrations in both fish were at similar levels. 6. CONCLUSIONS

On the basis of these studies we can summarise the present status of our knowledge particularly for radiocaesium.

68

(1)Our understanding of caesium sorption processes is almost at an adequate level for our needs in the immediate future. (2)Simple understanding of the processes occurring in catchments is now available. (3)The main processes in transporting radionuclides in and from the water column are now generally recognised. (4) Complex multi trophic level models of biological uptake are possible but they require significant amounts of calibration. ( 5 ) Cellular and molecular models of biological uptake are only just beginning to make a contribution to the science. (6) The importance of fish ecology is only beginning to be incorporated into conceptual models of radionuclide uptake. From this standpoint we can now start to consider where research is likely to move over the next few years. There is likely to be a continuing move from the simple box, pseudo equilibrium, models of the past to process based dynamic models. The methods of study for caesium should be transferred to other nuclides in a systematic way. However, in moving to other nuclides, the speciation of elements in the water column becomes increasingly important as exemplified by Fig. 10 which shows a schematic representation of the distribution of ruthenium species in water. Ruthenium exists in at least four different species in water and each species will independently sorb to particles with different Kds (assuming trace concentrations are present). Once sorbed the different species will have different rates of fixation within the solid matrix. If this is not taken

Fig. 10. A schematic representation of the speciation of Ru in water and its effect on Kd.

69

into account and global mean values for equilibrium and kinetic parameters such as Kd are used then the results will not be transferable from, and comparable with results from, systems with different water chemistry. With specific application to caesium there is still a small amount of work left on caesium sorption but this is mainly related to the kinetics of fixation, particularly the influence of water chemistry. Other aspects which would repay extra work would be the relationship of frayed edge site concentrations as a function of particle size and the effects of humics both directly and indirectly on the sorption at frayed edge sites. Further work is still required to define more clearly the parameters in catchment transfer models in particular in peat bogs where radiocaesium sorption is not dominated by frayed edge sites [57]. A little further work is still required to obtain good estimates of some basic water process parameters in particular the boundary layer and settling velocities. In addition expert systems are required to define which processes are important in which lake and river system. Work on cellular and molecular processes of radionuclide uptake by biological systems must be viewed on a much longer time scale but needs to be continued in order to obtain parameterisation of models from more fundamental and less variable parameters. In particular the importance of speciation in relation to the concentration of free ions should be included in models and further study is required of active transfer processes and excretion processes which create variations in the biological half life with both temperature and water chemistry. Almost no work has been done to date on molecular processes of transport across the gut wall. Ecological aspects need further study, particularly the effects of growth, metabolic rate and living conditions and the differences in radionuclide concentration factors between species in the same lake. These need to be incorporated into expert system based models to aid modellers in their estimations of T Nand uptake rates. MOOEL HYPOTHCSIS

I

$FW-' EXPERIMENT

LABORAlORl

EXPERIMENT

I

MONIIORING

u

MODEL TESTING

Fig. 11. The cycle of field measurements, laboratory measurements and model predictions required to refine our understanding of radioecology.

70

The development of knowledge in all ecological fields is based on a cycle (Fig.

11)beginningwith field measurementswhich allow us to form a hypothesis, which

is tested by obtaining more detailed data, initially in the laboratory.This,in turn, allows us to refine our hypothesis and then test model predictions against data from the natural environment. Future studies in radioecology will continue to require both field and laboratory studies to improve our understanding. 7. REFERENCES

1. Evans, D.W., J.J. Alberts and R.A. Clark, 1983. Reversible ion-exchange fixation of cesium-137 leading to mobilisation from reservoir sediments. Geochim. Cosmochim. Acta, 47: 1041-1049. 2. Brouwer E., B. Baeyens, A. Maes and A. Cremers, 1983. Cesium and rubidium ion equilibria in illite clay. J. Phys. Chem., 87: 1213-1219. 3. De Preter, P., 1990. Radiocaesium retention in the aquatic, terrestrial and urban environment: a quantitative and unifylng analysis. Ph.D thesis. Katholieke Universiteit, Leuven. 4. Cremers, A., A. Elsen, P.M. De Prater and A. Maes, 1988. Quantitative analysis of radiocaesium retention in soils. Nature, 335: 247-9. 5. Comans, R.N.J., J.J. Middleburg, J. Zonderhuis, R.J.W. Woittiez, G.J. DeLange, A.K. Das and C.H. Van der Weijden, 1989. Mobilisation of radiocaesium in pore water of lake sediments. Nature, 339: 367-369. 6. Comans R.N.J., M. Haller and P. De Preter, 1991. Sorption of cesium on illite: non-equilibrium behaviour and reversibility. Geochim. Cosmochim. Acta, 55: 433440. 7. Comans R.N.J. and D.E. Hockley, 1992. Kinetics of caesium sorption on illite. Geochem. Cosmochim. Acta, 56: 1157-1164. 8. Konoplev, A.V., A.A. Bulgakov, R. Comans, J. Hilton and V.E. Popov, 1997. Kinetics of 134Csimmobilisation by soils. In: G. Desmet et al., Freshwater and Estuarine Radioecology. Elsevier, Amsterdam, p. 173. 9. Madruga, M.J.B., 1993. Adsorption-desorption behaviour of radiocaesium and radiostrontium in sediments. PhD thesis. Katholieke Universiteit Leuven, 10. Spezzano, P., J. Hilton, J.P. Lishman and T.R. Carrick, 1993: The variability of Chernobyl Cs retention in the Water column of lakes in the English Lake District, two years and four years aRer deposition. J. Env. Radioactivity, 19: 213-232. 11. Hilton, J., F. Livens, P. Spezzano, and P. Leonard, 1993. The retention of radioactive caesium by different soils in the catchment of a small lake. Sci. Tot. Environ., 129: 253-266. 12 Carlsson S., 1978. A model for the movement and loss of Cs-137 in a small watershed. Health Physics, 34: 33-37. 13. Tipping, E., C. Woof, M. Kelly, K. Bradshaw and J.E. Rowe, 1994. Radio CHUM modelling radionuclides in upland catchments. Report to Ministry of Agriculture, Fisheries and Food. 14. Konoplev A.V. and Ts.1. Bobovnikova, 1990. Comparative analysis of chemical forms of long-lived radionuclides and their migration and transformation in the environment following the Kyshtyrn and Chernobyl Accidents. Proceedings of Seminar on Comparative Assessment of the Environmental Impact of Radionu-

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15. 16. 17. 18. 19. 20. 2 1. 22. 23.

24.

25. 26. 27. 28. 29.

clides Released during Three Major Nuclear Accidents: Kyshtym, Windscale, Chernobyl. Luxembourg, 1-5 October 1990, Commission of the European Community, Radiation Protection 53, EUR 13574. Vol. 1, pp. 371-396. Bulgakov A.A., A.V. Konoplev, V.E. Popov and A.V.Scherbak, 1991. Removal of long-lived radionuclides from the soil by surface run-off near the Chernobyl nuclear power station. Soviet Soil Sci., 23: 124-131. Smith, D.D., 1978. Predicting rainfall erosion losses a guide to conservation planning. Agric. Handb. 537 USDA-SEA in cooperation with Purdue Agric. Exp. Stn. Vanderploeg HA DC Parzyck WH Wilcox. Hesslein, R.H., W.S. Broecker and D.W. Schindler, 1980. Fates of metal radiotracers added to a whole lake: sediment-water interactions. Can. J. Fish Aquat. Sci., 37: 378-386, Hilton, J., W. Davison, J. Hamilton-Taylor, M. Kelly, F. Livens, E. Rigg and D.L. Singleton, 1994. Similarities in the behaviour of Chernobyl derived Ru-103, Ru106 and Cs-137 in two freshwater lakes. Aquatic Sci., 56 (2): 133-144. Robbins, J.A., G. Lindner, W. Pfieffer, J. Kleiner, H.H. Stabel and P. Frezel, 1992. Epilimnetic scavenging of Chernobyl radionuclides in Lake Constance. Geochim. Cosmchim. Acta, 50: 2339-2361. Santschi, P.H., P. Bower, U.P. NyfTeler, A. Azevedo and W.S. Broecker, 1983. Estimates of the resistance to chemical transport posed by the deep sea boundary layer. Limnol. Oceanogr., 28: 899-912. Li, Y. and S. Gregory, 1974. Diffusion of ions in sea water and in deep sea sediments. Geochim. Cosmochim. Acta, 38: 703-714. House W.A., F.H. Denison, J.T. Smith, P.D. Armitage, 1994. An investigation of the effects of water velocity on inorganic phosphorous influx to a sediment. J. Environ. Pollut., 89: 263-271. Zeleznyak, M.J. and O.V. Voitsekhovich, 1991. Mathematical modelling of radionuclide dispersion in surface waters afier the Chernobyl accident to evaluate the effectiveness of water protection measures. Proceedings of Seminar on Comparative Assessment of the Environmental Impact of Radionuclides Released during Three Major Nuclear Accidents: Kyshtym, Windscale, Chernobyl. Luxembourg, 15 October 1990, Commission of the European Community, Radiation Protection 53, EUR 13574. Vol. 2, pp. 725-748. Davison, W., J. Hilton, J. Hamilton-Taylor, M. Kelly, F. Livens, E. Rigg, T.R. Carrick and D.L. Singleton, 1992. The transport of Chernobyl-derived radio-caesium through two freshwater lakes in Cumbria, UK. J. Environ. Radioactivity, 19: 125-153. Thomman, R.V., 1981. Equilibrium model of fate of microcontaminants in diverse aquatic food chains. Can. J. Fish Aquatic Sci., 38: 280-296. Aoyama, I., Y. Inoue and Y. Inoue, 1978. Simulation analysis of the concentration process of heavy metals by aquatic organisms from the viewpoint of nutrition ecology. Water Res., 12: 837-842. Corisco, J.A.G. and M.C.V. Carreiro, 1992. Modalites de concentration du crustace planctonique Daphnia magna Straus avec le Cs-134. Etudes de la fixation et de la retention. Rev. Sci. l'Eau, 5: 381-397. Baudin, J.P., 1981. Budget for zinc-65 absorbed through the trophic chain in Anguilla anguilla L. Ann. Limnol., 17: 181-192. Baudin, J.P., 1982. Bioaccumulation and elimination of Zn-66 by Gammarus aequicauda Martimov. Mar. Environ. Res., 7: 227-233.

72 30. Baudin, J.P., 1983. Experimental study of bioaccumulation and excretion of Zn-65 by freshwater fish, Cyprinus carpio L. Acta Oecol. Oecol. Appl., 4: 139-149. 31. Baudin, J.P., 1985. Accumulation of 211-65 simultaneuosly directly from water and via the trophic chain by Cyprinus carpio L. (Pisces, Cyprinidae). Acta, Oecol. Oecol. Appl., 6: 259-268. 32. Baudin, J.P., 1987. Investigation into the retention of Zn-65 absorbed by the trophic pathway in Cyprinus Carpio L. Influence of the ingestion frequency and the radiozinc content of the food. Water Res., 21: 285-294. 33. Baudin, J.P. and A.F. Fritsch, 1987. Retention of ingested CO-60by a freshwater fish. Water, Air Soil Pollut., 36: 207-217. 34. Baudin, J.P and A.F. Fritsch, 1989. Relative contributions of food and water in the accumulation of CO-60by a freshwater fish. Water Res., 23: 817-823. 35. Baudin, J.P., A.F. Fritsch and J. George, 1990. Influence of labelled food type on the accumulation and retention of co-60 by a freshwater fish, Cyprinus carpio L. Water Air Soil Pollut., 51: 261-270. 36. Baudin, J.P. and R. Nucho, 1992. CO-60accumulation from sediment and planktonic algae by midge larvae (Chironornusluridus). Environ. Pollut., 76: 133-140. 37. Pally, M., J.P. Baudin, A.F. Fritsch, A. Lambrechts and A. Maurel-Kermarrec, 1986. Study of the chemical forms of co-60 during various experiments of transfer between water and aquatic organisms. Sci. Eau, 5: 273-290. 38. Nucho, R., and J.P. Baudin, 1986. Experimental data on CO-60retention by a planktonic alga, Scenedesmus obliquus. The influence of temperature and photoperiod. Sci. Eau, 5 361-376. 39. Nucho, R., and J.P. Baudin, 1989. (30-60 retention by a planktonic alga, Scenedesmus obliquus. Environ. Pollut., 62: 265-279. 40. Nucho, R., A. Rambaud, L. Foulquier and J.P. Baudin, 1988. Bioaccumulation of (20-60 by a planktonic alga, Scenedesmus obliquus Tuerps. (Kuetz). Influence of developmental stage of the culture on radionuclide fixation. Acta Oecol. Oecol. Appl., 9: 111-125. 41. Foulquier, F., J.P. Baudin and A. Lembrechts, 1989. Data on Cs-137 and CO-60 transfer in a river system: the Rhone. Rev. Sci. Eau, 2: 641-658, 42. Garnier, J., and J.P. Baudin, 1989.Accumulation and depuration of Ag-llOm by a planktonic alga, Scenedesmus obliquus. Water Air Soil Pollut., 45: 287-299. 43. Gamier, J., and J.P. Baudin, 1990. Retention ofingested Ag-llOm by a freshwater fish, Salmo Trutta L. Water Air Soil Pollut., 50: 409-421. 44. Garnier, J. and J.P. Baudin, 1992. Retention of ingested Ag-llOm by a freshwater fish, Salmo trutta L. Water, Air and Soil Pollut., 50: 409-421. 45. Gamier, J., J.P. Baudin and L. Foulquier, 1992. Accumulation from water and depuration of Ag-llOm by a freshwater fish, Salmo trutta L. Water Res., 24: 1407-1414. 46. Garnier, J., J.P. Baudin and L. Foulquier, 1992. Experimental study of Ag-llOm transfer from sediment to biota in a simplified freshwater ecosystem. In: B.T. Hart and P.G. Sly (eds.), Sediment Water Interactions. Vols. 235-236, pp. 393406. 47. Gamier-Laplace, J., J.P. Baudin and L. Foulquier, 1992. Experimental study of Ag-llOm transfer from sediment to biota in a simplified freshwater eco system. Hydrobiologia, 235 (6): 393-406. 48. Vray, F., J.P. Baudin and M. Svadlenkova, 1992. Effects of some factors on uptake and release of Ru-106 by a freshwater moss, Plathypnidium riparioides. Arch. Environ. Contam. Toxicol., 23: 190-197.

73 49. Fernandez, J.A., M.A. Heredia, M.J. Garcia-Sanchez, J.A. Gil, M.C. Vaz Carreiro and A. Diez de 10s Rios, 1994. Mechanisms of radiocaesium uptake and accumulation in Riccia fluitans. ibid. 50. Sanders, D., A. Corzo and J.A. Fernandez. Mechanism of potassium uptake in Riccia fluitans submitted to potassium deficiency. in press. 51. Vanderpleogh, H.A., D.C. Parzyck, W.H. Wilcox, J.R. Kercher and S.V. Kaye, 1975. Bioaccumulation factors for radionuclides in freshwater biota. 0.R.N.L.-5002.Nov. 1975,216 pp. 52. Karara, A.H. and V.A.McFarland., 1992. A pharmacokinetic analysis ofthe uptake of polychlorinated biphynyls (PCBs) by golden shiners. Environ. Toxicol. Chem., 11: 315-320. 53. Comhaire, S., R. Blust, L. Van Ginneken and 0. Vanderborght, 1994. Cobalt uptake across the gills of the common carp, Cyprinus carpio, as a function of calcium concentration in the water of acclimation and exposure. Comp. Biochem. Physiol. in press. 54. Blust, R., L. Van Ginneken, S. Commaire and 0. Vanderborght, 1994. Uptake of radio-cobalt by the common carp, Cyprinus carpio, in complexing environments. Sci. Total Environ. in press. 55. Comhaire, S., R. Blust, L. Van Ginneken, F. D’Haeseleer and 0. Vanderborght, 1994. Environmental calcium influences radio-cobalt uptake by the common carp, Cyprinus carpio. Sci. Tot. Environ. in press. 56. Forseth, T., 0. Ugedal, B. Jonsson, A. Langeland and 0. Njastad, 1991. Radiocaesium turnover in Arctic char (Silualinus Alpinus) and brown trout (Salmo trutta) in a Norwegian lake. J. Appl. Ecol., 28: 1053-1067. 57. Valke, E., 1994. The behaviour dynamics of radiocesium and radiostrontium in soils rich in organic matter. PhD thesis, University of Leuven.

Freshwurer und Estuarine Rudioeecoloxy '

Edited by G . Desmet et d. 1997 Elsevier Science B.V.

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Present thoughts on the aquatic countermeasures applied to regions of the Dnieper river catchment contaminated by the 1986 Chernobyl accident 0.Voitsekhovitcha,0. Nasvita, I. Los'yb, V. Berkovskyb aUkrainian Ministry of Chernobyl w a i r s , 8 Lvovskaya Sq., UA-254655, Kiev, Ukraine bUkrainian Centre of Radiation Medicine, 53 Melnikov St., UA-252050, Kiev, Ukraine.

ABSTRACT The results of radiation monitoring data and migration pathway analysis of water bodies within areas that were affected by the 1986 Chernobyl accident can provide the unique opportunity for decision-makers who are working in other extensively contaminated regions to optimize their approaches to surface- and ground-water protection. Most engineering measures inside the Chernobyl30 km exclusion zone were focused on prevention of secondary contamination of surface and ground water from entering the Pripyat River and the Kiev Reservoir. However, these measures required huge financial and human resources for their implementation. Therefore, lessons can be learned from the Chernobyl example concerning the post-accidental water-protective activities.

1. INTRODUCTION

Numerous studies have described the extensive radioactive contamination of large regions of Ukraine, Belarus, Russia and parts of western Europe that resulted from the 1986 Chernobyl accident at Reactor no. 4. Most radioactive atmospheric fall-out was deposited within the Dnieper River drainage basin adjacent to the Chernobyl Nuclear Power Plant (Ch.NPP) site. This and adjacent drainage basins form an extensive area from which contaminated run-off flows downstream through the Pripyat and Dnieper River systems across the Ukraine to the Black Sea [1,2]. Subsequent to the Chernobyl accident, overland flow across the contaminated landscapes continues to be a major'factor in radionuclide transport (Fig. 1). This flow contributes to the diverse migration pathways by which radionuclides are transported from the Chernobyl area to the greater Dnieper region in which more than 20 million people live. Of these, about 9 million people

76

I

Ir

I

01.86

01.87

01.88

01.89

- %r soluble;

01.90

01.91

01.92

01.93

01.94

- - - - 13'Cs soluble; -13%2ssuspended

01.95

~

Fig. 1. Radionuclide concentration (pCi 1-'1 in time changing (1986-1995) in the Pripyat River flow near the Chernobyl from UkrHMI data collection (1 = '%r in solution; 2 = 137 Cs in suspended part; 3 = 137 Cs in solution).

consume drinking water from the reservoirs and the rest one consume fish from the reservoirs or eat agricultural products irrigated by water from the reservoirs. Hence this problem is very important t o the population. Regional surfaceand ground-water pathways have been studied in order to better understand how contaminants are spreading across the landscape into relatively uncontaminated areas and how to better protect water resources. These studies were carried out to support a risk assessment for individuals living along the Dnieper River and/or consuming water and foodstuffs produced by water from the Dnieper catchment basin. 2. THE PRESENT STATE OF RADIOACTNE CONTAMINATION WITHIN THE DNIEPER RIVER SYSTEM

Between 1986 and 1994,surface run-off and other water-exchange processes dispersed contaminants from the Chernobyl accident within the Dnieper River drainage basin. Data collected by the Ukrainian Hydrometeorological Institute from the Pripyat River illustrate the time history of Sr-90and Cs-137in the reservoirs of the Dnieper cascade [3].These data demonstrate (see also Fig. 1) a close relationship of Sr-90concentration in the river with river flow levels. Riverine concentrations of Cs-137are less dependent on surface hydrology. This differingnature of radionuclide transport depends on soil properties and soil-contaminant interactions. Peaks in fluvial Sr-90contamination levels

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correspond most directly with inundation of flood plains within a 5-10 km radius of the Ch.NPP [41. The high radioactivity in soils of this flood plain remains a major source of secondary contamination in the Dnieper aquatic system. Moving downstream to the series of reservoirs along the Dnieper River, most Cs-137 from the Chernobyl accident has accumulated in the bottom sediments of the Kiev Reservoir (Fig. 1).In contrast, most dissolved Sr-90 (4040%) remains in solution and passes through the Dnieper's reservoirs without a significant drop in concentration. As a result of sedimentation, bioaccumulation, and adsorption, only 2-5% of the Cs-137 that enters the Dnieper through surface run-off reaches the Black Sea. 3. SCENARIO SIMULATION

The years that followed the 1986 accident were not typical in their precipitation and surface run-off conditions. The observed water discharge during the 1994 spring floods did not exceed 2100 m3 s-' (the maximum, observed in 1979 was about 5000 m3 d ) . The probability that water levels in the Pripyat river could exceed those observed in the 1994 spring water discharge was less than 40%. However, even during this relatively small event, most of the contaminated low-level lands on the flood plain near the Ch.NPP were flooded, releasing washed-out radioactivity to the river. With these observations in mind, possible future contamination levels within the Dnieper Cascade have been predicted, based on a probabilistic hydrological and physico-chemical scenario incorporating processes which could occur on the contaminated areas. Some results of the simulation are presented in Ref. [51 and show that without water protection measures, Sr-90 could exceed its maximum permissible level allowed in the Ukraine for drinking water (4Bq 1-l). On the basis of similar data, a decision had already been taken in 1992 to reduce the radionuclides transported by rivers from the close-in zone to other areas. 4. ASSESSMENT OF WATER-PROTECTION COUNTERMEASURES

The water protection and remediation efforts at the Ch.NPP site have a dramatic history that should be assessed in view of possible lessons to be learned. Since the accident, engineering and administrative countermeasures have been implemented. They were directed towards the limitation of the aquatic component of radiation exposure for the population that resides along the Dnieper reservoir system downstream of the Chernobyl area. Most of the executed countermeasures have been very expensive and limited in their success in reducing the radiation risk to the public from water usage. The history of water protection countermeasures can be split into three phases, as described below.

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4.1. Emergency phase (early post-accident, i.e. 2-3 months after the event)

For 2-3 three months after the accident, short-lived radionuclides, such as Ba-140, Ce-144, Ru-103, 106, Nb-95,Zr-95, formed a significant component of the radiation dose to local residents from hydrologic sources. This contrasts with the present time in which Cs-137 and Sr-90 dominate the radiological hazard. Countermeasures during this period were based mainly on administrative decisions and had the major intent of controlling the situation. These countermeasures included: 1 attempts to regulate the flow of contaminated water through the Kiev reservoir using the dam operating system; 2. increased use of ground-water sources for municipalities and, whenever possible, less use of the contaminated surface water resource; 3. supplementary purification of drinking water in municipal water treatment plants; and 4. construction of supplementary ground-water supply wells. In those early days the decision makers were inexperienced in dealing with such a novel catastrophe and even knowledgable scientists lacked a clear understanding of the processes of radionuclide transport processes in the environment. In particular the mobility of radionuclides was grossly overestimated. This resulted from an assumption that the majority of the radionuclides were in mobile forms rather than, as was discovered later, in either hot particles o r fmed t o soil particles which significantly reduced their capacity t o migrate. As a result, a number of very expensive, but useless measures were introduced in the first months to counter this assumed threat. During early May 1986 surface gates were opened and bottom gates closed on the dams of the Kiev Reservoir. It was thought that clean water was being let out of the reservoir so that the highly contaminated surface runoff water from spring rains could be captured in the reservoir. In reality, the lower water layers of the reservoir were much less contaminated than the upper zones because of atmospheric fall-out. A better approach to lowering the water level within the Kiev Reservoir immediately after the accident would have been to open the bottom dam gates and to close the surface gates. This would have reduced the levels of radioactivity in downstream drinking water in the first weeks after the accident. Another administrative decision during this period was to transfer water intake for the Kiev municipal water supply from the Dnieper River to the Desna River. Data suggests that, in this period immediately after the accident, levels of radioactive contamination of the Desna River were at higher levels than those of the lower Dnieper River below the Kiev Reservoir. This is yet another example of lack of information when making important administrative decisions under emergency conditions.

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4.2. Early intermediate phase (Summer 1986 to 1988)

In the summer of 1986, several kilometres of protective dikes were constructed along the Pripyat River to catch the contaminated urban runoff from the cities of Chernobyl and Pripyat. These countermeasures were not effective since run-offfrom the broad landscapes could not be readily controlled. Several special canal-bed traps were dredged along contaminated rivers to retain suspended radioactive sediment. However, subsequent studies indicated that these traps were ineffective in trapping the fine-grained, suspended radioactive sediment from the rivers. In the six years following construction of the traps, 1988 to 1994, the traps became choked with sediment but accumulated less than 10% of the suspended radioactive sediments [6]. During the early period of this second phase a special drainage system was built around the Ch.NPP cooling pond with the aim of catching infiltrating radioactive water. Up to the present, the drainage system has not been operated because of uncertainty in the consequences of its operation. As a result the costs of its construction and maintenance in a state of readiness have been an expensive error. Other examples of post-accident measures affecting transport in to the ground water and isolation of radionuclides released from Chernobyl have been described by Waters et al. [61. During this phase, an underground clay barrier was constructed between Reactor no. 4 and the Pripyat River. This barrier was to prevent migration of contaminated shallow ground water into the river. However, the reduction of migration towards the river was only localized and caused local elevated ground-water levels in the vicinity of Reactor no. 4. During 1986 and early 1987, more than 100 special zeolite-containing dikes were completed, with the objective of adsorbing radionuclides from smaller rivers and streams. Subsequent studies of the effectiveness of these dikes in capturing radionuclides from the stream flow indicated that only 5% to 10% of the entrained Sr-90 and Cs-137 was adsorbed by the zeolite barriers within the dams. Irrespective of the low adsorption ability of the dams, the flow in the larger rivers constituted a much bigger problem. The streams that were dammed during this procedure contributed only a few percent to the total radionuclide flux from the Pripyat and Dnieper drainage basins. In 1987, the construction of new dams was stopped and it was decided to destroy most of the existing dams. In 1987, the highly contaminated “Red Forest”, about 5 km from Reactor no. 4, was felled and buried. The decision to deal with the Red Forest in this manner so soon after the accident exposed many workers to extreme levels of radiation. Because of the necessity to work quickly, the cut trees of the forest were buried in shallow landfills and trenches without liners to prevent contamination of the ground water. As a result, intense local ground-water contamination from these buried trees poses a large, long-term problem for environmental remediation and restoration [1,61.

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4.3. Later intermediate phase (1988 to 1991)

A new phase of hydrologic remediation was begun afier the summer flood of 1988. High water levels covered much of the contaminated flood plain and introduced secondary Sr-90 contamination into the river systems 141. Surface hydrologic modelling indicated that a realistic, more dangerous or “worst-case” scenario, when the highest radionuclide concentration to be caused in rivers, would be a spring flood with a maximum discharge of 2000 m3 s-l, (i.e. a flood with a 25% chance of being exceeded). Initial estimates suggested that the increase of Sr-90 in waters downstream of the considered areas could reach up to 10 Bq 1-’, exceeding permissible sanitary level for Sr-90 in waters (4 Bq 1-’1. However, when flood plain wash-out processes, measured on isolated areas of radioactive soil, were included in simulations, the Sr-90 concentration decreased 2-4-fold. Several approaches for reducing radionuclide concentration in the river were proposed, and the potential effectiveness of each was simulated. Creation of dykes around the contaminated area on left (east) bank of the river was chosen as the best option. This measure, supplemented by decontamination of soils on the right bank (or their protection by another dyke), and by the identification of an acceptable solution to the seepage of water from the cooling-pondcould further diminish the Sr-90 concentration at the downstream boundary. A comparison of the effects of flood plain flooding in January 1991 and in summer 1993 has confirmed the validity of the simulated results. Construction of the dyke was finished at the end of 1992. This action is estimated to have prevented the washout into the Dnieper reservoirs of more than 3.7 x 10” Bq of Sr-90 in the spring floods of 1994. 5 . PRESENT UNDERSTANDING OF THE PROBLEM

As a result of the Chernobyl accident a huge amount of radioactive material is still retained in the catchment soils and the water and bottom sediments of lakes in the region, particularly the cooling pond. An impression of the scale of the problem can be obtained from a realisation that the flood plain soils and polder areas of the 30 km zone, which have a 5050 chance of being flooded each year in the spring floods, contain more than 3.7 x 1014Bq Sr-90 and 7.4 x 10” Bq Pu. In addition a huge amount of radioactive waste from contaminated natural materials is located in shallow underground waste disposal sites which are in contact with groundwater flowing towards the Pripyat river. The details of the potential secondary sources of aquatic contaminants are given by Voitsekhovitch et al. [1,21 and Zheleznyak et al. [5]. A significant finding of the first stage of water protection in the Chernobyl site was that the technological possibilities to control an existing source of radioactive contamination on such a large catchment scale are very limited. It became clear that optimizationof any water protection actions can be achieved only by compar-

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Fig. 2. Measured and predicted 3 r concentration in the Dnieper reservoirs (taken from Ref. I51).

ing the reduction in the actual human doses, that would result from any proposed engineering activities in the Chernobyl site [3,41. To this end a large amount of work has been carried out to provide a basis for the risk assessment and cost-benefit analyses required for the next stage of aquatic countermeasures [7]. Estimates of the potential committed collective doses from Sr-90 and Cs-137 to the population of the Dnieper's regions, integrated over 70 years, were calculated from previous data [7,9] and the results of the selected scenario of predicted radionuclide content in the Dnieper water up to the year 2056 (Fig. 2). The contributions of the different sources to the committed dose from water usage, accumulated over 70 years and averaged over all water consumers living

Redloactivity

Rad loactivity

Rad oactivity

Radnacrivity

of food

of drinhg

of urigated

of f s h from

products

water

product3

Dnieper

Fig. 3. Partial contribution of %r and '37Cs components by different elements of food chain pathways to averaged individual effective dose for Kiev citizens. Scenario, 1993.

82

I - %

34.07

1 35 30~

1 1

5

-

033

006

I

2

3

4

5

6

7

8

9

to

I I

Fig. 4. Aquatic component contribution of annual individual effective dose for peoples, living in different regions of Ukraine due to water usage from Dnieper's reservoirs.Scenario 1993. 1 = Chernigov reg.; 2 = Kiev reg.; 3 = Kiev city; 4 = Cherkassy reg.; 5 = Poltava reg.; 6 = Kirovograd reg.;7 = Dniepropetrovsk reg.;8 = Zaporozhiereg.;9 = Kherson city; 10 = Mikolaev city; 11 = Crimea republic.

along the Dnieper approximately were 35% from drinking water, 40% from fish and 25% from irrigation products. Estimates for doses obtained via water from Sr-90and Cs-137in 1993 (Fig. 3) show that the Cs-137component in to the total averaged individual expected dose is negligible (2%), compared with the dose contributed by Sr-90.These studies also show that the annual average individual effective internal doses for the different regions of Ukraine are very varied and actual proportions are very different in the different affected regions (Fig. 4). For instance, in 1993 the water pathway contribution to the total radiation dose for a Kiev citizen was about 6% but increased up to 2040% for people living in the southern region of Ukraine. 6. RADIATION RISK ASSESSMENT

Using the nominal probability coefficient of 7.3 x lo-' Sv-' [8]the number of stochastic cancer effects due to Dnieper water usage over a period of 70 years was estimated. Estimates were about 200 cancer cases out of 21 million people for a 70 years exposure period and about 60 cases for the exposure period 1986-1992. Recalculation of the dose value for the total exposed population (about 21 million), suggests that the averaged individual human radiation risk from Dnieper water use cannot be greater than lod. For some critical groups of water users the expected individual risk would be at least 4-5 times higher. Implementation of the most effective water protection countermeasures from those proposed above could reduce the assessed radiation risk from water usage by a maximum of 3-4 times. In fact the level of radiation risk to health of the population is very low compared with other sources of radiation. However, the effect of stress resulting from the psychological reaction of the population to consuming radioactive contaminated water, can exceed the effect

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of the pure dose component. In our study more than 30% of the people interviewed, covering a range of different educational levels, felt that the actual risk to their health was greater from water consumption than from other exposure pathways. In reality the averaged individual effective dose from natural radionuclides like Rn-226, Rn-222 and U-238 in the drinking water of the above regions is 0.17 m Sv year-' and can even reach 10 m Sv year-' for some districts, i.e. two orders of magnitude greater than post-Chernobyl risk component. 6.1. The problem

Unfortunately, at the present time, there is no clear theory or methods for the estimation of total and partial risk from using water which is contaminated by multiple pollutants. This is a major limitation since all the Dnieper reservoirs are situated in industrial and agricultural areas contributing high levels of non-radioactive pollutants. Toxicological investigations showed the presence in reservoir water of a number of non-radioactive toxic substances with strong carcinogenic and mutagenic properties. In many cases the origin of these toxic substances is unknown or they originate from uncontrolled effluents. As a result it is very difficult to immediately identify countermeasures for water protection. However, in a case such as the Chernobyl accident, when the source of water contamination is known, active intervention to protect water is preferable to non-intervention even though it is not possible to rank the importance of the industrial pollutants compared to the radioactive Chernobyl releases. 7. CONCLUSIONS AND RECOMMENDATIONS

7.1 Strategy for the next phase of water protection in the Chernobyl site

The Chernobyl close-in zone and the neighbouring catchment areas polluted by radioactivity are, and will remain both actual, and long-term potential, sources of secondary contamination of (a) ground water inside the Chernobyl close-in zone; (b) surface river waters crossing the area, and (c) the Dnieper reservoirs. As a result the radionuclide impact on the population of the 10 regions of Ukraine resulting from the Dnieper aquatic system will continue. The primary objectives for water projection should be: - to provide a safe water supply for people working inside the Chernobyl area; - to provide safe water for use by the present and future generations of people, living along the Dnieper river system; - to provide a safe environment for aquatic life in the areas influenced by Chernobyl. The immediate tasks for the present situation are:

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- t o reduce to a minimum any expansion of the accident area by controlling and minimizing the transport of radionuclides by surface and ground waters to regions outside the Chernobyl area; - to develop a radioactive monitoring system for ground and surface water inside and beyond the Chernobyl area. The immediate tasks for the long-term perspective are: - to reduce the likelihood of transport from the relatively localised sources (created by radioactive waste disposal sites) into the diffise sources. The problem was brought about by raised ground water levels caused by the previous construction of the engineering and geochemical barriers t o ground water movement; - to provide reliable monitoring and control of transuranic material transport by ground and surface waters beyond its present boundaries. 7.2.Decision-making criteria

The main monitoring point for decision making is the Pripyat river below the Chernobyl city cross-section, upstream of the confluence with the Dnieper river. The main radionuclides requiring control for water protection are Sr-90 in the short term and transuranic elements in the long term. The maximum levels of Sr-90activity acceptable as an intervention level criteria in the aquatic system at different distances from Chernobyl area are: Pripyat river (Chernobyl) 2 Bq 1-’; Kiev reservoir (operation dam) 1 Bq 1-’; Dnieper water intake (Kiev) 0.8 Bq 1-’; Kakhovka reservoir 0.25 Bq 1-’. As a result of water protective countermeasures, Sr-90activity levels are unlikely to exceed these limits. 7.3. The present engineering perspective on water protection

No countermeasure should be implemented without real benefits occurring, consistent with the well known “ALARA”(As Low As Reasonably Achievable) principle. In 1993,the following prioritised list of engineering schemes for water protective countermeasures was developed, based on this principle. 1. To build dykes to reduce the likelihood of flooding on the highly contaminated left and right banks of the flood plain close to the Reactor no. 4. 2. To solve the complex problem of cleaning up the bottom sediments in the existing cooling pond after the shutdown of the Chernobyl reactors and provide safe operation of NPP using water from cooling pond. 3. Following an accepted concept developed in Belarus, to provide water level regulation in the very highly contaminated wetlands of the Chernobyl site in order to keep peat bog areas flooded and reduce the potential risk of fire. 4. To provide an expanded ground water monitoring system inside the Chernobyl exclusive zone and around the existing temporary waste disposal site as an element of operating post-accidental decision support system for exclusion zone.

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5 . To prevent the significant spread of radionuclides beyond their present

localized waste disposal sites. Any other proposals directed towards water remediation presently being considered are unlikely to be effective and supporting funds are to be temporarily suspended. 8. ACKNOWLEDGEMENTS

This study was initiated and funded by the Ministry of Chernobyl Affairs of Ukraine. The authors wish to thank Dr S. Kazakov and E. Panacevitch from SPA “Pripyat” and also to Dr 0. Zvekov from Institute “Ukrwaterproject” for their continuous support and assistance in this study. We are also grateful to Ukrainian Hydrometeorological Institute for providing monitoring data. 9. REFERENCES

Voitsekhovitch, O.V., V.V. Kanivets, G.V. Laptev and I.Ya. Bilyi, 1992. Hydrological processes and their influence on radionuclide behavior and transport by surface water pathways as applied to water protection after Chernobyl accident. Proceedings UNESCO, Hydrological Impact of Nuclear Power Plant. 2. Voitsekhovitch, O.V., M.I. Zheleznyak and Y. Onishi, 1994. Chernobyl Nuclear accident: hydrologic analysis and emergency evaluation of radionuclide distributions in the Dnieper river, Ukraine during the 1993 summer flood. Report. Doc. PNL-9980, Contract DOE,USA, Battelle, June 1994, Washington. 96 pp. 3. Voitsekhovitch, O.V., 1993. On the concept of water protection measures against secondary contamination aRer Chernobyl accident. Trudy Ukr NIGMI, 245. 4. Laptev, G.V. and O.V. Voitsekhovitch, 1993. Experimental study of radionuclide wash-out from flood plain soils of Pripyat River during their flooding. Trudy Ukr NIGMI, 245 (in Russian) 5. Zheleznyak, M.I., O.V. Voitsekhovitch et al., 1991. Simulation of effectiveness of countermeasures designed to decrease radionuclide transport rate in the PripyatDnieper aquatic systems. Proceedings of the International Seminar “Intervention levels and countermeasures for nuclear accidents”, Cadarache. 6. Waters, R., D. Gibson, D. Bugay, S. Dzhepo, A. Skalsky and 0. Voitsekhovitch, 1994. A review of post-accident measures affecting transport and isolation of radionuclides released from the Chernobyl accident. In: Proc. of International Symposium on Environmental Contamination in the Central-Eastern Europe. Budapest. Hungry 1994. September, 19-24. 7. Berkovsky, V., G. Raia and 0. Nasvit (in press) Forming of internal doses to Ukrainian population as a consequence of using Dnieper water. Report on the Health Physics Society Meeting, June 24-28, 1994, San Francisco, USA. 10 pp. 8. International Commission on the Radiological Protection. Recommendations of the International Commission of Radiation Protection. ICRP Publication No. 60. Pergamon Press, New York, 195 pp. 9. Vakulovsky, S.M. and O.V. Voitsekhovitch, 1990. Radioactive contamination of water bodies in the area affected by releases from the Chernobyl Nuclear Power Plant accident. Proceedings “Environmental contamination following a major nuclear accident”. IAEA, pp. 231-246. 1.

Freshwuferund Esfuurine Rudioedogy Edited by G. Desmet et al. 0 1997 Elsevier Science B . V . All rights reserved

87

The characterization and retention of different transport phases of 137Cs and 90Srin three contrasting Nordic lakes John E. Brittaina, Helge E. Bjprrnstadb,Bjorn Sundblad’ and Ritva Saxend aFreshwater Ecology and Inland Fisheries Laboratory (LFI), University of Oslo, Sarsgt. 1, 0562 Oslo, Norway bLaboratory of Analytical Chemistry, Agricultural University of Norway, As, Norway (Present address: Norwegian Defence Research Establishment, Division of Environmental Toxicology, P.O. Box 25,2007 Kjeller, Norway) ‘Studsvik Ecology & Safety, 611 82 Nykoping, Sweden dFinnish Centre for Radiation and Nuclear Safety, P.O. Box 268, 00101 Helsinki, Finland

ABSTRACT The different transport phases of 137Csand ?3r in the inflowing and outflowing waters of three Nordic lakes, 0vre Heimdalsvatn in Norway, Hillesjon in Sweden and Saarisjarvi in Finland, have been studied using size fractionation techniques. Although all these lakes and their catchments received fallout from the Chernobyl accident, they differ markedly in hydrological regime, biological production and catchment characteristics, thus providing insight into the factors determining radionuclide transport in a range of lake types. Total daily inflows and outflows of wSrand 137Csduring the period of high discharge in spring are estimated and compared. Y3r is almost entirely present as low molecular weight forms in all three lakes, while 137Csis generally present a s both high and low molecular weight forms. In 0vre Heimdalsvatn and Saarisjarvi 42-53% of the inflowing 137Csis retained, while more I3’Cs flows out of Hillesjon than flows in, due to remobilization and resuspension. The difference between Hillesjon and the two other lakes also holds for T3r, although the retention in the two other lakes is lower (13431%). The increase in in the outflow of Hillesjon, probably due to remobilization from the sediments, is accounted for by low molecular weight species. The low molecular weight fraction of wSr is also the dominating transport phase in Saarisjarvi and 0vre Heimdalsvatn. There is also a remobilization of low molecular weight 137Cs in all three lakes. The potential bioavailability of the ultrafiltration fractions is also discussed.

88 1.INTRODUCTION

Fallout from the Chernobyl accident reached Finland, Sweden and Norway at the end of April 1986.Among the areas of high deposition (>70 kBq134+137Cs m") were localities in central southern Finland near Lammi, around the city of Gavle in Sweden and in the Jotunheimen mountains of central southern Norway [l]. Unfortunately, few analyses ofgoSrwere performed during 1986. Thus, both the deposition and the deposition pattern of this radionuclide is not known exactly. However, the deposition of wSr in the areas mentioned is assumed to be 1-5% of the total radiocaesium activity [21. Lakes in these areas have been the subject of several radioecological studies and thus formed a natural basis for the characterization of radionuclide inputs to Nordic lakes. Previous studies of the Norwegian subalpine lake, h e Heimdalsvatn, have shown the importance of inputs from the catchment for lake radionuclide dynamics [2,31.Size distribution patterns elucidated by fractionationtechniques and lake budget calculations have demonstrated the significanceof transport forms for the degree of retention in the lake system. On account of differences in the biological, chemical and physical characteristics of lakes and their catchments, transport form and mechanisms are likely to differ among freshwater systems. In order to identify transport mechanisms, the waters have been fractionated with respect t o particle size. Based on the input output budget, the fraction of radionuclides retained in the lake system can be estimated. Run-off during the spring snowmelt is an important pathway for radionuclide transport [4]. Therefore, during the spring snowmelt period of 1991 comparable investigations were carried out in 0vre Heimdalsvatn in Norway, Hillesjon in Sweden and Saarisjarvi in Finland. 2. SITE DESCRIPTIONS

A more detailed description of the location, chemistry, hydrology and catchments of the three study lakes is given in Ref. [5]. 2.1. 0 v r e Heimdalsvatn, Norway

The subalpine lake, 0vre Heimdalsvatn, is situated on the eastern edge of the Jotunheimen mountains in central southern Norway. This oligotrophic lake is poor in electrolytes and wind exposed. The mean depth is 4.7 m. The average renewal period for the lake varies considerably between a few days at the peak of the spring spate to a theoretical value of over 400 days during winter. The lake is ice-covered from mid-October until the beginning of June. The input of terrestrial plant (allochthonous) material from the catchment is of major importance as a source of organic matter for the lake 161. The deposition of Chernobyl 13'Cs was approximately 130 kBq m4.

89

2.2. Hillesjon, Sweden

The lake, Hillesjon, is situated north of the town of Gavle about 5 km from the eastern coast of central Sweden. Over 80%of the catchment is covered by forest; the remainder is agricultural land and marshes. The mean depth is only 1.7 m and during summer large areas of the lake become covered with aquatic macrophytes. Hillesjon is eutrophic and the lake is ice-covered between December and ApriV May. The deposition of Chernobyl 1 3 7 Cwas ~ approximately 100 kE3q m-’. 2.3. Saarisjarvi, Finland

Saarisjarvi is situated in the municipality of Lammi, Finland. About 75% of the catchment is forest, 15%bogs and marshes and 10%farm pasture. The lake is mesotrophic. The deposition of Chernobyl 13’Cs in the area was approximately 70 kBq m-’. 3. SAMPLING AND FRACTIONATION TECHNIQUES

Waters from the lakes, their inflows and outlet were collected during the spring of 1991. Material was collected from Hillesjon during the period 25 April to 8 May, from Saarisjslni 4 to 7 May and 0vre Heimdalsvatn from 24 May to 3 June. Discharge was measured directly, either using a current meter over a known profile or the salt dilution method 171. Cross-flow fractionation was carried out using three different ultrafiltration membranes, with the levels of 0.1 pm (Millipore VVLP) used as a prefilter, 10 kDa (Millipore PTGC) and 1 kDa (Novesett NS001005, Filtron, Mass., USA). The fractionation was not performed sequentially, but on aliquots of the total sample. In this paper, however, the 1 kDa fraction is not treated. The standardization of ultrafiltration membranes is usually carried out using globular proteins, or dextrans. The membranes used were specified according to globular proteins. As the components in natural water seldom have the spherical structure of globular proteins and differ in atomic composition (e.g. Si, Al, Fe) compared to organic calibration components (e.g. C, H, N), we prefer metric units. 10 kDa and 1 kDa correspond approximately to a Nominal Molecular Diameter (NMD) of 1.5 nm and 1.2 nm, respectively (Amicon publ. 426V, Amicon, MA, USA). However, as the lower limit for colloids is assumed to be between 1 and 5 nm [81, we find it appropriate to use the cut off of the 1.5 nm membrane to discriminate between high and low molecular fractions. Thus, in this comparative study we have chosen to group the fractions into two: a HMF fraction which describes all components associated with the radionuclide with NMD greater than 1.5 nm and a LMF fraction with NMD below 1.5 nm. However, care should be taken in assuming that this discriminates between elements in true “ionic solution” or not, as certain

90

complexes and molecules of both organic and inorganic origin are able to penetrate membranes with such pore diameters [91. For further details concerning fractions see [51. In the mass balance budget calculations for the lakes a state of hydrological equilibrium was assumed. This is a reasonable assumption as renewal periods are short and at a minimum during the spring. 4. SAMPLE PREPARATION AND MEASUREMENTS OF RADIO-ACTMTY

Total and fractionated samples (251) were collected and after adding carriers (20mg Cs and 30 mg Y per sample) and preservatives (2 ml HN03)/l sample) they were stored at 4°C in polyethylene containers until analysis and weighed accurately. Then the 25 1water samples were evaporated to 1 1and transferred to a Marinelli beaker (1 1) prior to gamma-spectrometry. Measurements were carried out at the Laboratory for Analytical Chemistry at the Agricultural University of Norway. The counting errors were in the order of 5% for wSr and 10%for 13'Cs. The limit for quantitative determination of radioactivity (LJ, 1.7 Bq (whole sample), was in accordance with [ 101. 4.1. Gamma-spectrometry

The evaporated water samples (1l), total and filtered water, were analyzed with respect to 137Csusing a Canberra Ge detector (20% efficiency and 2 keV resolution at 1332 keV) interfacing a PC equipped with the spectrum AT software manufactured by Canberra (Connecticut, USA). 4.2. Y3r determination

The content of ?3r in the samples was determined from analysis of '9 assuming radiological equilibrium between ?3r and 9,and no other high energyemitting radionuclides followed Y through the chemical separation 1111. ARer gamma spectrometry the water samples, total and filtered water were evaporated to dryness in a suitable ashing tray, and dry-ashed at 600°C for 12 h or overnight. Then the ash was dissolved in HCl, a Y-carrier added, the solution filtered and the pH adjusted to 1-1.2.9 was subsequently isolated by liquidliquid extraction using bis-(2-ethylhexyl>-hydrogen phosphate (HDEHP) in toluene [12].Then the 9 was back-extracted into 6 M HN03, precipitated as hydroxide, dissolved in diluted HCl and counted in a low-level scintillation spectrometer (Quantulus 1220,LKB, Wallac, Finland). The content of in the samples was then calculated from the Cerenkov-spectra of 9"y and the chemical yield determined by compleximetrictitration, based on the amount of Y-carrier added. The limit for quantitative determination of goSr-radioactivity (LJ,56 mBq (whole sample), was also here in accordance with Ref. [lo].

91

5. RESULTS AND DISCUSSION

The lakes studied represent a wide range of physical, chemical and biological characteristics. 13'Cs deposition was of the same order of magnitude, although the lowest deposition was around the Finnish lake, about half that recorded for the Norwegian site. Fallout in the Swedish lake catchment was intermediate. Radionuclide concentrations in the study lakes were relatively low (Table 1). Therefore, more emphasis should be given to the relationships between the fractions than the actual mass balance values. In the latter calculations potential errors may be magnified. All of the 137Csin the water phase in the inflow stream of Hillesjon was in the low molecular weight fraction (Fig. 1). In the outflow there was a clear increase in the low molecular weight fraction, as well as a major high molecular weight fraction (Fig. 1). This substantial increase of both fractions is explained by the resuspension of sediment material with high 137Csconcentrations. It has been shown in several cases that much of the primary load of Chernobyl fallout caesium is now located in lake sediments 113,141. The 137Csin the water phase transported by the inflow of Saarisjarvi was more evenly dispersed among the fractions (Fig. 1). In the outflow, however, it appears that practically all of the 137Csassociated with the high molecular weight fraction had sedimented in the lake as all the 137Csin the outflow stream was in the low molecular weight fraction. TABLE 1 Concentrations (Bq m-3) of 137Csand "Sr in high (HMF) and low molecular weight (LMF) fractions in the inflow and outflow of the Nordic lakes Hillesjon, Saarisjarvi and 0vre Heimdalsvatn during spring Fractions Hillesjon HMF LMF Total

137~s-inflow

d

q

39.9 39.9

'37~s-outflow

"Sr-inflow

goSr-outflow

167.0 355.0 522.0

3.65 10.03 13.68

20.79 20.79

Saarisjarvi HMF LMF Total

210 162 372

4

0vre Heimdalsvatn HMF LMF Total

201 50 251

35 83 118

215 215

4

4.41 4.41

4

13 13

4

l

-G

3.84 3.84

4

9 9

92

Hillesjiin Sweden

Hillesjon Sweden

90Sr Budget

1370 Budget

400

10000

300

5000 S 0

c 200 100

0 -5000

-loooo

'

* Inflow

!

Outflow

!

Retention

/mTotal I HMF eLMF

'

I I Total

HMF 0LMF

I

90Sr Budget

137th Budget I

-200

Saarisjarvi Finland

Saarisjarvi Finland 10000 I

o -100

I

8000

c 6000

$ x

4000

2000

0 -2000

Inflow

Outflow

I Total

Retention

HMF c!LMF

I

[WTotal

90Sr Budget

137Cs Budget

1

-20000

I

Inflow

I

4000

1

I

Outflow

I Total -11 HMF

I

Retention

LMF

I

I

Heimdalen Norway

Heimdalen Norway 80000

HMF Q LMF

1

I

I I T o l a l 3HMF

LMF

Fig. 1. Caesium-137 and '%r mass balance budgets for the total transport, high molecular weight fraction (HMF) and low molecular weight fraction (LMF) in the water phase in the Nordic lakes, Hillesjon, Saarisjarvi and @weHeimdalsvatn during spring.

The distribution of 137Cs in the various size fractions of the water phase in 0vre Heimdalsvatn has been reported earlier [3,41. About 80% of the 137Cs transported into 0vre Heimdalsvatn in the water phase was associated with the high molecular weight fraction, while this was reduced to about 15%in the lake outflow,due to the sedimentation of larger particles (Fig. 1).

93

!='"Sr in the high molecular weight phase was only present in the inflow of Hillesjon and all of this fraction was retained in the lake (Fig. 1).The high molecular weight phase also only constituted about 25% of the total inflow. In the outflows of all three lakes, %r was exclusively in the low molecular weight phase. Remobilization of !='"Sr was only recorded in Hillesjon, and then only in the low molecular weight phase (Fig. 1). For ?3r, the low molecular weight fraction plays an important role in its transport in freshwater systems and this should be taken into account in model simulations of such ecosystems. Radiocaesium demonstrates the same property, although not so strongly. Under the conditions studied the low molecular weight fraction showed little or no retention and was even "produced" in Hillesjon. The contribution of radionuclides to the water phase from the sediments has to be via relatively low molecular weight forms as larger particles will sediment out. In general, the bioavailability of an element is related to its free ion activity [ 15,161. Charged low molecular forms of an element have therefore received considerable attention due to their assumed toxicity to or accumulation in aquatic biota. Organic chemicals which have a cross-section exceeding 0.95 nm or a length exceeding 5.3 nm penetrate natural membranes very slowly, if at all [171. However many organisms feed on and digest particulate material 1181 and the accumulation of a given element may depend on the content of suspended material and rather than on dissolved concentrations. [19]. Furthermore, for several elements, the transfer through biological membranes requires a carrier [201. Thus, biological uptake mechanisms can be rather complex, where the size is only one factor influencing bioavailability. Our results suggest that the LMF-fraction is rather inert as it shows little or no retention in the lakes studied. The LMF-fraction of Cs even gains some Cs by remobilization of Cs from the sediments in certain situations. Therefore, it seems that this fraction plays a minor role in determining activity concentrations in benthos and fish in the lakes studied. In contrast there is an almost total retention and incorporation of allochthonous coarse particulate organic matter into the food chain [4,5]. Although we were able to separate low and high molecular weight phases using fraction techniques, their chemical nature is unknown. A knowledge of their chemical nature is necessary for a complete understanding of the processes governing their transport and bioavailability . Further research is clearly needed to determine the relationship between transport phases, retention and bioavailability in natural ecosystems. The role of organic matter is especially important as it can both increase or decrease mobility [21]. The results also demonstrate the role of sediment resuspension and high macrophyte production, and indicate that Hillesjon and similar lakes are potentially important sources of'"Cs and!='"Srfor downstream areas, including the coastal areas of the Baltic Sea [221. In the two other lakes retention of %r is also relatively low and thus a major fraction of the ?9r will also be exported downstream in all lakes.

94 6.ACKNOWLEDGEMENTS

Support for the project has been given by the authors' respective institutions. The studies in 0 w e Heimdalen were financed by the Norwegian Research Council's Programme for Research on Radioactive Fallout. From the Laboratory of Analytical Chemistry, Agricultural University of Norway, Anna Noren and Helge N. Lien kindly assisted with the radioisotope analysis, while Professor Brit Salbu made useful comments on the manuscript. We are also grateful for the assistance given by Dr. Jukka Ruuhijiirvi and the staff at the Evo State Fisheries and Aquaculture Research Station during our fieldwork in Finland. 7.REFERENCES 1. Nordic Nuclear Safety Research (NKS), 1991. Radioecology in Nordic Limnic Systems - present knowledge and future prospects. Report Naturvdrdsverket, Sweden, No. 49. 2. Antilla, M., 1986.The activity inventory of the fuel in a RBMK-type reactor. Tech. Rep. Tscherno, Nuclear Engineering Lab., Tech. Res. Centre of Finland, Espoo, No.

2-86.

3. Brittain, J.E., H.E. Bj~rnstad,B. Salbu and D.H. Oughton, 1992.Winter transport of Chernobyl radionuclides from a montane catchment to an ice-covered lake. Analyst, 117:515-519. 4. Salbu, B., H.E. Bjarnstad and J.E. Brittain, 1992.Fractionation of cesium isotopes and in snowmelt run-off and lake waters from a contaminated Norwegian mountain catchment. J . Radioanal. Nucl. Chem., 156:7-20. 5. Bj~rnstad,H.E., J.E. Brittain, R. Saxen and B. Sundblad, 1994. The characterization of radiocaesium transport and retention in Nordic lakes. In: H. Dahlgaard (ed.1, Nordic Radioecology. Elsevier, Amsterdam, pp. 29-44. 6. Larsson, P., J.E. Brittain, L. Lien, A. Lillehammer and K. Tangen, 1978.The lake ecosystem of 0vre Heimdalsvatn. Holarct. Ecol., 1: 304-320. 7. Hongve, D., 1987.A revised procedure for discharge measurement by means of the salt dilution method. Hydro1 Proc., 1: 267-270. 8. Benb, P.and E. Steinnes 1995.Trace chemistry processes. In: B. Salbu and E. Steinnes (eds.), Trace Elements in Natural Waters. CRC Press, Boca Raton, FL, pp. 21-39. 9. Stumm, W. and J.J. Morgan 1981.Aquatic Chemistry, 2nd Edn., John Wiley & Sons Inc., NY,780 pp. 10. Cunie, L.A., 1968.Limits for quantitative detection and quantitative determination. Application to radiochemistry. Anal. Chem., 40:586-693. 11. Bj~rnstad,H.E., H.N. Lien and B. Salbu 1990.Determination of 93r in soil and vegetation. Inf. Statens Fagtj. Landbruk No. 1-199,pp. 35-50 (in Norwegian). 12. Peppard, D.F., G.W. Mason and S.W. Moline, 1957.The use of dioctyl phosphoric extraction in isolation of carrier-free 140La,W e , lr13Prand lMPr.J. Inorg. Nucl. Chem., 5: 141-146. 13. Sundblad, B.,U. Bergstriim and S. Evans, 1991.Long term transfer of fallout nuclides from the terrestrial to the aquatic environment -evaluation of ecological models. In: L. Moberg (ed.), The Chernobyl Fallout in Sweden. Swedish Radiation Protection Institute, Stockholm, Sweden, pp. 207-238.

95 14. Blakar, I.A., D. Hongve and 0.NjBstad, 1992. Chernobyl cesium in the sediments of lake H~iysj~eCentral n, Norway. J. Environ. Radioact., 17: 49-58. 15. Jackson G.A. and J.J. Morgan 1978. Trace metal chelator interactions and phytoplankton growth in sea water media. Theoretical analysis and comparison with reported observations. Limnol. Oceanogr., 23: 268-282. 16. Allen, H.E., R.H. Hall and T.D. Brisbin, 1980. Metal speciation. Effects on aquatic toxicity. Environ. Sci. Technol., 14: 441443. 17. Opperhuizen. A., 1990. Bioaccumulation Kinetics: Experimental data and modelling. In: G. Angeletti (ed.), Organic Micropollutants in the Aquatic Environment. Kluwer, Dordrecht, pp. 61-70. 18. Cummins. K.W., 1973. Trophic relations of aquatic insects. Ann. Rev. Ent., 18: 183-206. 19. Memmet. U., 1987. Bioaccumulation of zinc in two freshwater organisms (Duphnia magna, Crustacea and Brachydunio rerio, Pisces). Wat. Res., 21: 99-106. 20. Williams, R.J.P., 1981. Physico-chemical aspects of inorganic elements transferred through membranes. Phil. Trans. R. SOC. Lond., 294: 57-74. 21. Toste, A,, L.J. Kieby and T.R. Pabl, 1984. Role of organics in subsurface migration of radionuclides in groundwater. Proc. Symp. Geochemical behaviour of disposed radioactive waste. ACS Symp. Ser., American Chemical Society, Washington, p. 246. 22. Evans, S., 1991,1991. Impacts of the Chernobyl fallout in the Baltic Sea ecosystem. In: L. Moberg (ed.), The Chernobyl Fallout in Sweden. Swedish Radiation Protection Institute, Stockholm, Sweden, pp. 109-127.

Freshwuter und Estuurine Rudioecology Edited by G. Desmet et al. 1997 Elsevier Science B.V.

97

The role of a spring river as a source of 137Csin a lagoon environment: the case of the Stella river (Marano lagoon, Northern Adriatic Sea) M. Bellia, E. Colizzab,G.P. Fanzuttib,F. Finocchiarob,R. Melisb, R. Pianiband U. Sansonea ' W P A , Via Vitaliano Brancati, 48-00144Roma, Italy bZstituto di Geologia e Paleontologia, Universita di Trieste, via Edoardo Weiss, Comprensorio di S. Giouanni, 34127 Trieste, Italy

ABSTRACT The results from some cruises made in order to determine the influence of the Stella river as a source of 13'Cs within the Lignano basin (Marano Lagoon, Northern Adriatic Sea) are presented. The suspended solid transport of this spring river is previously estimated. Furthermore, particle size and composition features of the Stella river particulate suspended matter are used to discuss the 137Csin situ Kd measured in suspended matter. The pattern of salinity of water bodies in the lagoon, nearby the Stella mouth, confirm the distribution of radiocaesium in the bottom sediments.

1. INTRODUCTION

After a radioactive fall-out on a drainage basin, soils act as temporary repository of deposited radionuclides. Radiocaesium can be then slowly removed by erosion and transported from the catchment area towards water bodies. Following the Chernobyl accident, the Friuli-Venezia Giulia region, located in north-easternmost Italy, was subjected to heavier rainfall than other Italian regions. On average, it received the highest radioactive deposition [1,21.The concentration values are particularly high on the mountain areas and then decrease towards the coast. Since 1986, concentrations of 137Csin sediment, water and suspended matter were monitored in the Marano and Grado lagoons, and in the Adriatic Sea between Trieste and the Tagliamento river delta fan [3,41, because these environments would be considered the final reception areas of radiocaesium transported from inland. This monitoring activity allowed the identification of two different areas in the lagoons: the inner part, into which spring rivers flow,

98

characterized by fine sediments and high caesium concentration; the outer part near the lagoon inlet, where marine water exchanges prevail, is characterized by sandy sediments and low caesium contamination. The high caesium concentration at the Stella mouth seems to be in contrast with the regimen of the river, which is considered a spring river. In this paper the authors provide an assessment of the radiocaesium associated with the solid transport of the Stella river, reaching the western part of the Marano lagoon, and the dispersion processes of river suspended load into the lagoon. 2. STUDY AREA

In the Friuli Plain, all the rivers with a mountain drainage basin lose their water discharge after a few kilometres due to the gravelly deposits of the high plain. Below the spring-line, in the low plain characterized by sandy and silty deposits, rivers receive waters from the ground-water table. Only during main floods, particularly in spring and autumn, do waters flow all along the riverbed, from mountain area to the sea. The Stella river (47km length) is the most important river flowing into the Lignano basin, the westernmost basin of the Marano lagoon (Fig. 1).Its source is formed by a large number of springs located some kilometres south-west of Codroipo (Udine), south of the spring-line. After a few kilometres, three main trunks can be recognized: Taglio, Stella and Torsa. Afterwards they join in a single channel. The Stella river slightly erodes the silty-clayed soils of the plain, producing a wide and flat depression, recognizable as far as the lagoon border [51. The influent trunk of the Stella river, named Corno stream, lies in the gravelly and permeable high plain; it becomes normally dry a few kilometres south of the Tagliamento morainic amphitheatre. During very important floods its waters can also flow into the Taglio river, and therefore in the Stella [6]. Sometimes it receives also the overflow water of Ledra-Tagliamento canal, diverted from the Tagliamento river for agricultural needs. From 1926 to 1950,at Casali Sacile station, an average annual discharge of 33.6 m3 s-I, was calculated [61.A similar value (32.6m3s-') was provided at the station of Ariis during the 1966-1974 period 171.The monthly average discharge of Stella is quite regular through the year: the minimum value seldom falls under 25 m3 s-l, while the maximum value is about three times the average discharge. By examining and comparing the daily discharge with the rainfall data in two barycentric stations (Fig. 21, it can be noted that the former increases for one or two days aRer heavy rains (over 25 mm), owing to a rapid drainage. In conclusion, two kinds of meteorological events are superimposed on the regularity of the spring water discharge: a short and heavy rainfall on the low plain increases the river discharge for one or two days. Moreover, when the rain is more intense and long lasting in the mountain area, the water of Corno stream and Ledra-Tagliamento canal can cross the permeable high plain and add to the Stella river waters.

99

Fig. 1. Sketch map of Friuli-Venezia Giulia plain and Marano and Grado lagoons.

The morphological evidence of the Stella river influence in the Lignano basin (surface: 50 km'; mean depth: 0.8 m) is represented by its delta, which was artificially cut and connected with a lagoon channel (Cialisia channel). The Lignano basin is characterized by wide tidal flats and by marshes of small extension. Its inlet is 500 m wide and about 11m deep; water flow through the inlet is up to 40-50 million m3 water at every tidal hemi-cycle [81. The tide is semidiurnal, with 65 cm mean tidal range; spring tides can reach range of 105 cm. The tidal stream velocity decreases &om inlet (up to 100 cm s-') to the inner part of the Cialisia channel. Here, during syzygy tides, a mean velocity of 25-30 cm s-' was measured.

100

‘O

t

I

d

7-

.-

dli

40

35

30

e

C

I

30 -

--

mrainfall discharge

Fig. 2. Relationships between daily discharge of the Stella river at Ariis station and rainfall at Talmassons station during 1973 (data from Magistrato alle Acque, Venice).

3. MATERIALS AND METHODS

In order to provide a complete set of environmental data to characterize such a complex environment, several field activities were carried out from 1991 to 1992. The physico-chemical characteristics of water and suspended matter were determined using samples collected near the surface and the bottom during seasonal surveys. Samples for 13%sdetermination were collected in May and October 1991 and November 1992. To assess the fluxes of substances from river to the lagoon environment, Total Suspended Matter (TSM) concentrations were measured by filtering 1 dm3 of water, sampled by means of a Niskin bottle, on a Whatman GF/F fibreglass filter (0.8 Fm pore size, 47 mm filter diameter) [9].The carbonate fraction was determined as difference in dry weight of TSM before and after treatment with HCl 1N. Elemental particulate organic carbon (POC) and nitrogen (PON) analyses were performed by ignition

101

in pure oxygen atmosphere, using helium as the carrier gas in a Perkin Elmer 2400 CHN Elemental Analyzer. Grain-size analyses of the suspended matter were performed on water sub-samples using a Coulter Multisizer 11, with an orifice tube of 140 pm. The TSM mineralogical composition was performed on a Siemens D 500 diffractometer, using CuKa radiation; scanning interval ranged between 2"and 35" of 20, pitch 0.1",2 seconds of computation per pitch. Semi-quantitative computation of the mineralogical phases were done using the diffractogram height of peaks. Samples of water and suspended matter for radiocaesium determination were carried out at the same depth (about 1 m from water surface) using two devices capable of filtering large amounts of water (more than 1000 dm3)using cartridge filters of 0.45 pm porosity. Each system was equipped with resin columns (ammonium hexo-cyano-cobaltferrate, NCFN) to fix radiocaesium dissolved in water. To determine the efficiency of the resins, two resins columns (diameter of 20 mm and height of 160 and 80 mm respectively) connected in series were used. During sampling, conductivity, pH and temperature were measured. 137Csconcentrations were determined in samples by gamma-spectrometry using high purity Germanium detectors (HPGe). 4.RESULTS 4 .1 . Concentration of total suspended matter in the Stella river

The solid flow of the Stella river has been always considered scarce owing to its spring characteristics [61.For this reason time series of solid measurement are lacking. Conversely, during researches on the suspended matter in the Lignano basin, it was observed that TSM concentrations at the Stella mouth could not be considered negligible, when comparing with those of the lagoon [lo].Figure 3 reports the frequency distribution of TSM concentrations in the Stella river, using all the available data (about 55 determinations at channel and mouth) collected duringvarious surveys from 1985 t o 1993 [9,10,121.The most frequent concentrations range between 5 and 10 mg dm-3; whereas concentrations between 10 and 30 mg dm-3 are observed in more than one third of cases. Concentrations higher than 60 mg dm3, measured only during flood tide, can be considered exceptional. 4.2. Characteristics of the Stella river total suspended matter

Some chemical and mineralogical analyses on TSM, referred to seasonal surveys (October 1991, February, April and July 1992) pointed out a prevailing clastic fraction over the organic one (Table 1). In fact, the mean percentage of POC is 6.9 _+ 3.1%of TSM weight and are equal or lower to these in the lagoon, The average of Stella river TSM mineralogical composition, results as follows

102

<5

5-10 10-15 15-20 20-25 25-30 30-35 35-40 40-45 45-50 50-55 55-60 >60

mg/l Fig, 3.Frequency distribution of Total Suspended Matter (TSM) concentrations in the Stella river.

TABLE 1 Main characteristics of suspended matter at the mouth of the Stella river October 1991 Parameters

Surf.

February 1992 April 1992

Bottom Surf.

Bottom Surf.

July 1992

Bottom Surf.

Bottom

2.95 10.13 5.04 7.30 6.17 36.89 Concentration (mgdm3) 9.13 43.8 48.0 47.4 30.5 40.5 Carbonate (%I 39.3 39.0 33.5 38.8 Organic carbon (mg dm-3) 506.2 2138.5 383.3 562.6 284.0 340.7 698.6 1667.1 5.6 Organic carbon (%I 5.5 4.9 13.0 5.6 4.7 11.3 4.5 11.6 13.1 7.3 8.9 9.8 6.7 7.7 9.5 C M ratio 7.2 8.7 8.6 12.2 Mean diameter (pn) 11.9 16.1 10.0 11.7 2.5 15.0 1.1 9.4 3.6 31.3 Salinity (%d 1.6 5.2 4.4 11.4 8.7 11.5 Modal diameter (pn) 13.6 21.8 11.4 14.2 22.6 25.6 23.9 33.5 5th percentile (pn) 29.3 38.3 21.7 28.5

(in percent): calcite (14 f 31, dolomite (50 f 91, quartz (18 f lo), feldspar (3 f l), illite (7f 41, kaolinite (2 It 21, chlorite (6 f 3).Dolomite is the most important mineral, followed by quartz and calcite. The sum of clay mineral percentages can reach 15%;illite and chlorite content are almost equal, kaolinite is lower. Montmorillonite or other expandable clay minerals were not detected.

103

~

-

.... .. ...... ... . . . ~

.... ....._

.........

i

.-.-..... ....

Diameter (yrn)

Fig. 4. Grain size frequency curve of the Stella river suspended matter (solid) compared with a lagoon basin one (dotted).Sampling of October 1991.

The grain size distribution of TSM shows a modal diameter ranging from 21.8 to 4.4 pm. The highest values relate to the measurements of October, during which a high water discharge was recorded; the lowest to April, in which the lowest tidal range was recorded. The mean diameter has a narrow range from 7.2 to 16.1pm. The diameter of the 5th (coarser)percentile does not exceed 40 pm. Figure 4 shows an example of grain size frequency curve of the Stella river particulate matter compared with one from the lagoon basin. 4.3. Water salinity

Salinity data (Fig. 5) show that brackish water (salinity <6%0) is confined to the northernmost part of the Cialisia channel, up to 1.5-2.0 km from the Stella mouth during ebb tide. During flood tide the area is further on restricted in a narrow strip along the lagoon border. 4.4. Radiocaesium content

Figure 6 reports the mean 137Csconcentrations measured in the superficial layer of bottom sediment samples collected in the Marano lagoon. The distribution of 137Csconcentrations range from 4 to 60 Bq kg-'. Table 2 indicates the mean 137Csconcentration measured in water and suspended matter of the Stella river. From May 1991 to November 1992 the 137Csconcentration in the Stella river water was quite uniform, ranging between 4.1 x 10"' and 12.0 x 10"' with a mean of 8 x lo4 Bq 1-'. A low variability it is also observed in the 137Cs concentrations measured in the suspended matter collected in the same period. Table 2 summarizes also the results of 13'Cs measurements in water and

104

Fig. 5. Surface salinity patterns in the Lignano basin near the Stella river mouth (ebb tide hemicycle):(a) October 8, 1991; (b) February 18, 1992; (c) April 28,1992; (d) July 30,1992.

suspended matter. I3'Cs concentrations in brackish water are from 2 to 4.5 times higher than those measured in fresh water. The concentrations of 137Cs in suspended matter are very close to that determined for samples taken in the Stella river.

105

Fig. 6. '37Cs in the superficial layer of Marano lagoon bottom sediments (Bq kg-'1.

In the same table the in situ Kdvalues are given for suspended matter from the Stella river and from the westernmost part of the Marano lagoon. The partitioning of 137Csbetween soluble and particulate phases is defined here as the ratio of 137Cssorbed in the particulate phase to the concentration of this radionuclide in solution.

106

TABLE 2 '37Cs concentrations and in situ Kd values

Location

Sampling periods

Number samples

Water (Bq l-'x104)

Suspended matter

(Bqg - ' ~ l O - ~ )

in situ Kd (mlg-1x10-5)

Stella River

May 1991 octo. 1991 Nov. 1992 May 1991 Oct. 1991

2 2 4 2 2

9f3 9f2 6f4 20f2 28f4

8.2M.2 11.35of0.001 9fl 7f2 7fl

1.of0.3 1.3f0.3 1.8f0.8 0.4m.i 0.25f0.01

Marano Lagoon

5. DISCUSSION AND CONCLUSIONS

The sediment 137Csconcentrations in the inner part of the lagoon, in which the influence of the Stella river prevails, are significantly higher than those measured in sediments taken near the lagoon inlet-zone (Fig. 6). As already seen, the salinity, together with the compositional and grain-size characteristics of the Stella particulate matter confirm that the influence of the river is restricted to the northern part of the Cialisia channel (Fig. 5). The bottom of the inner part of the lagoon is therefore a reservoir of fine sediments [ l l l , and consequently a sink for 13%s, transported by the Stella river. The decrease of caesium values from the Stella mouth towards the lagoon inlet can be due to the dispersion processes due to tidal stream or wind-induced resuspension on bottom sediments [121. As can be seen from the data given in Table 2, the in situ & values are very variable and highly dependent on the composition of water. The & values for suspended matter collected in the Stella river (mean conductivity value = 0.6 mS cm-') range between 1.0 and 1.8 ml g-' x 10'. The values determined for suspended matter collected in brackish water, where the mean conductivity value is fifty times higher (30 mS cm-'), are about five times lower (from 0.25 to 0.4 ml g-' x lo5)than those determined in the Stella river. K ' and Na' are the major ions competing with radiocaesium in brackish environments and there is a considerable literature 113,141 reporting values of & lower in the marine than in the fresh water environments. The differences in behaviour could be simply explained considering that when different water types interact, changes in the major chemical composition of the resulting water can alter the availability of 13'Cs adsorption sites on particulate matter. The desorption processes of 13%s on particles of the Stella river are favoured by an ion exchange mechanism due to the higher presence of ions such as K ' in the lagoon environment. The & presented in this paper cannot be evaluated in terms of K' and Na' variability in fresh and salt water because these data were not

107

measured during our samplings. Only for the Stella river literature values are available [Elfor ; the sampling area of the river considered in this paper, K+ values range from 2 to 3 ppm and Na’ from 3 to 40 ppm. Finally the in situ Kdvalues reported in Table 2 are higher (about two order of magnitude) if compared with measurements carried out by other authors [16]in similar environments. Our values could be explained considering the presence of significant concentrations of clay minerals (about 15%) in particles transported by the Stella river. Besides the TSM concentration values normally measured in Stella water can be compared to those in lagoon water (5-10 mg dm3), the flux of particulate, mainly inorganic matter from the Stella river cannot be considered negligible. Firstly, because the liquid discharge of the river is steady in time and its influence can be registered inside a conservative environment as the lagoon. Secondly, because during heavy rains the river solid discharge widely increases, thus providing an enrichment of caesium content in suspended matter coming from the Tagliamento mountain catchment area through the Ledra and Corn0 hydraulic systems. Combing the TSM data with the average annual discharge of Stella river, it is possible to evaluate the amount ofTSM and 137Cstransported into the lagoon. Assuming a TSM mean concentration value of 10 mg dm“, the corresponding annual amount cannot be lower than 10000 ton year-’, leading to an input of lo8 Bq year-’ of 137Csdischarged into the lagoon. 6. ACKNOWLEDGEMENTS

We wish to thank Prof. F. Princivalle, from the Mineralogy Institute of Trieste University for the clay mineral analyses and interpretation, and colleagues from the “Laboratorio di Biologia Marina” of Aurisina (Trieste) that kindly collaborated during the field work. The authors are also grateful to Dr. G. Mattassi and his group from “U.S.L. no. 8 Bassa Friulana” for the fruitful cooperation, and to the “Consorzio per la Bonifica e lo Sviluppo Agricolo della Bassa Friulana” for providing hydraulic and climate data. This work was partially supported by Italian MURST 60% “AmbientiUmidi” Research Project. 7. REFERENCES 1. 2.

3.

ENEA-DISP. Incidente di Chernobyl - Conseguenze Radioecologiche in Italia. Relazione a1 27/05/86, DOC.DISP (86) 1. ENEA-DISP. Incidente di Chernobyl - Conseguenze Radioecologiche in Italia. Relazione a1 30/11/86, DOCDISP (86) 14. Ventura, G.,M. Belli, U. Sansone, P. Nicolai, P. Spezzano, C. Papucci, M. Marinaro and G. Mattassi, 1988. Radioecological research in northern Adriatic lagoons: activities and first results. Proc. of the International Conference on Environmental Radioactivity in the Mediterranean Area, Barcelona, 10-13 May 1988, pp. 467-478.

108 4. Baldi, R. Delfanti, V. Fiore, C. Galli, 0. Lavarello, C. Papucci, A. Pentassuglia, G.

5. 6. 7.

8. 9. 10. 11. 12.

13.

14. 15. 16.

Ventura, F. De Guamni and G. Mattassi, 1989. ENEA, Sicurezza e Protezione, no. 21 Sept.-Dec. 1989, pp. 89-99. Feruglio, 1925. La zona delle risorgive del basso Friuli fra Tagliamento e Torre. Parte 11. Studio fisico-chimico e agronomico. Ann. Staz. Chim. Agr. Sper. di Udine, Sene 111, Vol. I, Udine, pp. 345476. Mosetti, 1983. Sintesi sull'idrologia del Friuli Venezia Giulia Quad. Ente Tutela Pesca, Udine, p. 296. Ufficio Idrografico Magistrato alle Acque, 1960-1971. Annali Idrologici MM.LL.PP., Servizio Idrologico, Venezia. Dorigo, 1965. La laguna di Grado e le sue foci. Ricerche e rilievi idrografici. Ufficio Idrografko del Magistrato alle Acque, Pubbl. no. 155, Venezia, p. 231. Finocchiaro, F., 1987. I1 particellato nella zona costiera: provenienza e dispersione. Universith di Trieste, Istituto di Geologia e Paleontologia, Tesi di Dottorato di Ricerca in Scienze Ambientali (Scienza del Mare), (not published). Definizione dei caratteri idraulico-sedimentologicidelle Lagune di Marano e Grado e dei fondali marini antistanti. Contratto di ricerca tra ENEA-DISP Roma e Istituto di Geologia e Paleontologia di Trieste, Linea B, 1993 (not published). Marocco, R., 1989. Evoluzione quatemaria della laguna di Marano (Friuli Venezia Giulia). I1 Quaternario, Napoli, 2: 125-137. Brambati, G.P. Fanzutti and F. Finocchiaro, 1990. Effetti della risospensione indotta da vento sulle concentrazioni e dimensioni del particellato nel bacino di Lignano (Laguna di Marano Adriatic0 settentrionale). Atti 8 Congr, Trieste. AIOL, pp. 191-212. Schell, A.L. Sanchez, T.H. Sibley and J.R. Clayton Jr., 1979. Distribution coefficients for radionuclides in aquatic environments. 111. Adsorption and desorption Studies of lo6Ru, 137Cs,241Am, and 237Puin maline and freshwater systems. Annual report: August 19784uly 1979. NUREGKR-0803.76 pp. Jannasch, B.D. Honeymann, L.S. Balistieri and J.W. Murray, 1988. Kinetics of trace elements uptake by marine particles. Geochim. Cosmochim. Acta, 52: 567577. Stefanini, 1976. Composizione delle acque fluviali del Friuli-Venezia Giulia durante la fase di magra e di piena dei corsi d'acqua. Istituto di Ricerca sulle acque 28 (5). Benes, P., M. Cernik and P. Lam Ramos, 1992. Factors affecting interaction of radiocaesium with freshwater solids. J. Radiochem. Nucl. Chem., 159 (2):201-218.

Freshwuter und Estuurine Rudioecokogy Edited by G . Desmet et al. 0 1997 Elsevier Science B.V. All rights reserved

109

Migration of radionuclides in rivers: effect of the kinetics of radionuclide interaction with suspended solids P. BeneB and M. Cernfk Department of Nuclear Chemistry, Czech Technical University, 11519 Prague 1, Brehova 7, Czech Republic

ABSTRACT The kinetics of the uptake of 137Csand 58C0on suspended solids of a small river was studied using laboratory batch experiments with the aim of obtaining data suitable for modelling the migration of these radionuclides in the river. The results were described by a two-step kinetic function and the parameters of this function were determined. The effect of stream variables on the parameters was examined. The significance of the description of the kinetics by the two-step function for the modelling of radionuclide migration in a model river is analyzed using a simple migration model and an arbitrary set of input data. The analysis confirms that the inclusion of sophisticated kinetic data into a migration model can improve the modelling only if other input data for the model are determined with sufficient accuracy.

1.INTRODUCTION

Migration of radionuclides in surface waters is strongly affected by the interaction of radionuclides with suspended solids and bottom sediments. The interaction depends on a number of factors, not always considered in the modelling [l]. Previous studies [l-31 have revealed that the kinetics of the interaction may be slow and that it may significantly affect the transport of radionuclides in rivers. In many cases, the kinetics corresponds to a two- or multi-step process and its description by a one-step kinetic model is imprecise 141. Therefore it has been proposed to replace the description in modelling radionuclide migration by a two-step kinetic model. In this paper, the possible effect of this replacement is examined using data obtained in the study of the interaction of radiocobalt and radiocaesium with suspended solids from a small river [4-61, and a simple migration model [71.

110

2. KINETIC MODELS AND PARAMETERS

The kinetics of the uptake (adsorption) of carrier-free 68Coand 137Cs on suspended solids of selected rivers was studied by laboratory experiments using batch method [4-6,8].The results were analyzed by means of three kinetic models: (a) a model of one-step reversible reaction of the first order, (b) a model of two parallel reactions for ion exchange of radionuclide at two different sites on the solid phase, (c) a model of two consecutive reactions, where the second reaction takes place by the transfer of bound radionuclide from one exchange site t o another one. For the two-step kinetic models, equations suitable for a description of the kinetics and four basic parameters have been proposed (41. Two of the parameters are apparent rate constants of radionuclide uptake by the solids (XI, b), two are equilibrium distribution coefficients (a,p), describing the equilibrium distribution of a radionuclide between the solution and two kinds of exchange sites in the solid phase. The one-step kinetics can be described by the kinetic coefficient (h)and the equilibrium coefficient (&). The kinetic parameters are determined by fitting of laboratory experimental results. The kinetic models were tested on a set of data on radiocobalt interaction with river sediments. The errors associated with description of the experimental kinetic data with the two-step kinetic models were found to be much smaller than the errors of similar description with the one-step kinetics. 3. EFFECT OF STREAM VARIABLES ON THE KINETICS

The kinetics of radionuclide interaction with freshwater solids can depend on the concentration of the solids (solid to liquid ratio, mN), on temperature, and on composition of both water and the sediment. The effects of m N and temperature can be described quantitatively and included in modelling the migration in a suitable functional form. The effect of m N on the parameters of two-step kinetics was analyzed theoretically [5] and tested experimentally for the uptake of %o (51and 13’Cs [6]on freshwater solids of unchanged composition.The tests have shown that the parameters thus obtained depend on the concentration of solid phase in the predicted way. Some deviations from a theory were probably due to experimental errors. Comparable accuracy found for description of the experimental curves with both two-step kinetic models was ascertained. The effects of the composition of water and the solids are too complicated and can be only expressed as the variability of the interaction parameters. Earlier [6] we proposed that this can be done by laboratory experiments with repeatedly sampled unfiltered water from the river. This is also a good way of obtaining average kinetic and equilibrium parameters characterising the interaction in the studied system. The variability was examined by laboratory study of the uptake of “Co and 137Cson suspended solids in 6 samples of unfiltered

111

water of a small river taken under different flow conditions [81. A substantial (up to three-fold) increase in the errors of the average values of the interaction parameters was found to be due to the variation in the composition. The errors were greater for 58C0 than for 13’Cs. The errors found for the models of consecutive and parallel reactions were approximately equal which corroborated the suggestion that the models are equivalent from the point of view of their use for description of radionuclide interaction with suspended solids. The two-step kinetic models remained significantly more accurate than the onestep kinetic model, despite the fact that their accuracy was diminished due to the variability of their parameters. 4. THE ROLE OF DESCRIPTION OF THE INTERACTION KINETICS IN THE MODELLING OF MIGRATION

The last step in evaluation of the kinetic effects to radionuclide migration in rivers is based on comparison of both kinetic approaches on a simple transport model. The comparison was aimed at finding whether the use of the more exact description of the kinetics would give a significantly better description of the migration by conditions when other input parameters of the transport model are determined within a certain error. For this purpose, a distribution of radiocaesium in bottom sediments of a model river was calculated with the migration model “SMC” proposed recently [71. In the model, a river of interest is divided into sections, where some parameters important for transport are constant. Each section is represented by a mixed tank which contains water, suspended particles, and bottom sediment. All bottom sediments are considered to be resuspendable. For all sections we considered the same time interval for a flow of water between upstream and downstream ends, so the water flow is realised as a shifting of a defined amount of water from a tank to the following one. Whole time of simulation is then divided into simulation periods, calculated based on a measured water flow and a defined volume of the tanks. Within the simulation period, a part of input suspended particles sediments to the river bottom and is completely mixed with the resuspendable bottom sediment. After that a part of the bottom sediment is resuspended into the stream. A mass balance equation for sediment transport equals differences between amounts of suspended sediments and differences of sedimentation (SED)and resuspension (RES)fluxes:

+ SL, - S,Q1= SED, - RES,

SL-IQ1-l

(1)

and S, is concentrawhere SL, is tributary input of suspended sediments, and QLinput and output volumetric tion of input and output sediments, water flow, respectively. The sedimentation flux, SED,, is calculated based on the sediment exchange coefficient, defined as the part of the suspended particles available for the exchange with the resuspendable bottom sediment.

112

Suspended particles and bottom sediments contain sorbed radionuclide. By sedimentation and resuspension the concentrations of the radionuclide are changed. Additionally, the radionuclide undergoes redistribution between dissolved and particulate forms in water. A mass balance equation for the radionuclide transport equals differences between the sorbed and dissolved radionuclide concentrations:

where Cw,i,Cs,i, and CB,iis the concentration of the radionuclide dissolved, sorbed on suspended particles, and sorbed on bottom sediment, respectively. Redistributionof the radionuclideis described by the kinetic equation for either one reversible reaction or two parallel reactions. In the present paper, the model “SMC”was applied for a comparison of the one-step and the two-step kinetic approaches. As a model system we used a system where parameters are as close as possible to the conditions in a real river. The model was in previous work [71 successfully applied for modelling of an accidental release of I3’Cs from the Jaslovske Bohunice nuclear power plants (Slovakia) into the Dudvah River. A time-dependent longitudinal profile of 13‘Cs activity in the bottom sediments was successfully modelled within a measured period of 500 days and some predictions of a profile evolution were made. Hence, the system was used as an example of a real system. The experimental data of 137Cssorption on suspended particles from the Dudvah river were fitted with the two-step kinetic model with deviations in a range of experimental errors. “Standard” model conditions applicable for the two-step model are shown in Table 1. Kinetic parameters for the one-step kinetic model are also presented, as used in [71. The one-step kinetic model fitted the data with larger deviations. The two-step kinetics was set as a description accurate enough in respect to kinetics. Inaccuracies of the one-step kinetic model are compared with inaccuracies given by inexactness of other input data in Table 2. The scenario of the model experiment is the following: radiocaesium was added into the river by release 106Bqof 13’Cs (100%in solution as Cs’) during one simulation period. The concentration of 137Csin the bottom sediments before the release was considered equal to zero. Distribution of 137Csin the bottom sediments along the stream was calculated for a certain period of time after the release. Figure 1 shows the distribution of radiocaesium in bottom sediments of individual sections of the model river (tanks) one month after the release calculated by three different kinetic models. As can be seen, the use of different kinetic models of the interaction in calculation of the migration leads to significantly different results. Activities of the bottom sediments calculated with less precise kinetic approaches are overestimated. In order to quantify the differences between the curves (“standard”and “nonstandard”),the coefficient of disagreement CD was introduced by equation:

113 TABLE 1 Parameters used for the model calculations. Kinetic parameters a, P, hi, h2 are set for the kinetic model of two parallel reversible reactions; parameters Kd and h correspond with the one-step kinetic model Parameter

Value

Number of mixed tanks River width Thickness of resuspendable bottom sediment Flow rate Linear speed of flow Simulation period Concentration of solid particles Sediment exchange coefficient Temperature a

29 10 m 6x103 m 1.8 m3 s-l 0.4 m s-l 1200 s 33x103 kg m3 0.12 23°C 4.27 2.46 3 . 8 ~ 1 s-l 0~ 2.2x104 s-1 14 m3 kg-’ 3 . 3 ~ 1 s-l 0~

P

A1

hz Kd h

TABLE 2 Coefficients of disagreement CDi(%’o)for distribution of 137Csin the bottom sediments calculated under different “non-standard”conditions Non-standard condition

Time elapsed after the release

One-step kinetic model Equilibrium model (Kd) mN= 6 6 ~ 1 kg 0 ~m-3 ~ Temperature 13°C Exchange coefficient 0.24 Sediment thickness 4 . 8 ~ 1 m 0~

C J=1

1 week

1 month

21.9 34.5

23.2 35.9 31.4 8.1 47.2 23.7

25.9 38.8 20.5 8.0 39.5 19.8

8.5

_.

n

CD,(%)= 100

1 day

n

I

/CAsJ J=1

(3)

where n is the number of tanks (n = 29),A, is the activity of 137Csin the bottom sediment of t a n k j calculated for set of “non-standard” input data denoted by i, and A, is similar activity, calculated for the “standard” set of conditions. The coefficient represents a mean difference (in %) between the activities of sediments in all 29 tanks for sets of standard (s) and non-standard (i) conditions.

114

tank Fig. 1.Activity of '37Csin the bottom sediments along the model river calculated for one month after the release of lo6Bq 137Cs calculated by three different descriptions of kinetics of the interaction: the two-step kinetics (curve 11,the one-stepkinetics (curve 21, and the immediate interaction (curve 3). The kinetic parameters are summarised in Table 1.

The coefficients CDi characterising curves 2 and 3 of Fig. 1are presented in Table 2 where also the effects of other parameters are shown. It can be seen that the coefficients CDi due to changes in the kinetic model are comparable with CDi coefficients due to changes in the other input data. From this fact it follows that the more precise description of the kinetics of the interaction can bring a positive effect only if the other input data for the migration model are determined with a sufficient precision. The relation between uncertainty of stream variables and the required precision of description of the interaction kinetics deserves further study. 5. REFERENCES

Beneg, P., 1988. Interaction of radionuclides with solid phases in the modelling of migration of radionuclides in surface waters. In: Impact des accidents d'origine nucleaire sur l'environnement. IV Symposium Internationale de Radioecologie de Cadarache. CEN Cadarache, France, Vol. 1, pp. C60467. Onishi Y.et al., 1981. Critical Review: Radionuclide Transport, Sediment Transport and Water Quality Mathematical Modeling and Radionuclide Adsorption/ Desorption Mechanisms. NUREG/CR-1322, Pacific Northwest Laboratories, Seattle, WA. Picat P. et al., 1986. Study of the physicochemical forms of cobalt in the Loire water. In: Speciation,of Fission and Activation Products in the Environment. EUR-10059, CEC, Brussels, p. 287. BeneB, P., P. Picat, M. Cernilr and J.M. Quinault, 1992. Kinetics of radionuclide interaction with suspended solids in modeling the migration of radionuclides in rivers. I. Parameters for two-step kinetics. J. Radioanal. Nucl. Chem., 159: 175186.

115

5. BeneS P. and M. Cernik, 1992. Kinetics of radionuclide interaction with suspended solids in modeling the migration of radionuclides in rivers. 11. Effect of concentration of the solids and temperature. J. Radioanal. Nucl. Chem., 159: 187-200. 6 . BeneS, P., M. Cernilr and P. Lam Ramos, 1992. Factors affecting interaction of radiocaesium with freshwater solids. 11. Contact time, concentration of the solid and temperature. J. Radioanal. Nucl. Chem., 159: 201-218. 7. Beneg, P., M. Cernik and 0. Slavik, 1994. Modelling of migration of 137Csaccidentally released into a small river. J. Environ. Radioactivity, 22: 279-293. 8. Benee P. and M. C e m i , 1994. Kinetics of radionuclide interaction with suspended solids in modeling the migration of radionuclides in rivers. 111. Variability of kinetic parameters. J. Radioanal. Nucl. Chem., 185: 15-26.

Freshwurer und Estuurine Rudioedogy Edited by G.Desmet et d. 1997 Elsevier Science B.V.

117

Distribution, cycling and mean residence time of 226Ra, 210Pband 210Poin the Tagus estuary F.P. Carvalho Direccao Geral do Ambiente, Departamento de Proteccao e Seguranca Radiologica, EN 10,P-2685 Sacavem, Portugal (Present address: International Atomic Energy Agency, Marine Environment Laboratory, P.O. Box 800, MC 98012, Monaco Cedex)

ABSTRACT Results for dissolved and particulate 226Ra,210Pband 210Poin the Tagus river, estuary and coastal sea system show different distribution and chemical behaviour patterns for these radionuclides in the three aquatic environments. 226Rafrom riverborne particles dissolves in the estuary and contributes to increased concentrations of dissolved 226Ra in estuarine water. In the estuary, dissolved 210Pband 210Pofrom river discharge and atmospheric deposition are scavenged by suspended matter, which in turn becomes enriched in these nuclides in comparison with riverborne particles. As a result of these processes, the estuarine water flowing into the coastal sea contains enhanced concentrations of dissolved zzsRa,but is depleted in dissolved 210Pband 210Po.Under average river flow conditions, mass balance calculations for dissolved 210Poand 210Pbin the estuary allowed their mean residence times to be estimated as 18 and 30 days, respectively. Due to the rapid sorption of these radionuclides on to settling particles, bottom sediments in the estuary represent a sink for zloPband 210Pofrom both natural sources and industrial waste releases. Results also suggest that partial re-dissolution of these radionuclides from bottom sediments and intertidal mudflata is likely to occur in the mid- and low-estuary zones. Nevertheless, box-model computations indicate that the discharge of zlOPband 210Po into the coastal sea takes place mainly with the transport of the sediment, whereas the discharge in the dissolved fraction can only account for one third of the activities entering the estuary in the soluble phase. Implications of these results to the cycling of radionuclides in phosphate waste released into estuarine environments are discussed.

The Science

of

the Total Environment, 196 (1997)151-161.

Freshwuter und Esruurine Rudidioecology

Edited by G . Desmet et al. 1997 Elsevier Science B.V.

119

Mobilization studies of 137Csin sediments from Rochedo Reservoir, Goiania, Go., Brazil Marcia Emilia M. De Lucaa a n d Jose Marcos Godoyb aInstituto de Biofisica Carlos Chagas Filhol UFRJlIlha do FundcZo, RJ, Brazil bInstituto de Radioprotepio e Dosimetria IIRD-CNEN, Av. Salvador Allende s l n Jacarepagua, Rio de Janeiro, RJ, Brazil CP 37750 (Present address: Pontificia Universidade Catolica do Rio de Janeiro, Depto. de Qutmica, Rua Marqu2s de ScZo Vincente 225, Gavea, RJ, Brazil, CEP 22453-900)

ABSTRACT An inventory of 137Csin the sediments of Rochedo Reservoir showed that 94 GBq reached the Meia Ponte River system, as a consequence of the GoiAnia radiological accident in 1987. 13'Cs profile shapes were dictated by their location relative to the main river inflow. When N m concentrations in the sediment were high there was a clear correlation between Kd and N m . Laboratory experiments showed that the efficiency of 137Csdesorption from the sediment, was a function of the illite content.

1. INTRODUCTION

In the Goifinia radiological accident in September 1987, a radiotherapy machine was dismantled in a residential area and a fraction of soluble '37CsC1 (50.9 TBq at the time) was deposited on unprotected soil surfaces and exposed to rainfall. Some 137Cswas introduced into the sewage system which was still being constructed at that time. The rain water and local sewage were drained to small tributaries of the Meia Ponte River, where the suspended particulate settled and were trapped at Rochedo Reservoir [1,21, about 80 km downstream from Goihia (Fig. 1). The Rochedo Reservoir has a 7.6 km2 area, with an average depth of approximately 8 m in the dry season and 12 m in the rainy season. The mean precipitation per year is about 1800 mm and the annual maximum and minimum discharge are 124 m3/s and 10 m3/s, respectively. Many studies of radiocesium in the aquatic environment suggest that, although 137Cs becomes strongly associated with particulate phase, it is mobilised

120

-

D

t

L

Fig. 1. Hydrographic basin of Meia-Ponte River and Rochedo Reservoir with the sampling points and sectors.

in anoxic environments [3-51. This mobilisation, as suggested by Sholkovitz [6], occurs in response to changing redox conditions in the sediments after deposition. The increase in dissolved I3'Cs in pore waters of anoxic lake sediments gives direct evidence of post-deposition mobilisation of radiocesium, caused by competitive ion-exchange with NK, which reaches high concentration in anoxic pore waters [3-71. The aim of this work is (a) to determine the inventory of 13'Cs inside the .. Rochedo Reservoir; (b)to confirm if the radiocesium in these sediments behaves as expected under anoxic conditions and (c) to investigate the relationship between mineralogy and the reversibility of 13'Cs sorption in sediments of freshwater systems of a typical sub-tropical aquatic environment in the southern hemisphere.

121 2. EXPERIMENTAL PROCEDURES

Fifteen sampling stations were established for sediment (bottom and profiles) and water analyses. One sampling station was in the Meia Ponte River before the reservoir, 13 in the reservoir and one downstream. In order to help the data interpretation, the dam was divided into three sectors (Fig. 1).Sediment profiles were sampled, between 1989 and 1992, using a gravity corer and the sediment columns were sectioned into 2-5 cm intervals. Bottom sediment samples were taken using an Ekman dredge. The sediment slices and bottom sediment samples were wet sieved, using water sampled at the same station, to analyze the grain size distribution. The samples were dried and 137Csconcentrations measured by gamma spectrometry using a 30% relative efficiency HPGe intrinsic detector. Pore water was separated from the individual slices by either gravity settling of solids after freezing or filtration in a glove box under a high purity nitrogen atmosphere (0, < 0.003%) to prevent any oxidation of anaerobic samples. The pore water samples were divided in order to allow both physicochemical measurements and measurement of 137Cs.The latter was measured in a low-background, proportional counter, after precipitation with chloroplatinic acid. In situ Kdsfor 137Cswere calculated from the activity in the solid and in pore water for each sediment slice. Laboratory experiments using radiotracers were performed to investigate 137Csmobility. Sediments that had been left in contact with radiotracer for different periods of time (1d, 1week, 2 weeks) were treated with lo3 M NH4Cl (V/m = 920) and the desorbed 137Cswas pre-concentrated on Giese granulate (NH4,Cu-Hexacianoferrate) in dialysis bags suspended in the extractant. The dialysis bags were taken out of solution on a number of occasions during the 60-day extraction period and the radioactivity was counted 171. 3. RESULTS AND DISCUSSION

The temporal and spatial variation of 137Csconcentration in the bottom sediment from Rochedo Reservoir can be split into three different groups according to its behaviour (Fig. 2). Samples from sector I and I1 show a decreasing (Pol) or a nearly constant behaviour ( P l l ) , depending on its position to the main channel and to the dam inlet. On the other hand, samples from sector I11 show an increasing behaviour (e.g. P07), denoting a physical transport from the upper part of the reservoir to the lower one. Since the bottom sediments downstream from the Rochedo dam are sandy (e.g. P15), no 137Cswas found after the reservoir. The spatial variation of 137Csconcentration in sediment profiles is shown in Fig. 3. As mentioned above, different profiles resulted from different positions of the sampling stations in relation to the main channel and to the reservoir

122

Fig. 2. Temporal and spatial variation of '37Cs concentration in bottom sediments. PO1 (a), PO7 (b) and P11 (c).

inlet. Sampling station 14,localised in the river itself, shows influence of the river current. The two 13'Cs concentration maximums found at stations 11 and 13 are due to the rainy season of 1987 and 1988,when a large amount of suspended matter is transported by the Meia-Ponte River (Fig. 4).Based on these maximums, the sedimentation rate could be calculated (15 and 10 cdyear, respectively). Station 07 shows only one maximum probably due to the slice thickness ( 5 cm) being bigger than the sedimentation rate (3.3cdyear). There is also a clear sedimentation rate gradient from sector I to sector 111.

123

I-

5' 10 15

!-

. .

',: 50

Fig. 3. Spatial variation of 1 3 k s in sediment profiles. P14 (a), P11 (b), P13 (c) and PO7 (d). December 1989.

Based on the simple mean of the sediment profiles taken during one sampling campaign and the reservoir area, the total inventory of 13'Cs in Rochedo Reservoir was calculated as 94 GBq for 1991 as well as for 1992. This means 1.4%of the unrecovered part of the 137Cssource [ll. The temporal variation of 137Csconcentration in sediment profiles is shown in Fig. 5. The 1991 maximum localised at 14 cm depth corresponds to the 1989 maximum. Using the sedimentation rate of 3.3 c d y e a r calculated above, 14 cm is exactly the expected depth after 2 years. This maximum was however lower in concentration than the one found before (40 Bqkg in 1991 and 90 Bqkg in 1989) and vanished the following year (1992). The second maximum found in 1991 was also deeper in 1992 than before and with a lower concentration. This

124 240 210

s

g

ci

’

I

\

v

I

180

.-c

-

Rainseason Dry Season

A

!

.

#

j

i

m

i

I A

A L

0

I 0

w 1

m 2

.

, @ = y D T m . .

. 3

A

4

5

6

7

8

.A

I

9 1 0 1 1 1 2 1 3 1 4 1 5

Sampling Stations Fig. 4. Suspended matter in surface water of the different sampling points during the rainy and the dry season.

maximum softening could be an indicator of a 137Csremobilisation motivated by ion-exchange with N E . Caesium-137 in pore water samples showed maximum levels of -0.5 BqA. In situ Kdscalculated based on these results were in the order of 102-103Vkg.Deep layers of the profiles of sectors I and I1 presented high ammonia concentrations b0.04 mM) in pore water as a result of negative redox condition. A good inverse correlation was found between Kd and ammonium concentration for these samples (Fig. 6 ) . The sediments from Rochedo Reservoir are weathering products from igneous rocks. The X-ray diffractometry analyses of clay fractions showed a typical composition of kaolinite with a varied proportion of mica or illite. Since these analyses were only semi-quantitative, kaolinitehllite ratios were calculated TABLE 1 Kaolinite/illite ratios (arbitrary units) for the Rochedo dam sampling points Kaolinitdillite 1-2 2-3 3 4 >4

Sampling point

125

a- 8

' 6

* *

lo-

0

1315 18

-

0

e

20-

Fig. 5. Temporal variation of 137Csconcentration in sediment profiles. Sampling point 07.

with arbitrary units (Table 1).The results show a kaolinitehllite gradient from sector I t o sector 111. Chlorite, quartz and goethite are secondary accessory minerals. Circa 90-95% of the sediment particles were smaller than 63 pm. Figure 7 demonstrates the influence of sediment mineralogy and contamination aging on the desorption of 137Csfrom these sediments when using NH4C1.At station 14 (Meia Ponte River, highest illite content) the desorption of I3'Cs was very low with only 50% being mobilised for fresh contaminated

126 10000

i t

P

1000 -_

s

W

100

-_

10 I

lo-‘

10 2

I

100

Ammonium Concentration (mM) Fig. 6. Correlation between Kd in situ and NH$ content in pore water. Data from sediment profiles of sectors I and 11. The straight line equation is given by log (Kd) = -1.023 log (NH$) + 3.389; r2 = 0.87.

sediment (1 day) and 30% for 2 weeks old contaminated sediment. In another sample from station 7 (sector 111,lowest illite content) it was found to be more efficient with a maximum of 93% for fresh contaminated sediment and 45% of 137Csavailable after 2 weeks. Two different desorption kinetics could be observed in both cases, a fast one during the 4 first days of desorption and a slower one after this time. The faster process is probably due to weakly bounded I3’Cs and the slower one to site-specific clay bounded 137Cs181. 4. ACKNOWLEDGEMENT

The authors thank Dr. Rob Comans (ECN) for his help during different steps of this work. 5. REFERENCES 1.

International Atomic Energy Agency, 1988. The Radiological Accident in Goihia. IAEA, Vienna.

127

1

loo 4)

i

lo 0 1 0

I

1

0

,

I

2

0

3

0

4

0

5

0

6

0

h Y S

Fig. 7. Desorption kinetics of %s from Rochedo Reservoir sediments with lo3 M NH&I under anaerobic conditions after 1 d, 1 week and 2 weeks contamination aging. PO7 (a) and P14 (b).

128 2. 3. 4. 5.

6. 7. 8.

Godoy, J.M., J.R. Guimaraes, J.C.A. Pereira and M. Pires do Rio, 1991. Cs-137 in the Goihia waterways during and after the radiological accident. Health Phys., 60: 99-103. Pardue, J.H., R.D. De Laune, W.H. Patrick Jr. and J.H. Whitcomb, 1989. Effect of redox potential on fixation of 137Csin lake sediment. Health Phys., 57: 781-789. Evans, D.W., J.J. Albert and R.A. Clark 111,1983. Reversible ion-exchange fixation of Cs-137 leading to mobilization from reservoir sediments. Geochim. Cosmochim. Acta, 47: 1041-1049. Comans, R.N.J., J.Z. Middelburg, J . Zonderhuis, J.R.W. Woitiez, G. J. De Lange, H.A. Das and C.H.V. Weijden, 1989. Mobilization of radiocesium in pore water of lake sediment. Nature, 339: 367-369. Sholkovitz, E.R., 1985. Redox-related geochemistry in lakes: alkali metals, alkaline-earth elements and 137Cs.In: W. Stumm (ed.), Chemical Processes in Lakes, pp. 119-142. Madruga, M.J., 1993. Adsorption-desorption behavior of radiocesium and radiostrontium in sediments. Doctor Thesis, Leuven University, 121 pp. Comans, R.N.J. and D.E. Hockley, 1992. Kinetics of cesium sorption in illite. Geochim Cosmochim. Acta, 56: 1157-1164.

Freshwurer und Esruurine Rudioecology

Edited by G. Desmet et al. 0 1997 Elsevier Science B.V. All rights reserved

129

Interpreting and predicting in situ distribution coefficients of radiocaesium in aquatic systems R.N.J. Comansa, J. Hiltonb, A. Cremersc, P.A. Geelhoed-Bonouvriea and J. T. Smithb aNetherlands Energy Research Foundation (ECN), P.O. Box 1, 1755 ZG Petten, The Netherlands bInstitute of Freshwater Ecology, River Laboratory, East Stoke, Wareham, Dorset BH20 6BB, UK ‘Laboratory for Colloid Chemistry, Katholieke Universiteit Leuven, Kardinaal Mercierlaan 92, B-3030, Heverlee, Leuven, Belgium

ABSTRACT This study presents an overview of our post-Chernobyl investigations of the mobility of radiocaesium in sediments, as expressed in terms of its sedimentlwater distribution coefficients or Kd values, and focuses on the two major factors controlling radiocaesium mobility: the quantity of selective binding sites and the competition for these sites by other cations. In situ Kd values have been measured in a number of very different western European lake sediments and show a variation of over three orders of magnitude. This variability can be quantitatively interpreted in terms of a competitive ion-exchange process between radiocaesium and ammonium ions on highly selective binding sites at the frayed particle edges of illitic clay minerals. These findings allow the radiocaesium Kd in freshwater sediments to be predicted, within acceptable limits, on the basis of the quantity of highly selective exchange sites and the pore-water NHi concentration. The implications of these findings for the exchangeability of sedimentbound radiocaesium are discussed.

1.INTRODUCTION

In aquatic radioecology, knowledge of the abiotic behaviour of radiocaesium, i.e. its mobility in the geosphere, is a prerequisite for a full understanding of the availability of this radionuclide for uptake and further transfer in the aquatic food chain. Since the Chernobyl accident, it has become clear that the mobility of radiocaesium is controlled by a highly selective interaction with the

130

frayed particle edges of illitic clay minerals [l] , It has been shown at the same time that competition for these binding sites by the high levels of ammonium in anoxic sediments may partly remobilise sediment-bound 13’Cs and increase its potential for uptake by biota [2,31. In the framework of the European Commission’s Nuclear Fission Safety Programme, a number of different western European sediments have been studied. The observed differences in the mobility of radiocaesium, both within and between sediments, as measured in terms of its sedimenuwater distribution coefficient or Kd have been interpreted in terms of the model for highly selective binding of radiocaesium on illite. This study presents an overview of these investigations and focuses on the two major factors controlling radiocaesium mobility: the quantity of selective binding sites and the competition for these sites by other cations. 2. MATERIALS AND METHODS

Five sediment profiles from four different freshwater lakes in The Netherlands and the UK (Table l), which differ widely in their chemical and mineralogical properties, have been carefully sampled and analyzed in our laboratories. Sediments were collected in October 1987 (Hollands Diep), November 1987 (Ketelmeer), April 1991 and August 1992 (Esthwaite), and February 1992 (Devoke). Sediments from Ketelmeer and Hollands Diep were collected with a box corer from which four vertical sub-cores were taken by carefully inserting PVC tubes with a polyethylene liner. Esthwaite and Devoke sediments were both sampled by taking four parallel cores from the same site using a Mackereth type corer [4]. The (sub)cores from each site were sampled at identical depth intervals under a nitrogen atmosphere. Pore water was extracted using either an Nz-pressure filtration system ([51 for Ketelmeer and Hollands Diep) or by high-speed (20,000 x g; 30 min) refrigerated centrifugation in centrifuge tubes which were sealed under an Nz atmosphere (Esthwaite and Devoke). Pore water samples were filtered through 0.2 pm membrane filters. Except for the TABLE 1 Sediments studied for in situ radiocaesium mobility, with sampling dates and values for the product of the selectivity coefficient and the concentration of caesium specific sites, i.e. the “radiocaesiuminterception potential”171 Sediment

Sampling date

eBINH4[FESI(meq g-’)

Hollands Diep, NL Ketelmeer, NL Esthwaite, UK Devoke, UK

21 October 1987 12 November 1987 10 April 1991 and 17 August 1992 28 February 1992

0.66 0.23 0.64 0.24

131

centrifugation, all pore-water separation procedures took place in a glove box close to in situ temperature under a high-purity nitrogen atmosphere (02< 0.003%). The (sub)cores were analyzed separately for K' (ICP) and NH; and Si by spectrophotometric techniques. No major differences were observed between identical intervals in the separate cores. This confirms the quality of our pore-water extraction and analytical techniques, and implies that the sediments showed no major lateral compositional variations. This vindicates our strategy of combining the four pore-water samples from each of the sampled depth intervals. The above procedures made available aliquots of approximately 100-500 ml pore water for radiocaesium analysis after the addition of stable caesium as a carrier and preconcentration on ammoniummolybdophosphate (AMP)[6], Low level 137Csy-spectrometry of the preconcentrated pore-water samples was performed in an anti-coincidence (AC) array consisting of an annular NaI shield around an intrinsic germanium detector. The AC facility was situated in a low background counting room with walls of low potassium concrete. The pore-water samples were counted for 72 h. This procedure enables 137Csto be determined to a limit of detection of -10 mBq with -15% standard deviation and no appreciable bias [61. The sediment samples were counted for 8-14 h in aliquots of 15-30 g with a coaxial Ge(Li) detector situated in the same low background counting room. Both 134Csand 137Csactivities were measured in the sediment samples. Further details of the low level counting procedure for 137Cs are given in Ref. [61. The highly selective binding sites for radiocaesium were measured on the same sediments by using AgTU procedures to mask non-selective sites, as outlined in Ref. [7]. 3. RESULTS AND DISCUSSION

All sediments show clear Chernobyl peaks in both 134Csand 137Csnear or a few centimetres below the sediment surface (Figs. 1-4). A second feature in only the 137Csprofile at greater depths can be attributed to the fallout from nuclear weapons testing in the 1950s-1960s. Sedimentation rates for these sediments calculated on the basis of the latter peaks vary between a few mm to 1c d y e a r . Peak (Chernobyl) 137Csactivities vary between about 200 Bq kg-' for the Dutch sediments, 500 Bq kg-' for Esthwaite and 3000 Bq kg-' for Devoke, and reflect the high deposition in the upland areas of Cumbria. Pore-water 137Csprofiles show very few features, but tend to decrease with depth. Only the profile for Devoke shows a small maximum that coincides with the Chernobyl peak in sediment-bound 1343137Cs. The separate measurements of both dissolved and solid-phase 137Csactivities at different depths in the sediments allows for calculation of in situ sedimentlwater distribution coefficients (or Kd values) and for assessment of

132 Ketelrneer, November 1987

(a)

actlvity 0

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0

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1

d

Ketelrneer, November 1987 concentratlon [pM]

0

40

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1000

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Fig. 1. Profiles of 1 3 ~ and s 137Cs in the solid phase and '37Csin pore water (a) and profiles of K+ and NHZ in pore water (b), in the sediment of Ketelmeer (The Netherlands [3]). (a) 0 = 137Csin solid phase; 0 = dissolved '37Cs;A = 1 3 k s in solid phase; (b) 0 = dissolved K'; = dissolved NHi.

133

Hollands Diep, October 1987 activity 0

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Hollands Diep, October 1987

(b)

concentration [pM] 0

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1000

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3000

4000

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Fig. 2. Profiles of 13%sand 137Csin the solid phase and 137Csin pore water (a) and profiles of K' and N H f in pore water (b), in the sediment of Hollands Diep (The Netherlands [13]).(a) 0 = 13'Cs in solid phase; 0 = dissolved 13'Cs; A = 13%sin solid phase; (b) 0 = dissolved K'; = dissolved NHZ.

134 Esthwalte, April 19911August 1992

(a)

actlvity

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Esthwaite, August 1992 concentration [pM]

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25 Fig. 3. Profiles of 13%s and 13'Cs in the solid phase and I3'Cs in pore water (a) and profiles of K+and N H f in pore water (b), in the sediment of Esthwaite, Cumbria, UK, sampled on two occasions in April 1991 (before stratification) and August 1992 (after stratification). (a) 0 = 137Csin solid phase; 0 = dissolved 13'Cs; A = 13ksin solid phase; (b) 0 = dissolved K+; 0 = dissolved NHf in 1991 (W = ibid, 1992).

135

their down-core variation. These values decrease strongly with sediment depth (solid-phase 137Csactivities show a much stronger decrease than does dissolved 137Cs), implying that the mobility of radiocaesium increases substantially with depth below the sedimenuwater interface. Radiocaesium is known to bind to soils and sediments by a highly selective ion-exchange process at the frayed particle edges of illitic clay minerals [ll. Therefore, in the absence of down-core variations in (clay) mineralogy, the observed Kd decrease in each of the sediments can only be the result of an increase in the pore-water concentration of ions which can compete with radiocaesium for these sorption sites. The major candidates for this process are K' and NH4 which can also bind strongly to illite because of their similar dehydrated ionic radius as caesium [BI. We have concluded earlier on the basis of the Ketelmeer data, that the increase in down-core mobility of radiocaesium is caused by competitive ion-exchange with NH: on illite [3]. The pore-water profiles of both K' and NH; in Figs. 1 - 4 indeed show that K' concentrations in all sediments remain almost constant with depth. The NH; concentrations, however, are considerably higher and show a strong increase which coincides with the decrease in the radiocaesium Kd. The complete set of sediment data, which is for the first time fully presented in Figs. 1-4, has allowed us to generalise our earlier conclusions and to investigate the relationship between the radiocaesium Kd and pore-water NH; in more detail in the framework of the ion-exchange process on illite [91. Compilation of all in situ Kdvalues in Fig. 5 191, reveals a single relationship between the radiocaesium Kd and the pore-water ammonium concentration. This observation is consistent with ion-exchange theory in that, among the major ions that compete with caesium for binding sites on illite clays, NH; out-competes K' in anoxic sediments as it reaches higher concentrations (Figs. 1-4)and is about five times more selectively bound [lo]. Hence radiocaesium binding in sediments can be described by the following ion-exchange reaction with the frayed edge sites (FES) on illite [91: FES - NH;

+ CS'

@a"<

H

FES-CS' + NH;

Under natural freshwater conditions, with negligible stable caesium concentrations (fraction of FES occupied by Cs + 0 and by NH; + l),the radiocaesium Kd (= [FES-Cs+l/[Cs'l) is related to the dissolved NH; concentration, on a log-log basis, according to the linear relationship:

in which [FESI is the frayed edge site capacity of the sediment (meq g-') and describes the preference of the FES for Cs' relative to NH:. The log Kd- log NH; plot of the in situ data for the investigated sediments (Fig. 5, [91) clearly indicates that the data follow a straight line with

cslNHd the selectivity coefficient that

136

Devoke, February 1992

(a)

activity 0

500

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3500

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Devoke, February 1992 concentration [pM] 0

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Fig. 4. Profiles of 13%sand 13ks in the solid phase and 137Csin pore water (a) and profiles of K+and NH; in pore water (b) in the sediment of Devoke Water (Cumbria, UK, [Comans et al., in preparation]).(a) = i37Cs in solid phase; 0 = dissolved 1 3 b ; A = 13%sin solid ; = dissolved NHZ. ' phase; (b) 0 = dissolved K

137 5 ,

1

4

G 3 X

2

n Y

0)

2

2

0

1

3

2

4

log NH4+ [Clmolesll]

Fig. 5. In situ 13’Cs distribution coefficients between sediments and pore water (Kd values) as a function of the pore-water NHI concentration in four widely different western European lakes [9]. 0 = Ketelmeer; A = Hollands Diep; 0 = Esthwaite 1991; = Esthwaite 1992; 6 = Devoke; = Devoke water column.

a slope close to (but significantly steeper than) -1. The vertical variation in the plot is about one order of magnitude or less in Kd and suggests that the product of the selectivity coefficient and the concentration of the caesium selective (frayed edge) sites in all of these European sediments would also show a limited variation. The intercept e l N H , [FESI can be independently measured when the FES are “isolated” by blocking all other exchange sites in sediments with AgTU. Using this procedure, Wauters [71 has measured e l N H 4[FESI for the sediments in Fig. 5. The results of these measurements are included in Table 1and show that the values vary indeed by no more than a factor of 3. The interpretation of the radiocaesium &s in Fig. 5 on the basis of equation (2) clearly shows that 137Csin the aquatic environment obeys ion-exchange theory. The ion-exchange model then allows the solid-liquid distribution coefficient (&) of this radionuclide in radiological assessment models to be predicted from environmental variables, rather than to be erroneously treated as a constant. The radiocaesium & in freshwater sediments can be predicted, within acceptable limits, on the basis of the quantity of highly selective

138

exchange sites and the pore-water NH; concentration. Figure 5 and Table 1 show that the variation in the former property is limited for widely different W. European sediments. This observation implies that, in situations directly following a nuclear accident, a first estimate of the sediment & for radiocaesium in a particular aquatic ecosystem can be made solely on the basis of estimates of the dissolved ammonium concentration in the sediments. Except in stratified lakes, where NH; reaches high concentrations in lake water, dissolved K' is generally the more important competing ion to evaluate the Kds for radiocaesium in the water column. We have shown earlier [11,12] that radiocaesium migrates slowly into the interlayers of illite from which it is difficult t o displace. This apparent fixation proceeds faster at low levels of competing cations, i.e. at high & values. The same process effectively increases [FES] over time. The effect of this process is apparent in the log Kd - log NH; plot (Fig. 5) in that the in situ Kd values are generally higher than the values predicted on the basis of (short-term) laboratory measurements of gaH4 [FESI. Moreover, the faster migration into clay inter-layers in high & (i.e. low NH4)environments may also be reflected in the slope of the data in Fig. 5, which is significantly steeper than -1 (--1.4).We also note that the Esthwaite and Devoke sediments, which have relatively low ammonium in their pore waters, deviate more from the predicted Kd values than the Hollands Diep and Ketelmeer sediments, which have pore-water NH, concentrations in the millimolar range and have in situ &s which are quite close to the predicted values. The exchangeability (i.e. availability) of sediment-bound radiocaesium clearly needs further investigation because of its relevance for the assessment of risks of remobilisation and uptake by aquatic biota. However, the observation that the large variability in total &s (Fig. 51, which do not take a limited exchangeability into account, is consistent with predictions by ion-exchange theory (Eq. 2) suggests that a substantial fraction of radiocaesium on the sediments may be exchangeable within time scales relevant for its partitioning between solids and pore water in sediments (months to years). We are presently investigating this issue in detail, 4. CONCLUSIONS

In situ sedimenuwater distribution coefficients, or Kdvalues, for radiocaesium in four very different western European lake sediments show a large variation both between and within sediments. The Kd values in all sediments show a strong decrease with depth beneath the sedimenuwater interface, which coincides with a strong increase in the pore-water NH; concentration. The variability in the measured in situ & values can be quantitatively explained by a competitive ion-exchange process between radiocaesium and ammonium ions on highly selective binding sites at the frayed edges of illitic

139

clay minerals, showing that the mobility of radiocaesium in sediments follows ion-exchange theory. The ion-exchange model relates in situ Kd values to fundamental properties of the sediments: the concentration of highly selective binding sites for radiocaesium (frayed edge sites on illite) and the concentration of the major ion competing with radiocaesium for these sites (the NH: ion). As the former property shows only a relatively small variation between the investigated sediments, a first estimate of the sediment & for radiocaesium in a particular aquatic ecosystem can be made solely on the basis of estimates of the dissolved ammonium concentration in the sediments. The result that the large observed variability in total &s for radiocaesium, which do not take a limited exchangeability into account, is consistent with predictions by ion-exchange theory suggests that a substantial fraction of radiocaesium on the sediments may be exchangeable within time scales relevant for its partitioning between sediments and pore water (months to years). This issue requires further investigation because of its relevance for the assessment of risks of remobilisation and uptake by aquatic biota. 5. REFERENCES 1. Cremers, A., A. Elsen, P. De Preter and A. Maes, 1988. Quantitative analysis of radiocaesium retention in soils. Nature, 335: 247-249. 2. Evans, D.W., J.J. Alberts and R.A. Clark, 1983. Reversible ion-exchange fixation of cesium-137 leading to mobilization from reservoir sediments. Geochim. Cosmochim. Acta, 47: 1041-1049. 3. Comans, R.N.J., J.J. Middelburg, J. Zonderhuis, J.R.W. Woittiez, G.J. De Lange, H.A. Das and C.H. Van Der Weijden, 1989. Mobilization of radiocaesium in pore water of lake sediments. Nature, 339: 367-369. 4. Mackereth, F.J.H., 1969. A short core sampler for subaqueous deposits. Limnol. Oceanog-r., 14: 145-151. 5. De Lange, G.J., 1986. Early diagenetic reactions in interbedded pelagic and turbiditic sediments in the Nares Abyssal Plain (western North Atlantic): consequences for the composition of sediment and interstitial water. Geochim. Cosmochim. Acta, 50: 2543-2561. 6. Das, H.A. and R.N.J. Comans, 1990. On the limits of low level measurements of 137Csas a natural radiotracer. J. Radioanal. Nucl. Chem., 139: 287-295. 7. Wauters, J., 1994. Radiocaesium in aquatic sediments: sorption, remobilization and fixation. Ph.D. thesis, Katholieke Universiteit Leuven. 8. Sawhney, B.L., 1972. Selective sorption and fixation of cations by clay minerals: a review. Clays Clay Miner., 20: 93-100. 9. Comans, R.N.J., J. Hilton, A. Cremers, P.A. Geelhoed-Bonouvrie and J.T. Smith, 1996. Predicting radiocaesium ion-exchange behaviour in freshwater sediments. (submitted). 10. De Preter, P., 1990. Radiocesium retention in the aquatic, terrestrial and urban environment: a quantitative and unifylng analysis. Ph.D. thesis, Katholieke Universiteit Leuven.

140 11. Comans, R.N.J., M. Haller and P. De Preter, 1991.Sorption of cesium on illite: nonequilibrium behaviour and reversibility. Geochim. Cosmochim. Acta, 55:433-440. 12. Comans, R.N.J. and D.E.Hockley, 1992. Kinetics of cesium sorption on illite. Geochim. Cosmochim. Acta, 56: 1157-1164. 13. Smith J.T. and R.N.J. Comans, 1996.Modelling the diffusive transport and remobilization of lS7Csin sediments: the effects of sorption kinetics and reversibility. Geochim. Cosmochim. Acta, 60:995-1004.

Freshwuter und Estuurine Rudioecribgy

Edited by C. Desmet et al. 0 1997 Elsevier Science B.V. All rights reserved

141

Microbially mediated redissolution of cesium radionuclides from the sediment of a shallow eutrophic lake S. Kaminskia, T. Richtera,M. Walsera, G. Lindnerband B. Schink' 'Fachhochschule Ravensburg-Weingarten, P.O. Box 1261,0-88241 Weingarten, Germany bFachhochschule Coburg, P.O. Box 1652,D-96406 Coburg, Germany 'Fakultat fur Biologie, Universitat Konstanz, P.O. Box 5560, D-78434 Konstanz, Germany

ABSTRACT In Vorsee, a small and shallow lake in the prealpine area in Germany, a seasonal cycling of dissolved cesium radionuclides and ammonium ions in the lake water was observed, resulting in concentration maxima in winter. Laboratory experiments demonstrated that part of the 137Csinventory of the sediment is readily exchangeable and that ion exchange with biologically produced ammonium ions is the dominating process for the release into the lake water. It is proposed that the seasonal cycling is the result of two contrary processes, on one hand the flux from the sediment into the water throughout the year due to microbial decomposition of organic matter and on the other hand the incorporation of dissolved cesium into organic matter in the water due to biological production in summer combined with the consumption of ammonium by plants.

1. INTRODUCTION

The prealpine area where Vorsee is located was one of the areas in Germany with the highest Chernobyl fallout deposition (about 30 kBq/m2137Cs).Because of persistently high 137Cscontaminations of some fish species in this lake (e.g. 1500 Bqkg in pike in 1990) and its use as a favourite fishing water, the concentration of dissolved 137Csin the water has been measured since 1990. A seasonal cycling of the 137Csconcentration peaking in winter was observed which was attributed to redissolution from sediment i1-41. A similar cycling is concentrations known from Par Pond, South Carolina, but with elevated 137Cs

142

in summer, which was attributed to the redissolution of 137Csfrom the sediment by ion exchange with ammonium ions which peak in summer under anoxic conditions [51. Comans et al. [61 also observed a postdepositional mobilization of 13'Cs from the sediment of Ketelmeer, Netherlands, probably caused by ion exchange with N H f which reaches high concentrations in anoxic pore waters. A number of field investigations and laboratory experiments were performed at Vorsee which should clarify whether also in this lake ion exchange reactions are responsible for the seasonal cycling of 137Cs: (a) monitoring of temperature, 13Tsand NHd in lake water, its inflow and outflow since 1990; (b) measuring of depth profiles of 13?Csand of temperature in the sediment; (c) measuring of depth profiles of 137Csand NHd in the pore water of the sediment; (d) sequential extraction of 137Csfrom sediments; (el stimulation of the microbial metabolic activity in the sediments by addition of nutrients at elevated temperature combined with measurements of extractability of 137Cs. The results of these investigations are presented and discussed in view of their possible importance with respect to microbially mediated processes in the radioecology of 13Ws. 2. MATERIALS AND METHODS

2.1. The study area

Vorsee is situated in the southern part of Germany (Fig. 1).It is a glacially formed, eutrophic lake at an altitude of 579 m with a surface area of 90000 m2, a mean water depth of only 0.6 m and a water retention time of 0.24years [7]. Due to its small depth it is never stratified and the water is always saturated with dissolved oxygen down to the sediment, except for periods with ice cover. The sediment has a very soft consistency down to a depth of 7 m, a very high water content (96% at 60 cm depth) and consists mainly of organic matter (70% at the surface, 55% at 60 cm depth). In summer, Myriophyllum spicatum covers half of the lake surface. The catchment with an area of 1.27 km2 is characterized by peats in the north and by meadows in the south. 2.2. Water samples

Surface water samples were taken with some interruptions weekly between June 1990 and January 1994 at three sites: the landing-stage, the northern inflow and the outflow (Fig. 1).For determination of the 137Csactivity, 25 1lake water were sampled. In order t o prevent adsorption of 137Cs to the walls of the sampling vessel, 10 ml of 0.1 M CsCl was added. In the laboratory, water

143

Fig. 1. Vorsee with sampling sites and its catchment area.

144

samples were filtered through paper filters, and dissolved lS7Cswas collected by coprecipitation on AMP (ammonium molybdophosphate) at pH = 4. The precipitates were analyzed by gamma spectrometry for 137Csusing HPGe detectors. Using 0.45 pm membrane filters instead of paper filters caused no difference in retention of 13'Cs on the filter. NHf was determined photometrically using a colour reaction with hypochlorite and salicylate ions (DEV, Deutsche Einheitsverfahren zur Wasser-, Abwasser- und Schlammuntersuchung, DIN 38406,12.Lieferung 1983,VCH Weinheim, Band 11);to this end about 100 ml water was filtered through a 0.45pm filter. Temperature and pH values were measured in situ. 2.3. Sediment samples

Sediment cores of a length of about 60 cm were taken between October 1993 and January 1994 from 5 locations (Fig. 1)with a gravity corer adapted to soft sediments, and sectioned into 10 cm slices. With one core, pore-water concentrations of 137Csand NHf were determined down to a depth of 40 cm. The pore-water samples were filtered through ordinary paper filters and one sample (10-20cm interval) through a 0.45pm membrane filter. No difference in retention of 137Csactivity was observed using a paper filter or a 0.45 pm membrane filter. 137Csand 13*Cs activities in sediment and pore-water samples were determined by gamma spectrometry and NHf concentrations photometrically. From September 1993 to January 1994,temperatures were measured in situ down to 150 cm sediment depth at the site "landing stage" using a specially constructed temperature sensor. 2.4. Laboratory studies

The geochemical association of cesium in the sediment was investigated using a sequential extraction procedure described in detail in Ref. [81.In five steps (i) directly exchangeable 13'Cs was displaced by ammonium ions (0.1M), (ii) carbonates were dissolved by pH-controlled addition of 5% hydrochloric acid, (iii) organic matter was removed by addition of 30% HzOz at 85"C, (iv) Fe- and Mn-oxides and -hydroxides were extracted by addition of 1 M NH40H.HC1in 25% (vh) acetic acid and (v) amorphous silicates were dissolved in hot (80OC) 0.1 M NaOH for 40 min. The remaining residue consisted of clay minerals, feldspars and quartz. Although the reliability of sequential extraction procedures is questionable, due to co-extraction from different components or incomplete extraction [91,at least the dominant geochemical associations or differences between sediments from different lakes can be determined. In order to study the dependence of 137Csremobilization on NH; concentration, about 150 g wet sediment was mixed with 200 ml volumes of 5 mM, 25 mM or 100 mM NH&l solutions, alternatively shaken for 5 hours or kept quiet for 27 hours.

145

The influence of stimulation of microbial activity on the extractability of 137Cswas studied with three sediment samples (wet weight 200 g) taken together with their overlying water. All three samples were kept at elevated temperature (30°C) over a period of two weeks (fermentation), but only two samples (nos. 1 and 2) were incubated with nutrient substrates (7 g peptone + 13 g yeast extract) prior to fermentation. One of the samples (no. 1) was extracted by ion exchange with NH; prior to incubation in order to remove the NH;-extractable fraction of 137Cs,This allows a discrimination between 137Cs release caused by microbial decomposition of organic matter or by ion exchange with microbially produced NH; during fermentation. If the latter process is dominant, the release after fermentation should be reduced in sample no. 1. 3. RESULTS AND DISCUSSION

Concentrations of I3'Cs and NH; in Vorsee water and its temperature measured between 1990 and 1994 are shown in Fig. 2. 137Csconcentrations increase with decreasing temperatures in autumn. In autumn, also increasing ammonium concentrations are observed. Enhanced values of ammonium in Vorsee water in winter were also mentioned by Zintz [7]; he explained them as a release from dying Myriophyllum spicatum, which acts as a predominant ammonium consumer in summer. We propose redissolution of cesium from the sediment as reason for its enhanced concentrations in winter, because cesium input by inflows can be neglected. The flow rate of the northern inflow with an average 137Csconcentration of 250 Bq/m3 (January 1994) is too low [71 and the 13?Cs

jul.

1990

jan.

jul.

1991

jan.

jul.

1992

jan.

jul.

1993

Fig. 2. Temperature, concentration of dissolved '37Cs activity, and concentration of ammonium ions in the water of Vorsee from 1990 to 1994.

146 TABLE 1 Fractions of 137Csextracted from different sediment samples after a five step extraction procedure Sediment 137Csactivity in the sediment relative

Lake Constance 1990 11700 f 510 Bqkg' 100%

Vorsee 1993 261 f 6.3 Bqkg' 100%

137Csreleased by Step 1 Step 2 step 3 Step 4 Step 5

(1.9f 0.41% (1.8f 0.51% (2.1f 0.41% (3.8f 1.01% (1.8f 0.31%

(5.2f 0.41% (4.1f 0.31% (3.6f 0.41% (2f 0.31% (2.6f 0.21%

Total

11%

17%

*Wetweight.

concentration in the southern inflow is less than 10 Bq/m3 (January 1994), which is small compared to 150 Bq/m3 in the lake (January 1994). The 137Cs concentration in the outflow coincides with that of the total lake. Most of the 137Cswas distributed in the upper 60 cm of the sediment with a maximum in about 20 cm sediment depth. The possibility of 137Csrelease from the sediment was proved by results of extraction experiments (Table 1).5.2% of the 13?Csinventory could be extracted by ion exchange with NH; and 17%of the 137Csinventory was released by all extraction steps. These fractions are larger than those obtained with Lake Constance sediments, where 137Csis mainly irreversibly bound to clay mineral particles [lo]. In order to explain 137Csmaxima in winter, it was assumed that a flux of 137Cs and NH; from the sediment into the water due to microbial decomposition of organic matter persists throughout the whole year, whereas the backflux of 137Csincorporated into organic detritus from the biological production in the lake is restricted t o the summer [lll.This conception is corroborated by the temperature distribution measured in the sediment: In autumn and winter, the temperature in the sediment is higher than in the water [ll]and even in January 1994 the temperature below 100 cm sediment depth was still above 10°C. In summer, the most abundant water plant Myriophyllum spicatum covers half of the lake surface and was considered to be the main sink of 137Cs. In this plant (without roots), a 137Csconcentration of 63 Bqkg d.m. was measured in summer 1993. Measurements of 137Csand NH; in the sediment pore water revealed 137Cs concentrations 5 times and ammonium concentrations two orders of magnitude higher than in the lake water, and show a distinct gradient (Table 2). These high concentrations corroborate the idea of a flux of both ions from the sediment into the water. In addition, the NH; concentration in the pore water seems to

147

TABLE 2 NH$ and 137Cs concentrations in pore water of a sediment sample at different sediment depths in Vorsee; comparison with NH$ and 137Csconcentrations in the surface water (November 1993). Standard deviations of the 137Csconcentrations are about 20% Sediment depth (cm)

NHt (mg/l)

137Cs(Bq/m3)

0-10 10-20 20-30

4.8 12.4 13.6

570 750 670

Surface water

0.05

120

be high enough to remobilize a substantial part of the NH;-exchangeable fraction of 137Csin the sediment. Approximately 0.5 mM NH; would easily counteract lo-" mM NH;-exchangeable cesium in 1 1 sediment. Another indication of a possible function of NH; ions in release of 137Csfrom the sediment comes from the relationship between the remobilized fraction of the 137Csinventory of the sediment and the concentration of NH; in pore water and in solutions, both in the field and in laboratory experiments described above, respectively (Fig. 3). In these experiments, the remobilized 137Csfraction varied between 3.6%and 5.2%for a shaking time of 5 h, and between 0.8%and 2.3%for a standing time of 27 h with 5 mM, 25 mM, and 100 mM NH; solutions. The logarithms of both quantities follow linear relationships in accordance with results of similar studies with Esthwaite Water sediment [12]. The majority of the results of the field measurements, i.e. the ammonium concentration in pore water and the cesium remobilization, obtained from the ratio of cesium concentration in pore water and in sediment, measured at different samples, agrees well with an extrapolation of the line fitted to results of the non-shaken assays. It was already demonstrated in earlier laboratory experiments that release of 137Csfrom Vorsee sediment can be enhanced by stimulation of microbial metabolic activity [31. These experiments were repeated with modified procedures as explained above. Fermentation without any other treatment (sample 3) released only 1.3%of the 137Csinventory, but fermentation after addition of yeast and peptone (sample 2) released 7.9% (Fig. 4). This difference proves again the importance of microbial activity involved in decomposition of organic matter and production of ammonium ions (sample 2: 60 mg/l NH; at the end of the experiment). In sample 1, however, in which also yeast and peptone were was removed before added, but where the NHf-extractable fraction of 137Cs fermentation, only 3.8%of the 137Csinventory was released by fermentation from Vorsee (Fig. 4).It is concluded from these results that release of 137Cs sediment is not mainly caused by dissolution of 137Csassociated with organic

148

s

h

v

I

extraction experiment

.-

-3 2i!!

.5

lo

f

extraction experiment

l--

0.1

z

f-

K

0

..

shaking time: 5h

..

field measurements

I

5

"'Cs activities in the supernatant afler ion exchanpe wilh NH,' fermentation

'2ion exchanpe with NH,'

-1:

sample 1

sample 2

afler fenenlalion

sample 3

Fig. 4. 137Csactivities in the supernatant of sediment samples after activation of microbial activity in the sediment and ion exchange with NHZ. Standard deviations are less than 10%. Samples were taken in November 1993. The i37Cs activity in each sample amounted to 39.4 Bq.

matter during its decomposition, but by ion exchange of previously adsorptively bound I3'Cs with N H f ions produced by fermentation. 4. CONCLUSIONS

Field measurements and laboratory experiments give strong indications of microbially produced N H f to be important in release of 137Cs from sediment into

149

lake water. The contribution of NH; ions introduced into the lake by its inflows due to agricultural NH: fertilization in the watershed, which was observed at the southern inflow, is considered to be negligible in that respect since concentrations in lake water always remain much smaller than in sediment pore water. Other ions have not been considered so far, but with respect to K, for instance, no enrichment in the pore water is expected since it is not a significant product of microbial metabolism. Therefore, the observed linkage between Cs and nitrogen transfer, which is mediated by microorganisms, is considered to be a rather general phenomenon in freshwater systems rich in organic matter. 5. ACKNOWLEDGEMENTS

These investigations were supported by the Ministry of Environment of the State Baden-Wurttemberg and by Deutsche Forschungsgemeinschaft within Sonderforschungsbereich SFB 248 “Cycling of Matter in Lake Constance”. 6. REFERENCES Lindner, G., I. Greiner, R. Grom, S. Kaminski, J. Kleiner, A. Kulikov, W.Pfeiffer, J.A. Robbins, 0. Seewald, 0. Smirnova and Ch. Wilhelm, 1992. Transport of Chernobyl radionuclides in freshwater lakes. Proc. Eighth World Congress of the International Radiation Protection Association, Montreal, pp. 1693-1696. 2. Lindner, G., I. Greiner, R. Grom, K. Hain, M. Ibler, S. Kaminski, J. Kleiner, W. Pfeiffer, J.A. Robbins, 0. Seewald, Ch.Wilhelm and M. Wunderer, 1991. Entfernungs- und Akkumulationsprozessevon Casium-Radionuklidenin Seen des Voralpengebietes. In: H. Jacobs and H. Bonka (eds), Strahlenschutz fur Mensch und Umwelt, Verlag T W Rheinland, Koln, pp. 271-276. 3. Lindner, G., S. Kaminski, I. Greiner, M. Wunderer, J. Behrschmidt, G. Schroder and S. Kress, 1993. Interaction of dissolved radionuclides with organic matter in prealpine freshwater lakes. Verh. Internat. Verein. Limnol., 25: 238-241. 4. Wunderer, M., U. Krinner and G. Lindner, 1993. Rucklosung von Casium-Radionukliden aus Sedimenten von Susswasserseen durch biogene AmmoniumIonen. In: M. Winter and A. Wicke (eds.), Umweltradioaktivitat, Radiookologie, Strahlenschutz, Verlag T W Rheinland, Koln, pp. 631-636. 5. Evans, D.W., J.J. Alberts and R.A. Clark, 1983. Reversible ion-exchange fixation of cesium-137 leading to mobilization from reservoir sediments. Geochim. Cosmochim. Acta, 47: 1041-1049. 6. Comans, R.N.J., J.J. Middelburg, J. Zonderhuis, J.R.W. Woittiez, G. De Lange, H.A. Das and C.H. Van der Weijden, 1989. Mobilization of radiocesium in pore water of lake sediments. Nature, 339: 367-369. 7. Zintz, K., 1986. Fischereiliche Nutzung von Stillgewassern in Naturschutzgebieten. Verlag Josef Margraf, Langen. 8. Robbins, J.A., G. Lindner, W. Pfeiffer, J. Kleiner, H.H. Stabel and P. Frenzel, 1992. Epilimnetic scavenging and fate of Chernobyl radionuclides in Lake Constance. Geochim. Cosmochim. Acta, 56: 2339-2361. 9. Forstner, U., 1985. Chemical forms and reactivities of metals in sediments. In: R. 1.

150 Leschber, R.D. Davis and P. L’Hermite (eds.), Chemical Methods for Aasessing Bio-available Metals in Sludges and Soils. Elsevier, London, pp. 130. 10. Kaminski, S.,1991.Radiocasium aus dem Tschernobyl-Fallout im Bodensee. GWF Wasser-Abwasser, 132:671-674. 11. Kaminski, S.,T. Richter, M. Walser and G. Lindner, 1994.Redissolution of cesium radionuclides from sediments of freshwater lakes due to biological degradation of organic matter. Radiochim. Acta, 66/67:433436. 12. Davison, W.,P. Spezzano and J. Hilton, 1993.Remobilization of Caesium from Freshwater Sediments. J. Environm. Radioactivity, 19: 109-124.

Freshwuter cmd Esruurine Rudioeecoloigy Edited by 0. Desmer et at. 0 1997 Elsevier Science B.V. All rights reserved

151

Migration and modelling of tritium in waste water reservoirs and a retention pond Masami Fukui Division of Fuel Cycle and Environment, Kyoto University, Noda, Kumatori-cho, Osaka 590-04,Japan

ABSTRACT An unusual but controlled release of tritium from the waste treatment reservoir at the Kyoto University Research Reactor Institute (KURRI) into a retention pond, occurred during October 1989. Treated liquid waste, 23 m3, in a reservoir tank, having tritium concentration of 2.0 x lo2 Bq cm3, was discharged into a monitoring reservoir. Dilution of the liquid waste in the reservoir tank with t a p water during discharge led to exponentially decreasing concentration.The maximum concentration, 3.0 x 10' Bq cm3, was recorded in the outflow of the monitoring reservoir. This waste water from the monitoring reservoir flowed into the southwest bank of the retention pond and the peak concentration decreased by about half due to initial mixing with pond water. The tritium arrived a t the outlet of the pond about 30 h aRer discharge, and the maximum concentration at the outlet was one fifth of the inlet concentration. Tritium concentrations in reservoirs were calculated using compartment models and those in the retention pond were calculated using the classical advection4ispersion model. Fair agreement was obtained between the calculated and measured values. These results provide not only estimates of dilution and mixing effects, but of the exposure dose to the public in future incidental releases.

1. INTRODUCTION

The release of radionuclides to aquatic systems may occur during an uncontrolled situation in nuclear facilities 11-31. Radionuclides, however, usually have been released under controlled situations and their concentrations are routinely monitored B-71. The Kyoto University Research Reactor (KURR)moderated with light water has been operated for about 70-80 h weekly at 5 megawatt thermal (MW*) since 1968.Tritium, at a low concentration, is the radionuclide usually detected in waste water derived from both the KURR cooling system and laboratories.

152

The tritium produced in light water reactors (LWRs) originates from ternary fission of the nuclear fuel, the activation of lithiumhoron isotopes, and (n,y) reactions with deuterium dissolved in the primary coolant. In general, the average release rate from boiling water reactors (BWRs) to the hydrosphere is estimated to be about 2.1 GBq per megawatt electric a year (MW,a) [8]. According to the 1982 report of the United Nations Scientific Committee on the Effects of Atomic Radiation [91, the river model used gave the collective effective dose equivalent based on the assumptions that the river is the source of drinking water within 50 km of the site, and that population density was 400 persons km-'. It has been pointed out, however, that collective dose commitments should not be applied to a given reactor with known discharge data in order to obtain estimates of health hazards and that site-specific data are required for meaningful surveillance programs [8,101. The purpose of this investigation was (1)t o measure the concentration and distribution of tritium (HTO)in a reservoir/pond that received effluent having HTO concentration significantly greater than the normal level of a few Bq cm3; (2) to estimate the arrivalhetention time and period that a conservative pollutant remains in the pond at the KURR aquatic system, and (3) to predict HTO concentrations in the reservoirs by the use of compartment models and HTO concentrations in the pond using the classical diffusion equation. An understanding of the HTO transport through the aquatic system is the first step toward evaluating the effect of radionuclides and/or pollutants on the food chain and the subsequent migration of hazardous materials through the environment [lll. Elevated HTO concentrations in the aquatic systems at the KURR site provided a unique opportunity to determine the movement of waste water. 2. SITE DESCRIPTION AND RELEASE CONDITION

The KURRI is located inland approximately 5 km southeast of Izumisano City near the Kansai International Airport built on a man-made island in Osaka Bay, Japan. The low level radioactive liquid waste has been stored in a 30 m3 tank before treatment such as flocculation and/or an ion exchange resin method. The HTO concentration in the KURR light water moderator had a constant value of about 2 x 10' Bq cm3 before May 1987. A small amount of heavy water leaked from a 2 m3 tank installed adjacent to the reactor core gradually increased the HTO concentration in the 30 m3primary coolant water five-fold within ten months of the supposed date of leakage. Recovery processes and surveys of the leakage point were carried out from September 1988 to March 1990 together with long-term air monitoring [12,131.This incident and the remediation activities associated with it led to an increase in the HTO amount released t o the KURR aquatic system. Figure 1 shows the average concentrations per year derived from the gross tritium activity and the waste

153

-concentratioi

1 ri'

.-

L 1987

1988

1989

1990

1991

1992

Fiscal year Fig. 1. Volume of waste water discharged (m3)and HTO activity (MBq) per fiscal year and the derived average concentration (Bq ~ m - ~ ) .

water volume discharged during the years since April 1987. The smallest discharge, 6.7 x 10' MBq, was recorded during the period from April, 1987 to March, 1988 (Fiscal Year (F.Y.), 1987) before the HTO leak had been recognized; whereas, amounts one to two orders of magnitude larger have been discharged yearly since F.Y. 1988, the total amount discharged for the six year period is estimated as 1.8 x 10' GBq. The main source of HTO discharged in the aquatic system, and reported here, was a small quantity of heavy water less than 2 x 10' cm3,that was taken from the DzO distribution system in the basement of the KURR building for chemical analysis. Its tritium concentration was 1.2 x 10' MBq cm-3 and it had been stored in an aluminum bottle but was carelessly discarded down a drain in a laboratory in September 1989. This led to an increase in the HTO concentration to 2.0 x lo2 Bq cm3 in the treated waste water, 23 m3 of which amount of radioactivity was 4.6 GBq in the reservoir before discharge. At the KURRI site the HTO concentration per single batch of effluent in the reservoir for the treated waste water has been lowered to less than 6 x 10' Bq cm3; equivalent to the average HTO concentration per quarterly release, as determined by the law for nuclear power regulation in Japan. The treated waste water of 23 m3was stored in a reservoir (hereafter, Res. A), after which it was discharged at the nominal flow rate of 10-20 m3h-' with dilution by tap water at a flow rate of 10 m3h-'. This led to a decrease in the HTO concentration in the effluent from Res. A with time . The mixing and discharge processes from

154

Ditch

0

v

U

0

T

0

S

0

Fiashboard

Retention pond (I m ai k e ) 0 0

Emergent

’ pExhaust i p e for

back washing

Reservoir for

-

72 m

-

20 m

(R0s.A)

Fig. 2. Sampling locations in Res. B (a-j) and in the retention pond (B-V).

Res. A lasted for about 8 h from 9:00on October 4,1989.The effluent from Res. A enters the location “enof another reservoir (Res. B: 10 x 7 m2 and 1 m deep) that has been used for monitoring waste water (Fig.2). Res. B receives not only treated liquid radwaste but domestic waste water at location “g“.The overflow (above the 1 m level) from Res. B (location “b”)enters a retention pond (named Imaike) at the inlet, E, in the southwest bank of the pond. During the investigation period the daily flow rates of the effluent from Res. B were measured with a continuous recording flowmeter near position A (Fig. 2) in the open channel with a cross section of 30 cm (depth) x 50 cm (width) in which flow rates (m3d-’) are given in Table 1.The flow velocity at position A in the channel was about 0.25 m s-l with ca. 4 cm deep when the treated radwaste

155 TABLE 1 Flow rate of waste water discharged into the retention pond Date (October 1989)

3

4*

5

6

7

8

9

10

Flow rate (m3d-’)

84

225

88

101

112

86

96

84

*Date of discharge of the treated waste water.

had been discharged and 0.2 m s-l with ca. 1 cm deep after the discharge termination. The recorded outflow from the Res. E was 225 m3 d-’ on 4 October (Table 1).This was more than twice that of the other days because of the discharge of the treated waste water from position “e”. The average flow rate for the 8 days after October 4 was estimated as 115 m3 d-’ using the recorded flow rates in Table 1. The 57 x 72 m2 pond is horseshoe-shaped (Fig. 2), and the average water depth is about 70 cm with a range of 50 to 100 cm. The impoundment and water volume of the pond respectively were estimated as 0.38 ha and 2.7 x lo3m3, and the estimated retention time of tritium in the pond as about 23 days (2700 m3/115m3d-’), assuming that there was no other inflow and there was complete mixing in the pond. 3. MONITORING PROCEDURE

The HTO concentration in the waste water effluent was five orders of magnitude higher than the background level in the aquatic environment. Moreover, the initial concentration of tritium in the pond derived from the previous discharge of waste water was negligible compared to the concentration in the waste water because it had taken place in August, two months prior to this discharge process. This indicated that the movement of tritium in the aquatic system could be traced without special treatment of the water samples. A 1 cm3 sample of the water therefore was pipetted directly into a vial containing 10 cm3 of scintillator and the vial placed in a liquid scintillation counter for 10 min (Aloka LSC-3500;detection limit: 0.2 Bq cm3) for the radiometric assay of tritium. The surface water samples were taken from points a-j in Res. B, except for “e” at which the effluent from Res. A enters. The water at “enwas monitored before it mixed with the water in Res. B. The effluent from Res. B was monitored at point A. Points B-V were selected for sampling because of ease of access and their proximity to natural landmarkers on the shore of the retention pond. Monitoring was done from October 4 to 11, usually twice a day, but with higher frequency near the inleuoutlet banks of the retention pond and at the beginning of the discharge process.

156

4. RESULTS AND DISCUSSION

4.1. Estimation of tritium concentration in effluentfrom reservoirs

The principal mechanisms that affect the migration and distribution of tritium in flowing surface waters are advection and dispersion. Sorption onto sediments is negligible and tritium has a relatively short biological half-life in an aquatic environment [14]. A single compartment model was applied in the form of semi-empirical expressions to describe HTO concentrations in Res. A and Res. B, because mixing and/or dilution through water movement is distinguishable in the near field of discharge. The mass balance of HTO for treated waste water in Res. A that is subject to dilution with tap water is: d(V,Ca)/dt = -qaCa

(1)

where V,, Ca,and qarespectively are the water volume, the HTO concentration, and the flow rate of the discharge from Res. A. The volume of the treated waste water in Res. A is given by:

where V,is the initial volume of the waste water in Res. A, qothe flow rate of the tap water into the reservoir used for dilution, and t the time elapsed after mixing. The HTO concentration of the effluent from Res. A is obtained by substituting both Eq. (2) and its derivative in Eq. (1): C, = C, (l-bt/a)'lb

(3)

where C, is the initial HTO concentration in Res. A, a is equal to VJq, and b is given by (qa- qo)/qo.If V, is unchanged, i.e., the discharge flow rate, q,, is equal to that for dilution, q,, the HTO concentration of the effluent from Res. A is: C, = Coexp(-qatN0)

(4)

The flow rate, q,, is not determined, but qois 10 m3h-'. The monitoring data for the effluent from Res. A then was fitted to Eq. (3) using the values of 200 Bq em3 for C, and 23 m3 for V,. As seen in Fig. 3,the HTO concentration in the effluent decreases rapidly, as the flow rate, q,, increases from 10 to 14 m3h-'. The best fit flow rate for the effluent from Res. A. was 10 m3h-'; i.e., qa was found to be approximately equal to qo. This led to V, being equal to V, in Eq. (2).Equation (4)then can be used for expressing the HTO concentration in the effluent from Res. A instead of Eq. (3)and gives the amount of HTO discharged with time M(t): M(t) = q a I Ca dt

= Vo ( C o - Ca)

(5)

157 200

I

I

I

I

I

I

I

I

I

I

I

n

T

E

u

m

150

W

C

.-c0, 2 100 c,

c al

u C

8

-

50

0 !I 0

0

100

200

300 400 500 Time elapsed after mixing (min)

600

Fig. 3. Evolution of HTO concentrations in waste water effluent from Res. A of qa

The effluent from Res. A flows into Res. B and is mixed with the influx of domestic waste water at location “g”.The overflowing waste water from Res. B then is drained off at point “b”.The mass balance of HTO in Res. B is

where qb is the flow rate of the effluent, vb the water volume (70 m3), and Cb the average HTO concentration in the effluent from Res. B that is obtained as Eq. (7) by solving Eq. (6)in which Eq. (4)has been substituted

The concentration,

cb,

becomes maximum at tmax:

Figure 4 gives the monitored concentrations in the effluent from Res. B and the predicted values calculated from Eq. (7). Setting qa at 10, 15 and 20 m3 h-’ gives the respective flow rates for domestic waste water (qb- qa)of 6,4.3 and 2.7 m3 h-’ for effluent flow rate of 225 m3 d-’ (Table 1).As shown in this figure the tritium values calculated from Eq. (7) for qa= 10 m3h-’, agree well with the monitoring data, which indicates accuracy of the discharge flow rate, qa, as estimated from Eq. (4)and showed a maximum concentration of 30 Bq cm3 at an elapsed time of about 3 h after release.

158 I

n

m

I

I

,

I

I

I

,

I

,

'E u

CT

m c

U

.-0

10'

c a u c 0 u 0

Flow rate (m3 h-')

1

1

\

-t 0

1

I

I

100

200

I

I

I

300

400

I

I

500

600

Time elapsed after discharge (min) Fig. 4. Evolution of tritium concentrations in effluent from the Res. B and calculated HTO concentrations using Eq. (7)with varying discharge rate, qa, and flow rate, q b - qa

After the termination of discharge of the treated waste water from Res. A into Res. B, the HTO concentration in Res. B should have decreased because of dilution by domestic waste water. Concentrations ranging from 1.53 to 1.83 Bq cm3, were found at the 10 locations a-j at 9:00 a.m. on 6 October, 40 h after the discharge. Of these locations, points a, e, h, and i, were selected for further monitoring to estimate the dilution effect by domestic waste water. The HTO concentrations at these locations decreased accordingto an attenuation rate 5.8 x lo-' h-' during the 27 h after 9:00 on 6 October, though no data are shown for the sake of brevity. On the basis of the attenuation rate estimated with a simple mixing model as expressed by Eq. (41, the flow rate of domestic waste water into Res. B was calculated as 97 m3 d-', which value is in good agreement with the recorded discharge flow rate from Res. B of 101 m3 d-' on 6 October (Table 1). This indicates that the dilution of tritium in Res. B can be estimated by assuming complete mixing in the case of an unexpected future release. In light of the above, the HTO concentrations in the effluent from Res. B for different types of discharge can be obtained: For a steady state inflow condition, i.e. Ca= Co(0< t ) , Cb = co qaqb' (1- exp(*btNb))

For a step release, i.e., Ca= C, (0< t c T ) and Ca= 0 (2' < t), O
Cb(t) = Co Qa qb' (1 - exp(*btNb))

t>T

Cb = Cb(t) - cb(t - T )

= c, qa Qb' kxp (QbTNb)- 1) eXp(qbtNb)

(10)

159 20 n

m

E

er a

15

Locations and distance from inlet

W

c

0 .CI

!

CI

c

10

8c

8: 10 m left side

C: 5 m left side

H E: Inlet

+

0 W

e I

0

A

F: 0.5 m right side

5

0

0

1

2

3

4

5

6

7

8

Time elapsed after discharge (days) Fig. 5. HTO concentration-time curves for locations near the inlet of the retention pond.

4.2. Monitored tritium concentrations in the retention pond and the calculated concentrations along the shoreline

The HTO concentrations in the retention pond were usually lower than the detection limit (0.2 Bq cm3) when measured for 10 min by the ordinary method without special treatment of the water samples, e.g. enrichment schemes. Figure 5 shows the concentrations of tritium near inlet E (Fig. 2) over a distance of less than 10 m as a function of time after the 4 October release. The maximum concentration in the effluent from Res. B, about 30 Bq cm3, was decreased by about half at points E and C due to initial mixing with the pond water. On the whole, the concentrations at these locations tended to reach the maximum concentration rapidly on the day of discharge because of the rather short period of discharge and then decreased with time because of advectioddiffision. Concentrations at locations G, H, I, J, and Kin the intermediate region along the shore of the pond are shown in Fig. 6. The HTO concentrations decreased toward the outlet of the pond, and the peak concentration was about 10 Bq cm3, approximately two thirds of the maximum concentration near the inlet, E. Figure 7 depicts decreasing HTO concentrations with distance from the inlet. The peak concentration at the outlet (R) was about 3 Bq cm3 30 h aRer

160

6

z- 1 s

v

I

Distance from inlet

-

C

0 .-c, !. c,

su

11.3 rn (G)

10

A

-

- + - 30.9 m (I)

C

0

/

u

0

!?

5 -

0

24.3 m (H)

A

/

38.1 m (J) 52.1 m (K)

\ \ \

‘\\ \ a \\

/

1

-+-

\ \

2

3

4

5

6

7

8

Time elapsed after discharge (days) Fig. 6. HTO concentration-time curves for locations between the inlet and outlet of the retention pond.

the release. This means that only 10% of the pond water (the ratio of inflow volume over 30 h to the entire volume of water in the pond: 280 m3/2700 m3) was displaced when the discharged tritium arrived at the point R. Lower peak concentrations than that at the outlet were obtained on the left side ( S , U, V) of the E-Q line (Fig. 2). At the location V, a concentration close to the detection limit was found 75 h after the release, indicating that the tritium had little spread to the northwest corner of the pond, near the point V. Consequently, as .is apparent from Figs. 5-7, the retention time for the tritium in this pond was 7 days or less. The HTO concentration distribution along the shoreline is shown as a function of time (days) in Fig. 8. The unexpected release of flushing water from a water purification facility, whose drain pipe is near the point M, lowered the concentration at the locations M, N, and 0 five days after the tritium release. Figure 8 also shows that the tritium arrived at location “J”on the first day of discharge was purged fkom the retention pond within 7 days of its release. This led to about 30% (115 m3 d-’ x 7 a2700 m3)of the pond water being involved in the migration of the nonreactive pollutant. A mathematical model for the release of contaminants in effluent near the shore has been proposed for the movement of effluent flowing parallel to the shore and a maximum concentration at the shore [151.The same model was

161 10

1

1

1

,

1

u

1

1

1

,

1

1

1

1

Locations and distance from inlet

n

? €

1

8

-

rn

-+ 0:83.1

W

-

B

0 0

S: 1 0 7 m -a - U: 89 m 0 V: 68 m A

rn

- + - Q: 98.1 rn

0-

m

M: 68.6 m

1

2

R: 1 0 3 m

3

4

5

6

7

1

11 8

Time elapsed after discharge (days) Fig. 7. HTO concentration-time curves for locations near the outlet of the retention pond.

used to estimate the concentrations at fured points along the shoreline, our main interest, because the data described previously suggested that the main flow was along the shore on the right side of the E-Q line. Neglecting difision in the direction of travel 111, the relative concentration distribution for a line source, allowing for the"reflection" of the plume by the shoreline, is CIC, = 0.5 [erf Kh-y) / a s y )+ erf I(h+y)/ fiS,)l

(11)

where S,, the standard deviation of plume growth, is 0.1 x (m) as a crude approximation [ E l , x the distance from the source, h the width of the source located at the shore calculated from the estimated volume of waste water (287.5 m3 = 4.6 GBq/l6 MBq/m-3),y the perpendicular distance from the shore (4.8 m = 287.5 m3/(2x30m length, 1 m deep)); and C, the initial concentration in the pond near the inlet. At the shore (y=O), the shore concentration, C,, is rewritten as

The results calculated with Eq. 12 together with the observed values are shown in Table 2 at four locations for distances greater than 50 m from the inlet; K, M, 0, and Q. The concentrations observed near the outlet were less than those

162

20 n

7

6CT 15

m

W

C

.-c0, c1

10

C

Q)

u

C

8

s

0

5

0

BCE

-20

0

G

H I 20

J 40

K L M N O P 60 80

Q R 100

120

Sampling locations and distance from the inlet (m) Fig. 8.

HTO concentration distribution along shoreline of the retention pond for various

times t.

TABLE 2 Observed and calculated tritium concentrations along the shoreline of the pond Location

K

L

0

Q*

Distance (m) C , observed (Bq cm3) C$Co observed C$C, calculated ratio of C$Co (CalculatedObserved)

52 9.0

69

83 3.6 0.22

98 2.1

0.56 0.64

1.1

4.5

0.28 0.51 1.8

0.44 2.0

0.13

0.38 2.9

*Near outlet of the pond.

calculated, suggesting dilution effect by the unexpected release of flushing water from a water purification facility near point M, as mentioned above. A diffusion model, however, used because of its relative simplicity, gave calculated concentrations of a fair degree of accuracy;i.e. less than a factor of three at the shoreline (Table 2).

163

5. CONCLUSIONS

Nuclear facilities may occasionally release more tritium to aquatic systems than is released under normal operating conditions. Such releases, although not significant in terms of health, can serve as field experiments both for obtaining site-specific data for a radiological impact assessment and for taking countermeasures against the accidental release of radionuclides in fresh water ecosystems. The following conclusions were drawn concerning the mixing and movement of water in two reservoirs in series and a retention pond at the KURRI site. 1. The concentration of waste water in Res. A having initial concentration, 200 Bq cm3, decreased exponentially as predicted by a dilution model for a flow rate of 10 m3 h-' for both the inflow of tap water and the effluent from the reservoir. 2. After the tritium waste water entered the monitoring reservoir (70 m3),it became mixed with sewage waste water. The peak HTO concentration in the effluent released to a channel adjacent to the retention pond was about 30 Bq cm3 at 3 h after release. The discharge of the waste water lasted for 8 h at a flow rate of 10 m3h-' which was determined from fitting the model predictions to the measured tritium concentrations. 3. The maximum concentration of tritium in the effluent from the monitoring reservoir was decreased by about half (16 Bq cm3) due to initial mixing with the pond water. The tritium arrived at the retention pond outflow, a distance of about 100 m along the shoreline, 30 h after its release, and it took 7 days to be purged from the pond at the average inflow rate of 115 m3 d-'. About 30% of the water volume was estimated as being involved in the tritium migration in the retention pond. 4. The peak concentration in the effluent from the pond was one fifth (ca. 3 Bq cm3) of the initial concentration found near the inlet, and concentrations at locations along the shoreline could be predicted within a factor of three using the classical advection-dispersion equation. 6. REFERENCES 1. 2.

3.

Veska, E. and B.L. Tracy, 1986. The migration of reactor-produced tritium in Lake Huron. J. Environ. Radioactivity, 4: 31-38. Champ, D.R., R.M. Brown, E.L. Cooper and R.J. Cornett, 1990. Emergency response to a spill of tritiated heavy water; the interface between emergency response, routine monitoring and research. IAEA-SM-31619. IAEA, Vienna, pp. 23-38. Hamby, D.M., R.P. Addis, D.M. Beals, A.L. Bani, J.R. Cadieux, Jr., W.H. Carton, D.L. Dunn, G . Hall, D.W. Hayes, J.D. Heffiner, R. Lorenz, M.V. Kantelo and R.W. Taylor, 1993. Environmental monitoring and dose assessment following the December 1991 K-Reactor aqueous tritium release. Health Phys., 65: 25-32.

164 4. Ophel, I.L., 1973. The environmental capacity of freshwaters for waste radionuclides. IAEA-SM-172/45. IAFA, Vienna, pp. 613-624. 5. Hayes, D.W., Tritium in the Savannah river estuary and adjacent marine waters. IAEA-SM-232f80, IAEA, Vienna, pp. 271-281. 6. Langhorst, S.M., J.S.Morris and S.R. Bull, 1981.Tritium monitoring methodology and application at a research reactor. Health Phys., 40: 823-827. 7. Miller, C.W., W.D.Cottell, J.M. Loar and J.P. Witherspoon, 1990. Examination of the impact of radioactive liquid effluent releases from the Rancho Seco nuclear power plant. Health Phys., 58: 263-274. 8. UNSCEAR, 1988.Sources, Effects and Risks of Ionizing Radiation. United Nations Sales, Publ. No. E.88.IX.7, New York. 9. UNSCEAR, 1982. Ionizing Radiation: Sources and Biological Effects. United Nations Sales, Publ. No. E.82.IX.8, New York. 10. Voshell Jr., J.R.,J.S.Eldridge and T.W. Oakes, 1985. Transfer of 137Csand “Co in a waste retention pond with emphasis on aquatic insects. Health Phys., 49: 777-789. 11. Juanico, M., R. Ravid, Y. Azov and B. Teltsch, 1995. Removal of trace metals from wastewater during long-term storage in seasonal reservoirs. Water Air Soil Pollut., 82: 617-633. 12. Fukui, M., 1992. Modeling the behavior of tritiated water vapor in a research reactor containment building. Health Phys., 62: 144-154. 13. Fukui, M., 1993. Development of a convenient monitoring method for tritiated water vapour in air using mall water basins as passive samplers. Radiat. Prot. Dosim., 48: 169-178. 14. Blaylock, B.G. and M.L. Frank, 1979. Distribution of tritium in a chronically contaminated lake. IAEA-SM-232/74, IAEA, Vienna, pp. 247-256. 15. Csanady, G.T., 1970. Dispersal of effluents in the Great Lakes. Water Res., 4: 79-114.

Freshwuter und Estuarine Rudioecology Edited by G. Desmet et al.

0 1997 Elsevier Science B.V. All rights reserved

165

Solid phase speciation of radiocaesium in bottom sediments J. Wautersa,M.J. Madrugab,M. Vidalb and A. Cremersa aLaboratory of Colloid Chemistry, Katholieke Universiteit Leuven, Kardinaal Mercierlaan 92, 3001 Heverlee, Belgium bDGAIDPSR, 2685 Sacavbm, Portugal

EXTENDED ABSTRACT One of the key issues to be resolved if we wish to forecast the behaviour of radiocaesium in freshwater bodies is the identification of the sorption pool, responsible for the radiocaesium sorption and the selectivity factors governing sorption in that pool. Radiocaesium may be adsorbed either in the micaceous Frayed Edge Sites (FES) characterised by a very high caesium selectivity, or the sites in the Regular Exchange Complex (REC), i.e. clays and humic acids, characterised by a relative low caesium selectivity. The partitioning of radiocaesium between FES and REC depends on the relative values of the respective sorption potentials, defined as the product of pool capacity and Cs to K (or NH4) selectivity coefficients. A comprehensive characterisation study was carried out on some 75 sediments (riverine, lacustrine and estuarine), originating from various locations in Europe and covering a wide range in textural properties. Sediments were characterised in terms of cation exchange capacity (CEC), FES capacity, caesium ion selectivity in the FES (with respect to K and NH4) and exchangeable K and NH4 contents. It is shown that, on average, the FES represents some 4 (k2)% of the CEC and that the ratio of FES capacity to the amounts of exchangeable K and NH4 in the REC is about unity. This means that the capacities of the two sorption pools are nearly equal in value. Both pools are however characterised by very large differences in radiocaesium ion selectivity. For the FES, the trace CslK selectivity coefficient is about lo3; the trace Cs/NH4 selectivity coefficient is about 2. lo2. These coefficients are some two orders of magnitude lower in the REC: K&Cs/K)and KJCdNH4) are about 5 in the clay fraction and about unity in the humic acid pool. Consequently, the radiocaesium sorption potential of the REC represents some 1to 2% of that of the FES and it can be concluded that the radiocaesium sorption behaviour in sediments is ruled by the properties of the FES. Predictions of in situ short-term Kd values can accordingly be based on FES characteristics of the sediment.

Full paper in Science of the Total Environment, 187 (1996)121-130

Freshwurer und Estuurine Rudioecology

Edited by G . Desmet et al. 0 1997 Elsevier Science B.V. All rights reserved

167

Redistribution of sedimentary 137Csin small Swedish lakes after the Chernobyl fallout 1986 K. Konitzer and M.Meili Znstitute of Earth Sciences, Uppsala University, Norbyvagen lBB, 752 36 Uppsala, Sweden

ABSTRACT The horizontal distribution of sedimentary 137Cswas examined from sediment cores in six Swedish lakes with different morphometry to assess the long-term immobilization of 137Cscontamination after the Chernobyl nuclear accident in 1986. In 1993 the mean inventories of sedimentary 137Csin deep stratified lakes were about equal to the initial deposition in the area, while in shallow lakes mean inventories were all lower than the original deposition. Horizontal distribution patterns vary between different lake types. Deep lakes with a low ratio between the epilimnetic and maximum depth show a distinct focusing of contaminated particles towards the profundal zone of the lake basins with a loss of 137Csfrom littoral areas. In shallow lakes with a higher epilimnetic to maximum depth ratio, 137Csis more evenly distributed.

1. INTRODUCTION

Thousands of Swedish lakes have been strongly affected by radioactive fallout from the Chernobyl accident in 1986 (up to 200 kBq 137Csm-') resulting in heavy contamination of biota, water and sediments [1,21. Most of the 137Cs entering lakes was rapidly removed from the water column, with initial residence times of only about two months [3,41. As 13'Cs has a strong affinity for particles [5,61, the removal from the water column occurred either through adsorption to suspended particles followed by incorporation into the sediments [7,8] or direct adsorption to the sediments [91, while some fraction was rapidly removed from the lakes by hydraulic flushing [2,101. In small glacial lakes, the most common lake type in Sweden, the generally shallow water depth favours resuspension and horizontal redistribution of surface sediments [11,121. Cesium-137 is therefore likely to be subjected to repeated cycling between sediments and water. Remobilization of cesium from

168

lake sediments to the water column is expected to result in a much slower decline of 137Csconcentrations both in water and in biota 12,131. This led us to investigate the sediments of six small soft-water lakes with respect to the total storage and the horizontal distribution of 137Cs.The study was focused on vertical and horizontal transport processes of contaminated particles in order to estimate rates of "'Cs accumulation and redistribution and their implications for the recovery of the lakes from contamination. 2. EXPERIMENTAL

The lakes studied are located in central Sweden. The deposition of Chernobyl "?Cs in this area varied between 5 and 27 kBq rn-' [14], while fallout of 13'Cs left from nuclear weapon tests amounted to about 2 kBq m-'. The lakes are all small (0.11-0.86 km2)and low-productive. The maximum depths of the lakes range between 2 and 19 m. Theoretical hydraulic residence times vary between 0.04 and 1.2 years. Sediment samples were collected mainly in transects along two major axes of the lakes. The samples were taken with a gravity core sampler (Willner type) with an inner diameter of 6.5 cm. The cores (25-30 cm) were divided with a slicing device, mainly on site, into sections of 5-50 mm, the thickness increasing with depth. All samples were analyzed for water content and 137Cs.The water content was determined by weighing sediment samples in preweighed scintillation vials before and after freeze-drying. Dry samples were homogenized and analyzed for 137Csby sodium iodide (NaI) detector gamma-ray spectrometry (Intertechnique Model 4000 Gamma Counting System). The system was calibrated against Chernobyl-fallout-contaminateddry reference material. The 137Cs activity of this material has been determined by intercomparisons with several other laboratories using different types of gamma-ray detectors, using both dry and wet standard reference materials. Measured activities of 13'Cs were corrected for radioactive decay to 1 May 1986 in order to allow comparison with the initial Chernobyl fallout. Activity concentrations were also corrected for background radiation from natural radionuclides in the sediment. These background values were based upon weight-specific values observed at sediment depths >20 cm. 13'Cs inventories for each core were calculated by summing the total amount of 137Csin each section of a core from the surface to the deepest sampled level. 3. RESULTS AND DISCUSSION The inventories of sedimentary 137Csin the six lakes varied between 4 and 21 kBq m-'. These average area-specific inventories were calculated by weighting

169 Cs-137 inventory (kBq m2)

1 Epilimnion Mixing depth

h

E

Y

sQ a

n

Hypolimnion

I I I

I

t

+50...+96%

Fallout 1986 (4.5-24 kBq m-') Sediment inventory 1992 I93 (4.5-21 kBq m-2)

Cs-137 inventory (kBq m-') 6

Loss I Accumulation - = ,

I

b

Erosion zone

-15...'+10%

Y

I

-15...+15%

Epilimnion

Mixing depth Burial zone

Hypolimnion

I

L-i8;:i6

(16-27 kBq m-2) Sediment inventory 1992 193 (9.5-10.5 kBq m-')

Fig. 1. Redistribution of sedimentary Chernobyl '37Cs in lakes with different morphometry: loss and accumulation in different depth zones relative to the area -weighted mean sediment inventory of '37Cs in lakes with an epilimnetic to maximum depth ratio <0.4 (top) and >0.4 (bottom).

170

the mean inventories from different bathymetric depth zones according to the proportion of sediment area in the zone. The inventories of sedimentary 137Cs were correlated to lake morphometry. In deep lakes (>8m) the mean inventories were about equal to the initial fallout of 13'Cs in 1986 (Fig. 1).In shallow lakes (<7m), the amount of 137Csstored in the sediments was 40-70% less than the initial deposition on the lakes (Fig. 1).Shallow lakes normally have a short hydraulic residence time and the apparent 137Cslosses are probably due to initial hydraulic flushing of the lakes by a heavy spring flood in 1986 [10,151. Within lakes, the area-specific inventories varied among different localities with maximum to minimum ratios ranging between 1.9and 20.9 in different lakes. Low ratios were found in shallow well-mixed lakes where 137Csis horizontally evenly distributed in the sediments. In deep stratified lakes 137Cs inventories between different sites were more variable with the highest values occurring in the profundal zone of the lakes. The horizontal distribution of 137Cswas assessed by comparing mean areaspecific inventories from different bathymetric depth zones to the mean inventory of the lakes. The largest difference between littoral and profundal sedimentary 137Csinventories was found in lakes where the epilimnion during the period of maximum stratification is shallow (<40%) in relation to lake maximum depth. In one of these lakes, the accumulation of 137Csin the profundal zone exceeded the mean inventory by as much as 96%, and in the other lakes by 50-70%. The accumulation of 137Csin the deepest part of the lakes was accompanied by losses from littoral zones of between 15 and 50%. This high variability of 137Csinventories between different depth zones suggests that 137Cshas been substantially redistributed during the six to seven years following the fallout. In well-mixed lakes, where the late-summer epilimnion accounts for more than 40% of the maximum depth, 13'Cs is more evenly distributed with no significant patterns of net losses or accumulation. The long-term consequence of sediment redistribution is most likely a delayed recovery of contaminated lake ecosystems:The long-term removal of 137Cs from the water column will be largely controlled by sediment resuspension and redeposition. In shallow lakes the burial process will be slow but may be accompanied by a net export. In deep lakes redistribution and focusing of 137Cs is likely to result in an eventual burial of 137Csin the least bio-active areas which reduces the potential uptake in the food chain. 4. ACKNOWLEDGEMENTS

We are grateful t o Lena Braf and Johan oholm, County Administration in Gavle, and to Eva Wass, h a Jadelius and Malin Kanth, Institute of Limnology, Uppsala University, for their assistance in sampling and analysis of sediment samples. Financial support was provided by the Swedish Radiation Protection Institute.

17 1

5.REFERENCES 1. Moberg, L. (ed.), 1991. The Chernobyl Fallout in Sweden. Swedish Radiation Protection Institute, Stockholm, 631 pp. 2. Andersson, T. 1993. Mercury and radiocesium in Swedish lakes. Ph.D. thesis. Dept. of Physical Geography. University of Umei, Sweden, Gerum N r 18. 3. Meili, M., 1988. Radioactive caesium in Swedish forest lake ecosystems after Chernobyl: Zooplankton 1986, Sediment 1988. Proceedings of the 5th Nordic Seminar on Radioecology, Riittvik, Sweden. 4. Kansanen, P.H., T. Jaakkola, S. Kulmala and R. Suutarinen, 1991. Sedimentation and distribution of gamma-emitting radionuclides in bottom sediments of southern Lake Paijanne, Finland, after the Chernobyl accident. Hydrobiologia, 222: 121140. 5. Evans, D.W., J.J. Alberts and R.A. Clark 111, 1983. Reversible ion-exchange fixation of 13’Cs leading to mobilization from reservoir sediments. Geochim. Cosmochim. Acta, 47: 1041-1049. 6. Cremers, A., A. Elsen, P. De Preter and A. Maes, 1988. Quantitative analysis of radiocaesium retention in soils. Nature, 335: 247-249. 7. Robbins, J.A., G. Lindner, W. Pfeiffer, J. Kleiner, H.H. Stabel and P. Frenzel, 1992. Epilimnetic scavenging of Chernobyl radionuclides in Lake Constance. Geochim. Cosmochim. Acta, 56: 2339-2361. 8. Wieland, E., P.H. Santschi, P. Hohener and M. Sturm, 1993. Scavenging of Chernobyl 137Csand natural zlOPbin Lake Sempach, Switzerland. Geochim. Cosmochim. Acta, 57: 2959-2979. 9. Santschi, P.H., S. Bollhalder, K. Farrenkothen, A. Lueck, S. Zingg and M. Sturm, 1988. Chernobyl radionuclides in the environment: Tracers for the tight coupling of atmospheric, terrestrial, and aquatic geochemical processes. Environ. Sci. Technol., 22: 510-516. 10. Meili, M., A. Rudebeck, A. Brewer and J. Howard, 1989. Cs-137 in Swedish forest lake sediments, 2 and 3 years after Chernobyl, in: W. Feldt (ed.), The Radioecology of Natural and Artificial Radionuclides. Verlag TLJV Rheinland GmbH, Koln, Germany, Progress in Radiation Protection Series Vol. 22, pp. 306-311. 11. Konitzer K. and M. Meili, 1995. Retention and horizontal redistribution of sedimentary Chernobyl 137Csin a small Swedish forest lake. Mar. Freshwater Res., 46: 153-158.. 12. Ritchie J.C. and J.R. McHenry, 1990. Application of radioactive fallout cesium--l37 for measuring soil erosion and sediment accumulation rates and patterns: A review. J. Environ. Qual., 19: 215-233. 13. Andersson T. and M. Meili, 1994. The role of lake-specific abiotic and biotic factors for the transfer of radiocesium fallout to fish, in: H. Dahlgaard (Ed.), Nordic Radioecology -The Transfer of Radionuclides through Nordic Ecosystems to Man. Elsevier, Amsterdam, pp. 127-139. 14. Edvarson. K., 1991. Fallout over Sweden from the Chernobyl accident, in: L. Moberg (ed.), The Chernobyl Fallout in Sweden. Swedish Radiation Protection Institute, Stockholm, pp. 47-65. 15. Hlikanson, L., T. Andersson and A.Nilsson, 1992. Radioactive caesium in fish in Swedish lakes 1986-1988 - General pattern related to fallout and lake characteristics. J. Environ. Radioactivity, 15: 207-229.

Freshwuter und Estuurine Rudioecokogy Edited by G . Desmet et 01. 0 1997 Elsevier Science B.V. All rights reserved

173

Long-term kinetics of radiocesium fixation by soils A. Konopleva,A. Bulgakova,J. Hiltonb,R. Comans‘ and v. popova aZnstituteof Experimental Meteorology, SPA “Typhoon”,Lenin au. 82, 249020 Obninsk, Kaluga Region, Russian Federation bZnstituteof Freshwater Ecology, East Stoke, Wareham, Dorset, BH20 6BB, UK ‘Netherlands Energy Research Foundation ECN, Westerduinweg 3, P.0.Box 1, 1755 ZG Petten, The Netherlands

ABSTRACT Results of a one-year laboratory experiment on the kinetics of 137Csfixation on mineral (MS) and organic (OS1 and OS2) soils are presented. The soils were collected from different areas contaminated after the Chernobyl accident (Ukraine, Russia, UK). Three phases of fixation are identified: rapid sorption on highly selective sites, redistribution from non-selective to highly selective sites and solid-state diffusion of 137Csinto mineral particles. A model of cesium distribution processes is proposed and parameter values are evaluated. For modelling short term transport processes the use of an exchangeable 137Csdistribution coefficient is recommended.

1. INTRODUCTION

Cesium fixation and remobilization in soils and sediments are the key processes determining redistribution of this radionuclide in the aquatic environment. Although cesium sorption on minerals, soils and sediments has often been reported, the mechanisms and kinetics of underlying processes remain unclear. Also, the adsorption process is usually studied using very short (-1 day) or relatively short (days-weeks) equilibration times, even though the real equilibration time can be much longer (months) 111. In the present paper the results of a long-term investigation of 137Csfmation in soils are presented, possible mechanisms of underlying processes and mathematical modelling of cesium chemical speciation in soils are discussed.

174

2. MATERIALS AND METHODS 2.1. Soils

Three subsoils (5-10 cm) were used in experiments. The sod podzolic soil (MS) was sampled in the 10-km zone of the Chernobyl NPP (Benevka), the peaty soil (OS1)was sampled on the Devoke Water watershed, Lake District, UK, and the sod podzolic gley soil (OS2)was sampled on the Kojanovskoe Lake watershed, Bryansk region, Russia. Some properties of the soils are shown in Table 1. TABLE 1

Physical chemical properties of soils under study Soil

MS OS1 os1

pH (water)

4.0 4.2 3.5

C,, (9%)

1.6 30 23

CEC (mEd100 g)

20 72 69

Exchangeable cations (mEq/100 g )

K

Ca

0.5 0.9 1.1

3.7

1.4 5.5

2.2. Experimental procedure

The soils were air-dried and the size fraction c 1mm was separated by sieving. Soil samples (20 g ) were placed in plastic 250 ml bottles. 200 ml of lo3 M KCl solution and 1 ml of carrier-free 137Cssolution (pH 7)containing 2.0 kl3q of the radionuclide were added to each bottle. The experiment was performed at room temperature. The contents of the bottles were mixed continuously in a shaker during the first week of the experiment, then they were shaken periodically by hand. At intervals during the experiment, two bottles were taken for monitoring the 13?Csactivity and cation concentrations in the water phase and for the determination of the exchangeable 137Csand cation content in the solid phase. Cation concentrations were determined by atomic absorption spectrometry; y-counting of the 137Csactivity was performed with 1282-Compugamma counter. After centrifbgation (20 min at 3000 rpm) and separation of the water phase, exchangeable fractions of 137Csand cations were extracted from the soil with 160 ml of 1N ammonium acetate solution. The extraction time was 15 min. All the solutions were filtered through 0.45 nm filters. Selected water phase samples were then filtered through 1.6 nm filters which were y-counted to evaluate the colloidal fraction of "'Cs in the solution. Fractions of the colloidal 13'Cs were less than 3% in all the solutions and it was assumed that the role of colloids in sorption-desorption processes is negligible.

-

175

Cesium-137 sorption from ammonium acetate solution was carried out as follows. Two samples (20 g) of each soil were suspended in 160 ml of 1 N ammonium acetate solution. The suspensions were spiked by 1kBq of carrierfree 137Csand the amount of sorbed cesium was measured by monitoring the radionuclide activity in the liquid phase. The rate of 13'Cs fixation in the soil OS2 suspension as a function of potassium concentration in liquid phase was investigated as follows. Soil samples (10 g) were prewashed by KCl solutions with concentrations ranging from 0.01 to 0.1 MA and then placed in 250 ml plastic bottles. 100 ml of corresponding KC1 solution and 2.0 kBq of carrier free 137Cssolution were added. Bottles were continuously shaken for 1h and then exchangeable 137Cs was extracted from the soil with 80 ml of 1N ammonium acetate solution aRer centrifugation and separation ofthe water phase. The extraction time was 15 min. Cesium-137 desorption by ammonium acetate solution as a function of pH of the liquid phase was investigated with the soil OS2. Different amounts of concentrated NaOH or HC1 were added to the soil samples (10 g) suspended in 80 ml of 1N ammonium acetate solution to adjust pH values from 5 to 13. The next morning the suspensions were centrifugated and filtered, and 137Csactivity was measured in the liquid phases. 2.3. Calculations

The distribution coefficients of the total 13'Cs (Ft) were calculated as follows:

(et) and exchangeable

137Cs

and

where A. is the initial activity of 137Cs(Bq);A,, A,, are activities of 137Csin the water phase and in the first ammonium acetate extraction respectively (Bq); V is volume of the liquid phase (I); M is weight of the solid phase (kg). The selectivity coefficients of cesium-potassium exchange are calculated as follows:

[Cs].,, [We, are concentrations of exchangeable 137Csand potassium in the solid are concentrations of 137Cs phase, Bqkg and meqkg, respectively; [Cs],, and potassium in the water phase, Bq/l and meq/l, respectively.

[aw

176

3.RESULTS AND DISCUSSION 3.1. Time dependence of cesium distribution in soil-water system

Figures 1and 2 show fractions of 13?Csin the water phase and of the exchangeable 13'Cs as a function of time. In the soil OS1 suspension they decreased rapidly and in two weeks concentrations of 13'Cs both in the water phase and in the first ammonium extraction became lower than the detection limit. In the mineral soil MS the process was slower and it was possible to follow I3'Cs concentrations decreasing in the liquid phase over 210 days, and in the first ammonium acetate extraction over 380 days. After 380 days the system seemed to be near equilibrium. So, the time of I3?Csequilibration in the mineral soil suspension is about a year. During this period, the distribution coefficient of the total radionuclide increased from about 600 after 1h exposure to 20000 after 210 days (see Fig. 3).Thus, strictly speaking, the total cesium distribution coefficient cannot be used for mathematical modelling of migration processes with characteristic times less than several months. The distribution coefficient of the exchangeable cesium can be proposed as an alternative parameter. F$increased slightly during the first few days of the experiment and then remained constant within the limits of experimental error and soil sample variability. This parameter can only be used for prediction purposes with a model of radionuclide chemical speciation transformation,

0.011'

0

I

'

I

100

'

"

I

200

'

I

'

'

300

"

'

1

2

400

Time, days Fig. 1. Kinetics of 137Csfmation by mineral soil (MS). 1: Percentage of 137Csin water phase; 2: percentage of exchangeable i37C8 in soil.

177

0.01l 0

"

"

I

5

'

"

"

10

"

"

15

Time, days Fig. 2. Kinetics of 1 3 k s fixation by organic soil. 1: Percentage of I3'Cs in water phase; 2: percentage of 13ks in 1 N ammonium solution;3: percentage of exchangeable 13'Cs in soil.

which should be based on results of studies into mechanisms of transformation processes. 3.2. Mechanistic interpretation

Figure 1 shows that process of cesium fixation by soil can be characterized by three phases with different velocities. The first is almost instantaneous (characteristic time of several minutes) and occurs in both lo3 M KC1 and 1 N ammonium acetate solutions (Figs. 1, 2 and 5). These observations indicate that the first phase of cesium fixation is the cation exchange adsorption on highly selective adsorption sites. During the second phase, which is relatively slow (characteristic time of several days), exchangeable distribution coefficients and selectivity coefficients of Cs-K exchange increase with time (Figs. 1-4). This phase is, obviously, a result of the adsorbed cesium redistribution from low selectivity to more selective sites. Comparison of kinetics of cesium fwation by soils MS and OS1 from lo3 KCl and 1N ammonium acetate and by OS2 soil from KC1 solutions with different concentrations indicate that this redistribution occurs mainly in the solid phase of suspensions without mediation of the liquid phase. In the experiment with soil OS2, the portion of fixed cesium is approximately directly proportional to the portion of exchangeably sorbed cesium (Table 2).These observations can be interpreted in the f'ramework of the following hypothesis: a significant part of selective adsorption sites

178

50000 I

A 250 150 200 100 50

0 0

Time, days Fig. 3. Time dependence of distribution coefficients. 1: selectivity coefficient; 3: 1000@ for mineral soil MS.

40000

at(Vkg); 2: 100.f l (Vkg) and

1

30000 -

0

0.5

1

1.5

Time, days Fig. 4. Time dependence of distribution coefficients. 1: or organic soil OS1.

2

at(Vkg); 2 100.ax(Ykg); 3: lOOO.@

179

0

0.5

1

1.5

2

2.5

Time, days Fig. 5. Comparison of fixation '37Cs fixation by mineral soil MS from water and from 1 N ammonium solution. 1: Percentage of '37Cs in water phase; 2: percentage of '37Cs in ammonium solution; 3: portion of '37Cs in 1 N ammonium extraction.

TABLE 2 Cesium fixation in suspension of soil 052 as a function of potassium concentration in solution ~~

KCI concentration in solution (Mfl)

0.01

0.025 0.05 0.1

Portion of 137Csafter 1 h (%) Exchangeable

Fixed

20.2 29.5 35.3 40.7

40.1 31.9 22.9 11.7

located on the surface of clay minerals is screened by organic or other amorphous soil matter and not available for direct adsorption. Cesium initially adsorbed by the low selective sites on the surface of this organic material slowly migrates through the organic material to the high selective sites on the illite. An additional support to the hypothesis is lent by the dependence on pH of the cesium desorption in ammonium acetate solution (Fig. 6). The portion of desorbed cesium decreased along with soil organic matter dissolution at high pH values. The reduction in the amount of cesium in solution cannot be explained

180

desorbed 137-Cs, Y

151

i

10 -

5-

4

6

8

10

12

14

PH Fig. 6. '37Cs desorptionfrom soil OS2 by 1N ammonium acetate solution as a function of pH.

simply by an increase in the soil CEC as a result of the dissociation of functional groups on the organic matter. Organic adsorption sites are non-elective and a factor of 5 decrease in desorbed cesium requires an increase of about 50-fold in the soil CEC. The most probable interpretation of the data is an increase in the number of highly selective sites available for direct adsorption as a result of the dissolution of screening organic matter. The third phase of fixation is the slowest and is associated, most likely, with cesium diffusion into the body of the mineral particles, possibly through frayed edge sites (FES) of illitic clay minerals 131. This phase seems to be reversible because there are data indicating that the exchangeable cesium portion in soils does not decrease continuously, but to the certain stationary level, which remains constant at least for several years [1,21. 3.3. Modelling

The above observations allow us to improve the detail of previously published [4,5] models and t o propose a scheme of cesium distribution processes in soilwater systems (see Fig. 7). The main differences of this scheme from those published before are: (a) in the 3-box model proposed in Ref. [4] the second phase of cesium fixation is assumed to occur from solution and the third phase is assumed to be irreversible; (b) in the model proposed in Ref. [5] the second phase of fixation is assumed to be instantaneous and the chemical form (water-soluble or exchangeable) from

181

Fig. 7. Scheme of cesium distribution processes in soil-water systems. W = cesium in the water phase; EXCH = exchangeably sorbed cesium on non-selective sites (extractable by 1N ammonium acetate); HSSl = cesium sorbed on high selective adsorption sites available for direct adsorption; HSS2 = cesium sorbed on high selective adsorption sites screened by soil amorphous matter; FD = cesium fixed due to diffusion into solid phase; K1, K2 = correspondent equilibrium constants; ki = rate constants.

TABLE 3 Parameter values of the model of 137Csdistribution in soil-water system Parameter

Soil MS

Soil OS1

400 920 1.4k0.1 0.14f0.02 0.015f0.002 0.0018kO.0004

300 1450 1.3f0.2 -

which it occurs is not identified. The parameter values of the model for soil MS were estimated directly from the experimental data (Kl and K2)and calculated with a non-linear squares regression procedure (rate constants). For soil OS1 it was possible to estimate only three parameters K1,Kzand hi. The parameter values are listed in Table 3. 4. CONCLUSIONS

It is shown that the interaction of cesium with soils is characterized by three phases with distinctly different time scales: initially rapid uptake (characteristic time of several minutes); relatively slow intermediate uptake (characteristic time of several days) and the third phase with a characteristic time of several months. The initial phase is interpreted as the rapid cation-exchange

182

sorption on high selective adsorption sites located on the surface of soil particles; the intermediate phase is a result of cesium redistribution from non-selective to highly selective adsorption sites and the third phase seems to be associated with cesium diffusion in mineral particles. The scheme of cesium distribution processes in a soil-water system is proposed and the parameter values are evaluated. The distribution coefficient of the total cesium increased for about one year, while the exchangeable cesium distribution coefficient increased slightly during the first few days and then remained constant. So, Pdx is a more relevant parameter for modelling short-term transportation processes. 5. REFERENCES 1. Surkova, L.V. and R.I. Pogodin, 1991. 13'Cs speciation in soils polluted after the Chernobyl accident. Agrokhimiya, 4 84-86 (in Russian). 2. Yudintseva, E.V., T.L. Zhigareva and L.I. Pavlenko, 1983. Speciation of and l3'Cs in dernopodzolicsoils as a function of used fertilizer. Pochvovedenie,9: 41-46 (in Russian). 3. Cremers, A., A. Elsen, P. De Preter and A. Maes, 1988. Quantitative analysis of radiocaesium retention in soils. Nature, 335: 247-249. 4. Comans, R.N.J. and D.E. Hockley, 1992. Kinetics of cesium sorption on illite. Geochim. Cosmochim. Acta, 56: 1157-1164. 5. Bulgakov, A.A. and A.V. Konoplev, 1992. The role of chemical speciations of radionuclides in soils in their transfer to surface run-off. Proceedings of the International Symposium on Radioecology. Chemical Speciation - Hot Particles. Znojmo, October 12-16,1992.

Freshwuter und Estuurine Rudifiecf~logy

Edited by G . Desmet et al. 0 1997 Elsevier Science B.V. All rights reserved

183

Physical and chemical features of the Chernobyl nuclides migration processes in the rivers of Belarus A. Kudelsky, V. Pashkevicha,Ye. Petryayevb,S. Ovsyannikovab and G. Sokolikb aZnstituteof Geological Sciences, Academy of Sciences of Belarus, Minsk, 7 Zhodinskaya str., Belarus bBelarussian State University, Minsk, 14 Leningradskaya str., Belarus

ABSTRACT Data on the radioactive contamination of river systems in southeastern Belarus as a result of the Chernobyl accident are reported for the first time. Results covering several years’ work are presented giving levels of a number of radionuclides (Cs-134, Cs-137, Sr-90,Pu-238, Pu-239, Pu-240, Am-241 and “hot” particles) in water, suspended solid and bottom sediments. Estimates of the trans-border radionuclide removal with river runoff suggest that it is of minor importance compared to radioactive decay in the soils.

1.INTRODUCTION

According to Lyutsko et al. [ l l , caesium-137 and strontium-90 are responsible for, respectively, 7.16 x 10l6and 0.81 x 10I6Bq of the total activity of 185 x 10l6 Bq released as a result of the Chernobyl accident. Assuming that 70% of the radionuclides fell withh the territory of Belarus, then the caesium-137 and strontium-90 depositions were 5 x 10l6and 0.56 x 10I6Bq respectively. The total area contaminated by radionuclides is more than 15,282 km2, of which 1100 k m 2have a specific activity over 1.5 M Bq m-2, about 3600 km2with 1.5-0.56 M Bq m-’, and more than 9900 km2with 0.56-0.19 M Bq m-2. The contaminated lands are drained by the Dnieper river and its major tributaries (Pripyat, Sozh, etc.). Hence radionuclide transfer by river runoff is likely to be an important process for the natural decontamination of polluted lands. As a result, these rivers also constitute the most active transporters of secondary pollution in ecosystems, and contribute greatly to the formation of the internal radiation dose of the population (drinking water supply, consumption of fish and production of irrigated farming etc.).

184

2. SITE DESCRIPTION

The territory showing the maximum specific activity is situated in the southeast of Belarus (Gomel and Moguilev regions) and is drained (Fig. 1) by the Dnieper, the Pripyat and its tributaries, the Sozh and other smaller rivers (Bragumka, etc.). More than 50% of the discharge of the rivers is from snow melt. Groundwater and rainfall equally make up the remaining flow. The spring flood of the Pripyat is as high as 60% of the annual runoff. The summer and autumn low water makes up 24% and winter drought period 16% of annual runoff. The average annual runoff per unit of area is equivalent to 3.68 1 s-' km-' for the Pripyat basin, 6.341 s-l km-' for the Dnieper, 10.51 s-l km-' for the Sozh. River water dissolved solids do not usually exceed 280-500 mg/l. In spring, the total salt content is much lower (100-175 mg/l). Catchments of most of the river basins are extensively tilled (25% in the River Pripyat basin, 45% Sozh, 50% Iput). Morestation typically varies from

Fig. 1. Scheme of the river network in southeast Belarus in the zone of radioactive contamination. (1)Fliver network with a river water sampling site. Contamination of catchments:(2) radiocaesium levels 37-185 k Bq m-2, (3) radiocaesium levels 185-555 k Bq m-'; (4) radiocaesium levels, >555 k Bq m-2, (5) plutonium-239,>3.7k Bq m-2, (6) Chernobyl nuclear power station.

185

1615%but increases to 27% in the Iput and 79% in the Zhelon. The basins of many of the rivers contain high proportions of boggy areas (Pripyat 31%,Iput 11%, Ubort 48%). 3. METHODS

Bottom sediments and silts in running and standing waters were collected using a sampler developed at the Institute of Geological Sciences of the Academy of Sciences of Belarus [21. River waters were sampled directly without stirring bottom sediments; groundwater samples were taken from the bottom of previously constructed pits, with a depth 20-30 cm below the groundwater level. The volume of samples was between 50 and 100 1for river water and ca 10 1 for groundwater. Analytical studies of water and bottom sediment samples followed standard procedures [3]. Identification and evaluation of activities of Sr-90, Pu-238, Pu-239,240 and Am-241was carried out using common radiochemical methods [3].y-activity was measured on an "ORTEC" ADCAM-300 gamma-spectrometer equipped with a hyperpure germanium detector. Alpha-activity was measured on a Norland-560, and p activity on an RRK-I-OIA radiometer. Major cations were determined on an atomic absorption spectrometer AAS-1. 3. RESULTS

The history of radioactive contamination of river water by the Chernobyl accident falls into three periods: (i) pre-accident; (ii)primary aerosol contamination; (iii) decrease of initial activity and development of secondary effects. In the pre-accident period the Sr-90 activity of the Pripyat river was in the range of 0.0033-0.0185 Bq 1-', Cs-137 was about 0.0066 Bq 1-'. In the first days after the accident during the period of primary aerosol contamination radioactivity levels in water were very high. The Ubort river water sampled on 27 April, 1986 (36 hours after the accident) near the village of Krasnoberezhie (120 km from the Chernobyl station) showed extreme levels with the total beta-activity over 10110 Bq 1-' and high gamma emitter levels (Table 1). Among the isotopes identified in this sample, 14'Ce and % ' !e showed the highest activities. Similarly in May 1986, the total beta-activity of the Pripyat water in the Chernobyl nuclear power station region was over 3000 Bq 1-' [41. However by July/August 1986 it had decreased to 4-10 Bq 1-'. In the same way, the maximum activity (14.8 Bq 1-') of Sr-90 measured in the Pripyat water in May, 1986 decreased within a month to 1.10-1.85 Bq 1-'. The maximum Pu-239 concentration in the Pripyat water was 0.37 Bq 1-'. As the aerosol contamination decreased there was a general decrease ofthe river water activity (Table 1).These data are consistent with the data of Izreal et al. [4,5] and with the general tendency of reducing river water activity noted by Voitsekhovitch et al. [SJ.

186 TABLE 1 Radionuclides in the Ubort, Pripyat and Dnieper rivers River

Sampling Activity (Bq 1-l) date

Ubort 27.04.86 Pripyat 01.05.86 (Chernobyl) 02.05.86 06.05.86 16.07.86 Dnieper 03.05.86 (Kiev)

Ce-144

Ce-141

1-131

4465 370 -

1336 407 88.8 14.8 333

2109 4440 814 1295

-

37 -

-

Ru-103 Ru-106

Cs-134 (28-137

Zr-95 Nb-95

767

619 248 555 159.1 7.4 -

2923 407 1554 166.5 37 703

555 814 170.2 14.8 -

Ba-140

-

1406 2220 166 703

In 1987 in the middle section of the river Pripyat (towns of Pinsk and Turov) which drained slightly contaminated territories of Belarus and Ukraine, the river water activity ranged within 0.002-0.009Bq 1-’ for Sr-90and 0.023-3.82 Bq 1-’ for Cs137 (unpublished data, A.B. Chernyakhovsky and L.I. Rodionov). In the lower stretch (village of Masany, at the boundary with the Ukraine) after the river had crossed highly contaminated territories (Fig. 11, Sr-90and Cs-137 activities in river water were respectively, 0.48-33.88 and 33.64 Bq 1-’. In subsequent years, the river water activity at the latter site decreased to activities as low as 0.02-0.03 Bq 1-’ (for Sr-90)during drought periods, when groundwater sources became dominant. The highest Sr-90 activities (from 1.59 to 2.70 Bq 1-’) observed in 1987 occurred in waters of small rivers (Braguinka, Zhelon, Rozhava) draining lands with a high strontium contamination level, and in ox bow lakes (old channels) of the river Pripyat. The same distribution of maximum activities (0.6-2.45Bq 1-’) is also peculiar to (3-137. During the summer field seasons of 1991 and 1992 the authors collected and studied bottom sediment samples from the rivers Sozh, Dnieper and Pripyat (channel deposits), shoreline silt deposits (silty particles settled from flood water) and mud sediments from the bottom of creeks. It was established that Cs-134,137,Sr-90,Pu-239,240, Am-241and “hot”particles are present in the bottom sediments. Cs-137contributes most of the total gamma activity of the bottom sediments (as much as 80.5%, sample 43,Fig. 2). Cs-137 levels were 14.4 f 2.9 times Cs-134 levels. On the basis of the activity levels (Table 2) the following sequence can be deduced: bottom muds of submerged lands > shoreline silt deposits > channel coarse- and medium-grained sediments. Levels in Dnieper samples were generally much lower than in samples from the other two rivers.

187

Fig. 2. Eiver Pripyat sampling pattern. Sites of sampling: (1) channel sediments; (2) silt deposits;(3) creek bottom sediments;(4) sample reference numbers and year of sampling; ( 5 ) number of observation sites (profiles).

The highest levels of caesium contamination of channel sediments and shoreline silt deposits were normally found in the river Sozh. The highest Cs-137 activities were found in bottom muds of the Pripyat creeks (Fig. 2, Table 2), and high levels in the Sozh creeks. Even higher Cs-137 activities were found in the flooded lands of some small rivers of the Sozh basin (up to 80-85 kBq kg-I), which are more than 20,000 times the pre-accident levels of this isotope. Sr-90 activity in river sediments varied from 2.2-66.6 (silt deposits and channel sediments) and 407-7215 Bq kg-' (mud deposits of creeks). The activities of alpha-emitting radionuclides in bottom sediments of rivers were less

188 TABLE 2 Caesium-137 activity levels in the sediments of the Pripyat, Sozh and Dnieper rivers River

Activity range

mk)

Mean activity (BqAsg)

(a) Bottom sediments of creeks

l’ripyat Sozh Dnieper

402-20387 2 173-5455 22-1055

5038 3288 781

(b) Shoreline silt deposits

Sozh Pripyat Dnieper

244-2755 21-553 87-543

116 459 270

(c) Channel sediments

Sozh Pripyat Dnieper

48-359 13-255 8-69

210 127 36

than their activities in the soil cover of catchments, but higher than in river water (Pu-238 ranges from 0.05-9.10 Bq kg-’; Pu-239,240 -- from 0.13-28.13; Am-241- from 0.07-16.2 Bq kg-’1. Maximum accumulation of actinides was noted in bottom muds of the Pripyat creeks, near the mouth of the River Zhelon (Fig. 2, sample 43). “Hot” particles were found in many river sediment samples. Numbers were as high as 9004000 particles per kilogram and the activity varied in the range 2.8-23% of the total beta-activity of samples. Maximum concentrations of “hot” particles were measured in the bottom mud samples from the river Pripyat creeks near the mouth of the River Zhelon (sample 43). 4. DISCUSSION

The general pattern of the primary radionuclide contamination of landscapes and river systems of southeastern Belarus resulting from the stage of aerosol fallout will, in the next few years, undergo irreversible changes due to the physical decay of radioactive isotopes and to radionuclide redistribution and removals by rivers. The present (1990-1993) activity of (3-137 (average 0.73 Bq 1-’; range 0.069-2.45 Bq 1-’) and Sr-90 (average 0.71 Bq 1-’ range 0.03-2.70 Bq 1-’1 in water of Belarus rivers are hundreds of times less than the initial post-accident values. However they are still thousands of times higher than the pre-accident activities of these isotopes in surface water. The river water contamination observed now is mainly due to both dissolved radionuclide washout from the catchment surface and suspensions of eroded particles. The level of the water radioactive contamination is dependent on the catchment contamination (correlation coefficients are 0.7 for Sr-90 and 0.3 for

189

(3-137); the speciation of the radionuclides in the soil; the severity of catchment erosion; the rates of solid and liquid washout; the carrying capacity of water streams; the amount of turbidity and settled solids; etc. The relationship between the radioactivity of river water and contamination of catchments can be judged from the data of flood water studies. The Sr-90 activity of flood water within the amelioration system of Aravichy, where strontium contamination is over 11k Bqm-'(= 3 Ci km-2)was 13.812 Bq 1-' (sample 1209,April 1993).Flood water of the Pripyat itself (August 19931, draining territory upstream of the observation station of Mozr, with much lower Sr-90 contamination had a Sr-90 activity in water, after 24 hours settling, as low as 0.109 Bq 1-' (95%in solution, 5%related to solid suspensions). Equivalent values for Cs-137 in Aravichy were 0.230 Bq 1-' where radiocaesium Contamination of the soil was >1500 k Bq m-' (= 40 Cilkm') and in the Pripyat, with a contamination typically <185k Bq m-' (= 5 C h ' ) total Cs-137 activity was 0.347 Bq 1-'. Suspended particles <1--3 pm accounted for 33%of activity; 1-0.2 pm for 25%. The filtrate activity was 0.142 Bq 1-' (41% of the total Cs-137 activity). The value of the washout coefficients depends on the thickness of the surface runoff layer, i.e. the annual run-off volume divided by the catchment area (for the Pripyat basin it ranges from 60 to 100 mm a year), catchment surface slope, extent of bog and forest within catchments, soil cover type, etc. Laptev et al. [71 give values of normalized (to the sediment layer) coefficients of liquid washout ranging from 0.1 to 0.5 pm-' for Sr-90 and from 0.005 to 0.007 pm-' for (3-137 in the lower course of the River Pripyat (integral estimates 1987-1990). Estimated values of the sediment runoff coefficients for small rivers of the basin vary enormously from 0.003 to 2 pm-' for Cs-137. The activity transfer with suspended solids in rivers contributes significantly to Cs-137 migration. According to Voitsekhovitch et al. [6], in 19871991, 30-40% of the total annual activity removed by rivers was associated with suspended materials. The caesium removal with solid suspensions was even more significant in 1986, when their activity in the river Pripyat runoff was as high as 105-106 Bq kg-' (by 1990 the activity of solid suspensions decreased on the average to 103-104 Bq kg-'). As mentioned above, radiocaesium accounts for 2 0 4 0 % of the sediment runoff activity. The greater part of activity (50-80%) is associated with a granulometric fraction less than 20 pm and varies between 500 and 15000 Bq kg-'. In a fraction of 0.2-3 pm retained by special filters after 24 hours settling of the water sample, the specific activity of Cs-137 ranged from 4544 (river Dnieper) to 33518 Bq kg-' (dead channel of the river Pripyat). Unlike Cs-137, the greater portion (55 to 99%) of Sr-90 migrates from the catchment in dissolved state. Our researches show that (after 24 hours sample settling), Sr-90 dissolved in river water accounts for 92-98% of its total activity. The contribution of fhely dispersed (0.2-3 pm) material of solid suspensions contains the residual (1to 8%)of the total Sr-90 activity. The Sr-90 specific activity in this granulometric fraction volume varies between 639 and 4981 Bq kg-',

190

Highly active bottom sediments (up to 80-85 k Bq kg-' for Cs-137 and 7-7.5 k Bq kg-' for Sr-90) of river dead channels, branches, creeks and mouth areas of small rivers (Zhelon and others) are formed by deposition of high-activity suspended solids. Pu-238 (up to 9.1 Bq kg-'), Pu-239,240 (up to 28,13 Bq kg-I), Am-241 (up to 16.2 Bq kg-') and other radionuclides and '?lot" particles have been noted in the bottom sediments. These show a relatively even distribution in the vertical profile (up to 10-15 cm). Bottom sediments of rivers are potent accumulators of radionuclides and "hot" particles washed off the catchment surface. Very important goals for future research are to estimate the total activity in bottom sediments of river systems in southeastern Belarus, and to identify the mechanisms of formation and redistribution of radionuclide reserves in the solid runoff and bottom sediments. A simple estimate of the trans-border removal of Cs-137 and Sr-90 by river runoff was made. "he total flux was estimated from mean values of the run-off coefficient and the deposition in the area (Table 3). Since the estimates take no account of the difference in transport rates at different flow rates the errors on the estimates are probably high. However, they give a general idea of the annual radionuclide removal by the principal rivers of the Dnieper basin in Belarus. Relative to the total radionuclide reserves in catchment areas, Cs-137 removal fiom the river Pripyat basin is 0.097% per year, from the Sozh basin 0.005%,from the Dnieper basin 0.214%.Analogous values for Sr-90 are for the Pripyat basin 0.227%, Sozh 0.117% and Dnieper 0.244%. Compared with the effects of radionuclide physical decay the data suggest that the trans-border radionuclide removal with river runoff makes an insignificant contribution to the natural decontamination of the lands polluted as a result of the Chernobyl accident. TABLE 3

13'Cs and 90Srfluxes in Belorussian rivers River Catchment Radionuclide activity in observation area (thou. catchment (Bq x h-2) site

Average activity (Bq 1-I)

Cs-137

Sr-90

Cs-137

Sr-90

Annual removal (Bq x

Cs-137

Sr-90 444.8

Pripyat, Masany

106

720.8

196.1

0.55

0.35

699

Sozh, Leov town

42

1079.4

58.8

0.84

0.10

580

69.06

102 Dnieper, Loev town

652.8

40.8

0.70

0.05

1395

99.6

191

5. REFERENCES 1.

2. 3.

4.

5. 6.

7.

Lyutsko, A.M., I.V. Rolevich and V.I. Chernov, 1990. To live after the Chernobyl disaster. Minsk, Vysheishaya shkola Publ., 109. Bogdanov, A.P., V.N. Doroshkevich, G.M. Chmura, and V.A. Petrov, 1990. Estimation of the near-earth atmosphere contamination by Cs-137 as a result of ground sources dusting. Vesti Academii nauk BSSR. Ser. fiz.-energ. nauk, 4: 53-58. Drugachenok, M.A., V.P. Mironov and V.P. Kudryashov, 1993. Radioactive contamination of the air within the territory of the Republic of Belarus. Abstracts of Reports a t the International Conference “Science and medicine for Chernobyl”. Minsk. pp. 128-129. Izrael, Yu.A., S.N. Avdyushin, N.K., Gasilina, et al.,1987. Radioactive contamination of natural environments in a zone of Chernobyl accident. Meteorologiya i ghidrologiya, 2: 5-18. Izrael, Yu.A., 1990. Chernobyl and radioactive contamination of natural environments. Gidrometeoizdat Publ., Leningrad, 296 pp.. Voitsekhovich, O.V., V.V. Kanivets and G.V. Laptev, 1993. Analysis of the radioactive contamination of the Dnieper water system during five years after the Chernobyl accident. Trudy Ukrainskogo nauchno-issledov. ghydrometeorol. institut, Gidrometeoizdat Publ., Moscow, 245: 106-107. Laptev, G.V. and O.V. Voitsekhovich, 1993. Experimental investigations of radionuclide washout from floodplain soils of the Pripyat area under their flooding. Trudy Ukraunskogo nauchno - issledovat. ghudrometeorol. inst., vyp. 245. Gidrometeoizdat, Moscow, pp. 127-143.

Freshwuter und Estuurine Rudioecology Edited by G . Desmet et al. 0 1997 Elsevier Science B.V. All rights reserved

193

Effects of a partial drawdown on the dynamics of 137Cs in an abandoned reactor cooling reservoir F.W. Whicker, T.G.Hinton and D.J. Niquette Savannah River Ecology Laboratory, Drawer E, Aiken, SC 29802, USA

ABSTRACT The effects of a partial drawdown on 137Csdynamics in an abandoned nuclear reactor cooling reservoir, Par Pond at the Savannah River Site in South Carolina, USA, were examined. The drawdown, which occurred in 1991, caused major ecosystem changes, exposed 5.3 km2 of contaminated sediments, and led to hydrological changes that altered the limnology of the reservoir. Measurements of 137Csin sediments, largemouth bass (Micropterus salmoides), and aquatic plants were begun at the time of the drawdown and the status of these studies is reported. Cesium-137 concentrations in largemouth bass muscle have increased steadily since the drawdown. The most likely cause is the decreased potassium concentrations in water resulting from a change in the primary water source for Par Pond. Decreased body condition of the bass as well as a greater average 137Csconcentration in sediments in contact with the water column may also be contributing to the 137Cstrend in the fish. Sedimentation rates and water turbidity were increased after the drawdown due to erosion processes, but the natural colonization of the littoral zone and lake bed by plants has reduced these problems. Preliminary data on 137Csin vegetation indicate higher but more variable concentrations in plants on the lake bed as compared to littoral zone macrophytes.

1. INTRODUCTION

This paper concerns Par Pond, a 10.5 km2reservoir on the U.S. Department of Energy’s Savannah River Site (SRS)near Aiken, SC (Fig. 1).The reservoir was used from 1958 until 1988 as a thermal cooling pond for P and R reactors [1,2]. These reactors were used to produce plutonium and tritium for defense purposes. Radio-activity from leaking fuel elements in R reactor contaminated one drainage (“Hot Arm”) of Par Pond prior to its completion, between 1954 and 1958; subsequent contamination entered the impoundment via North Arm until 1964, at which time R reactor ceased operation [1,31. P reactor continued to use Par Pond until it was placed on indefinite standby in 1988.

194

PAR

After 6m Drawdown

Fig. 1. Map of Par Pond at the Savannah River Site near &en, SC, USA. Shorelines are shown for the full and drawdown conditions, as well a5 water sampling locations.

In the spring of 1991,evidence of internal erosion was discovered on the downstream slope of the Par Pond dam. As a precaution, the water level was lowered nearly 6 m (Fig. 1).The drawdown commenced on 21 June 1991 and was completed 92 days later (19September 1991).The drawdown resulted in the loss of 65% of the water volume and exposed approximately 5.3 km2 of sediments. These sediments are contaminated primarily with I3'Cs, and with smaller quantities of %r, 239,240Pu, 241Am, and "4Cm. Since completion of the drawdown, the water level has been stable. Aquatic vegetation has invaded the littoral zone, and terrestrial plants have colonized the exposed lake bed. The natural surface and ground waters of the area are SOR,mildly acidic (pH 5.0-6.8), low in nutrients (conductivities generally c 20 pS) and low in K ' (c 0.3 mg l?. However, Par Pond, prior to the drawdown, exhibited atypical limnology because it received inputs of nutrient-rich water from the Savannah River to replace evaporative losses when it was used for reactor cooling [41. The reservoir had a typical pH of 7.2, a higher conductivity (> 60 pS)and K ' values > 1 mg 1-' while it received Savannah River inputs. During and after the drawdown, there has been little or no need to pump Savannah River water into Par Pond. Therefore, the water chemistry has generally changed toward that reflective of natural surface waters in the area. This change, combined with ecological instability resulting from the drawdown,

195

and increased erosional inputs of sediment from the old lake bed, caused alterations in the dynamics of 137Cswithin the ecosystem. In this paper, we focus on changes in the 137Csconcentrations in the top predatory fish, largemouth bass (Micropterus salmoides), and explore factors that may be responsible for the changes. In addition, some of the general radioecological characteristics of the reservoir system are described. 2. MATERIALS AND METHODS

Since the drawdown of Par Pond, water quality has been measured at monthly intervals. Conductivity and temperature were measured through the vertical profile at four locations using a YSI Model 33 S-C-T meter from a boat (Fig. 1). Rates of particle sedimentation in the water column were estimated with a cluster of three sediment traps (10 cm diameter x 51 cm long) suspended at a depth of 5 m in three different locations. The traps were changed at 90 day intervals. The sediment in the traps was isolated by centrifugation before it was dried at 80°C and weighed. Sediment cores (5 cm diameter x 36 cm long) were taken during the fall, 1991 at 28 locations, both on the old lake bed and underwater. On the exposed lake bed, polystyrene core tubes were driven into the sediment with a mallet; underwater cores were taken with a weighted gravity coring rig and pontoon boat. Due to the large sand content, the coring methods did not cause significant compression of the cores. Cores were cut into 1 cm thick sections to examine the depth distribution as well as the total inventory of 137Cs. Largemouth bass were sampled by angling on monthly intervals for measurement of body condition and on quarterly intervals for 137Csanalysis. The health of the fish was described by a condition factor (K), where K = M lo5 L3 [5]. M is the fresh mass in g and L is the total length in mm. Approximately 100 g of fresh muscle tissue was dissected from each fish and packed into 40 dram plastic vials for 137Csanalysis. Otoliths were taken from each fish for determination of age. Plants were collected from the littoral zone of the reservoir and from the exposed lake bed in the fall of 1991, '92 and '93. The collections were made from about 6 locations around the reservoir on substrate types ranging from highly organic deposits to sand. The above-ground or above-sediment parts of plants were sampled. Plant tissues were rinsed, dried (80"C),and ground for analysis. All samples were assayed on a 90% efficient (relative to a 7.6 x 7.6 cm NaI detector) HPGe (EG&G ORTEC) detector coupled to a multichannel analyzer. EG&G ORTEC MAESTRO I1 Software was used to analyze the gamma spectra. All counts above the Compton continuum in the 662 KeV total absorption region were recorded and compared to counts from NIST traceable 137Csphantoms of identical geometries.AU sample activitieswere well above the detection limits and counting standard deviations were typically c 5%of the mean count rates.

196

3. RESULTS AND DISCUSSION

3.1. Sediments and sedimentation rates

Results from 28 sediment cores collected in 1991 are plotted in Fig. 2. The sediments from underwater locations contain more 137Csthan those from the exposed lake bed. This result is reasonable because some contamination entered the stream flood plains prior to construction of the Par Pond dam, and because fine sediments tend to absorb 137Csthen accumulate in the profhndal zone [3,6].The sediments on the exposed lake bed probably did not accurately reflect the character of the sediments before the drawdown. Some erosion of fine material occurred as the water level receded, and enhanced aerobic decomposition of organic matter occurred as the sediments became exposed. The peak 13?Csconcentration was at 5-6 cm depth in the underwater sediment profiles, but at 8-9 cm depth in the exposed lake bed profiles. The reason for this is not entirely clear, but it may relate to the fact that the underwater sediments are of generally finer texture than the more sandy sediments of the exposed lake bed. Rains after the drawdown may have leached 137Csfurther into the sandy

3.5 3 2.5 2 N

E

9 1.5 0-

m

1 0.5 0

-0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 3436 Depth in core (cm)

Fig.2. Concentrations of '37Cs (Bqcm-2) by 1 cm thick sediment core layers versus depth in core. Means shown for 9 underwater and 19 exposed sediment locations on Par Pond.

197

substrates. Erosion during the drawdown may also be responsible for the difference in depth of the peak activity. Integration over depth in all sediment cores and multiplication by the system area yields a total inventory estimate of about 1.6x 1OI2Bq (44Ci) of 137Csin the reservoir sediments. Sediments are expected to contain roughly 99% of the ecosystem inventory of 137Cs[3]. The rates of sedimentation were about 8 g m3 d-' from the end of the drawdown through March 1992,when the basin was largely devoid of vegetation. After that time, both the littoral zone and the exposed lake bed experienced rapid colonization by vegetation. This appeared to significantly retard shoreline washing and sheet or gully erosion from the exposed lake bed. By the April-July 1992 period, the sedimentation rate had dropped to about 2-3 g m-' d-'. It has since remained at that level. This observation correlates well with the secchi disk visibility, which has increased since February 1992,from about 110 cm to >350 cm. 3.2. Cesium-137 in largemouth bass

Since February 1992,concentrations of 137Csin largemouth bass muscle have steadily increased from <0.3 Bq g-' (wet) to about 0.6 Bq g-' (Fig. 3). The standard errors shown are relatively small, and since each is based on a

0.7 0.6 0.5

h

c. Q)

3

0.4

0

\

D

m

0.3

I DRAWDOWN 0

.

1

'

I

I

I

I

I

I

I

l

I

I

I

I

I

I

I

I

I

I

I

I

I

I

I

I

I

I

I

I

I

l

Fig. 3. Concentrations of '37Cs in largemouth bass muscle as a function of time following the Par Pond drawdown.

198

reasonable sample size (n= 10 t o 40), the statistical significance of the trend is obvious. Since no additional inputs of '37Csto the ecosystem have occurred, it is of interest to examinepotential causes for the increasing concentrations in bass. One possibility is the fact that the water is in contact with more highly contaminated sediments. From Fig. 2 it is evident that the top few cm of the sediments now under water are about twice as contaminated as the average would have been prior to the drawdown. This may have increased 13'Cs in the foodchain. Unfortunately, we do not have adequate time series data on 137Csin the bass foodchain. The concentrations of 137Csin the water were about 0.1Bq 1-' after the drawdown [71,but we do not yet have data on any subsequent trends. A likely causal factor for the increase of '37Cs in bass is the decline of potassium in water (Fig. 4). Historically, between 1965 and 1973, K+ranged from 1.1 to 1.5 mg 1-' in Par Pond water [41. It appears that K+has declined from about 1 mg 1-' at the termination of the drawdown to roughly 0.4-0.5 mg 1-' in October 1993.This trend was highly significant (r = -0.72;p c 0.002).A test for autocorrelation using Durbin-Watson's D statistic indicated that the data were not significantly correlated over time (D= 1.67;1st order autocorrelation = 0.135).Furthermore, a Spearman rank correlation analysis indicated a highly significant relationship between potassium concentrations in water

1.2 150.8-

E

+

n

g0.6 -

0.4 0.2

-

~

I

I

I

I

I

I

I

I

I

I

I

I

I

II

I

I

I

I

I

I

I

I

I

I

I

I

Fig. 4. Concentrations of potassium ion in Par Pond surface water since completion of the drawdown (r = -0.72; p < 0.002).

199

and 137Csconcentrations in bass muscle ( r = -0.70;~ < 0.003).This relationship has been observed by many investigators and is a classic paradigm of radioecology [3,81.The bass muscle/water concentration ratio for 137Csin this study (-3,000 for a K ' concentration of -1 mg 1-') is compatible with data in Blaylock [8] and data [3] for Pond B at the SRS (CR= 8,500 for a [K'l of 0.29 mg 1-'1. The mean condition factors ( K ) for largemouth bass declined significantly following the drawdown, with r = -0.72; p < 0.01 (Fig. 5). Autocorrelations in these data were not significant (D= 1.68; 1st order autocorrelation = 0.12).The Spearman rank correlation between 137Cs concentration in muscle and the K factor was -0.52 ( p < 0.04). Whether the decline in the condition factor was causative or coincidental to the increased 137Csconcentrations is not clear. The general cause of the condition factor trend is likely related to food availability. During the drawdown, forage fish lost the cover provided by littoral zone macrophytes. A prolonged (-3 months) feeding frenzy by the larger bass on forage fish was regularly observed during the drawdown and the K factor increased from about 1.2 to nearly 1.5 (Fig. 5). After that time, forage fish appeared to become scarce, and the K factor declined to ~ 1 . by 1 August 1992.

1.5

E W

1.4

3 1.3 0 I-

z 0 1.2 t n z 1.1 0

0

1

Fig. 5. Condition factor ( K ) in Par Pond largemouth bass since start of drawdown. Solid line includes data after completion of drawdown ( r = -0.72;~ < 0.01);dashed line includes all data since start of drawdown (r = -0.59; p < 0.01).See text for definition of K.

200

Since August 1992,the reestablishment of littoral zone vegetation has allowed obvious recruitment of forage fish stocks and the Kfactor has been more stable, except for seasonal fluctuations. Other factors examined relative to the increase of 137Cs in bass muscle were water temperature, conductivity, bass age, and sex. None of these variables were statisticallyrelated to 137Cs in bass, based on Spearmanrank correlation analyses. 3.3. Cesium-137 in vegetation Concentrations of 137Csin aquatic vegetation measured to date are presented in Table 1. Mean values by species for 1992 and 1993 ranged from 0.07Bq g-' TABLE 1 Concentrations of 137Csin aquatic vegetation (Bq g-' dry) that colonized the littoral zone of Par Pond following the drawdown (preliminary data) Species

Myriophyllum spicatum Najas minor Typha latifolia Vallisneria americana

1992

1993

Mean

l s ema

n

Mean

lsema

n

0.62 0.66 0.07

0.07 0.09 0.007

6 6 5

0.44 1.07

0.04 0.16

12 10

-

0.13

-

-

-

-

-

1

al standard error of the mean. TABLE 2 Concentrations of 137Csin vegetation (Bq g-' dry) that naturally colonized the Par Pond lake bed (1991-92 preliminary data) Species

Mean

1 sema

Range

n

Cyperus erythrorhizos Juncus effusus Eleocharis acicularis Panicum sp. Eupatorium sp. Typha latifolia Scirpus cyperinus Bacopa caroliniana Polygonum sp. Salix sp. Pinus sp.

3.78 3.59 0.85 2.33 1.00 0.06 0.70 1.15 5.52 0.33 0.15

1.19 1.52 0.59 1.37 0.48 0.01 0.52

0.26-7.67 0.04-7.67 0.07-2.00 0.33-4.93 0.04-1.56 0.05-0.07 0.19-1.22

5 5 3 3 3 2 2 1 1 1

a

1 standard error of the mean.

-

-

-

1

201

(dry) for Typha latifolia to 1.07 Bq g-' (dry) for Najas minor. The data base at the time this paper was written was not sufficient to examine trends or location differences, but it appears that substantial species differences in 137Cswill be evident. Other papers detailing this aspect are in preparation. Concentrations of 137Csin vegetation that colonized the Par Pond lake bed are presented in Table 2. In general, it appears that plants which colonized the exposed lake bed had greater 137Csconcentrations than those which colonized the littoral zone, and that 137Csconcentrations in these plants show considerably greater spatial variability than the aquatic species. The texture and 137Cs content of the exposed lake bed soils varied greatly from site to site (10 Bg g-') so the latter result is not surprising 191. 4.CONCLUSIONS

Although our data are still preliminary, it is evident that: 1. Concentrations of 137Csin largemouth bass muscle have increased by a factor of about 2 since the drawdown of Par Pond. 2. Levels of potassium in the water and the body condition factors of large-mouth bass have declined since the drawdown of the reservoir. These declines appear due, respectively, to natural surface and groundwater beginning t o dominate the inputs to Par Pond, and to disruption of the food base in the reservoir caused by the drawdown. 3. The most likely cause of increased 137Csin largemouth bass muscle is the decline of potassium in water; however, body condition factor declines, as well as the increased average 137Cscontent of sediments in contact with the water may be contributing factors. 4. Concentrations of 13?Csin the exposed lake bed vegetation are higher and more variable than littoral zone macrophytes. 5. Colonization of the lake bed and littoral zone with vegetation significantly reduced erosion and sedimentation and improved water clarity within a year following the drawdown. 5. ACKNOWLEDGEMENTS

This work was supported by the Savannah River Ecology Laboratory (SREL) through contract DE-AC09-76SR00-819 between the U.S. Department of Energy and the University of Georgia. Partial support was also provided by the Westinghouse Savannah River Company and SREL through contracts RR267022/5199263 and RR267-027/ 5199233 with Colorado State University, where the senior author is based. We thank L. Marsh, C. Bell and J. See1for technical support. Dr. C. Jagoe, SREL, provided potassium analyses in water. K. Garrett provided statistical assistance.

202 6. REFERENCES 1.

2. 3. 4.

5. 6.

7. 8.

9.

Wilde, E.W., 1985. Compliance of the Savannah River Plant P Reactor cooling system with environmental regulations. DP-1708JUC-11, E.I. dupont de Nemours & Co., Aiken, SC. U.S. Department of Energy, 1990. Environmental impact statement. Continued operation of K, L, and P reactors, Savannah River Site. DOE/EIS-0147. Savannah River Operations Office, Aiken, SC. Whicker, F.W., J.E. Pinder 111, J.W. Bowling, J.J. Alberts and I.L. Brisbin, Jr., 1990. Distribution of long-lived radionuclides in an abandoned reactor cooling reservoir. Ecolog. Mon., 60: 471-496. Tilly, L.J., 1975. Changes in water chemistry and primary productivity of a reactor cooling reservoir (Par Pond). In: F.G. Howell, J.B. Gentry and M.H. Smith (eds.), Mineral Cycling in Southeastern Ecosystems. CONF-740513. National Technical Information Service, Springfield, VA, pp. 394-407. Carlander, K.D., 1969. Handbook of Freshwater Fish Biology, Vol. I. Iowa State University Press, Ames, IA. Hakanson, L. and M. Jansson, 1983. Principles of lake sedimentology. SpringerVerlag, New York, NY. Hayes, D.W.,1991. Inventory and concentrations of Cs-137 and tritium in Par Pond and Lower Three Runs Creek System, SRL-ETS-910327. Westinghouse Savannah River Company, Aiken, SC. B.G. Blaylock, 1982. Radionuclide data bases available for bioaccumulation factors for freshwater biota. Nucl. Safety, 23: 427-438. Whicker, F.W., D.J. Niquette and T.G. Hinton, 1993. To remediate or not: A case history. In: R.L. Kathren, D.H. Denham and K. Salmon (eds.), Environmental Health Physics. Research Enterprises Publishing Segment, Richland, WA, pp. 473-485.

Freshwater und Estuarine Rudioecoliqy Edited by G . h m e t et d.

0 1997 Elsevier Science B.V. All rights reserved

203

Correlation analysis of the contamination of freshwater sediments in the Labe (Elbe) river catchment with gamma-emitting radionuclides P. BeneGa,J. Johna, F. Sebestaa and J. Veselyb aDepartment of Nuclear Chemistry, Czech Technical University, 115 19 Praha 1, Brehova 7, Czech Republic bCzech Geological Survey, 118 21 Praha 1, Malostranske namesti 19, Czech Republic

ABSTRACT One hundred and thirty-nine samples of sieved sediments of rivers and reservoirs in the Elbe (Labe) river catchment in Bohemia (Czech Republic) were analyzed by gammaspectrometry for lUCs, 137Cs,226Ra,228Raand 228Th.The results characterize contamination of the catchment with radiocesium mainly from the Chernobyl accident, with 226Rafrom uranium mining and milling, and natural background values for 226Ra,228Ra and 22eTh.The data obtained were analyzed on the basis of their mutual correlations and correlations with parameters characterizing composition of the sediments: content of silica, carbonates, organic carbon, ferric oxide, phosphorus, sulphur, uranium, thorium, barium and magnesium.

1. INTRODUCTION

With the aim of basic mapping of the radioactivity of freshwater sediments in the Czech Republic and of characterizingthe sources of anthropogenic contamination of the fresh waters, we carried out sampling and analysis of river and reservoir sediments in the catchment of the Labe (Elbe)river in Bohemia. One hundred and thirty-nine samples were analyzed by gamma spectrometry for 134Cs,137Cs,226Ra,'"Ra and zzeTh[ll. At the same time, analysis of chemical composition of the sediments was carried out [21. In this way the most extensive set of data on radioactivity and composition of freshwater sediments in this region was obtained. This enabled us to assess the background contents of several radionuclides in the sediments, to identify regions contaminated by man and to carry out basic correlations among the parameters of the sediments which contributed to understanding the processes of contamination.

204

2. METHODS

The sediments were sampled in 1990-1992. Several kg of fine sediment were collected with a plexiglass sampler from the surface layer (0-20cm) of bottom sediments, In the laboratory the samples were wet-sieved with a nylon sieve. The fraction of less than 63 pm grain size was dried at ~ 8 0 ° C and ground to less than 74 pm grain size. About 85 ml of the resulting sample was weighed into a cylindrical container, capped and sealed with melted paraffin wax. The gamma activity of the samples was measured for 60000 s not earlier than 1 month after sealing, using a Canberra 8180 Intelligent Multichannel Analyzer attached to a hyperpure germanium coaxial detector. Total contents of Ba, Th and U in the sediments were determined by instrumental neutron activation analysis, phosphorus and organic or carbonate carbon by standard methods [2]. Linear correlation among selected parameters of the sediments was analyzed using computer code 4M from BMDP Statistical Software, Inc., Los Angeles, USA. 3. RESULTS AND DISCUSSION

Simple inspection of all the results obtained revealed that the contents of '"Ra and "qh varied between 35-192 and 42-205 Bqkg, respectively. This variation reflected variation in natural contents of 232Thin this region, and no anthropogenic contamination with these radionuclides was detected. The increase in the average (background)activity in the order 232Th (50 Bqkg) c '"Ra (72Bqkg) c '"Th (79Bqkg) yielded evidence that a substantial part of 228Ra and '?h in the sediments was "unsupported" by 232Thso that it was adsorbed or precipitated from the water phase. Natural variation (background) of 226Ra was in the range of 37-160 Bqkg, the values near to the upper limit being found in areas with increased contents of uranium in rocks. Still higher contents of "'Ra in sediments of some waters were due to contemporary or past uranium wining or milling, Contamination of sediment with 134Csand 137Cs was mainly due to the Chernobyl accident. This was corroborated by the tight correlation between 134Csand 137Csactivities in the sediments ( r = 0.952for rivers and r = 0.997for reservoirs). Activities in the range of 0.4-198 and 1-2440 Bqkg were determined, respectively. A large similarity between geographic distribution of the contamination and that of the original (1986)contamination of surface soils in Bohemia was detected. Table 1 presents correlation coefficients found for naturally occurring radionuclides and also for those composition parameters which significantly correlated with at least one of the radionuclides.The correlations are presented separately for river and reservoir sediments. Significant values of the coefficients are underlined. As can be seen, the tightest correlations exist between

205 TABLE 1 Correlation matrix for selected parameters of sediments of the Labe (Elbe)river catchment. Lower left: river sediments, n = 106, significant r > 0.25for p < 0.01.Upper right: reservoir sediments, n = 33,significant r > 0.44 forp c 0.01

Q&

0.14 0.15 0.15

0.22

p39m

ma39 0.27

0.18 0.14

0.12 -0.10 0.23

QJ4

0.38

a9P

rn

-0.22

a39

0.15 0.09 0.22 ;a26

0.15 0.11 0.12 -0.23

a29

IL29

M

0.18 -0.13

m

-0.07

ma48

m m p 3 4 0.29 0.17 0.12

m

0.18

rn

0.36 0.18 0.04

m m

0.00

0.28 0.09 -0.27

m

0.20 0.44

a3p

'"Ra and "&rh and between "'Ra and 238U.These correlations reflect a substantial level of radioactive equilibrium established between these radionuclides in the sediments. In the first case, it is due to the relatively short half-life of the daughter, "&rh. For the second case, simple calculation has shown that the average percentage of "'Ra "supported with 238Uin the sediments was 90%, indicating that most "'Ra came to the sediments with crystalline detritus in near equilibrium with uranium. A lower but still significant correlation exists between 232Thand 228Raor '"Th in all the sediments. The correlation is probably negatively affected by the higher percentage of "unsupported" '"Ra as compared with zz6Ra.Similar correlation was found between U ("'Ra) and '"Ra or "&rh in reservoir sediments, whereas the analogous correlation coefficients for river sediments were low. The reasons are not clear. The difference between river and reservoir sediments is particularly pronounced for the correlation between radionuclide contents and chemical composition of the sediments. It appears that the presence of carbonates and phosphates in reservoir sediments is associated with increased contents of U and "'Ra. Very probably the coprecipitation of both the radionuclides with carbonates and phosphates occurs during the seasonal increase in pH due t o enhanced photosynthesis. On the other hand, increased concentration of organic carbon in river sediments seems to support binding of '"Ra, uranium and thorium. The correlation between barium and "'Ra or uranium probably reflects similarity in their behaviour in surface waters. These findings may help in elucidation of factors affecting migration of the radionuclides in surface waters, particularly if supplemented with sequential leaching of the sediments.

206

4. REFERENCES

1. 2.

Beneh, P., J. John and F. Sebesta, 1993.Analysis of the contaminationof sediments in Labe River watershed with radionuclides. Final Report for Project Labe, Faculty of Nuclear Sciences and Physical Engineering, Prague (in Czech). Vesely, J., 1992. Contaminationof Czech rivers with trace elements. Report Czech Geological Survey, Prague (in Czech).

Freshwuter und Estuurine Rudioeecology

Edited by G. Desmt et nl. 0 1997 Elsevier Science B.V.All rights reserved

207

On the differential binding mechanisms of radiostrontium and radiocaesium in sediments Maria Jose Madruga* and Adrien Cremers Laboratory for Colloid Chemistry, K. U. Leuuen, Kardinaal Mercierlaan 92, 3001 Heuerlee, Belgium (*Present Address: DGA IDPSR, E.N. 10,2685 Sacauh, Portugal)

ABSTRACT It is commonly thought that the fraction of sediment-bound radiostrontium and radiocaesium, dispersed in 1 M ammonium solutions - the ion exchangeable pool - is associated with the “regular“part of the ion exchange complex (the planar and easily exchangeable sites). It is the purpose of this paper to demonstrate that radiostrontium and radiocaesium are associated with different exchange sites in the solid. Such a conclusion is based on a comprehensive study of sorption reversibility, covering a range of sediments and desorption agents (complex ions, KC1, NH4C1, MgC12, CaC12, Sr (NO&). The difference in solid-phase speciation of the two radionuclides is further demonstrated by the results of a sequential ion exchange displacement procedure allowing quantitative separation of the ion exchangeable fractions of the two radionuclides. This procedure is based on a dispersion of the sediment in a 1N SrClz solution, leading to a quantitative displacement of radiostrontium and marginally low desorption yields in radiocaesium (21%).Fractional desorption of radiocaesium can be brought about by a subsequent infinite bath desorption protocol in dilute ammonium solutions.

1.INTRODUCTION

In classical soil chemistry literature, it is generally accepted terminology to call the fraction of a metal (e.g. heavy metal) which is being displaced upon dispersing a soil (or sediment) in a concentrated electrolyte solution “the ion exchangeable fraction”. The first step of a sequential extraction protocol 111, or some modifications of it, is aimed at measuring such fraction. Apparently, there is no a priori reason for not extending such terminology to radiocaesium and radiostrontium. Very often, the message conveyed by such terminology is one of speciation, implying that such fractions are associated with what is sometimes vaguely referred to as the “regular”part of the ion exchange complex (the

208

“regular” exchange sites correspond to the planar and easily exchangeable sites) [2,3]. If this argument is pursued, and the metal ion is associated with the “ion exchange complex” then one would expect the nature of the displacing cation to have no effect on displacement yield. Yet it was found that in the case of radiocaesium, large differences in displacement yields are obtained, depending on the nature of the cation [41. A number of features (uncommon in classical ion exchange processes) which characterize the sorption of radiocaesium in sediments, have been highlighted [5,6]: extreme selectivity differences among ions of otherwise similar properties (hydration),pronounced kinetics effects in sorption and pronounced irreversibility effects [7]. These uncommon features are linked with the (near) quantitative interception of radiocaesium in the frayed edge sites FESI (specific sites located at the frayed edges of the clay particles) of the micaceous minerals [8,91. The sorption behaviour of radiostrontium in soils and sediments is - in contrast to radiocaesium - in line with “classical”behaviour, characterized by small differences in selectivity among metals in the so called lyotropic series (involving mainly electrostatic effects). Several authors [lo-141 pointed out that the major fraction of strontium added to soils remains available in exchange sites, and only a small proportion becomes more strongly adsorbed. The objective of this study is to develop a selective and differential ion-exchange methodology to separate the ion exchangeable fractions of radiocaesium and radiostrontium, and to demonstrate that these exchangeable fractions are associated with totally different ion exchange sites. This study approaches the objective in three steps: (a) sorption reversibility of radiostrontium in electrolyte solutions and infinite bath conditions; (b) sorption reversibility of radiocaesium in electrolyte solutions and infinite bath boundary conditions; (c) a mixed infinite bath-ion exchange protocol for separating radiostrontium and radiocaesium. 2. EXPERIMENTAL 2.1. Physico-chemical characterization of sediments

Sediment samples (dried at room temperature) have been characterized in terms of overall cation exchange capacity (CEC) and exchangeable ions, using the silver thio-urea procedure (pH = 7) 1151, organic matter content (OM) based on weight loss at 750°C, and pH (solid/liquid ratio of 1/10, KC1 = lO-’M). 2.2. Radiostrontium displacement in electrolyte solutions

T2 (Tejo river) and A (Tejo estuary) sediments and Camp Berteau (Morocco) montmorillonite (a reference material) were included in this study. One-g sediment samples (T2, A) were dispersed in 20 ml lod M CaClz solutions

209

labelled with 85Sr(SrC1,) and equilibrated for 24 hours. Sediment suspensions were centrifilged (20min, 27000 g) and supernatants assayed radiometrically for obtaining the amount of radiostrontium adsorbed. Sediments were then dispersed in 20 ml of the following solutions: 0.015 M AgenTU (silver ethylene thio-urea), 0.01 M BTM-6 (bis-quaternaryammonium hexane), 1M NH4Cl and 1N Sr (NO3),. Systems were shaken for 24 hours and centrifuged; @Srdesorption was obtained from gamma assays of the supernatants. In the case of montmorillonite, labelling was made on the Na-form of the clay in lo4 M NaN03. Displacement procedures were otherwise identical to the ones described for the other systems. 2.3. Radiocaesium displacement in electrolyte solutions Exactly the same protocols were carried out for studying radiocaesium desorption from T1, T2 (Tejo river), A (Tejo estuary) and montmorillonite. However, in this case 8 different desorption fluids were studied (0.015 M AgTU, 0.015 M AgenTU, 0.01 M BTM-6, 1 M KC1, 1 M NH4Cl, 1 M MgC12, 1 M CaCl,, 1 N Sr(NO,),). In the case of homo-ionic-Na montmorillonite two protocols were studied. The system was labelled with 137Cs(CsCl) (carrier free) or with lo4 M CsCl (corresponding to a caesium loading of about 2.5% of the CEC). 2.4. “Infinite Bath” procedure

In order to assess the possibility of a combination of the infinite bath methodologies for separating exchangeable forms of radiostrontium and radiocaesium, the “InfiniteBath” technique [5] was tested. For radiostrontium this technique was applied to TO (Tejo river sediment <20 pm) sediment and a suspension of calcium carbonate (CaC03).In the case of TO sediment two desorption conditions were tested: NH4-Dowex50x8 resin in M NH,C1 and Ca-Dowex 50x8 resin in lo3 M CaC12. For CaC03 only the second scenario was tested (Caresin). For radiocaesium desorption this protocol was applied to TO sediment in Ca-Dowex 50x8 ( 5 ~ 1 M 0~ CaC1,) and Sr-Dowex 50x8 (lo3 M SrC1,) resins and to T2 sediment in Sr-Dowex 50x8 (lo3 M SrC1,) resin. 2.5. Mixed “Infinite Bath” methodology

This protocol was tested for Tejo river (Tl, T2), Tejo estuary (A, S), Devoke water (D4) and Kiev reservoir (KR-4) sediments. Sediment samples (= 1 g) inside dialysis membranes were thoroughly equilibrated with mixed K-Ca solutions (lo-‘ M KC1, 10“ M CaC1,) which were double labelled with 137Cs (CsCl) and wSr (SrCl,). After three days equilibration 13’Cs activity in the dialysate was counted by gamma spectrometry and the amount of 13’Cs adsorbed was calculated. For wSr,dialysate samples were counted by beta spectrometry after 16 days (allowing a stationary state for the 9 daughter nuclide), and

2 10

‘OSr activity adsorbed on the sediment was calculated. Appropriate corrections were made for the 13’Cs interference (maximum energy of 0.51 MeV) in the liquid scintillation counting assays of gOSr(maximum energy of 0.54 MeV). Radiostrontium desorption was carried out by transferring the dialysis membranes to 1 N SrC12solution (end-over-end shaking, 24 hours); wSr and 137Csactivities were monitored in the dialysate (taking appropriate time delays and corrections as described). From such measurements, desorption levels of both radiostrontium and radiocaesium could be calculated. Finally, dialysis membranes were transferred to a vessel containing Giese granulate in lo3 M NH4C1 solution, and the radiocaesium desorption was monitored by regular gamma counting of the adsorbent. In addition, reference desorption experiments were carried out on the various sediments (using single labelling), applying the 1N SrClz and the “Infinite Bath” protocol (lo3 M NH4Cl, Giese granulate) [5]separately. 3. RESULTS

Some chemical parameters for the sediments studied are presented in Table 1. Tables 2 and 3 summarize all data on radiostrontium and radiocaesium desorption levels, obtained with the various displacement solutions. All measurements are carried out in duplicate (difference of 1-2% at most). Figures 1and 2 show the results on radiostrontium and radiocaesium desorption behaviour using different desorption agents in combination with the corresponding resin “sinks” (“Infinite Bath” procedure). The results concerning the mixed “Infinite Bath” methodology and the reference experiments are summarized in Table 4. Five data sets are shown: the eOSr desorption levels obtained with 1 N SrC12(double-labelled systems), 137Cs desorption levels in 1N SrC12(double-labelled),cumulative 137Csdesorption levels (obtained as the plateau values after 11 days of desorption) using the mixed “Infinite Bath” technique (double labelled), %r desorption levels in 1N SrClz(single-labelled),and 137Csdesorption levels (single-labelled)with the “Infinite Bath” technique. 4. DISCUSSION

From data in Table 1it is seen that for Tejo river and Kiev reservoir sediments, the sum of exchangeable cations nearly equals the CEC, which is consistent with the high pH of the overlying water column (pH = 7.8). For the estuarine sediments, the apparently high levels of “exchangeable”calcium are most likely due to the high CaC03levels present. In the case of Devoke Water sediment, a rather high degree of desaturation is seen in the exchange complex, which is probably due to the relatively high OM content and a fairly low pH of the water column (pH = 5.0).

211 100

80

* TO

60

sed.

+ TO sed

40

-C- CaC03

20 0

0

10

20

30

40

50

60

desorpt ion time (hours) Fig. 1. Time dependence of radiostrontium desorption for TO <20 pm sediment in M NHd-Dowex resins; for CaC03 in lo3 M Ca-Dowex resin. Ca-Dowex and

80 loo

60

M

i

40

20 0

0

3

6

9

12

15

18

desorption time (days) Fig. 2. Time dependence of radiocaesium desorption for TO <20 pm sediment in 5 ~ 1 M0 ~ Ca-Dowex and M Sr-Dowex resins; for T2 ~ 5 0 pn 0 sediment in lo3 M Sr-Dowex resin.

Data presented in Table 2 show that (nearly) quantitative radiostrontium desorption is obtained with 1 N Sr(NO& for all systems, a result which agrees with results obtained by many others authors [13,16-181. Similarly high

2 12 TABLE 1 Origin and some relevant parameters of the sediments studied Sed.

Origin

PH

Tejoriver Portugal Tejoriver Portugal Tejoestuary Portugal Tejoestuary Portugal D4 Devoke Water England KR-4 Kievreservoir Ukraine

T1

T2 A S

5.9 5.9 7.6 8.1 5.8 6.0

CEC

OM

(mEq

(96)

Exchangeable cations (mEq 100 g')

100 g')

7.4 5.1 13.4 13.8 20.1 16.5

14.3 7.5 27.9 31.4 18.0 45.0

Na

K

Ca

Mg

0.1 0.1 0.3 2.1 0.4 0.3

0.6 0.3 1.7 3.6 0.2 0.9

9.5 4.4 56.9 55.3 6.1 31.2

2.9 1.9 9.1 14.1 1.4 6.7

TABLE 2

Radiostrontium desorption yields (%) for various substrates and different displacement solutions. Standard deviations are given in parenthesis Solutions

AgenTU 0.015 M BTM-6 0.01 M NH4Cll M Sr (NO& 1N

Substrates T2

A

Na-mon.*

61.1 (i0.5) 39.5 (i0.6) 93.1 kt 0.2) 99.7 (* 0.1)

59.9 (i0.2) 40.3 kt 0.5) 88.5 (i0.1) 95.0 (i0.5)

95.5 (i0.5) 78.3 (& 0.7) 94.5 kk 0.6) 92.9 (+ 0.3)

*Na-mon. = Na-montmorillorete carrier free.

desorption yields (90-95%)are obtained with 1M NH4Cl.Consequently, it can be stated that radiostrontium desorption is reversible and desorption yields are quite insensitive t o the nature (size) of the displacement cation. Table 3 shows that radiocaesium desorption yields in 1 M KC1 are higher than in NH4Cl (roughly 15%) and that the radiocaesium desorption yield in 1 M NH&l is only half of what was found for radiostrontium. In the case of alkaline earth metal ions, it is seen that desorption yields (T1and T2) decrease drastically from Mg to Ca to Sr (about l%), i.e. with increasing ionic radius (crystallographic). The near zero desorption level in 1N SI-(NO~)~ is in sharp contrast with the (near) 100%desorption found for radiostrontium (in T2 and A) and demonstrates that radiocaesium in these systems is quantitatively associated with sites from which it cannot be displaced by 1N Sr. The same conclusions can be drawn from the data, based on the use of the bulky cations

2 13 TABLE 3

Radiocaesium desorption yields (%) for various substrates and different displacement solutions. Standard deviations are given in parenthesis Solutions

AgTU 0.015 M AgTU 0.015 M BTM-6 0.01 M KCll M NH&l 1 M MgClz 1 M CaClz 1 M Sr (NO& 1 N

Substrates T1

T2

3.2 (k0.02) 1.6 (k0.01) 1.4 (* 0.01) 58.2 (* 0.1) 46.6 (* 0.1) 12.9 (f0.2) 4.2 (k 0.04)

7.0 (k 0.07) 1.9 (* 0.02) 1.5 (+ 0.01) 58.8 (* 0.2) 42.3 (k0.4) 27.6 (k0.4) 6.9 (rt 0.06) 0.6 (k0.01)

A

Na-mom*

Na-mon.**

9.2 (k 0.1) 2.3 (+ 0.02) 42.6 (* 0.5) 18.7 (k0.2)

95.1 (* 0.4) 90.1 (* 0.3) 85.2 (+ 0.6) 91.0 (k0.6)

*Na-mon. = Na-montmorillonitecarrier free. **Na-mon. = Na-montmorillonitewith carrier

(AgTU, AgenTU and BTM-6). It is seen that desorption yields decrease in the order AgTU > AgenTU > BTM-6; in the case of BTM-6, desorption levels are of the order of 1%.Consequently, there is no doubt that radiocaesium in these systems is quantitatively associated with the FES, and that the radiocaesium desorbed by concentrated K and NH, solutions do not originate from the regular ion exchange complex. Moreover, they demonstrate that some pronounced (probably structural) differences do exist among the FES for different substrates. The data obtained in Na-montmorillonite (Table 3) require some specific comments. It is seen that, when working in carrier free conditions, the same picture as before is observed (2% desorption in BTM-6 and about 20% in 1N Sr). This clearly indicates that in montmorillonite, some FES (illitic residues) are present. However, when adding stable caesium (far in excess of the FES capacity) radiocaesium is shifted to the planar sites and desorption levels of about 90%, irrespective of the size of the displacing ion are observed. From Fig. 1 it is seen that, for both systems and the two desorption agents (NH, and Ca), 100%radiostrontium desorption is accomplished. This indicates that, as already demonstrated, radiostrontium desorption is reversible in sediment and CaC03 (at least within the adsorption time scale studied). Moreover, it appears that the desorption process is quite rapid (80%desorption within two hours), as compared to radiocaesium (Fig. 2). The results obtained on radiocaesium desorption behaviour using strontium or calcium as desorption agents in combination with the corresponding resin “sinks”(Fig. 2) show that the desorption plateaus, which are reasonably well defined after a desorption time of two weeks, are quite high (50%for Sr and about 20% for Ca in TO)

2 14 TABLE 4

Radiostrontium and radiocaesium desorption yields (%) for a set of sediments, in the presence of 1 N SrC12 and lo3 M NH&l Giese (“Infinite Bath” method). Standard deviations are given in parenthesis Mixed “InfiniteBath”

90Sr Sed. T1 T2 A S D4 KR-4

137cs

1 N SrClz 98.4 (k 0.3) 99.3 (* 0.2) 96.4 (* 0.2) 97.1 (* 0.4) 99.7 (* 0.6) 100 (* 1.4)

2.7 (* 0) 3.3 (* 0.1) 1.3 (* 0) 1.3 (* 0.1) 3.3 (* 0.1) 1.1 (* 0)

137cs

90Sr

137cs

lo3 M NH4 Giese

1 N SrClz

lo9 M NH4 Giese

33.4 (50.5) 28.2 (It 0.8) 39.6 (* 0) 40.2 (* 0.2) 65.7 (* 0.9) 16.6 (* 0.2)

95.6 (+ 0.1) 97.3 (* 0.6) 96.8 kt 0.1) 97.3 (* 0.1) 99.0 (* 0.5) 97.9 (* 0)

49.3 (* 0.5) 46.5 (* 0.1) 61.9 (k0.2) 67.5 (* 0) 91.7 (i0.5) 21.8 (* 0.1)

as compared to the results obtained in 1N solutions (1% in 1N Sr) (Table 3). Moreover, in contrast to what was found for concentrated solutions, the strontium ion is now the most efficient in displacing radiocaesium. This shows that the use of concentrated solutions is conducive to some structural alterations of the FES regions, leading to some kind of irreversible occlusion of radiocaesium in the structure. From the results presented in Figs. 1and 2 it would appear that a sequential displacement procedure based on a combination of infinite bath protocols is not possible since both calcium and ammonium appear t o displace both radiostrontium and radiocaesium. Therefore, it seems that the most appropriate procedure should be the mixed “Infinite Bath” methodology. Data in Table 4 show that, in all systems (double-labelled and single-labelled), desorption is nearly quantitative (96-loo%), clearly demonstrating complete reversibility. As expected, 137Csdisplacements in the 1 N SrClz treatment are quite low (13%)which demonstrate that 137Csis not at all present in sites accessible to strontium. The desorption levels obtained for 137Cs,after having been submitted to a 1N SrClztreatment are seen to be significantly lower (a factor of about 1.5) than the values obtained in the single-labelled systems (no 1 N SrClz treatment). Evidently, this effect is due to the enhancement of fixation, resulting from the effect of concentrated solutions of strontium, as referred for Ca and Mg [51. The radiocaesium desorption levels, as measured after the 1 N SrC12 treatment represent some underestimate of the desorbable levels on account of fmation enhancement in the SrClz treatment. No relationship between the radiocaesium and radiostrontium desorption yields and the CEC and OM content for the sediments studied, was found.

2 15

5. CONCLUSIONS

The comparative study of desorption behaviour of radiostrontium and radiocaesium, using a combination of infinite bath boundary methods, concentrated solutions of potassium and ammonium, and solutions of cations characterized by high adsorption affinity for the sites of the regular ion exchange complex demonstrate that radiocaesium and radiostrontium are associated with different regions of the solid phase. Radiocaesium is quantitatively associated with the FES and its adsorption is only partly reversible; radiostrontium is quantitatively associated with the regular ion exchange complex and its adsorption is completely reversible. Such difference in solid phase speciation is clearly demonstrated by a simple methodology allowing nearly complete separation of the ion-exchangeable forms of the two radionuclides. 6. REFERENCES 1. Tessier, A., P.G. Campbell and M. Bisson, 1979. Sequential extraction procedure for the speciation of particulate trace metals. Anal. Chem., 51: 7. 2. Bolt, G., M. Summer and A. Kamphorst, 1963. A study of the equilibria between three categories of potassium in an illitic soil. Soil Sci. Soc. Am. Proc., 27: 294-299. 3. Brouwer, E., A. Baeyens, A. Maes and A. Cremers, 1983. Caesium and rubidium ion equilibria in illite clay. J. Phys. Chem., 87: 1213-1219. 4. Schulz, R., R. Overstreet and I. Barshad, 1960. On the soil chemistry of caesium 137. Soil Sci., 89 (1): 16-27. 5. Madruga, M.J., 1993. Adsorption-desorption behaviour of radiocaesium and radiostrontium in sediments, PhD Thesis, K.U. Leuven, Belgium, October 1993, p. 121. 6. Wauters, J., 1994. Radiocaesium in aquatic sediments: sorption, remobilization and fixation, PhD Thesis, K.U. Leuven, Belgium, February 1994, p. 109. 7. Comans, R., M. Haller and P. De Preter, 1991. Sorption of caesium on illite: non equilibrium behaviour and reversibility. Geochim. Cosmochim. Acta, 55: 433440. 8. De Preter, P., 1990. Radiocaesium retention in aquatic, terrestrial and urban environment: a quantitative and unifylng analysis, PhD Thesis, K.U. Leuven, Belgium, April 1990, p. 93. 9. Sweeck, L., J. Wauters, E. Valcke and A. Cremers, 1990. The specific interception potential of soils for radiocaesium. In: G. Desmet, P. Nassimbeni and M. Belli (eds.), Transfer of Radionuclides in Natural and Semi-Natural Environments. Elsevier, Amsterdam, London and New York, pp. 249-258. 10. Wiklander, L., 1964. Uptake, adsorption and leaching of radiostrontium in a lysimeter experiment. Soil Sci., 97: 168-172. 11. Taylor, A., 1968. Strontium retention in acid soils of the North Carolina coastal plain. Soil Sci., 106 (6): 440-447. 12. Killey, R., 1982. Long-term strontium-90 behaviour in a sand aquifer, Proceedings series of environmental migration of long-lived radionuclides, IAEA-SM-257/86P, IAEA, Vienna. 13. Jackson R. and K. Inch, 1983. Partitioning of strontium-90 among aqueous and

2 16

mineral species in a contaminated aquifer. Environ. Sci. Technol., 17: 231-237. 14. Coughtrey, P. and M. Thorne, 1983. Radionuclide Distribution and Transport in Terrestrial and Aquatic Ecosystems. A Critical Review of Data. Vol. 1, A.A. Balkema, Rotterdam, pp. 211-223. 15. Chhabra, R., J. Pleysier and A. Cremers, 1975. The measurements of the cationic exchange capacity and exchangeable cations in soils: a new method, in: Proceedings of the International Clay Conference. Applied Publishing Ltd, IL, USA, pp. 439-449. 16. Cerling, T. and R. Turner, 1982. Formation of freshwater F e M n coatings on gravel and the behaviour of 6oCo, and 137Csin a small watershed. Geochim. Cosmochim. Acta, 46: 1333-1343. 17. Wilkins, B., N. Green, S. Stewart and R. Major, 1985. Factors that affect the association of radionuclide with soil phases. In: R. Bulman and J. Cooper (eds.), Speciation of Fission and Activation Products in the Environment, Elsevier, Amsterdam, London, and New York, pp. 101-113. 18. Fukui, M., 1990. Desorption kinetics and mobility of some radionuclides in sediments. Health Phys., 59 (6): 879-889.

Freshwuter und Esruurine Rudioemlogy

Edited by G. Desmet et nl. 0 1997 Elsevier Science B.V.All rights reserved

2 17

Tracing of sedimentation and post-depositional redistribution processes in Lake Constance with 137Cs S. Kaminskia,T. Richtera,T. Klenka, M. Eckerlea, G. Lindnerb and G. Schroder' 'Fachhochschule Ravensburg-Weingarten, P.O. Box 1261,D-88241Weingarten, Germany bFachhochschuleCoburg, P.O. Box 1652,D-96406Coburg, Germany 'Znstitut fur Seenforschung, Landesanstalt fur Umweltschutz Baden-Wurttemberg, P.O. Box 4146,D-88081Langenargen, Germany

ABSTRACT From measurements of (i) the depth distribution of 137Csin sediments of Lake Constance, (ii) the specific 13'Cs activity in sediment layers contaminated by the Chernobyl fallout and (iii) the 137Csdistribution among different grain size fractions, information about sediment formation and post-depositional redistribution processes in the lake and its catchment area can be obtained. These processes are of importance with respect to the long-term fate of cesium radionuclides in a drinking water reservoir.

1. INTRODUCTION

Lake Constance is a large (surface area: 571 km2)and deep (maximum depth: 254 m) pre-alpine hard-water lake, located between Germany, Austria and Switzerland. Water and solids are mainly supplied by river Rhine from its alpine watershed. Lake Constance was contaminated with cesium radionuclides from the fallout of atmospheric nuclear weapons testing (137Cs)and the Chernobyl fallout (134Csand '37Cs).Since this lake is an important drinking water reservoir for more than 5 million people, the fate of these radionuclides introduced (i)directly across the water surface, via (ii) rapid run-off or wash-off by tributaries and (iii) slow erosional or redissolution processes from its watershed was of utmost interest. Chernobyl radionuclides were washed out from the atmosphere within several hours on April 30,1986 due to heavy rainfalls and so the first radionuclides reached the stratified lake by direct input across the water surface. A

2 18

rapid removal of cesium radionuclides from the epilimnion was observed [1,21, and explained by adsorption of dissolved cesium radionuclides at clay particles and their subsequent sedimentation, which was enhanced by a biogenic calcite precipitation event happening shortly after the input [31. Another process of rapid transport of these radionuclides into the sediment was the input by tributaries, which was most important near the mouth and the flow path of river Rhine in the lake [4,5]. Thus a thin layer of sediment was formed in 1986, whose contamination by cesium radionuclides was considerably higher than in the previously formed sediment layers and it was proven by extraction experiments that these radionuclides were firmly bound t o clay mineral particles 161. Therefore no indications of redissolution from sediment could be found so far and the cesium radionuclides can be utilized as tracers for sedimentation and post-depositional redistribution processes in Lake Constance [7-91. Since illite was identified t o be the most abundant clay mineral species in these sediments 131 and its high capability for irreversible sorption of cesium is well known [lo], it is assumed that this mineral species plays an important role in cesium furation in the sediment. In this contribution further evidence for the possibility to use cesium radionuclides as tracers of clay particles contaminated in 1986 is provided from grain size fractionation and the analysis of the specific activities of sediments formed or redistributed by different transport processes. 2. MATERIALS AND METHODS

In winter 1992/1993, sediment cores were collected at 23 locations in Lake Constance exactly determined with a differential satellite-based global positioning system (DGPS). The coring locations are depicted in Fig. 1.Cores were taken using a 5.9 cm inside diameter Meischner & Rumohr gravity corer. At each location, three cores of about 1m length were taken and stored at 4°C in the refrigerator until further preparation. Among the three cores one served for the determination of the 137Csdistribution, one for analysis of stratigraphy, mineralogical and geochemical parameters (the results are not reported in this contribution) and the third one was kept in reserve or in archive. The sediment cores were split longitudinally into equivalent halves. Cores provided for cesium analysis had to be undisturbed and representative for the special location. Visual inspection of the sediment layers and comparison with the second core from the same location guaranteed these conditions. The cores provided for cesium analysis were sectioned into 5 mm thick slices using a specially constructed microtome. After freeze-drying the samples were homogenised by grinding and filled into calibrated vessels for analysis by gamma spectrometry on high purity Ge detectors. The “Chernobyl-layers”of several type A sediment cores (see below) taken in the western part of Lake Constance were combined to obtain about 200 g wet

2 19

S 0

2

4

I

l

l

6

8

1Okm

Fig. 1. Map of Lake Constanceshowing coringlocations (numbers)and classification according to the 137Csdepth profile (letters).

sediment. This sediment sample was micro-sieved using a Retsch ultrasonic sieving apparatus. For the purpose of this investigation, a “Chernobyl-layer”is defined as the upper layer of a core, from the top down to the base of the Chernobyl activity. The six grain size fractions were freeze-dried, homogenized and 137Csactivity concentrations within the fractions were determined. Cesium-137 activities were in all cases decay-corrected to May 1, 1986. 3. RESULTS AND DISCUSSION

Different shapes of the Chernobyl peak in 137Csdepth distributions in sediment cores from Lake Constance led to a classification of the cores into four different groups, which can be related to different sedimentation processes dominating at these locations [5,91. Undisturbed sedimentation in Lake Constance showing little direct influence of inputs by tributaries or post-depositional redistribution processes resulted in 137Csdepth profiles similar to that shown in Fig. 2 (type A locations), which exhibits two well-resolved maxima due to the Chernobyl (2 cm depth) and the nuclear weapons testing fallout (10.5 cm depth). The specific 137Cs activities in the uppermost sediment layer, the layer formed in 1992, and the

220

0

500

- - ~ - __

-_

1000

"'Cs (Bqlkg) 1500 ---., ____

2000

-,

__

2500 &

31 00

c 1986 (Chernobyl) h

E 5

v

sp g

10

t

1963 (maxlmumnuclear weapons testing)

Fig. 2. 13'Cs concentration profile against depth in Lake Constance sediment at location 21 (core collection: 18 January 1993, 214 m water depth). Error bars indicate 1 o standard deviation.

layers formed between about 1970 and 1985 are very low. Deviations from the regular shape of type A could be attributed to the input of '37Cs-carrying particles by tributaries (at type B locations by river Rhine or at type C locations by other smaller tributaries) or to post-depositional redistribution processes (type D locations) [5,9]. In 1987 a river Rhine high water occurred, which was the most prominent in this century. Therefore much more coarse material was brought into the lake in 1987 than during normal high water events. This becomes apparent in the corresponding '37Cs depth profiles of type B locations as a minimum of the specific activity in the 1987 sediment layer. All cores taken in the flow path of river Rhine - from the mouth of river Rhine along the north shore in Lake Constance (Fig. 1)- show this minimum in their 137Csdepth distributions [4]. Cesium-137 depth profiles attributed to group C are characterized by higher specific 137Csactivities in the upper sediment layers above the Chernobyl maximum and a 137Csdistribution shifted t o larger sediment depths because of higher sedimentation rates. Profiles of type C are found near the mouths of smaller tributaries (Fig. 1). Type D profiles are created by erosion and accumulation processes at the sediment surface and are found in shallow water depths and at locations where water turbulence occurs in the bottom water. Often there is no sharp separation between Chernobyl and nuclear weapons testing cesium in the depth distribution and the peaks are broadened. One unusual example for a 137Csdepth profile of a type D core is shown in Fig. 3. The sediment core depicted in this example shows very high specific 137Csactivities and also a very high total 137Csactivity resulting from the Chernobyl fallout. This is explained by the accumulation of fine grained and '37Cs-enrichedmaterial at this coring location (in 25 m water depth) in recent years. In contrast specific 13%s activities resulting from nuclear weapons

22 1

13’Cs (Bq/kg) 0

1000

2000

3000

4000

5000

Fig. 3. ‘37Cs concentration profile against depth in Lake Constance sediment at location 24 (core collection: 18 January 1993, 25 m water depth). Error bars indicate 1 o standard deviation.

testing fallout are not enhanced and the nuclear weapons testing peak is flattened. Previous sedimentological investigations of shallow water areas in Lake Constance have shown a washing-out of fine-grained particles above 10 m water depth and that erosion phenomena in the near shore areas has increased strongly during recent decades I l l ] . Our observations of enhanced Chernobyl cesium activity in 25 m water depth is in accordance with an accumulation of fine grained material resuspended in shallow water areas. Presumably, such resuspension processes did not occur to such an extent three decades ago during the period of deposition of nuclear weapons testing fallout. It is known from extraction procedures that cesium radionuclides are firmly bound to clay minerals in the sediment of Lake Constance [6].Clay minerals form the small grain size fractions (c2pm). Therefore it is assumed that cesium radionuclides should be mainly found in these fractions. The analyses of the specific 137Csactivities in different grain size fractions of a sediment sample, composed of “Chernobyl-layers”of type A sediment cores, confirm this assumption. Considerably higher specific activities were measured in small grain size fractions (< 20 pm, Fig. 4) and small specific activities in large grain size fractions. These observations allow an interpretation of the mean specific 137Csactivities in the “Chernobyl-layers” in the sediment of Lake Constance in terms of different formation processes (Fig. 5). In all cores of type A (moderate allochthonous and strong autochthonous sedimentation) similar mean specific 137Csactivities were measured, whereas the specific activities in sediments mainly formed by allochthonous material introduced by the river Rhine (type B) were much smaller either due to dilution of the clay fraction by coarser material or the admixture of clay particles eroded from the watershed which

222 400

6

150 T

100

50

+

10-20

20-30

3040

40-50

>50

grain size (pm) Fig. 4. Specific activities of ‘37Csfrom the Chernobyl fallout versus grain size in a sediment sample, composed of the “Chernobyllayers” of several type A sediment cores taken in the western part of Lake Constance.

were not contaminated by the 1986 fallout. Specific 137Csactivities increase with distance from the mouth of the river Rhine. Specific 13’Cs activities in front of the mouths of small tributaries (type C) are higher than for type B. This can be explained by the higher contamination of the catchments of these tributaries by the Chernobyl fallout and/or the input of smaller-sized,and therefore more highly contaminated clay particles. In sediments with an irregularly shaped 137Csdepth profile (type D) both larger and smaller specific activities were measured, and this was attributed to an accumulation (larger activity) or erosion (smaller activity) of fine grained and 137Cs-enrichedmaterial due to resuspension processes. From these results we can conclude that knowledge of the specific 137Cs activity can help to understand the different transport and sedimentation processes of suspended solids in Lake Constance. 4. ACKNOWLEDGEMENTS

These investigations were supported by Deutsche Forschungsgemeinschaft as part of Sonderforschungsbereich248 “Cyclingof Matter in Lake Constance”.

223

Y

0

!2

.z >

1000 l2O0

; %

3

0"

800

t

800

400

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200

0

3

4

5

8

17 21

22 23

2

7

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location

Fig. 5. Mean specificactivities of '37Cs from the Chernobylfallout in the sediment layer formed after 1986 at different locations in Lake Constance. These values were calculated from the '37Cs depth profiles. 1c s standard deviations were less than 5% for all locations.

5. REFERENCES 1.

2.

3.

4. 5.

6.

Santschi, P.H., S. Bollhalder, K. Farrenkothen, A. Lueck, S. Zingg and M. Sturm, 1988. Chernobyl radionuclides in the environment: tracers for the tight coupling of atmospheric, terrestrial and aquatic geochemical processes. Environ. Sci. Technol., 22: 510-516. Mangini, A., U. Christian, M. Barth, W. Schmitz and H.H. Stabel, 1990. Pathways and residence times of radiotracers in Lake Constance. In: M.M. Tilzer and C. Serruya (eds.), Large Lakes, Ecological Structure and Function. Springer Verlag, Berlin, pp. 245-264. Robbins, J.A., G. Lindner, W. Pfeiffer, J. Kleiner, H.H. Stabel and P. Frenzel, 1992. Epilimnetic scavenging and fate of Chernobyl radionuclides in Lake Constance. Geochim. Cosmochim. Acta, 56: 2339-2361. Richter, T., G. Schroder, S. Kaminski and G. Lindner, 1994. Transport of particles contaminated with Cesium radionuclides into the sediment of Lake Constance. Water Sci. Technol., 28 (8/9): 117-121. Kaminski, S., T. Klenk, G. Lindner, T. Richter, G. Schroder and M. Schulz, 1993. Die Bedeutung verschiedener Eintragsprozesse fiir die Verteilung von Casium-Radionukliden im Sediment des Bodensees. In: M. Winter and A. Wicke (eds.), Umweltradioaktivitdt, Radiookologie, Strahlenschuk, Verlag T W Rheinland, Koln, pp. 622-627. Kaminski, S., 1991. Radiocasium aus dem Tschernobyl-Fallout im Bodensee. GWF Wasser Abwasser, 132: 671-674.

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7. Dominik, J., A. Mangini and G. Muller, 1981. Determination of recent deposition rates in Lake Constance with radioisotopic methods. Sedimentology, 28: 653-677. 8. von Gunten, H.R., M. Sturm, H.N. Erten, E. Rossler and F. Wegmiiller, 1987. Sedimentation rates in the central Lake Constance determined with zlOPband 137Cs.Schweiz. Z. Hydrol., 49: 275-283. 9. Kaminski, S., T. Richter, T. Klenk and G. Lindner, 1994. Transport processes of cesium in a lake and its catchment system. In: Fourth International Conference on the Chemistry and Migration Behaviour of Actinides and Fission Products in the Geosphere, Charleston, SC, USA, December 12-17 1993. R. Oldenbourg Verlag, Munchen, pp. 493-498. 10. Comans, R.N.J., M. Haller and P. De Preter, 1991. Sorption of cesium on illite: Non-equilibrium behaviour and reversibility. Geochim. Cosmochim. Acta, 55: 433440. 11. Dittrich, A. and B. Westrich, 1988. Bodensee Ufererosion: Bestandsauhahme und Bewertung. Institut fur Wasserbau Universitat Stuttgart, Mitteilungen, Heft 68.

Freshwuter und Estuarine Rudioecology Edited by G . Desmet et id. 0 1997 Elsevier Science B.V. All rights reserved

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Sediment resuspension as a long-term secondary source of Chernobyl 13'Cs in lake ecosystems: the example of Blacksiistjiirn (Sweden) M. Meilia, L. Braa and K.Konitzera aInstitute of Earth Sciences, Uppsala University, Norbyvagen 18 B, 752 36 Uppsala, Sweden bInstitute of Limnology, Uppsala University, Norbyvagen 20, 752 36 Uppsala,Sweden

ABSTRACT Thousands of Swedish lakes have been heavily contaminated by the radioactive fallout from the Chernobyl nuclear accident in 1986,especially with 137Cs(up to 200 kBq m-*). The initially high concentrations of 137Csin small fish (up to 100 kBq k g ' ww) have declined since 1987, but this decline has slowed down since 1989, and concentrations are virtually stagnant since 1990-92. Accordingly, the ecological half-life of 13'Cs in fish is not constant but gradually increasing. The recovery of the lakes is probably delayed by substantial mixing and resuspension of bottom sediments, which usually contain >90% (often >99%) of a lake's 137Csinventory. Primarily in shallow near-shore sediments, mixing processes carry buried contaminated particles back to the sediment surface, where they are frequently resuspended into the water column, followed by an even redeposition over the whole lake. This selective erosion has resulted in a pronounced focusing of 13'Cs towards deep lake areas. The significance of resuspension is supported by comparisons of la7Cs concentrations in vertical sediment profiles, in surficial sediments, and in settling matter. Sediment resuspension can maintain high 13'Cs concentrations in lake waters, and resuspended as well as deposited particles are taken up by planktonic or benthic invertebrates, which are likely to assimilate associated 137Cs.Food chain transfer of both sedimented and resuspended 13'Cs may thus substantially retard the natural decontamination of lacustrine fish communities. The observed slow burial of contaminated particles suggests that the effects of the Chernobyl accident will remain a major problem in lakes for several decades. 1.INTRODUCTION

The reactor explosion at the Chernobyl nuclear power plant in April 1986 resulted in a severe contamination of the Swedish environment with several

226

radionuclides [l].Of major concern is 137Cs(fallout up to 200 kE3q m-'1, partly because of its long physical half-life of 30.2 years, partly because it is readily taken up by biota. From extensive monitoring, the number of Swedish lakes where the activity concentration in fish within the first two years exceeded the governmental guidelines of 1.5kBq kg-' (fresh weight) was estimated at 14000, and occasionally concentrations up to 100 kBq kg-' were observed [21. Various Scandinavian studies have shown that the radioactivity in small non-piscivorousfish started to decline already in 1987, one year aRer the fallout (e.g. Refs, [3-6]).At present, several years after the fallout, the contamination of small fish is still declining, but much more slowly than suggested by studies of physiological elimination (e.g. Ref. [71). The 137Csconcentration ratio between small fish or invertebrates and the ambient water (bioconcentrationfactors) has in many different lakes been observed to be fairly constant over time, suggesting a rapid equilibration of these animals with their environment. Accordingly, the slow recovery rates are controlled by a slow remobilization of 137Csfrom initial deposits. Long-term radioecological prognoses require therefore an understanding of the mobility and remobilization of 137Csin the abiotic environment. Most of the affected Swedish lakes are small water bodies (often c1 km2) with a low maximum depth (2-20 m). In these lakes, more than 90% (often >99%)of the 137Csinventory is contained in the bottom sediments [3,8,9].Even a minimal mobility of this large 13?Cspool can have considerable effects on the bioaccumulation of 137Cs.In such lakes, the shallow water depth invites to resuspension and horizontal redistribution of surface sediments. 137Csis therefore likely to be subjected to repeated cycling between sediments and water, and the turnover of sediments is most probably of greatest importance for the natural decontamination of these lakes. For this reason, we evaluated the horizontal and vertical distribution of 137Csin the sediment of a small softwater lake, where a time series of 137Csconcentrations in fish was available for comparisons. The study was focused on the vertical and horizontal transport of contaminated particles, and on the implications for the recovery of the lake from contamination. 2. METHODS Lake Blackslstjarn is located in central Sweden (61.7"N, 16.9"E) in an area where the deposition of Chernobyl 137Cswas around 20 kBq m-' or higher (Edvarson [lo] and pers. comm.), and at least tenfold higher than the total fallout remaining from earlier nuclear weapon tests. Lake BlacksPstjarn is a small humic forest lake (area 0.12 km', colour 70 g R m3, total organic carbon 10 g m3, phosphorus 12 mg m3). Sediments contain around 30% organic matter (dw).The maximum depth is 6.8 m, the mean depth 2.4 m, and the mean hydraulic residence time 0.5 years. The catchment (2.1 km') is covered by coniferous forest (76%),mire (16%),and arable land and pastures (9%).

227

Sediment cores were collected at 13 locations of the ice-covered lake in late March 1992.The cores (0 to 110 cm) were taken with gravity corers (inner diameter of 6.4and 6.9cm) and sectioned on site with a slicing device into subsamples of 5-40 mm, the thickness usually increasing with depth. All samples were analyzed for the content of water and 137Cs,and selected samples for bulk density, C and N. Measured activities of 137Cswere corrected for radioactive decay to 1 May 1986. Total inventories were calculated after conversion of weight-specific concentrations to volume- and area-specific values using water content and bulk densities. Further methodological details are given elsewhere [lll. Most fish data are part of a data set evaluated by Andersson and Meili [61 and were obtained according to methods described in [121. In 1994,new fish samples were taken and analyzed in the same way as the sediments. Fish data were decay-corrected to the sampling date. 3. RESULTS AND DISCUSSION

3.1. Chernobyl 137Csin lacustrine fish

The activity concentrations of 137Csin small perch (Perca fluviatilis) started to decline already one year after the fallout (Fig. l), similar to other non-piscivorous fish (e.g. Refs. [3-51). However, the annual decline has gradually slowed down, even in relative terms (percent per year). Accordingly, the ecological residence time, often conceived as an ecological “half-life”,of 137Csin lakes is steadily increasing over time, rather than being a constant for use in assessment models. Since 1990-92, four to six years after the fallout, the 13’Cs 1

m

1

-”

“E

01

-06 LL 0“

001

. c

B

0001 1986

1987

1988

1989

1990

1991

1992

1993

1994

Fig. 1. Changes in the relationship between Chernobyl fallout and the resulting activity concentration of 137Csin small perch (Perca fluuiutilis, 0.01 kg) observed in Lake Blacksistjam until 1994 (dots and bold line) and in 240 Swedish lakes until 1991 (range of data from Andersson and Meili 1994).The dashed line shows the slope expected from the physical decay of ‘37cs.

228

activities in small fish at low trophic levels have remained virtually unchanged until 1994,or have declined by only a few percent per year. This has been observed not only in BlacksLtjarn but also in other Swedish and Finnish lakes (unpubl. data from E. Andersson and R. SaxBn). The slow decline of the 137Csactivity in fish reflects a remobilization of 137Cs from initial deposits. In the case of small perch, which mainly feed on zooplankton, the prolonged 137Cscontamination is most probably mediated by the water. One potential secondary source of 137Csin lacustrine food webs is the remobilization from contaminated sediments, as long as these are not buried by clean particles. Vertical sediment core profiles of 137Csindeed showed that >>90% of the total amount of 137Cswas contained in the top 10 cm, and that most 137Cs usually was located in the upper 4 cm of the sediment. 3.2. Chernobyl 137Csin lake sediments

The total sediment inventory of 137Csat different sites in Lake Blacksfistjam varied from 4 t o 16 kBq m-' (Fig. 2).The lake mean inventory in 1992 was 6.9 kBq m-', as calculated by areally weighting the means from different bathymetric depth zones (<3.5m, >5 m, and intermediate). This is considerably less than the initial deposition of 13'Cs on the lake surface (around 20 kBq m-'1, in contrast t o other lakes where these values are similar [8,111.Moreover, the mean sediment inventory in 1992 was slightly less than in 1988 and 1989 [ 8 ] .This indicates that no net accumulation of 137Cshas occurred in the lake, neither during the first half nor during the second half of the period since the fallout, and suggests that the net inflow of 137Csfrom the catchment is insignificant. A clear relationship of I3?Cs sediment inventories with water depth was found (r = 0.83,Fig. 3).Profundal sediments contained several times more 137Cs than the shallow near-shore sediments. The increase of 137Csinventories towards the deep centre of the lake is also reflected by the maximum focusing factor of 2.3,which is the ratio between the highest inventory and the mean inventory [13].This pattern is common in stratified lakes (e.g. Refs. [11,131), and applies even to small lakes such as BlackslstjCirn,which is dimictic, with a typical epilimnion depth of 1.5-3.5 m during summer. The distribution of 137Csin the sediment can be explained by a selective resuspension of near-shore sediments followed by an even redeposition of contaminated particles over the whole lake. This results in a horizontal redistribution (focusing) of sediments towards the wave-protected bottoms in the deeper central part of the lake (e.g. Ref. 1141).Simultaneous resuspension and focusing of 13'Cs is indicated by the similarity of activity concentrations in littoral surface sediments and in sinking particles collected in epilimnetic sediment traps in the central part of the lake (unpublisheddata, see also Ref. [ll]). In fact, the contamination of settling material even during the summer season, when the water inflow from the watershed is small or absent, strongly

229

It

kBq m-*

100 m

Fig. 2. Bathymetry and total sediment inventories of '37Cs (Bq m-2) in Blackslstjarn, a forest lake in central Sweden, in spring 1992.

suggests that a large proportion of the settling 13?Cs originates from resuspended sediments. This may also apply to other seasons, as the decline of the total sediment inventory over time indicates that the water flow through the lake leads to a net export of 137Csfrom the lake, rather than to an input. A near-shore erosion of sedimentary 13?Csrequires that the suficial sediments still contain considerable amounts of 137Cs.This is evident from vertical sediment profiles of 13?Cs,showing a significant vertical mixing of near-shore sediments due to wind-induced turbulences or biological activity, usua!ly to a depth of several centimetres (unpublished data, cf. Refs. [9,11,151).Vertical mixing repeatedly brings contaminated sediments back to the sediment surface, and the burial with cleaner particles is inhibited or at least retarded. The vertical mixing of sedimentary 137Cs was less pronounced or absent in profundal sediments below the thermocline, which are protected from wave action during most of the year, and where bioturbation is low due to lack of oxygen and food. The maximum weight-specific 137Cs activity was in most cores located at a depth of 0.5-1.5 cm below the sediment surface. The depth of the 137Cspeak was roughly proportional to the water depth, as was the case for the 137Cs inventories, indicating again a higher net sedimentation in deep waters due to resuspension in shallow waters.

230

0

Cs-137inventory (kBq m-9 5 10 15

20

I

1 - 2 E

3 6 a B

4

I I

5 6

I

I T

I

0

0

Fig. 3. Relationship between water depth and total inventories of 13'Cs (Bq m-2, in the sediment of Blackslstjarn, a forest lake in central Sweden, in spring 1992. Lines show the typical range of the mixing depth in the water column during summer stratification(horizontal lines), and the area-weightedmean inventory of '37Cs in spring 1992 (verticalline).

3.3. Transfer of 137Cs from sediment to lake water and fish

The horizontal distribution of 137Csin the sediment (Fig. 3) showed in 1992 a deficit of about 2040% at shallow sites relative to the mean I3'Cs inventory observed in different years. This suggests an annual resuspension loss of 137Cs of a few percent from the littoral sediments, of which most is accumulated in the deep areas. An annual net loss of 5% from the shallow areas, which cover more than half of the lake area, and where sediments contain around 5 kBq m-', would correspond to a net flux from the sediment to the water of around 100-200 Bq m-' year-'. The 1992 sediment inventories in deep areas (12-16 kBq m-2)suggest that the gross resuspension flux is about 2-10 times higher, based on the assumption that the initial sediment inventory was around 8-10 kBq m-', while a large fraction of the fallout on the lake surface was rapidly removed from the lake by snowmelt water [2,81. The difference between gross and net flux simply reflects a repeated resuspension and settling of particles before deposition in deep areas, and is in agreement with sediment trap studies in similar lakes [ l l , 161. The influence of this resuspension flux on the 137Cs concentration in the water can be estimated from the residence time of resuspended particles in the water column. Based on a sedimentation velocity of 0.2-1 m d-', and an ice-free period of around 200 d year-', the average 137Cs concentration in the water due to resuspension alone is around 2-20 Bq m-3. Since most of the 137Csin natural waters is dissolved, the total concentration in the lake water maintained by equilibration with resuspended 137Cscan be several times higher. Consequently, resuspension of contaminated sediments is sufficient to explain the observed activity in fish (Fig. 11, given a bioconcentration factor of 1000 to 10000 in softwater lakes [171. In many lakes, resuspended sediments

231

constitute a dominant fraction of the suspended particles [161. Suspended particles are taken up by filtering zooplankton, whereby associated 137Csis likely to be transferred into the food chain to fish [18,191. Moreover, benthic animals, which also constitute an important source of food to fish, are exposed to the 13'Cs at the sediment surface. As a secondary source to biota, resuspension of 137Csis of particular importance during the most productive summer period, when the inflow of potentially contaminated water from the watershed is negligible. 3.4. Prognosis

From the vertical distribution of 137Csin sediments, a prognostic estimate can be made for the concentration of 137Csin the water and in biota maintained by remobilization of 137Csfrom the sediment. This process is controlled by the rate of sediment burial and by the depth of mixing in the sediment. The 137Cs profiles in the surface sediments of shallow sites representing the most bioproductive habitats indicate a depth of mixing of a few cm and a burial rate of around 1mm year-'. This suggests that the recovery of the surface sediments proceeds with a rate of a few percent per year, which is in agreement with the rates presently observed in fish. Since vertical sediment mixing will continue to retard the burial of Chernobyl 137Cs,future recovery rates may be of similar magnitude or lower. 4. CONCLUSIONS

Valuable insight into lake internal processes controlling the radioactivity in fish is provided by the horizontal and vertical distribution of Chernobyl 137Cs in lake sediments. The observed horizontal distribution of '37Cs in lake sediments can only be explained by an intermittent resuspension and redeposition of contaminated sediment particles. As long as surficial sediments are contaminated, this process maintains high concentrations of 137Csin lake waters. Resuspended as well as deposited particles are taken up by planktonic or benthic invertebrates, which are likely to assimilate associated 137Cs.Consequently, concentrations of 137Csin lacustrine food chains appear to be largely controlled by the turnover and burial of contaminated sediment particles. The observed rate of this process is very slow and suggests that the fish contamination from the Chernobyl fallout will remain a large-scale problem in many lakes for several decades, in particular if the immobilization of 137Cscontinues to slow down. Eventually, the ecological residence time of the radioactivity in fish may be determined by the physical decay of 137Csand approach a half-life of 30 years. 5. ACKNOWLEDGEMENT

This study was financially supported by the Swedish Radiation Protection Institute.

1. Moberg L., (Ed.), 1991. The Chernobyl Fallout in Sweden. Swedish Radiation Protection Institute, Stockholm, 631 pp. 2. Hlkanson, L., T. Andersson and A. Nilsson, 1992.Radioactive caesium in fish in Swedish lakes 1986-1988 - General pattern related to fallout and lake characteristics. J. Environ. Radioactivity, 15:207-229. 3. Broberg A.and E. Andersson, 1991.Distribution and circulation of Cs-137in lake ecosystems. In: L. Moberg (ed.), The Chernobyl Fallout in Sweden. Swedish Radiation Protection Institute, Stockholm, pp. 151-175. 4. Meili, M.,T. Forseth, S. Nordlinder and R. Saxen, 1991.Radioactivity in fish and turnover of radiocesium in lacustrine food webs, in Radioecology in Nordic Limnic Systems. National Swedish Environmental Protection Board, Solna, Report 3949, 5.185.25. 5. Saxen, R., 1994. Transport of 137Csin large Finnish drainage basins. In: H. Dahlgaard (ed.), Nordic Radioecology - The Transfer of Radionuclides through Nordic Ecosystems to Man. Elsevier, Amsterdam, Studies in Environmental Science, Vol. 62,pp. 63-78. 6. Andersson T. and M. Meili, 1994.The role of lake-specific abiotic and biotic factors for the transfer of radiocesium fallout to fish. In: H. Dahlgaard (ed.), Nordic Radioecology -The Transfer of Radionuclides through Nordic Ecosystems to Man. Elsevier, Amsterdam, Studies in Environmental Science, Vol. 62,pp. 79-92. 7. Ugedal, O., B.Jonsson, 0. Njdstad and R. Naeumann, 1992.Effects of temperature and body size on radiocaesium retention in brown trout (Salmo trutta). Freshwater Biol., 28:165-171. 8. Meili, M., A.Rudebeck, A. Brewer and J. Howard, 1989.Cs-137in Swedish forest lake sediments, 2 and 3 years after Chernobyl. In: W. Feldt (ed.), The Radioecology of Natural and Artificial Radionuclides. Verlag T W Rheinland GmbH, Koln, Germany, Publ. Ser. Prog. Radiat. Prot., 22: 306-311. 9. Kansanen, P.H., T. Jaakkola, S. Kulmala and R. Suutarinen, 1991.Sedimentation and distribution of gamma-emitting radionuclides in bottom sediments of southern Lake Piiijiinne, Finland, after the Chernobyl accident. Hydrobiologia, 222: 121140. 10. Edvarson, K., 1991. Fallout over Sweden from the Chernobyl accident. In: L. Moberg (ed.), The Chernobyl Fallout in Sweden. Swedish Radiation Protection Institute, Stockholm, pp. 47-65. 11. Konitzer K. and M. Meili, 1995.Retention and horizontal redistribution of sedimentary Chernobyl 137Csin a small Swedish forest lake. Mar. Freshwater Res., 46: 153-158. 12. HBkanson L. and T. Andersson, 1992. Remedial measures against radioactive caesium in Swedish lake fish after Chernobyl. Aquat. Sci., 54: 141-164. 13. Eadie B.J. and J.A. Robbins, 1987.The role of particulate matter in the movement of contaminants in the Great Lakes. In: R.A. Hites and S.J. Eisenreich (eds.), Sources'and Fates of Aquatic Pollutants. American Chemical Society, Washington, D.C., Advances in Chemistry Series, 216:319-364. 14. Hilton, J., 1985.A conceptual framework for predicting the occurrence of sediment focusing and sediment redistribution in small lakes. Limnol. Oceanogr., 30:11311143.

233 15. Broberg, A,, 1994. The distribution and characterization of 13’Cs in lake sediments. In: H. Dahlgaard (ed.), Nordic Radioecology - The Transfer of Radionuclides through Nordic Ecosystems to Man. Elsevier, Amsterdam, Studies in Environmental Science, Vol. 62, pp. 45-62. 16. Weyhenmeyer, G.A., M. Meili and D.C. Pierson, 1995. A simple method to quantify sources of settling particles in lakes: Resuspension versus new sedimentation of material from planktonic production. Mar. Freshwater Res., 46: 223-231. 17. Rowan D.J. and J.B. Rasmussen, 1994. Bioaccumulation of radiocesium by fish: the influence of physicochemical factors and trophic structure. Can. J. Fish. Aquat. Sci., 51: 2388-2410. 18. Meili, M., 1988. Radioactive caesium in Swedish forest lake ecosystems after Chernobyl: Zooplankton 1986, Sediment 1988. Proc. 5th Nordic Seminar on Radioecology, Rattvik, Sweden, August 22-26. 19. Meili, M., 1991. The importance of feeding rate for the accumulation of radioactive caesium in fish after the Chernobyl accident. In: L. Moberg (ed.), The Chernobyl Fallout in Sweden. Swedish Radiation Protection Institute, Stockholm, pp. 177182.

Freshwuter und Estuurine Rudioecoloy Edited by C . Desmet et al. 0 1997 Elsevier Science B.V. All rights reserved

235

The role of the rivers in Chernobyl radiocesium delivery, distribution and accumulation in coastal sediments of the Northern Adriatic Sea Roberta Delfantia, Mauro Frignanib, Leonard0 Langoneb, Carlo Papuccia and Mariangela Ravaiolib aCentro Ricerche Ambiente Marino, ENEA, CP 316, 19100 La Spezia, Italy 'Istituto per la Geologia Marina del CNR, Via Gobetti 101, 40129 Bologna, Italy

ABSTRACT The fate of radiocesium transported by rivers to the Adriatic Sea and accumulated in sediments was investigated in the Northern Adriatic coastal area. Concentrations and inventories obtained for the areas of influence of the most important rivers (Tagliamento, Isonzo, Piave, Adige and Po) were compared. Radiocesium preferentially accumulates in the prodelta areas. In 1987 137Csmaximum concentrations and inventories in these zones ranged between 200 and 300 Bq kg' and between 12 and 64 kBq m-2, respectively. The temporal dynamics in selected zones was studied by sampling at the same site in different years. Temporal differences in the radionuclide inventories show that some areas are unstable on the time scale of one year due to sediment resuspension processes.

1. INTRODUCTION

The accumulation of radiocesium in coastal marine sediments provides a means of understanding the mechanism of delivery of riverine material from land to the coastal environment. After the Chernobyl accident, the distribution of natural and anthropogenic radionuclides in selected areas of the Northern Adriatic Sea was described by Frignani et al. [ l l , Frignani and Langone [2], Albertazzi et al. [31, and Delfanti et al. 141, but a general picture of the behaviour of radiocesium in the whole Northern Adriatic was lacking. The aim of this work is to understand how coastal processes interact with riverborne material to control the distribution of surficial activities and inventories of radiocesium in coastal sediments and the temporal dynamics of the system. For this purpose we sampled more than 70 stations from 1986 to 1990, using box corers and

236

gravity corers. Sediment cores were sectioned at 0.5 t o 3 cm intervals, dried and analyzed by gamma spectrometry. For most locations, activity profiles to a depth of at least 20 cm were obtained. 2. RESULTS AND DISCUSSION

The Northern Adriatic Sea is a shallow basin (maximum depth 30 m), strongly influenced by the discharges of some of the most important Italian rivers: Tagliamento, Isonzo, Piave, Adige and Po. Sampling sites were chosen based on the sedimentological textural map of the area shown in Fig. l c [51, with a preference for the zones characterized by fine sediment accumulation and close to the major river mouths. Some sampling locations and results of the analyses are summarized in Figs. l a and lb, and Table 1. The following discussion is based on two main parameters: (a) 137Cssurface activity (Bq kg-'1, useful to define the extent of the area influenced by river discharges; (b) I3'Cs integrated activity in the sediment core per unit surface. The inventory (kBq m-') is a function of both the concentration of the radionuclide in particles being deposited and the sediment accumulation rate. This parameter can be used to identify sites of maximum deposition and accumulation and to estimate the relative importance of the different sources of radionuclides (direct bomb and Chernobyl fallout, river supply) to the coastal marine environment, Its time evolution gives information on the stability of the deposits of riverborne material in the continental shelf. In any case we determined activity profiles of both 134Csand 137Csin the sediment cores. We focus on I3'Cs values because this isotope is a better tracer for processes on a time scale of years, while 134Csactivities vary more rapidly due to its short half life. 134Cs,being a specific tracer, was used to estimate the depth of penetration of Chernobyl 13%sinto the sediment column. In 1987, 137Csactivities in surficial sediments ranged from a minimum of 0.5 Bq kg-I to a maximum of about 300 Bq kg-'. The lowest values were found in the sandy areas offshore (relict sands) where the balance between deposition and resuspension results in no net accumulation of recent material. Relatively high values, between 2 and 20 Bq kg-', are characteristic of fine sediments, while the prodelta areas of the rivers show the highest activities. This indicates that rivers may be the most important suppliers of radionuclides to the coastal environment in this area, even in presence of significant atmospheric input. Data from samples taken from the same and other areas in the period 19881990, and discussed elsewhere L2-41, substantially confirm the same pattern for the prodeltas of the major rivers (Isonzo, Tagliamento, Piave, Adige and Po). The inventories span between 0.1 and 60 kBq m-', with low values in coarse sediments, 0.4-5 kBq m-' in fine sediments and up to 16.5 and 60 kBq m-' in the prodelta areas of the Po and Isonzo, respectively. In the upper 20-30 cm of sediment, the integrated activity of Chernobyl I3"Cs is up to 90-100% of the

Fig. 1. Sampling locations and surficial distribution of 137Csactivities (Bq kg-' d.w.1 near the mouth of the rivers Tagliamento and Isonzo (a) and Po (b). Sedimentologicaltextural map of the study area (c);after Brambati et al. Ref. [51).

total inventory in the prodelta samples, 20-30% in fine sediments and only a few percent in offshore sand. The huge inventory near the Isonzo mouth is probably due to the high concentration of radiocesium in particles transported

238

by the river in combination with the very high accumulation rate ("Cs was found in November 1987 down to 26 cm in a sediment core). For a discussion on the relative importance of the different sources of Chernobyl 137Csto coastal sediments, we can assume that direct deposition from the atmosphere in the study areas of Figs. l a and l b is 5 and 3.5 kBq m-' respectively, as reported for the land areas nearby [6,71. Comparing these fluxes with the inventories, the presence of 13'Cs in Northern Adriatic coastal sediments could be entirely accounted for, in most cases, by atmospheric deposition, but it is unlikely that after the Chernobyl accident such an efficient transfer of fallout to the coastal sediment occurred on a short time scale. In contrast, the prodelta areas have the highest inventories, that are well above the fallout delivery and definitely related to river supplies. This holds for four of the five prodeltas in the study area. The stability of temporary deposits in the prodelta areas is analyzed by comparison of inventories obtained in different years at the same site. Some TABLE 1 Inventories of 1 3 7 C(kBq ~ m-2) in sediment cores from the Northern Adriatic Sea. The year of sampling is given in parenthesis with further detail for 1987 (587is June 87 and N87 is November 87).No. indicates the number of cores; when two or more cores were studied the range between maximum and minimum values is reported. The sign > means that the value is a minimum estimate, because the base of the profile was uot reached due to the shortness of the box core. Area

Prodelta mud

No.

Shelf mud

No.

1

1.8-5.8(587) 6.3(N87) 2.3-4.7(88)

3

64.0(N87)

2 1

Isonzo

Offshoresand

No.

1.2 (587)

1

0.1-0.8(86)

4

1

2

21.1(89)

1

11.8(587) 15.4 "87)

1 1

17.4 (89)

1

1.9-2.3(587) 4.0(N87) 2.8(88) 6.3(89)

Piave

6.2(88)

1

0.4-0.7(89)

2

Adige

2.5 (86) 4.0 (88)

1 1

1.3-2.0(86) 2.4(89)

6

>16.5(587) >6.0(89)

1 1

1.1-2.9(587) 1.8-3.7(89) 3.7(90)

10 3 1

0.4-0.7(587)

7

0.6(90)

1

1.1-2.9(587) 1.9-3.2(89) 2.7(90)

10 3 1

0.6(90)

1

Tagliamento

Po della Pila

Po di Goro

5.1-9.1 (587) 2 >21.5(90)

1

1 1

1

239

zones were sampled several times and two sets of data are particularly interesting. Table 1shows that in the Tagliamento prodelta the inventory increases during the period considered (1987-1989). Here the sediment column contains only Chernobyl radionuclides in a thin layer overlying coarse sediment, in which no artificial radionuclides have been detected, indicating that in this shallow area, periods of sediment accumulation follow events of erosion which are effective at removing sediment layers as thick as several centimetres. These episodic erosions are effective on a time scale of several years, since between 1987 and 1989 there were prevailing depositional conditions. In the other zones we can assume similar trends even if the data are less complete. In the case of the Isonzo area the inventories show significant diminutions over the same period. This is due to an instability of this system on a shorter time scale than in the case of the zone near the Tagliamento. The zone near Po della Pila shows similar behaviour. 3. CONCLUSIONS

Although the atmospheric delivery of Chernobyl radionuclides to this environment is quantitatively important, the distribution of radiocesium in coastal sediments is mainly controlled by rivers. Oceanographic processes control the spatial re-distribution of the material transported by the rivers and temporarily deposited in the prodelta areas which are influenced by erosion events on a time-scale of years or less. 4. ACKNOWLEDGEMENTS

This work was partially carried out under the CEC-ENEA contract no. FI3PCT92-0046. We wish to thank G. Zini who made the drawings and S.Albertazzi, M. Alboni, R. Lorenzelli who helped in sample preparation and analysis, and D. Hirschberg for helpful comments. This is contribution no. 973 from the Istituto per la Geologia Marina del CNR, Bologna. 5. REFERENCES 1. 2. 3.

Frignani, M., L. Langone and M. Ravaioli, 1988. Radionuclide activity-depth profiles in sediments of the Gulf of Venice (Italy). Rapp. Comm. int. Mer Mbdit., 31 (2): 311. Frignani M. and L. Langone, 1991. Accumulation rates and 137Csdistribution in sediments off the Po River delta and the Emilia-Romagna coast (Northwestern Adriatic Sea, Italy). Cont. Shelf Res., 11: 525-542. Albertazzi, S.,M. Alboni, M. Frignani, L. Langone, M. Ravaioli and E. Tesini, 1992. Chernobyl derived radiocesium in marine sediments near the Po River delta. Rapp.

240 Comm. int. Mer MBdit., 33: 337. Delfanti, R., V. Fiore, C. Papucci, R. Lorenzelli, S. Salvi, M. Alboni, L. Moretti and E. Tesini, 1992. Monitoraggio della radioattivita’ ambientale nell’Adriatico centrosettentrionale. In: Proceedings of V Congresso Nazionale della Societh Italiana di Ecologia, Atti SItE, 15: 739-742. Brambati, A., M. Ciabatti, G.P. Fanzutti, F. Marabini and R. Marocco, 1983.A new sedimentological textural map of the Northern and Central Adriatic Sea. Boll. Oceanol. Teor. Appl., I: 267-271. Battiston, G.A., S. Degetto, R. Gerbasi, G. Sbrignadello and L. Tositti, 1988. Fallout distribution in Padua and Northeast Italy a h r the Chernobyl Nuclear Reactor Accident. J. Environ. Radioactivity, 8: 183-191. Belli, M., M. Blasi, A. Borgia, F. Desiato, M. Poggi, U. Sansone, S. Menegon and P. Nazzi, 1987. Indagini radioecologiche nella regione Friuli Venezia Giulia: primi risultati dell’indagine nell’ambiente agricolo della pianure friulana. Doc.DISP/ ARAISCA(1987)21, ENEA Roma, 28 pp.

Freshwater und Estuarine Radirieecolrigy Edited by G. Desmet et al. 0 1997 Elsevier Science B.V. All rights reserved

241

Distribution of artificial radiocontamination in lagoon environment of northern Adriatic C. Giovania, G. Mattassib, R. Padovania, A. Zanellob and S. Zaninia 'Servizio di Fisica Sanitaria, Lab. Reg. Rad. Ambientale USL, Udine, Italy bServizio di Igiene Ambientale, USL, Palmanova, Italy

ABSTRACT In 1991 the authors started a multi-annual program for monitoring environmental radioactivity in the northern Adriatic, in order to evaluate the diffusion of artificial radionuclides in areas close to coasts and lagoons between Grado and Punta Tagliamento. This program involves the sampling of environmental matrices in different seasons. The contamination deriving from the Chernobyl accident was evaluated using 134Csand 13?Cs,and the pollution deriving from medical use of radionuclides was evaluated through 1311. The work presents the main results on artificial radionuclide contents in algae and surface sediments during the first three years of monitoring. Relationship between sediment grain-size distribution and 137Cscontent are presented. Moreover the use of algae as biological indicators of radionuclides in marine environment, as well as for heavy metals, nutrients and microorganisms are discussed.

1. INTRODUCTION

Due to orographic effects and intense precipitation in 1986, fallout from Chernobyl has heavily contaminated the Friuli-Venezia Giulia region (NEItaly, Fig. 1). The mean value of 13'Cs surface activity for mountain areas was 25 kBq/m2 [ 11.Radiological investigations performed in Marano and Grado lagoons [2] and in Trieste littoral area 131 in the years following the Chernobyl accident pointed out the presence of artificial radionuclides in coastal and lagoon areas of FriuliVenezia Giulia region. On this basis, in 1991 the authors started a multi-annual program for monitoring environmental radioactivity in the Northern Adriatic, in order to evaluate the diffusion of artificial radionuclides in lagoons and areas close to coasts between Grado and Punta Tagliamento(Fig.2). The samplingprogrammes

242

Adrlillc 681

Fig. 1. Friuli-Venezia Giulia region (NEItaly).

Fig. 2. 137Csdistribution in sediments (Bqkg-' d.w.1in December 1991.

243

involve different environmental matrices (surface sediments, algae, filter feeders, molluscs, macrobenthos, ichtyc fauna) in different seasons. In order to evaluate contamination deriving from the Chernobyl accident, lMCsand 137Cs were examined, the evaluation of pollution deriving from medical use was evaluated through 1311. In this paper we present some of the main results concerning the distribution of 1311, 134Csand 137Csin algae and surface sediments. Moreover the correlation between 137Csconcentrations in algae and in sediments are investigated. The correlation between sediment grain-size distribution and 137Csconcentrations in sediments are also studied. 2. METHODS AND MATERIALS

The northern part of the Italian coast of the Adriatic Sea is characterized by a series of lagoons, from Ravenna to the Isonzo river. The investigated area, denominated as Grado and Marano lagoons, is located in the northernmost part of the Adriatic Sea, limited on the west by the Tagliamento river and on the east by the Isonzo river. Many rivers flow into the Marano lagoon which has more complex water exchanges than the area of Grado lagoon because of its small number of openings to the sea. In 1991 40 sampling sites were chosen in the Grado and Marano lagoons area to determine the main pathways of diffusion of polluting agents. Some of them were in the final tract of the rivers, others in the lagoons themselves and finally some in the marine area close to lagoon openings and to the Tagliamento and Isonzo mouths. In order to improve the investigations of I3lI sediment contamination and 137Cssediment contamination in the external marine area further sampling sites were added in the following years. Two samplings (usually Autumn and Spring) per year were performed, beginning December 1991. Ulua and Gracilaria genera, if present, were collected every time. Unfortunately, in 1993 algae were completely absent from the lagoon. Surface sediments (0-2 cm) were collected by means of a Van Veen grab only in the Autumn samplings for a total of 140 samples. Gamma spectrometry measurements were carried out by 4 high-purity intrinsic germanium detectors with relative efficiencies from 18%to 80%.'34Cs, 137Cs,1311 activities were considered. Samples were measured in 1-1 Marinelli beakers. Sediment samples were untreated while algae samples were homogenized. Both sample sets were measured fresh and then dried . All data are expressed by dry weight. Counting times varied from 10000 to 70000 s according to sample activity. Reference time for radiometric data is the sampling time except where indicated otherwise. Grain-size distribution was determined by wet sieving. Samples were divided into 4 fractions according to the grain sizes: 0 >1 mm, 63 pm < 0 < 1 mm, 38 pm < 0 < 63 pm, 0 c 38 m.

244

3. RESULTS 3.1. Caesium-134 and Caesium-137

Table 1reports mean 137Csand 134Csconcentrations and their standard deviations for all sampling locations for three successive years, and the '37Cs/'34Cs ratios, These data refer to 1st May 1986. It can be noticed that while the mean values are quite constant in the years 1991and 1992, the 1993 137Csconcentration is lower than the earlier values. This result can be explained by the very high resuspension due to the extraordinary precipitation that occurred before the 1993 sampling. '37Cs/'34Csratios are in all cases greater than 2 due to the presence of pre-Chernobyl 137Csfrom nuclear tests. Because of the physical decay, in 1993, '"CS was detected only in 17 sediment samples. For this reason the 134Csmean concentration from the 1993 sampling cannot be compared with the concentrations from 1991 and 1992 samplings. In any case, the higher '37Cs/'34Csratio for the 1993 data can also be explained by the exceptional precipitation before sampling, which could remove a greater part of the surface sediments. 134Cscontent in Ulua and Gracilaria samples was often under the minimum detectable activity. '37Cs/134Cs mean ratio in 5 UZua samples collected in 1991is 2.44 (reference time: 1st May 1986). In a previous paper 141 the authors presented the 137Csdistribution in sediments in December 1991 (Fig. 2). The results were used to distinguish 4 different areas according to the level of radiocaesium contamination: (a)river mouths, where the highest concentration were detected (up to 90 Bq kg-' d.w. at the Isonzo mouth); (b) lagoons: higher concentrations were detected in the Marano lagoon, which has more river contributions and lower water exchange in comparison with Grado lagoon; (c) marine area close to lagoon openings: this area shows the lowest absolute concentration (i.e. 0.1 Bq kg-' d.w.1; (d) external marine area: in this area high values were detected again (up to 70 Bq kg-' d.w.1. Analogous results about 13?Csdistribution were obtained by other authors [ 5 ] . Caesium-137 concentration in sediments (Bq kg-' d.w.) collected in 1991vs 63 pm-1 mm fraction percentage is shown in Fig. 3. The correlation is negative and significant (r = 0.758, p < 0.1%). TABLE 1 134Csand 137Cs concentrations in sediments from 1991, 1992 and 1993 sampling programmes (mean values and standard deviations) and '37Cd'34Csratios. Activity data and ratios refer to 1st May 1986 137cs

n

26.9 (25.4) 25.3 (24.1) 20.0 (17.8)

40 40 40

(Bq kg-' d.w.1 1991 1992 1993

'34cs

n

13.1 (10.4) 12.0(10.4) 12.0(5.4)

31 31 17

(Bqkg' d.w.1

.

137cs/134cs

(Bq kg-' d.w.1 2.1 (0.5)

2.8 (0.5) 3.0(0.4)

n

31 31 17

245

C s - 1 3 7 (Bq/kg d . w . ) i n sediments 80

-____

r=O.758 P
~

G r a i n - s i z e d i s t r i b u t i o n (% o f 63um-lmm f r a c t i o n ) Fig. 3. 13"Csconcentration vs grain-sizein sediments of 1991 sampling (% of the 63 pm-1 mm fraction).

r-

C s - 1 3 7 (Bq/kg d . w . ) i n U l v a sp.

8o

r=O.880 p
Cs-137 (Bq/kg d . w . ) i n sediments Fig. 4. 13"Csconcentration in Ulva samples (Bq kg-' d.w.)vs '37Cs concentration in sediments in the same sampling sites (May 1992).

In order to investigate the correlation between algae and sediment 137Cs concentrations, the genus UZva was chosen because of its abundance in the sampling area. 137Csconcentration in UZua samples vs 137Csconcentration in sediment samples collected in 1991 is shown in Fig. 4. The correlation is positive and significant ( r = 0.880,p c 0.1%).

246

. . AussaR. . ' . '. . ' , ' . . . . .:.. . . .CormorR. . . . . . . , :. . ' . . . .:. . , ,, . -., . .. . . . . .. . . . . . . .'.CornoR. .. '

'

'

t

.

'

_

:.

. . . . . ... . . . . ,.. . .. .

.

.

. .. . . . . . . .. . . .

..

.

. . . . . . .

Rdrialic Sea

.

< 5 Bq/kg d.w.

(1 0 Bq/kg d.w.

Zm >10 Bq/kg d.W. Fig. 5. 1311 distribution in UZua sp. in samples in May 1992 (Bq kg-' d.w.1.

3.2.Iodine-131

Figure 5 [4] shows the 1311 distribution in Ulua samples collected in May 1992. In the western part of the Marano lagoon, at the Cormor and Stella mouths, the highest values of 13'1 were detected. The concentration decreases towards Grado lagoon and lagoon openings. Because of these results, in November 1992 4 sediment samples were collected along the Cormor river, which conveys waters coming from Udine and towns nearby. The first sample was collected at the mouth of the river and the other respectively at 8,13.5and 18 km from the mouth. 13'1 contents (Bq kg-' d.w.1 are shown in Fig. 6. 4. CONCLUSIONS

Dynamics of water exchanges inside lagoon environment is quite complex, thus the comprehension of the dynamics of the diffusion of pollutants is rather difficult. However, experimental results allow us t o say that rivers are the principal means for transport and distribution of radionuclides in near shore environments, as well as for heavy metals, nutrients and microorganisms [61.

247 1-131 c o n c e n t r a t i o n i n sediments (Bq/kg d.w.) _____

______

-___

0 8 13 18.5 Distance from t h e Cormor r i v e r mouth (km) Fig. 6. 13’1 concentration (Bq kg-’ d.w.1in sediment samples from the Cormor river.

Because of the persistence of pre-Chernobyl radiocaesium in surface sediments and the uniformity of radiocaesium mean values in successive years, lagoon environments seem to be a sink for this kind of pollutant. Grain-size distribution strongly affects radiocaesium absorption on sediments, and as a consequence it is important to take into account of this variable in investigations of spatial radiocaesium distribution in sediments. ratio in UZua samples it appears possible to On the basis of the 137Cs/’34Cs say that the pre-Chernobyl 137Csis not available for aquatic organisms. However, because of the low number of data, this hypothesis has to be validated. The significance of the correlation between 137Csconcentrations in algae and sediments confirms the role of these kinds of organisms as biological indicators of radiocontamination as well as of conventional pollutants. The peculiar affinity of algae for iodine allows easy detection of 1311 contamination coming from the wide use of this isotope in medicine. Next spring, algae collection and the planned sampling and analysis of matrices other than sediments and algae will allow us to highlight the peculiarity of different organisms as indicator of trace pollutants, as well as to validate the hypothesis that are not presently supported by a sufficient number of species or samples. 5. ACKNOWLEDGEMENTS

The authors wish to thank Dr Stefania Franchi, Mr Claudio Zanatta and Mr Livio Zanatta of ‘Settore Igiene Pubblica’ of Palmanova for their help during the samplings.

248

6. REFERENCES 1.

2.

3.

4.

5.

6.

Padovani, R., Contento, G., Giovani, C. and Malisan, M.R., 1990. Field study of fallout radiocaesium in upland soils, in: G. Desmet, P. Nassimbeni and M. Belli (eds.), Transfer of Radionuclides in Natural and Seminatural Environments. Elsevier, London and New York, pp. 292-299. Belli, M., Blasi, M., De Guarrini, F., Franchi, M. Giacomelli, R., Marinaro, M., Mattassi, G., Nocente, M., Sansone, U., Spezzano, P. and Ventura, G., 1989. Risultati di due anni di indagini radio-ecologiche nelle lagune di Marano e Grado Sicurezza e Protezione no. 21, pp. 77-88 Tassi Pelati, L. and Albertazzi, S., 1988. The impact of Chernobyl fallout on Adriatic sea near Trieste and Ancona. Preliminary evaluation and comparisons, 2nd International Contact Seminar in Radioecology, Universith Agraria Piacenza. pp. 133-144 Giovani, C., Daris, F., Mattassi, G., Padovani, R. and Zanello, A., 1992. Cs-137 and 1-131 Distribution in Lagoonal and Coastal Environment in Northern Adriatic, in: Rapports et proces - Verbaux des Riunions, XXXIIIe Congres-Assemble Pleniere de la Commission Internationale pour 1’ExplorationScientifique de le mer Mediterranee, Trieste 12-17 ottobre 1992, Rapp. Comm. Int. Mer Medit., 33: 337. Albertazzi, S., Hieke Merlin, O., Menegazzo Vitturi, L., Molinaroli, E. and Tassi Pelati, L., 1987. Distribution and behaviour of Cs-137 in nearshore sediments of the northern Adriatic and at the Adige River estuary, northern Italy. Appl. Geochem., 2: 3574366 Mattassi, G., Daris, F., Nedoclan, G., Crevatin, E., Modonutti, G.B. and Lach S., 1991. La qualita delle acque della laguna di Marano, U.S.L. no. 8.

Freshwuter ond Estuurine Rudiiiecihgy Edited by G. Desmet et nl. 0 1997 Elsevier Science B.V.All rights reserved

249

Recent radioecological investigations in the Austrian part of the Danube river F.J.Maringera, M. Tschurlovitsband D. Ranka aBundesforschungs-und Priifzentrum Arsenal, Faradaygasse 3, A-1030 Vienna, Austria bAtominstitute of Austrian Universities, Schiittelstrasse 115, A-1020 Vienna, Austria

ABSTRACT Radionuclides present in the Danube catchment area were used to investigate the behaviour of radionuclides in the Austrian part of the Danube river. Sampling of different compartments such as water, suspended matter and fine sediment was carried out from 1989 to 1992;on some sites since 1987.Measurements of some radionuclides of these complementing samples, which were taken at different locations on the Danube river in Austria on a monthly basis lead to well proved results. Investigations were devoted to the influence of high-water flooding on the behaviour of the radionuclides in the system. The results were taken as a basis for evaluating environmental parameters, modelling and dose assessment to give a uniform view of the radioecology in the Austrian part of the Danube river.

1. INTRODUCTION

Recently, various measuring programs beyond routine monitoring were carried out in the Austrian part of the Danube river. Some of them were concerned with long-term investigations on radionuclide concentrations in water and dose assessment [1,21.Another program was concerned with a detailed investigation of radionuclide concentration in fish 131. Special attention was paid to the assessment of activity concentrations of H-3 since the early sixties [4]. The present project complements the previous programs by in situ investigations of the environmental behaviour of radionuclides in sediments and suspended matter under the conditions appearing in a three-year investigation period including seasonal variations and other influencing parameters. Some of the data generated in this program are shown and some details and other aspects are discussed in brief.

250

For routine monitoring and interpretation of radioactive contamination of surface water it is necessary to know the variation and distribution of activity and the influencing parameters to reduce both equipment and manpower cost. With the aid of the present investigations, which were carried out to complement previous projects, parameter assessments for radioecological models concerning water-solid matter interactions were made to provide a well proved basis for optimisation of routine environmental monitoring programs. 2. MAmRIALS AND METHODS

The sampling concept for this project is based on a daily collection of 2 1of water from a depth of 1.5 m from 4 locations in the Austrian part of the Danube and continuous sampling of sediment in traps. The water samples were combined to give a single monthly sample of about 60 1. Suspended material and water were separated by flow-through centrifugation. Each 60 1 water sample was centrifuged continuously for about 3 h at 10000rpm (Haereus Laborzentrifuge 15000).This rotation speed caused a centrifugal acceleration of 75000 m s-' and separated solid particles (density 2.6 g cm3) with Stoke's diameters of > 0.4 pm from the water sample. The 60 1 water samples free of suspended matter were evaporated in large volume (20 1)vacuum rotation evaporation flasks (Rotavapor) to preconcentrate the dissolved radionuclides for radiometric measurement. The amount of solid evaporation residue of a 60 1 water sample was between 15 and 20 g. This procedure lasts about 24 h for a 60 1 water sample. After pretreatment, the centrifbged and evaporated residues and homogenised sediments were dried at 105°C.The gamma emitters were determined with low-level gamma spectrometry equipment (HP-Ge detector), the 'OSr content was measured with low-level proportional counters after radiochemical separation (nitric method). 3. RESULTS

The complete experimental data of the investigation period are found in detail elsewhere [51. As an example the variation of the I3'Cs activity in the water at a given site is shown in Fig. 1.One can see that the particle bound radioactivity is strongly related to the discharge (flow rate). Caesium-137 is transported mainly (about 90%) with suspended matter, leading to a total annual activity of about 1TBq. Figures 2 and 3 show the long-term trend of 137Csand 3Hin the Danube river. As a consequence of the Chernobyl accident the 13?Cscontamination of sediments increased from about 5 to 10 Bq kg-' to some, thousands Bq kg-' [6].After a rapid decrease of 137Csactivity between 1986 and 1987, a slower decrease with an ecological half-life of about 4 years followed (Fig. 2). The 3Hconcentration

251

3

8q/m3 activity concentration 5 - r , . , , , ,

,

,

.

.

,

,

.

,

.

discharge; suspended matter conc. m”s , . . . , . . , . . , . I 3500

g’m3 350

11121 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 2 3 4 5 6 89

I

90

I

91

I

92

sampling period

Fig. 1. Caesium-137 in water, Total and dissolved part of activity.

sampling period

Fig. 2. Course of ‘37Cs in sediments, Danube, Vienna.

(decreasingsince the atomic weapons test period in the sixties) was not affected by the Chernobyl accident (Fig. 3 , l TU = 0.12 Bq kg-’). Further discussion can be found in Ref. [41.

252

+ Precipitation: Men, Hobe Work

.-.-Dnnuba Men, Reichsbflcke

Fig. 3. H-3 in water and precipitation, Danube km 1931 (Vienna).

susp. matter

water

sediment

700

Ra-226

600 IJ) 120 E 110 m" 100 d 90 -

2 p !'

5m

6050 40 30 20 -

7 1 7 1 r

Fig. 4. Distributions of 22%aand 21%, Danube, 1989-1992.

' ,j

c

500 400

L>' 300

2 200 100

0

solids

253 5

I

1

I I

1

1

731 1 5 3

I I

I

I

0

O

I I I 1

i

I

1

I I

I

r-

f E Y cv

c

F

J,

I

1

I

I

c Q)

. I

0

I

a3 0

E Y r-*

m

I

m

i

0

E

Y

r; m

I-0

3 3 7

F

0

P

Y

$2

N

Fig. 5. Activity ratio, suspended mattedsediment, Danube, 1989-1992.

As an example of natural radioactivity the distributions of the 226Raand 'loPb activity concentrations at different sampling locations are presented in the form of box-plots (25-75% quantile boxes with median lines, error bars represent 10 and 90% quantiles, points 5 and 95%quantiles). The results shown in Fig. 4 suggest a slight downstream decrease of "'Ra activity concentration in suspended matter and sediment. This might be interpreted as a desorption process. The coefficient of a presumed first order kinetic desorption can be estimated from the data of the different locations (mean flow velocity of 1.2 m s-l, distance of sampling locations of about 210 km)as about 1.6 10" s-'. The 'loPb concentration shows a very large variation for suspended matter but a small one for sediment. This might be explained by the immediate atmospheric input of '"Pb in the suspended matter of the surface water. The median activity ratio of suspended matter to sediment concentration for lS7Csand some natural radionuclides is between 1 and 2 (Fig. 5). This fact is due to the high amount of fine grained solids (clay and mica) both in suspended matter and bottom sediments. The 90Srcontent in water in the investigation period was found as about 3 Bq m-3in water and 2 Bq kg-' in bottom sediments [7]. The use of the data for assessment of Kd factors is described in Ref. [81.

254 4. CONCLUSIONS

Experience gathered in the program shows clearly that large variations of parameters result. In order to keep sampling errors small, environmental research and even routine monitoring can be carried out reasonably only when continuous monitoring is used. This is because of the many unknown, both external and internal, parameters influencing transport, retention and distribution of radionuclides in the aquatic environment. The results of this investigation will be used for optimisation of routine monitoring programs. 5. REFERENCES 1. 2. 3. 4.

5.

6.

7.

8.

Tschurlovits, M., K. Buchtela, E. Unfiied, J. Sas-Hubicki, 1979-1984. Contributions to IAEA's coordinated research program on the radioecology of the Danube river 1976 to 1982, IAEA TECDOC 219,229,311. Wien. Tschurlovits, M., 1983. Atomkernenergie-Kerntechnik, 42: 238. Streisslberger, F. and M. Tschurlovits, 1988. Kerntechnik, 52: 39. Rank, D. et al., 1994. Geotechnical Institute, Annual Report 1993. Wien. Maringer, F.J., 1994. The behaviour of radionuclides in water, suspended matter and sediment in the Danube river. Diss. Wien, Techn. Univ. Wien. Rank, D., F.J. Maringer and J. Terlunen, 1990. The radioactivity of sediments in the Danube reservoirs in Austria before and after the Chernobyl accident. Wat. Sci. Techol., 22 (5):211-218. Maringer, F.J., P. Jachs, D. Rank and M. Tschurlovits, 1994. On the behaviour of Sr-90 and Cs-137 in water, suspended matter and sediment of the River Danube. Proc. Austr.-Ita1.-Hung. Rad. Prot. Symp., Obergurgl, 28-30 April 1993. 6VS, Wien. Tschurlovits, M. and F.J. Maringer, 1997. In situ assessment of &factors in the Austrian part of the Danube river, in: G. Desmet et al. (eds.), Freshwater and Estuarine Radioecology. Elsevier, Amsterdam.

Freshwuter und Estuurine Rudioecoloxy

Edited by G. Desmet et al. 1997 Elsevier Science B.V.

255

In situ assessment of Kd factors in the Austrian part of the Danube river M. Tschurlovitsa and F.J.Maringerb aAtorninstitute of Austrian Universities, Schuettelstrasse 115, A-1020 Vienna, Austria bFederal Research Center Arsenal, Geotechnical Institute, A-1030 Vienna, Austria

ABSTRACT As a part of a special monitoring program, evaluation of the measurements for deriving in situ & factors was carried out. Radionuclides present in the Danube catchment area were used to investigate the behaviour of radionuclides in the Austrian part of the Danube river. Measurements of some radionuclides of different components of sediments representing complementing samples, which were taken at different locations at the Danube river in Austria on a monthly basis lead to well proved results. Some investigations were devoted to the influence of unusual hydrological conditions as high-water flooding to the behaviour of radionuclides in the system. The results are reported including uncertainties and influencing parameters. The results of these investigations are discussed in relation to default values and for their importance in environmental modelling and dose assessment.

1.INTRODUCTION

Since Kd factors represent many interacting parameters, large uncertainties have to be expected. Many of the influencing parameters are internal, i.e. not available or detectable at site. Therefore, a statistical black box approach seems promising, taking into account external parameters (i.e. observable at site), provided that the number of available data is sufficiently large. The present paper is based upon an in situ assessment of Kd.Some external parameters are considered. A sampling procedure reducing some uncertainties and subsequent radiometric measurement was employed.

266

2. DEFINITION

The Kd factor for a given radionuclide i is

where is activity concentration in suspended material and is activity concentration in water. Since the quantities have a dimension activity per unit mass or volume, respectively, the dimension is eventually m3kg-', but traditionally 1kg-' is used. 3. MATERIAL AND METHODS

Water samples were taken daily from a depth of about 1.5m. An amount of 2 1 was taken daily, leading to a sample volume of 60 1 month-'. Suspended material and water were separated by flow-through centrifugation for about 3 hours at 10000 rpm. With this procedure, solid particles with a density of 2.6 g cm-3 and a Stoke's diameter of >0.4 pm were separated from the water sample. The sediment-free water sample was evaporated using a large volume rotation evaporator (Rotavapor) to concentrate radionuclides bound in solved material, leading to a residue of about 20 g for a 60 1 sample. After sample preparation, the samples were measured with a low level gamma spectroscopy equipment for about 24 h each. An LLD of 0.1Bq ms and 2 Bq kg-' were obtained at a present activity concentration in water of about 2 Bq m-3 (median) 13'Cs. In normal hydrological conditions, the grain size of suspended material was 80%< 20 )I, and of sediments 50% < 20 p. The main mineralogical components of the suspended matter were clay and mica minerals (approx. 45%), carbonates (calcite, dolomite, approx. 30%),quartz and feldspar (approx. 20%) and organic matter (approx. 5%). However, in periods with higher flow rates, high flow speed of water and hence a higher transport capacity lead to a larger grain size distribution of the suspended solids. In these situations, the clay and mica fraction decreases and the quartz and feldspar fraction increases. Further characteristic parameters of the water samples were pH 7.0-7.8, conductivity 250 to 300 pS and NHf 0.1-0.3mg 1-'. 4. RESULTS

Figure 1 shows the results of measurements, covering a period of nearly three years. Sampling was done at 4 sites along the Austrian part of the Danube River. Each point represents a pair of measurements (approx. 60 1 water/ approx. 1 g suspended material). In order to reduce the large variation of data to be expected, samples were collected on a monthly basis. In spite of this procedure, it can easily be seen that for all radionuclides large deviations result and no clear

257

400000

Uko Kd

300000 200000 100000 0

120000

100000 80000

60000 40000 20000 0 25000

20000

15000 10000

5000 0

Sampling period

Fig. 1. Measured Kd values versus time.

trend can be derived. It was therefore promising t o correlate the observed Kd values with some external parameters. The followingparameters were considered: flow rate, concentration of suspended material and site dependence. Figure 2 shows a correlation of l3'Cs K ,values with flow rate for a given site. Data for other sites are similar. It can be seen that generally lower Kd values can be found at conditions at high flow rate. Plotting all data, as shown in Fig. 3, gives a very broad range of results, and no clear general relation between the considered parameters can be derived. However, the observed changes in the

268

sampling period Fig. 2. Caesium-137 Kd values and discharge versus time, Danube km 2094 (Wallsee).

400000

Location:

0 300000

'

km 2146.7, Ottensh. km 2094.5, Wallsee km 1949.2, Greifen. v krn 1938.0, Wien 0

er,

5

200000

Yo

100000

0 0

I000

2000

3000

discharge rnYs (Danube, Wallsee)

Fig. 3. Caesium-137 Kd values versus flow rate.

4000

259 1000

1 )

I

I

I

I

I

I

I

Danube km

Fig. 4. Distribution of concentration of suspended matter at different sites.

mineralogical composition might contribute to a lower total concentration of some radionuclides such as 137Cs. Figure 4 (raw data by courtesy of Wasserstrassendirektion Wien) shows how the concentration of suspended material varies along the length of the river. This figure shows: (i)the variability is large, but roughly the same at different sites; and (ii) the means at different sites are in reasonable agreement. 5. CONCLUSIONS

Correlations of the observed Kdvalues in the Austrian part of the Danube river from 4 sampling sites over a length of about 280 km during a time interval of almost 3 years do not show a proved relation to external parameters as flow rate, concentration of suspended material and site. It is therefore justified to use a statistical approach by constructing a cumulative probability distribution. This distribution is shown in Fig. 5. Recent standards propose a default value of Kd for 137Csof 30000 [l]and expected gross average Kd value of lo3with a range of 5xlo'to 8x104(1 kg-') [2]. The median obtained from the present paper for 13'Cs is 1x10' (m3kg-') = lo5 (1 kg-'1, the range as shown in Fig. 5 is 5x104to 2 . 5 ~ 1 (5%, 0 ~ 95% percentile, respectively 1.

260

99,o 9a,o 95,O $ 9090

2 ao,o 2 70,O

3 60,O h 50,O 2 40,O

3

30,O

20,o

10,o

5,o

2,o 1,O

03

1000

10000

100000

1000000

K, Ukg Fig. 5. Kd values, cumulative probability.

In modelling, concentration of suspended material is important. It is shown that the mean of this figure is roughly constant at different sites, but a considerable inherent variation appears. The observed variations suggest the use of stochastic rather than deterministic models. 6. REFERENCES 1. 2.

IAEA Safety Series 57, 1982. Generic Models and Parameters for Assessing the Environmental Transfer of Radionuclides from Routine Releases. IAEA Technical Series 364, 1994. Handbook of Parameter Values for the Prediction of Radionuclide Transfer in Temperate Environments.

Freshwuter und Estuurine Rudioecokogy Edited by G.Desrnet et al. 1997 Elsevier Science B.V.

261

Caesium-137 transport from the rivers located in the Chernobyl area to the Kiev reservoir U. Sansonea,M. Bellia,M. Riccardia,V. Kanivetcb,G. Laptevb and 0.Voitsekhovitchb 'ANPA, Via Vitaliano Brancati 48, 00144 Rome, Italy bUkrainian Hydrometeorological Research Institute, Kiev, Ukraine

ABSTRACT This paper deals with the quantificationof radiocaesium transport through the aquatic system located in the Chernobyl area. The role of the physico-chemical parameters of water bodies on 137Csadsorption-desorption processes on suspended materials are discussed. Preliminary in-situ distribution coefficient values (&) obtained during a survey around Chernobyl area are presented.

1. INTRODUCTION

The results presented in this paper are part of a project started in 1992 concerned with the radioactive contamination of aquatic ecosystems located near the Chernobyl nuclear power plant. The goal of this project is t o evaluate the transport of radionuclides from the Chernobyl area by the Pripyat and Dnieper rivers and to define the role of the physico-chemicalparameters of water bodies on the adsorption-desorption processes for radionuclides on suspended materials. The Dnieper river crosses the Ukrainian territory from its border with the Russian Federation and the Republic of Belarus in the north to the Black Sea coast in the south. The Dnieper's water is used for drinking, municipal, recreational and industrial needs, and for irrigation along its 1000 km journey length across the Ukrainian territory. The Chernobyl nuclear power plant is situated on the bank of the Pripyat river, 20 km from its inflow into the Kiev reservoir. The problem of radioactive contamination of surface water in the Ukraine is therefore primarily associated with the Pripyat-Dnieper river-reservoir system [ l l . At present this arises mainly from the erosion of radioactively contaminated surface soils during times of snow melt and flooding. The data presented in this paper are essentially restricted to a first evaluation of the

262

137Cstransport from the Chenobyl area to the Kiev reservoir and the determination of the in situ Kd values for the different grain sizes of suspended material. 2. MATERIAL AND METHODS

The survey was carried out from 17 June to 14 July 1993 and was focused on the two reservoirs (Kanev and Kiev) and five rivers (Dnieper, Desna, Pripyat, Uzh and Ilya) in the Dnieper river-reservoir system, characterizedby different morphological scales and hydrological regimes and different levels of radionuclides contaminations (Fig. 1). Samples of water and different fractions of suspended materials were collected along the above mentioned rivers, in four locations in the Kiev Reservoir and in one point in the Kanev reservoir.

PRJPYAT XUUVER

a

Fig. 1. Map of the Pripyat-Dnieper river-reservoir system showing the locations of the sampling stations.

263

Sampling was carried out in duplicate using sampling devices capable of performing both size fractionation of suspended materials and fixation of dissolved caesium. In these devices, different fractions of suspended materials are gathered using nylon cartridge filters (PALL filters, HDC 11, 1000) of pore sizes 40 pm, 10 pm and 0.45pm, with a diameter of 60 mm and a filtration area of 0.49 m2. Dissolved caesium is fixed using columns containing ammonium hexocyanocobaltferrate (NCFN) ion-exchange resins. To determine the efficiency of the resins, each device contains two such columns connected in series, of diameter 20 mm and height 160 mm and 80 mm respectively. For each measurement the water filtered ranged from 500 to 2000 1. To determine the amount of suspended matter, the filters were dried and weighed before and after filtration. All filters and resins were analyzed by gamma spectrometry using HPGe detectors. The samples were counted for 20 h giving a standard deviation
Table 1 reports the physico-chemical characteristics of the water. Water pH range from 6.9 to 8.7.The values are generally constant in the reservoirs (8-8.3) and in the rivers (8.1-8.7), if we exclude the pH of Ilya river (sampling point 11)that appears very low (6.9).The data show that suspended material concentrations in the river waters are generally higher than in the reservoirs where there are low water velocities and comparatively high sedimentation rates. Suspended material concentrations in the rivers range between 6.5and 23.5 mg 1-'. The average value in the Kiev reservoir is 4 mg 1-I. The other physico-chemical properties of the water samples show little variability. Table 2 reports the 137Csconcentrations in water and the in situ 137Cs distribution coefficients (Kd)calculated at each sampling site for the different grain size of suspended material. The data show that the highest concentration of 13'Cs dissolved in water was found in Ilya river (point 11). In the Uzh river (point lo), after the confluence with the Ilya river, the dissolved caesium values are comparable to those found in the Pripyat river (point 9),while the data of the northern part of Dnieper river (point 7)are about 4 times lower than the Pripyat river values. In the Kiev reservoir the dissolved 137Cs concentration is about 1.3times higher than that found in the Pripyat river. In the Desna river water, which crosses low contaminated areas, the 137Csconcentrations were near the minimum detectable activity. Finally, the dissolved caesium in the section of the Dnieper river downstream from the Kiev reservoir (Kiev city, point 3) is comparable to the values found in the Kanev reservoir (point 5).

4.833.5

0.36M.006

0.377M.009

7.98M.04

8.27M.06

0.163M.001 10.4M.5

7 5.7M.1

3.0 13.0 10

8.LM.2

10.0

6.9L.02

9.3f1.5

40.5

0.281i0.001

8.11H.09

0.82

3.2 16.0 9.6

56.4

22

8.M.3

0.383M.002 13.4H.5

8.6H.06

0.54

3.2 14.0

9.9 50.8

18

5.8M.1

0.383M.001 12.M.7

8.66M.02

0.90 3.1 14.2

9.8

51.0

8

5.2M.2

7.9io.8

0.391i0.001

8.02M.03

0.95 3.2

14.3 9.7

52.1

4

6.7M.2

5.LM.5

0.37739.021

8.2239.04

0.76

3.3 15.0 9.6

-

0.34

(mgl-9

NH4

-

3.1

K (mg1-9

53.4

3.ZM.4

0.351H.001

8.27M.02

-

-

14.0

Na (mg1-l)

3

3

7.2M.3

0.346M.002

8.29M.07

8.6

Mg (mg1-9

7.3M.1

24

7.7M.3

0.445M.004 13.5f2.9

8.72-N.03 3.M.O

9

6.5M.2

6.5M.9

50.0

Suspended Ca materials (mg1-9 (mg1-11

6

(mg1-11

02

Dissolved

5.9H.2

(NTU)

Kanev Reservoir (68km south of Kiev dam) Dnieper River (Kiev City) Desna River (1.5km north of Kiev Reservoir) Kiw Reservoir (3.5k m north of Kiev dam) Kiw Reservoir (25km north of Kiw dam) Kiev Reservoir (45 km north of Kiw dam) Kiw Reservoir (Pripyat and Dnieper confluence) Dnieper River (10k m north of Kiev reservoir) Pripyat River (Chernobvl) 10 Uzh River (Pripyat River tributary, 15 km north) 11 Ilya river (Uzh River tributary, 2.5 km north)

Conductivity Turbidity

(mScm-1)

PH

Sampling points

Water physico-chemical properties

TABLE 1

265 TABLE 2 137Csin water and in situ Kd values in the different fractions of suspended material ~~

Sampling points

137Csin Water (Bq 1-')

In situ Kd (1 kg-'1 Total

Suspended material size (pm)

40 Kanev Reservoir (68km south of Kiev dam) Dnieper River (Kiev City) 3 Desna River (1.5km north 1 of Kiev Reservoir) 2 Kiev Reservoir (3.5km north of Kiev dam) 4 Kiev Reservoir (25km north of Kiev dam) 8 Kiev Reservoir (45km north of Kiev dam) 6 Kiev Reservoir (Pripyat and Dnieper confluence) 7 Dnieper River (10km north of Kiev reservoir) 9 Pripyat River (Chernobyl) 10 Uzh River (Pripyat River tributary, 15 km north) 11 Ilya river (Uzh River tributary, 2.5km north) 5

10

0.45

0.0454f0.0002

79f5

9lf5

79f4

53f3

0.050f0.003

69f2

77f4

64f3

39fl

69f15

64f14

-

0.0744f0.0004

-

-

-

-

87f3

109fl

0.094f0.002

113f1

143f7

103fl

50f6

0.106

106

124

100

47

0.09f0.01 0.0165f0.0007 0.07f0.01 0.073f0.002 0.42f0.01

79f4

90f8

73f16

28fl

10Sf12

106f5

1811t59

22f5

44333 38f6

17f5 20fl

69f33 50f6 8f1

74f36 70f8 23fl

9f1

3.220.2

In all sampling sites 137Csseems to be more strongly associated with the highest size fractions of suspended matter (40 and 10 pm). These results appear surprising and could be attributable to the high bloom of algae observed during the sampling period (JuneJuly 1993). Data on the organic matter content of the different fractions of suspended materials (presently being measured) will probably clarify this aspect. Since the 40 and 10 l m filters may have been affected by the presence of algae, in the following only the data relating to the fraction retained on the 0.45 pm filters (mineral fraction) are discussed. To this end, the &s reported in Table 2 could be subdivided in the following 3 groups: 1. reservoirs - Kiev (sampling points 4,8,6 and 7)and Kanev (point 5); 2. rivers - Pripyat (91, Uzh (10)and northern Dnieper (7); 3. Ilya river (11). The & values calculated for Kiev and Kanev reservoirs were fairly uniform, and had the highest values. The low suspended material concentration found in the reservoirs (from 3 to 8 mg 1-'1 could explain these data. Furthermore, the low variability observed is typical of the environmental physico-chemical characteristics of the reservoir waters which fluctuate in a narrow range.

266

The in sztu Kd values found in the Pripyat (sampling point 9) and Uzh (10) rivers are 17 and 22 lg-' respectively and are only half the values found in the reservoirs. The lower Kd values in the river waters could be related in this case to the higher solids concentrations in the rivers (10and 22 mg 1-l). The Kdvalues obtained in the lower part of the Dnieper river (sampling point 3),15 km downstream from the Kiev reservoir, are about twice as high as the values measured in the other rivers. This difference might be explained by the fact that most of the water in this part of the Dnieper river comes directly from the Kiev reservoir and consequently has similar characteristics to those of the Kiev reservoir. The Kd values obtained in the Ilya river (sampling point 11) are about an order of magnitude lower than in the other rivers. It is reasonable to assume that the different chemical characteristics of the water (pH 6.9) could result in a higher degree of mobility and remobilization of radiocaesium from suspended material. In conclusion, the 13'Cs input to Kiev reservoir comes mainly from the Ilya-Uzh-Pripyat system. Concentrations in inputs from the Dnieper river (point 7) are 4 times lower than in the Ilya-Uzh-Pripyat system. The Kiev reservoir is characterized by low water velocities and comparatively high sedimentation rate and can be considered as a temporary sink of the material transported by the rivers crossing the areas contaminated by the Chernobyl event. The Kd values calculated for the 0.45 pm particle size show that an equilibrium state in solid-liquid interaction is reached in the lower part of the Kiev reservoir. The variability of the Kd values found in the rivers should be investigated in more detail. The measured values do not appear to be related to the K, Mg and NH4 concentrations that generally regulate the caesium adsorption-desorption processes [2,31. 4. ACKNOWLEDGEMENTS

This study was supported by the Commission of European Communities under contract COSU-CT92 0003 and COSU-CT93-0041. 5. REFERENCES 1.

2. 3.

Zheleznyak, M.J., R.I. Demchenko, S.L.Khursin, Y.I. Kuzmenko, P.V. Tkalich and N.Y.Vitiuk, 1992. Mathematical Modelling of Radionuclides Dispersion in the

Pripyat-Dnieper Aquatic System after the ChernobylAccident. Sci. Total Environ., 112: 89-114. Comans, R.N.J., M. Haller and P. De Preter, 1991. Sorption of cesium on illite: non equilibrium behaviour and reversibility. Geochim. Cosmochim. Acta, 55: 433-440. Cremers A. and P.N. Henrion, 1985. Radionuclide Partitioning in Sediments: Theory and Practice. In: Seminar on the Behaviour of Radionuclides in Estuaries, Renesse (the Netherlands), 17-2 1 September 1984. Commission of the European Communities, XIV380/85-EN: 1-25.

Freshwuter und Esruurine RudioecoloAy Edited by G . Desmet et al. 1997 Elsevier Science B.V.

267

Distribution of natural radioactivity within an estuary affected by releases from the phosphate industry A. Travesi, C. Gasc6, M.Pozuelo, J. Palomares, M.R.Garcia and L. PBrez del Villar CIEMAT-IMA.Avda. de la Complutense 22, Madrid 28040, Spain

ABSTRACT The distribution and behaviour of the radionuclides zlOPb,zlOPoand zz6Rain the Odiel and Tinto river estuaries, southwest Spain, have been studied. This system receives large quantities of solid and liquid effluents in the form of phosphogypsum waste from the phosphate industry containing natural radionuclides. Ranges of activities from 20 to 5000 Bq kgl(d.w.) in riverine sediments were observed. The ratios of radionuclides were also determined (uncertainties quoted to 2 01, showing clear disequilibria in the effluents from the factories (210Pb/210Po= 2.7k0.6,z10Pb/226Ra = 0.6kO.1,z10Po/L26Ra = 0.24M.03)and from the phosphogypsum piles (z10Pb/210Po= 2.1k0.6,z10Pb/226Ra= 1.5kO.6,210Po/226Ra = 0.7kO.2).However, the sampling sites on the rivers affected directly by the discharges exhibit activity ratios other than those found in the effluents, manifesting their different behaviour in the estuarine environment. The estimated inventory in sediments for these radionuclides was 0.92k 0.20TBq (1993)which can be compared with the annual release of 0.52M.04TBq (1993)from the phosphogypsum piles and factories. Preferential deposition of zlOPoand zlOPbrather than zz6Raonto the river bed was observed. The proportion of total sediment zlOPbactivity associated with particles less than 2 pm in diameter, which is one of the most resuspendable and transportable sizes, is 5%-15%.

1. INTRODUCTION

In contrast to the nuclear industry little is known about the discharges and risks of radionuclides from non-nuclear industries. However, due to the industrial activity of the non-nuclear industry, natural radionuclides can be concentrated in the industrial effluents and cause a significant dose to the population. Due to the large bulk transfer, large quantities of radionuclides are released in this way to the environment.

268

In Spain, a large phosphate ore processing complex [llis located at Huelva, close to the estuary formed by the rivers Tinto and Odiel. The "phosphogypsum" produced as a waste product of the industrial process is, in part, directly dumped in suspension into the Odiel River near its confluence with the Tinto river before it reaches the sea. Approximately 8 million cubic meters of liquid effluents are discharged into the Odiel every year, containing around 4 x 10' Kg of phosphogypsum 111.The major fraction of phosphogypsum is not directly dumped, but carried out in suspension and deposited over the tidal flats on the eastern side of the Tinto river, forming large deposits of phosphogypsum which have resulted in the near total sterility of the tidal flats. These deposits are formed by settling of suspended matter from the discharges in pools created along the river which are successively covered by new flows of the suspended matter. The overlying liquid drains away through fissures, after the deposition of the solids, into the Tinto river. The gypsum deposits reach a thickness of 4-6 m and their total surface covers approximately 4x106m2. It is estimated that, up to the present, more than 10" Kg of phosphogypsum has been deposited in this area. Both environmental and radiological impacts produced by these dikes, were analyzed in previous studies 12-41.The environmental impact is caused by the desertification of the zone, and the radiological impact by its proximity to the urban area of Huelva. The estimation of the dose to the population is done using models that require the determination of the concentration in different components of the ecosystem, These models should consider the disequilibrium of natural radionuclides after the chemical treatment of the factories and their later releases. Another fact of significance is the disequilibria among radionuclides belonging to the natural radioactive chains that are supposed to be in secular equilibrium in the environment. Some authors reported this fact for certain elements such as polonium and lead in the estuarine areas [5,61due to their preferential association with the suspended particulate matter. Where phosphate factories exist, these disequilibria can be produced by chemical treatment of the raw mineral, which contains large quantities of radionuclides in the 238U decay chain [7].They are discharged to the aquatic envjronment,with the radiologically important radionuclides '%Ra, 'loPb and 'loPo [8].The largest doses h m marine pathways are predicted for these radionuclides, 'loPo being the dominant contributor via the preferential pathway of the consumption of molluscs [91. Besides increasing the knowledge of the behaviour of natural radionuclides in estuarine areas, the main objectives of this research were: (a) to analyze the 210Po,210Pb and 226Radistribution in the estuary, focusing the attention on the abiotic part of the ecosystem, and (b) to assess quantitatively the radiological consequences of the aquatic discharges of the phosphate industry. In this paper, the identification of the source term (releasesof the factory),the distribution of natural radionuclides within the two rivers, the inventories of radionuclides in sediments, and the fractionation of activity concentration are presented.

269

Fig. 1. Sampling stations in the estuary formed by the Odiel and Tinto rivers.

2. MATERIALS AND METHODS

2.1. Sampling A sampling network was established on the Odiel and Tinto rivers. Sixteen stations were selected; examining the waters and bottom sediments along both rivers, up-stream from the effluent discharge sites, along the estuary and on

270

the beaches of the Atlantic coast. The sampling stations are shown in Fig. 1. The sediments were collected with a Shipek grab sampler by the University of Seville in February 1993. The samples were dried at 40°C until constant weight was achieved, except for those samples used for the determination of granulometric composition. In this case the sediments were frozen and stored until their particle size analysis [lo]. 2.2. Radioanalytical methods

The 'loPo was extracted from the sediment after its total dissolution with sequential acid leaching (HN03, HF, HC1 and HClOJ. The polonium was electroplated onto a silver disk according to the method of Flynn [ill.The chemical recovery was determined by addition of "'Po tracer obtaining an average recovery of 90%. The polonium activities were measured by alpha spectrometry using silicon surface-barrier detectors. The radiochemical procedure used to determine 'loPb activity is based on that described in Joshi [121.The lead leached from the sediment as described above. The solution was then passed through an anion-exchange resin (Dowex 1x8 C1-) A pure lead sulfate precipitate was obtained after various steps of purification [131. 'loPb was determined by counting the 1.17 MeV beta emission of its daughter product "OBi. Yield was calculated gravimetrically with a stable tracer of lead obtaining an average recovery of 90%. Also, "OPb was directly determined by its 46.5 KeV gamma peak. The sediments prepared in 7c geometry were measured by y-spectrometry,with a low energy photon planar germanium detector. The results obtained for both methods were compared by applying the following statistical analysis between duplicates [14]:

where: Sd = standard deviation between duplicates; di = difference between duplicates divided by the mean of the duplicates. P = number of duplicates. The results of both 'loPb analyses are in good agreement (88%), with a confidence level of 16.In the calculation of ratios between radionuclides the radiochemically determined results were used due to their lower uncertainty. The activity of 226Rawas determined by y-spectrometry using a coaxial germanium detector. The contribution from 236Uwas subtracted from the 185 KeV peak activity. The uncertainties are quoted at 2 6. 2.3. Inventory estimation

The determination of inventory was made using the following formula

I,=Ai .Dj

271

where: I, = inventory of radionuclide i expressed in Bq m"; A, = concentration activity of radionuclide i expressed in Bq kg-' (dry weight); D, = surface density of sediment expressed in kg m-'. To calculate the inventories, D, was assumed constant along the river, with an average value (to a depth of 5 cm) of 43 f 16 kg m-' (6 stations). Three areas were identified for the purposes of this study. The Odiel river, estimated by the University of Sevilla to have an area of 3 km2 [15,16], was divided into four sectors, called A,B,C and D. The areas of the Tinto river and the Estuary were both divided into two sectors, called A and B. 2.4. Granulometric analysis of the sediments

For separation of the <2 pm fraction, the dry sample was stirred in distilled water. The fraction remaining in suspension after 24 hours was then collected. Stokes' law was used to show that particles remaining in suspension after this time are those with a diameter <2 pm. The process was repeated until a quantity of these particles sufficient for analysis was obtained [171. The particle size distribution of the c62 pm diameter fraction was made using a Coulter Counter Model TA-11. 3. RESULTS AND DISCUSSION

3.1. Radioactivity of factory effluents

The most significant discharges from the phosphate works were the direct discharges from the factory to the Odiel and the supernatant of phosphogypsum piles outflowing to the Tinto River [181. The discharge is released by extracting water from the river and mixing it with the liquid that contains the acid used in mineral dissolution. The releases are made via a pipe line that is located at the front of the industrial installation. The activity ratios between the different radionuclides from the discharge pipes illustrate the disequilibrium existing after the treatment of the phosphate minerals. The bulk of the inventory released to the river during the operation of the factory since it started production cannot be calculated as there is no historical discharge or effluent radionuclide concentration data. Indeed the first records are from 1988. 3.2. Distribution of radionuclides activities on riverine sediments

The results of ""Pb, zlOPoand "'Ra concentration activities (1993) along the river are presented in Table 2. There is a considerable increase in radionuclide activity close to the discharge point of the eMuent pipes (S4, SlO) and a

272 '" I

I

5-4 v-

0 5 5 6 9 6 6 10.9 13.6 17421.9 278 347 438 552 695 87

P e r

S-6

C

e

n

I

I

o

16 1 141................ 3 .,

I._

5 5 6.9 a6 10.9 13.8 174 21 9 276 347 438 552 695 87

_

_

.-

.

.....

.......

........

s-10 0

5 5 6 9 8 6 109 136 17.4 21 9 276 347 438 552 695 87

s-11

Grain size urn Fig. 2. Granulometric composition of selected riverine sediments.

decrease of activity in the stations located close to the estuary (S15, S16), as expected. The210Pb/210Po activity ratio upstream (stations S1 and S2)is close to unity as expected in an area not influenced by the discharge. The stations downstream of the pipes in both rivers (S3,S4,S5, S6,S7,S8,S9,S10, S13), and close to the estuary 615,S16),show 210Pb/210Po activity ratios between 0.36 k 0.27and 0.86 k 0.05,significantly lower than in the discharge pipe and the phosphogypsum piles (Table 1).This reduction in the activity ratio of these radionuclides in the riverine sediments can be attributed to their different geochemicalbehaviour. Because zlOPo is more easily adsorbed onto the suspended

-

Effluent

2.10'0f2.109

4.10'0f3.109

-

2.939.8

2.83).8***

19+_2**

2.9fo.5

2 . 1 0 ~ ~ ~ 1 . 1 01w2* ~

Annual

.009fo.001 -

2.Mo.2***

4.7M.3**

1.439.1

2.4~.2*

Effluent

-

3.1010f8.109

2.10'%2.10'0

-

8.10'0+1.10'0

Annual

2.1jB.6

2.7M.6

0.8jB.8

1.5f0.6

0.6M.l

0.2M.2

FORET and FECSA are the phosphate plants (water is taken from the Odiel river. FECSA 1,2,3,4 represents the number of the pipe). Phosph. = Phosphogypsum piles supernatant. Odiel = Odiel Captation.

***Basedon a discharge of 1200 m3 h-'.

**Based on a discharge of 1000 m3 h-'.

*Basedon a discharge of 800 m3 h-'.

<2.7

4.3f1.1*** 5.10'0f1.1010

Phosph.

Odiel

12.5+2.7** l . l O ' ~ . l O ' o

FORET

-

<2.8

FECSA 394

1.10'okl. 10"

2.1f1.9*

Annual

FECSA 1,2

Effluent

Discharges to the river measured experimentally in Bq 1-' f 20 (1993) and annual release in Bq

TABLE 1

0.7f0.2

0.24f0.03

0.22M.03

I

S-12

S-ll

1 1

I 1

+ + +

744 f59

65k37

44+13

914+40

82+20

31f16

< 24

595 f 85

I

723k 11I

763 k 35

375+59

212+7

240+40

254+23

54k8

1062k47

474k13

76&10

221f16

I498f75

884k33

I 1 4 O f 129

_____

1070k 169

< 62

< 67

364k77

211k68

70 k 20

< 203

618+110

723k65

223k50

< 241

103+43

235f 30

288k25

125k20

231 k23

I 1 I

0.36k0.27

0.59f0.04

0.94k0.06

0.40+0.21

0.37k0.09

0.61+0.04

0.86f0.05

1.19*0. I I

--

0.43 f0.08

0.69k0.07

0.56k0.02

1.26k0.06

3395k 198

584k88

0.97k0.08

z'OPb/zloPo

2743k64 333k I5

726+21

406k96

n6Ra(2)

0.69fO. 13

241 k50

740k 114

518k26

210P0(3)

< 148

922k38

s-2

460 k 75

'"Ph(2)

125&21

506f31

s-I

210Pb( 1)

I

I I

I 1 I

2.9k0.63

2.24f0.72

I .08+0.34

__--_-

-

2.42k0.44

1.22*0.12

_ I

1.73k0.37

2.1 I k0.69

0.44k0.26

1.47k0.27

1.05~0.ll

1.14k0.27

0.95f0.21

--

I .03 f 0.12

1.41k0.19

-

I .45kO.O9

--

1.24k0.19

1.27k0.31

"OPoP6Ra

0.98k0.16

0.81 i0.05

1.57kO.25

1.24k0.30

z10PbPz6Ra

226Ra and zlOPoexpressed in Bq kg' f 20 and ratios (f20) in sediment samples along the river bed (1993)

( I ) Radiochemically ('2) 7-Spectrometry (3) a-Spectrometry

a r Y

U

1

S

E

n

t

i i n

T

r

e

V

i

R

I

e

d

0

Station

Activity concentrations of 21%,

TABLE 2

275

TABLE 3 Contents of "OPb in the fraction of sediment <2 km in diameter Station

Measured activity in 1 g of sediment particles <2 p(Bq)

Fraction of bulk sample Fraction of activity on particles c2 p(%) <2 pm (%)

s-4

7.7f0.3 0.22f0.02 1.45f0.05 0.12f0.02

1.7 5.9 9.2 3.9

S-6

s-10 s-11

4.8 10.4 14.6 5.7

particulate matter than "'Pb, this results in a rapid removal of the polonium and a higher accumulation rate for this element than lead, and consequently a higher polonium concentration in the sediments and a decrease in the 210Pb/210Po activity ratio. A similar behaviour can be observed in the Tagus estuary [19],which is also influenced by the releases of phosphate industries. (1:2)in the particuThere is a different ratio of these radionuclides 210Pb/210Po late suspended matter from the Tagus estuary, but unfortunately there is no data on disequilibria of radionuclides in their effluents after the treatment of the phosphate minerals. The uncertainty in the 210Pb/226Ra activity ratios obtained at some stations does not allow us to determine their different behaviour. At stations S4 (close to Foret) and S10 (close to phosphogypsum piles), i.e. those directly affected by the discharges, the 210Pb/226Ra ratios are in good agreement with the ratios in the effluent (see Table 1). The enhanced 210Po/226Ra activity ratios at stations S4 and S10 close to the discharge points reflect the incremental increase in the concentration of polonium in the sediments compared to radium for the reasons given above. The radionuclide contents in the upstream stations (Sl,S2 Odiel river) are high if compared with the natural radioactivity of non-polluted Spanish rivers. The natural radionuclide contents of Catalan river sediments range from 6 to 20 Bq kg-' 238U[20,211and in the Jarama river they range from 12 to 105 Bq kg-' 238U [22].Contents from 45 to 138 Bq kg-' (226Ra) are reported in Tagus river [23]and 28 to 62 Bq kg-' (23eU)and 30 to 124 Bq kg-' ('l0Pb) in French rivers [24].The existence of old Roman galena mines and the mineralogical composition of the river bed may be the cause of the high '"Pb activities (506-922 Bq kg-') at stations S1 and S2. The activity concentration in the sediment fraction less than 2 pm at selected stations is shown in Table 3.These stations were selected as representatives of maximum and minimum values of activities. The percentage of activity associated with the size less than 2 pm was calculated using the following formula:

276

where: F = fraction of activity on fine particles;p = fraction of bulk sample <2 p; C = measured activity in bulk sample; Cf= measured activity in fraction <2 pm. As is shown, the fraction of radioactivity present in these particles is between 5 and 15%. This fraction is "theoretically"resuspendable, and can be transported and collected by the organisms that live in the estuary. This is an important factor that must be taken into account when models are applied in the context of radiological hazard. 3.3. Riverine sediment inventory

The estimated total inventory of 210Pb,210Poand 226Rain the sediments is presented in Tables 4 and 5.The estimated quantity of radionuclides released during 1993 in the whole area is 0.52 f 0.04 TBq, which is comparable with the total inventory in the sediments of 0.92 f 0.20 TBq present during that year. It TABLE 4 Estimation of radionuclides inventories in sediments from Estuary

Odiel river A 0.59 B 0.20 0.30 0.20 C 0.23 0.27 0.21 D 0.35 0.36 0.23

SlS2 s-3 5-4 5-5 S-6 s-7

s-9 s-9 s-9

2.10'0f7.109 l.109f4.10' 4.10'0f1.10'0 2.109f7.lo8 1.109f5.108 1,10'0f5. 10' 2. 109*9.108 1.10'0f4.109 1.10'0*44.109 8.109f3.109

Tinto river A 2.4 B 2.5

s-10 s-11

9.1010f4.10" 9. 109f3.109

Estuary A B

S-13 S-14

3.10'0f1.10'0 5.1010f2.10"

1.8 1.8

5-8

2.10'0*6.109 2.lO9*6. lo8 6. 10'0f2.10'0 3.109f1.109 3.10gfl.lo9

-

2.109f7.lo8 1.10'0f5.109 1.10'0f5.109 9.1O9*3.1O9

4. 101ofl,10" 8.10'0f3. 10"

*Radiochemistry values considered of 210Pb. **AverageSurface density expressed in Kg m-2 = 43 (5 cm depth).

1.lO'Of5. 10' 2.109f8.10~ 1.10'0f4.109 1.10'0f4.109 7.109rt3.109

277 TABLE 5 Inventory of the 'l0Pb, 'loPo and zzsRa(5 cm depth) (1993) Inventory Bqf2a

Total (TBq)

zlOPb

210Po

226b

*Released **Sd

*Released **Sd

*Released **Sd

*Released **Sd

2.10"f 3.1010

8.10"f

4.10'

3.10"f 2.10"

0.52f 0.04

3.101&t 5.101°

4.10"f 7.10"

2.10"f 3.10"

0.92f 0.20

is worthy of note that errors in the estimation of inventories could have been made due to the calculation of the surface area of the river bed (from unknown bathymetry) and the scarce information obtained from the factories (realistic and controlled information of the volume released is needed). However, a better estimate of the total inventory could be made if the sedimentation rate of the area was known and core sampling to a depth of 50 cm was made. This is one of the objectives of further research in the area. 4. CONCLUSIONS

The radiological impact of phosphate factories on the environment is easily detectable in the area of Huelva estuary. Higher levels of natural radioactivity are observed in the rivers Tinto and Odiel than in others not affected by such industries (ten to fifteen times the content of a non-polluted Spanish river). The releases of 0.5 TBq from the factories are preferentially transferred to the river-bed which has a present inventory approximately 1TBq for the three radionuclides considered in this study. The 210Po/210Pb, 226R&10Pb and zzsRaf210Poactivity ratios manifest disequilibria in the natural radioactive series after the acid treatment of the mineral and as a consequence of differential behaviour in the estuarine ecosystem. The particles less than 2 mm in diameter contain a small percentage of radionuclides (5-15%), but this has to be considered in models of radiological hazard assessment as this is the fraction which is easily resuspended and transported. 5. ACKNOWLEDGEMENTS

The authors would like to thank the University of Sevilla (Department of Nuclear Physicsj for collaboration in this project and in the sampling campaign. They would also thank the Agencia del Medio Ambiente Andaluz for technical

278

assistance and the use of sampling equipment.They would like to mention the excellent analytical work performed by F. Palomares. This work was partially funded by the Radiation Protection Research Programme of the European Union (contract no. FI3P-CT-0035“Pathways of radionuclides emitted by non nuclear industries”)and by ENRESA (Empresa Nacional de Residuos Radiactivos S.A of Spain). 6. REFERENCES 1. La Industria Quimica y Bhsica en Huelva, 1989. Libro blanco. Huelva. 2. Josa-Garcia, J.M., 1980. Procesos para la separacidn y recuperaci6n del uranio del Lido fosf6rico. Junta de Energia Nuclear, Jornadas Minerometaltirgicas. Huelva. 3. Ryan, M.T. and S.J Cotter, 1980. An Integrated Assessment of the Phosphate Industry. Oak Ridge National Laboratory, ORNL-5583. 4. Ama, J., 1989.A Radiactividad en Andalucia. Informe 2, Convenio con Universidad de Sevilla. 5. Bacon, M.P. and D.W. Spencer, 1976. 210PbP26Ra and 210Po/210Pb disequilibria in sea water and suspended particulate matter. Earth Planet. Sci. Lett., 32: 272. 6. Sediment Kds and concentration factors for radionuclides in the marine environment. IAEA. Technical Reports Series 247,1985. 7. Garcia, R., J.P. Bolivar and M. Garcia Le6n, 1994. Radiactividad en fertilizantes comerciales. 5” Congreso Nacional de la Sociedad Espaiiola de Protecci6n Radiol6gica. Santiago de Compostela, Abrill994,383 pp. 8. Cancio, D., J. GutiBrrez, R. Salvador, A. Garcia-Olivares, E. Carrasco and J. Palomares, 1989. EvaluaciBn radioldgica de la industria de fosfatos de Huelva. CIEMAT/PRIMA/UCRE/lY9. CIEMAT. Madrid. 9. Aarkrog, A. and W.C. Champlin, 1984. Radioactivity in North European waters. Report of CEC Project Marine. 10. Quejido, A., 1994. Comunicacion personal. Round-table on sample pretreatment for sediment analysis. Barcelona, Mayo 1994. 11. Flynn, W.W., 1968. The determination of low levels of zlOPoin environmental materials. Anal. Chim. Acta, 43: 221. 12. Joshi, L.U., 1979. Measurement of zloPbfrom a sediment core off coast of California. J. Radioanal. Chem., 52: 329. 13. Garcia Sanz, M.R. Procedimiento para la determinaci6n de Pb210 en aguas, aerosoles, suelos y alimentos. PR-X!2-05. CIEMAT 92. Madrid. 14. Gasc6, L., 1970. Fundamentos de estadistica. I Curso sobre estudio de la radiactividad ambiental en torno a instalaciones nucleares. IEN. J.E.N. 15. Abril, J.M. and M. Garcia Le6n, 1991. A mathematical approach for modelling radionuclide dispersion in the marine environment. J. Environ. Radioactivity, 13: 39-54. 16. Abril, J.M. and M. Garcia Le6n, 1993. A 2D 4-phases marine dispersion model for non-conservative radionuclides. Part I and 11. J. Environ. Radioactivity, 20: 89115. 17. Moore, D.M. and R.C. Reynolds, 1989. X-Ray Dif€kaction and Identification and Analysis of Clay Minerals. Oxford University Press, Oxford. 18. Direcci6n de FESA y FORET. Comunicaci6n personal. Junio 1989.

279 19. Carvallo, F.P. 1997. 210Pband zlOPoin sediments and suspended matter in the Tagus Estuary. Local enhancement of natural levels by wastes from phosphate ores processing industries. Report Contract Bi-006. CEC. Bruxelles. In press. 20. Ortega, X.,J.R. Rose11 and I. Vallb, 1988. Contribucion a la determinacion de la radiactividad en las playas catalanas. Conferencia Internacional sobre Radiactividad Ambiental en el Area del Mediterraneo. Barcelona. 21. Vallbs, I., X. Ortega and I. Serrano, 1993. Contribucion de la radiactividad de las aguas potables de la zona de Cataluiia a la dosis por ingestion. 5" Congreso Nacional de la Sociedad Espaiiola de Protection Radiblogica. Santiago de Compostela, p. 363. 22. Gutierrez, J., 1993. Programa de Vigilancia Radiologica del CIEMAT. Informe 1993. CIEMAT/IMA/UCREY03/94. 23. Sequeira, M.A. and M.C. Vaz Carreiro, 1991-1992. Controlo da radioactividade nos nos Tejo, Zecere e Guadiana INETI/BPSFUB/32. 24. Lambrets, A., L. Foulquier and J. Gamier-Laplace, 1992. Natural radioactivity in the aquatic components of the main French rivers. Radiat. Rot. Dosim., 45: 253-256.

Freshwuter und Estuurine Rudioeoology Edited by G.Desmet et at. 0 1997 Elsevier Science B.V. All rights reserved

281

Natural radionuclides in the Amazon river flood plain soils E.S.B. Ferraz Centro de Energia Nuclear Agricultura, Universidade de Sdo Paulo, 13400-970Piracicaba, Sdo Paulo, Brazil

ABSTRACT The Amazon depression (vbzea) is a large area, over 100,000 km2,formed by the deposition of sediments of Andean origin carried by the Amazon river. Gamma ray spectrometry analysis was performed to determine the distribution of natural radioactivity in this region, especially 226Ra,232Th,40Kand 137Cs.Floodplain soils (106 samples) were collected (10 sites) along a 1000 km stretch of the Amazon river between Vargem Grande (lat. 3"16.'i"S;long. 67"55.7'W)and Manacapuru Oat. 3"19.4'S;long. 60'32.7W) during the early period of falling water levels (August) in 1991. The sampling points formed 10 transects inland from the river and represented three types of vegetation cover: forest, mixed foresUgrass and grass. 137Cswas found only in 14 samples, with an average of 0.75 Bq kg', maximum of 1.40 Bq kg' and minimum of 0.05 Bq k g l . Average concentrations of 226Ra,232Thand 40Kin the surveyed floodplain soils were 34.91f1.18 Bq kg', 45.62k2.00 Bq k g ' and 622.5f41.1 Bq kg', respectively. Observation of the ratios Ra/Th, Ra/K and Th/K a t all stations showed that the concentrations of these radionuclides remain approximately the same along the sampled area, except for one site where 232Thand 40Kconcentrations were lower than the floodplain average. 1. INTRODUCTION

The Amazon Basin extends over 6.4 million km2and is cut across from west to east by the Amazon river, which carries sediment from the Andes to the Atlantic Ocean. The seasonal movement of the river water floods a large area of lowland where a great amount of sediment is deposited, mainly holocenic sediment of Andean origin 111. The Amazon floodplain (vhrzea) is the result of this process and forms a region of over 100,000 km2of fertile soils, located at the margins of the mainstream. The floodplain was formed over several thousand years, from the cycle of deposition and erosion, covering the original soil

282

with a sediment layer several metres thick. The geochemical characteristics of the floodplain soil are completely different from Amazon soils [21and the main differenceis its fertility. Contrary to the local substrate, the chemical composition of trace elements of floodplain sediments is uniform [31from the Andes to the Atlantic continental plateau, i.e. over a 3500 km extension. Studies with trace elements have also shown that there is local influence at points close to the mouth of the main tributaries, especially those originating from the Guiana plateau [41.Biogeochemistry and physics of the Amazon lowland soils have been extensively studied. However, there is very little information about their environmental radioactivity. Knowledge of concentrations of the natural series of 226Raand 232Th,of 40K and 13?Csradionuclides from atmospheric fallout is a very important tool to solve ecological questions. Since such radionuclides are easily detected by direct gamma spectrometry, the samples collected by the CAMREX Project (Carbon on the Amazon River Experiment) were used in a survey of the radiometry of the region. The objective of this study was the radiological characterization of the Amazon floodplain (vhrzea)by determining concentrations and distributions of some natural radionuclides. The area chosen for this study is a typical stretch along the Amazonas river, named Rio Solimties. 2. MATERIALS AND METHODS

During Cruise 12 of the CAMREX Project, samples were collected at 10 locations along the river. At each location samples were taken along a transect inland and perpendicular to the river with three types of vegetation cover: (i) inundation forest, (ii) grasses, and (iii) mixed forest (where the vegetation changed from grasses near the river bank to forest inland). During AugustlSeptember 1991 with the University of Sao Paulo research boat AMANAI, 106 floodplain soil samples,were collected along 10transect series, distributed over 1000 km of the Solim6es/Amazonas river. The city of Vargem Grande is near the Brazil/Peru/Colombia border. Manacapuru is a city along the margin of the Solim6es/Amazomas river, a few kilometres from the mouth of Rio Negro, at the city of Manaus. The map in Fig. 1 shows the sites of the study and Table 1 information on sample locations. Samples of about 5 kg each were collected at the 0-20 cm depth, soon after removal of the litter deposited on the soil. The first sample of each transect was collected at the water line (zero)and the others at every 10 m. perpendicular to the river bank (8-14 samples per station). The material was air-dried and sieved (2mm). After oven drying (105"C,24 h) samples were placed in 150 cm3 polyethylene cylindrical containers, slightly compacted to contain 180-2 10 g, to reach approximately the same bulk densities. The containers were sealed with silicon and left to rest for at least 30 days in order that short-lived natural series attain their equilibria [51. Following the same procedure the certified

283 700w 5'

6YW

600 W

N

55" w

5oOw

EQ.

5O

s

100 s

Fig. 1. Map of the studied region of the Amazon Basin showing the 10 points (0) of sample collection of floodplain sediment and the four lakes (*) close to Manacapuru.

TABLE I Identification of floodplain soil sample collection sites. Distance in km along the river downstream of the city of Vargem Grande Site VGR FJT BJU LUR

ALV

JUT ITA PIU MAN FBA

Vargem Grande Foz do Jutai Boca do Jurua Lago Urua Alvarles Jutica Itapeua P a r a d Iuara Manacapuru Floresta Barroso

Lat.S

Long. W

Margin

Cover

Distance

Date

Z"16.7' 2O41.1' Z"41.1' 2O39.9' 3O12.5' 3O34.1' 4"Ol.O' 3O51.2' 3O19.4' 3O19.3'

67O55.7' 66O39.4' 65O47.5' 65O38.3' 64O48.4' 64'17.6' 62'59.1' 61O23.0' 60O32.7' 60O32.4'

Left Left

Forest Mixed Forest Forest Mixed Grass Grass Grass Grass Mixed

0 186 259 267 450 500 680 884 998 1014

1818191 21/8/91 22/8/91 15/8/91 13/8/91 25/8/91 2 718191 2918191 3 V8/9 1 3 l/8/9 1

Right

Left

Right

Left Left

Right Right Right

reference material LAEA Soil-6, was prepared and used for calibration and efficiency calculation (International Atomic Energy Agency SOIL-6, 137Cscontent: 1450 pCi/kg, c.i.: 1390-1565 pCi/kg; "'Ra content: 2160 pCi/kg, c.i.: 1880-2525 pciikg; reference date: 30 January 1983).

284

Sediment samples from the bottom of four lakes close to the last two stations were also analyzed: three of the lakes, Lago do Cemitkrio (CE), Lago Tup6 (TU) and Lago Faustino (FA) are typical of black waters and not flooded when the Amazon river overflows; the fourth, Lago Passarinho (PA), although more distant, is however, a typical floodplain lake. Detection was carried out by high resolution gamma-ray spectrometry using a hyperpure germanium semiconductor detector EGG-ORTEC GMX 20190 P (105.26cm3;25% relative efficiency; 1.85keV resolution at 1.33 MeV) coupled to a multichannel analyzer and a spectral analysis system with software designed for low count-rates. Counting times varied between 8 and 48 h; however, 90% of the samples required counting times greater than 24 h. To quantify Uranium /Radium series, the '"Ra radioactivity was determined using the '14Bi photopeak of 609.31keV, and also the photopeaks of 295.17, 351.87 and 1120.27keV, as references. For the Thorium series, 232Thactivity was calculated with the '"Ac photopeak of 911.07 keV, using as references 338.4,583.14and 727.18keV of '"Ac, '"Tl and '"Bi, respectively. This choice was based on the best relationship between signal and background, found under the experimental conditions. 137Cswas calculated by the photopeak 661.65keV and *OKby 1460.75keV. The efficiency of the system is high at this energy interval (609-911 keV) and so, an adequate number of events were accumulated in 24 h. As the bulk density of the samples was about the same for all samples (1.16-1.321,count-rates were not significantly influenced by grain size. The gamma spectrometry analysis was performed on all 106 soil samples. Since the samples had different texture, particle-size analysis was carried out in 67 representative samples according to the hydrometer method [6].Four fractions were separated: 2-0.2 mm, coarse sand; 0.2-0.053mm, fine sand; and below 0.053mm. The fractions of silt and clay were sorted using hexa-metaphosphate. 3. RESULTS AND DISCUSSION

The 13'Cs from atmospheric fallout was found in 14 samples, at an average radioactivity of 0.75Bq kg-', maximum 1.40Bq kg-' and minimum 0.05 Bq kg-'. 137Cswas detected mainly at Itapeua (6samples) and Lago UruA (4samples), and at 4 other stations. The fact that 137Cswas detected in a few samples only was due to the protection of the soil by the forest cover, grass or simply organic matter. In the Amazon region 137Csis mainly found in sediments at the bottom of lakes, and even there at low concentrations because the convection currents of the equatorial zone result in low fallout in this region. In view of the above, the greatest interest of the work was directed to some primordial radionuclides, 40Kand representatives of the Uranium/Radium and Thorium series. If the sediment from the Andes Mountain is transported

285

h

M

4

60 -

5

./

B

El. c t-

-444 0

_-

40 -

-*-Th + K 20

I

I

I

I

I

200

through the SolimBes/Amazonas river without suffering intense weathering and without significant local contamination, the concentrations of such radionuclides, and especially their proportions, should remain constant within experimental limits. This must be true both longitudinally along the river and transversally away from the river. To confirm this hypothesis concentrations of 232Thand 40Kwere plotted against the concentration of 226Ra.As shown in Fig. 2 there is a good relationship between them, but there is some scatter about the line. In general, the results indicated that the samples collected near the river bank, especially at 0 and 10 m, showed low concentrations of 226Ra, 232Thand 40K. This might be due to a process of mechanical removal of clay and silt by river waters, but it might also be the result of a selective process of sediment deposition at the lowland. Sand content plotted against the distance from the river bank indicates that there is not only a large variability among the results of 0-10 m but also an exponential dependence on distance (Fig. 3). The activity concentrations of 226Raand 232Thof all 106 samples plotted as a function of the distance from the river bank is shown in Fig. 4. It can be noted that the radioactivity of the samples closer to the river bank is lower than the others as a consequence of the increase of sand content. These samples are atypical and cannot represent a vhrzea soil. Based on these findings it was decided to exclude samples collected 0 m and 10 m from the water line (8 samples). Table 2 shows the average specific radioactivity (Bq kg-') and the number of samples per station (N)used after this exclusion. Results in Table 2 show that the concentrations of these radionuclides remain approximately the same along the sampled area except for Floresta do

286

80 -

8 h

60-

*

71

*

0

Distance from the river bank (m) Fig. 3. Sand content of 67 samples as a function of the distance from the river bank. “he line shows the statistically calculated general tendency.

60

,

10 -

pcRaF 0

40

20

60

80

100

120

140

Distance from the river bank (m) Fig. 4. Variation in 22%a and 23% collection point and the river bank.

concentration as a function of distance between the

Barroso where 23% was low. This might be due to the high percentage of sand in this site or else contamination from local material. Such hypotheses were checked observing the ratios R n h , Ra./K and Th/K at all stations. Figure 5 shows that this station is a26Raenriched and 232Thand 40Kdepleted when

287

Vargem Grande Fbz do Jutal Boca do Juruii Lago Uruii Alvaraes Jutica ltapeua Paranii Iuara Manacapuru Floresta do Barroso

I ' 0.6

0.5

0.7

0.8

0.9

1 .o

Ra/Th coefficient Fig. 5. Ratio Ra/Th (average-+ std) for the 10stations. The dashed line represents the general average (88 samples) and the solid line the average without the Floresta Barroso station.

TABLE 2 Collection sites number of samples used average and standard deviation of the specific activities (Bq kg-') of zzsRa 232Thand *OK Site

N

226h

232Th

40K

Vargem Grande Foz do Jutai Boca do Jurua Lago Urua Alvarles Jutica Itapeua Parana Iuara Manacapuru Floresta Barroso

8 9 9 7 7 7 11 9 12 9

33.9+4.4 35.6f3.0 33.1f4.7 34.5f4.5 35.3f2.2 35.lk2.1 35.8f2.5 33.253.1 36.3f3.6 32.6f2.6

44.2f5.5 46.0f4.5 45.3f2.9 45.5f5.0 46.2f3.8 45.6f4.I 48.9B.O 41.2f4.O 45.7f5.1 37.6f4.3

644.M27.1 652.0f41.6 546.3e2.8 630.1f37.0 663.4f48.4 627.6f18.7 65 7.6f21.5 553.9f16.9 614.9f28.6 582.7f15.0

comparing its Ra/Th average with the general average calculated using 88 selected samples. The ratio R f l h in this site is 0.852 (with a standard deviation of 0.066)while the general average (88samples) is 0.786 and the average without Floresta do Barroso station is 0.778.Station Floresta do Barroso is an uneven place consisting of a low flooded area linked to small lakes and an upper forested area. In Fig. 2 all samples from this site (11)appear below the line of linear regression indicating a systematic deviation.

288 TABLE 3 Specific radioactivity(Bq kg-') found in lake sediment Lake

m e

226b

2 3 2 m

40K

Ra/Th

Lago Cemithrio Lago Tup6 Lago Faustino Lago Passarinho

black water black water black water floodplain

81.7 113.8 120.7 69.6

66.9 92.7 97.3 94.5 .

508.4 180.3 926.3 757.2

1.22 1.23 1.2 0.74

TABLE 4 Statistical resume of radiometric analysis performed for 79 typical soil samples from 9 Amazon floodplain sites

AVG (Bq kg-') STD (Bq kg-') C.V. (a) MAX. (Bq kg-') MIN.(Bq kg-')

2ZSb

232Th

40K

34.91 1.18 3.37 41.95 26.75

45.62 2.00 4.39 54.35 31.54

622.5 41.1 6.6 724.8 508.0

The soils from the region near Manaus are rich in nuclides from the Uranium and Thorium series (10or more times greater) and depleted in 40K(3-4times less) in relation to the floodplain sediment. This explains the high indices of 226Raand 232Thfound in the bottom sediments from lakes not flooded by the Amazon river like the black water lakes of this region. Table 3 shows the concentrations found in the three blackwater and one floodplain lakes and their Ra/Th relationship. Passarinho which is a typical floodplain lake, shows a Ra/Th relationship close to the varzea average, whereas the black-water lakes have significantly higher values. The results for bottom sediments from the lakes of the region strengthen the hypothesis of local contamination in the Floresta do Barroso site. The average radioactivity levels for all 106 samples taken in the present work are 34.7f 1.3 Bq kg-' for 226Rxi,44.8f 3.1 Bq kg-"for and 618.5f 40.7 Bq kg-' for 40K. However samples taken close to the river bank (18)and those from station Floresta do Barroso (9) do not represent typical Amazon floodplain soils. Average floodplain soil levels excluding these data are given in Table 4.

289 4. ACKNOWLEDGEMENT

The present work could only have been carried out thanks to the support received from CNPq National Council for Scientific and Technological Research; FAPESP Foundation for the Support of Research of the state of Sao Paulo Brazil. 5. REFERENCES 1. 2. 3. 4. 5.

6.

Richey, J.E., R.H. Meade, E. Salati, A.H. Devol, C.F. Nordin Jr. and U. Santos, 1986. Water discharge and suspended sediment concentration in the Amazon River: 1982-1984. Wat. Resources Res., 22(5): 756-764. Victoria, R.L., L.A. Martinelli, J.E. Richey, A.H. Devol, B.R. Forsberg and M.N.G. Ribeiro. 1989. Spatial and temporal variations in soil chemistry on the Amazon floodplain. GeoJournal, 19(1):45-52. Fernandes, E.A.N., E.S.B. Ferraz and H. Oliveira, 1994. Trace elements distribution in the Amazon floodplain soils. J. Radioanal. Nucl. Chem. Art.,179: 251-258 Ferraz, E.S.B., R.L. Tuon and E.A.N. Fernandes, 1991. Transfer of trace elements in the Amazon basin. In: On the Validity of Environmental Transfer Models. Swedish Rad. Protect. Inst., 307: 312. Mishra, U.C. and S. Sadasivan, 1971. Gamma spectrometry measurement of soil radioactivity. Int. J. Appl. Radiat. Isotopes, 22: 256-257. Gee, G.W. and J.W. Bauder, 1985. Particle size analysis. In: A. Klute (ed.), Methods of Soil Analysis, Part 1: Physical and Mineralogical Methods. American Society of Agronomy Monograph 9,2nd edn., Madison, pp. 404-408.

Freshwuler und Estuarine Rudioeecolqy Edited by G. Desmet et al. 0 1997 Elsevier Science B.V. All rights reserved

291

210Pb enhancement in rivers affected by the phosphate rock processing in southwestern Spain A. Martinez-Aguirre and M. Garcia-Le6n Facultad de Fisica, Universidad de Sevilla, Apdo. 1065, 41080 Sevilla, Spain

ABSTRACT The activity levels of 210Pbin solution and bottom sediments were measured in the estuary formed by the Odiel and Tinto rivers in southwest Spain. The levels in both water and sediment samples indicate that the discharges from two fertilizer factories in the area enhance the radioactivity of such samples. 1.INTRODUCTION

Recently, high radioactivity levels of U, Th and "'Ra isotopes were found in solution, suspended matter and bottom sediments of the Odiel and Tinto rivers located in southwestern Spain [l-31. The anomaly was attributed to two fertilizer factories located in an industrial complex surrounded by these two rivers (Fig. 1).These factories release their wastes directly to the Odiel river or store them in uncovered piles near the Tinto river channel. In this paper, we have extended previous work to the study of 'lOPbin solution and bottom sediments. 2. SAMPLESAND EXPERIMENTALMETHODS

Seven points on the Odiel river, four on the Tinto river and one at the confluence of both rivers (Fig. 1)were sampled for water and bottom sediments in July 1990 (dry season) and in February 1991 (wet season) to evaluate seasonal variations in 'loPb activities. The pH of the waters was measured at the time of sampling. The suspended matter was separated by filtration through Nucleopore filters of 0.45 pm pore size. Immediately, the filtrate was acidified to pH -2 with concentrated HN03. The small size fraction (d < 63 pm) was separated from sediment samples in order to determine the 'loPb content. Determinations of percent organic matter and percent of water were carried out on each bottom sediment sample.

292

Fig. 1. Map of the Odiel and Tinto rivers which shows the sampling stations along both river channele. The fertilizer factories and the phosphogypsum storage area are also shown.

'loPb was determined through the measurement of its daughter 210Poby a-spectrometry, after secular equilibrium was achieved. The samples were spiked with known activities of z08Poto determine the chemical recovery of the total procedure. Samples were first acid digested with concentrated HN03 followed by aqua regia and, finally dissolved in 8 M HN03. Po was separated using a solvent extraction method with TBP as the organic phase and 8 M HN03 as the inorganic phase. After vigorous shaking Po remains in the inorganic phase whereas other radionuclides join the organic phase. The solution containing the Po was evaporated to dryness and self deposition of Po onto silver plancheta was encouraged by shaking gently at 60°C. The planchet was finally measured by a-spectrometry with ion implanted detectors. Further details on the radiochemical procedure are presented in Mor6n et al. [4]. 3. RESULTS AND DISCUSSION

To simplify the subsequent discussion we will first present the results for water

samples from both rivers for all sampling campaigns, followed by those obtained for bottom sediments. Samples 0 represent those taken in the Odiel

293

river, T in the Tinto river and OT in the confluence of both rivers. Sediment samples are identified as SO, ST and SOT for the Odiel, Tinto and the confluence respectively. The index represents the sampling station along each river (Fig. 1). 3.1. Waters

The results obtained for the analysis of '"Pb in water samples taken during the low tide in 1990 (dry season) and 1991 (wet season) are presented in Table 1. The levels of 'loPb in the Odiel river area under study range from 3.7f 0.5 to 289 k 22 mBq 1-' with the maxima, in summer and in winter, in front of one of the fertilizer outfalls (Fig. 2).The levels decrease quickly downstream from this point, due, probably, to precipitation of Fe and Mn during mixing downstream [5].This activity pattern is similar to those obtained previously for other radionuclides [1,21reflecting the presence of a local source of radioactivity (the fertilizer industries) along the river channel. The minimum levels found in summer are clearly higher than those in winter, probably due to a lower water stream flow of the river in the dry season. ~n the case of the Tintb river the levels along the channel are quite constant, ranging from 17.0f 1.5to 26.6 f 3.0mBq 1-' in summer 1991,with a slight decrease downstream of the channel. In 1991, the levels range from 15.3 f 3.1 to 45.6f 2.7 mBq 1-'. In both campaigns the TABLE I

Data of 210Pbin mBq 1-' in water samples (low tide) taken from the Odiel and Tinto river basins in 1990 (dry season) and 1991 (wet season). The pH of the waters at the time of sampling is also given. N.M means not measured 1991

1990

Code

PH

'loPb

PH

"OPb

01 02 03 04 05 06 07

2.86 6.37 6.42 6.35 6.32 6.48 6.40

21.1f2.5 7.9k1.0 10.2f3.4 289f22 34.452.2 12.2f1.4 14.0f1.0

3.90 5.52 5.90 5.96 6.03 6.06 6.02

N.M. 7.8k0.7 3.733.5 36.4i2.6 8.4M.8 7.4fl.l 50.6f3.9

T1 T2 T3 T4

2.41 5.54 5.82 6.10

4 1.7f3.1 26.6f3.0 19.5f1.5 17.0f1.5

2.88 3.22 5.56 6.40

N.M. 45.632.7 15.3f3.1 30.7f5.7

OT

6.56

11.7f1.0

6.23

10.5f1.2

-

294

3-.

. . .

I

.

1890

- - - - -- lo01 ? :

$9 v

iI f -

K,: c

8'

A,

.,

A, I'

'.,.

*-

maximum level in the Tinto river was found in station T2. This station is located close to an artificial stream coming from the phosphogypsum storage area. In fact, the pH of the water at this station is lower than at the rest of the stations, at 3.22 in 1991 (Table l), which reflects the wastes released at this point. We also observe that the level of '"Pb found at station T4 of the Tinto river is quite similar to that found at station 0 7 of the Odiel river. This fact could be explained by the influence that contaminated waters from the Odiel river have on the "intoriver channel. Thus,contaminatedwater from the Odiel river can flow upstream into the "into river when the tide changes from low to high. In the Netherlands, Koster et al. [61 obtained levels of "OPb of 0.9 mBq 1-' in waters of the Oosterchelde system while in the area around a fertilizer factory in the Nieuwe Waterweg system they found 10 mBq 1-'. In general, the authors assumed levels below 1mBq 1-' as a background level, those higher than 3 mBq 1-' as probably enhanced and finally, those higher than 5 mBq 1-' as clearly enhanced. Lewis [5] reported dissolved 'loPb in normal river waters to be less than 0.2 mBq 1-'.By contrast in acid river waters, dissolved '"Pb was found to reach 230 mBq 1-' in the Colorado system and 2.8 mBq 1-' in the west branch of the Susquehannah river 171. Comparing the levels of '"Pb in the Odiel and Tinto rivers for both sampling campaigns we should consider both rivers to be clearly enhanced in '"Pb activity by the fertilizer industries, particularly in the area close to the outfalls. The background level away from the outfalls appears to be around 7 mBq 1-'. We will consider separately the case of samples 01 and T1, which were collected at the source of both rivers, far from the fertilizer industries (20 km

295

upstream in both cases) and unaffected by their wastes. Both sampling stations present levels of 'loPb much higher than the usual values in fresh river waters. This fact must be related with the acid pH of the waters (Table 1) at both stations. These acid pHs produce a dissolution of 'loPb from soil particles and consequently a higher 'lOPbactivity in solution, as was previously found in the Colorado river and in the Susquehannah river [6,71. This effect of dissolution from bottom sediments by the acid pH of the waters was also found for other radionuclides in the same sampling stations (1-31.

3.2.Sediments The small size fraction (d 5 63 pm) of 7 bottom sediments from the Odiel river, 4 from the Tinto and 1 from the confluence of both rivers sampled in 1990 and 1991 were separated for '"Pb determinations. The results obtained together with percent of water and percent of organics for each sediment sample are presented in Table 2. Levels of 'loPb are quite high in the area close to the fertilizer industries in the Odiel river, with a maximum level of 799 k 48 mBq g-' in 1990 and 534 k 25 mBq g-' in 1991.These levels of radioactivity at stations 04 to 07 are much higher than the background level, 1100 mBq g-' reported elsewhere [61.Only in two stations (Fig. 3), upstream from the industries, in both sampling campaigns, does the level of "OPb fall in the non enhanced range (1100mBq g-'). 'loPb activity levels at station 0 7 were much lower (1100mBq g-') in the 1990 TABLE 2

Data of "OPb in mBq g-' in the small size fractions of bottom sediments taken from the Odiel and Tinto river basins in 1990 (dry season) and 1991 (wet season). Percent of water and percent of organics in the sediment samples are also given. N.M. means not measured Code

%Water

% Organics

'loPb

so1 so2 SO3 SO4 SO5 SO6 SO7

52.58 26.64 60.58 52.53 65.51 58.18 65.35

5.73 11.76 9.51 10.91 5.26 9.47 9.47

13.9f1.3 27.251.5 212f10 438f21 799f49 78.6f3.7

ST1 ST2 ST3 ST4

79.63 38.78 59.29 61.46

8.38 4.34 9.64 8.64

96.7f6.1 39.8f1.9 74.4f4.8

OT

64.98

8.69

N.M.

N.M.

149f11

%Water

% Organics

'loPb

61.18 24.53 57.21 39.13 59.83 67.93 55.64

15.40 3.09 8.25 11.57 9.74 12.95 9.58

8.OfO.7 40.9f2.7 284f14 420f31 534-5 41 l f 2 4

39.80 51.37 56.8 56.03

2.25 8.96 11.72 10.93

33.1f3.3 233f9 47.9f2.5

66.77

11.49

204f16

N.M.

N.M.

296 Wlel and Thto sdlrnents

5 0 1 x K ) ~ s o 8 5 0 6 5 0 1

sot

st4

st3

StZ

Fig. 3. 21%bin mBq g-' in bottom sediment samples taken from the Odiel and Tinto rivers in 1990 and 1991.

sampling campaign than in that of 1991. This must be related to some drainage activities carried out in the area in 1990. In the Tinto river the levels range from 33.1 f 3.3 to 233 f 9 mBq g-' in the fine fraction for both years. 'loPb levels in the Tinto river sediments, for the same sampling campaigns, are much lower than in the Odiel river. Moreover, there is a clear peak of activity in station T3 in the sampling campaign of 1991 (Fig. 3), with levels much higher than the typical background level. This station is located at the confluence with a small natural stream, Estero del Rinch, (Fig. 1)which crosses the phosphogypsum storage area, and could transport some gypsum particles with high activity levels. These particles will eventually be deposited on the Tinto river bed at the confluence. High activity levels of other natural radionuclides were also found at the same station in 1988 and 1989 [1,2]. The stations upstream from the industries at the Odiel river and also stations ST2 and ST4 of the Tinto river, however, present levels of ""Pb much lower and similar to the background level (5100mBq g-'). In general, no correlations between 'loPb content and organic or granular composition were found in either river, and the activity patterns obtained are similar t o those found for other radionuclides in previous years [1,21. 4. ACKNOWLEDGEMENTS

The authors wish to thank J.M. Abril, G. Manjon and J. Diaz for helping in the sampling. The work was partially supported under contract DGICYT PB890621 and EEC contract FI3P-CT920035.

297 5. REFERENCES

1. 2. 3.

4.

5.

6.

7.

Martinez-Aguirre, A. and M. Garcia-Leon, 1991. Natural radioactivity enhancement by human activities in rivers of the southwest of Spain. J. Radioanal. Nucl. Chem. Lett., 155: 97-106. Martinez-Aguirre, A., M. Garcia-Leon and M. Ivanovich, 1994. The distribution of U, Th and 226Raderived from the phosphate fertilizer industries on an estuarine system in southwest Spain. J. Environ. Radioactivity, 22: 155-177. Martinez-Aguirre, A., M. Garcia-Leon and M. Ivanovich, 1994. U and Th distribution in solution and suspended matter from rivers affected by the phosphate rock processing in southwestern Spain. Nucl. Instrum. Meth. Phys. Res. A, 339: 287293. Moron, M.C., A. Martinez-Aguirre and M. Garcia-Leon, 1988. Determination and levels of U, Th and Po from different environmental samples. In: International Conference on Environmental Radioactivity in the Mediterranean Area. SNEENS, Barcelona, p. 111. Lewis, D.M., 1977. The use of zlOPoas a heavy metal tracer in the Susquehanna river system. Geo. Cosmochim. Acta, 41: 1557. Koster, H.W., P.A. Marwitz, G.W. Berger, A.W. Weers, P. Van Hegel and J. Niewuenwize, 1991. 210Po,'l0Pb and zz6Ra in aquatic ecosystems and polders, anthropogenic sources, distribution and enhanced radiation doses in the Netherlands. In: V International Symposium on the Natural Radiation Environment, Salzburg, Austria. Scott, M.C., 1982. The chemistry of U and Th series nuclides in rivers. In: M. Ivanovich and R.S. Harmon (eds.), Uranium Series Disequilibrium: Applications to Environmental Problems. Oxford Science Publications, Chapter 8.

Freshwuler und Estuurine Rudioecology Edited by G. Desmet et al.

0 1997 Elsevier Science B.V. All rights reserved

299

Bioavailability of radiocobalt to the common carp, Cyprinus carpio, in complexing environments R. Blust, L. Van Ginneken and S. Comhaire Department of Biology, University of Antwerp (RUCA), Groenenborgerlaan 171, 2020 Antwerp, Belgium

ABSTRACT The uptake of cobalt by the common carp, Cyprinus carpio has been studied in chemically defined freshwater in the presence of different organic ligands (i.e. glycine, citrate, histidine, NTA and EDTA). This to verify the hypothesis that uptake is a direct function of the free cobalt ion activity in the solution. The organic ligands used were very different in their affinity for cobalt, covering a very broad range of stabilities. Cobalt uptake decreased with decreasing free cobalt ion activity and the effect was independent of the organic ligand present. However, cobalt uptake did not increase linearly with the free cobalt ion activity in the solution. A good fit to the data was obtained when the observations were fitted to a model for mediated transport of the metal ion across the biological interface. The model assumes two uptake sites, one with a high and one with a low affinity for the metal ion. The relation provides a mechanistic model that accurately describes the effect of complexation on the uptake of radiocobalt from solution in carp.

1. INTRODUCTION

The uptake and accumulation of radiocobalt strongly depends on the chemical speciation of the radionuclide in the environment. Both inorganic and organic ligands present in the environment bind cobalt, which in parallel with other metals, should result in a decrease in the bioavailability of the radionuclide to aquatic organisms [ 11. In general, metals are believed to cross biological interfaces via gating systems which facilitate the transport of certain metal species across the lipid bilayer membranes which separate the organisms from the surroundings. These membranes are otherwise nearly impermeable for ions and other polar species. The selectivity of the gating systems, often also referred to as channels or carriers, depends on the size, charge and configuration of the chemical species and transporters involved [21. It appears that only the

300

free metal ion can cross the interface, while most other species are not taken up. In natural environments cobalt is complexed by a multitude of ligands covering avery broad range of stabilities. Some monodentate complexes are rather weak, while other often polydentate complexes are very strong [31. The free metal ion activity concept states that the bioavailability of metals only depends on the activity of the free metal ion in the solution and that there is a linear relation between the free metal ion activity in the water and the metal uptake rate. This also implies that it does not matter whether cobalt is complexed by either weak or strong ligands. These critical assumptions, however, have never been verified. In the present study the uptake of cobalt by the common carp, Cyprinus carpio has been studied in the presence of weak and strong organic ligands over a broad range of free cobalt ion activities. 2. MATERIAL AND METHODS

2.1. Uptake experiments

Juvenile carp of about 4 weeks were obtained from the fish hatchery of the Agriculture University of Wageningen, The Netherlands. Fish were kept for at least 12 weeks in the laboratory under controlled water conditions before use in the experiments (2' = 25fl"C, pH = 7.6-8.0, Ca, 348 pM,Mg, 500 pM).The fish were fed with commercial pellets for under yearling freshwater fish. Experiments were performed with fish weighing between 2 and 6 g. The solutions used for cobalt uptake experiments were of the same composition as the medium hard water used for acclimation. The solutions were spiked with a fixed concentration of radioactive cobalt (740 kBq 1-' of 57C0,Amersham, UK) and different concentrations of stable cobalt (10-7-104 MI. The solutions were buffered by inclusion of 10 mM of the non-complexing buffer EPES (Sigma, USA) to stabilise the pH around 8.0f0.1.To determine the effect of complexation on the uptake of cobalt, five different organic ligands were used (EDTA, NTA, histidine, citrate and glycine). The ligands were added to the solutions from concentrated stocks. Solutions were prepared 24 hours before the start of an experiment for equilibration. The stability constants of the cobalt-ligand complexes formed covers several orders of magnitude. Fish were not fed 24 hours before the start of an experiment. Fish were individually transferred to the beakers and cobalt uptake was followed for a period of three hours. Thereafter, fish were transferred for 5 min to beakers containing the same solution without radioactive tracers. This to remove radioactive cobalt associated to the body surface. This water also contained 10 pM of the sedative propyl DL- 1-(l-phenylethyl)-imidazole-5-carboxylatehydrochloride (Sigma). Thereafter, fish were transferred to scintillation vials (Canberra Packard, USA) and counted for 1min in a Packard Minaxi Auto-Gamma Counter 6530 to determine the amount of 6 7 Cin~ the fish.

301

Previous experiments already showed that uptake was linear during at least the first nine hours of exposure. During the three hours exposure period the concentration of cobalt in the water did not decrease by more than 5% [41.

2.2. Chemical speciation

A chemical speciation model was constructed to calculate the concentrations and activities of the metal species. The model calculates the equilibrium speciation from a compilation of the interactions among the components present in the solution at given hydrogen ion concentration, partial carbon dioxide pressure and temperature. Thermodynamic stability constants used in the calculations are based on the data of Dickson and Whitfield [5] for the major components and on the data of Smith and Martell [61 for the other metal species. For each species considered the stability constants measured at different ionic strengths were fitted to an interpolation function which has the form of an extended Debye-Huckel equation [71. The obtained equations were then used in the computer program SOLUTION an adaptation of .the program COMPLEX [81. 3. RESULTS

3.1. Chemical speciation model

The results of the chemical speciation calculations are shown in Fig. 1. In chemically defined medium hard freshwater without organic ligands cobalt is predominantly present as the free metal ion and some complexes of sulphate, carbonate and hydroxide. The presence of an organic ligand decreases the free cobalt ion concentration by the formation of different organic complexes. The thermodynamic stability constants of the metal ligand complexes used decreases in the following order: EDTA (log KML= 18.2) > NTA (11.8)> histidine (7.6)> citrate (6.6)> glycine (5.1). For relatively weak ligands, such as glycine, the ligand must be present in excess before a significant decrease in the free cobalt ion activity is observed. For strong ligands, such as EDTA, a significant effect is already observed in the presence of a small amount of ligand. 3.2. Cobalt uptake in complexing solutions

Cobalt uptake experiments were performed in chemically defined freshwater containing either lo-' or lo4 M of cobalt and 6 different concentrations of either of the 5 ligands. These different combinations generated a wide range of free cobalt ion activities ranging from lo-'' to lo4 M. In Fig. 2 free cobalt ion activities are plotted against cobalt uptake rates. Clearly, complexation decreases cobalt uptake and the effect only appears to depend on the free metal

I

I

I

I

I

I

I

' Histidine

108

107

108

105

104

103

102

Ligand concentration rno1.kg-l

Fig. 1. Effect of complexationby different organic ligands (i.e. citrate, glycine, histidine, NTA and EDTA) on the free cobalt ion activity in medium hard water containing lo6 M of cobalt (pH = 8.0 and T = 25°C).

ion activity. For the same free cobalt ion, cobalt uptake is the same in the presence of either a weak or strong ligand. However, over the entire range of free cobalt ion activities the rate of cobalt uptake does not remain linear. For example the rate of cobalt uptake measured in solutions containing either or lo4 M of cobalt is 0.0064 k 0.0016 and 0.0182 f 0.0021 kmol kg-' h-', respectively. Thus, a ten-fold increase in the free cobalt ion activity only causes a three fold increase in cobalt uptake under these specific conditions. To describe the observed curvature, the data were analysed using a second order reversible reaction model for mediated transport [91. Assuming equilibrium conditions, the relation between the free metal ion activity and uptake rate is that of a rectangular hyperbola. This relation is know as the Michaelis-Menten equation:

in which u is the rate of metal uptake, V,, (mol kg-' h-') is the maximum rate of metal uptake, K (mol kg-') is the ratio of reactant concentrations to product concentrations (dissociation constant) and (M) is the activity of the free metal ion (mol kg-')(l kg is 11 of water). Fitting this type of equation to the observations shows that the results can only be explained in a reasonable way when

303 0.030I

I

Y

'F

0.025

1

108

EDTA

0

T

0 Glycine

Histidine

10-5

10-4

10-3

10-2

10-1

100

Free cobalt ion activity prnol.l-'

Fig. 2. Effect of complexation by different organic ligands (i.e. citrate, glycine, histidine, NTA and EDTA) on the rate of cobalt uptake by carp as function of the free cobalt ion activity in the water (pH = 8.0 and T = 25°C). Total cobalt concentrations are either lO-'or 104M. Data points represent means with standard deviation for 6-7 fish. The solid line is the MichaelisMenten model fitted t o the data.

two binding sites for cobalt are assumed. One binding site with a high afKnity for cobalt and relatively low uptake rate, which already becomes saturated at relatively low levels of cobalt ion and a second binding site, with a much lower affinity for cobalt but higher uptake rate which becomes the more important system at higher exposure levels.

with u and V,, values in pmol kg-' h-' and K and (Co2+)values in pmol kg-I. The line fitted to the data presented in Fig. 2 shows that the model describes cobalt uptake very well over a very broad range of free cobalt ion activities. 4. DISCUSSION

A number of earlier studies have already demonstrated the importance of the free metal ion for the uptake of metals by aquatic organisms [lo]. Generally,it is found that metal uptake decreases upon complexation. This implies that metal complexes are not or poorly available for uptake. The present results confirm this and

304

show that the effect is independent of the total cobalt concentration or the ligand involved. The stability of the metal-ligand complexes formed does not influence the rate of uptake when expressed on a free metal ion activity scale. The magnitude of the stability constants is determined by the rates of metal complex formation and dissociation 1111.The rate of complex formation generally increases with the charge on the ligand while the rate of complex dissociation decreases with the thermodynamic stability of the complex formed. Coordination kinetics may limit the rate of metal uptake when the dissociation rate of the metal-ligand complexes is less than the rate of metal uptake by the organisms. Under these conditions the dynamic equilibrium between the free metal ion and the metal-ligand complexes is no longer maintained and the free metal ion concentration decreases in the layer lining the membrane surface. Thus, for the same free metal ion activity, the rate of metal uptake should decrease with the thermodynamic stability of metal complexes present. Such a dependence is not observed, indicating that cobalt uptake rates are not limited by metal-ligand complexation kinetics. Cobalt uptake rates, however, are not a mere function of the free metal ion activity in the solution. Relative uptake rates are considerably higher at low free metal ion concentrations than at high free metal ion concentrations. The Michaelis-Menten model for mediated transport of solutes across biological interfaces appears a good tool to describe the observed variation. It allows a mechanistic description of the process assuming a transport system that is characterised by a maximum rate of transport (Vmm)and a dissociation constant ( K ) (or Michaelis constant) which is a measure of the affinity of the transporter for the solute being transported. The effect of complexation is included in the model by including the free metal ion activity as the solute concentration. This approach shows that cobalt uptake by carp is best described by a system involving two uptake sites. The first binding site has a high affinity for cobalt and accumulates cobalt from the environment at very low concentrations. The second system has a much lower affinity and accumulates cobalt at higher concentrations in the environment. The site with the low affinity transports cobalt faster than the site with the high affinity. The model can describe the uptake of cobalt over a very wide range of free cobalt ion levels in the environment. Although beyond the scope of this work the model can be easily expanded to account for the effects of competing ions and changes in hydrogen ion concentration (competitive or non-competitive inhibition). As such it provides an expedient instrument to incorporate the effects of different interacting factors on radionuclide uptake in one mechanistic model. 5 . ACKNOWLEDGEMENTS

This work is part of contract with the European Atomic Energy Community (no. Bi7*OOS-C). RB is a research associate of the Fund for Scientific Research,

305

Flanders (FWO). LvG and SC are research fellows of the Flemish Institute for the Promotion of Scientific and Technological Research in Industry (IWT). 6. REFERENCES 1. Newman, M.C. and C.H. Jagoe, 1994. Ligands and the bioavailability of metals in aquatic environments. In Bioavailability: Physical, Chemical and Biological Interactions (Eds. J.L. Hamelink, P.F. Landrum, H.L. Bergman and W.H. Benson). Lewis Publishers, pp. 39-61. 2. Simkiss, K. and M. Taylor, 1989. Metal fluxes across the membranes of aquatic organisms. CRC Crit. Rev. Aquatic Sci., 1: 179-199. 3. Martell, A.E. and R.J. Motekaitis, 1988. The Determination and Use of Stability Constants. VCH Publishers. 4. Comhaire, S., R. Blust, L. van Ginneken and O.L.J. Vanderborght, 1994. Cobalt uptake across the gills of the common carp, Cyprinus carpio, as a function of calcium concentration in the water of acclimation and exposure. Compar. Physiol. Biochem., 109C: 63-76. 5. Dickson, A.G. and M. Whitfield, 1981. An ion-association model for estimating activity constants (at 25°C and 1 atm pressure) in electrolyte mixtures related to seawater (ionic strength 5 1 mol kg'). Mar. Chem., 10: 315-333. 6. Smith, R.M. and A.E. Martell, 1974-1989. Critical Stability Constants. Vols. 1-6. Plenum Press. 7. Turner, D.R., M. Whitfield and A.G. Dickson, 1981. The equilibrium speciation of dissolved components in freshwater and seawater a t 25°C and 1 a t m pressure. Geochim. Cosmochim. Acta, 45: 855-881. 8. Ginzburg, G., 1976. Calculation of all equilibrium concentrations in a system of competing complexation. Talanta, 23: 142-149. 9. Weiss, T.F., 1996. Cellular Biophysics, Vol. 1: Transport. The MIT Press. 10. Campbell, P.G.C., 1995. Interactions between trace metals and aquatic organisms: A critique of the free-ion activity model. In: Metal Speciation and Bioavailability in Aquatic Systems (Eds. A. Tessier and D.R. Turner). John Wiley and Sons, pp. 45-102. 11. Hering, J.G. and F.M.M. Morel, 1990. The kinetics of trace metal complexation: implications for metal reactivity in natural waters. In: Aquatic Chemical Kinetics (Ed. W. Stumm). John Wiley and Sons, pp. 145-171.

Freshwuter und Estuurine Rudioeof~lo#y Edited by G. Desmet et al. 0 1997 Elsevier Science B.V. All rights reserved

307

The quantification of metallic or radioactive pollutant flows in freshwater by the use of a mathematical model describing the evolution of contamination levels of a bryophyte species, Platyhypnidiurn riparioides P. Ciffroya,K. Beaugelinb,B. Claverid,F. %leta, J.-P. Baudinb"and D. Vazellea 'Electricite' de France, Environment Department 6, quai Watier, 78401 Chatou, France bZnstitut de Protection et de Surete' Nucle'aire, Dhpartement de Protection de l%nvironnement et des Installations, Laboratoire des Earn Continentales, IPSNI CEA, 13108 St-Paul-lbDurance,France 'Centre National de la Recherche Scientifique 'Centre de Recherches Ecologiques, Universite' de Metz, Laboratoire &Ecotoxicologie, B.P. 4116, 57040 Metz, France

ABSTRACT This paper describes a method for measuring bioavailable micropollutants concentrations in freshwater by the use of transplanted bryophytes. The method is based on the use of a mathematical model, capable of describing the bryophytes kinetics in the accumulation or the release of micropollutants. This model allows to calculate the mean concentration of bioavailable pollutants present in the aquatic medium, by studying the evolution of contamination levels of transplanted bryophytes. The validity of the model was first tested on a heavy metal, copper, by using an identified bryophyte species, Platyhypnidium riparioides. In vitro experiments were carried out to calculate the kinetic constants of the model. The model was afterwards validated on three French rivers, where predicted values were compared to field data. An example of such an experiment, taking place downstream from Dampierre nuclear power plant, is presented in this paper. The results of these studies were decisive; consequently, a similar methodology was applied to verify whether bryophytes were good quantitative bioindicators of radioactive micropollution. mCo specific kinetic constants were estimated by laboratory experiments. Some of the data obtained by an in situ experiment conducted in the nuclear power plant of Dampierre during a scheduled release of radioactive effluents were used to test the validity of this method of detection.

308

1. INTRODUCTION When metallic or radioactive micropollution is directly measured in fkeshwater, the result only gives information on the instantaneous pollution of the aquatic medium; this is not sufficient to estimate its average pollution level. For example, downstream from nuclear plants, discharges of radioactive eMuents are intermittent; therefore, concentrations of micropollutants can be significantly different in space and time. Besides, the detection of low levels of pollution is limited by metrological problems. In order to develop new methods of measurement, aimed at giving a quantitative indication of the average pollution of the aquatic medium, a research programme was carried out to study the interest of specific bioindicators -the bryophytes - which are able to integrate the polluting load of a flow. Aquatic bryophytes have been used for some years to monitor metal presence in many French rivers. Experiments carried out on different ecosystems have shown that they were better bioindicators of radioactive pollutants than sediments, aquatic plants or fish [ll. However, the current method of interpretation is limited to descriptive information: identification of micropollutants, location of the major contaminating sources, etc. 121. In order to obtain quantitative information, a mathematical model, capable of describing bryophytes kinetics in the accumulation or release of micropollutants, has been developed. This model allows calculation of the mean concentration of dissolved pollutants potentially present in the aquatic medium by studying the evolution of contamination levels of transplanted bryophytes. The validity of this model was first tested on a heavy metal, copper. The kinetic constants of the model were calculated by using results of in vitro experiments; the model was validated on French rivers, where predicted values were compared with field data. The results of the studies were decisive; consequently, a similar methodology was applied to verify whether bryophytes were good quantitative bioindicators of radioactive micropollution. For these studies, an identified bryophyte species -Platyhypnidium riparioides - collected in a French uncontaminated river, the Sorgue, was used. 2. THE MODEL

Many experiments on exchange processes occurring between water and bryophytes have shown the following. - Metals, supplied in an ionic form, are taken up by bryophytes in two distinct stages [31. The first stage, a rapid one, probably depends on a passive extracellular adsorption governed by ion exchange processes. The second stage, which is slower, could be the consequence of intracellular absorption [4]. - Micropollutants accumulated by bryophytes may be partially and slowly

309

desorbed. Only a small part of micropollutants is irreversibly sorbed; some authors suggest that this residual contamination might be concentrated in intracellular location, where it is highly stored [5,61. - Some authors observed a passive movement of extracellular micropollutant to intracellular locations [7,81. Given these experimental observations, the following reaction is proposed to describe micropollutant exchanges between water and bryophytes:

where M is the bioavailable dissolved micropollutant; S is the binding site in the cell wall; M-S is the micropollutantbinding site complex; Mi is the micropollutant absorbed within the cell; kads,k d e s and kabs are the kinetic constants for the reactions of adsorption, desorption and absorption respectively. The following hypothesis are also acknowledged: every reaction obeys oneorder kinetics; the binding sites are not saturated; as their number (S),is supposed to be unchanged, a new kinetic constant is defined: K a d s = kads(S)o. Consequently, the micropollutant exchanges between water and bryophytes can be described by the following kinetic equations:

Computer software based on the above equations then allows derivation of the mean bioavailable water pollution from the evolution of the contamination levels measured in the bryophytes. Obviously, to apply this model, it is necessary to know the kinetic constants; their values have been previously calculated by laboratory experiments. 3. STANDARD METHOD FOR THE CALCULATION OF THE KINETIC

CONSTANTS

A standard method to calculate &ds, k d e s and kabsvalues has been defined. To obtain the data necessary for such a calculation, a previous laboratory experiment has to be carried out in two stages: a sample of uncontaminated bryophytes is placed in a continuous bioreactor, the volume of which is known; during the first stage of the experiment, a solution containing a well-known concentration of the pollutant under study is continuously added into the bioreactor; after some days of continuous input, this solution is replaced by an

3 10

I

I

I

I

* O fli

1"mge :contamination

$4 t2i

f2.3

rn

time

2nd stage : decontamination

Fig. 1. Schematic representation of the contamination level evolution of bryophytes during the two-stage laboratory experiment.

uncontaminated medium. The following variables must be particularly monitored: the input flow, the absence of suspended materials, pH and cation concentrations (Ca" and Mg2'in particular). Generally, the curve representing the contamination level of bryophytes during the experiment is as shown in Fig. 1. It is then possible to estimate &a, k d e s and kabs values by studying the boundary conditions of the experiment: - at the beginning of the experiment, the desorption and absorption processes are negligible. Equations (1)and (2) can be simplified as follows:

is the average concentration of the bioavailable micropollutant in where (M) water between toand tli; A[(M-S) + (Mi)]is the variation of the contamination level of the bryophytes between to and tli; At is the difference (tli - to) (see Fig. 1). - the k d e s value can be estimated by studying the evolution of the contamination level of bryophytes at the beginning of the second stage of the experiment. kdeais then given by the following equation:

where ( M a )is the average concentration of the bioavailable micropollutant adsorded on the cell wall between tl-2 and tzi; AKM-S) + (Mill is the variation of the contamination level of bryophytes between tl-z and tzi;At is the difference (t2i - tl-2).

311

As the value of (M-S) is unknown, we consider that it ranges between the two following extremes:

Therefore, a range of kdes values is obtained. -to specify kdes and haba values, different triplets (Kab,kdes, kab& are tested on a particular computer software; the values of the concentrations of micropollutants present in water are first calculated for each triplet and then compared with the measured concentrations. kdesand kabs values are chosen in such a way as to obtain the optimum correlation. 4. EXAMPLE 1: APPLICATION OF THE MODEL FOR THE DETERMINATION OF DISSOLVED COPPER

The validity of this model was first tested on a heavy metal, copper. The kinetic constants of the model were calculated by using results of in vitro experiments; this model was validated on French rivers, where predicted values were compared to field data. 4.1. Determination of the kinetic constants

A two-stage laboratory experiment (similar to that described above) was carried out in order to calculateK,d,, kdes and kab kinetic constants. The experimental major variables are presented in Table 1. The two stages last 168 and 240 hours respectively. To verify the independence of the kinetic constants from the concentrations of micropollutants in the aquatic medium, five laboratory experiments were carried out simultaneously: the solutions added to the bioreactors were contaminated by CuClz at 20,40,80,160 and 320 pg/l respectively. Copper uptake TABLE 1 Experimental conditions of the Cu calibration experiment Biological variables

Hydraulic var.

Physical and chemical variables

Bryophyte sp.

Bio. vol.

1.f. (Vmin)

pH

18 1

0.5

7.8 15

Biomass

Platyhypnidium -80 g ripariocdes fresh ______~

~~

~

Bio.vol. = bioreactnr volume; 1.f. = input flow

T Susp. Ca2+ Mg2' Org. ("C) matt. (mg/l) (mg/l) comp. -

105

11

EDTA 2 mg/l

3 12

-

(Culwater during the contamination stago

P

-0

..

+-

40ppb 80ppb 160ppb

*--. 320 ppb

I . . . .

d

2

0

r

200

100 contamination stage

I

400

300

decontamination stage

time (h)

1

Fig. 2. Contamination levels of Platyhypnidium riparioides during 5 in vitro experiments.

TABLE 2 Kinetic constants describing the exchanges of copper between water and bryophytes at different copper concentrationsin the experimental medium (Cu),,te, during the stage of contamination

20

40

80

160

320

Average value

Kads (en 1 g-' h-') kdes (en h-'1 kah (en h-')

0.24 0.045

0.2 0.046

0.22 0.059

0.21 0.055

0.22 0.053

0.009

0.01

0.25 0.062 0.008

0.008

0.008

0.009

(m)

and release by bryophytes are presented in the Fig. 2 (measurements of mineralized samples by atomic absorption spectrometry). For each experiment, Kads,k d e s and kabs kinetic constants are calculated on the basis of the aforementioned standard method (Table 2). The results show that the values of the kinetic constants are not related to the concentrations of micropollutants present in the aquatic medium. This important observation demonstrates that the model can easily be applied to a vast range of pollution levels similar to those generally found in natural aquatic media. 4.2. Application of the method for the determination of dissolved copper in natural aquatic media

The validity of the model has been tested by numerous in situ experiments. The following experimentation is an example. It took place downstream from Dampierre nuclear plant (on the Loire river) from 19 to 26 July 1993.

3 13 TABLE 3 Experimental conditions of the in situ experiment ~

~~~

Biological variables

Hydraulic variables

Physical and chemical variables

Bryophyte species

bioreact. input flow vol. (Vmin)

pH T susp. mat. Ca2+ Mg2' org. ("C) (mgll) (mgll) (mg/l) comp

18 1

8.5 24

biomass

Platyhypnidium -80 g riparioides fresh

0.5

20

35

7

?

TABLE 4 Measurements of copper accumulated by Platyhypnidium riparioides Time (d) (Cu) accumulated by P.riparioides ( F P k dry)

10

218

268

378

436

493

Bryophytes, initially uncontaminated, are placed in a bioreactor supplied with water which is pumped from the discharge canal of the power plant. The input flow of the water is continuous and constant. Consequently, biological and hydraulic parameters of the in situ experiment are identical to those of the laboratory experiment described above. Besides, before being input into the bioreactor, the water goes through a decanter where suspended particles are partly eliminated. As suspended particles generally have a damaging effect on the contact between dissolved micropollutants and bryophytic cells, their partial elimination reduces errors in measurements. The major parameters of the experiment are summarized in Table 3. Simultaneously, an average sample of water is collected daily. It is then filtered (0.45 mm) and the dissolved copper is measured by atomic absorption spectrometry. Copper accumulation kinetics by the bryophytes placed in the bioreactor is presented in Table 4. From these data and on the basis of the model presented above (Eqs. (1) and (2)), it is possible to calculate the mean concentration of the bioavailable copper present in water. Time step is drawn from the intervals between two measurements of the contamination levels of bryophytes. Calculated values can be compared to dissolved copper quantities measured in water samples (Fig. 3). In general, there is a good correlation between calculated and measured daily averages: in 5 cases out of 7, the gap does not exceed 10%;the 2nd and

3 14 loo 90

5T

80 70

m

0 - 5 0

3

;30 20

(lime step

I

1 day)

10 0 0

1

2

3

4

5

6

7

time (days)

Fig. 3. Comparison between measured and calculated concentrations of dissolved Cu.

3rd day calculated values only significantly exceed measured values. Furthermore, the exploitation of the model over a longer period (calculation time step = 1week) corroborates the validity of the method: over the week, calculated and measured average concentrations of dissolved copper are 61 mgA and 56 mgA respectively. 5. EXAMPLE 2: APPLICATION OF THE MODEL FOR THE DETERMINATION OF DISSOLVED RADIOCOBALT

As the model described above has been shown to quantify metal pollution, a

similar method is suggested for detecting radioactive pollution. The following example concerns radiocobalt. 5.1. Determination of the kinetic constants

k&, kdes and kabskinetic constants suitable for cobalt radioactive isotopes were calibrated following a method similar to the standard method previously described: bryophytes are placed in a bioreactor supplied with a sequence of a 6oCo contaminated solution and a clean solution. In this experiment, the rate at which the contaminated solution is provided is 6/48 h. The key conditions are given in Table 5. Cobalt-60 uptake and release by bryophytes are presented in Fig. 4. I ( a d s , bee and kahkinetic constants are drawn from these data and from the measurements of dissolved “co. In this case, the following values are calculated: Kads = 65 1g-lj-’; kdes= 10j-’;/tab = 0.15j-’. It is verified that using these values, a good correlation is obtained between in uitro measured and calculated concentrations of dissolved 6oCo(Fig. 6 ) .

3 15 TABLE 5 Kinetic constants describing the exchanges of radiocobalt between water and bryophytes Biological variables

Hydraulic variables

Physical and chemical variables

Bryophyte spe- biomass cies

bioreac. input flow vol. (ml/h)

pH

T susp. Ca2+ M e org. ("C) matter (mgN (mg/k) comp.

Platyhypnidium 40 g riparioides fresh

31

7.7

18

630

97

-

i

19.5

-

contamination stage

o d e c o n t a m i n a t i o n stage

20000

10000

0

0

n

I

I

1

I

2

4

6

8

n

m

a

n

10

time (days)

Fig.4. Uptake and release of "Co by Platyhypnidium riparioides.

5.2. Application of the method for the determination of dissolved radiocobalt in natural aquatic media

The application of the method to measure the concentrations of radionuclides in general, and of radiocobalt in particular present in natural aquatic media raises problems. Indeed, Kads,Kdes and kabs kinetic constants are calculated from laboratory results; because of metrological limitations, the pollution levels of the laboratory experiments are much higher than those generally found in natural aquatic media. Consequently, it is necessary to verify whether the model, based on laboratory kinetic constants, can be extrapolated to calculate good estimations of low pollution levels found in natural aquatic media. A previous in situ experiment, aiming at answering this question, took place downstream from Dampierre nuclear plant (on the Loire river) from 19 July to 5 August 1993. The principle of the experiment as follows: - bryophytes, initially uncontaminated, are placed in mesh-bags which are

3 16

-

-

1

5 z3" -

8

'p

calculated dissolved 60Co

contamination stage (6 h)

20

! 0

3

10

0

2

0 t

l

l

L

J

4

1

u 11

6

" -i

0

lime (days)

Fig. 5. Comparison between measured and calculated concentrations of dissolved 6%o.

fully submerged in the river; 4 km separate the discharge canal of the power plant from the location where bryophytes are immersed. - during the experiment, radioactive effluents are discharged on the following dates: 20-21/07;24-26/07;03-04/08; the composition of these effluents is known. Based on 3H measurements, it is possible to calculate the dilution factor of the effluents at the location where bryophytes are immersed. - during the first discharge, suspended matter is collected by centrifugation; it is then possible to measure the concentrations of radionuclides adsorbed on particles. Cobalt-58 accumulation kinetics by the bryophytes is presented in Fig. 6 (the time "0"indicates the arrival of radioactive contamination at the "bryophytes point"; it is determined thanks to 3H measurements). During the experiment, the contamination level of bryophytes significantly increases; this confirms that bryophytes are good qualitative bioindicators of

A

i?

20

-

0

8s u 8

15-

ZE

Ha zf 3a a m

p"

Fig. 6. Uptake of 6 k o by Platyhypnidium riparwides.

0 period of discharge

3 17

0

400

period of discharge

300

8 k 0

ki

200

v)

100

T dissolved 58Co flow 0

I time (days)

Fig. 7. Cumulated 5%0 flows (total, dissolved, adsorbed on suspended matter.

low radioactive contaminations. Nevertheless, some measurements are unexpected: 58C0is not detected in the sample of bryophytes collected after 6 hours of contact with contaminated water; desorption does not occur when no discharge takes place (0.5-2.75 days). These unexpected data could be due to the presence of large quantities of particles which were observed in the bryophytes bags and which probably had a competitive effect on the contact between dissolved micropollutants and bryophytes cells. Despite these unexpected results, the model has been tested. The major results of the calculation are synthesized in Fig. 7. In this figure, the cumulative quantities of 58Cotransported in each phase of the aquatic medium are presented: - Curve 1 shows the flow of dissolved 58C0which is calculated from the contamination levels of the bryophytes measured at the following dates: 0; 0,5; 9,75; 16,75 days (Fig. 5); the aforementioned unexpected values are not taken into account. The model is based on the laboratory Kads,kdes and kabskinetic constants previously calculated and suitable for 6oCo. Besides, the dissolved Y!o transport is supposed to occur only during the periods of discharge. - Curve 2 is the sum of the 58C0quantities transported in two phases: the flow of dissolved 58C0(previously calculated) and the flow of particulate 58C0. The flow of 5 8 Ctransported ~ by particles is calculated from the contamination level measured on suspended matter collected during the first discharge. The distribution coefficient Kdand the concentration of suspended solids are supposed to be constant in space and time; the measured value of Kd is 143 m3/kg. - Curve 3 shows the total discharged 58C0,according to data concerning the composition of the radioactive discharged effluents. In theory, the sum of the 58C0quantities transported in both phases (Curve 2) should be equal to the total discharged 58C0(Curve 3). The results show that the estimations drawn from the application of the model are satisfactory: the gap between theoretical and calculated total 58C0flows does not exceed 25%.

318

6. CONCLUSIONS

The method described aims at estimating the average concentrations of dissolved pollutants, potentially present in natural aquatic media, by studying the evolution of contamination levels of transplanted bryophytes. The object of the first stage of the study was to define a model capable of describing the kinetics of bryophytes in the accumulation or release of micropollutants. This model is based on experimental observations; three phenomena are supposed to be responsible for the exchanges of micropollutants between the water and the bryophytes: adsorption, desorption and absorption. Each process is characterized by a specific kinetic constant, the value of which can be calculated thanks to a standard method based on simple laboratory experiments. The model was then tested on heavy metals and radionuclides. The cases of copper and radiocobalt are presented in this article. The results concerning copper are decisive: laboratory experiments demonstrate the independence of the kinetic constants from the concentrations of micropollutants in the aquatic medium; the application of the method to field data shows a good correlation between calculated and measured average concentrations of dissolved copper. The application of the method to radionuclides in general and radiocobalt in particular raises some problems, but the preliminary results are encouraging: the kinetic constants are calculated from laboratory experiments in which the pollution levels are much higher than those generally found in natural aquatic media, Despite this potential problem, a good estimation of dissolved 68Coflows downstream from the discharge canal of a power plant was obtained thanks to measurements on bryophytes. Nevertheless , the sensitivity of the detection was probably limited by the presence of suspended particles in the microenvironment of the bryophytes. It is possible to define priorities to improve the method: the kinetic constants suitable for radionuclides should be calculated thanks to laboratory experiments carried out in contamination conditions similar to those generally found in natural aquatic media. It is necessary to limit the detrimental effect of suspended particles on the contact between dissolved micropollutants and bryophytic cells. The influence of some parameters (hydraulic conditions, cation concentrations) should be studied and then complete the model. 7. REFERENCES 1. 2.

Baudin, J.P., A. Lambrechts and M. Pally, 1991. Utilisation des mousses aquatiques comme bioindicateurs de contamination radioactive. HydroBcol. Appl., 3 (2): 209-240. Mouvet, C., 1986. MBtaux lourds et mousses aquatiques. Synthbse m6thodologique. Agence de l'Eau Rhin-Meuse. Agence de l'Eau RhGne-MBdit6rranBe-Corse. Universit6 de Metz. 110 pp.

319

3. Clymo, R.S., 1963.Ion exchange in Sphagum and its relation to bog ecology. Ann. Botany, 27:309424. 4. Pickering, D.C. and I.L. Puia, 1969.Mechanism for the uptake of zinc by F o n t i d i s antipyretica. Physiol. Plant, 22:653-661. 5. Gullvig, B.M., H. Skaar and E.M.Ophus, 1974.An ultrastructural study of lead accumulation within laeves of Rhytidiadelphus squarrosus (Hedw,) Warnst. A comparison between experimental and environmental poisoning. J. Bryol., 8: 117-122. 6. Mouvet, C., 1987.Accumulation et relargage de plomb, zinc, cadmium, chrome e t

cuivre par des mousses aquatiques en milieu nature1 e t au laboratoire. Agence de Bassin RhBne-MBdiGrranee-Corse.Universit6 de Metz. 122 pp. 7. Brown, D.H.and R.P. Beckett, 1985. Intracellular and extracellular uptake of cadmium by the moss Rhytidiadelphus squarrosus. Ann. Botany, 55: 179-188. 8. Wells, J.M. and D.H. Brown, 1987.Factors affecting the kinetics of intra- and extracellular cadmium uptake by the moss Rhytidiadelphus squarrosus. New Phytol., 105:123-137.

Freshwuter und Estuurine Rudioecology Edited by G. Desmet et a]. 0 1997 Elsevier Science B.V.All rights reserved

321

Calcium influences radio-cobalt uptake by the common carp, Cyprinus carpio S. Comhaire, R. Blust, L. Van Ginneken, F. Dhaeseleer and 0. Vanderborght Department of Biology, University of Antwerp (RUCA), Groenenborgerlaan 171, 2020 Antwerp, Belgium

ABSTRACT The effect of different calcium concentrations on the uptake of cobalt through the gills of the common carp, Cyprinus carpio, was studied in chemically defined freshwater. Fish were acclimated for 16 days to a set of different calcium concentrations, while cobalt uptake experiments were conducted over a 3-hour period at the same range of calcium concentrations. A clear decrease in cobalt influx with increasing calcium concentrations in the water of exposure was observed. The effect of the calcium concentration in the water of acclimation is significant, but of minor importance. Increasing the free cobalt ion activity in the water increases the cobalt influx, while calcium influx is inhibited. High calcium levels in the water reduce the blocking of calcium influx by cobalt. Since uptake kinetics of both cobalt and calcium show similar results for influx in body, gills and blood, and both elements inhibit each others uptake, a competitive interaction at the apical translocation system of the gill epithelium is suggested.

1.INTRODUCTION

Radio-cobalt, present in the environment, can be taken up by aquatic organisms in two possible ways: (1)dietary uptake of cobalt by feeding and (2) direct uptake from the aquatic environment. Baudin and Fritsch [ll reported that although dietary sources may be important, the uptake of radio-cobalt by the carp, Cyprinus carpio, is mainly determined by the waterborne concentration. The gills of freshwater fish are the primary site of uptake of alkaline, earth-alkaline and transition metals. Despite this, little is known about the mechanism by which cobalt ions transverse the gills of freshwater fish. The mechanism of metal uptake has generally been considered to be a facilitated diffusion process [2,3]. Acclimation and exposure of fish to various external calcium levels

322

induces structural and functional changes in the gill epithelium. Calcium may compete with other ions for the uptake sites and changes the ion and water permeabilities of the gill epithelium. As such, environmental calcium concentrations are an important controlling factor in metal uptake. The purpose of this study was to determine the effect of various environmental calcium levels and acclimation regimes upon the uptake of radio-cobalt by the common carp, Cyprinus carpio. We also wanted t o get some insight into the mechanism by which Co2+might transverse the gill epithelium of the carp. 2. MATERIALS AND METHODS

Two sets of experiments were conducted. First, the effect of acclimation and exposure of the fish to various environmental calcium levels on the uptake of cobalt by carp was studied. For this purpose fish (3-6 g) were acclimated to a set of different calcium levels ranging from 100 to 10000 pM Ca2' for 16 days. These calcium levels were obtained by modification of the standard water (Ca2+ 348 pM; Mg2' 500 pM; Na+ 1143 pM; K ' 54 pM; SO; 848 pM;C0,"-1143 pM; C154 FM added to deionised water, pH = 7.6-8.0,25°C f 1°C).Cobalt uptake experiments were performed in waters of the same range of calcium concentrations. Waters used during the experiments had the same basic composition as the waters used during acclimation. In addition, 10 mM of the non-complexing buffer (H)EPPS (Sigma)was added to keep the pH at 8.0 f 0.1during the cobalt uptake experiments. These waters also contained 1 pM of cobalt and were spiked with tracers of cobalt (67C0)and calcium (46Ca). To examine the nature of the interaction between cobalt and calcium, fish were acclimated to standard water, while uptake experiments were performed at 3 different calcium levels (i.e. 100,348 and 1000 pM Ca2+).Waters used during the uptake experiments had the same composition as in the former uptake experiments. In contrast different cobalt concentrations, ranging from 1 to 1000 pM Co2+,were added to these solytions. Uptake experiments were performed over a 3-h period, after which fish were rinsed for 5 min in water with the same composition but without radioactive tracers. 67C0influx in fish was measured by in uiuo y-counting. Subsequently the fish were killed, blood was collected by puncturing the heart. Gill filaments were dissected out and removed from the gill arches. 67C0and 45Ca levels in gills and blood were measured by y and p counting, respectively. Total cobalt and calcium uptake was calculated using the specific activity of the solutions for both isotopes. For calculation of the uptake of cobalt and calcium by the gills, the measurements were corrected for the blood content in the filaments.

323 3. RESULTS

The effect of the calcium ion activity in the water of acclimation and exposure on the uptake of Co2+by whole fish, gills and blood is shown in Fig. 1. Cobalt influx decreases with increasing free calcium ion activities of both acclimation and exposure water. To determine the relative importance of acclimation and exposure to calcium on the uptake of cobalt, a non-linear regression model was built. This model accounts for the chemical and biological effects of changes in the concentration of calcium in the water on cobalt uptake. Considering the change in free cobalt ion activity caused by an increase in the ionic strength of the solution and the formation of the cobalt sulphate ion-pair at increasing calcium sulphate concentrations, and the effect of the free calcium ion activity in the water of acclimation and exposure, the model explains 80437% of the measured variation in cobalt uptake. The predicted cobalt influx according to the model is represented as a surface plot in Fig. 1. Increasing the cobalt concentration of the water results in an increase of cobalt influx in the body, gills and blood (Fig. 2). Cobalt uptake displays saturation at low external cobalt concentrations, while at high free cobalt ion activities in the water, cobalt uptake is mainly determined by a non-saturable, cobalt ion activity dependent component. Increasing the free cobalt ion activity also reduces the calcium influx in gills and blood (Figs. 3 and 4). This effect is more profound at low environmental calcium levels. 4. DISCUSSION

The results show that the uptake of cobalt from the water across the gills depends on the concentration of calcium in the water. Although an increase of the calcium concentration in both acclimation and exposure water decreases cobalt uptake, the effect of calcium in the water of exposure on the uptake of cobalt is much more profound than the effect of calcium in the water of acclimation. The effect of calcium on the uptake of transition metals is a well documented phenomenon. Part et al. [4],Wicklund and Runn 151 and Bentley [6] reported that the uptake of cadmium by freshwater fish decreases with increasing environmental calcium levels. Bradley and Sprague 171 and Spry and Wood [8,91found the same effect on the uptake of zinc. Although cobalt uptake kinetics display saturation (indicative for facilitated transport), and the external calcium concentration shows an inhibitory action, no kinetic parameters could be determined. Consequently we are not yet able to characterise the nature of the interaction between calcium and the uptake of cobalt in an unequivocal way. The inhibitory effect of calcium on the uptake of cobalt and the effect of cobalt on the uptake of calcium are similar for the influx measured in body, gills and blood. We thus can conclude that the interaction between both elements must take place at the initial step of

324

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* (Ca”

Fig. 1. Effect of Ca2+ion activity in the water of acclimation and exposure on the uptake of Co2 t by the fish body, the gills and the blood. Plotted points represent data averages (n = 5-14). Surface plot represents the predicted cobalt uptake according to the fitted model.

influx = a * (co”)

Co2+ influx in blood

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326

Co2' influx in blood

Co2+influx in gills

Co2' influx in body

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Co2+activity in solution Fig. 2. Co2' influx in body, gills and blood at various external free cobalt ion activities in the solution. Uptake is measured at 3 different calcium concentrations( 0 = 1000,H = 348 and A = 100 pM Ca2+).Plotted points represent data average (n = 5-14)f standard deviation.

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200

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Co2+activity in solution (pM) Fig. 3.Ca2+influx in gills at various external free cobalt ion activities in the solution. Uptake is measured at 3 different calcium concentrations(1000,348and 100pM Ca"). Plotted points represent data averages (n = 6-14)f standard deviation.

327 [Ca2’] = 100 pM

(CaZt] = 348 pM

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Co2+activity in solution (pM) Fig. 4. Ca2+influxin blood at various external free cobalt ion activities in the solution. Uptake is measured at 3 different calcium concentrations(1000,348and 100 pM Ca2+).Plottedpoints represent data averages (n = 5-14) f standard deviation.

entrance. Therefore, the observed interaction between cobalt and calcium appears to occur at the apical epithelium of the gills. Summarising, both an inhibitory effect of calcium on the uptake of cobalt as an inhibitory effect of the environmental cobalt level on the uptake of calcium is observed. High external calcium levels reduce the cobalt blocking of calcium uptake. This can be seen as circumstantial evidence for a competitive interaction between cobalt and calcium a t the apical translocation system of the gill epithelium. Although it is likely that a competitive interaction is involved, this still remains to be confirmed 5. ACKNOWLEDGMENTS

S. Comhaire is a Research Fellow of the Institute for Scientific Research for Industry and Agriculture (I.W.O.N.L.)and R. Blust is a Research Associate of the National Fund for Scientific Research (N.F.W.O.)of Belgium. The study is financially supported by the E.C. Radiation Protection programme “Towards a functional model of radionuclide transport in freshwater ecosystems” (contract no.: FI3P-CT92-0029).

328

6. REFERENCES 1. Baudin, J.P. and A.F. Fritsch, 1989. Relative contributions of food and water in the accumulation of @Coby a freshwater fish. Water Res., 23: 817423. 2. Simkiss, K. and M.G. Taylor, 1989. Metal fluxes across the membranes of aquatic organisms. CRC Crit. Rev. Aquat. Sci., l ( 1 ) : 173-188. 3. Da Silva, J.J.R. and R.J.P. Williams, 1991. The Biological Chemistry of the Element, the Inorganic Chemistry of Life. Clarendon Press, Oxford. 4. PW, P., 0. Svanberg and A. Kiessling, 1985. The availability of cadmium to perfused rainbow trout gills in different water qualities. Water Res., 19: 427434. 5. Wicklund, A. and P. Runn, 1988. Calcium effects on cadmium uptake, redistribution,and elimination in minnows, Phoxinus phoxinus, acclimated to different calcium concentrations. Aquat. Toxicol., 13: 109-122. 6. Bentley, J.P., 1991. Accumulation of cadmium by channel catfish (Icatlurus punctatus): influx from environmental solutions. Comparative. Biochem. Physiol., 99C (3): 527-529. 7. Bradley, R.W. and J.B. Sprague, 1985. Accumulation of zinc by rainbow trout as influenced by pH, water hardness and fish size. Environ. Toxicol. Chem., 4: 685-694. 8. Spry, D.J. and M.C. Wood, 1988. Zinc influx across the isolated, perfused head preparation of the rainbow trout (Salmogairdneri)in hard and soft water. Can. J. Fish. Aquat. Sci., 45: 2206-2215. 9. Spry, D.J. and M.C.Wood, 1989. A kinetic method for the measurement of zinc in vivo in the rainbow trout, and the effects of waterborne calcium of flux rates. J. Exper. Biol., 142: 425-446. 10. Verbost, P.M., J. Van Rooij, G. Flik, R.A.C. Lock and S.E. Wendelaar Bonga, 1989. The movement of cadmium through freshwater trout branchial epithelium and its interference with calcium transport. J. Exper. Biol., 145: 185-197.

Freshwuter und Estuorine Rudioecology Edited by G.Desmet et 01. 0 1997 Elsevier Science B.V. All rights reserved

329

Mechanisms of radiocesium uptake and accumulation in Riccia fluitans Jose A. Fernandeza, Miguel A. Herediaa, Maria J. Garcia-Sancheza, Jose A. G. Coriscob, M.C. Vaz Carreirob, and Antonio Diez de 10s RiosC aDpto. de Biologia Vegetal, Universidad de Malaga, Campus de Teatinos s l n . 29071, Malaga, Spain bDpto. de Protecpio e Seguranca Radiolbgica, D.G.A.,Estrada Nacional 10, 2685 Sacavkm, Portugal 'Dpto. de Fisica Mkdica, Universidad de Mdlaga, Campus de Teatinos s l n . 29071, Malaga, Spain

ABSTRACT The mechanisms of radiocesium uptake and accumulation have been studied, from a physiological point of view, in Riccia fluitans. There are two mechanisms of radiocesium uptake in this plant. One takes place when the external potassium concentration is above 0.1 mM. In this case, the uptake kinetic is linear, and the transport system exhibits a low affinity for cesium. Radiocesium enters the cells through potassium channels, the electrochemical potential gradient for this ion being the driving force. A second mechanism is developed in plants adapted to low or very low concentrations of potassium (less than 0.1 mM). The uptake kinetic is hyperbolic and exhibits a great sensitivity for cesium. This mechanism is carrier-mediated, protons probably being the driving ions, and takes place against the electrochemical gradient for potassium and cesium.

1.INTRODUCTION

There are only a few reports on radiocesium uptake by freshwater plants [1,2]. After the Chernobyl accident, some attempts have been made to study this process in microalgae [31 and to model the transfer of radiocesium through simplified freshwater food chains [4,51. However little is known of the basic mechanisms of radiocesium uptake and accumulation in freshwater plants. The lack of a mechanistic model for the process makes it very difficult to define

330

the major environmental variables controlling the process and, as a consequence, to offer a series of possible countermeasures. At present, the principles of ion transport in plant membranes are considered to be well understood 161. According to these principles, transport processes in the plant membrane (plasmalemma), take place through channels, carriers and pumps [6]. So far, the major ion channels discovered in the plasmalemma are K', Cland Ca2' channels [61, which are responsible for the passive transport of the non-metabolizable ions. Typically, the primary pump in plants is a proton pump ATPase [7]. The activity of this pump accumulates energy in the membrane (proton motive force, that is used for the active uptake of the major metabolizable ions. The transport of these substances takes place against electrochemical gradient and takes place through carrier systems, protons being the major driving ion. Such mechanisms have been proposed for nitrate [8],phosphate 191,sulfate [ 101 and some amino acids [lll. This membrane model is also valid for Riccia fluitans cells, as demonstrated by Felle [11,121.In this species, K' is near equilibrium with diffusion potential (ED) in plants grown in a non-limiting K' environment [12]. On the other hand it has been recently shown that K' is incorporated actively in plants submitted to K ' deficiency [131; in this case K' uptake is carrier mediated, and protons are probably the driving ion as in the case of Arabidopsis thaliana [ 141. However, it has recently been demonstrated that Na' can also drive K' transport, as in Chara australis 1151 or Nitella translucens 1161. The aim of this paper is to investigate the uptake of radiocesium in R. fluitans under two different growing conditions in terms of external K' concentration i.e. under K ' deficiency, 1nM K', and under K' sufficiency, 0.1 mM K', in order to develop a mechanistic model for the uptake and accumulation of this radionuclide and t o predict, as far as possible, the concentration factors (CF) in these experimental conditions. 2. EXPEBIMENTAL

2.1. General

Thalli of R. ftuitans were kindly supplied by Prof. Felle from the Botanisches Institut der Justus von Liebig Univeraitat in Giessen. Plants were grown as described previously [121. Experiments were performed in a simplified artificial pond water (APW) containing 0.1 mM KC1, 0.1 mM NaCl and 0.1 mM CaClz buffered with 20 mM HEPES-Ca(OH)zat pH 7.3. In the case of plants grown at low K' concentrations, the experimental solution contained 1 nM KCl. These plants were preincubated during three days in the same medium in which the experiments were performed. Temperature during preincubations and experiments was 20°C.

331

2.2. Electrophysiological measurements Membrane potentials were measured using the standard glass microelectrode technique as in Felle 111,121. Capillary glass containing internal filament was pulled using a Narishige PD-5 horizontal puller. Tip diameters were 0.30.5 pm. Microelectrodes were backfilled with 0.5 M KCl. Micropipettes were fixed to electrode holders containing a Ag/AgCl pellet, connected to a high impedance voltmeter WPI FD-223. Signals were continuously recorded on a pen chart. Experiments were performed under the microscopy light adjusted to 200 mmol m-2 s-'. 2.3. Radiocesium uptake experiments

Uptake experiments were performed in Erlenmeyer flasks with continuous gently shaking under continuous fluorescent light, 150 mmol m-2 s-' (Silvania FZOW/CW-RS). Between 1.5 to 2 g (fresh weight) of R. fluitans thalli were placed into 300 ml of APW. Every flask was contaminated with '37CsC1up to a final activity of 20 Bq ml-'. Every experiment was performed in triplicate. Concentration factors (CF) were computed as the ratio between the activity inside the plants, expressed in terms of plant water volume, and the activity per volume of assay medium. Plant water volume was determined as the difference between plant fresh weight and dry weight (24 h at 1lOOC). 3. RESULTS

3.1. Plants adapted to 0.1 mM K ' Riccia fluitans thalli adapted to 0.1 mM K' exhibited a low rate of 137Cs+ uptake (Fig. l), and a concentration factor (CF) expressed in terms of fresh weight of 51.0k2.0. Increasing concentrations of external K' inhibited the accumulation of radiocesium (Fig. 2). The presence of 1mM tetraethylammonium (TEA) in the external solution, a well known potassium channel blocker [17], inhibited also the accumulation of radiocesium, CF being equal to 26.0k0.9 (n = 7). This figure represents 50% of radiocesium accumulation with respect to the control. When cesium uptake rates were plotted versus the external concentration of cesium, the kinetics was linear (Fig. 3). The linear regression obtained for those data was CsUR = 0.56 + 0.013 [Cs'], r = 0.99 (n = 151, CsUR being the uptake rate of cesium (expressed in mmol g-' h-') and [Cs'l the external concentration of cesium (expressed in mM) respectively. For a plant cell, the electrochemical potential for an ion, AcLJ+/F, depends on the charge of the ion ( z ) ,the membrane potential (Em)and the Nernst potential for this ion (En'):

Apj+lF = z(Em - E d )

332

0' I 0 1 0 20 30 4 0 5 0 6 0 7 0

time (h) Fig. 1. Time course of the 13'Cs+ activity (expressed in cpm per gram of plant fresh weight) in the experimental medium containing Riccia fluituns thalli adapted to 1nM KCl during three days (closed circles)and adapted to 0.1 mM K+(open circles).The external concentration of stable cesium was zero. Data are means f SD (n = 3).

n

3

.c v

LL 0

1

0

2

4

6

External

8

10

12

K' (mM)

Fig. 2. Changes in concentration factor (CF), with increasing external concentrations of potassium. Data are means f SD (n = 3).

Since the membrane potential depends on the operation of the proton pump present in the plasmalemma of the plant [11,121, it is possible to manipulate the value of the membrane potential and, as a consequence, the value of b 8 + / F ,by the addition of different amounta of a metabolic inhibitor such as cyanide.

333

0

, 0

40

I

80 120180200240280320

External cesium

m+1PM

Fig. 3. Cesium uptake rate (expressed in pmol Cs' g-' h-'1 in plants adapted during three days to low external potassium concentration (1 nM) (closed circles);and in plants adapted during the same time to high external potassium concentration (0.1 mM) (open circles). Data are means f SD, n = 30 for the saturable kinetics and n = 15 for the linear kinetics.

The Nernst potential for a given ion 0') can be computed from the expression: En' = RTIzF In ColC'i where R is the gas constant, T is the absolute temperature, F is the Faraday constant and CJoand Ci are the ion concentration outside and inside the plant cell, respectively. The value of the Nernst potential for radiocesium in this case, can be computed from the concentration factor, because Q o E i is equal to CF-', expressed on a plant water volume basis. In Table 1, the values of the membrane potential (Ern), Nernst potential (EnC"+) and the electrochemical potential for cesium (Apc,*lF are shown for three different concentrations of cyanide. The concentration factor in R. fluitans, for radiocesium, increased as Apes+/ F increased (Fig. 4). 3.2. Plants adapted to 1 n M K +

' concentrations took up radiocesium at Riccia fluitans thalli adapted to low K a very high rate (Fig. 11, and they were able to concentrate more radiocesium than thalli grown at 0.1 mM K', hence CF for radiocesium in plants adapted to 1 nM K+ was 1329f128, more than 25 times the value obtained for thalli adapted to a high (0.1 mM) K' concentration. The uptake rate kinetic for radiocesium in these plants exhibited a Michaelis-Menten behaviour. The calculated kinetic parameters, maximum

334

TABLE 1 Values of concentration factor (CF) for 137Cs+,Nernst potential for 137Cs+(En137Ca+), membrane potential (Em),and electrochemicalpotential for 137Cs+(Ms+lF), in the presence of 0.1 mM K+, under the three concentrations of sodium cyanide used in the experiments. Figures are means f SD ( n = 5). NaCN (mM)

CF

~~137Cs+

Em (mv)

AWs*IF

0 0.01 0.1

5145f3 39f2

-99.2f1.0 -96.0f1.7 -92.432.0

-245f3 -177f2 -16M3

-145.M2.0 -81.0fo.3 -67.6f2.0

56 T

a0

60

80

100

120

140

160

-Ap1 37cs+/F Fig. 4. Variation in concentration factor (CF),computed in terms of fresh weight, with respect to the variation of the computed electrochemical gradient for 137Cs+( A w S + l F )Data . are meanafSD (n = 3 for both variables).

cesium uptake rate (V-) and semisaturation constant (K,) were respectively 1.9f0.2 pmol g-' h-', and 16.4f5.9pM (meanfSE), r = 0.96 (n = 30). The efficiency of the transport system can be estimated as the ratio between V,, and K,.This parameter is comparable to the slope of the linear kinetic found in plants adapted to high K concentrations. The ratio V&Ka was 0.121 g-' h-', around ten times higher than the slope of the linear kinetic (0.0131g-' h-'). 4.DISCUSSION

Cesium uptake in R.ftuituns takes place by means of two different transport mechanisms. One of them exhibits a Michaelis-Menten saturation and the

335

other exhibits linear kinetics. The mechanism showing saturation occurs only at low potassium concentration in the external medium (below 0.1 mM). In contrast, the mechanism exhibiting linear kinetics seems to be present under any external potassium concentration, but in potassium deficient plants, the contribution of this mechanism to the overall uptake rate seems to be not significant. Similar Michaelis-Menten kinetics have been classically reported for K' uptake in higher plants [MI, but also for phosphate uptake in algae [19]. Kochian and Lucas 1131 observed the same pattern of K' uptake in corn roots and they suggested that the saturable component is due to the operation of an active transport system, whereas the linear component is due to K' transport through a channel 16,171. In the first case, K' transport takes place against the electrochemical gradient for K'. The energy for the carrier mediated K ' uptake is provided by the electrochemical proton gradient generated at the plasmalemma by the operation of the proton pump [141. In the second case, the transport of cesium through K' channels is diffusive, the electrochemical gradient for cesium being the driving force for Cs' uptake. In R. fluitans thalli submitted to K ' deficiency, a high affinity transport system for K', that exhibits saturation kinetic, has been recently discovered [24].Such a system could be the responsible for Cs' uptake in this species when submitted to K' deficiency. As has been suggested for Arabidopsis thaliana [14], the carrier system used for Cs' uptake would be proton cotransport but Na' could be also used as driving ion for Cs' uptake, as it has been recently described for K' uptake in Cham australis 1151 or in Nitella translucens Il61. The effect of external K' concentration on 137Cs+uptake in K' sufficient plants, the effect of TEA, and the relationship between CF and the electrochemical driving force for Cs', point out that the linear Cs' uptake kinetic observed in R. fluitans is due to the operation of K' channels. These channels have been characterized for a number of plant cells [171, in particular Nitella [20] and Vicia guard cells [211.K' channels in Nitella [201 and Vicia guard cells [21] exhibit a permeability sequence for monovalent cations, K' > Rb' > NHt > Na' 2 Li' > Cs' > TEA' = Choline, but different species could have different permeability sequence [22,231. The carrier mediated transport system for K' seems to be able to transport others monovalent cations as Cs' [24] but a detailed sequence of transport preferences still needs to be determined. Since both mechanisms were originally developed for K' transport, the most important environmental variable influencing Cs' uptake in R. fluitans should be the external K' concentration, but some other variables influencing channel or carrier operation as Ca", pH and temperature have to be taken into account. 5. ACKNOWLEDGEMENTS

The authors are very grateful to Professor Hubert Felle (Justus von Liebig Universitat, Giessen) for the supply of Rzccia fluitans. We also thank Dr. J a n

336

Wauters the critical reading of the manuscript. This work has been supported by Nuclear Fission Safety Program, CEC contract no. F13P-CT92-0029,and by grant no. PB91-0962 of the Spanish Directorate for Science and Technology (DGICYT). 7. REFERENCES 1. Williams, L.G. and H.B. Swanson, 1958. Concentration of cesium-137 by algae. Science, 127: 187-188. 2. King, S.F., 1964. Uptake and transfer of cesium-137 by Chlamydomonas, Daphnia and bluegill fingerlings. Ecology 45(2):852-859. 3. Gil Corisco, J.A. and M.C. Vaz Carreiro, 1990. l h d e experimentale sur l'accumulation et la retention du 134Cspar une microalgue planctonique, Selenastrum capricornutum Printz. Rev. Sci. L'Eau, 3: 457468. 4. Sombre, L., 1987. Contribution a l'etude du transfert du radiocbsium (134Cset 13'Cs) dans une chaine alimentaire d'eau douce simplifiee: eau-algue verte (Scenedesmus ob1iquus)-mollusque filtreur (Dreissena polymorpha). These de 3e cycle en lhologie (Radiohydrobiologie), Universitk de Provence, 146 pp. 5. Lambrechts, A., Essai de modelisation du transfert du cesium-137 dans les compartiments d'un bcosyst&med'eau douce simplifik. Rapport CEA-R-5268,181 pp. 6. Maathuis, F.J.M. and D. Sanders, 1992. Plant membrane transport. Current Opin. Cell Biol., 4: 661-669. 7. Serrano, R., 1989. Structure and function of plasma membrane ATPase. Annu. Rev. Plant Physiol., 400: 61-94. 8. McClure, P.R., L.V. Kochian, R.M. Spanswick and J.E Shaff, 1990. Evidence for cotransport of nitrate and protons in maize roots. Plant Physiol., 93: 290-294. 9. Sakano, K., Y. Yazaki and T. Mimura, 1992. Cytoplasmic acidification induced by inorganic phosphate uptake in suspension cultured Catharanthus roseus cells. Plant Physiol., 99: 672-680. 10. Lass, B. and C.I. Ullrich-Eberius, 1984. Evidence for protodsulfate cotransport and its kinetics in Lemna gibba G1. Planta, 161: 53-60. 11. Felle, H., 1981. Stereospecificity and electrogenicity of amino acid transport in Riccia fluitans. Planta, 152: 505-512. 12. Felle, H., 1981. A Study of the Current-Voltage relationships of electrogenic active and passive membrane elements in Riccia fluitans. Biochim. Biophys. Acta, 646: 151-160. 13. Kochian L.V. and W.J.Lucas, 1982. Potassium transport in corn roots. Plant Physiol., 70: 1723-1731. 14. Maathuis, F.J.M.and D. Sanders, 1993. Energization of potassium uptake in Arabidopsis thaliana. Planta, 191: 302-307. 15. Smith, F.A. and N.A. Walker, 1989. Transport of potassium in Chara australis: I. A symport with sodium. J. Membr. Biol., 108: 125-137. 16. Walker, N.A. and D. Sanders, 1991. Sodium-coupled solute transport in charophyte algae: A general mechanism for transport energization in plant cells? Planta, 185: 443445. 17. Bentrup, F.W., 1990. Potassium ion channels in the plasmalemma. Physiologia Plantarum, 79: 705-711.

337 18. Epstein, E., D.W. Rains and O.E. Elzam, 1963. Resolution of dual mechanisms of potassium absorption by barley roots. Proc. Natl. Acad. Sci. USA, 49: 684-692. 19. Fernhndez, J.A. and M.J. Garcia-Sanchez, 1994. Photosynthetic induction of dual phosphate uptake kinetics in Porphyra umbilicalis. Physiologia Plantarum, 91: 581-586. 20. Sokolik, A.I. and V.M. Yurin, 1986. Potassium channels in plasmalemma ofNiteZZa cells at rest. J. Membr. Biol., 89: 9-22. 21. Schroeder, J.I., 1988. K+-transport properties of K+-channelsin the plasmamembrane of Vicia faba guard cells. J. Gen. Physiol., 92: 667-683. 22. Tester, M., 1988. Blockade of potassium channels in the plasmalemma of Chara corallina by tetraethylammonium, Ba+,Na+ and Cs+. J. Membr. Biol., 105: 77-85. 23. Tester, M., 1988. Potassium channels in the plasmalemma of Chara corallina are milti-ion pores: voltage dependent blockage by Cs+ and anomalous permeabilities. J. Membr. Biol., 105: 87-94. 24. Maathuis, F.J.M., D. Verlin, F.A. Smith, D. Sanders, J.A. Fernandez and N.A. Walker, 1996. The physiological relevance of Na+-coupled K+-transport. Plant Physiol., 112: 1609-1616.

Freshwuier u d Esiuurine Rudioecoloky

S>d by 0. &*met ct d. 0 1997 Elsevier Science B.V.All rights reserved

339

Contamination of fish with 137Cs in Kiev reservoir and old river bed of Pripyat near Chernobyl R.H. Hadderingha, G.H.F.M. van Aerssena, I.N. Ryabovb* A.O. Koulikovb and N. Belova‘ ‘KEMA, Environmental Services, P.O. Box 9035, 6800 ET Arnhem, The Netherlands bInstitute of Evolutionary Morphology and Ecology of Animals, Leninsky prospect 33, Moscow 11 7071, Russia cMoscow University, Faculty of Biology, Department of Ichthyology, Kosinskaja str. 28-1-135,Moscow 111538, Russia

ABSTRACT In 1992 a project was started on contamination of fish with I3’Cs in an area near Chernobyl. This study was undertaken by order of the Commission of the European Communities and the Dutch Electricity Supply Companies. The objectives of the study are to determine the relation of the concentration of 137Csbetween fish and their food and to determine relations between the 137Csconcentration and individual fish size (“sizeeffect”). This paper gives the results of samples of water, fish, zooplankton and invertebrates collected in 1992 in the northern part of Kiev Reservoir and in an old river bed of the Pripyat river. Six fish species with different food preferences were selected for the study. The 137Csconcentration was about 5 times higher in predatory fish (perch) than in the other species (non-predatory). Perch and pike showed a size effect the 137Csconcentration increases with the weight of the fish. This phenomenon was not present in the other species. Concentrations in fish from Kiev Reservoir are higher than in the old river bed. Possible reasons for the difference in the concentration of 137Cs between predatory and non-predatory fish and for the size effect are discussed. 1. INTRODUCTION

In 1991 the Experimental Collaboration Projects (ECPs) were started by the CEC in collaboration with Russia, Ukraine and Belarus. The behaviour and transport of radionuclides from the Chernobyl nuclear power station are studied in terrestrial and aquatic systems. The general aim is to develop countermeasures to prevent further distribution of radioactive material.

340

In ECP-3 the mechanisms are studied of the transport of radionuclides from terrestrial towards aquatic systems. One project is concerned with investigations on the contamination of 137Cs in fish. The objectives of this project are: - to determine the relation of the concentration of 137Csbetween fish and their food for different fish species - t o determine relations between the 137Csconcentration and individual fish size (“size effect”) This paper presents the results of measurements in water, fish, zooplankton and invertebrates samples collected in May 1992 in the northern part Kiev Reservoir and in an old arm of the Pripyat river. The followingfish species were selected for this study: bream (Abramis brama), silver bream (Blicca bjoerkna), roach (Rutilus rutilus), tench (Tinca tinca), rudd (Scardinius erythrophthalmus), perch (Perca fluuiatilis), ruffe (Gymnocephalus cernua) and pike (Esox Zucius).Bream, silver bream, roach and ruffe are obviously pronounced benthophagous. Tench has a wide spectrum of feeding and uses faunal and floral alimental objects; rudd feeds preferably aquatic vegetation whereas perch and pike are predatory species. These species belong to the common ecological group of phytophilous fishes whose spawning and development are closely linked to aquatic vegetation. 2. STUDY AREA

Morphometric and hydrological aspects Kiev Reservoir is an artificial lake north of Kiev (Fig. 1). The reservoir was filled by the rivers Dnieper and Pripyat during the period 1964-1966. The water of the reservoir is used for drinking water and for electricity production by hydropower. Kiev Reservoir has a length of 110 km,a surface area of 900 km2and an average depth of 4.5m. A great part of the reservoir is very shallow with a depth below 2 m. The volume is 3.7~10’m3. The average water inflow from the rivers Dnieper and Pripyat is 960 m3 s-’. The turnover time of the reservoir is 1.5month. The water is slightly eutrophic.

Chemical compounds of the water In November 1992 water samples from Kiev Reservoir and from the old arm of the Pripyat river were taken for analysis of the major chemical compounds. The analysis was carried out by the Institute of Freshwater Ecology in Ambleside, England. The results are presented in Table 1.

Biotic data Kiev Reservoir has a dense vegetation of waterplants and helophytes. About 32% of the reservoir surface area is overgrown with vegetation. The total biomass of the vegetation amounts 40,000tons air-dry weight [1,21.

341 (Dnieper

river

f

pond

river

-

I

0

I

5

I

10 km

Teterev river

Fig. 1. Map with the Dnieper reservoirs between the confluence of the rivers Dnieper and Pripyat in the north and the Black Sea in the south, the Chernobyl NPP and the location of sampling stations in the northern part of Kiev Reservoir. P: Old arm of the Pripyat river; S : Kiev Reservoir near Strakholesye.

A total number of about 50 fish species was encountered in Kiev Reservoir, the inflowing rivers and the cooling pond of the Chernobyl NPP [31 by collaborators of the Integrated Radioecological Expedition of Russian Academy of Sciences during the years 1986-1992. Kiev Reservoir has a commercial fishery with an average landing of 1200 tons fish per year for the period 1980-1991 (see Fig. 2). No significant changes are found after the Chernobyl accident in 1986. The most abundant species in the catch are bream (29%),silver bream (24%) and roach (19%).The catch of predatory fish was 1.5%for perch and 8% for pike. Contamination after the accident

After the accident with the NPP in 1986, the concentration of 137Cs was measured frequently in the Dnieper reservoirs by the Ukrainian Hydrometeorological Institute in Kiev [41. Yearly average values of 137Csin the water of Kiev Reservoir (Fig. 3) show a steady decrease. The total concentration decreases

342 TABLE 1 Chemical composition of water samples fmm Kiev reservoir and the old arm of the Pripyat river, 11-15 November 1992 Parameter

Kiev Reservoir

Calcium (Cat) mgh Magnesium (Mgt )mgA Sodium (Na9 mgA Potassium (Kt)mgh Chloride (C1-1 mgA Sulphate (SO{-)mgA Nitrate "03-N) mg/l Ammonia (NH4-N) mgA Silica (SiOz)mgA Alkalinity (HC03) mEh Phosphorus mgA (soluble reactive P) Phosphorus mgA (total dissolved P)

Pripyat river

34 8.3 14 3.1 20 25 1.3

34 7.5 13 3.4 21 35 0.8

1.9 1982 16 28

8.5 1835 19 42

0.05

0.07

2000 1800

a

*

1600 1400

L Q)

1200

c

1000

Q

0

c

.-0 L

E

800 600

400

200

0 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991

1

1

2

Fig. 2. Commercial catch records for 1980-1991 in Kiev Reservoir. 1:All species; 2: bream, silver bream, roach, tench and perch. Data are consolidated statistics of agencies of the Ukrainian Ministry of Agriculture (Fisheries and Water Industries) submitted by M.D. Lomakin (Ecopolis Co. Ltd.) as part of ECP3 study.

343

0.90 1r

, 0.80 , \

\,

0.70 0.60

0.50 0.40 0.30

0.20 0.10 0.00 1986 --A-

1987

total

1988 +

1989

dissolved

1990

1991

-asuspended

Fig. 3. Concentration of '37Csin water of Kiev Reservoir during 1986-1991 [4].

from 0.9 Bq 1-' in 1986 to about 0.15Bq 1-' in 1991.The average 137Cscontent of the reservoir sediment was 90 kBq m-' in August-October 1987. Published data on contamination of biota in Kiev Reservoir and Pripyat river are scarce. Kuz'menko [51reports the following 137Cs concentrations for different biota in 1987(in Bq kg-' wet weight) for the northern part of Kiev Reservoir: filamentous algae (11841,Typha angustifolia (701,gammarids (111)'crayfish (518)'Dreissena bugensis (125)and pike (629).Volkova [61 mentions the following concentrations, in Bq kg-' wet weight, for bream and pike-perch from Kiev Reservoir: Bream Pike-perch

1986 960f400 220k100

1987 480f160 590f170

1988 440f100 1040f360

1989 370+80 440f150

The sampling locations of these fish samples are not given by these authors. Therefore interpretation of these data is difficult as the concentration in biota will depend strongly from the location in such a great area as Kiev Reservoir.

344

Description of sampling stations

The locations of the sampling areas are indicated in Fig. 1.One area is situated in the northern part of Kiev Reservoir near Strakholesye. Within this area, sampling was carried out at 3 stations at distances of 0.3,0.7 and 1.2 km from the shore. The average water depth is about 1 m, the sediment consists of clayhilt with an amount of 13'Cs of 40-200 kBq ma (measurements Voitsekhovich, 1990, pers. comm.). This area has a dense vegetation of submerged water plants, water plants with floating leaves and reeds. This area is used by several fish species, especially cyprinids, for spawning in the spring. The second area is an old arm of the Pripyat river just upstream from the inflow into Kiev Reservoir. The maximum depth is about 9 m. The sediment is clay with a 137Cscontent of 200-1000 kBq 137Csm-' (measurements Voitsekhovich, 1990, pers. comm.). The shores of this area have dense vegetations of submerged water plants and reeds. Sampling was carried out in the river arm itself and also in a shallow area at about 500 m from the old river arm. 3. METHODS

Fish was collected with gill nets (stretched mesh 8-12 cm), a trawl net (stretched mesh in the cod end 20 mm) and with a rod. The length of all individuals was measured to the nearest mm and the weight to the nearest gram. For each species the individuals were divided into 2 to 5 agehengthclasses depending on the available number of fishes. A part of the perch was divided in groups based on age by examination of opercular bones. Each sample, consisting of whole fishes (intestines included) was ground in a cutter. About 200 g fresh material was dried in a oven at 105°C. For identification of the consumed food, stomach contents of several fish were preserved. Plankton samples have been collected in Kiev reservoir near Strakholesye. The samples were collected with a conical plankton net with a mesh varying from 250 mm (first 4.5 m) to 80 mm (last 0.5 m). Molluscs were collected in the old Pripyat arm with the trawl net. In the reservoir molluscs (Viuiparus contectus) were collected by hand from the reed stems. The lengths were measured and the molluscs were pooled in one sample per station. The flesh was separated from the shells and dried in the same way as the fish. Water was collected by filling buckets at the water surface. From each station 3-4 1 water was concentrated by evaporation to about 100 ml. Cesium-137 concentration was measured in the KEMA laboratories with a hyperpure Ge ?detector (Canberra), continuous cooled at -180°C. The samples were measured in 0.2 1 Marinelli beakers during 8 h. The concentration of the radionuclides was expressed as Bq kg-' dry weight. This seems to be more reliable than on a basis ofwet weight, as the water content in the samples is not the same.

345

4. RESULTS AND DISCUSSION

Water

The total concentration of 137Cs in Strakholesye on the 3 sampling points had the same value: 0.183 Bq 1-'. So the concentration seems to be extremely uniform in this area. In the old arm of the Pripyat the mean concentration, 0.085Bq l-', is about half in comparison with Strakholesye. This difference corresponds with the lower concentration in fish from this location. Zooplankton

The zooplankton, collected near Strakholesye in July 1992, consisted of copepods (50%)and cladocerans (50%).The 137Csconcentration in the zooplankton sample (Table 2) had a relatively high concentration of 1190 Bq kg-' dry weight, which is much higher than in the molluscs. TABLE 2 137Csconcentration in Mollusca (May 1992) and zooplankton (July 1992) at sampling stations in the northern part of Kiev reservoir and in the old arm of the Pripyat river

Species

Station

Mean length (cm)fs.d.

Mean wet weight (g)

1 3 7 (Bs ~ ~ kg-1

Shell Kiev reservoir: Viviparus contectus Zooplankton

2 1

Pripyat Viviparus contectus Unio sp. Anodonta sp. Dreissena sp.

1 1 1 1

-

2* 8.5fl.O 11.4k0.9 2.1f0.3

dry weight) Tissue

4.9 1067

-

438 1190

4.5 54 125 1.8

87 67 143 22

298 129 126 145

*No standard deviation available.

Moll USCS The highest concentration of 137Cs (Table 2) has been found in the gastropod Viuipurus contectus and is about two times higher than in the Bivalvia. The concentration in tissue of the three Bivalvia species is of the same level: 126 Bq kg-' for Anodontu and 145 Bq kg-' for Dreissenu. The highest concentration in Viuipurus contectus (438 Bq kg-') was found near Strakholesye.

346

Fish Apart from the fish mentioned in the “Introduction”the following species were also caught: Gibe1 carp (Carassius auratus gibelio), saberfish (Pelecus cultratus), asp (Aspius aspius), pikeperch (Stizostedion lucioperca). The ratio between the wet and dry weight of the samples was calculated. The average ratio for all fish samples was 3.8, with a minimum ratio for silver bream (3.5) and a maximum for tench (4.2). The analysis of the stomach and intestine contents showed that the food composition is strongly depending on fish species. Dominant food items in perch were: Gammarus spec., insects and fish for individuals < 26 cm and fish and crayfish (Astacus Zeptodactylus) for individuals > 26 cm. Consumed fish species by perch were: roach, gobies (Gobiidae) and sticklebacks (Gasterosteidae). Tench had preference for molluscs and insect larvae. Bream ate chironomids and molluscs while silver bream had a very divers diet (fish roe, molluscs and Ephemeroptera larvae). Rudd differs from the other species by the high proportion of vegetation in the stomach. It must be realised that the composition of the consumed food will strongly depend on the density of the food items in the environment. This density will change with the season. Fish roe for example will only be present in spring, the main spawning time of the fish community in Kiev reservoir. In Table 3 a summary of the fish data is presented. The average 137Cs concentration in perch is much higher than in the other fish species. Lowest concentration is found in bream ,silver bream and rudd. In ruffe and tench the concentration is intermediate. For Kiev Reservoir the difference between perch and other species ranges from a factor 3 (tench) and 8 (silver bream). For the old arm of the Pripyat river this difference is between a factor 2 (ruffe) and 5 (rudd). All measurements are based on whole fishes (total body). Measurements of fish samples of November 1992 (perch and tench) showed that the concentration in muscle tissue is about two times higher than in the total fish. This has to be taken into account in relation to the consumption of fish. The relation between the 137Csconcentration and the fresh individual weight of the different fish species is given in Fig. 4. For perch the I3’Cs concentration clearly increases with the weight of the fish (‘‘size effect”).This is also the case for pike. For the other species the concentration of 137Csdoes not change with weight. This feature has been found both for the fish sampled near Strakholesye and in the Pripyat old arm. The lines in Fig. 4 are the least-squares regressions. The data of perch and pike give a relatively high correlation: perch (Kiev Reservoir) 0.90,perch (Pripyat) 0.81,pike (Kiev Reservoir)0.85, and pike (Pripyat) 0.82. For the other species the correlation is low with coefficients lower than 0.75. This means that the 13‘Cs concentration does not clearly increases with the fish weight.

347 TABLE 3 Number of samples, weight, length and 137Csconcentration of fish from Kiev reservoir and the old arm of the Pripyat river, 21-25 May 1992 Species

Kiev reservoir Perch Tench Rudd Bream Silver bream Pripyat Perch Ruffe Tench Rudd Roach Bream Silver bream

Range of average wet weight (g)

Range of average length (cm)

137Cs (Bq kg-' dry weight)

Min.

Max.

Min.

Max.

Mean

s.d.

12 7 5 7 8

20 470 212 166 187

724 1046 473 822 710

12 30 25 24 25

38 38 31 43 38

2571 864 446 388 329

890 117 59 98 25

14

38 36 896 326 47 17 16

662

14 14 38 28 16 12 12

36

1339 687 494 278 409 306 332

727

No. samples

1

3 2 3 6 4

-

1953 394 248 1216 456

-

45 30 27 48 33

-

68 70 17 58 51

Comparison between Kiev Reservoir and Pripyat river

In perch, pike and tench of Strakholesye (Kiev Reservoir) the concentration of 137Csis about two times higher than in the old river arm (Fig. 4). For bream and silver bream the concentration level at the two stations is more or less the same. The higher concentration of 137Csin water at Strakholesye (0.183 Bq 1-') in comparison with the Pripyat old arm (0.085 Bq 1-'1 will be the reason for this difference. Migration of fish to and from other areas might also influence the concentration levels. Difference Percidae I Esocidae and Cyprinidae

Between the Percidae I Esocidae and Cyprinidae we have found differences in two phenomena: (1)the concentration level of 137Csand (2) the size effect. Figure 5 illustrates these differences for Percidae and Cyprinidae at the two sampling locations. (1) Concentration level The carnivorous feeding habits of the perch and pike, and the high place in the food chain is often given as explanation for the relative high level of 137Csin

348 1200

200 0' 0

100

200

300

400

500

800

700

I

800

200

500

0

1000

1500

mean wet weight (g) + -

Strakholesye

+-

ZOO0

2500

1.:-

0 1 0

300

I

I

"

500

"

"

1 1 0

'

"

1000 1500 2000 2500 3000 3500 4000 4500 5000

n n

100

200

300

400

500

mean wet weight (g)

Pripyat

Fig. 4. Relation between the concentration of 137Cs in fish (total body) and the individual wet weight of the fish from Strakholesye and the old arm of the Pripyat river, 21-25 May 1992. The lines are the least squares regressions. The pike data are based on muscle tissue, wet weight.

these two species. This cannot be the only reason however. In small perch we found a much higher 13'Cs concentration than in cyprinids of the same or greater size. These small perch eat predominantly macroinvertebrates as do the cyprinids. So the type of food does not seem the main reason for the difference in Cs concentration. A second factor which might influence the release of Cs from the food is the pH level in the stomach or intestine. A low pH might facilitate the release of Cs from the food and subsequently the uptake of Cs in the tissue. Production of acid gastric fluids (HC1) occurs in most fishes with a stomach, in fishes without a stomach no HC1 is formed [7]. In percids it is known that HCl is

349 5000 c

c

,a

4ooo

6

3000

f

1,

/

Strakholesye

/'

+ +' /

1

I

I

/ '

*O0O

100 200 300 400 600 800 700 800 800 100011001200

0

.

perch

6

roach

0

ruffe bream

tench --I

0

I

//"200

400

800

800

1000 1200 1400 1600 1800 2000

mean wet weight (g)

mean wet weight (g)

+

1

0

rudd

sllv br

Fig. 5. Comparison of the '37Cs concentration in fish (total body) from Strakholesye and old arm Pripyat river, 21-25 May 1992. The lines are the least squares regressions.

produced in the stomach [81.Western and Jennings [91 mention that this acid is present in the stomach of Perca but not in the intestinal duct of the cyprinid genera Cyprinus, Rutilus and Gobio. In our samples we found in cyprinids (roach, tench, gibe1 carp) an average pH value of 7.3 f 0.3. In pike, perch, ruffe we found much lower pHs: 4.0 +_ 1.2,5.6and 3.9 k 0.7, respectively. The possible effect of the pH level has to be confirmed with laboratory experiments. A third factor might be the evacuation time of for food in the stomach or intestine. In perch and pike this time seems to be longer than for some cyprinids 171. The fourth factor might be the longer biological half life for predators. For perch a half-life of 200 days for Cs was found and 57-150 days for roach at 15°C [lo]. (2) Size effect The increase of the 137Csconcentration with fish weight has also been found in other studies. For perch this relation was found in Sweden [ l l ] , in the Netherlands [121, in Germany [131 and in the U.K. [141. One of the reasons might be the change of food composition with 1engtWweight: perch changes from plankton (juveniles) and macroinvertebrates (smaller individuals) to fish (greater individuals) while cyprinids take more or less the same food at different life stages. An other possible reason for the size effect is an increase of the biological half life with weight. Haskinen et al. 1101 found that the half time increased with age (=weight) for roach, but not for perch. This is in contradiction with our findings: size effect for perch but no size effect for roach. 5. CONCLUSIONS

The highest 137Cs concentration was found in predatory fish. In the bigger individuals the concentration is above the EEC-standard of 600 Bq kg-' fresh weight (= 2500 Bq kg-' dry weight). Tench has the highest concentration among

350

cyprinids. Differences in concentration between predatory and non-predatory fish might be caused by: - high Cs concentration in the food of predatory fish; - difference in release of Cs from fish to the water (biologicalhalf life); and - relative high uptake of Cs from the food under acid conditions in the stomach with perch, ruffe and pike. Concentrations in perch and tench from Kiev Reservoir are higher than in the old arm of the Pripyat river, probably caused by the higher contamination level in water, sediments and benthic fauna. Other species have the same level however. Migration of fish to and from other areas might also influence the concentration levels. The size effect in predatory fish might be caused by: - increase of biological half life with weight; and - change of food with size. It is recommended that the consumption of predatory fish from the northern part of Kiev reservoir be limited. Sport fishing for perch during the winter is very popular in this area. 6.ACKNOWLEDGEMENTS

The authors gratefully acknowledge the financial support of the Dutch Electricity Supply Companies and the Commission of the European Community, Ecopolis Co Ltd based in the Ivankov Region District of Kiev for general assistance, Gemba, Yaushkin and Rozhok for collecting the fish, Kiezenberg, Donk and Schuurman for measuring the samples and Dr. Lomakin for critical remarks on the manuscript. 6.REFERENCES 1. 2.

3. 4. 5.

6. 7.

Korelyakova, I.A., 1982.Vegetation of Dnjieper Reservoirs, Dissertation, Kishinev, p. 42. Voropayev, G.V. and Avokyan, A.B. (eds.), 1986.Reservoirs and their Influence on the Environment. Nauka, Moscow, p. 368. Ryabov, I.N., 1992.Effect of radioactive contamination of hydrobionta within the thirty-kilometer zone of Chernobyl NPP. Radiobiology, 32:662-667. Voitsekhovich, O.V.,1992.Contribution to Fourth Vamp Research coordination Meeting, Vienna, Austria, 2-6 March, 1992. Kuzmenko, M.I,1990.Radioecologicalinvestigatioins of Ukrainian waters. Hydrobiolog. J., 26:63-75. Volkova, E.N., 1990.Radioactive Contamination of Fish Fauna in the Dnieper Reservoirs after the Chernobyl Accident, Ukraine. Academy of Sciences, Kiev, pp. 1-25 (in Russian). F h g e , R. and Grove, D., 1979.Digestion. In: Fish Physiology, W.S.Hoar, W.S., D.J. Randall and J.R. Brett (eds.), Academic Press, London, pp. 161-260.

351 8. Nikolski, G.V., 1963. The Ecology of Fishes. Academic Press, London. 9. Western, J.R.H. and Jennings, J.B., 1970. Histochemical demonstration of hydrochloric acid in the gastrictubules of teleosts using a n in uiuo prussian blue technique. Comp. Biochem. Physiol., 35: 879-884. 10. Hasanen, E., Kolehmainen, S. and Miettinen, J.K., 1968. Biological half-times of Cs137and NaZ2in different fish species and their temperature dependence. In: Radiation Protection, Part I, W.S. Snyder et al. (eds.), Pergamon Press, New York, pp. 401-406. 11. Andersson, E., 1989. Incorporation of 137Csinto fishes and other organisms. In: The Radioecology of Natural and Artificial Radionuclides, W. Feldt (ed.), Proceedings of the XVth Regional Congress of IRPA, Visby, Gotland, Sweden, 10-14 September, 1989, pp. 312-317. 12. Hadderingh, R.H., 1989. Distribution of 137Csin the aquatic foodchain of the IJsselmeer after the Chernobyl accident. In: The Radioecology of Natural and Artificial Radionuclides. W. Feldt (ed.), Proceedings of the XVth Regional Congress of IRPA, Visby, Gotland, Sweden, 10-14 September, 1989, pp. 325-330. 13. Lindner, G., Pfeiffer, W., Robbins, J.A. and Recknagel, E., 1989. Long-lived Chernobyl radionuclides in lake Constance: Speciation, sedimentation and biological transfer. In: The Radioecology of Natural and Artificial Radionuclides. W. Feldt (ed.), Proceedings of the XVth Regional Congress of IRPA, Visby, Gotland, Sweden, 10-14 September, 1989, pp. 295400. 14. Elliot, J.M., Hilton, J., Rigg, E., Tullet, P.A., SwiR, D.J. and Leonard, D.R.P., 1992. Sources of variation in post-Chernobyl radiocaesium in fish from two Cumbrian lakes (north-west England). J. Appl. Ecol., 29: 108-119.

Freshwuter und Extuurine Rudic~eecodogy Edited by 0.Demnet et al. 0 1997 Elsevier Science B.V. All rights reserved

353

Trace metal transfers between water and sediment in a freshwater system. Influence of microbial activity F. Hambuckers-Berhina,A. Hambuckersband J. Remaclea aUniversity of Likge, Microbial Ecology, B22 Sart I'ilman, B-4000 Likge, Belgium bUniversity of Likge, Plant World Observatory, B77 Sart Tilman, B-4000 Likge, Belgium ABSTRACT The purpose of our work was to determine, in a freshwater batch system, the importance and the direction of trace metal transfers between sediment and water as influenced by bacterial activity. Sediment was incubated in Meuse water in different conditions. Net transfer occurred on an average from sediment to water for Co, Cs, Cr, Cu, Hg, La, Ni, Zn and from water to sediment for Bi, Cd, Pb, Sb, T1. Positive correlations between oxygen consumption and transfer of nine metals from sediment to water demonstrate the influence of bacterial activity. Correlations of the metal transfer either with water pH or with the variation of sediment weight a t the end of incubation led to suppose that the alteration of the chemical conditions also strongly influenced the transfers. It was confirmed by the comparison of chemical characteristics of the water and of the sediment a t the end of incubation in contrasted conditions. The uptake of 12 metals by a bacterial community isolated from the sediment was related to metal concentrations in the water. The specific transfer from the water to the bacterial biomass was appraised in the sediment incubation experiments. It allowed to compute the net metal transfer of 12 metals from the sediment to the water with significant bacterial activity. The comparison of these values with the transfers occurring a t 4"C, i.e. with reduced bacterial activity, demonstrated that the transfer of 11 metals from the sediment to the water is clearly enhanced by bacterial activity.

1. INTRODUCTION

Many observations suggest the hypothesis that microorganisms, and more precisely bacteria, play a key role within the cycling of trace metals or radionuclides in freshwater ecosystems. Bacterial biomass significantly contributes to the immobilisation of metals by 3 main processes: (1)biosorption, (2) bioaccumulation and (3) insolubilisation. These processes coexist but their relative importance depends on the conditions of the medium, particularly on the concentration of each metallic ion and on their chemical speciation.

364

(1)Biosorption concerns many modes of non active metal uptake by microbial biomass [ll. This physico-chemical mechanism is chiefly influenced by the biochemical characteristics of the cell envelops [2,51. It is observed on living or dead cells but also on fragmented cells [6]. (2) Bioaccumulation results from the cellular metabolism and for this reason is only observed on living cells. Toxic or non-essential metals enter the cell by substituting for the essential ions and by making use of their membrane carriers [71. Into the cell, metals are either quickly exported from the cell [8]or chemically neutralised by several types of intracytoplasmic compounds which synthesis is induced (metallothioneins, polyphosphates, etc.) or not (poly-p-hydroxybutyric acid, DNA, etc.) by the presence of the metal 191. (3) Insolubilisation of metals occurs by precipitation in the form of sulphides, carbonates or oxides at the cell surface or in the water column following the excretion of bacterial metabolic by-products [10,111. The pools of metals immobilised by bacterial biomass could be transferred to other parts of the ecosystem. On the one hand, to the water through (1) desorption of the biosorbed pool [12], (2) release of the bioaccumulated pool by the mechanism of efflux [81 and (3) biodegradation of the dead bacteria. On the other hand, the grazing of the bacterial biomass could transfer the metals up to higher trophic levels as observed in the bacterial loop constituting nutrient regeneration pathways [13]. Therefore, the bacterial biomass is a potential secondary source of metals for any other compartments of the freshwater ecosystems. In addition, bacteria are the main actors of the biodegradation of the organic matter. Their interactions with the released metals should be also considered. We summarise in a conceptual scheme (Fig. 1) the interactions of organic matter and bacteria [141 connected with the cycling of metallic ions or radionuclides which could be observed in the water column or in the pore water of the sediment (modified from [12]). The hydrolysis of the particular or polymeric organic matter (POM) by bacterial ectoenzymes produces the utilizable dissolved organic matter (UDOM), i.e. small molecules such as amino acids, organic acids, mono- and oligosaccharides that can be easily consumed by heterotrophic bacteria (bacterial organic matter, BOM). A part of POM, not or slowly assimilable, constitutes the refractory organic matter (ROM). The excreted matter of living organisms, the lysis of carcasses (including of dead bacteria) and the inputs of terrestrial material supply the pools of POM with organic macromolecules. When POM is hydrolysed into UDOM, the metals bound to POM should be released and transfer to the water or remained with UDOM. The consumption of UDOM and the growth of BOM should lead to the uptake, by BOM, of the metals bound to UDOM 1151 or in solution in the water. Bacterial yields evaluated in the Meuse river [161 show that 30% of consumed UDOM are anabolized and that 70% are catabolized with disappearance of organic matter. This necessary implies metal fluxes from UDOM to BOM or to the water. The

355

1 0

hlL I AL POOL

catabolism

0

M A I TLK POOL

+

M t IA L I RANSFER

-

MAIIIK

IKANSIIK

Fig. 1. Conceptual scheme of the interactions of bacteria and organic matter [14]connected with the metal cycling (modified from Ref. [121.ROM: refractory organic matter, POM: particulate or polymeric organic matter, UDOM utilisable dissolved organic matter, BOM: bacterial organic matter, PIM: particulate inorganic matter (see text).

density of BOM is difficult to assess in river ecosystems. However, it could be assumed that 30% of the primary production is consumed by planktonic bacteria [13]. In steady state, the bacterial density remains relatively unchanged. This is due to grazing which is of the same order of magnitude as bacterial growth rate (0.1 h-') 1161. An input of UDOM provokes a bacterial bloom followed by the restoration of the initial bacterial density aRer the activity of the predator populations [17]. However, predation of bacteria does not play the key role in every aquatic system. For example, in the Sambre river (Belgium), the bacterial density is mainly controlled by the supply of substrate [18].Therefore, the degradation of BOM as a result of grazing or lysis seems significant in the redistribution of trapped metals to water, to POM or to higher trophic levels. Finally, the bacterial activity acts on the chemical conditions (in particular on pH and Eh). For this reason, it could alter the solubility of the metals provoking chemical exchange between water and the particulate inorganic matter (PIM: defined as the inorganic part of the sediment and the suspended precipitates). The alteration of the water conditions could also influence all the metal transfers between the different pools of organic matter and water. Within the framework of the water pollution in freshwater ecosystems by metals and radionuclides, three sources must be distinguished: (1) the

356

atmospheric deposition, (2)the disposal of urban or industrial waste water and (3)the pool of elements trapped into the sediment. The purpose of our work was to determine for a batch system the importance and the direction of trace metal transfers between the sediment and water as influenced by bacterial activity. 2. EXPERIMENTAL

2.1, Effect of bacterial activity

Sediment collected from the Meuse river (Hastihe, Belgium) was incubated in sterile Meuse water (20g wet weight 1-'1 for 3 days. Three sources of variation at 3 levels (temperature: 4,15,26"C; shaking: no, 0.5per h, continuous; organic N enrichment: 0,100,200mg 1-'1 were combined with the intention of varying the microbial activity of the system. The levels of the factors were chosen by referring to field conditions. Fifteen experiments (each experiment was at least repeated twice) were carried out following the three factors experimental design of Box and Behnken [19].The advantage of those designs on complete factorial plans is the reduction of the number of experiments with a balanced combination of the factor levels. The oxygen consumption was recorded with an electrolytic respirometer (Voith-Sapromat). At the end of the incubation, the sediment (organic and inorganic, leaving and dead particles) was separated from the supernatant by centrifugation (12500g, 20 min, 4°C).We estimated the transfers of 13 trace metals (Bi, Cd, Co, Cu, Cr,Cs,Hg, La, Ni, Pb, Sb, T1, Zn) between the sediment and the water by the differences between the final and the initial concentrations of the supernatant. Trace metal concentrations were assessed by inductively coupled plasma-mass spectrometry (ICP-MS; Plasmaquad) with the addition of In at a final concentration of 50 pg 1-' as internal standard (the glassware was decontaminated with diluted HCl followed by several rinses with distilled de-ionised water). We also measured the final pH of the supernatant with a glass electrode and the ponderal variation of the sediment by the difference between the final and the initial amount of sediment added. The oxygen consumption was modelled as a function of the sources of variation by multiple regression. The factors (linear, quadratic or interaction 2 by 2)were chosen using a stepwise procedure among all the possible combinations [201.The correlations between the variables (oxygen consumption, ponderal variation of the sediment, water final pH, transfers of trace metals) were determined by the computing of the Pearson correlation coefficients. 2.2. Effect of shaking on some chemical parameters of the water and of the sediment

Sediment (20g wet weight 1-'1 was incubated in sterile Meuse water supply with bacto-peptone at a concentration of 1.25 g 1-' for 3 days at 26"C,with or

357

without shaking (5 repeats of both conditions). At the end of the incubation, the sediment was harvested by centrifugation. The supernatant was analysed for pH, for sulphides by iodometry [21] and for organic and inorganic carbon using a DC-180 Dohrmann carbon analyser. The sediment was examined for amount, for organic and inorganic carbon using a DC-180 Dohrmann carbon analyser fitted up with a Model 183boat sampler and for sulphides by distillation in acid condition followed by iodometry [211. The variations between the h a l and the initial values were compared by the Wilcoxon rank test 1201. Uptake of trace metals by the bacterial community of the sediment A bacterial community was isolated from the sediment of the Meuse river [ 121. Bacteria were incubated for 3 days in sterile Meuse water contaminated with the same metals added as chlorides (Cd, Co, Cu, Cr, Ni, Sb, Zn) or as nitrates (Bi, Cs, Hg, La, Pb, Tl) in a set of 25 experiments. The metal concentrations in the water were combined following the N = 20 experimental design of Plackett and Burman [22]. Such an experimental design allows to test a larger set of independent factors than the Box and Behnken designs [191 but only for linear responses. For each factors, the lower level corresponds to the metal concentration of our Meuse samples while the higher level was chosen closed to the highest value determined in a set of preliminary experiments in similar conditions to those used in Section 2.1 to test the effect of bacterial activity (up to 10 ppb for Cs, Cd, Sb, La, Hg, Tl, Pb, Bi, 100 ppb for Co, Cr, Cu, Zn and 500 ppb for Ni). The initial biomass of bacteria in the water (300 mg dw 1-I) was chosen according t o estimates of bacterial biomass in sediments analysed in the set of preliminary experiments. The others experimental conditions were the same as the median ones of the experiments described in Section 2.1: temperature of 15"C, intermittent shaking (5 min per 10 min), 626 mg l-'of bacto-peptone and 454 mg I-' of starch. At the end of incubation, bacteria were harvested by centrifugation (12500 g, 20 min, 4°C). The dry bacterial biomass was weighted and ashed following [231. The metal concentrations (excepted Hg) were assessed by ICP-MS as described above. The accumulation of metals in the bacterial biomass was analysed as a function of the concentration of the 13 metals in the water [241. Let X, the concentration of the metal i in the water, Y , the concentration of the metal j in the bacterial biomass and EY,, the main effect estimate of the concentration in the water of the metal i on the concentration in the bacterial biomass of the metal j :

E , , = (IY, at high X, / N * )- (CY,at low X, / N"*), with N* the number of experiments at high X,, and N** the number of experiments at low X,. The concentration proportionality factor is defined as:

PFY,,x~ = EYJ 1AX with AXt the difference among the highest and lowest levels ofX,.

358

When the same metal is considered in the water and in the biomass (i.e. i = j in PFyA), the concentration proportionality factor could be compared with the concentration factor (ratio between concentrations in biomass and liquid phase). The response error (SY,J,)is estimated by computing the standard deviation on the central points. The signification levels of the main effects are determined by assuming that E~J/(S~J, follows a t(Ne+N-J/2-1 distribution of Student.

m)

3. RESULTS AND DISCUSSION

3.1. Control of bacterial activity by culture conditions

The objective of using an experimental design was to avoid bacterial activity to be a collinear factor of one particular limiting factor. In cme of such a collinearity, it would not be possible to determine whether the metal transfers were controlled either by the factor or by the bacterial activity. Bacterial activity is actually influenced by the sources of variation as shown by the model of the oxygen consumption vs the sources of variation (Table 1). Moreover, the model shows that the microbial activity highly depended (signification level of the model is 0.0001) on the interaction of the chosen factors. TABLE 1 Regression model (see text) relating the oxygen consumption (mg kg-' [sediment D.W.] d-') to temperature ("C), shaking (0 to 1)and organic N enrichment (mg 1-'1: Fisher's F and its signification level (SL); R2;parameter estimates of the model with signification level (SL). Variable

Parameter estimate

SL

Intercept Temperature Shaking Temperature x shaking Shaking x N enrichment

-8846 982 12000 -1051 29

0.0052 0.0001 0.0250 0.0006 0.0771

F(4,34)= 10.28;SL = 0.0001;R2= 0.55.

It is likely that the sources of variation provoked, according to their combinations, not only the development of aerobic, but also of anaerobic germs known to have a 10 times as low mass yield [25]. The activity of both types of germs alters the medium composition in contrasted ways. It is exemplified by the comparison of chemical parameters of the water and of the sediment at the end of the incubation at 26"C, with or without shaking (Table 2). In the water, the pH, the organic and inorganic carbon concentrations and the sulphide concen-

359 TABLE 2 Chemical characteristicsof water and sediment after incubation (26"C,bacto-pectone:1250 mg I-') with or without shaking: initial values (I), mean variations (no shaking: NS, shaking: S ) and signification level of the Wilcoxon test (SL)

I

NS

S

SL

Water PH Inorganic C (mg 1-l) Organic C (mg1-'1 Sulphides (mg 1-'1

7.8 31 406 <0.83

-1.0 +22 -19 +1.66

+1.0 -16 -329 0

0.0092 0.0122 0.0122 0.0636

Sediment Amount (g dw 1-l) Inorganic C (mg I-') Organic C (mg I-') Sulphides (mg I-')

13.7 12328 32847 23

-0.020 -476 +4257 +23

+0.18 +198 +7008 -23

0.0153 0.0947 0.5309 0.0593

tration evolved in opposite ways as a function of shaking. The same shift was observed for the concentrations in the sediment as well as for the sediment weight change. In anoxic conditions, the bacterial activity does not result in a deep oxidation of organic carbon but rather in fermentations with the production of organic acids. This explains the lower reduction of the organic carbon concentration in the water and the decrease of the pH value when the sediment was incubated without shaking. The lower pH is probably the cause of carbonate solubilisation from the sediment producing the decrease of inorganic carbon concentration in the sediment. The shortage of oxygen also leads to the reduction of sulphur, resulting in the accumulation of sulphides. By contrast, when shaking, the sharp decrease of the organic carbon concentration in the water and the disappearance of sulphides from the sediment allows to conclude that those materials were oxidised to a great extent. The rise of pH, when shaking, could be provoked by the production of ammonium as a result of the consumption of the added bacto-peptone. The above considerations could explain the ponderal variation of the sediment in the course of incubation. In aerobic conditions by contrast with anaerobic ones, we suppose (1) that the production of bacterial biomass from the added substrate and from the sediment was larger than the consumption of organic carbon from the sediment, the bacterial mass yield being high (-0.35 [25]) and (2) that the disappearance of sulphides was balanced or more by the precipitation of carbonates. On the one hand, carbonate has a higher molecular weight (mw: 60) than sulphide (mw: 32) and a large amount of carbonate precipitates can be induced by CO, coming from the microbial respiration or from the atmosphere [lo].

360

3.2. Metal transfers between sediment and water

Table 3 summarises the results of the 15 experiments and shows the effect of microbial activity on the metal transfers between water and sediment. Oxygen consumption sharply varied between 0 and 30.3 g. kg-' sediment d.w. d-'; the final weight of the sediment fluctuated between 93% and 142% of the initial amount (variation between -2.3%. d-' and +14%. d?; the final pH increased or decreased by comparison with its initial value of 8.2. The centrifugation allows to separate PIM, BOM, POM and the insoluble fraction of ROM, from the supernatant constituted of water containing UDOM and the soluble fraction of ROM.At the end of incubation in conditions where bacterial activity was significant, the concentration of UDOM was probably low because of microbial consumption and the associated pools of metals were assumed to be labile. The soluble ROM concentration and its pools of metals should remain constant during the incubations, excepted in the course of experiments in which fermentations occur. For these reasons, the difference of metal concentration in the supernatant between the final and the initial values, as an estimation of the transfer between water and sediment, has to be considered with caution: the concentrations of UDOM and soluble ROM as well TABLE 3 Sediment incubation experiments. Mean values (n = 39)after 3 days (Mean), standard deviation (SD),minimum (Min) and maximum (Max)value: total oxygen consumption ( 0 2 ; g kg' [sediment D.W.) d-l), final pH (initial pH: 8.21,difference between final and initial amount of sediment (Asediment; % d-i), net metai transfer between sediment and water (see text; pg kg-' [sediment D.W.1 d-l. ~~~

Mean 0 2

Final pH ASediment Bi Cd co

Cr

cs cu Hg

La Ni Pb Sb TI Zn

5.9 7.8 3.7 -1.5 -17.2 86.0 134.2 1.3 328.0 11.7 2.4 530.8 -34.0 -202.3 -0.3 7625.6

SD

6.7 0.7 3.7 2.2 43.0 162.0 320.6 2.3 628.3 22.3 3.3 960.8 75.0 1.7 23242.8 906.5

Min

0 6.0 -2.3 -5.9 -86.6 -270.0 -593.3 -3.6 -128.5 -33.9 -3.1 -423.5 -181.9 -1062.1 -3.5 -341.3

Max

30.3 8.9 14.0 4.2 96.9 685.7 942.1 5.7 2610.5 61.8 11.0 3889.8 149.7 333.1 6.5 122896.1

361 800

-

8

600 -

F

3

400

; "i 1

rn

L

8

*0° 0

'm Y -200 -

4

-400 -

T

'm x m

6 -

-------

rn

8

d

8

; 8

I

I

I

8

I

I

8

I

1

8

-4-

as their pools of metals were not separated from the water and could significantly vary in some circumstances. Bearing this remark in mind, the net transfer of metals (Table 3) occurred on an average from water to the sediment for Bi, Cd, Pb, Sb, T1 and from the sediment to water for Co,Cs,Cr,Cu,Hg, La, Ni and Zn. The minimal negative values of the latter metals indicate that they could be also transferred from water to the sediment. Stimulation of microbial activity of lake sediment is reported to increase 13'Cs transfer from sediment to water [26]. Our result for stable Cs confirmed this observation. At the signification level of 0.1, the transfers of Bi,Co,Cr,Cs,Cu,Hg,La, Sb and T1 were positively correlated with the oxygen consumption (Table 4).

362 TABLE 4 Sediment incubation experiments. Correlation between oxygen consumption (021, final pH of the water (pH), difference between final and initial amount of sediment (AS) and metal transfers: Pearson correlationcoefficient (first line), signification level (second line), significant value at level

0.100(*I.

Hg

Bi

Cd

co

Cr

cs

cu

0.28* 0.10 -0.18 0.29

0.07 0.70 0.03 0.84

0.41* 0.02 0.30* 0.08

0.46* 0.01 0.43* 0.01

0.51* 0.002 0.27 0.12

0.38* 0.02 0.43* 0.01

-0.11 0.51

0.13 0.42

0.15 0.39

0.34* 0.04

0.15 0.38

0.16 0.35

-0.20 0.22

-0.29* 0.08

Ni

Pb

Sb

TI

Zn

0 2

PH

AS

-0.20 0.26

0.10 0.57

-0.17 0.34 -0.08 0.66

0.30* 0.06 0.16 0.34

La

0.47* 0.003 0.06 0.72

0.37* 0.02

0.58* 0.00

0.21 0.20

1.00 0.00

0.51* 0.001

0.06 0.72

-0.11 0.52

0.06 0.71

0.30* 0.07

0.06 0.70

0.51 0.001

1.00 0.00

0.56

0.06 0.73

-0.10 0.53

-0.18 0.29

0.06 0.72

0.56* 0.00

1.00 0.00

0.06 0.71

0.00

Examples of data distributions are given in Fig. 2 for Co and in Fig. 3 for Cs. The final pH is positively correlated with the oxygen consumption as well as with the transfers of Co, Cr, Cu and T1. The ponderal variation of the sediment is positively correlated with the final pH and the transfer of Cr and negatively correlated with the transfer of La. The positive correlation between oxygen consumption and the transfers of metals suggests the hypothesis that bacterial activity is implicated in the metal release from the sediment. However, all the concerned metal could also show transfers from the water to the sediment. If we suppose that the development of the bacterial biomass releases the metals by hydrolysis of POM and UDOM, two mechanisms could explain the transfers from the water to sediment. Firstly, the released metals could be taken up by the growing bacterial biomass. Secondly, the alteration of the chemical conditions could induce the precipitation of the released metals. The distribution of the final pH values as a function of oxygen consumption (Fig. 4) leads to doubt of an actual correlation between both these variables. It is the probable consequence of particular combinations of culture conditions

363 lo 1

5

5

0

10

15

20

25

35

30

oxygen consumption -1

9.kg

sejlmrn d w .

day''

Fig. 4. Relationship between oxygen consumption and final pH of the supernatant in the experiments of sediment incubation (Pearsoncorrelation coefficient: 0.51; signification level 0.0009).

6 5

1

'

1

~

l

'

l

~

1

'

1

'

l

'

:

'

I

'

I

that either stimulate anaerobic activities or that are not propitious to any bacterial activity. In these cases, there should be no oxygen consumption, but either deep alteration of the pH or little pH change. It is exemplified in Fig. 4 by the group of points alongside the pH axis corresponds to an oxygen consumption lower than 100 mg 1-I. On the other hand, the comparison of the chemical changes after incubation at 26°C with or without shaking (Table 2) showed a decrease of pH in parallel with the production of sulphides. The pH decrease would enhance the solubilisation of most of the studied metals while the sulphides would more probably provoke precipitation of the metals. This could highlight the positive correlations between final pH and metal transfers (Table 4) and between final pH and ponderal variation of the sediment (Fig. 5). In

TI Zn

Ni Pb Sb

La

cu

cs

Bi Cd co Cr

2.73* -0.16 -0.09 -15.72* -0.03 8.63* 0.36 1.84 6.63* 0.04 0.01 42.38*

Bi

47.30*

0.06*

4.67* 0.12*

4.04*

0.14 2.59* -0.02 -13.55* 0.04 6.75* -0.56

Cd

-0.03 0.27 -0.35* -0.01 0.00 3.93*

0.88*

0.00

0.02 0.00 0.31* 0.98*

co

5.38*

0.00

-0.87* 0.01 -0.02 0.58 -0.01

o.oo*

-0.02 0.01 0.01 0.95*

Cr

44.31*

0.05*

0.23* -8.52* 0.63 1.53 5.58* -0.06

8.08*

-0.52 0.69 -0.10

cs

4.57*

o.oo*

0.01 -0.10 0.03 0.70* 0.00 1.11* -0.04 0.47* 0.38* 0.27*

cu

0.10 0.02 0.23 4.91* -0.02 8.85* -0.03 2.22 412* -0.02 -0.02 -44.01*

Hg

0.47 -1.02 -0.28 11.17* 0.02 -9.05 2.03* -1.43 4.22 0.11* -0.05 -39.54

La

-0.01 -0.01 -0.60

-0.08

0.02* 0.01 0.00 -0.32 0.00 0.17* -0.01 0.35*

Ni

-0.69 -0.13 -0.14 -10.79 0.01 -8.17 -0.02 3.19* 6.27* 0.10 0.007* 53.25*

Pb

-7.52 -0.07 3.13 3.81* 0.22* 0.02 -0.60

-0.01

-0.14 25.42*

0.85

-0.33

Sb

zn -0.01 0.21 0.10 0.59 0.01 0.29 0.91* -11.56 -0.01 -0.02 0.97* 9.53* 0.00 0.41 2.05 -0.46 3.80* 0.51* 0.001 0.00 0.26* -0.01 53.25* 32.84*

Tl

Immobilisation of metals by the bacterial biomass. Relationship between metal content in the water and metal content in the bacterial biomass: concentration proportionality (see text). Significantvalues, at signification level 0.1 are labelled with *.

TABLE 5

Ip

Q,

0

365

addition, these correlations prove that the transfers of material between water and sediment are deeply influenced by the chemical variations in the course of incubation. The ability of metal uptake by the bacterial biomass was determined by cultivating bacteria in the presence in the water of all the 13 metals. Although most of the metals occurred as traces in the water, the concentration proportionality factors, P F T , of each metal in the biomass and of the same metal in the water (Table 5 ) is always significant and positive. Moreover, most of the other significant PFYJ, are positive, which means that the uptake of one metal is broadly reinforced by the presence of the other metals in solution, Antagonistic effects are often reported but mainly occurred at higher concentrations [27-281. Therefore, the results suggest that much of the studied trace metals in the observed ranges of concentrations could be considered as oligoelements for the bacteria because they are at infra-toxic levels and could supply lacking limiting metals (e.g. Cd and Co substitution for Zn [291). Table 6 gives an appraisal of total metal transfer from the sediment to the water in the presence of bacterial activity, i.e. the transfer from PIM, POM, insoluble ROM to the water. It is the s u m of the net transfer from sediment to water (mean transfer from PIM, POM, insoluble ROM and BOM to supernatant in the experiments of sediment incubation) with the transfer between water and BOM (average metal concentration in bacterial biomass in the TABLE 6 Estimation of metal transfer (pg kg-' [sediment D.W.1 d-'. Mean from water to BOM, net from sediment to water with bacterial activity (mean transfer from sediment to supernatant), total from sediment to water with bacterial activity (mean transfer from sediment to supernatant plus transfer from water to BOM), net from sediment to water without bacterial activity (mean transfer from sediment to supernatant at 4°C).

Bi Cd co Cr cs cu La Ni Pb Sb T1 Zn

Mean from water to BOM (1)

Total from sediment to Net from sediment water: with bacterial to water: with bacterial activity (2) activity (1+ 2)

130.8 300.0 138.7 2284.5 15.4 838.4 122.8 1146.1 530.7 31.0 23.1 4938.3

-1.5 -17.2 86.0 134.2 1.3 328.0 2.4 530.8 -34.0 -202.3 -0.3 7625.6

129.3 282.8 224.7 2418.7 16.7 1166.4 125.2 1676.9 496.7 -171.3 22.8 12563.9

Net from sediment to water: without bacterial activity

-1.3 21.9 -56.6 295.1 0 195.4 -0.7 1234.6 -3.5 -591.5 0.9 -135.4

366

experiments of metal immobilisation multiplied by the average bacterial biomass). It could be compared with the transfer (net total) from sediment to water at 4"C, i.e. with low bacterial activity. It is important to note that the total transfer is positive, excepted for Sb, and always higher than the net transfer at 4°C. This confirms that the bacterial activity is an effective mechanism of recycling the metal trapped in the sediment and that BOM is a significant trapping compartment of metals in the freshwater. The fate of the trace metals in the freshwater will therefore largely depend on bacteria: on their ability to release the metal accumulated in the sediment, on the immobilisation potentiality of BOM and on the efficiency of the microbial loop to prevent sedimentation of BOM with the trapped metals.

-

4. CONCLUSIONS

The results demonstrate that the bacteria probably intervene in a significant manner on the transfers between water and the sediment of trace metals naturally occurring in a freshwater ecosystem. They specifically act (1)probably by hydrolysing the organic matter (POM and UDOM) which releases the bound metals, (2) by taking up and immobilising the metals in solution or bound to UDOM and (3) by altering the chemical conditions. In our experiments, release and immobilisation fluxes are of the same order of magnitude, the sign of the resulting transfers between sediment and water depending on the metal. The experiment set of sediment incubation demonstrates the complexity of a batch system because bacteria rapidly and deeply alter the chemical conditions, Main progress should be achieved on the one hand by studying simplified systems, as realised for the assessment of the metal uptake by the bacterial biomass, and on the other hand, by using open experimental systems such as chemostat. 5. ACKNOWLEDGEMENTS

This work was supported by the Ministere de la Sant6 Publique of the Federal State of Belgium. We are grateful to the Collectif Inter-Universitaire de GBochimie Instrumentale for the ICP-MS measurement. 6. REFERENCES 1. 2.

Volesky, B., 1990. Biosorption and biosorbents, in: B. Volesky (ed.), Biosorption of Heavy Metals. CRC Press, Boston, pp. 3-5. Simon, C., J. Remacle and M. Mergeay, 1985. Cadmium immobilization by a resistant microbial strain and its derivatives, ecological and applied implications, in: T.D.I. Lekkas (ed.), Heavy Metals in the Environment. CEP Consultants Ltd, Edinburgh, pp. 57-59.

367 3. Remacle, J., C. Houba, and F. Hambuckers-Berhin, 1986. Cadmium accumulation by two gram negative bacteria: Alcaligems eutrophus CH34 and Pseudodomom aeruginosa AK1800. Preliminary results, in: F. Megusar and M. Gantar (eds.), Perspectives in Microbial Ecology. Slovene Society for Microbiology, Ljubljana, pp. 668-672. Hambuckers-Berhin, F. and J. Remacle, 1987. Cadmium accumulation by Alcaligenes eutrophus, the role of the envelopes, in: S.E. Lindberg and T.C. Hutchinson (eds.), Heavy Metals in the Environment. CEP Consultants Ltd, Edinburgh, pp. 244-246. Infantino-Masuy, B., F. Hambuckers-Berhin and J. Remacle, 1988. The role of envelopes in the cadmium accumulation by two strains of Bacillus coagulans, in: G. Durand, L. Bobichon and J. Florent (eds.),Proceedings of the 8th International Biotechnology Symposium, Socibt.6 Francaise de Microbiologie, Paris, p. C94. Berhin, F., C. Houba, and J. Remacle, 1984, Cadmium toxicity and accumulation by Tetrahymena pyriformis in contamined river waters. Environ. Poll. Ser. A, 35: 315-329. 7. Tynecka, Z., Z. Gas and J. Zajac, 1981. Energy-dependent eMux of cadmium coded by a plasmid resistance determinant in Staphylococcus aureus. J. Bacteriol., 147: 313-319. 8. Nies, D.H. and S. Silver, 1989. Plasmid determined inducible eMux is responsible for resistance to cadmium, zinc and cobalt in Alcaligenes eutrophus. J. Bacteriol., 171: 896-900. 9. Remacle, J. and C. Vercheval, 1991. A zinc binding protein in a metal-resistant strain, Alcaligenes eutrophus CH34. Can. J. Microbiol., 37: 875-877. 10. Remacle, J., I. Muguruza and M. Fransolet, 1992. Cadmium removal by a strain of Alcaligenes denitrificans isolated from a metal-polluted pond. Wat. Res., 26: 923926. 11. Remacle, J., 1988. The removal of toxic metals by microorganisms, in: G. Durand, L. Bobichon and J. Florent (eds.), Proceedings of the 8th International Biotechnology Symposium, Societ.6 Franeaise de Microbiologie, Paris, pp. 1187-1197. 12. Hambuckers-Berhin, F., A. Hambuckers and J. Remacle, 1993. The role of the bacterial community in the radionuclide transfers in freshwater ecosystems, in J.-P. Vernet. (ed.), Environmental Contamination. Studies in Environmental Science, Vol. 55, Elsevier, Amsterdam, pp. 337353. 13. Chrost, R.J., 1990. Microbial ectoenzymes in aquatic environment, in: J. Overbeck and R.J. Chrost (eds.), Aquatic Microbial Ecology. Biochemical and Molecular Approaches. Springer-Verlag, New York, pp. 47-78. 14. Billen, G. and P. Servais, 1988. Modelisation des processus de degradation bacterienne de la matiere organique en milieu aquatique, in M. Bianchi, D. Marty, J.-C. Bertrand, P. Caumette and M. Gauthier, M. (eds.), Micro-organismes dans les gcosystemes Oceaniques. Masson, Paris, pp. 219-245. 15. Coombs, T.L. and S.G. George, 1978. Mechanisms of immobilisation and detoxication of metals in marine organisms, in: D.S. McLusky and A.J. Berry (eds.), Physiology and Behaviour of Marine Organisms. Proceedings of the 12th European Marine Biology Symposium. Pergamon Press, Oxford, pp. 179-187. 16. Servais, P., G. Billen and M.C. Hascoet, 1987. Determination of the biodegradable fraction of dissolved organic matter in coasters. Wat. Res., 21: 445-450. 17. Daumas, R. and M. Bianchi, 1984. Bioturbation and microbial activity. Arch. Hydrobiol. Beih. Ergebn. Limnol., 19: 289-294.

368 18. De Leval, J. and J. Remacle, 1979. The estimation of bacterial predation by aquatic microfauna. Wat. Res., 13: 1335-1337. 19. Box, G.E.P. and D.W. Benhken, 1960. Some new three level designs for the study of quantitative variables. Technometrics, 2: 455-475. 20. SAS, 1985. User’s Guide: Statistics. SAS Institute Inc., Cary, NC, p. 956. 21. Allen, S.E., J.A. Parkinson and A.P. Rowland, 1989. Pollutants, in: S.E. Allen (ed.), Chemical Analysis of Ecological Material. Blackwell, Oxford,pp. 201-239. 22. Plackett, R.L. and J.P. Burman, 1946. The design of multifactorial experiments. Biometrika, 18: 305-325. 23. Hambuckers-Berhin, F. and J. Remacle, 1990. Cadmium sequestration in cells of two strains of Alcaligenes eutrophus. FEMS Microbiol. Ecol., 73: 309-316. 24. Murphy, T.D., 1977. Design and analysis of industrial experiments. Chem. Eng., 6: 168-182. 25. Edeline, F., 1979. L’Bpuration Biologique des Eaux RBsiduaires. ThBorie et Technologie. CBbedoc, Libge, p. 306. 26. Lindner, G., S. Kaminski, I. Greiner, M. Wunderer, J. Behrschmidt, G. Schroder and S. Kress, 1993. Interaction of dissolved radionuclides with organic matter in prealpine freshwater lakes. Verh. Internat. Verein. Limnol., 25: 238-241. 27. Nakajima, A. and T. Sakaguchi, 1986. Selective accumulation of heavy metals by microorganisms. Appl. Microbiol. Biotechnol., 24: 59-64. 28. Xue, H.B., W. Stumm and L. Sigg, 1988. The binding of heavy metals to algal surfaces. Wat. Res., 22: 917-926. 29. Price, N.M., and F.M.M. Morel, 1990. Cadmium and cobalt substitution for zinc in a marine diatom. Nature, 344: 658-660.

Freshwuter und Estuurine Rudioecoio.qy Edited by G.Dosmet et al. 1997 Elsevier Science B.V.

369

Caesium-137 excretion and bioenergetic processes in Cyprinus carpio L. acclimatized to different potassium concentrations in water V.D. Romanenkoa, 0.1. Nasvita, V.D. Solomatinaa, C.V. Carreirob and M.A. Fomovskya ahstitUte of Hydrobiology, Academy of Sciences of Ukraine, Geroev Stalingrada Prosp. 12, 254210 Kiev, Ukraine %GAI DPSR, 2685 Sacavkm, Portugal

ABSTRACT The results of an investigation on the retention of 137Csfrom carp acclimatized to different potassium concentrations in water are reported here. The differences in characteristics of ion exchange and bioenergetic processes between fish, acclimatized to different potassium concentrations, were mainly eliminated by the 28th day of the acclimatization period. The dynamics of radiocaesium release is characterized by slow and fast components, the mean biological half-life of the long-lived component being 182+13days. No differences in 137Csrelease rate were observed in the experiments with different potassium concentrations in water.

1.INTRODUCTION

The influence of water potassium concentration on the accumulation of radioactive caesium by fish has been studied by many investigators. Through different investigations, some authors obtained significant correlations between concentrations of 137Csin fish and potassium in water [1,2]; some others did not [31. This situation was carefully analyzed by Fleishman reveal any correlation [4], who proceeded from the known facts that potassium was a nonisotopic carrier of 137Csand that potassium concentration in fish tissues was independent of that in the water, and showed that this data disagreement was an apparent one, because 137Csconcentrations vary between lakes and the 137Cs fiswwater ratio is correlated to potassium concentrationin water. The relationship of 137Csbioaccumulationfactor to K' seems to be mainly due to uptake from

370

water by algae or microalgae, thus a relationship between K ' concentration in water and 13'Cs excretion by fish, would not be expected. However, this question was raised and it was considered of scientific and applied interest because of being based in fundamental cell ion exchange processes and having a possible yield in the elaboration of methods of fish decontamination. The main objective of the present work was to study the influence of the potassium concentration of water on the 137Csexcretion rate in fish. As the maintenance of ion homeostasis in freshwater fish is an energy-dependent mechanism, the state of cell energy exchange processes was also investigated. 2. EXPERIMENTAL METHODS The experiments were carried out in two stages. In the first stage, three groups of carp (Cyprinus carpio L.), which weighed between 100 and 150 g, were maintained during four weeks in aquaria (360 1each) with an artificial medium differing only in potassium concentration, the other main ion concentrations being similar to Dnieper river water (sodium 13.1 mg 1-', calcium 44.7 mg 1-' and magnesium 9.5 mg 1-'1. Initial K ' concentrations of the water were 0.35, 3.5 and 35 mg 1-' (variants 1 , 2 and 3, respectively). Oxygen concentration was maintained at 6.0-6.8 mg I-' and the temperature was kept at 22-23°C. However, in spite of a partial change of water in the aquaria twice a day, it was found that it was difficult to maintain constant K ' concentrations. In the aquarium where initial K ' concentration were 0.35 mg 1-' a range of 0.49 t o 5.26 mg 1-' was observed. In the second aquarium (initially 3.5 mg 1-' of K') concentrations varied from 3.8 to 21.4 mg 1-'. In the third aquarium (initially 35 mg 1-' of K'), ranged from 37 to 45 mg 1-l. On the 7th, 14th and 28th days from the beginning of the experiment, bioenergetic and ion exchange processes were investigated for gill and hepatopancreas tissues: the content of Na', K'; the content of ATP, ADP, AMP and their sum; Na', K', Mg" -ATP activity [51. This first stage consisted of test fish groups, which at the end of this period were found acclimatized. In the second stage of the experiment, two groups of 120 carp each, approximately the same weight as in the first stage, were previously acclimatized during 28 days (as tested before) in the same artificial media, with initial K+ concentrations of 0.35 mg 1-' and 3.5 mg 1-' (var. 1 and var. 2, respectively). Then several fish from each group were removed to determine the same metabolic parameters as before. After this, about 0.5 kBq of 137Csin gelatine was orally introduced into each fish stomach and the carp were placed into two aquaria (200 1 each) with the same medium as at the beginning of the study of the acclimatization period. Fish were fed with Tubifex sp., at a rate of 1%of body weight per day. From their food, fish received daily 0.45 mg of potassium per 100 g of weight. On the

371

7th, 14th and 28th days, fish from each group were removed for biochemical analysis and determination of characteristics of bioenergetic and ion exchange processes. At the same intervals, 10 fish of each group were taken for the evaluation of 137Csretention. The total amount of 13’Cs in each fish was determined gamma-spectrometrically using a Ge(Li) detector and multichannel analyzer (SBS-30).The experiment was carried out for 170 days following the 13?Csperoral intake. 3. RESULTS AND DISCUSSION

As is shown in Fig. 1,after peroral 13?Csincorporation, two components are found which characterize radiocaesium release from the organism - fast and slow. The rates of radiocaesium excretion and the contribution of slow and fast components, do not differ significantly in fish acclimatized to these two potassium concentrations in water, so the experimental results were averaged and the parameters recalculated (Fig. 2). The biological half-life of the long-lived component is 182f12 days and its relative contribution is 61%;the biological half-life of the short-lived component is 2.8f0.3 days and its relative contribution is 39% (Table 1). During the first two weeks of the acclimatization period differences in the characteristics of ion and energy exchange processes between fishes acclimatized to different potassium concentrations were observed. These differences

I

137cS,Bqlkg 1000

x B

100 J 0

50

100

I

150

200 Days

-Var. 1

x -Var.2

Fig. 1. The dynamics of I3’Cs content in carp.

372

Fig. 2. 13’Cs retention component.

( 0 ) as

a function of time, averaged from both variants; 0,short

TABLE 1 Parameters of radiocaesium release from carp, acclimated to water potassium concentrations of 0.35 mgA (Var. 1) and 3.5 mgA War. 2) Variants

1 2

Average

Fast component

Slow component

Tbl, days

Partial contribution, %

Tb2, days

Partial contribution, %

2.8f3.0 1.9f9.0 2.8f0.3

43 36 39

190f20 176f12 182f12

57 64 61

were tissue specific and changed with respect to different observed parameters and conditions. By the 28th day of the acclimatization period, there were no statistically significant differences between variants of the experiment (Fig. 3). The results of the comparison of ion and energy exchange parameters in fish, acclimatized to different potassium concentrations, suggest that the rate of ion exchange is independent of the potassium concentration in water. Similar results were found during the second stage of the experiment (“normal”and lower potassium concentrations) (Fig. 4).

373

a)

1000

1

I

I1

1000

2

3

4

5

3

4

5

h\

100

l : 0.1

1

2

- Var. 2

-Var. 1

Fig. 3. The differences in content of adenine nucleotide (11, energy charge (21, K', Na', Mg++-ATP-activity(31, K+ (4) and Na' ( 5 ) content in hepatopancreas (a) and gill (b) tissues on the 28th day of the first stage of experiment. Units: 1, mcM adenine per 1 g tissue; 2, relative; 3, mcg P per 1 mg protein per hour; 4 and 5,mg per 1g tissue.

1000

loo

100 10 10

1

0.1

1

1

2

3

-Var. 1

0.1

-

-Var. 2

Fig. 4. The differences in content of adenine nucleotide (l), energy charge (21, K+, Na+, Mg++ -ATP-activity(3)in hepatopancreas (a) and gill (b)tissues on the 28th day of the second stage of experiment. Units: the same as in Fig. 3.

374 4. CONCLUSIONS

The results obtained did not reveal the influence of a lower potassium concentration in the environment on the radiocaesium excretion rate fkom the fish organism. 5. REFERENCES 1.

2.

3.

4. 5.

Preston, A., D.E. Jefferies and J.W.R. Dutton, 1967.The concentrations ofcaesium137 and strontium-90 in the flesh of brown trout taken from rivers and lakes in the British Isles between 1961 and 1966.Water Res., 1:475-496. Kevern, N.R. and S.A. Spigarelli, 1971.Effect of selected limnological factors on the accumulation of cesium-137 fallout by largemouth bass (Micropterm salmoides). In: D.J.Nelson (ed.), Radionuclides in ecosystems. Oak Ridge, 'I",pp. 354-360. Whicker, K.W., W.C. Nelson and A.F. Gallegos, 1972.Fall out (36-137and Sr-90 in trout from mountain lakes in Colorado. Health Phys., 23:519-527. Fleishman, F.G., 1982.Alkaline elements and their radioactive isotopes in water ecosystems. Nauka, Leningrad p. 160. Zarubina, I.W. and B.I. Krivoruchko, 1982.Division and direct colorimetric determination of adenine nucleotides on silyfo. Ukr. Biochem. J. (Russ.), 54:437-439.

Freshwufer und Esfuurine Rudioecoloxy Milcd by G.Desmet ct al. 0 1997 Elsevier Science B.V.All rights reserved

375

Caesium-137 biological half-life evaluation in Cyprinus carpio L. of different weights from the cooling pond of the Chernobyl NPP 0. Nasvita, M.C. Vaz Carreirob, V. Romanenkoa, M. Fomovskia, L. Jurchuka, V. Belyaeva and 0. Bashkova ahstitUte of Hydrobiology, Academy of Sciences of Ukraine, Geroev Stalingrada Prosp., 12, 254210 Kiev, Ukraine ’DGAl DPSR, 2685 Sacave‘m, Portugal

ABSTRACT Having verified that a number of freshwater fish species show increasing 137Csconcentration in muscle with increasing fish weight and knowing that excretion rate is dependent on fish size, an experiment was designed to estimate 137Csbiological half-life in common carp, Cyprinus carpio, from the cooling pond of Chernobyl NPP (where this species showed “fish size effect” on 137Csconcentration), and to verify whether 137Cs biological half-life in the referred species depends on fish size. Therefore, fish chronically exposed to contamination, as they were caught at the cooling pond of Chernobyl NPP, and of large size, because the initial weight ranged from 0.245 to 0.950 kg, were used in this study. About 50 carp were kept in three aquaria with water pumped from the Dnieper river. Chemical parameters and temperature in water were measured at regular intervals. Measurements of live fish were made at certain intervals. Only one biological half-life was detected -the long one ranging from 130 to 400 days. It was verified that fish up to 0.5-0.6 kg show increasing 137Csbiological half-life with the weight increase. Fish weighing more than 0.5-0.6kg show a lower biological half-life than expected, i.e., the biological half-life decreases with the weight increase. The dependence of biological half-life on the fish growth rate was found: lower biological half-life is associated with higher growth rate.

1. INTRODUCTION

The effect of fish size on 137Csconcentration has been noticed by several authors, the evidence of a radiocaesium concentratiodweight relationship being shown for some species, [l-41.Data showing a higher caesium specific

376

activity in bigger fish, silver carp (Hypophtalmichthys molitrix),was presented [ 11.The same size effect for muscle tissue was observed for other fish species like pike-perch (Lucioperca lucioperca), carp (Cyprinus carpio) and catfish (Amiurus nebulosus). Another author [21, mentions that 137Csconcentration increased by a factor of four in Lepomis macrochirus in White Oak Lake, from 1 to 70 g. Some authors 131 described a power function relationship between 137Csand fish weight for trout (Salrno trutta) from the lakes Devoke and Loweswater and for perch (Permfluuiattilis) only from the first lake. Increasing 137Cslevels in perch, with increased body weight, have been reported, and similar relationships were observed for pike, both species feeding on higher trophic levels [41. The increasing 137Cslevels, with increasing body weight, referred to above [4],might be an indication for a change of feeding habits with fish age. Other authors also noted that after Chernobyl, the concentration of radioactive caesium in fish varied strongly with time between fish species and sizes, mainly depending on the nutrient intake of the fish [51. It was also observed that feeding rates and metabolic activity may explain the large variations of radiocaesium concentrations between different species and size classes in a lake [6]. Differences in accumulation of radiocaesium from the Chernobyl fallout between brown trout (Salmo trutta) and arctic char (Saluelinus alpinus) in a Norwegian lake, were mentioned [71. Among the major factors that may have an influence, these authors pointed to the biological half-life of radiocaesium. Brown trout lives at higher temperatures and feeds mainly on zoobenthos, while arctic char lives in colder waters and has a lower food consumption, mainly of zooplankton. Their ecological half-lives were calculated respectively 1.0 and 1.4years, as trout were shown to have a faster excretion rate than char. Some authors [8,91 found that the radiocaesium excretion rate is strongly dependent on ambient temperature. Other authors [lo1 reported the influence not only of the temperature but also of the body size on the radiocaesium retention by brown trout. The biological half-life increases with decreasing temperature and with increasing body weight. Radiocaesium biological halflives increasing with body weight in poikilotherms and caesium excretion as a function of metabolic rate were reported [ l l l . A half-life of 3.4 years for trout in a mountain oligotrophic lake was mentioned [121, and an ecological half-life for 13'Cs in pike (the top predator in oligotrophic lakes) of about 13 years was noted [131. The increase in 13%swith weight in Oak Lake Lepomis macrochirus was a result of the increase in the absorption and the decrease in the elimination rates [2]. It was also noted [31 that the 137Csexcretion rate decreases due to fish growth or increasing fish age. In a literature review [121,a strong tendency was noted towards higher 13'Cs values in carnivorous fish. In rivers, based on a half-life of 200 days, it takes 2.5 to 4.5 years before the 13%sconcentration in fish returns to the former levels (before the accident). The half-lives are considerably longer in lakes than in

377

rivers: never less than 100 days in herbivorous fish and several years in some carnivorous species. Half-lives of more than one year are cited by several authors, the kinetics depending on many factors. Concerning 137Csbiological half-lives in fish, it has been noted [141 that the in situ measurements of the radiocaesium decontamination generally show two biological half-lives: Tb, ranging from 5 to 12 days and Tb, ranging from 25 to 600 days, but the latter may reach about 3 years. In general, they increase with fish age and with decreasing temperature in water, but many other environmental factors may affect this parameter. However, when fish were chronically exposed in White Oak Lake they showed a single component elimination [2]. Elimination curves of radiocaesium in bluegill (Lepomis macrochirus) consisted of two components, as in other fish, and the rate of the slow component decreased with bluegill size, also reported for other fish [21. This means that rates of radiocaesium elimination decreased with increasing weight in bluegill. Finally it is important to notice that the new tendency is not to use the steady-state concentration factor to assess fish contamination, but to use models based on rate constants. Models using the biological turnover time of radiocaesium showed better agreement to the observed data [151. From the physiological point ofview, therefore, there should be a dependence between metabolic rate and fish size within the same species. In addition, there is evidence of a relationship between radiocaesium biological half-lives (or retention rates) and metabolic rate. Therefore, an experiment with in situ chronically contaminated fish, of different sizes, to study 137Csretention kinetics at the laboratory, was considered of the greatest interest. The objectives of the present work are to estimate 137Csbiological half-life in common carp, Cyprinus carpio, from the cooling pond of the Chernobyl NPP, where this species showed fish-size effect on 137Csconcentration, and t o verify whether 137Csbiological half-life in the referred species depends upon fish size. 2. MATERIALS AND METHODS

When studying the kinetics of radionuclide release by aquatic organisms, the experiments are, as a rule, carried out on large groups of artificially contaminated bionts, being the radionuclide retention measurements made at regular intervals on groups of organisms. The rate of radionuclide decrease in a biont is calculated through the results of 137Csmeasurements related to the initial (injected) amount of radionuclide. There are at least two difficulties when implementing this methodology in experiments with fish chronically contaminated in natural habitats. The first is of a technical character: a large number of fish is required. For example, if several size ranges are taken and ten samplings are done during the experiment, at least 400-800 fish are needed. Maintaining this number of fish in laboratory conditions is difficult, especially if the weight of the fish in the larger size group reaches 1-1.5 kg. The second

378

difficulty -and probably the principal one -is that fish of the same size taken from a natural population could have large differences (several times) in the initial level of 137Cscontamination. In this case it is impossible to employ the above-mentioned calculation technique. However, measuring live fish in experiment allows for satisfactory observations over a restricted group of individuals. In this case, monitoring of individual fish mass and size is possible. Although precise determination of fish 137Cs content is not possible with live fish, subsequent contamination levels are related to the initial one of each fish, and the values of these relations can be obtained with sufficient accuracy. For live fish measurements, a special y-spectrometric installation was constructed. It consists of a NaI(T1) 63x63 mm detector with energy resolution of 7.4% and absolute efficiency of gamma-quanta counting of 30% (661.6 keV), a multichannel analyzer with an EC-1840 computer and a measuring chamber, protected, together with the detector, from the external y-radiation with 5 cm of lead. An aquarium with the fish t o be measured is placed in the chamber. The fish is fured in relation t o the aquarium and detector with a special device providing a constant geometry during each measurement. Fish caught in the coolingpond of Chernobyl NPP (71individuals)were brought to the aquarium complex of the Institute of Hydrobiology (Kiev)and placed into three 300 1 basins with Dnieper water, which is similar to that of the cooling pond from the point of view of the chemical composition. On the second day of the experiment 20 fish of different sizes (zero group) were taken for determination of 137Cscontent. The other fish (main group) were labelled with colour marks for individual identification. Fish were daily fed with an amount of 2% of their weight. During the initial 80 days of the experiment, a fodder for warm-water fish breeding was used, and from 80 days to the end of the experiment, a fodder for extensive pond fish-breedingwas used, because of extrinsicreasons. Gamma-spectrometric analyses of both fodder samples were done, being 137Csconcentrations about the same and negligible. Ten percent of the water in the basins was renewed daily. Daily monitoring of water temperature showed a variation of 11.5-15.loC, without any regular tendency. Regular measurements of chemical water composition showed its correspondence to Dnieper water (Table 1). At certain intervals, fish of the main group were measured (length and weight) and 137Csradioactivity determined. The experiment was carried out for 166 days and 11series of measurements were performed. During the initial 76 days, the intervals between measurements were 7-13 days and afterwards about 30 days. The time of each fish measurement was about 30 min and consisted of three independent measurements (about 7 min each) in order t o calculate a mean value. So, for each fish, a series of consecutive values of mass, size and 137Cscontent (in related units counts per second) was obtained. Results on the zero fish group showed a rather narrow interval of 137Cs concentration in muscles, 4.1-11.5 kBq kg-', and a certain concentration increase with fish mass (Fig. 1).

379 TABLE 1 Main chemical composition of water in Dnieper river and experimental basins Component

Units

Dnieper water

Basin water

Ca2+ M e Na+ K+ HCOS

mg 1-' mg I-' mg I-' mg I-' mg 1-l mg I-' mg I-' mg I-'

63-72 13-19 13-16 2.8-3.5 214 55-65 22-23.5 393-402 7.4-8.2 0.02-0.08 0.09-0.37

63-72 13-22 13-17 3.2-3.7 214-220 55-86 22-23.5 390-405 6.7-8.3 0.09-2.1 0.03-0.59

so$-

c1Total PH NH4

mgN I-' mgN I-'

Ptotal

"'CS, k B q k 1mw

1000

1oD

0 10

im

Mass, kg

loOD

Fig. 1. Mass dependence of '37Cs concentration in muscles of zero group fish.

3. RESULTS AND DISCUSSION

Radionuclide release from hydrobionts is expected to be exponential. After resettlement of the contaminated biont into uncontaminated medium, radionuclide burden in an organism, independently of the contamination pathway, changes as follows:

380

where C(t)is the radionuclide content at time t, C,is the radionuclide content at time zero t = 0, Ak is the partial contribution of k component of radionuclide release, pkis the loss rate of k component. As a rule one or two components are observed and in the last case their loss rates generally differ 5-10 times. They are evaluated by decomposition of the experimental curves of radionuclide release, graphically or by consecutive back calculations. Analysis of the experimental data did not reveal more than one component, as is expected according to [21. For each fish, radioactivity data were normalized to its initial level and parameters of linear regression were calculated: In (C(ti))= ati+b

(2)

From a comparison of (1) and (2) it is easy to understand that a = -p, p being directly connected with 13'Cs biological half-life (Tb): (3) Tb= -1n(2)/p Calculations of Tbwere done through the data obtained up to 76 and up to 166 days, only one component being found. (Retention analysis of two components revealed two equal biological half-lives, which is impossible.) The squared correlation coefficient in all cases, but 10, was higher than 0.7. Figure 2 shows the values of Tb plotted versus fish mass and it is possible to see that no distinct dependence was found. Regression analysis showed very poor correlation with slightly positive (76 days) and slightly negative (166 days) regression:

Tb= 244.m0.054, ?=0.0047 (76 days)

(4)

Tb= 308.m4.035,r2=0.0030(166 days)

(5)

From Fig. 2 a tendency of Tb increasing with mass for smaller fish and decreasing for larger ones could be supposed. So, it was decided to group fish into mass classes and therefore, to make new calculations. Within each class, time retention rates were averaged and Tb recalculated as described above (Table 2). The supposed tendency was proved: fishes of mass less than 0.6 kg showed increasing I3'Cs biological half-life with increasing mass, but fishes of mass more than 0.6 kg do not follow this pattern (Fig. 3). Regression calculations on pooled data for fishes of mass less than 0.6 kg showed a good correlation:

Tb= 356.m0,48, r2=0.99(76 days)

(6)

Tb = 533.m0'52, r2=0.97(166 days)

(7)

Regression calculations for unpooled data for the same range of fish mass as used to obtain (6) and (7) showed poor correlation coefficients. It is also evident, that Tb values calculated for 166 days, on average, exceed those for 76 days (see Fig. 3, Table 2 and Eqs. (4147)). Some possible explanation of this phenomenon will be presented below.

381

600

so0

aoo

300

a

a

200

100

0 . 2 0 . 3 0 . 4 0 . 5 0 . 6 0 . 7 0 . 8 0 . 9

1

Fish mass, (kg)

a)

500

-

I

0

400F

i

L

300,

i

ZOO

100

O

0

-

C

=

0

0

0

0

I

I

0 . 2 0 . 3 0 - 4

,

1

0 - 5 0 . 6 0 . 7 0 . 8 0 . 9

b)

1

Fish mass (kg)

Fig. 2. Individual half-lives of '37Csin carp calculated at the 76th (a) and 166th (b) days of experiment.

382 TABLE 2 Radiwaesium biological half-lives calculated at 76th and 166th days of experiment Classes

Ranges (kg)

Results at 76th day

Tt, (days)

1 2 3 4 5 6

c0.3 0.3-~0.4

0.4-~0.5 O.kO.6 O.kO.7 20.7

Results at 166th day sq.

Tt,(days)

Means

STD

carrel.

Means

STD

sq. coeff. correl.

208 232 271 307 232 248

20 15 33 31 19 21

0.95 0.92 0.96 0.98 0.94 0.95

262 324 365 374 281*

27 31 38 19 26

0.93 0.94 0.93 0.98 0.95

coeff.

*Calculationswere made for fishes of mass 20.6 kg, i.e. classes 5 and 6 together.

Fig. 3. ‘37Cs biological half-life in carp of different mass classes calculated at 76th (1) and 166th (2) days of experiment.

The increase in I3’Cs biological half-life with mass has been reported in many works, as already noted, and is in agreement with present physiological understanding of the process. But we did not find in the literature any mention of this kind of change at certain increases of fish mass. On the other hand, and it is important to notice, no paper reported experimentalwork with fishes of mass larger than 0.5-0.6 kg. Since the series of data on 13’Cs content and mass alterations were obtained for each fish individually, to analyze them together was also possible. It was found that fish which showed less growth or did not grow at all had larger Tb

383 TABLE 3 Mean biological half-lives for fishes belonging to different classes according to mass changes (76 days) No. fish

Class

Mass changes

(days)

(%)

7

2

10 20 12

Means

STD

258 251 204 205

32 14 10 10

Mass (kg) 0.9: ,

I ,

2

I

0.2'

i

0

20

4 0

60

80

100120140160

Time (days)

Fig. 4. Alteration of mean fish mass within classes during experiment. Figures on the right are class numbers.

values than those which grew better (Table 3). This seems to be very important and, perhaps, could explain increasing Tbfrom the 76th to 166th day. Analysis of changes in fish mass showed that in all mass classes the mean value of fish mass decreased from the 76th to 166th day of experiment (Figs. 4 and 5). It could be connected with the changes in fodder type (which very likely should be avoided), followed by the decreasing of growth rate, even to negative, and associated decreasing of metabolic rate.

384

"

1

2

3

4

Classes

5

6

Fig. 5. Decreasing of the mean fish mass within classes from the 76th to 166th day of experiment.

It was also verified whether differences in 13'Cs biological half-life could be associated with fish sexual differences. Mean values of T b for each sexual group were calculated, but due to presence of size effect, with comparatively large standard deviations, fish number was not enough to build size dependence separately for male and female fishes. So, no sexual differences in T b could be found. 4. CONCLUSIONS

In carp from the cooling pond of the Chernobyl NPP,in chronically exposed conditions, the retention experiment carried out in the laboratory, at a mean temperature of 13"C, revealed only one 137Csbiological half-life. Individual biological half-lives were in the range of 130-400 days. Fishes of mass lower than 0.6 kg showed increase in "'Cs biological half-life with increasing mass, but fishes of mass higher than 0.6 kg showed a biological half-life decrease. The dependence of biological half-life on the fish growth rate was found: lower biological half-life was associated with higher growth rate. An increasing trend on biological half-life with fish mass was observed (up to 0.6 kg), being described by power function with good correlation. 5. REFERENCES 1.

Koulikov, A.O. and I.N. Ryabov, 1992. Specific cesium activity in freshwater fish and the size effect. Sci. Tot. Environ., 112: 125-142.

385 2. Kolehmainen, S.E., 1972. The balances of 137Csstable cesium and potassium of Bluegill (Lepomis mucrochirus Raf.) and other fish in White Oak Lake. Health Phys., 23: 301-315. 3. Elliot, J.M., J. Hilton, E. Rigg, P.A. Tullett, D.J. SwiR and D.R.P. Leonard, 1992. Sources of variation in post-Chernobyl radiocesium in fish fiom two Cambrian Lakes (north-west England). J. Appl. Ecol., 29: 108-119. 4. Linder, G., W. Preiffer, J.A. Robnins and E. Recknagel, 1989. Long-lived Chernobyl radionuclides in Lake Constance: speciation, sedimentation and biological transfer. Proceedings of the XVth. Regional Congress of IRPA. Visby, Gotland, Sweden, 10-14 Sept. pp. 295300. 5. Andersson, Ti, L. Hakanson, H. Kvarnas and A. Nilsson, 1991. Atqarder mot hoga halter av radioaktivt cesium i insjosk. SSI-Rapport 91-07, 114 pp. 6. Meili, M., 1991. The importance of feeding rate for the accumulation of radioactive caesium in fish aRer the chernobyl accident. In: L. Moderg (ed.) The Chernobyl Fallout in Sweden. The Swedish Radiation Protection Institute, pp. 177-182. 7. Forseth, T., 0. Ugedal B. Jonsson, A. Langeland and 0. Njastad, 1991. Radiocesium turnover in Arctic Cham (Salvelinus alpinus) and Brown Trout (Salmo truttu) in a Norwegian lake. J. Appl. Ecol., 28: 1053-1067. 8. Kevern, N.R., 1966. Feeding Rate of Carp estimated by a Radioisotopic Method. Trans. Am. Fish. SOC.,95: 363371. 9. Hasanen, E., S. Kolehmainen and J.K. Miettinen, 1969. Biological half-time of freshwater fish: perch, roach and rainbow trout. In: B. Aberg and F.P. Hungate (eds.) Radioecological Concentration Processes. Pergamon Press, Oxford, pp. 921924. 10. Ugedal, O., B. Jonsson, 0. Njastad and R. Naeumann, 1992. Effects oftemperature and body size on radiocaesium retention in brown trout (Sulmo truttu).Freshwater Biol., 28: 165-171. 11. Mailhot, R.H. Peters and R.J. Cornett, 1989. The biological half-life of radioactive cesium in poikilothermic and homeothermic animals. Health Phys., 56 (4): 473484. 12. Foulquier, L. and Y. Baudin-Jaulent, 1990. The impact of the Chernobyl accident in continental aquatic ecosystems. A Literature Review. Proceedings of the seminar on comparative assessment of the environmental impact of radionuclides released during three major nuclear accidents: Kyshthym, Windscale, Chernobyl. Luxembourg, 1-5 Oct. 1990, pp. 679-704. 13. Hakanson, L., 1991. Radioactive cesium in fish in Swedish lakes aRer Chernobyl geographical distributions. Trends, models and remedial measures. In: L. Moderg (ed.) The Chernobyl Fallout in Sweden. The Swedish Radiation Protection Institute, pp. 239-281. 14. Foulquier, L., 1979. Etude bibliographique sur la capacit6 et les modalitks de la fixation du radiocesium par les poissons. Rapport CEA-BIB-231(2), 360 pp. 15. BIOMOVS Technical Report 12. Scenario A5: dynamics within lake ecosystems. Bjorn Sundblad (Ed.), National Institute of Radiation Protection, Stockholm, Sweden, Sept. 1991.

Freshwuter und Esfuurine RUdilJt'CfJkJgy Edited by G.Desmet et al.

0 1997 Elsevier Science B.V. All rights reserved

387

A bioenergetics approach to modeling seasonal patterns in the bioaccumulation of radiocesium D.J. Rowana*, J.B. Rasmussenb and L. Chanta aEnvironmental Research Branch, Chalk River Laboratories, Chalk River, Ontario KOJ lJ0, Canada bDepartment of Biology, McGill University, 1205 Dr. Penfield Ave., Montreal, Quebec H3A lB1, Canada *Present address: Department of Radiological Health Sciences, Colorado State University, Fort Collins, CO 80523-1673, USA

ABSTRACT A conceptual bioenergetics model that can predict the seasonality in 137Cs concentrations in fish has been developed and tested with two data sets. Our results suggest that temperature is the driving force behind the observed seasonality (almost 2-fold)in 137Cs concentrations in fish. Although faster clearance is largely responsible for the observed decline in 137Csconcentrations a t peak water temperatures, ration and growth also contribute. Ration is best modeled as the first derivative of a Gaussian representation of the annual water temperature cycle (producing a bimodal pattern with a minimum a t the peak of the summer), whereas growth appears to be a direct function of the temperature curve. This pattern was consistent with ration estimated from gut contents and clearance rates. The model was developed with data from Centrarchids and further testing with other fish taxa is necessary to confirm the generality of these results.

1. INTRODUCTION

Much of the variability in fiswwater radiocesium bioaccumulation factors (BAF)can be explained by physico-chemical and ecological parameters [ll. Physico-chemical factors that reduce 137Cs BAFs include dissolved potassium and suspended sediment concentrations. Ecological factors include the trophic level of the fish (piscivores bioaccumulate more than planktivores and benthivores) and the length of the food chain (longer food chains lead to higher BAFs).Although these empirical models have high predictive power (r2= 0.87 to 0.95) and relatively low uncertainties in their predictions (SE,, = 0.19 to

388

0.31), there is often 2-fold variation in 137CsBAFs among fish of the same trophic level (or species) within a system [ll . Seasonal variation within an age class can also approach 2-fold, with a minimum in 13'Cs concentration during the temperature maximum in mid- to late summer [2,31. We hypothesize that this decline in 137Csis related to the temperature regime of the system, because the clearance rate of 137Csis strongly temperature dependent 141 and as well many bioenergetic parameters are temperature dependent. Bioenergetics parameters that can decrease the concentration of 13'Cs in fish include increased growth, and decreased ration, prey concentration, and/or assimilation efficiencyof prey. Of these parameters, assimilation efficiency is temperature independent [61 and there is little indication of seasonal variation in 137Csin zooplankton (Rowan, unpublished data). Growth and ration should, in general, be lowest during winter, but whether they peak with temperature or are bimodal with respect to temperature is not well known. However, we expect that the effect of ration will be greater than that of growth, and along with clearance should be dominant factors in the seasonality. In this paper, we develop a conceptual approach to bioenergetics modeling that produces a seasonal pattern similar to that observed in bluegills (Lepornzs rnacrochirus) living in White Oak Lake [2,31 by linking the bioenergetics parameters ration and growth to the temperature regime of the system. As the relationship between growth, ration and temperature is not clear, we model both growth and ration as direct functions and first derivatives of the annual temperature curve. We then test this conceptual model with observed 13'Cs concentrations in rock bass (Ambloplites rupestris) from the Ottawa River. 2. THE MODEL

The concentration of 137Csin a fish ([137csfi8h] 1 can be modelled on a daily basis (all rates are assumed constant) as:

where [137csfish]tois the concentration of 13'Cs at the beginning of the interval, [ 137Csprey], is the concentration of Ia7Csin prey i, AEi is the assimilation efficiency of f37Csfrom prey i , Pi is the proportion of prey i in the diet, R is the ration (d-'), and K is the sum of clearance, radioactive decay and growth (d-'). This is essentially a mass-balance model of the type published by Thomann [5],which simultaneously models the mass balance of 137Csand biomass. 3. METHODS The concentration of 137Csin White Oak Lake bluegill and their prey, the assimilation efficiency of 137Csfrom the prey, bluegill size and growth, and

389

water temperature were obtained from literature 131. The concentration of 137Cs in Ottawa River rock bass and their prey was determined by gamma spectrometry from samples collected on two dates: July 8 and August 10, 1993. On the former date, we captured three 3+, three 4+, four 5+, six 6+ and four 7+ rock bass, and determined 13?Csfor composite samples for each year class. On the latter date, we captured seven 4+, four 5+ and two 6+ rock bass and analyzed these fish individually for 137Cs.The diet composition was determined from gut contents, the 137Csconcentration was assumed constant and the assimilation efficiency of 137Cs from the predominantly invertebrate prey was estimated as 0.638 (fO.191) [2,6,7,81. Water temperature was modeled as a function of Julian day by a Gaussian curve [81:

Water temperature (T,"C) of White Oak Lake was estimated from Eq. 2 using non-linear regression (Fig. la):

T = 3.g + 22.3

u)

0

9

e-(da~-208.7f/ 109.72, 2 .,

= 0.96

(3)

- -. ration calcukbd from Eq.3 500 - -d o n cakulabd from 1st derivative of Eq. 3

Y

Fig. 1. (a)Annual water temperature cycle for White Oak Lake (points) [31 with the predictions of Eq. 3. (solid line). (b) Seasonal pattern in [137Cslof bluegill from White Oak Lake 131 is best predicted by Eq. (1) with growth estimated as a function of temperature, ration as a first derivative of temperature (solid line).

390

25 O Y P

a)

20-

5 15g 10E 5g!

c

OO

100

200 300 Julian day

Julian day 250 - j

8

150

3+

4+

5+

6+

-: - g r o w calouhtndfrom let doriviv.tivmof

89 6 189 6 189 6 189 6 Julian day

€1

I

Fig. 2. (a) Annual water tem erature cycle for the Ottawa River with the predictions of Eq. (4). (b) Seasonal pattern in [8 7Csl of several year classes of rock bass from the Ottawa River is best predicted by Eq. (1)with growth estimated as a function of temperature, and ration as a first derivative of temperature (solid line). The lower dashed line is the result of increasing temperature by 10°C between sampling dates. (c) Growth of Ottawa River rock bass is best modeled as a function of temperature (dashed line) rather than a first derivative (solid line) of temperature. Error bars are 2 SD.

Water temperature data for the Ottawa River was also estimated from Eq. (2) by nonlinear regression (Fig. 2a):

Daily growth (G,d-'):

G =In

(g)

391 (5)

was calculated from mean year class weights (W, g) using the temperature relationships (Eqs. (3) and (4)), and their first derivatives by setting A = 0 (essentially no growth in winter), and fitting the unknown B iteratively (see Eq. (2)).The slow component of elimination ( E , d-') of 137Cswas estimated as:

where W is weight (g) and T is water temperature ("C)141. The radioactive decay constant (RD,d-') for 137Csis 6.29 10". Daily clearance, radioactive decay and growth rates can then be summed:

K =E

+ RD + G

(7)

Thus, the only unknown in Eq. (1) is ration, which was solved for by assuming that seasonality in ration either tracked the temperature curve (Eqs. (3) and (4))or its first derivative, in the same manner as growth. 4. RESULTS

Seasonal variation in the concentration of 137Csin 4+ age class bluegill from White Oak Lake is largely driven by the temperature effect on clearance (Figs. 1 a,b). The only difference between the two curves in Fig. l b is the manner in which ration was calculated. The dashed line represents ration calculated from the water temperature curve (Eq. (3)), while for the solid line, ration was calculated from the first derivative of the temperature curve (Eq. (3)). It appears that low ration at peak water temperatures is necessary to produce the observed minimum in 137Cs,with higher ration at moderate water temperatures producing the remaining trend. Growth has only a very small effect on the seasonality and from these data it is not possible to resolve whether growth is more likely uni- or bimodal with respect to temperature. Prey 137Cs concentrations do not have any effect on the seasonality, as

is unrelated to water temperature. The variation in the concentration of 137Csin Ottawa River rock bass collected on two sampling dates is also inversely related to the temperature curve (Fig. 2a,b). Unless ration is calculated from the first derivative of the temperature curve (solid line, Fig. 2b) the concentration of 137Cswill not decline at maximum water temperature (dashed line, Fig. 2b). Gut contents (g, cor-

392

rected for clearance) also support a low ration at peak temperatures, with a decline of about 3.5 fold from early July to mid-August. It is not possible to simulate the dramatic seasonal fluctuations of these data using the model described earlier. This suggests that either elimination is underestimated or there is a seasonal pattern in

There is a small decrease in the concentration of lS7Csin crayfish (the main prey) as water temperature increases (2.8 to 2.4 Bq kg-' ww, July to August), but this is insufficient to explain the dramatic drop. The pattern is most likely due to clearance, as it is possible that in spawning (the fish spawned between the two dates), these fish (especially the 5+ and 6+ age classes which are the main spawners) remained in very warm shallow water. A difference of about 10°Cfrom the main river channel would account for the observed drop (Fig. 2b). We also hypothesized that by laying eggs, the fish could have cleared 137Cs,but found egg concentrations of 5.7 Bq kg-' ww vs fish concentrations of 13.1 Bq kg-lww. Again, growth has a small effect on the seasonality, and by calculating growth from the water temperature curve (Eq. (4)), we match the observed growth rates (Fig. 2 4 . 5. DISCUSSION

These results suggest that the mid-summer decline in 137Csconcentrations is mainly caused by temperature driven clearance and ration. At peak temperature, clearance is greatest, while ration appears to follow the first derivative of the temperature curve, with maxima in spring and fall. There is also some evidence that growth and growth efficiency peak with water temperature, although growth has only a small effect on the seasonal pattern. It is evident that to reduce uncertainties in estimates of 137Csconcentrations in fish from 2-fold to less than 20%, it will be necessary to model the seasonality. The conceptual model developed here appears to reproduce the seasonality for two populations of Centrarchids using simple relationships with water temperature. We are currently studying the seasonality of 137Csin a Percid (walleye,Stizostedion uitreum) and its prey in the Ottawa River to extend these results to fish other than Centrarchids. 6. REFERENCES 1.

Rowan, D.J., and J.B. Rasmussen, 1996. The bioaccumulation of radiocesium by fish: the influence of physico-chemical factors and trophic structure. Can. J. Fish Aquat. Sci., 53: 734-745.

393 2. 3. 4. 5. 6. 7. 8.

Kolehmainen, S.E., 1972. The balances of 137Cs,stable cesium and potassium of bluegill (Lepomismacrochirus ran and other fish in White Oak Lake. Health Phys., 23: 301-315. Kolehmainen, S.E., 1974. Daily feeding rates of bluegill (Lepomis macrochirus rat) determined by a refined radioisotope method. J. Fish. Res. Board Can., 31: 67-74. Rowan, D.J. and J.B. Rasmussen, 1995. The elimination of radiocaesium from fish. J. Appl. Ecol., 32: 739-744. Thomann, R.V. and J.P. Connolly, 1984. Model of PCB in the Lake Michigan lake trout food chain. Environ. Sci. Technol., 18: 65-71. Kevern, N.R., 1966. Feeding rate of carp estimated by a radioisotopic method. Trans. Am. Fish. SOC., 95: 363-371. Hewett, C.J. and D.F. Jefferies, 1978. The accumulation of radioactive caesium from food by the plaice (Pleuronectesplatessa) and the brown trout (Salmo trutta). J. Fish Biol., 13: 143-153. Forseth, T., B. Jonsson, R. Naeumann, and 0. Ugedal, 1992. Radioisotope method for estimating food consumption by brown trout (Salmo trutta). Can. J. Fish. Aquat. Sci., 49: 1328-1335.

Freshwuter und Estuurine Rudiiiecology Edited by G . Desmet et d.

1997 Elsevier Science B.V.

395

Potassium and stable caesium effect on radiocaesium uptake and loss by the Cyprinid fish, Chondrostorna polylepis polylepis J.A. Gil Corisco and M.C. Vaz Carreiro DGAIDPSR,E.N. 10,2685Sacavtm, Portugal

ABSTRACT Many environmental parameters affect radiocaesium accumulation by freshwater biota. One of them is the chemical composition of water and mainly the potassium concentration, as both elements are chemically analogous and potassium is the non-isotopic carrier of caesium. Under the hypothesis that one of the parameters that may affect radiocaesium concentration factors in freshwater fish is not only the potassium concentration in water, but also the ratio of potassium-stable caesium, the objective is to study the influence of both stable elements on the accumulation and retention of radiocaesium by fish. Therefore, a series of experiments was programmed. The first set of experiments was carried out at three different K+ concentrations, (0.35,3.5 and 35 mg 1-l)and at a low constant Cs+ concentration ( 5 . 8 x l V mg 1-l). In the second set of experiments K+ was kept at low constant concentration (5.8~10"'mg 1-l) and three different Cs+concentrations (0.35, 3.5 and 35 mg 1-l) were used. Results showed that at low constant Cs+concentration, the relation between K+ concentration in water and concentration factor in fish is inverse. The loss of the radioisotope followed non-significantly different kinetics for the three groups of fishes, therefore, did not reveal significantly different biological half-lives. Inverting the predominance of both stable elements in water, stable caesium affects 134Csconcentration by fish in a similar way as potassium, but 134Cselimination is slower. The whole set of experiments showed that the influence of environmental potassium and stable caesium on the uptake of 134Csis quite similar, but the deficiency of potassium reduces the capacity of elimination of the accumulated radioisotope by fish.

1. INTRODUCTION

In nature the radiocaesium bioaccumulation shows a large variability, being higher in oligotrophic lakes with low potassium concentration and lower in freshwater with high potassium content [ll . In lakes it is possible to say that

396

radiocaesium accumulation by fish is directly proportional to the radiocaesium content and inversely proportional to the potassium content in water [2]. Radiocaesium concentrations are inversely related to K ' concentration in the water over the range 0.8 to 3.6 ppm K', being the highest 137 Cs concentrations in oligotrophic lakes [3]. Another author [41 studied the metabolic rates of 137 Cs and K ' in pike from a northern lake at the temperature of 8-10°C.However, it must be stressed that in these cases the bioaccumulation occurs not only through the water but mainly through the food webs. The influence of soluble potassium on radiocaesium uptake have already been studied by several authors: an inverse relation was quoted in muscle tissue of carp (experimental data) over a range of 1 to 400 ppm K ' (sea water) [5];other authors [6]used two extreme K ' concentrations, 2.9 and 390 ppm, and the same inverse relation was reported; assuming that K ' concentration in freshwater is in the range of 3.9 to 39 ppm, the CFs vary from 39 to 14 (experiments at 20°C) [61. Concentration factors for radiocaesium in freshwater fishes reported in the literature, either experimental or field data, range from 3x10-' to lo4, at different temperatures [7-131. Several values for radiocaesium biological half-life in freshwater fishes are referred to in the literature [8,11,121. Foulquier in a literature review 181 remarked that radiocaesium decontamination measurements, either in situ or in experiments, generally show two biological half-lives: Tbl ranging from 1 to 25 days and Tbzfrom 20 to 600 days. The balances of radio and stable caesium and potassium were studied in nature and related with seasonal cycling of both stable elements [141. Concerning the stable caesium a study with freshwater phytoplankton refers to the fact that K ' in high concentrations decreased 137Csuptake, but considerably smaller concentrations of Cs', up to 0.15 mM 1-' (20 ppm), had a greater effect. In certain conditions 1 mM 1-' (133 ppm) of CsCl appeared to produce a slight toxic effect [15]. More recently, after the Chernobyl accident very high 137Csconcentrations in fishes were found, mainly in lakes in Northern Europe, with large differences from lake to lake [16,171. On the assumption that it is not only the potassium concentrationin water that affects the radiocaesium accumulation in fish, but also the potassium-stable caesium ratio in water, a series of experimentswas programmed to investigatethe role of stable caesium and potassium in fish ls4 Cs concentration and retention. 2. MATERIALS AND METHODS

The experiments were performed in small plastic aquaria filled with 5 1of an artificial freshwater medium. Knowing the main water composition of the Fratel Reservoir (in Tejo River), artificial water was prepared, keeping the

397 TABLE 1

Concentrations of K+, stable Cs+ and radioactive Cs+ in the artificial medium

K+ -

Group 1 Group 2 Group 3 Group 4 Group 5 Group 6

(PPd

Stable Cs+ (PPd

Radio Cs+** (PPm)

0.35 3.5 35 5.83-04 5.83-04 5.83-04

5.8E-04 5.83-04 5.83-04 0.35 3.5 35

6.163-04 to 6.283-04 6.163-04 to 6.283-04 6.163-04 to 6.283-04 6.563-04 to 6.643-04 6.563-04 to 6.643-04 6.883-04 to 7.043-04

-

**Onlyfor uptake phase

main cation concentrations and changing K+and Cs+ concentrations, whose mean values for three years are 3.3kO.3 and (5.8f1.7) x lod mg 1-', respectively. The artificial medium was composed of distilled water to which some salts were added, in order to get a basic cationic composition similar to that of the Fratel Reservoir. Ca", M e and Na+concentrations were 3 6 , l l and 25 mg 1-', respectively. Table 1 shows the concentrations of stable Cs+, K+and also of 134Cs+ added during the uptake phase. Caesium-134 was added to aquaria in a solution 0.1 M chloridric acid with a concentration of 2 pg Cs+m1-l. The quantities given in Table 1are equivalent to a presumed radioactivity of 20 Bq ml-' in the aquarium water, although the real measured value was expected to be less than that, because of some lMCs adsorption to the aquarium surfaces. Potassium concentration in water and food was monitored in one set of experiments. Water was changed once a week and the contaminated faecal pellets were daily separated by screening, to prevent their ingestion by fishes. The aquaria had no water filtration system. Aeration was maintained by aquarium air compressors and plastic inlet tubes, water temperature was kept at 2Ok2"C and artificial light by fluorescent tubes was added to natural sunlight, for 8 hours a day, except for weekends. Fishes were small specimens of the cyprinid Chondrostoma polylepis polylepis, aged less than 1year, fed 5 days a week with milled soft parts of bivalves, each meal representing about 5%of the total fish weight. Six groups of fishes were selected and kept in the aquaria according t o the conditions described in Table 2 (group no, 6 was divided into two sub-groups to maintain similar biomass conditions). Each group was previously acclimatized to the artificial medium, for 10 days, before contamination with radiocaesium. The continuous exposure to 134Csin water (direct uptake) lasted for 4 weeks, followed by a decontamination period of 6-7 weeks. Caesium-134 radioactivity was measured using a NaI(T1) well-type detector with a multi-channel analyzer. Radioactivity measurements were made on

398 TABLE 2 Initial conditions in the aquaria for the six groups of fishes Group

No. of fishes Water (1) Grams per fish Biomass (g 1-'1

1

2

3

4

5

6a + 6b*

10 5 0.78M.12 1.56

10 5 ' 0.8M.13 1.6

10 5 0.86f0.12 1.72

6 5 1.85M.7 2.22

6 5 1.65M.43 1.98

3x2 5x2 3.93f1.0 2.4

*Subdivided group.

pre-weighed living fishes, anaesthetized in an aqueous solution of 0.3 g 1-' of MS-222(Sandoz).Fishes were kept in inactive water while being counted. 5 ml samples of membrane (0.45 pm) filtered labelled water were used to measure lMCsconcentration in the liquid phase during the uptake experiments. Data are expressed in Bq g-' fresh weight of fish along with the 0.95 confidence interval. Concentration factors, CF,(the ratio Bq g-' (fish):Bq ml-' (water)),were computed considering the mean value of water radioactivity for all the uptake period. Retention, Rt, was computed considering the mean burden of the fish (Bq fish-'), eliminating the effect of biological dilution of radiocaesium due t o the weight increase of fishes. Retention data represent the percentage of the initial radioactivity of fishes during the elimination phase. Uptake and loss kinetic curves result from a treatment described by GarnierLaplace [la] and Badie et al. 1191, which is based on a multicompartmental analysis of retention. The constant parameters were estimated by a converging iterative process, based on the criterion of least squares. For this criterion, the accepted solution is the one by which the sum of squares of deviations (i.e. differences between experimental and estimated data) is minimum. The method requires the acceptance of initial values for those constants. Then the resulting function may be progressively optimized by successive trials where new values for the constants are tested, all trials converging to a h a 1 solution, which is the best fit. 2.1. Elimination

Loss functions were fitted to series of retention values R, = 100 (Q,/Qo),with Q, the average of the total radioactivity of fish (Bq fish-') at time t and Qo the initial radioactivity of specimens during the elimination phase. The adopted model is the general function: i=l

n

i=l L

n

399

The most common feature is a two compartment (n = 2) loss function:

R, = Ale-(Al' A P

+

+

Three parameters must be estimated, Al, hl and b. Al and Az:contribution of each compartment to the retention, with A2 = 100 - A1 ln2 hl and b:elimination rate constants of each compartment, with hi = -, Tbi Tbi being the biological half-life of the compartment i ln2 hp:decay rate of the radioisotope, h - -with Tpthe half life Tp

'-

2.2.Accumulation

The uptake functions were fitted to series of concentration factor data CF,= CJL, with C,the average concentration of radiocaesium in fish (Bq fish-') at time t, and L the radioactivity of the liquid phase (Bq ml-'), which was considered a mean value for the whole period of contamination. The adopted model is the function:

Two parameters must be estimated, B1 and B2(Al and h2 are estimated from the loss function). B1and Bz:accumulation constants (function of the species and of the radioisotope). G:exponential growth rate of fishes, assuming that the mass increase is well represented by the exponential function W,= Wo eGf,with Wo the initial weight. If no weight increase is verified, as may happen due to a rough adaptation of the specimens to the strict physical conditions of the experiment, the uptake function takes the form:

3. RESULTS AND DISCUSSION

3.1. Uptake

Caesium-134 concentration in fish during 4 weeks of direct uptake (Table 3) increased in all six groups but did not reach a steady state. With a low stable Cs' concentration (5.83-04 mg 1-'1 in the artificial medium (groups 1 , 2 and 31, radiocaesium concentration of the fish decreases with increasing K'concentration of the water. A similar result is obtained with low K ' concentration (5.83-04 mg 1-') and

400

TABLE 3 Caesium-134 concentration in water (w) and fish (0during uptake phase Days

3 7 10 14 17 21 24 27 28

Group1

Group 2

W

f

W

f

10.9 11.2 8.5 9.0 9.7 12.3 13.9

158.6f80.6 313.4f116.3 427.2f138.6 671.9f212.3 703.1f180.0 831.3f211.5 973.01t268.8

13.2 11.9 10.1 12.2 12.8 12.0 13.0

34.6f10.7 62.5f17.0 105.8326.0 142.4f32.5 179.9f46.3 252.2M3.9 298.3f69.9

11.7

1084.8f305.4

12.6

339.4f74.9

Group 4

3 4 7 9 10 14 17 18 19 21 24 28

Group 3

Group 5

W

f

11.9

136.5f56.3

13.2

210.0rt88.0

10.8 10.4

326.2f112.3 438.*191.2

12.5 12.0 9.3 13.4

434.2f165.9 423.1177.3 665.1f420.2 676.8f376.4

W

f

13.2 14.2 12.0 12.8 13.4 13.6 13.9 14.8

17.6f5.0 46.3f9.2 65.6f17.5 101.1f24.1 129.M27.4 160.9f34.4 225.4f44.3 229.2f29.8

Group 6

W

f

12.7

51.2f7.2

14.6

139.2f45.8

13.9 13.3

226.1f39.6 250.2f47.8

12.9 13.6 14.5

330.8f88.2 361.3f86.2 380.7f100.2

W

f

14.5

13.7f5.7

12.3

30.1f7.9

13.3 13.0

4 1.8f7.8 54.8f10.1

12.7

68.8f11.5

14.0 14.3 13.3

74.7f8.3 91.Ort12.2 98.2f14.6

w: Bq ml-'; f: Bq g-', fresh weight.

with stable Cs' as the major cation (groups 4,5 and 6).Figures 1and 2 show the experimental data and the adjusted uptake functions for groups 1,2,3and 4,5,6, respectively, Analysis of variance reveals that for CF,experimental data, variances within groups 1,2,3and 4,5,6are significantly different at the significance level of 0.95. For the first set of experiments, the CF's being inversely dependent on the K' concentration of water, at equilibrium (t approaching 3 years), they will be 426,96 and 50 respectively. These values are within the range quoted in the literature already mentioned. Although in these experiments an artificial medium was used, at 3.5ppm K'(concentration similar to that of the river) the estimated CF approaches the field CF [lo].

40 1

(k+]=0.35ppm A [k+]=3.5ppm

0

5

10

15

20

25

30

Days Fig. 1. Concentrationfactor kinetics for 134Csin three groups of freshwater bogue at different K' concentrations in water. 1. CF't = 419 (1 - e-0.0094+ 7 (1- e-0.1834;2. CFt = 96 (1 - e-0,0"4 + 0.15 (1 - e-0.1s13;3. CFt = 50 (1 - e-0,0134+ 1.3 (1 - e-0.114t

b ,m 5

100 3

c

0 .-w 2 w

10 :

c

8 C

0

0

1:

A [Cs+]=3.5 ppm

o ! 0

1

I

5

10

15

20

25

30

Days Fig. 2. Concentrationfactor kinetics for 134Csin three

oups of freshwater bo

Cs' concentrations in water. 4. CFt = 653 (1 - e-0,003r5.CFt = 227 (1 - ea. e-@.?l;6. CFt = 232 (1 - e4.001$+ 1.05 (1 - e-0.12s5.

different 854e at+ 0.24 (1 -

The dependence of CFs with the K' concentration of water (pprn), at a temperature of 20°C, shows the following trend:

CF,, = 228 [K+14.46 r2= 0.95 It must be emphasised that in th i s work only three different potassium concentrations were used. However, other authors 161 used only two concentrations,

402

representing the two extreme aquatic environments - fresh and saline saying that the general form of the equation they obtained was shown to be valid in other similar cases [121. A comparison of the results obtained for fish groups 1,2 and 3 (Fig. 1)and for groups 4,5and 6 (Fig. 21,shows that 13'Cs uptake is depressed either with an increase of soluble potassium, or with an increase of soluble stable caesium. Although stable caesium appears to depress radiocaesium uptake by fish more intensely than potassium does, at the normal K ' concentration in Tejo water, 3.5mg 1-' (group 2) and the same concentration of Cs'(group 41,CFs at the end of experiment are similar. Assuming good quality of the kinetic curves, the extrapolated CFs at equilibrium will be higher for groups 4,5and 6 than for groups 1,2and 3,once the estimated elimination rates of the former are lower. A similar statement has been mentioned by other authors 161. 3.2. Retention

Analysis of variance applied to the retention data (Table 4)reveals that groups 1,2,3are not significantly different, the same happening in groups 4,5,6.Nevertheless, results from both sets of experiments are significantly different. TABLE 4 Caesium-134 retention (%I in fish after uptake phase

Days

Group1

Group2

Group3

1 3 4 7 10 11 14 17 18 21 28 35 36 38 41 42 43 47 49

97.9 95.4

98.8 92.8

99.3

91.4 85.3

82.9 80.7

85.0 81.5

73.9 72.4

79.7 73.9

70.7 64.2

90.4 86.3 81.5 76.1 73.3 70.0 61.3 57.6

68.4 54.5 60.6

Group4

Group5

Group6

98.4

95.4

97.8

98.1 97.3

92.8 90.7

96.9 93.8

97.5 93.9

89.2

92.8 92.6

86.1

93.5

82.9

92.5

93.0 92.7 89.9

52.6

83.0

48.3

85.0

92.6 80.1 77.1

90.9

403

L.l

1

c

.-0 c al

3

[k+]=0.35 ppm

!

10.0

0

I

10

20

30

50

40

Days Fig. 3. Caesium-134 retention curves of grou 1 (0.35 ppm ) ' K and group 4 (0.35 ppm Cs'). 1. Rt = 6 e-0.183t+94 e4.009~4. Rt = 100 e4." 4

P

100.o

C

0 .e

c

b) e

2

10.0

4

0

I

10

20

30

40

50

Days Fig. 4. Caesium-134 retention curves of group 2 (3.5 ppm K ) and group 5 (3.5 ppm (2s'). 2. ' 86 e4.01': 5. Rt = 3 e-9.6t+ 97 e-0.0°54

Rt = 14

The retention experiment showed, for groups 1,2,3, that the external K ' concentration does not affect radiocaesium elimination. Actually the biological half-lives of 53-77 days are within the values quoted [3,6,8,10,121. Caesium-134 retention is very strong when the highest ion external concentration is that of stable caesium instead of potassium. Actually comparing both retention experiments (Figs. 3-5) it is possible to say that stable caesium is less efficient'than potassium in the removal radiocaesium. In fact, comparing what we might consider as being the 'inversely homologous' groups, i.e., 1us. 4,2 us. 5 and 3 us. 6, all the long-term retention components of groups 4 , 5 and 6, exhibit longer biological half-lives than their respective pairs, as is shown in Table 5.

404 100.0

h

E

10.0

-I 0

I

10

20

30

1

I

40

50

Dars Fig. 5. Caesium-134 retention curves of group 3 (36ppm ) ' K and group 6 (35 ppm Cs'). 3. Rt - 11 e-0.114t+ 89 e-0.013t, 6. Rt = 7 ,-0.126t+ 93 e-o.oOlt

TABLE 5

Biological half-lives of 134Csin fishes submitted to different K+:Cs+balances in water Group

[CS+l (PPm)

(PPd

WI

Tbl (days)

Tbz (days)

5.83-4 5.83-4 5.83-4 0.35 3.5 35

0.35 3.5 35 5.83-4 5.83-4 5.83-4

3.8 4.3 6 0.07 5.5

77 63 53 203 139 693

One possible explanation is that practically no more exchange is possible between the radiocaesium in fish and the potassium in water, as in this case it is only in a tracer amount, and fish must keep the internal K+ constant (homeostatic regulation). On the other hand, observations made by Williams [XI, although in phytoplankton, could suggest a kind of toxic effect, but there was nothing in fish behaviour pointed to such an effect. 4. CONCLUSIONS

According to the proposed objective, it appears that the [K+l/[Cs+lratio is determining the 134 Cs uptake by fishes, and there seems to be a resemblance in the behaviour of Cs' and K+when their relative concentrations in the medium are inverted. The high stable caesium concentrations in the medium

405

cause a decrease of the radiocaesium concentration factor, but in the long term the decrease brought about by potassium is stronger. Results suggest that, at a temperature of 2Oe0C, the elimination of radiocaesium by fish is independent of the external potassium concentration.These results also suggest a stable caesium discrimination by fish physiology. 5. REFERENCES 1. Blaylock, B.G., 1982. Radionuclide data bases available for bioaccumulation factors for freshwater biota, in: R.O. Chester and C.T. Garten, Jr. (Ed.), Environmental Effects. pp. 427-438. 2. Fleishman, D.G., 1973. Accumulation of artificial radionuclides in freshwater fish, in: D. Greenberg (Ed.), Radioecology. Wiley, New York, pp. 347-370. 3. Preston, A., D.F. Jefferies and J.W.R. Dutton, 1967. The concentrations of Caesium-137 and Strontium-90 in the flesh of Brown Trout taken from rivers and lakes in the British Isles between 1961and 1966: the variables determining the concentrations and their use in radiological assessments. Water Res., 1:475-496. 4. Carlsson, S., 1978. A Model for the Turnover of 137Csand Potassium in Pike (Esox lucius). Health Phys., 35: 549-554. 5. Lebedeva, G.D., 1966. The effect of different salt composition of the water on the accumulation and excretion of Caesium-137 by freshwater fish. Radiobiologiya, 6: 556-559. 6. Srivastava, A., H.O. Denschlag, 0. Kelgerg and K. Urich, 1990. Accumulation and discharge behaviour of 137Csby Zebra Fish (Brachidaniorerio) in different aquatic environments. J. Radioanal. Nucl. Chem. Art., 138 (1):165-170. 7. Jinks, and M. Eisenbud, 1972. Concentration factors in the aquatics environment. Radiat. Data Rep., 13(5): 243-247. a. Foulquier, L., 1979. Etude bibliographique sur la capacite et les modalites de la fixation du radiocesium par les poissons. CEA-BIB-231(2), p. 360. 9. Foulquier, L., M. Pally, B. Descamps, Y. Baudin-Jaulent and A. Lambrechts, 1979. Etude Radioecologique du Rhone Moyen. Essay #Interpretation des Mesures de 1’Activite des Poissons. 2eme Symposium International de Radioecologie, 19-22 June, 1979, Cadarache (France). Comissariat a 1’EnergieAtomique. 10. Carreiro, M.C.V. and M.M. Sequeira, Cesium-137 in the Portuguese Rivers Douro and Tejo. J. Environ. Radioactivity, 5: 363-377. 13.. Corisco, A.G. and M.C.V. Carreiro, 1991. 134Cstransfer from water and food to the Cyprinid Tinca tinca L.: Uptake and loss kinetics, LNETYDPSR-A no. 2 (IIIsBrie), p. 16. 12. Hewett, C.J. and D.F. Jefferies, 1976. The accumulation of radioactive caesium from water by the brown trout (Salmo trutta) and its comparison with plaice and rays. J. Fish Biol., 9: 479-489. 13. Morgan, F., 1964. The uptake of radioactivity by fish and shellfish. I 134 Caesium by whole animals. J. Mar. Biol. Assoc. UK, 44: 259-271. 14. Kolehmainen, S.E., 1972. The balances of 137Cs,Stable cesium and potassium of bluegill (Lepomis macrochirus Raf.) and other fish in White Oak Lake. Health Phys., 23: 301415. 15. Williams, L.G., 1960. Uptake of Cesium-137 by cells and detritus of Euglena and Chlorella. Limnol. Oceanogr., 5: 301-311.

406 16. SaxBn, R., 1990. Radioactivity of Surface Water and Freshwater Fish in Finland in 1987. Report STUK-A, Suppl. 3 to Annual Report STUK-A74, pp. 59. 17. Elliot, J.M., J . Hilton, E. Rigg, P.A. Tullett, D.J. SwiR, D.R.P. Leonard, 1992. Sources of variation in post-Chernobyl radiocesium in fish from two Cumbrian lakes (north-west England). J. Appl. Ecol., 29: 108-119. 18. Garnier-Laplace, J., 1991. gtude des MBcanismes de Transfert de 1'Argrent-ll0m en Eau Douce (PhD. Theses, UnivBrsit.6 Montpellier II), Rapport CEA-R-5549, p. 198. 19. Badie, C., M. Belluau, J.M. Fernandez and G. Gontier, 1985. Transferts aux Organismes Marins: Analyse et Synthkse des Exp6rimentations Menbes au Laboratoire de RadioBcologie Marine de Toulon, Rapport CEA/EDF, p. 122.

Freshwuter und Estuurine Rudioecology Edited by G. Desmet et nl.

1997 Elsevier Science B.V.

407

Polonium-210 in mussels and fish from the Baltic-North Sea estuary Henning Dahlgaard Ris0 National Laboratory, DK-4000 Roskilde, Denmark

ABSTWCT Polonium-210 has been measured in Danish fish meat caught in the North Sea, the Kattegat and the Baltic in 1991-1994. Average values of 0.35,0.65 and 0.96 Bq zlOPo kg' fresh weight were observed for cod, herring and plaice fillets, respectively. The difference between species is statistically significant, whereas no effect of salinity could be observed. There is a high variation, giving SD values in the range 70-100%. Mytilus edulis soft parts were analyzed for zlOPofrom 11Danish locations ranging from full North Sea salinity to Baltic 8%0water. Signficantly increasing zlOPoconcentrations with a decreasing "condition index" were observed. Concentrations a t two former phosphate industry sites were not statistically different from the other locations. The average zlOPoconcentration in the Mytilus edulis soft parta was 149 Bq kg-' dry & 55% SD (n = 41). The present levels of zlOPoin fish and mussels may represent a natural baseline.

Journal of Environmental Radioactivity, 32 (1966)91-96.

Freshwurer und Estuurine Rudioecolrigy Edited by G. Desmet et al.

0 1997 Elsevier Science B.V. All rights reserved

409

Uptake of polonium-210 by mussels from effluents emitted by different phosphorus plants R.M.J. Penndersa, M.P.M. Janssena, H.W. Kostera, J.F.M.M. Lembrechtsa, H. Hummelb, P.G. Schoutb and B.M.H. Timmermansb aNational Institute of Public Health and Environmental Protection, Laboratory of .Radiation Research (RNM-LSO),P.O. Box 1,3720 BA Bilthouen, The Netherlands b ~ A W - N I O IOCEMO Vierstraat 28, 4401 EA Yerseke, The Netherlands

ABSTRACT The uptake of zlOPoby mussels (Mytilus edulis) exposed to effluents from different phosphorus plants was studied as a function of time in continuous flow systems in winter and summer. The background concentration observed in mussels caught in winter was twice that for mussels caught in summer; exposure to effluents resulted in comparable differences between winter and summer. Analysis of variance, with weight as covariable, revealed that these differences could be attributed partly to differences in weight. The uptake of 210Powas linear throughout time, which indicated that the excretion rate is low. The uptake rates differed considerably between the effluents in both seasons. Comparison of the concentration factors shows an effect of the matrix upon uptake, which is most apparent from the data on 210Po(N03)~.210Po added as 210Po(N0&is more readily available than zlOPoin the effluents.

1. INTRODUCTION

Production of fertilizers from phosphate rock will result in discharges into water and air of the enclosed naturally occurring radionuclides,the concentrations of which are enhanced in comparison to those of normal soils and sediments 111. Two basically different production processes are used in the Netherlands: in the wet process, phosphoric acid and gypsum are produced by treating ground rock with sulphuric acid, whereas in the thermal process, elemental phosphorus and slag are produced by heating the rock material. With regard to the overall chemical composition of the effluents and their load with radionuclides there are considerable differences between the two production processes [2,3].

4 10

In Dutch gypsum effluents, which contain up to 30% of solids, 226Ra,210Poand "OPb are nearly in equilibrium at levels up t o 1000 Bq kg-' dry matter [4,5], whereas in liquid effluents from a thermal plant, which contain hardly any solids, levels of 210Povary between 4000 and 7000 Bq m3 and are an order of magnitude greater than those of '"Pb 131. Since the radiation dose to humans from effluent discharges into the marine environment is mainly due to 'loPo stored in molluscs and shrimps [6,71 our query focused on the influence of the source of the effluent on 'loPo accumulation by mussels (Mytilus edulis).The relative importance of the physiological condition of the animals forms a second point of interest of this study. This is because earlier investigations showed considerable fluctuations in the concentration of 'loPo in mussels and winkles collected at the same site but at a different time [8,9]. Changes in the environmental concentrations as well as in the physiological activity of the mussels may have contributed to these fluctuations. As a result, in the experiments reported on below, groups of mussels have been exposed in continuous flow systems to estuary water spiked with 'loPo from a different origin both in winter and in summer. 2. MATERIALS AND METHODS

Experiments with mussels (Mytilus edulis)were carried out in February and September in East Scheldt water (salinity ~30%)which was collected 1 or 2 days before the start of the experiments and to which different effluents were added. Fresh algae (Phaeodactylurn cornuturn) equivalent to 2 mg dry matter per litre were added as food. In winter experiments were carried out with effluent from a thermal process plant (HT), phosphogypsum eMuent (PT), filtered (0.45 pm) phosphogypsum effluent (PD) and without an additional 'loPo source (CONT).In summer the filtered effluent was replaced by a treatment in which a '~'Po(NO~)~ solution (DIS) was used. PT was collected at different plants for the winter and summer experiment at the start of the experiments. Time proportional effluent samples were collected weekly from one thermal process plant during both experimental periods. All effluents were diluted to obtain a feasible solution which still contained a reasonable 'loPo concentration: PT was diluted 1000-fold, PD 100-fold and HT 10-fold. The diluted effluents were pumped into 14-1aquaria at an average speed of 12 1d-', except for the PD treatment which had a percolation rate of 36 1d-', because of PDs low "OPo content. The solutions were aerated and the diluted effluentswere gently stirred to keep suspendedmatter well-mixed.The experiments were carried out at 6°C in February and 15°C in September. Each aquarium contained 12 mussels which had been gathered in the western part of the East Scheldt (location NL 51"33', EL 4'00'). Animals with a shell length of 5-7 cm were acclimatized for at least three days. For all treatments water and mussel samples were taken from three aquaria after one

411

month. AEter both 10 and 20 days two additional aquaria were sampled for HT and PT. Reference samples were taken at the start of each experiment to quantify the background concentration of 'loPo. The soft parts of the mussels were freeze-dried and weighed individually (kmg). The condition of the animals, represented by the condition index - dry weight of soft parts in mg cm3 (shell length) - was determined. After being lumped into one sample per aquarium they were homogenized with an agate mortar prior to analysis for 'loPo. The aqueous samples (e.g. subsamples of HT, samples from the in- and outflow water of the aquaria) were acidified and spiked with "'Po as internal standard. Samples were stored at 6°C.Suspended matter was collected through filtration with a 0.45 pm millipore filter, faeces were collected with a pipette followed by filtration with a 80 pm millipore filter. Filtered residues (suspended matter, faeces) were freeze dried, and weighed before 'loPo analysis. PT was dried by heating subsequently at 90 and 105°C. Dry phosphogypsum was homogenized in a mortar. Polonium was concentrated from hardly contaminated water samples by iron(II1)hydroxide precipitation. Solid materials were digested with mineral acids after addition of 'O'Po as an internal standard. Po was precipitated from weak acid solutions with hydroxylammonium chloride onto small silver discs. The activity on the discs was determined with surface barrier detectors coupled to a multichannel analyzer. The start of the experiment has been used as reference date for decay correction. Direct measurements of 'l0Pb with a planar Cfe-detector were used to correct for the ingrowth of 'loPo from 'lOPb. Uptake as a function of time was described by regression analysis for each treatment separately. For the analysis of variance concentrations were ln-transformed to achieve homogeneous variation. Differences between the concentrations of the mussels at the end of the experiments were tested with a one-way analysis of variance for both seasons separately and were followed by Tukey's pairwise comparisons of means as a posteriori comparisons. One-way analysis of variance with season as variable and weight as covariate were applied to the reference samples and the control treatment separately. A two-way analysis of variance was applied to the data of PT and HT with season and treatment as independent variables and weight of the samples as a covariate [lo]. 3. RESULTS

The concentrations of 'loPo in mussel samples will first be given as such. Subsequently these data will be expressed as a function of the concentration in the water-effluent mixtures supplied (Bq 1-') and of the daily gift. A significant increase in the concentration of 'loPo throughout the experiment was observed in mussels in the PT and HT treatments in both experimental periods, and when added as P0(NO3I2,which was tested in summer. No significant change was observed in the control and PD treatment (Table 1).The rate of increase in concentration was high for HT in winter and comparable to

412 TABLE 1 Results of a regression analysis of the 'loPo concentration in mussels (Bq kg' dry weight) a~ a function of time (d) for exposure to different effluents (PT, PD, HT, C O W and DIS) in winter and summer Treatment

PT PD HT CONT DIS

Winter

Summer

P

Equation

P

Equation'

0.000

conc. = 263 + 6.48.t

0.046

conc. = 127 + 1.51.t

conc. = 234 + 66.5.t

0.000 0.388 0.000

conc. = 108 + 9.21.t

0.595 0.000

0.514

conc. = 121 + 64.54

'Equations are only given when the concentration increases significantly, as indicated by a Pvalue

5 0.05.

that for 210Po(NO&in summer. The increase in the 'loPo concentration in M. edulis can be described by linear regression. Polonium-210 concentrations in mussels of different treatments differed considerably after 30 days of exposure. In winter the highest concentrations were observed for HT; IYT also differs significantlyfrom the control. In summer 'loPo concentrations in mussels exposed to PT, HT and Po(N03)' differed significantly from those of the control treatment, but also among treatments significant differences were observed (Table 2). The condition of the mussels, expressed by means of the condition index, was much higher in summer due to increase in weight during the previous months. The mean condition index of the reference samples was 4.14 in winter and 6.99 mg cm9 in summer, mean weights of the soft parts were 0.65 and 1.32 g for TABLE 2

Mean 'loPo concentrations (Bq kg-' dry weight) in mussels after exposure to different effluents for one month in winter and in summer, with 95% confidence intervals (n = 3,n = 2 in reference) in parentheses. Means sharing a common letter (a,b,c,d) do not differ significantly a t the 5%level from other means within the same season (Tukey's painvise comparisons of means)

Ref.

PT PD

HT CONT DIS

Winter 210Po(Bq kg-')

Summer 210Po(Bq kg-')

263 464 (114)b 271 (72)a 2330 (1694)c 240 (180)a

121 (161) 172 (9)a 397 (155)c 114 (22)b 2060 (585)d

413 400

3

winter

300

-0

cn

5 0

m,

200

A

reference

8

control

8

summer

>.

+ .>

.-+ 0

la

A

reference

0

control

100

0

0

5

10

15

20

weight (9) Fig. 1. Relation between 21%'o concentration and weight of mussels in reference and control samples in winter and summer.

winter and summer, respectively. The 'loPo concentration in reference mussels collected in winter was twice that measured in summer. A significant difference between the seasons was also observed for the other treatments, which were studied both in winter and summer (Table 2). Weight was shown to be an important variable in explaining the seasonal differences in concentration (Fig. 1).Seasonal differences in the reference samples and in the control samples were not significant when weight was used as covariate in the statistical analysis. Differences between the seasons remained in the PT and HT samples after correction for weight and can probably be attributed to differences in concentration and composition of the effluent. Subsequently, the data were expressed relative to the 'loPo concentration in water, as considerable differences existed between some of the treatments. Polonium-210 concentrations based on the fraction of 210Pobound to suspended matter were used for correction instead of the total 210Poconcentration. There is a large variation in concentration factors between the different treatments, expressed in Bq g-'/Bq l-', ranging from 2000 to 85,000 (Table 3). Concentration factors appear to be high in the treatments with a low exposure and low in treatments with a high exposure. The concentration factors for PT, for example, are comparable to those found for HT, which indicates that differences in concentration can be mainly attributed to differences in exposure. Polonium210 from the solution spiked with 210Po(N03)2 (DIS) seems to be accumulated more efficiently than from either PT or HT.

4 14 TABLE 3 Concentration of 'loPo bound to suspended matter (in Bq 1-l) and mean concentration factors (CF) plus 95% confidence intervals (in parentheses) calculated from 'loPo concentrations in mussels at the end of the experiment for the different treatments. Concentration factors are calculated by dividing 'loPo concentrations in mussels by 'loPo concentration bound to suspended matter

PT

PD

HT CONT DIS

Winter 'loPo (Bq 1-'1

CF

Summer 'loPo (Bq 1-'1

CF

0.062 0.006 0.274 0.003

7480 (1831) 46,200(12,000) 8490 (6190) 79,900(59,800)

0.060

2880 (151)

0.226 0.001 0.279

1750 (684) 87,300(16,700) 7380 (2090)

EZZI

0winter

summer

7 20

400

240

PT

PD

HT

PT

DIS

HT

treatment Fig. 2. Increase in ''% concentration in relation to load (in Bq kg-' per Bq d-') for different treatments in winter and summer. Mean values with 96% confidence limits.

Finally, the ''Po concentrations in the mussels are expressed as a function of the daily gifk (in Bq bound to suspended matter per day), since apart from the 'loPo concentration, treatments differed in flow rate as well. The concentration factor of HT and PT,expressed in Bq g-%q d-', differs significantly from that of PD, but not from that of the control in winter. In summer all treatments differ significantly from each other (Fig. 2).

415

4. DISCUSSION

Marine organisms are known to accumulate large amounts of naturally occurring 'loPo and have been recognized as a potential uptake route for human exposure [6,11]. However, data on mussels and other shellfish are scarce and information on the enhancement of naturally occurring 210Poas a result of phosphate-rock processing industries has only become available recently [7-91. Background concentrations between 111 and 459 Bq kg-' dry weight have been reported for mussels from different locations in Europe by McDonald et al. [12], who concluded that these values would represent the natural background concentrations. Concentrations of 114 to 523 Bq kg-' dry weight were found on different sites in the UK [81, whereas a slightly higher concentration of 555 Bq kg-' dry weight was mentioned for mussels ( M . galloprovincialis) from Portugal [13].Our results generally agree with these data, concentrations in reference and control samples varying between 100 and 250 Bq kg-' dry weight. Accumulation of 210Poin mussels could be described by linear regression, which indicates that excretion of 2'0Po is relatively low and consequently biological half life long. Our results show that mussels (M. edulis) are capable of rapidly accumulating 'loPo up to concentrations of 2000 Bq kg-' dry weight, being 10-fold the initial concentration, within a period of one month. In experiments with fish and with the shrimp Lysmata seticaudata 2'0Poconcentration within the organisms was clearly regulated. Biological half lives of 2.8-4.2 days were calculated for anchovy, 7.8-11 days for pilchard and 7-28 days for the shrimp [14,151.The difference in half-life should be considered when interpreting data from the field. As a consequence of the low excretion rate in mussels a decrease in concentration can be attributed mainly to radioactive decay of 'loPo (Ty2= 138 days) in contrast to anchovy, pilchard and shrimp in which the decrease in concentration can mainly be attributed to excretion. A concentration factor of 10,000 for 'loPo uptake by molluscs has been recommended by the IAEA [16].A concentration factor of 25,800 was calculated on the basis of field samples for mussels captured in the Irish Sea [17]. The concentration factors calculated from our reference samples and control treatment (Table 3) appear to be relatively high compared to reported values. The concentration factors of the different treatments are lower than the values reported above, which can be attributed to the fact that concentration factors tend to decrease with increasing environmental concentrations and to the fact that equilibrium has not yet been reached in the experiments. We observed a two-fold difference in ''Po concentration both in reference mussels and the control between winter and summer (Fig. l),similar differences were observed in the other treatments (Fig. 2). Seasonal differences have been observed for several elements in marine organisms. Concentrations oRen tend to be high in autumn and winter and low in spring and summer, although

4 16

deviations from this pattern have also been found [18-201. Highest 'loPo concentrations in mussels were observed in winter and spring [9], whereas 'loPo concentrations in winkles showed to be the highest in summer [8]. Seasonal variation in our samples could be explained by differences in weight. Boyden and Phillips 1191 attributed the seasonal variation of eight elements in oyster also to changes in the weight of its soft parts. Concentrations often tend to decrease with weight in shellfish and are generally described by numbers raised to powers [211. Our results generally agree with this pattern. Mussels exposed to HT showed a higher uptake than those exposed to PT, uptake from DIS was even higher than from HT (Table 1).The differences remained after correction for concentration and load (see Table 3 and Fig. 2), which indicates that uptake could partly be attributed to matrix effects. As the data on '~'Po(NO~)~ clearly show that also matrix effects may appear, more investigations on the effects of matrix on uptake are recommended. Further variance in 'loPo concentration in mussels is introduced by season of sampling, which attribute to about a 2-fold difference in concentration. In calculating mean dose to man due to consumption of mussels, season should be taken in account. The 'loPo concentration in mussels from field sites will largely be determined by concentration in the effluents. Calculations using the data on the effluents revealed that a similar dilution of PT and HT effluent will result in a much higher uptake of 'loPo by mussels in the PT effluent in both seasons. 5. ACKNOWLEDGEMENTS

This research was supported by the Radiation Protection Programme of the

European Communities under contract no. FI3P-CT92-0035.The authors are grateful to colleagues from the Centre for Mathematical Methods (RNMCWM) for useful suggestions on the statistical analysis and Mrs R de WijsChristensen for editing the manuscript.

6. REFERENCES UNSCEAR, 1982. Report of the United Nations Scientific Committee on the Effects of Atomic Radiation to the General Assembly. United Nations, New York, pp. 113-117. 1991. Study of the radionuclides contained in wastes produced by BaetslB, L.H., the phosphate industry and their impact on the environment. Report No. EUR13262, CEC, Brussels, 83 pp. Pennders, R.M.J., H.W. Koster and J.F. Lembrechts, 1992. Characteristics of Po-210 and Pb-210 in effluents from phosphate producing industries: a first orientation. Radiat. h o t . Dosim., 45: 737-740 Woittiez, J.R.W., 1992. De bepaling van de doorzet aan natuurlijke radioactiviteit bij de fosforzuurfabricage volgens het natte proces. 1.Defosforzuur van Hydro Agri Rotterdam te Vlaardingen. IRI, Delft, 25 pp.

417

5. Woittiez, J.R.W., 1992. De bepaling van de doorzet aan natuurlijke radioactiviteit bij de fosforzuurfabricage volgens het natte proces. 2. De fosforzuurfabriek van Kemira Pernis BV te Rotterdam. IRI, Delft, 27 pp. 6. Koster, H.W., H.P. Leenhouts, A.W. van Weers and M.J. Frissel, 1985. Radioecological model calculations for natural radionuclides released into the environment by disposal of phosphogypsum. Sci. Total Environ., 45: 47-53. 7. Koster, H.W., P.A. Marwitz, G.W. Berger, A.W. van Weers, P. Hagel and J. Nieuwenhuize, 1992. zlOPo,zlOPband 226Ra in Dutch aquatic ecosystems and polders, anthropogenic sources, distribution and radiation doses. Radiat. Prot. Dosim., 45: 715-719. 8. Rollo, S.F.N., W.C. Camplin, D.J. Allington and A.K. Young, 1992. Natural radionuclides in the UK marine environment. Radiat. Prot. Dosim., 45: 203-209. 9. Germain, P., G. Leclerc and S. Simon, 1992. Distribution of zlOPoin MytiZus eduZis and Fucus vesiculosus along the channel coast of France; Influence of industrial releases in the Seine river and estuary. Radiat. Prot. Dosim., 45: 257-260. 10. Sokal, R.R. and F.J. Rohlf, Biometry. 2nd edn. W.H. Freeman, San Francisco, CA, 859 pp. 11. Cherry, R.D. and M. Heyraud, 1982. Evidence of high natural radiation doses in certain midwater oceanic organisms. Science, 218: 54-56. 12. McDonald, P., S.W. Fowler, M. Heyraud and M.S. Baxter, 1986. Polonium-210 in mussels and its implications for environmental alpha-autoradiography. J. Environ. Radioactivity, 3: 293-303. 13. Carvalho, F.P., 1988.zlOPoin marine organisms: A wide range of natural radiation dose domains. Radiat. Prot. Dosim., 24: 113-117. 14. Cherry, R.D., M. Heyraud and A.G. James, 1989. Diet prediction in common clupeoid fish using polonium-210 data. J. Environ. Radioactivity, 10: 47-65. 15. Caravalho, F.P. and S.W. Fowler, 1993. An experimental study on the bioaccumulation and turnover of polonium-210 and lead-210 in marine shrimp. Mar. Ecol. Prog. Ser., 102: 125-133. 16. IAEA, 1985. Sediment Kds and concentration factors for radionuclides in the marine environment. Technical Report Series no. 247, IAEA, Vienna, 71 pp. 17. McDonald, P., M.S. Baxter and S.W. Fowler, 1993. Distribution of radionuclides in mussels, winkles and prawns. Part 1. Study of organisms under environmental conditions using conventional radio-analytical techniques. J. Environ. Radioactivity, 18: 181-202. 18. Bryan, G.W., 1983. The occurrence and seasonal variation of trace metals in the scallops Pecten maximus (L.) and Chlamys opercularis (LA J. Mar. Biol. Assoc. U.K., 53: 145-166. 19. Boyden, C.R. and D.J.H. Phillips, 1981. Seasonal variation and inherent variability of trace elements in oysters and their implications for indicator studies. Mar. Ecol. Prog. Ser., 5: 29-40. 20. Amiard, J.C., C. Amiard-Triquet, B. Berthet and C. Metayer, 1986. Contribution to the ecotoxicological study of cadmium, lead, copper and zinc in the mussel Mytilus edulis. I. Field study. Mar. Biol., 90: 425431. 21. Boyden, C.R., 1977. Effect of size upon metal content of shellfish. J. Mar. Biol. ASSOC.U.K., 57: 675-714.

Freshwuter und Estuurine Rudioecology Edited by G . Desmet et al. 1997 Elsevier Science B.V

419

Polonium-210 uptake by Mytilus edulis (L.) in Irish estuarine and inshore waters T.P. Ryan, A.M. Dowdall and A.T. McGarry Radiological Protection Institute of Ireland

ABSTRACT Polonium-210 is present in the Irish estuarine and inshore environments due to atmospheric deposition, erosion, the outgassing of radon from sub-marine geological formations and the input of radium-rich phosphogypsum from the fertiliser industry. As the edible sedentary filter-feeder Mytilus edulis (L.), the common mussel, concentrates zlOPo,it provides a significant pathway for the nuclide into the food chain. In March 1993 a sampling programme was initiated with the objectives of: (i) establishing the variation in zlOPoconcentration in mussels around Ireland; (ii) examining seasonal variations and (iii) studying the effect of mussel size on zlOPocontent. The concentration of 210Poin mussels around the coastline ranges between 80 Bq kg-' and 459 Bq kg' (dry flesh weight). There is some evidence for a seasonal variation in concentration. There is a significant linear relationship between the zlOPocontent and the dry matter content of the mussel at the location examined. 1. INTRODUCTION

Mussels have been used as sentinel organisms in environmental watch studies where the emphasis has been on non-radioactive pollutants (Phillips, 1976). The development of the nuclear industry has given rise to interest in their ability to concentrate radioactive pollutants such as plutonium and americium (Goldberg et al., 1978;Mitchell et al., 1986)and also to the important role they play in introducing these elements into the food-chain (Pentreath and Allington, 1988;Crowley et al., 1990;Rollo et al., 1992).Sources of radioactivity to the marine environment exist other than the nuclear industry. Polonium210,a member of the uranium decay series, is an alpha particle emitter which decays with a half-life of 138.4days to stable lead. It is introduced into the marine environment by: (1)the fallout or rainout of airborne particles or gasses from the troposphere; (2) sediment transport from rivers; (3)leaching of radium from sediments and (4)the outgassing of radon from sub-marine geological

420

formations.These background or 'natural' levels of polonium can be augmented by the discharge of radium-rich phosphogypsum which is a by-product of the fertiliser industry. A number of such industries have been active in Ireland but production of phosphogypsum has now ceased. This study examines: (i) the variation in 'loPo concentration in mussels around Ireland; (ii)seasonal variations in 21"Poconcentrations in mussels and (iii) the effect of mussel size on 'loPo content. 2. SAMPLING

Mussels were collected from 26 locations around the island of Ireland between March 1993 and January 1994to establish the variation in 'loPo concentration. Sites were selected in a river estuary (Waterford),in loughs (Carlingford and Belfast), along exposed coast (Dunquin) and in proximity to fertiliser plants (Belfast and Cork) (Fig. 1).

Fig. 1. The variation of 21%'o concentrations in mussels around Ireland.

42 1

A mussel bed at Sutton, north of Dublin, was chosen for a study of (a) seasonal variations in concentration and (b) the relationship between mussel size and polonium content A minimum of 50 mussels were collected from each site in the size range 5.5-6.5 cm where possible. At locations where mussel sizes were smaller, a similar size range about the mean was taken. Ten specimens were randomly selected from each sample to determine the mean length, wet and dry flesh weights and shell weight. The remaining sample was then dried and homogenised. Water samples (251) were taken each month from Sutton over the five month period between October 1993 and February 1994. 3.ANALYSIS

A gramme of each mussel sample was spiked with zOgPO yield monitor and digested in nitric and hydrochloric media using a Prolabo MAXIDIGEST MX 350 micro-wave digestion system. Polonium was then spontaneously deposited on to silver discs using a variation of the method described by Flynn (1968), before being measured by alpha spectrometry. The supported polonium was determined by measuring the 'loPb concentration using a LOAX semi-planar gamma spectrometer. Water samples were filtered, acidified, spiked and polonium was precipitated with permanganate. The precipitate was dissolved in 0.3M hydrochloric acid and the polonium spontaneously deposited on to silver discs as before.

4.RESULTS AND DISCUSSION The concentration of 'loPo in the dry flesh of mussels around the coast of Ireland was found to range between 80 Bq kg-' (sampling date: 30/6/93,mean shell length: 5.8 cm) at a site near Belfast and 459 Bq kg-' (sampling date: 26/3/93, mean shell length: 4.5 cm) at Dunquin (Fig 1). Expressed in terms of mean activity per mussel, the concentrations were found to range between 0.05 Bq mussel-' (sampling date: 17/6/93, mean shell length: 3.3cm) at Arklow and 0.34 Bq mussel-' (sampling date: 3/3/93, mean shell length: 7.1 cm) at Achill Island. The explanation for these variations is, as yet, unclear but proximity to fertiliser plants does not appear to play a significant role. There is some evidence for suggesting the existence of a seasonal variation in the 210Poconcentration in mussels from Sutton. Mussels were sampled from Sutton at monthly intervals, standardizing on mussels in the narrow size range between 5.5 and 6.5 cm (shell length). While the concentration of 'loPo remained relatively constant between June and November with a mean value of 179f30Bq kg-', it peaked in December at 246f16 Bq kg-' (Fig. 2)and a general trend of increasing mean 'loPo content was observed between June and November

422

300

"

I I

T

Month (1993)

ocl

Dec

Fig.2. Temporal variation of 21*o concentration in mussels at Sutton.

(Fig. 3). Whether or not these variations are seasonal can only be established by examining the changes over a number of annual cycles. In a separate experiment to examine the relationship between mussel dry flesh weight and 'loPo content, a large mussel sample was taken from Sutton. The mussels were grouped into six different size classifications and analyzed for zlOPo.A linear regression analysis between mussel dry flesh weight and activity per mussel yielded a Pearson's correlation coefficient (12) of 0.98,with slope 0.15 and intercept 0.04(Fig. 4). Furthermore, taking into account the mussel samples from the seasonal variation study and repeating the regression analysis with the extra data, the high degree of correlation was maintained. The correlation between 2'oPo content and dry weight content was not preserved between different sites (r2= 0.02). It was observed that over the 5 month period between October 1993 and February 1994,the polonium content in the filtered waters of Sutton did not vary significantly (200-385 mBq ma) suggesting a relatively constant rate of supply to the site over that period. It is known that as the available polonium content of water increases, the concentration in mussels also increases (Pennders et al., 1994).It is tentatively suggested therefore, that a significant increase or decrease in available polonium in Sutton could be detected as a deviation from the dry flesh weight/polonium content relationship established in Fig. 4.

423

DK

OCl

Aug

JUn

Month (1993)

Fig. 3. Temporal variation of 'l%o content of mussels at Sutton.

0.6

I

0

T

0.5

1

1.5

2

2.5

Mean Dry Flesh Weight/Mussel (9)

Fig.4. Variation of 'l%o content with mussel dry flesh weight at Sutton.

3

3.5

424

5. ACKNOWLEDGEMENTS

This research was supported by the Nuclear Fission Safety Programme of the European Community under contract number F13P-CT92-0035. The authors would like to gratefully acknowledge the Department of the Environment in Northern Ireland for their cooperationin sampling in Northern Ireland. 6. REFERENCES 1.

2. 3.

4.

5.

6.

7. 8.

Crowley, M., P.I. Mitchell, J. O'Grady, J. Vives, J.A. Sanchez-Cabeza, A. VidalQuadras and T.P. Ryan, 1990. Radiocaesium and plutonium concentrations in Mytilus edulis (L.) and potential dose implications for Irish critical groups. Ocean Shoreline Manage., 13: 149-161. Flynn, W.W., 1968. The determination of low levels of polonium-210 in environmental materials. Anal. Chim. Acta, 43: 221-227. Goldberg, E.D., V.Y. Bowen, J.W. Farrington, G.H. Harvey, J.H. Martin, P.L. Parker, R.W. Risebrough, W. Robertson, E. Schneider and E. Gamble, 1978. The mussel watch. Environ. Conserv., 5 (2): 101-124. Mitchell, P.I., J.A. Sanchez-Cabeza, A. Vidal-Quadras and J.L. Font, 1986. Plutonium in Mytilus edulis from Galician Rias. In: Actas de las I1 Jornado Sobre Fondo Radioactivo Ambiental de la Sociedad Espanola, Barcelona 12-13 May 1986, Sect. 2.4, 1.8. Pennders, R.M.J., H.W. Koster, J.F.M.M. Lembrechts, M.P.M. Janssen, H. Hummel, P.G. Schout and B.H.M. Timmermans, 1994. Uptake of Po-210 by Mussels from Effluents emitted by different Phosphorous Industries. To be published in the Proceedings of International Seminar on Freshwater and Estuarine Radioecology, Lisbon, Portugal, 21-25 March, 1994. Pentreath, R.J. and D.J. Allington, 1988. Dose to man from the consumption of marine seafoods: a comparison of the naturally-occurring Po-210 with artificially produced radionuclides. In: Radiation Protection Practice, IRPA 7, 3, pp. 15821585. Phillips, D.J.H., 1976. The common mussel Mytilus edulis as a n indicator of pollution by zinc, cadmium, lead and copper. 1. Effects of environmental variables on uptake of metals. Marine Biol., 38: 56-69. Rollo, S.F.N., W.C. Camplin, D.J. Allington and A.K. Young, 1992. Natural radionuclides in the UK marine environment. In: The Natural Radiation Environment, Proceedings of the Fifth International Symposium on the Natural Radiation Environment held at Salzburg, Austria, September 22-28,1991. A. Janssens, W. Lowder, M. Olast, J. Sinnaeve and F. Steinhausler (eds.), Radiat. Prot. Dosim., 45 ( 1 4 ) :203-209.

Freshwuter und Estuurine Rudii~eeciiliqy

Edited by C.Desmet et al. I997 Elsevier Science B.V.

425

A screening model approach to determine probable impacts to fish from historic releases of radionuclides T.G. Hinton and F.W. Whicker Savannah River Ecology Laboratory, Drawer E, Aiken, SC 29802,USA

ABSTRACT The term “ecological risk assessment” is often used to describe studies of contaminant concentrations, toxicity tests, or other components of ecotoxicological research. Absent in many of theses studies is the “risk assessment” component (i.e. the risk factor), which by definition equates exposure to a probabilistic prediction of a harmful effect (based on knowledge of exposure pathways and biological damage). This risk factor is the critical key in a risk assessment. Risk factors, however, do not generally exist for aquatic organisms, therefore, complete risk assessments are difficult to perform. We tried an alternative approach of using a screening model, and tested the concept by calculating dose to a fish population that has inhabited radionuclide contaminated waters on the Savannah River Site since 1954. The model input parameters were conservatively chosen so that fish dose was maximized. Ingestion and external irradiation from contaminated ‘o, %Sr,1311,137Csand 239Pu were considered. sediments and the water column due to 3H,@C Combining the dose from the six radionuclides across all pathways resulted in a dose rate to the fish of 0.23 mGy d-l. Having estimated a dose rate, but lacking the necessary risk factors to perform a risk assessment, we compared our calculated dose to dose rates in the literature that have documented effects associated with chronic exposures. This comparison allowed us to qualitatively predict the probability of (1)mortality and (2) physiological effects encountered by the exposed fish population.

1. INTRODUCTION

The Savannah River Site (SRS)is an 800 km2 U.S. Department of Energy nuclear production complex. The site contains five reactors and two chemical separations facilities that operated intermittently between 1954 and 1990. Numerous routine and accidental releases have resulted in detectable concentrations of radionuclides within the stream biota contained on the SRS [1,2]. Risks from these releases need to be quantified to provide guidance for future management of the watersheds. Estimating risks to non-humans, however, is a developing science plagued with many uncertainties; particularly trouble-

426

some is the problem of equating exposure to the probability of a harmful effect. The probability component is the key to a complete risk analysis, yet the necessary data are largely absent for non-human organisms. The type of data needed is exemplified in human risk assessments, where radiobiological sciences have advanced to the point of being able to assign a probability of contracting a fatal cancer for each mSv of absorbed dose received [3].The risk factor used for humans by the International Commission for Radiological Protection is 5x10" mSv-', that is, there is approximately one chance in 10,000 of an individual dying from cancer for each mSv absorbed. Risk factors do not exist for aquatic organisms, so it is difficult to assign a probability of damage from a given exposure. Our interest was to determine the probability of harmful effects to fish from historic releases of radionuclides on the SRS. Lacking risk factors, we used a screening model approach. Our goals were to (1)examine the historic radionuclide releases into SRS streams, (2) use a screening model to conservatively estimate the absorbed dose rate fish might have received from chronic exposure to such releases, and (3) estimate the probability of damage to the fish population by comparing our calculated doses to those in the literature that have documented definite effects. 2. METHODS

There are too many unknowns to precisely reconstruct dose absorbed by aquatic organisms from 30 years of chronic exposure at the SRS. Therefore, we opted to use a screening model in which the input parameters were conservatively chosen. If dose levels estimated using this approach are inadequate to cause concern, then it is probable that the actual doses were inconsequential. If, however, doses approach levels at which injury have been documented,then a reevaluation and more precise calculation may be necessary. Estimation of the source term

Our initial calculations indicated that the largest contributor to fish dose was exposure from 13'Cs. We reviewed the SRS literature and found that the maximum I3'Cs discharges occurred in 1964, when a failed fuel rod resulted in the release of 3.1 TBq (10" Bq or 83.4 Ci) into the drainage of Lower Three Runs Creek [5],We combined these 13'Cs releases with the 1964 releases for 3H,6oCo, "Sr, 1311, and 239Puto estimate a cumulative impact. We chose the BIORAD model to estimate dose to fish because it was recently used by the National Council on Radiation Protection and Measurements [41 and the International Atomic Energy Agency [61 to analyze the effects of ionizing radiation on aquatic organisms. BIORAD requires an equilibrium concentration of radionuclidesin water (Bq 1-'1 as the starting point for subsequent calculations. To estimate the 1964 equilibrium concentrations of radionuclides in the water

427 TABLE 1

1964 radionuclide releases into the Lower Three Runs drainage. Initial concentrations are based on 1964 water discharges added to normal stream flow (3.2~10"1). Dividing these initial concentrations by the Inventory Ratim (IR) fkom Pond B produced estimates of 1964water concentrations aRer equilibration with sediments. The equilibrated values were used in subsequent dose calculations. Conc. at equil.

Radionuclide

Annual release

Initial cone,

'H (a) %+

6.0~10'~ 8.8~10'' 2.2x 1011

1.8~10~ 2.7~10' 6.9~10'

141.0 6.9

137cs

3.1~10'~

9.7~10'

150.0

'%o (b) 1311 (c)

2 3 g (d) ~

-

-

-

0.0 -

-

1.8~10~ 0.02 1.00 3.77 0.65 0.01

(a) Tritium is not sorbed to soil particles and remains soluble 1101. (b) Data from Pond B were not available, the IR for %o was estimated from 13'Cs & and IR relationship. IIRlco = ([Kdlc,,/ [KdlcA [IRlcs. (c) Since 1964 release data were not available, we used a maximum concentration measured in 1962 from Steel Creek on the SRS 111. (d) Because early 60s data were not available and only gross alpha was reported, we used a maximum concentration reported for Four Mile Creek on the SRS [lll.

we used the 1964 release rates, and then adjusted them to account for the high sorption affinity of specific radionuclides to sediments. The sorption correction was derived from existing inventory ratios (IR) in Pond B, a well studied aquatic system within the same drainage as the 1964 release 171. The IR is the total activity in the sediments divided by the total activity within the water column. Data for IRs and the resulting sediment-equilibrated water concentrations (Cw(equilJ are presented in Table 1. Dose from ingestion

To estimate the dose from ingestion the BIORAD model applies a concentration factor to the radionuclide levels in the water column, and then accounts for the effective absorbed energy per disintegration for each radionuclide 181. The calculations performed by the BIORAD model have been reduced to dose conversion factors by the IAEA [61 (Table 2). Dose from external exposure (water)

The dose rate to fish from external irradiation within the water column is derived assuming an effectively infinite, uniform contaminated source [41.Due to their limited range, alpha particles were assumed not to contribute to exterConversion factors are presented in Table 2. nal dose [4].

428 TABLE 2 Distribution coefficients (Kd) and decay energies of radionuclides used in estimating external exposure to fish from contaminated sediments. Kds for Sr,Cs and Pu are from Whicker et al. 11. Dose factors are also given for the internal and external exposure of fish (BIORAD[8] and IAEA [61; mGy year-' per Bq 1-'1. ~

Radionuclide

3H 6'co

90Sr 1311

137cs 239pu

~~

Kd

b energy

g energy

Dose factors

(1 kg-')

(MeV)

(MeV)

Internal exposure

External water (puU)

0.0 2.5~10' 0.0 3.8~10-' 5.6~10-' 8.Ox10"

5.1~10" 1.5x10-' 2 . 7 ~ 1 0 (a) -~ 3.2~10-~ 1 . 2 ~ 1 (a) 0~ 9.5~10'(a)

1 . 610" ~ 1 . 310" ~ 2.7~10~ 2.5~10~ 3.2~10~ 2.2x10"

0 30,000 1,200 200 32,000 5.9~10~

(a) These generic dose conversion factors were multiplied by 150, 21 and 0.34 for ?3r, 13'Cs, and 239Pu,respectively, to incorporate site specific concentration factors from Pond B 171.

Dose from external exposure (sediments)

The BIORAD model does not estimate exposure of fish via irradiation from contaminated sediments. We followed the approach used by the NCRP [4] and the IAEA [6]and assumed that the concentration of a radionuclide in the sediment could be determined using its Kd value. We used site specificKds from Pond B when possible 171. The dose rate at the sediment-water interface was estimated by: HdB)= 2 . 5 2 ~ 1Cw(equil) 0 ~ Kd E(tota~), where E(,d, is the total energy of the decay modes from the radionuclides.Values for C W ( ~are U ~found ~ ) in Table 1,Kd, and E(tod)data are in Table 2. Conservative assumptions

The four conservative assumptions used in our screening model are depicted in Fig. 1, and assure that our predicted doses are larger than the real dose experienced by the fish. This is a fundamental requirement for a screening model approach. 3. RESULTS AND DISCUSSION

Table 3 summarizes the dose rates received by fish. Combining the six radionuclides considered, across all pathways of exposure, resulted in a dose rate of 0.23 mGy d-' (23mrad d-9. The major contributor to internal exposure was 137Cs(16 mGy year-'), followed by 3H(10mGy year-'). Tritium was also the primary source of external irradiation fiom contaminantsin the water column, contributing three orders of magnitude more than those radionuclides that tend to sorb to the sedi-

429 1) SOURCE TERM: used 1964

maximum release as a mean for calculations 2) EXPOSURE:assumed fish were living at point of discharge 5) ABSORFWON: assumed all fish were 30 a n in diameter which mudmized absorbed 4) IRRADIATION behavior of fish ignored,assumed they spent 100% of time on bottom sediments where > 90% of radionuclides are located

Contaminated

Fig. 1. Conservative assumptions used in the screening model to assure that the predicted dose to fish was larger than the real dose they experienced.

ments. 137Cs was the largest contributorto external irradiation from the sediments (40 mGy yea.f'), an order of magnitude greater than the next larger contributor (60Co).If dose rates fkom all radionuclides are combined, the contribution from internal contamination and external exposure from the sediments are similar. Recall, however, that the behavior of the fish is not considered in this conservative approach and the model assumes that the fish spends 100%of its time on the sediment surface where irradiation would be maximum (Fig. 1). It was interesting that the use of site-specific concentration factors from Pond B increased the dose rate to the fish by a factor of 150 for wSr and 21 for 137Cs(footnote Table 2). The increased availability of the radionuclides is due, in part, to the low 'K and Ca concentration in the water [71. The resulting change in dose rates also shifted the relative importance of the radionuclides away from 3H and towards 13'Cs. The increase in dose from using site-specific data is contrary to the philosophy of a screening model approach. Our data demonstrate the unusual case where a generic, conservative model underestimates dose and points to the importance of collecting site specific data.

Risk analysis Effects to fish from a 0.23 mGy d-' chronic exposure were evaluated by comparison to dose/effect studies in the literature, including reviews by the NCRP 141 and the IAEA 161.

430 TABLE 3 Total dose (mGy year-') to fish h m internal exposure due to the ingestion of contaminated food and water, plus external irradiation from the water and sediments Radionuclide

Internal exposure

External exp. Water (b+g)

Ext. exp. Sediment (b)

Ext. exp. Sediment (g)

Total

3H

3.13 0.0003 0.0027 0.01 0.002 2.2~10-'

0.0 0.15 3.3 0.36 12.9 1.0

0.0 3.8 0.0 0.73 28.9 0.12

13.10 3.95 7.35 1.22 57.93

239Pu

9.97 0.003 4.05 0.12 16.13 0.32

Combined

30.59

3.14

17.71

33.55

84.99

6OCO

90Sr 1311

'37cs

1.44

Grand total = 84.99mGy year-' (0.23mGy d-' or 0.023rad d-').

We summarized this comparison graphically in Fig. 2 for the endpoints of mortality and physiological effects. The dose rates received by fish in the SRS watershed, even with the very conservative assumptions we used, seem to be at least an order of magnitude lower than those documented to have caused mortality. These findings corroborate the NCRP [4] conclusion that "deleterious effects of chronic irradiation have not been observed in natural populations at dose rates I 10 mGy d-' over the entire history of exposure to ionizing radiation." The IAEA [6] recommended that limiting the dose rate to the maximally exposed individual in an aquatic population to I10 mGy d-' would provide adequate protection to the population. That level of exposure is considerably greater than the dose rate we calculated for fish on the SRS (0.23mGy d-'); thus there is a very low probability that fish mortality occurred from radionuclide exposures, since we conservatively maximized dose rate and are still well below 10 mGy per day. The SRS dose rate is also below those observed to have caused physiological damage (Fig. 2). However, unlike the mortality endpoint, the studies referenced for these effeds were still documenting damage at the lowest range of exposures tested, which do not extend down to the low rate encountered by the SRS fish. Thus, data are inconclusive as to whether SRS fish might have experienced harmful physiological effects.

4.CONCLUSIONS Our ability to judge the significance of radionuclide exposures to non-human organisms is currently limited by the lack of data relating dose to the probability of harmful effects. Until those data are available a screening model

431

BPPY BPPY

BPPY salmon

salmon 10

Dose rate (mGyl d)

Fig. 2. Documented mortality and physiologicaleffects from chronic exposure to radionuclide The left side of the y-axis lists the organisms studied, with the correcontamination [4,6]. sponding end point on the right side. Dose rate comprises the logarithmic-scaledx-axis. The connecting circles show the range of dose rates examined for each study. The dose rate at which an effect was observed is highlighted in black, compared to the hatched circles indicative of dose rates at which effects were not observed. This is reinforced by the symbols following the end points on the right side of the y-axis; an oval indicates that effects were not found over the range of doses studied, arrows indicate the direction of response from observed effects. Additionally, the dose rate estimated for fish exposed to the 1964 SRS release is indicated, as well as the present average background.

approach may be of value. The approach, however, has limitations. A screening model is only viable when the predicted dose is considerable less than doses at which harmful effects have been documented. This was the case in our study for the endpoint of mortality (Fig. 2). Because of our overly conservative assumptions, we know the predicted dose is much greater than the actual doses received by the fish. We also know our predicted dose is well below those at which effects have been observed. Therefore, we can be confident that the actual doses were insufficient to cause fish mortality. However, the screening model approach fails when the conservatively predicted dose approaches doses

432

at which effects have been observed, as was the case in our study for the endpoint of physiological damage. We cannot say with certainty that physiological effects were absent. 5. ACKNOWLEDGEMENTS

This work was supported by the Savannah River Ecology Laboratory through contract DE-AC09-76SR000819 between the U.S. Department of Energy and the University of Georgia. We appreciate reviews of an earlier version of this manuscript by C. Strojan, D. Niquette, and J. Hinton. 6. REFERENCES

1. Kantelo, V., L.R. Bauer, W.L. Marter, C.E. Murphy, Jr. and C.C. Ziegler, 1991. Radioiodine in the Savannah River Site Environment, WSRC-RP-90-424-2,Westinghouse Savannah River Co., Savannah River Laboratory, Aiken, SC. 2. Cummins, L., C.S. Hetrick and D.K. Martin, 1991. Radioactive releases at the Savannah River Site 1954-1989,WSRC-RP-91-684,Westinghouse Savannah River Co., Savannah River Laboratory, Aiken, SC. 3. International Commission on Radiological Protection (ICRP), 1991. The 1990 Recommendations of the ICRP, Publication 60, Annals of the ICRP 21, Permagon Press, Oxford, pp. 1-201. 4. National Council on Radiation Protection and Measurements (NCRP), 1991. Effects of ionizing radiation on aquatic organism. NCRP Report No. 109, Bethesda, MD, 115 pp. 5. Carlton, H., L.R. Bauer, A.G. Evans, L.A. Geary,C.E. Murphy, Jr., J.E. Pinder I11 and R.N. Strom, 1992. Cesium in the Savannah River Site Environment, WSRC-RP-92250, Westinghouse Savannah River Co., Savannah River Laboratory, Aiken, SC. 6. International Atomic Energy Agency (IAEA),1992. Effects of ionizing radiation on plants and animals a t levels implied by current radiation protection standards, Technical Reports Series No. 332, Vienna, 73 pp. 7. Whicker, W., J.E. Pinder, 111, J.W. Bowling,J.J. Alberts and I.L. Brisbin, Jr., 1990. Distribution of long-lived radionuclides in an abandoned reactor cooling reservoir. Ecolog. Mon., 60: 471496. 8. Turbey, K. and S.V. Kaye, 1973. The EXREM I11 computer code for estimating external radiation doses to populations from environmental release, Rep. ORNLTM-4322, Oak Ridge Nat. Lab., TN. 9. Whicker, W. and V. Schultz, 1982. Radioecology: Nuclear Energy and the Environment. CRC Press, Boca Raton, FL. 10. Murphy, E., L.R. Bauer, D.W. Hayes, W.L. Marter, C.C. Ziegler, E.E. Stephenson, D.D. Hoe1 and D.M. Hamby, 1991. Tritium in the Savannah River Site Environment, WSRC-RO-90-424-1,Westinghouse Savannah River Co., Savannah River Laboratory, Aiken, SC. 11. Holloway, W. and D.W. Hayes, 1981.Transuranics in a stream near a nuclear fuel chemical separations plant, DP-1592, E.I. du Pont de Nemours and Company, Savannah River Technology Center, Aiken, SC.

Freshwater and Estuarine Radioecology Edited by G . Desmet et al. 1997 Elsevier Science B.V.

433

Modelling the long-term behaviour of radioactive substances in fresh water systems: role of migration from catchment basins and of radionuclide exchange between water and sediment U. Bergstroma,J. Boardmanb,R. Helingc,J. van der SteenC and L. Monted aStudsvik Eco & Safety AB,S-61182 Nykoping, Sweden bAEA, Warrington, Cheshire WA3 6AT, UK ‘KEMA, Utrechtseweg 310, 6812 AR Arnhem, The Netherlands ‘ENEA, CP 2400, 00100 Roma ALI, Italy

ABSTRACT The migration of radionuclides through catchment basins, by run-off or wash-off waters and rivers, the resuspension from sediments and the subsequent transport are important phenomena involving long-term contamination of water bodies. The main aim of the CEC Project “Analysis and modelling of the migration of radionuclides deposited in catchment basins of fresh water systems” is to investigate the various aspects of these phenomena in order to develop models assessing the behaviour of radionuclides in drainage areas of fresh water systems. In the present paper preliminary results of the research will be described: (a) The migration from catchment basins to water body may be quantified by using the so called “transfer functions” (“T.F.”= amount of radionuclide (Bqs-’) flowing, per unit time, from the catchment to the water body following a pulse deposition on the catchment). A variety of such functions were evaluated using experimental data collected in various European rivers following the Chernobyl accident; (b) A literature survey of models predicting radionuclide migration from catchment to water bodies was carried out. The model review was intended to highlight the dominant processes involved in radionuclide migration from catchment areas to surface water bodies and to investigate the various possible approaches to drainage area modelling; (c) The long-term exchange of radionuclides between sediment and water was investigated.

434

1.INTRODUCTION

The contamination of fresh water, following an accidental release of radionuclides into the atmosphere, may represent an important source of dose to man as a consequence of the fresh water exploitation (fishery, drinkable waters, irrigation waters etc.). The migration of radionuclides in catchment basins via run-ofhash-off waters, rivers and groundwaters, the resuspension from sediment and subsequent transport are problems of considerable and general importance relevant to the long-term contamination of water bodies. Models that describe the migration of deposited radionuclides in drainage areas via rivers and, more generally, via run-off and wash-off waters are tools of great importance in evaluating the consequences of an accidental release of radionuclide into the environment. The analysis of the most important phenomena concerning the relocation due to water run-owwash-off and the remobilisation from bottom sediments to the water column of deposited radionuclides and the development of models that describe the consequencesand the behaviour of the radioactive contaminants in the aquatic part of the environment following a nuclear accident, are the main goals of the research programme “Analysisand modelling of the migration of radionuclides deposited in catchment basins of fresh water systems” financed by the CEC (contract N FI3P-CT930073). The aim of the present paper is to show some preliminary results obtained during the above research programme. The quantification of the radionuclide migration from catchment to water bodies and the importance of radionuclide remobilisation from lacustrine sediments are discussed in detail. 2. MODELLING THE PROCESSES OF MIGRATION OF RADIONUCLIDES IN CATCHMENT AREAS

The transport of radionuclides following deposition on to the catchment, through to a surface water body is associated with the movements of water and particulate above and beneath the soil surface, while transfer of activity between the two phases (dissolved and particulate form) occurs by sorption from solution onto soil particle surfaces. This transfer between solid and liquid phases is often described very simply by the distribution coefficient, Kd,which relates the concentration of adsorbed activity to that in solution. However, the efficiency of sorption processes exhibited in the environment, which link transport in the particulate and liquid phases, is highly variable and complex. The process generally depends on factors such as physico-chemical properties of the element, available surface area (depending on particle size), mineralogy (e.g. competing cations) and the organic content of soil. The catchment responses to atmospheric fallout may be explained in terms of a fast and slow component of transport. “Fast”response of the catchment is generally attributed to overland flow of rainwater - a process known as direct run-off. ”Slow” response is

435

attributed to leaching of activity within the soil by rain water and subsequent subterranean transport toward the receiving water course. The “Transfer Function (T.F.)” from the catchment to a water body relates the flux of radionuclides (Bq s-’), at a specific point of a watercourse, to the water flow and to the amount of the radionuclide deposited on the upstream catchment basin following a single pulse of deposition of a radioactive substance. Using water contamination data collected, following the Chernobyl accident, in the rivers Pripyat, Dnieper, Teterev, Uzh (Ukraine [ll),Po (Italy [2]) and Rhine (data submitted by KEMA, The Netherlands, to the VAMP “Validation of Model Prediction” project organised by the International Atomic Energy Agency, Vienna, Austria) by various European laboratories, the mathematical form of the T.F. for the dissolved part of radionuclides was evaluated for the above watercourses. Assuming the presence of two components the following function, comprising a “fast”and “slow”term, was used to fit the experimental data:

where: A1,A, = relative weight of short and long-term components of transfer function (pure numbers); D = average impulsive radionuclide deposition onto catchment (Bq m-’); t = time ( s ) ;al,a2= exponents of water flux in transfer function (short and long-term components, pure numbers); E = transfer coefficient deposition + water (m-’); @(t)= water flux (m3 s-?; ( t ) = transfer function of dissolved radionuclide: flux, at time t, of dissolved radionuclide following a pulse deposition onto catchment basin at time t=O (Bq s-’); h, = radioactive decay constant (s-’);hl + h, = effective decay constant due to environmental effects and to the radioactive decay (short term component) (s-’);hz + & = effective decay constant due to environmental effects and to the radioactive decay (long-term component) (s?. The evaluations of some of the parameters of function (1)are given in Tables 1 and 2. Figure 1 shows, as an example, the “fast” and “slow” component for river Rhine. A more detailed discussion on the T.F. is reported in [3]. The analysed data show that the transfer function for wSr is not linearly related to water flow (the coefficient a2is significantly higher than 1).In the case of 137Cs, the data do not demonstrate a significant non-linearity of the radionuclide flux to the water flow (azis not significantly different from 1). However studies carried out on the river Dora Baltea [4], for which the drainage basin is located in the Alps region, showed that, during the period of snow and ice melting, the release of radionuclides accumulated in glaciers and in areas covered by

436 TABLE 1 Evaluation of parameters of short term component of transfer function for dissolved 137Csin rivers in rivers Pripyat and Dnieper (Results of the Dnieper, Pripyat, Rhine and Po and for dissolved regrassion analysis of data collected from 20 to 120 days after 1 May 1986 using a1 = 1)

+ lir (8-l)

Radionuclide

Geometric mean of hi + Ar (8-l)

Range of hl

1 3 7 ~ ~

5.1x 10-7 6.8x

2.3 x 10-7- 8.8x 10-7 6.2 x 10-~- 9.0 x 10-~

%r

TABLE 2 Evaluation of parameters of long-term component of transfer function for dissolved 137Csand wSr in rivers Dnieper, Pripyat, Rhine, Teterev and Uzh (results of the regression analysis of data collected 240 days after 1 May 1986) Radionuclide

137cs

"Sr

Geometric mean of 013 0.86

1.3

a2

Range of

Geometric mean of hz + b (s-9

Range of hz + hr (8-1)

0.5-1.08 1.1-1.4

1.5 x lo-' 4.9x 10-~

8.2x 10-9-2.7x lo4 3.6 x 10-9-5.9x

lEll O d i s s o l v e d 137Cs flux B q d-1 O f a s t component of 137Cs flux. A s l o w component o f 137'2s flux

lElO

Days from May, t h e 1st 1 9 0 6

Fig.1.Flux of dissolved 137Cs in river Rhine.

437

perennial snows was significantly nonlinear with respect to the water flux; indeed the concentration of 13'Cs in water increased with water flux. The radionuclide migration from catchment to water bodies depends on the characteristics of the catchment area. Studies carried out on Swedish lacustrine systems showed that there is a positive correlation (12 = 0.811) between the catchment leakage and the percentage of bog area in the catchment. It is extremely instructive to compare the above T.F. with the predicted pulse response of some existing models for the assessment of radionuclide migration in catchments. In the present paper the model developed by Joshi 151 was analysed in detail. The model is based on typical assumptions used by a large class of models developed to predict the movement of radionuclides in catchments. It gives a clear idea of the state-of-the-art techniques used to model the radionuclide transfer from catchment to water bodies. The fluvial removal Fir(Bq m-' s-') is assumed to be proportional to the radionuclide inventory in the watershed Zi (Bq m-')

Multiplying both sides of Eq. (5)by the area of the watershed, A, we get ($,.,, ( t ) = predicted radionuclide flux Bq s-'):

The radionuclide inventory is calculated according to the following equation:

where F, ( t )is the time dependent input flux of radionuclide into the watershed (Bq m-' year-'), V, ( t )is the annual volume of rainfall (m year-'), V,, ( t )is the water penetration depth (m), Ar is the radioactive decay constant and Kdlis the dimensionless distribution coefficient given as kdl = p k d (p = soil density (kg dm3), kd = water soil distribution coefficient dm3kg-'. The radionuclide flux predicted by the model following a single pulse deposition may be very complex depending on the time behaviour of V., (t)and Vw, ( t ).If the ratio V,, (t)N,., ( t )= p is constant, the solution of Eq. (7) is

++iq

Ii(t)= li(0)e

The predicted radionuclide flux is then

438

The distribution coefficient kd plays an important role in the model. The effective decay constant (k. + l/pkdi) is a decreasing function of kd in contrast with the experimental values of b.Indeed the experimental effective decay constant of w)Sr,a radionuclide characterised by a low sorption and thereby low kd, is lower than the effective decay constant of 137Cs.The model does not predict the short term component of the transfer function and is based on the hypotheses that the radionuclide removal is linearly dependent on the water flux. 3. ROLE OF LAKES IN CATCHMENTS

When a deposition occurs, the transport of 137Csfrom water to the sediment is quite rapid due to the strong affinity of 13'Cs t o particles like clay minerals and detritus. Studies carried out on Swedish lakes [6,71 show that lakes play an important role in catchments, indeed, in the long run, they may release radionuclides to the environment through outlets. The majority of 137Csdeposited on lake surface accumulated in sediments (see Fig. 2). The consequent radionuclide release from sediment leads to prolonged concentrations in water and thereby prolonged levels of contamination in aquatic organisms. The radionuclide present in the various components of the lake system (water, suspended matter, sediment) may partly be released to the environment through the I

1

d

.n :0 4J

z (I

0

d

.n :0

.rl

Rn

Fig. 2. Comparison of the relationship between '37Csinventory and deposition in 6 Swedish lakes.

439

Fig. 3. The total flux of i37Cs in GBq year-' through the inlet and outlet of Lake Hillesjon (Sweden).

outflow. Figure 3 shows the total amount of 137Csin GBq year-' arriving and leaving through the inlet and the outlet water in lake Hillesjon. 4. CONCLUSIONS

The evaluation of data of water contamination collected in some rivers, for approximately 6 years after the Chernobyl accident, showed that the time dependent migration of radionuclide from catchment to water body shows two exponential decay components. The effective half time of the fast component is ofthe order of few weeks whereas the effective half time of the slow component ranges from 1year to 3 years for 137Csand from 4 to 6 years for %Sr.The models used to predict the migration of radionuclides in catchments are based on the classical concept of the reversible watedsediment partition coefficient. Unfortunately it seems that the models exclusively based on the above concept cannot explain the time behaviour of radionuclides in water flowing through catchments. Indeed they predict that the effective decay constants are inversely related t o the k d which is in contrast with the analysed data. It is possible that effects such as the non reversible interaction of dissolved radionuclides with soil particles is important to justify the time behaviour of the radionuclide transfer from catchments to water bodies. The research also demonstrated that lakes may play an important role as points of accumulation of radionuclides that may be released to the environment on the long term. It seems extremely important to investigate in detail the above aspects of the radionuclide migration in catchments to improve the model performance.

440

5. ACKNOWLEDGEMENT

The present work was partially financed by CEC (contract N FI3P-CT930073) in the framework of the Nuclear Fission Safety Programme, and also by the Swedish Radiation Protection Institute. 6. REFERENCES Kaniviets, V.V. and O.V. Voitcekhovich, 1992.Scientific report: Radioecology of water systems in zone of consequences of Chernobyl accident. Report of Ministry of Chernobyl Affairs of Ukraine. Contract Number U92 (in Russian). 2. Queirazza, G. and W. Martinotti, 1987. Radioattivith nell’acqua del Po: tratto mediano e delta. Acqua Aria mensile di scienze e tecnologie ambientali. Arti Poligrafiche Europee, Milano, Italy. Luglio agosto. 3. Monte, L., 1995. Evaluation of radionuclide transfer functions from drainage basins of fresh water systems. J. Environ. Radioactivity, 24. 4. Spezzano, P., S.Bortoluzzi, R. Giacomelli and L. Massironi, 1993.Seasonal variation of 137Csactivities in the Dora Baltea river (northwest Italy) after the Chernobyl accident. J. Environ. Radioactivity, 21. 5. Joshi, S.R. and B.S. Shukla, 1991.The role of the waterhoil distribution coefficient in the watershed transport of environmental radionuclides. Earth Planet. Sci. Lett., 105:314-318. 6. Broberg, A.and E. Andersson, 1991.Distribution and circulation of 137Csin lake ecosystem. In: L. Moberg (ed.), The Chernobyl Fallout in Sweden: Results from a Research Program on Environmental Radioecology. Swedish Radiation Protection Institute SSI, pp. 151-175. 7. Sundblad, B., U. Bergstrom and S. Evans, 1991.Long term transfer of fallout nuclides from the terrestrial to the aquatic environment. Evaluation of ecological models. In: L. Moberg (ed.), The Chernobyl Fallout in Sweden: Results from a Research Program on Environmental Radioecology. Swedish Radiation Protection Institute SSI, pp. 151-175.

1.

Freshwater and Estuurine Rudioecology Edited by G . Desmet et al. 0 1997 Elsevier Science B.V. All rights reserved

441

The use of 210Pb and 13'Cs as tracers in modelling transport processes in lake catchment systems P.G. Appleby Department of Applied Mathematics and Theoretical Physics, University of Liverpool, Liverpool L69 3BX, UK

ABSTRACT This paper reviews transport processes governing the relationship between atmospheric fluxes and sedimentary records and illustrates the role that the fallout radionuclides 210Pband 137Cscan play as tracers in studying those processes. Large quantities of data on 210Pband 13'Cs in the environment have been obtained as a result of their widespread use in sediment dating programmes. The value of this data can be enhanced by better information on fallout levels and by a greater understanding of key distribution parameters in aquatic systems.

1. INTRODUCTION

Predictive models of transport processes in lakekatchment systems are of fundamental importance not only in radiation protection programmes but also in a wide range of important environmental programmes, e.g. soil erosion, reservoir siltation and, increasingly, palaeolimnological studies using lake sediment records to reconstruct the depositional history of atmospheric pollutants. These records represent the outcome of the transformation of atmospheric fluxes by a complex series of mediating transport processes, the effect of which must be taken into account if sediment records are to be interpreted in a quantitative way. The validation of transport models demands empirical data on the outcome of the transport processes on tracers whose input to the environmental system being studied is reasonably well defined. The application of 210Pband 137Cs dating in palaeolimnological studies has generated a large quantity of data on the distribution of these radionuclides in lake sediments. Since 210Pband 137Cs both have a reasonably well defined atmospheric flux, this data offers an opportunity to validate models of transport processes in a wide range of lakekatchment systems. The object of this paper is to illustrate the potential

442

value of this data using results obtained from the University of Liverpool Environmental Radiometric Laboratory sediment dating programme, and to highlight the way in which it could be enhanced by additional measurements of certain key parameters. 2. PAJAEOLIMNOLOGICAL TRANSPORT MODEL

The basic objective of the palaeolimnological transport model is to relate the atmospheric flux of a given tracer to its sediment record. Since the input of a tracer to a lake may include a significant contribution from the catchment, and a signscant fraction of the component in the water column may be lost via the outflow, key elements in the model will include a quantification of the catchmenfflake transport rate and the lake waterlsediment transfer fraction. 2.1. Catchment /lake transfer

For a tracer with a time-dependent atmospheric flux W t ) ,the rate of transfer from the catchment to the lake can be written w c ( t ) = Ac

I @

where I 0 is a catchmenfflake transfer function and A, is the catchment area. This function may be characterised by a catchment transport coefficient, defined as the ratio K=

transport rate _catchment inventory Q, W C

where Qc is the total inventory of the radionuclide in the catchment. The reciprocal Tc= 1 / represents ~ a residence time of the radionuclide in the catchment. The value of the transport coefficient for older deposits which are less available for transport may be expected to be lower than its value for more freshly deposited material. This time-dependence can be represented more transparently using the concept of a unit response function h(z). Following the analogue of the unit hydrograph, this may be defined as the (decay corrected) transport rate due t o a unit amount of fallout on the catchment.Assuming that the response of the catchment to a unit of fallout does not change significantly with time, the catchmenfflake transfer function can then be written

-

( I @ ) ( t=) @(t- z) h(z) e-" dz 0

where h is the radioactive decay constant. The response function h(z) has been modelled variously by one or more exponential functions [1,21.

443

2.2. Lake water lsediment transfer

The total rate of supply of the tracer to a lake through both direct fallout and transport from the catchment is

AL(1+ aT)@ where AL is the area of the lake and o!is the catchmenfflake area ratio. Once in the lake waters it may be transported to the bed of the lake through the process of sedimentation, or lost from the lake via the outflow. The critical operational factors controlling the distribution are the lake water residence time Tw, the residence time of sediments in the water column Ts, and the fraction fD of the tracer resident on the sediments, defined by:

sd Ts =t

scs

f d = c

where VLis the lake volume, q the discharge from the lake, d the mean water depth, s the suspended sediments concentration, r the mean sedimentation rate, C the mean radionuclide concentration in the lake waters and Cs the mean radionuclide concentration of the particulates. Since the loss rates from the water column are: radioactive decay: hVLC discharge via the outflow: VLCITW transport to the bottom sediments: ALr CS= VLf D CITS the fraction of the input transferred to the sediments is [31

where TLis a residence time of the tracer in the lake waters, given by

2.3. Application to "OPb

Assuming a constant atmospheric '"Pb flux P and that the transport processes are in a steady state, the catchmenflake transport rate has the constant value wc = Ac T p

where

444

-

q = h(z)e-" dz 0

is the decay-weighted area under the 'loPb catchment unit response function [4]. From equilibrium considerations it is readily shown that the parameter q is related to the 'loPb transport coefficient by

Balancing the steady state 'loPb input to the lake by direct fallout and catchment transport with the steady state losses t o the outflow and sediments and rearranging, the equilibrium 'loPb concentration in the lake waters is given by the equation 1 Cequ = - TL( 1 + aq)P . d

The mean flux of 'loPb to the sediments is [51

P, = FpI, (1+ aq)P where Fm is the 'lo-Pbtransfer fraction.The mean unsupported 'OPb inventory of the sediments A, is given by the formula:

A, = F P b (1 + aq)P 2.4. Application to I3'Cs

Since fallout from the Chernobyl accident was delivered more or less instantaneously, transport of Chernobyl radionuclides from a catchment comes close to a direct representation of the catchment unit response function for the transport of 13?Cs.Assuming an instantaneous initial input I. ,the cumulative decay corrected input to the lake after t years will be:

r

-

1

L

o

1

Id 1+ a h(z) dz I e-' Assuming that the 137Cspartition fraction fD remains relatively constant, except on timescales which are of the order of the residence time TLthe contribution to the 13'Cs inventory of the sediments will vary with time in accordance with the formula

r

-

O L

0

1 1

I s = F I Il+ajh(r)dzle-'. cs

445

In the short term, this will be largely determined by the direct fallout onto the lake I. and the caesium transfer fraction Fc,. As time progresses, catchment inputs (represented by the integral in this equation) will be of increasing significance, and measurements of the sediment inventory I, over a period of years will provide information about the catchment response function h(d. Weapons 137Csinventories can be modelled by applying this result to each year's annual input [1,21. 3. DISCUSSION

Given values of the transport parameters h(s) and F,the above model allows the possibility of determining atmospheric fluxes from measured sediment records. Conversely, by comparing sediment records with known atmospheric fluxes it is possible to make inferences about values of the transport parameters. This is illustrated by the results shown in Fig. 1 which plot measured unsupported 'lo Pb, weapons and Chernobyl Cs inventories versus time in cores taken from a number of lakes in Galloway, SW Scotland during the period 1980-91. The 137Csvalues have been converted to decay corrected nominal fallout units that are independent of the date of collection. Although the results are highly variable, it is immediately apparent that the both the weapons and Chernobyl 137Csinventories are considerably lower than the values that would be determined by direct exposure to the atmospheric flux. This is in contrast to 'loPb where the mean value is comparable to that determined by the direct atmospheric flux. Much of the scatter in these results will be due to the localised effects of sediment focusing. The influence of this may be partly reduced by normalising the 137Csmeasurements against '"Pb. This is illustrated by Fig. 2 which plots weapons 13'Cs versus unsupported 'loPb inventories for cores from (a) the Galloway lakes and (b) a number of lakes from continental Europe. With only a small number of exceptions, the sediment cores are significantly depleted in 137Cscompared to "OPb relative to the atmospheric flux. Proper analysis of these results is contingent on better information concerning the radionuclide fluxes and the transport parameters. Even in the best monitored sites, estimates of the atmospheric flux of 'lOPband 137Csare subject to considerable uncertainty and are largely dependent on regional estimates corrected for local rainfall [61. This uncertainty could be significantly reduced by direct estimates from measurements of radionuclide inventories in soil cores collected from undisturbed sites in or adjacent to the catchment. Two key physical parameters controlling the transport of radionuclides in lake waters are the suspended sediment concentration, s, and the radionuclide partition fraction, f D , both of which are relatively amenable to direct measurement. Routine determination of suspended sediment concentrations in the water column of lakes subject to palaeolimnologicalinvestigations would, when

I

+

.

8

Date

.

+

137

1W

18M

Date

lR0

1-

Galloway Lakes Weapons Cs-137 Inventory versus Time

l-1

Date

n

v .

.

Galloway Lakes Chemobyl Cs-137 Inventory versus Time

Fig. 1. '%b, weapons and Chernobyl Cs inventories of sediment cores from lakes in Galloway, SW Scotland plottedversus date of coring. Also shown are estimates of inventories supported by the direct atmospheric flux.

.7 E lomo

llM0

1 -

lam

Galloway Lakes Pb-210 Inventory versus Time

21

-t

0

woo moo

low0 lZM0 1

m -1

Unsupported 210Pblnvenlory (Bq m-')

zoo0 4ooo

1woo

West European Lakes Cs-137 versus Pb-210 Inventories

zomo

1

Fig. 2. Weapons Cs versus "Pb inventories for cores from lakes in (a) Galloway, SW Scotland and (b) western Europe. The dotted line corresponds to inventories in the same ratio as that supported by the direct atmosphericflux.

137

Unsupported 'lOPb Inventory (Bq m-')

Galloway Lakes Cs-137 versus Pb-210 Inventories

448

coupled with radiometrically determined estimates of the sedimentation rate, provide a useful data base that could be used to provide better estimates of mean settling velocities and hence of the residence time of sediments in the water column, T,.For individual coring sites this data could also be used to assess the extent of sediment focusing. Determination of the "OPb and 13'Cs distribution coefficients in lake waters from a range of different sites would, apart from giving better estimates of the lake watedsediment transfer fraction, F, also give a better insight into the processes controlling this fundamental parameter. 4. CONCLUSIONS

Sedimentary records of the fallout radionuclides 'loPb and 13'Cs obtained in the course of a large number of palaeolimnological studies of more general environmental issues constitute an important data set on radionuclides in the environment. Using simple models, these records can be used to study the transport of radionuclides through lake/catchment systems. Making full use of the potential offered by this data does, however, depend on the availability of more reliable estimates of the atmospheric fluxes of fallout radionuclides and better knowledge of radionuclide partition fractions in aquatic systems. 5. REFERENCES 1.

2. 3.

4. 5. 6.

Helton, J.C., A.B. Muller and B. Bayer, 1985. Contamination of surface-water bodies after reactor accidents by the erosion of atmospherically deposited radionuclides. Health Phys., 48: 757-771. Smith, J.T., 1994. Mathematical modelling of Cs-137 and Pb-210 transport in lakes, their sediments and the surrounding catchment. PhD thesis, University of Liverpool, 219 pp. Santschi, P.H. and B.D. Honeyman. Radionuclides in aquatic environments. Radiat. Phys. Chem., 34: 213-240. Appleby, P.G. and J.T. Smith, 1993. The transport of radionuclides in lake-catchment systems. Proc. UNESCO Workshop on the Hydrological Impact of Nuclear Power Plant Systems, UNESCO, Paris, pp. 264-275. Appleby, P.G. and F. Oldfield, 1992. Application of Pb-210 to sedimentation studies, in: M. Ivanovich and R.S. Harmon (eds.), Uranium Series Disequilibrium, OUP, pp. 731-778. Appleby, P.G., N. Richardson and J.T. Smith, 1993. The use of radionuclide records from Chernobyl and weapons test fallout for assessing the reliability of Pb-210 in dating very recent sediments. Verh. Int. Verein. Limnol., 25: 266-269.

Freshwuferund Estuurine Rudioec~il(igy

Edited by G . Desmet et al. 0 1997 Elsevier Science B.V. All rights reserved

449

Modelling of Chernobyl radiocaesium behaviour in catchment-lake-sediment system Devoke Water (Cumbria, UK) I.Ya. Bilyia, R.N.J. Comansb, J. Hilton' and O.V. Voitsekhovitcha 'Ukrainian Hydro-Meteorological Institute, Nauka Ave. 37, Kiev, 252028, Ukraine bNetherlands Energy Research Foundation, Westerduinweg 3, P. 0.Box 1, 1755 ZG Petten, The Netherlands 'Institute of Freshwater Ecology, The Ferry House, Far Sawrey, Ambleside, Cumbria, LA22 OLP, UK

ABSTRACT A local equilibrium model of radionuclide migration was used to reconstruct a time series of Chernobyl radiocaesium concentration in a small upland lake, Devoke Water (UK),and to assess the wash-off rate. Radiocaesium, ammonium and potassium profiles in bottom sediment cores sampled in 1992 were used as input data. Whereas the water column has been considered as a well-mixed system, bottom sediment profile properties are modelled as strongly dependent on concentration of competing univalent ions (mainly ammonium). Model fits resulted in values of 0.02y e a r ' for wash-off rate, 0.01 for rapid flush and 0.5-1.0 cm for the boundary layer thickness. The slope of the modelled profile down the Chernobyl peak (which does not depend on fitted parameters) has shown a good consistency with a slope of experimental one.

1. INTRODUCTION

A significant area of Lake District National Park in north-west England was affected by Chernobyl radiocaesium fallout of contamination density up to 20 KBq m-'. In the majority of the lakes caesium concentration in the water rapidly decreased to low pre-Chernobyl levels of a few mBq l-', but some, including the small upland lake Devoke Water, showed unexpectedly long periods of high concentration b100 mBq 1-I) despite rather intense hydraulic flushing 11-31. For that reason Devoke scenario was included in VAMP and BIOMOVS programmes for model validation. A series of investigations has been undertaken

450

to explain this phenomenon from a geophysical point of view and to describe it mathematically. Hilton et al. 141 compared radionuclide wash-off from six subcatchments of the lake and have shown by means of multiple regression that the main factor responsible for rapid losses of '"Cs from the catchment is its fibrous peat cover. In 1992 Devoke Water has become a test ground for the international CEC-CIS Chernobyljoint research project ECP-3. Within the framework of this project several field exercises have been carried out on the lake by an international research team. Using up-to-date methods and equipment, they sampled and analyzed water, bottom sediments and soils from the lake catchment. After discussion of the results of experimental studies, it was proposed that these results be combined with previous radiation monitoring data for the construction and verification of a mathematical model explaining radiocaesium behaviour in this type of lake-catchment system. Although some peculiarities of the CALAS (CAtchment-Me-Sediment) model are stipulated by particular features of Chernobyl fall-out and the Devoke lake system (e.g. a well-contoured catchment, regular precipitation regime), it can be adapted to other types of lake systems and time scales of deposition events. The approach is similar to Refs. [2,3,51 but with much more detailed consideration of processes within the sediment subsystem. In fact the authors regard the radiocaesium profile in bottom sediment of the lake as a 'record' of it's fate in the system, and the model itself as an instrument for reconstruction. The model is not purely predictive since it has several fitted macro-parameters e.g. radionuclide wash-off rate I, and a - a portion of immediate post-deposition losses. Still these parameters could be obtained by fitting the experimental sediment profile with the calculated one and verifying by water monitoring data. 2. DESCRIPTION OF THE MODEL

The structure of the model is presented in Fig. 1.and the basic assumptions for its construction are as follows: (i)instantaneous radionuclide fall-out is homogeneously distributed over the catchment and water surface of the lake; (ii) a small fraction of radioactivity is washed off and transferred to the lake within very short period; (iii) further wash-off from the drainage area is a first-order process (with some rate constant), which is stipulated by the regular rainfall regime in the sea climatic zone; (iv) radionuclide concentration in the water column is the same at any location and depth (the system is well mixed) and two species -water soluble and reversibly sorbed (exchangeable) on suspended particles - are in local equilibrium with each other;

451

I

/I1IyI

Catchment

Lake hydraulic

<

soluble

flushing

L

d& dl

plfi.

shady w a r h 4

m @OX)

dinusion

/ J

sedbllentsticfl

(continuum)

Fig 1. The structure of the CALAS model.

(v) from the water column of the lake radionuclide could be either flushed through the outlet or deposited onto the bottom; (vi) radionuclide vertical redistribution in bottom sediment is governed by advection-dispersion mechanisms due to sedimentation, mixing and molecular diffusion through the porous water in chemically and physically inhomogeneous medium; local equilibrium for water soluble and sorbed species also takes place; (vii) radionuclides can re-enter the water column from the bottom sediment pore water due to diffusion mechanism. Thus it can be seen that the model consists of two compartments (catchment and water column) and one chemical bicontinuum (bottom sediment). To justify the local equilibrium assumption (LEA) some qiantitative characteristic of comparative intensity of mass transfer and kinetic exchange between mobile (water-soluble) and immobile (sorbed) phases could be used. Usually they are referred to as Darmkohler numbers [61. Physical redistribution of caesium in bottom sediment is mainly governed by diffusion through the interstitial water. So Darmkohler number criterion could be applied to this subsystem:

&)e/&

Typical values for Rb - 1 in bottom sediment that is p(1are not less than 100 whereas the kinetic constant r has an order of magnitude 1.0 1 d-' or

462

greater. The diffusion coefficient D, for caesium (with tortuosity factor taken into account) is about 1.0 cm2d-I. So taking a proper linear scale L about 1.0 cm one has at least Da* 2 100, which according to Ref, [61 guarantees the validity of LEA. For the water column a similar criterion could be formulated:

which is a direct analogy to the Darmkohler number [6] for pure advection. Although the retardation factor in water never usually exceeds 10.0, very high kinetic exchange rate r makes DUO sufficiently large to adopt LEA. 3. MATHEMATICAL FORMALISM

The governing equations of the model could be summarized as follows. Since water-soluble and particulate caesium fractions are in equilibrium with each other i.e. Af, = &4i, total radionuclide balance in the water column is given by

with unknown volumetric specific activity A'(t) and flux A t ) . Here Routis defined in the same way as R1in Eq. ( 2 )and A1 =A!.,+ TIA~!.,. The radioactive decay term in Eq. (3) and below is omitted because of the assumption about the instant character of the fall-out. At any time one can correct the result using simple exponential factor. The source term $ in Eq. (3)is determined by steady wash-off assumption:

It is convenient from a mathematical point of view to consider the lake bottom-water column boundary as immobile in spite of the sedimentation process going on. So radionuclide redistribution in bottom sediment along the vertical axis x directed downwards is governed by advection-dispersion equations which can be written in the general form: aAb

aJb

ax

-+-=(I

at

453

where specific radioactivities Ab(x,t),Ak(x,t),A,b(x,t)and flux Jb(x,t) are unknown. The actual diffusion coefficient D, depends on the so-called tortuosity factor: D, = Dd$. All bioturbations and hydrodynamic mixing of sediments are considered as negligible, otherwise one should add a proper dispersion term to the right-hand part of Eq. (7). Applying local equilibrium, A,b6= assumption to Eq. ( 6 )and (7) one can substitute them with +(EU,+SG)--

Ab m b

The substantial inhomogeneities of the bottom sediment profile are stipulated by variations of its chemical (the distribution coefficient and retardation factor) and physico-mechanical (porosity and tortuosity parameters) properties. In the case of Devoke, the last of the above-mentioned parameters practically do not change with depth whereas caesium J$ changes according to variations of concentration of competing cations i.e. univalent ions with a low hydration energy and an ion radius similar t o Cs', such as K', NH: and Rb' [7,8]. Since potassium concentration in pore water is usually stable along the profile [8,9] the variation of caesium is determined by concentration of ammonium, i.e. by factor (rn"Hi])-'. Unknown variables from the water column compartment and bottom sediment subsystems (concentrations and fluxes) are linked together by the boundary condition:

a

J(t)= Jb(0,t) = sAL(t) + EU, AL(t)+ m(AL(t)- Ak(0,t))

(9)

where the first term shows sedimentation input and the two others describe advection-diffusion exchange between pore and lake water. The coefficient for pore water-water column diffusion could be expressed as

Using the local equilibrium assumption Eq. (9) can easily be rearranged in terms of total specific activities A'(t)and Ab(x,t).For the numerical solution of Eqs. (5), ( 8 ) and (9) the method of test functions 1101 modified for the Laplace transform has been used. 4. VALIDATION OF THE MODEL

Validation of CALM model by the field data has been carried out using three classes of parameters: (1)definite parameters i.e. standard morphometric and hydrologic characteristics of the lake-catchment system (see Table 1and Appendix).

454

(2) semi-definite parameters the order of the magnitude of which could be estimated (see Table 2 and Appendix). (3) indefinite parameters which must be found by fitting to the field and laboratory data (see Table 3 and Appendix). TABLE 1 Definite input parameters for CALM model, lake Devoke Water Parameter

Unit

Value

cm2year-' KBq m-2 1 year-' dimensionless km2

547 20 4.1 0.8 3.1

km2

0.3

meq I-' m3 g cm3

varies 191 1 360 000 1.2

TABLE 2 Semi-definite input parameters for CAMS model, lake Devoke Water (best estimations and range) Parameter

Unit

Value

sb

dimensionless 1 kg-1 km2 dimensionless dimensionless

2.OM.5 40000f20000 0.17M.05 l.lM.l 1.3M.15

Rout

Ri

TABLE 3 Fitted input parameters for CALAS model, lake Devoke Water (best estimations and range) Parameter ci

he S

h

Unit

Value

dimensionless Vyear kg m-2 cm

0.001M.0003 0.02M.006 2.2M.2 o.m.0

455

0

0.5

Cs-137activity Bqfg 1

1.5

2.5

2

3

3.5

0 1

2

3 4

5

s6 sa7

6

8

9

-

measured 1992

12

calculated

13

Fig. 2. Calculated and measured ‘37Cs vertical distributionin Devoke Water bottom sediment.

Table 1 presents the values of the parameters from Class 1 and in Table 2 the range for each parameter from Class 2 is given. In fact a wider ranges of semi-definite parameters were tested in computer simulations but after the fitting procedure some of the intervals were narrowed. Each simulation produced Chernobyl radiocaesium profile in bottom sediment and its concentration in lake water by the moment of interest. For various sets (from reasonable range) of semi-definite parameters the fitting to experimental sediment profile sampled in 1992 [91 were performed (see Fig. 2) and indefinite parameters determined. The ‘bombogenic’ part of the experimental profile has not been taken into account. Then the experimental and calculated concentration series were compared (Fig. 4). Table 3 shows a range for the optimized values of indefinite parameters and in Fig. 3 three successive sediment profiles (with best-fit parameters) for 1989, 1992 and 1996 are plotted. 5. CONCLUSION

The CALAS model has shown its validity for reasonable values of semi-definite and fitted parameters (Figs. 2-4) giving the general trend for radiocaesium concentration in the lake water but incapable to predict all the minor variations. The previous data [11,121 on migration of ‘global’radiocaesium within

466

Cs-137activity Bq/g

0

2

1

3

! I

4

5

,

i

I

I

1

2 3 4

6

5

E

B6

a7

8 9 10 11

12

c

Fig. 3. Calculated Chernobyl radiocaesium vertical distribution in Devoke Water bottom

-

measured

caclulated

1

1

CT

m

E

.-a > .-

9 100 --

b

'II k

W

I

101986

1987

1988

1989

1990

Yem

Fig 4. Calculated and measured Chernobyl '37Csconcentrationin the water column of Devoke Water after 1986.

457

lake catchments show that generally maximum 1%of it could be removed from the catchment by rapid flush and <0.1%per annum. Although for the Devoke case rapid flush is of the same order of magnitude, the annual wash-off rate is much higher and is consistent with the data of Davis et al. 1131. Basing on indirect evidence they proposed that up to 5% of the total catchment deposition may have been remobilized in some New England and Scandinavian lakes. It is clear that the model could lose its validity for time periods greater than a decade because in the course of time the wash-off rate significantly decreases due to radiocaesium vertical redistribution in catchment soils. Moreover, statistical uncertainty and sensitivity analysis 1141 has to be done to assess possible deviations in predictions due to parameter uncertainty. Nevertheless, the authors believe that using CALM one can more or less reliably reconstruct the chronology of Chernobyl 137Csbehaviour in the lake system. From this point of view, the model is retrospective rather than predictive. This procedure could also provide an estimation of the retardation factor for the whole catchment from

and it would be very interesting to compare this value with that obtained from direct estimations. One more interesting point is the overlapping of the profiles’ slopes down the Chernobyl peak (Fig. 2), although the slope of the calculated profile does not depend on any indefinite parameter but is definitely predicted by the variation of If the distribution coefficient did not decrease with the depth and growth of ammonium concentration in pore water, the slope of the I3’Cs profile would be much steeper. This is another strong argument for the role of ammonium ions in caesium remobilization. As can be expected, the profiles do not overlap at the bottom of the profile because the model does not take account of bomb testing fallout, hence the modelled profile rapidly tends t o zero.

e.

6. REFERENCES

1. 2.

3.

Camplin, D.R.P. Leonard, J.R. Tipple and L. Duckett, 1989. Radioactivity in freshwater systems in Cumbria (U.K.) following the Chernobyl accident. CEC contract B16 0246, U.K. (H). Fish. Res. Data Rep. 18: 90. Spezzano, P., J. Hilton, J.P. Lishman and T.R. Carrick, 1993. The variability of Chernobyl Cs retention in the water column of lakes in the English Lake District, two years and four years after deposition. J. Environ. Radioactivity, 19: 213-232. Davison, W., J. Hilton, J. Hamilton-Taylor, M. Kelly, F. Livens, E. Rigg, T.R. Carrick and D.L.Singleton, 1993. The transport of Chernobyl-derived radiocaesium through two freshwater lakes in Cumbria, UK. J. Environ. Radioactivity, 19: 125-153.

458 4. Hilton, J., F.R. Livens, P. Spezzano and D.R.P. Leonard, 1993. Retention of radioactive caesium by different soils in the catchment of a small lake. Sci. Total Environ., 129: 253-266. 5. McDougall, J. Hilton and A. Jenkins, 1991.A dynamic model of caesium transport in lakes and reservoirs. Wat. Res., 25: 437-445. 6. Bahr, J.M. and J. Rubin, 1987. Direct comparison of kinetic and local equilibrium formulations for solute transport affected by surface reactions. Water Resources Res., 23(3): 438-452. 7. Cremers, A., A. Elsen, P. De Preter and A. Maes, 1988. Quantitative analysis of radiocaesium retention in soils. Nature, 335: 247-249. 8. Comans, R.N.J., J.J. Middelburg, J. Zonderhuis, J.R.W. Woittiez, G.J. De Lange, H.A. Das and C.H. Van Der Weijden, 1989. Mobilisation of radiocesium in pore water of lake sediments. Nature, 339: 367-369. 9. Comans, R.N.J., J. Hilton and J.T. Smith (manuscript in preparation). 10. Celia, M.A., J.S. Kindred and I. Herrera, 1989. Contaminant transport and biodegradation. 1. A numerical model for reactive transport in porous media. Water Resources Res., 25(6): 1141-1148. 11. Brunskill, G.W., S.D. Ludlam and T.H. Peng, 1984. Fayetteville Green Lake, New York, USA. VIII Mass balance for Cs-137 in water, varved and non-varved sediments. Chem. Geol., 44: 101-117. 12. Davis, R.B, C.T. Hess, S.A. Norton, D.W. Hanson, K.D. Hoagland and D.S. Anderson, 1984. Cs-137 and Pb-210 dating of sediments from soft water lakes in New England (USA) and Scandinavia, a failure of Cs-137 dating. Chem. Geol., 44: 151-185. 13. Helton, J.C., A.B. Muller and A. Bayer, 1985. Contamination of surface-water bodies after reactor accidents by the erosion of atmospherically deposited radionuclides. Health Phys., 48: 757-771. 14. Baverstam, U., P. Davis, A. Garsia-Olivares, E. Henrich and J . Koch, 1993. Guidelines for uncertainty analysis. BIOMOVS I1 Technical Report 1,39 p.

APPENDIX: LIST OF PARAMETERS AND VARIABLES

total Cs-137 volumetric specific activity in sediment [An3] specific radiocaesium activity in solid phase of sediment [A/M] specific radiocaesium activity in sediment pore water [A/L3] total (3-137 specific activity in lake water [ALL3] specific activity of particulate Cs-137 in lake water [AM] specific activity of dissolved Cs-137 in lake water [An3] portion of the rapid flush [dimensionless] caesium molecular diffusion coefficient [L2/TI caesium diffusion coefficient in porous media [L2/T] “asterisk” Darmkohler number [dimensionless] zero Darmkohler number [dimensionless] first Darmkohler number [dimensionless] areal density of radiocaesium deposition [An2] porosity of the bottom sediment [dimensionlessl

459

hydraulic flow [L3R'l total radiocaesium input from the catchment [A/T] cpW tortuosity [dimensionless] h thickness of the boundary layer [L] J(t) total caesium flux from the water column to the sediments [A/L2T] >(x,t) total radiocaesium flux in the bottom sediment [A/L2Tl @(x) distribution coefficient in the bottom sediment [L3/M] distribution coefficient in the water column [L3/Ml L linear scale [Ll 1, radiocaesium wash-off rate from the catchment [1/T] hf hydraulic flushing rate [h"] m pore water-water column mass-exchange coefficient [ZST] m [NH;](x) ammonium concentration in pore water [M/L31 P bottom sediment bulk density [M/L31 r kinetic exchange rate [1/TI R I ~ ) retardation factor for the bottom sediments [dimensionless] RC generalized retardation factor for the catchment [dimensionless] Rl retardation factor for the water column [dimensionless] R0"t retardation factor in the outlet [dimensionless] S sedimentation rate [M/Lvl stl effective sedimentation area of the lake bottom [L21 sc catchment area [L21 SI lake area [L'] suspended solids content in the lake water [M/L3] TI v, lake volume [L21 advective velocity of the pore water [YTI UJX)

F

f(t)

a

Freshwuter and Estuurine Rudioeecology Edited by G. Desmet et al. 0 1997 Elsevier Science B.V. All rights reserved

461

Modelling 226Radispersion in an estuarine system at the southwest of Spain R. PeriAiieza,J.M. Abrila and M. Garcia-Le6nb 'Dpto. Ftsica Aplicada, E. U.Ingenieria Tkcnica Agrtcola, Universidad de Sevilla, Ctra. Utrera km. 1, 41014-Seville, Spain bopto. Ftsica Atomica, Molecular y Nuclear, Universidad de Sevilla, Apdo. 1065, 41080-Seville, Spain

ABSTRACT A numerical model to study 2z6Radispersion in the Odiel river, in which two phosphate fertilizer factories release their wastes, has been developed. The hydrodynamic equations are solved each time step to obtain the suspended matter distribution and the advectivdiffusive dispersion terms, which allow us to include in the model the ionic exchanges of zz6Raamong water, suspended matter and sediments. Good agreement between the computed and measured concentrations of 2z6Rain water and suspended matter has been achieved. 1.INTRODUCTION

The Odiel river, in southwest Spain, discharges its waters into the Atlantic Ocean. Its mouth forms an estuarine system affected by tidal dynamics, Mz being the main component. On the left shore of the river there is an industrial complex in which two phosphate fertilizer processing plants are located. These plants release part of their wastes directly to the Odiel river and elevated concentrations of U, Th and Ra-isotopes have been measured in waters, suspended matter and sediments collected from the river. Our group has been investigating this radioactive impact for some years by measuring concentrations of the above mentioned isotopes in the Odiel river and in the surroundings. We are developing a more quantitative study, by using numerical models, of the radioactive impact and the dispersion of contaminants along the river. In a first stage, the model has been applied to zz6Radispersion, for which enough radiological information is available.

462

According to the literature [ll the medium value for the 226RaKd is 5x1031 kg-', ranging from 0 . 5 ~ 1 to 0 ~5Ox1O31 kg-'. Thus, although most of the 226Ra remains in solution in the Odiel river 121, a fraction of it will associate to suspended matter and sediments. The model must include the ionic exchanges of 226Raamong water and the solid phases. In order to include these ionic exchanges, the suspended matter distribution must be known. Thus, we have developed a hydrodynamic model of the Odiel river. This model is based on solving the hydrodynamic equations with appropriate boundary conditions and with typical time steps of a few seconds. It is briefly presented in Section 2.Then the advective-diffusive dispersion equation for a conservative substance has been incorporated in the model, which is presented in Section 3. The horizontal movement of suspended matter is governed by this advective-diffusive dispersion equation and the vertical movement by the resuspension and deposition terms. Once the instantaneous water state (water elevations and velocities) and suspended matter concentrations are known, "'Ra dispersion can be solved. Dissolved and suspended '"Ra dispersion is governed by the advective-diffusive equation, to which the exchange terms have been added. This is presented in Section 4. Some results are presented in Section 7. 2. THE HYDRODYNAMIC MODEL

Solving the hydrodynamic equations allow us to know the instantaneous water state. The vertically averaged hydrodynamic equations can be written as [3]:

6 2 -+-

6t

6

ii%

6

[(D+z)ul+- [(D+z)ul= o

sy

-+ u -+ u -+ g - - nu + K

u

m

Pa

CD

ax ax D+z pw ( D + z ) aU av aU az Uh%? CD I WI Wsine = 0 -+ u - + u -+ g -+ Ru + K at ay ax ay D+z pw(D+z) at

ay

p a

(2)

(3)

where u and u are the water velocities in the directions of the x - and y-axis respectively, z is the displacement of the water level from the mean depth D,g is the gravity, R is the Coriolis parameter and K is the bed friction coefficient. The last term is the response t o wind stress: pa and pware the air and water densities, W the wind velocity and 0 is the direction to which the wind blows measured anticlockwise from east. An acceptable value for CDis given by [3]: CD

= (0.63 + 0.066 W 1 0 4

if 2.5 < W < 21 with W measured in m s-l, 10 m above the sea level.

(4)

463

The water response to changes in atmospheric pressure has also been included in the model. Thus, for a local variation AP about the mean atmospheric pressure over the ocean, the water level will change according to [31:

m=--AP

(5) g Pw To solve these equations a spatial and temporal discretization of our estuarine site has been carried out and a centred fmite differences scheme was adopted. In Fig. 1the grid used in the model is shown. The compartments’ lengths are Ax = Ay = 100 m and the time step was 6 s. The model resolutions were selected so as to verify the Courant criterion and to minimize the numerical dispersion [4]. In the southern boundary water elevations were introduced for each time step from field data and in the northern border a radiation condition was adopted [51. Depths were introduced as input data for each compartment from marine charts. In Figs. l a and l b water elevation and velocity maps are shown for the case of‘medium tides. Model results are representative of the site, since differences in elevations are a few mm all along the grid, as can be seen in tidal tables. On the other hand, computed water velocities are similar to those measured in the river. In the case of medium tides, computed velocities when water level was increasing and decreasing were 0.45 and 0.61 m s-l respectively, while the b

0

1000

0

1000

0

1000

Fig. 1. Grid used in the model. Water elevations and velocities map for medium tides when water level is increasing (a) and decreasing (b). The step between lines is 3 mm in the first ca8e and 5 mm in the second.

464

measured ones were 0.48 and 0.66 m s-'. In the case of neap tides the computed velocities were 0.38 and 0.29 m s-', while the measured ones were 0.40 and 0.28 m s-' (when water level is increasing and decreasing respectively).The detailed calibration of the hydrodynamic model can be seen in Refs. [41 and [61. 3. THE DISPERSION EQUATION

The dispersion of a conservative substance is governed by an advective-difisive dispersion equation, which can be solved once the instantaneous state of the water is known.This equation can be written as 151:

ac

ac

ac

[y

[;

I];

HK,+- HK,H ax 1 where C is the vertically averaged concentration, which depends on the instantaneous water level H = D + z . The diffusion coefficients have been written as

-+u-+u-=at ay ax

[51:

p1 and Pzbeing numerical factors to be calibrated for each site.

The dispersion equation has been written in finite differences in the following way (see Ref. 141 for details):

An * indicates a value to be calculated at the new time step. H 1 is the depth at

the centre of side 1 of compartment (x,y) and n': and nl are used to avoid transport from water to land compartments and to secure that the advective flux is always in the same direction as the water velocity. This equation has been calibrated in our estuarine site and has been applied in studying 226Radispersion as a conservative substance, as a first approximation. The calibration process consists of selecting the boundary conditions and the numerical values of the diffusion coefficients. The detailed calibration of the equation and its application can be seen in Ref. 141. The suspended matter dynamics can be obtained if some new terms are added to the dispersion equation, which governs the horizontal movement of

465

suspended matter. These terms, which take into account the vertical movement of suspended matter are the resuspension and deposition terms. These terms depend on critical resuspension and deposition velocities in such a way that, if the water velocity is larger than the critical deposition velocity, then the deposition term will be zero, since water turbulence makes particles remain in suspension. On the other hand, if water velocity is smaller than the critical resuspension velocity, then the resuspension term will be zero. As is usual in this kind of study, only particles with a diameter < 62.5 pm will be considered to remain in the water column as suspended matter. Larger particles sink rapidly to the bottom. Under these circumstances, only one resuspension and deposition velocity is used, although the deposition velocity depends on the suspended matter concentration, since clouds of particles sink faster than single particles because some particles fall in the wake of others. On the other hand, the critical resuspension velocity depends on the estuary bed roughness. As this parameter increases, the critical resuspension velocity decreases. A detailed discussion of these processes and their equations can be seen in Refs. [7] and 181. The suspended matter concentration profiles at both high and low water can be seen in Figs. 2a and 2b respectively. The intense peak is due to discharges of material from a mining factory. The model also gives information about the sedimentation rates (net balance between the deposition and resuspension terms) in the river. The averaged

a H

lSO

0

0

1000

Fig. 2. Suspended matter concentration (ppm) profiles in high (a) and low (b) water along the Odiel river. The x-axis is the compartment number. (c):Averaged sedimentation rates in g cm-2 year-'.

466

sedimentation rates along several tidal cycles are shown in Fig. 2c. The positive values indicate that a net sedimentation is being produced in the Odiel river, although the rate is low. A more detailed discussion of the results can be seen in the above mentioned References. 4. IONIC EXCHANGES. 22eRADISPERSION

Four phases or sub grid compartments and two transfer coefficients are considered in our model. The phases are dissolved, suspended matter and two grain fraction of sediments. The transfer coefficients govern the ionic exchanges between them. We will consider that the dissolved and suspended phases are homogeneously distributed in the water column, which is true only for wellmixed waters in depth. Both the suspended and dissolved phases can be exchanged with the surrounding compartments by advection and diffusion. Only the small grain fraction of the sediment (diameter c 62.5 pm) can be resuspended into the water column, adding to the suspended matter. On the other hand, when suspended matter is deposited on the estuary bed, it adds to the small grain fraction of the sediment. The dissolved phase is in contact with the other three phases, so ionic exchange of "'Ra takes place between them. The exchange from dissolved to suspended matter and sediments is governed by a coefficient k1 and the inverse process by a coefficient k,. 5 . THE DISSOLVED PHASE

The equation which governs the time evolution of "'Ra concentration in the dissolved phase is:

H H acd - - k C -+ k, Cam+ k2(sed,+ sed,) at dIF I€ where c d and C,are the 226Raconcentrations in the dissolved and suspended phases respectively and the last term represents the exchange from both fractions of the sediment to water. The first term is transfer from water t o suspended matter and sediments and the second term is transfer from suspended matter to water. The advective-diffusive terms (Eq.6) must be added t o this equation. The transfer from sediments has been written in the following way (in Bq ma):

467

where a,and al are the specific activities (Bq g-'1 in the small and large fractions of the sediments respectively, pa is the sediment bulk density, and L is the mixing length which is 0.1 m @I. and y~' are geometrical factors which take into account that not all the mass of the sediment is accessible to water. Finally, fis the dry weight fraction of small particles in the sediment. The transfer coefficient k1 depends on the amount of suspended matter and sediments. The transfer will increase as these quantities increase since there will be more available surface to exchange radionuclides through. Thus, kl must be proportional to the demand surface per unit volume of water. A more detailed discussion and the mathematical formulation for the demand surface can be seen in Ref. [lo]. The values for the transfer coefficients have been obtained from laboratory experiments which have been developed f 101. 6. THE SUSPENDED PHASE

The activity concentration in suspended matter is governed by the equation:

The advective-diffusive terms must be added to this equation. The resuspension and deposition terms have been written as in the case of suspended matter dynamics, taking into account the critical resuspension and deposition velocities. Now all the exchange processes have been formulated. An additional equation for sediments could be included but, as it has been tested, the rate of change of sediments is much slower than the duration of our simulations. Thus, as a first approach, the zz6Ra concentrations in sediments are considered constants. Finally, the source term for radionuclides in suspended matter and the dissolved phase must be added to Eqs. (9)and (12)in the points where they exist . 7. RESULTS AND DISCUSSION

In July 1990 a sampling campaign was performed in the Odiel river. River water samples were collected at high and low water, and "'Ra concentrations were measured in both the dissolved [ll]and suspended phases [21,The experimental results (points) and the computed 2z6Raconcentrations (lines) are presented in Fig. 3 for high and low water. As it can be seen the agreement is rather good for both phases. To obtain these concentration profiles an investigation of the source term was carried out since it was unknown. The magnitude of the input rate was changed by trial and error until the model reproduced the experimental results.

1000

800

-

__--

600 0

:

400 -

200

-

.............. 0 - ?!

0 *

. I

1600

.. I

.., ..

*

,

....

..............

I

-dissolved

.

..

0

0

.

.. ..

I

-

.

. ,

I

1200 -

400

m.

... ,..

-

-

........................

0

-

800

.

I

2400 -

2000

'..

.-.-suspended

*

dlrrolved

I

* ...h-

0 suspended

I

Fig. 3. Results for 226Radispersion. The x-axis is the position in the grid, points are measured concentrations (mBq 1-' for water and ml3q g-' for suspended matter) and lines are the computed concentrations.

To reproduce the sampling conditions a simulation over three tidal cycles was performed. High water concentrations were obtained from cycle number 2 and low water concentrations from cycle number 3, since both sets of samples were collected with a time difference of 18 hours. Meteorological conditions (wind and atmospheric pressure) for the sampling dates were introduced in the model 141. In the case of high water a short discharge was realized in the beginning of cycle 1; the input rates were 9 . 0 ~ 1 and 0 ~ 9.9~10'Bq per time step

469

for dissolved and suspended matter respectively. In the case of low water the input lasted nine hours and the rates were 2 . 0 ~ 1 and 0 ~ 2 . 5 ~ 1 Bq 0 ~per time step for dissolved and suspended matter respectively. This activity input began in cycle 3. The model also gives information on the distribution coefficients Kd of 226Ra between the suspended and dissolved phases. These are experimentally determined as the ratio of the specific activity in suspended matter and the corresponding specific activity in the dissolved phase. We have considered that only the surface layer of the particles will participate in the ionic exchanges, thus, the centre of the particles will be clean of radioactivity. Obviously this is not true, since 226Rais a natural radionuclide. Thus, to obtain the computed values of& the activities in the centre of the particles have to be added to the activities in the surface layer, which are the calculated by the model. This is related to the f a d that, when a experimental determination of Kd is carried out, the activity present in the central nucleus is also measured (although it is not active). 8. ACKNOWLEDGEMENT

The work was partially supported by ENRESA and the Spanish DGICYT (project PB89-0621). 9. REFERENCES 1. 2.

3. 4.

5. 6.

7

.I

8.

IAEA, 1985. Sediment K,j and concentration factors for radionuclides in the marine environment. Tech. Rep. Ser., 247. Perifiez, R., M. Garcia-Leon and J.M. Abril, 1994. Radium isotopes in suspended matter in a n estuarine system in the southwest of Spain. J. Radioanal. Nucl. Chem. Art., 172: 395-407. Pugh, D.T.,1987. Tides, Surges and Mean Sea Level. Wiley, Chichester. Periaiiez, R., J.M. Abril, and M. Garcia-Leon, 1994. A modelling study of 226Ra dispersion in a n estuarine system in southwest Spain. J. Environ. Radioactivity, 24: 159-179. Prandle, D., 1984. A modelling study of the mixing of 137Csin the seas of the european continental shelf. Phil. Trans. R. SOC. Lond., A310: 407-436. Perifiez, R., J.M. Abril and M. Garcia-Leon, 1994. Aplicacion de modelos numericos a1 estudio de sistemas portuarios: dinamica de las aguas, dispersion de contaminantes y sedimentologia en el Puerto de Huelva ( n o Odiel). Obra Publica, 30: 104-111 (in Spanish). Periafiez, R., J.M. Abril and M. Garcia-Leon, 1996. Modelling the suspended matter distribution in an estuarine system. Application to the Odiel river in southwest Spain, Ecolog. Mod., 87: 169-179. Periaez, R., J.M. Abril and M. Garcia-Leon, 1994. Formulacion y desarrollo de un modelo matematico de un sistema estuario. Aplicaciones, in: A. Valle and C. Pares (Eds.), Modelado de Sistemas en Oceanografia, Climatologia y Ciencias Medioam-

470 bientales. Aspectos matemhticos y num6ricos, Imagraf, Malaga, pp. 205-210 (in Spanish). 9. Abril, J.M., and M. Garcia-Ldn, 1993. A 2D 4-Phases marine dispersion model for non conservative radionuclides. Part 1: conceptual and computational model, J. Environ. Radioactivity, 20: 71-88. 10. Periaez, R., 1995. Un modelo matemhtico para la simulacidn de la dispersi6n de radionficlidos no conservativos en un sistema estuario. Aplicacidn a la ria de Huelva, Ph. D. Thesis, Universidad de Sevilla (in Spanish). 11. Periaez, R. and M.Garcia-Ledn, 1993. Ra-isotopes around a phosphate fertilizer complex in an estuarine system at the southwest of Spain. J. Radioanal. Nucl. Chem. Art., 172: 71-79.

Freshwuter und Estuurine Rudioeco1i1,qy

Edited by C. Desmet et ol. 0 1997 Elsevier Science B.V. All rights reserved

471

Radioecology assessment in waterways in France with nuclear facilities (1989-1993) Luc Foulquier and Alain Lambrechts lnstitut de Protection et de Suretk Nuclkaire, Service d'Etudes et de Recherche sur les transferts duns l%nvironnement, IPSNI CEA, Cadarache, B.P. 1, 13108, Saint-Paul-Lez-Durance,France

1. INTRODUCTION

France covers 75% of its power requirements with the energy produced by 56 nuclear reactors of various types (natural uranium-graphite gas, pressurised water, breeder reactors). All fuel cycle phases exist on the French territory, from mineral extraction to reprocessing of spent fuel and waste storage. The aim of this paper is to summarise, after several years of operation, the radio-ecological impact on French rivers of the fifteen power plants and of the fuel reprocessing plant located next to various rivers (Fig. 1). Within the scope of radio-ecological studies of nuclear sites, carried out by the Protection and Nuclear Safety Institute (on its own initiative, or in the framework of contracts with plant operators) radioactivity due to gamma, beta and alpha emitters is regularly measured in sediments, submerged aquatic plants and fish samples. This report gives the main results observed from January 1989 to January 1993, since previous samplings have already been the subject of various publications 11-51. 2. NUCLEAR SITE RADIOECOLOGICAL STUDY METHODOLOGY

Sampling, preparation and measurement methodologies have been in practice for the last twenty years [ M I .Sediments are sampled using a Berthois cone, aquatic plants are gathered from the bank or a boat; and fish are collected by electric fishing. Conditioning reduces volume by drying or incineration, homogenises the final product, allowing, if necessary, division into equal samples.

472

Gravelines

La Hague Flamanville

Saint Laurent

N

120 km

0

I

@

Natural Uranium Gaz Reactor Breeder

1

A

PWR 900 MWe open circuit cooling

j

I

PWR 900 MWe closed circuit cooling, Towers

4

PWR 1300 MWe open circuit cooling

1

1

PWR 1300 MWe closed circuit cooling, Towers

~

~

Fuel fabrication or reprocessing plant

Fig. 1. Location of nuclear power plants in France.

473

Alpha-emitters are measured by radiochemistry; other radionuclides are detected by Ge y-spectrometry. Sampling, conditioning and measurement data are managed by a relational database using SQL (Structure Query Language). 3. IMPACT OF VARIOUS SOURCES

Some of the detected radionuclides are of natural origin (telluric or atmospheric); others are artificial as the result of bomb tests carried out in the sixties and from the Chernobyl accident, or from liquid effluent released by nuclear installations. Our aim is to determine the impact of the different sources of radionuclides following concentrations found in different compartments of the aquatic ecosystem. For each river, results have been grouped in order to highlight two areas: the part upstream, uninfluenced by nuclear installations, and the section downstream from power stations and, for the Rhone, the area downstream from the Marcoule plant. 3.1. Impact of natural radionuclides

The concentrations of radionuclides of natural source are indicated in Table 1 which gives averages and standard deviations of measurements made from January 1989 to January 1993 on seven rivers. They are due to 40K, 7Be, "'Pb and t o radionuclides belonging t o the uranium and thorium families. Total natural radioactivity is calculated using the formula: 40K+ 7Be + (l.4.238U)+ (10.232Th).In this river, regular sampling of submerged aquatic plants was not possible - only of semi-aquatic plants (not taken into account in this table). Natural radioactivity in sediments ranges from 100 to 1000 Bq kg-' D.W. in the Seine. This value varies from 700 to 3500 in other rivers. This difference may be due to geological differences between rivers basins, the Seine flowing through the sedimentary Paris basin, whereas the other rivers come down from granite formations in the Alps, the Jura, the Massif Central or from the Pyrenees [5,91 The average levels for plants range from 700 to 1600 Bq kg-' D.W., and for fish from 80 to 100 Bq kg-' W.W. Different species of fish or plants are not taken into account, since it is not possible to evidence natural radionuclide concentration variations. Unlike sediments, averages are more closely grouped, since living bodies usually regulate concentrations in chemical elements (potassium in particular). Table 1shows that the nuclear installations considered have no influence on the ecosystem's natural radioactivity [5,91.

474 TABLE 1 Total natural radioactivityof compartments of French rivers, sampled upstream and downstream of nuclear installations (1989-1993) River

Garonne Loire Seine Meuse Moselle Rhine Rhone: Downstream from power plants Downstream from Marcoule

Sediments (Bq kg-' D.W.)

Aquatic plants (Bq kg-' D.W.)

Fish (Bq kg' W.W.)

Upstream Downstr.

Upstream

Downstr.

Upstream Downstr.

1272f504 2496f1005 656f370 1570 1580 1653f395 1342f502

962f284

*

1146f371

85f18 101B 92f19 83f15 79e7 94f31 101f26

1170f291 2008f588 368f301 153W14 1945f420 1620f477

-

*

1065f501 1075 1130f106 1094f928 1564f663

684f517

-

1008k348 940f424

-

91f15 94f7 91f27 81f25 92f14 87f19

-

1705f440

956f475

81f23

2226f225

1592f770

109f18

3.2. Impact of radionuclides from atmospheric fallout

Artificial radioactivity in sediments, submerged aquatic plants and fish, related to fallout from atmospheric weapons tests carried out in the years 1955 to 1965,is still quantifiable, particularly in areas of rivers unaffected by nuclear installations. This fallout contains mainly 137Cs,%3r and 238 239 p U [lo-121.Three decades later, strontium is barely detected, whereas 137Cshas been detected in upstream parts of French rivers (Table 2).In the West of the country (Garonne, Loire, Seine) concentrations of 137Cs are approximately 10 Bq kg-' D.W. in sediments, inferior to 2 Bq kg-' D.W. in submerged plants and below 0.3 Bq kg-' W.W. in fish. These values represent approximately 0.1% of natural radioactivity, and correspond approximately to the values of fallout resulting from overground tests. In upstream areas of rivers in the East of France, concentrations of 137Csare approximately 10 times higher than in the others. These values are due to the radioactive plume which appeared following the Chernobyl accident, which, for meteorological reasons, was not really measurable in other regions of the country. The plume contained 19 radionuclides mainly composed of '03,'06Ru, 134,137C~, and '""Ag [13-151 Fallout from the Chernobyl accident has been measured since the month of May 1986 in the rivers of eastern France. In the upper-Rhone upstream of nuclear installations, radioactivity due to these artificial nuclides was 600 Bq kg-' D.W. in sediments, 1500 Bq kg-' D.W. in aquatic plants and 15 Bq kg-'

475 TABLE 2 Radioactivity of radiocesium in French rivers, sampled upstream of power plants (1989-1993) River

Garonne Loire Seine Meuse Moselle Rhine Rhone

Sediments (Bq kg-' D.W.)

Aquatic plants (Bq kg-' D.W.)

Fish (Bq kg' W.W.)

'34cs

'37cs

"CS

'37cs

'34cs

'37cs

l.lf0.9 l.lf0.8 1.7 1l f 5 4.1f3.7

4.8f3.2 13.6f13.3 13.3f6.0 31 6 65f23 31.3590.9

0.6f0.2 7f9 2.5

1.8M.9 1.5f1.6 4 2.9f2.0 34f37 10.7f5.8

-

0.08f0.05 0.30M.05 0.2f0.1 0.4M.3 3.7f2.1 1.e1.2 1.7fl.l

0.05f0.03 0.2f0.1 0.7M.2 0.3f0.3 0.2f0.1

W.W.in fish [161. Very rapidly, due to effective periods observed in situ, radioactivity levels have decreased in all compartments. Table 2 shows that activity in eastern rivers in 137Csstill varies from 10 to 90, and ranges from 1 to 70 Bq kg-' D.W., respectively, in sediments and submerged aquatic plants; and that is inferior to 6 Bq kg-' W.W. in fish. Caesium-134 is also traceable in rivers not influenced by nuclear installations. This is attributed to the Chernobyl accident, as is shown by the ratio 'TJCs/'34Cswhich was 2 at the moment of the accident and which reached 5.6 in January 1989 and 16.6 in December 1992 due to the decrease of these isotopes [31. 3.3. Impact of radionuclides fiom liquid nuclear power-plant efluent

Power plants release gamma emitter nuclides including 58760C0,'lomAg,lz4Sb, 134,137Cs, 54Mn,and 13'I. Activity released by these radionuclides are approximately 12 GBq for 90 MWe REPs and 9 GBq for 1300 MWe REPs [3,4,17]. In parts of rivers located downstream from all the power plants, artificial gamma radioactivity is inferior to 300 Bq kg-' D.W. in sediments and in aquatic plants, and is 10 Bq kg-' W.W. in fish (Table 3). These values are still considerably lower than natural radioactivity found in the same samples. In general, artificial radioactivity measured downstream is superior to that measured upstream, apart from the Rhine where the influence of Swiss power plant (Gosgen and Beznau) liquid release is still detected. On the contrary, the impact of the Golfech power plant on the Garonne is practically not visible. On the Loire, downstream from Chinon, some sediments sampled in 1990 show concentrations of "'Ag and of '%o superior to normal values. They are not taken into account in the average.

476 TABLE 3 Artificial radioactivity due to gamma emitters in compartments of French rivers, sampled upstream and downstream from nuclear power plants (1989-1993) River

Garonne hire Seine Meuse Moselle Rhine Fthone

Sediments (Bq kg' D.W.)

Aquatic plants (Bq kg' D.W.)

Fish (Bq kg' W.W.)

Upstream

Downstream

Upstream

Downstream

Upstream

Downstream

4.8f3.2 14f14 14f7 33M 6.7 80k29 34lt39

2.5k2.9 19f8 32f56 92258 45*47 71f35 38f30

3.1f2.4

0.1M.3 0.3M.1 O.lM.l 0.3M.4 4.2f2.5 1.7f1.4 1.8f2.4

0.2fo.4 1.5f2.0 0.4fo.2 2.111.4 0.9B.8 1.3fl.l 1.5f2.0

1.4fl.l

-

1.5f1.6 4fO 3.5k1.7 94f89 11.8f9.5

-

24f78

-

27f23 58M4 144f171

TABLE 4 Comparison between liquid release composition from the Tricastin power plant with that of compartments sampled in the Rhone downstream from the power plant (1989-1993) ~

Nuclides

1lOm&

58c~ 6OCO % 'I

137cs

54Mn

Others 141J44Ce+ Pr etc.)

(1249125Sb,

Liquid effluent (GBq)

Sediments (Bq kg-' D.W.)

Aquatic plants (Bq kg' D.W.)

Fish (Bq kg-' W.W.)

10.9 (26.1%) 15.7 (37.7%) 5.8 (14.0%) 0.7 (1.7%) 1.2 (2.9%) 0.6 (1.5%) 5.2 (16.1%)

6.5 (13.3%) 3.5 (7.1%) 3.7 (7.6%) 3.0 (6.2%) 30.1 (61.7%) 0.5 (1.0%) 1.5 (3.1%)

15 (9.2%) 78 (47.9%) 34 (21.2%) 3.6 (2.2%) 16 (9.8%) 4.5 (2.7%) 11.5 (5.6%)

0.6 (16.1%) 1.4 (34.6%) 0.4 (9.3%) 0.2 (5.0%) 1.1(26.6%) 0.1 (2.8%) 0.3 (17.8%)

It is particularly interesting t o compare the distribution of radionuclides of liquid effluents with that in the different compartments of the river's ecosystem. Table 4 shows the example of the Rhone downstream from the Tricastin power plant (Fig. 1). This table reveals that aquatic plants are the most significant i n terms of release composition, and that they make the best contamination bioindicators. Sediments are a privileged stocking environment particularly for 13'Cs, whereas fish only fix very little nuclides but give an image of the long-term evolution of concentrations, particularly for radiocesium.

477

3.4. Impact of radionuclides fiom Marcoule power plant liquid efluents

A fuel reprocessing plant is located on the Rhone at Marcoule, downstream from all the other power plants (Fig. 1). Since 1958,this plant has released in the Rhone, within legal limitations, lo6Ru,13'Cs, '44Ce,'=Sb and alpha emitter nuclides such as natural uranium, Pu,241Am,242p244Cm. The radioactivity levels of effluent from the Marcoule plant are much higher than that of effluent from power plants, but has been decreasing regularly during the last ten years [18-211. Total gamma activity released in the Rhone is of 8 TBq in 1992. Table 5 shows that downstream from Marcoule, artificial gamma radioactivity is approximately 700 Bq kg-' D.W. in sediments, 1500 Bq kg-' D.W. in aquatic plants, which is approximately equivalent to natural radioactivity levels. The y-radioactivity is 20 Bq kg-' W.W. in fish, approximately 25% of natural radioactivity. '=RU and 13'Cs are the most strongly concentrated elements in the different compartments of the ecosystem. Several samples of bivalve mussels, Dreissena polymorpha, collected from 1989 to 1993 on dam walls located downstream from Marcoule, show that these inuertebrata make the best bioindicators of the plant's liquid releases. 23892399240

TABLE 5 Comparison between the composition of the Marcoule plant liquid release and that of compartments sampled in the Rhone downstream from the plant (1989-1993) Nuclides -

Liquid effluent (TBq)

34 (0.4%) 27 (0.3%) 137cs 220 (2.7%) lffiRu 762 (94.2%) Others (54Mn, 183 (2.3%) 6oCo,lZ5Sbetc.) '44Ce '34cs

Sediments Aquatic Fish Dreissena (Bq kg-' W.W.) (whole) (Bq kg-' D.W.) plants (Bq kg-' D.W.) (Bq k g ' W.W.) 35.8 (5.7%) 22.5 (3.6%) 264 (41.8%) 258 (40.9%) 46.3 (8%)

68 (4.7%) 19 (1.3%) 126 (8.7%) 873 (60.2%) 363 (25.1%)

1.9 (10.0%) 0.8 (4.3%) 7.1 (36.4%) 7.7 (39.7%) 1.8 (9.6%)

1.0 (0.8%) 4.3 (3.7%) 10.4 (8.8%) 78.5 (66.0%) 24.6 (20.8%)

Unlike power plants, fuel reprocessing plants release alpha emitter radionuclides. It is particularly interesting to measure the impact of these releases by comparing concentrations found in sediments and submerged aquatic plants sampled immediately upstream and downstream from Marcoule, with those sampled in the upper Rhone (Table 6).In fish, alpha emitter nuclide concentrations are still a lot lower than detection limits. In the sediments, concentrations of 241Amare a factor of 300 higher in samples taken downstream compared to upstream while corresponding values for 238Pu.and 239+240Pu are 400 and 75 respectively. The 238pu/239+240Pu ratio

478

TABLE 6 Concentrationof a-emitter nuclides (in Bq kg-’ D.W.) in sediments and aquatic plants sampled in several parts of the Rhone (1989-1993) 241Am

239+24Opu

Location

Compartment

Upper Rhone Upstream of Marcoule Downstream from Marcoule

Sediments 0.0019M.0018 0.0526M.0282 0.0169M.0196 0.0032M.0016 0.0573M.0274 Sediments Aquatic plants 0.0136M.0119 0.0024M.0028 0.0306M.0292 3.135f1.882 1.320M.713 4.332e.567 Sediments plants 1.180M.085 3.68M.212

0.032 0.066 0.078 0.30 0.32

ranges from 0.03 t o 0.08 upstream of the plant.This ratio is identical t o that found in other French rivers, and is characteristic of old overground test fallout. Downstream from Marcoule this ration is 0.3 agreement to the plant release [11,12,211. 4. CONCLUSION

The results of radioactive measurements of sediments, aquatic plants and fish samples taken from 1989 to 1993 in French rivers show that artificial radioactivity in aquatic ecosystem compartments is very low compared to natural radioactivity levels. Downstream from Marcoule, artificial y-radioactivity was, for a long time, in the same order of magnitude as natural radioactivity but, owing to the fact that new processing techniques were used, the radioactivity of liquid wastes decreased strongly in these last years. Sediments are a privileged stocking environment of radionuclides present in rivers. Submerged aquatic plants are the best indicators of radio contamination, whereas fish which are the only organisms consumed by nearby population, show very low nuclide concentrations. Alpha emitter radio nuclides, released by the Marcoule plant, within legal limits, are detected in sediments and aquatic plants with a 238Pu/239+240Pu ratio of approximately 0.3. 5. REFERENCES Lambrechts,A. and Foulquier, L. 1987. Radioecology of the Rhone Basin; data on the fish of the Rhone (1974-1984). J. Environ. Radioactivity, 5 (2): 105-121. 2. Lambrechts,A.,Levy,F. and Foulquier, L., 1991. Donnbes sur les concentrations en plutonium dans l’bcosystbme aquatique en aval de I’usine de Marcoule. Radioprotection, 26 (4):627-635 1.

479 3. Foulquier, L., Gamier-Laplace, J., Descamps B., Lambrechts, A. and Pally, M., 1991. Exemples d’impact radiokologique de centrales nucleaires sur des cours d‘eau francais. Hydmkologie appliquke 3 (2): 149-208. 4. Foulquier, L., Gamier-Laplace, J., Lambrechts, A., Charmasson, S. and Pally, M., 1993. The impact of nuclear power stations and of a fuel reprocessing plant on the Rhone river and its prodelta. In: Environmental impact of nuclear installations. Proceedings of the joint seminary from September 15-18th 1992 at the University of Fribourg (Suisse), organised by the Societ6Francaise de Radioprotection and the GermanSwiss Fachverband f& Strahlenschutz. pp. 263-270. (5. Lambrechts, A., Foulquier, L. and Garnier-Laplace, J., 1992.Natural radioactivity in the aquatic components of the main French rivers. Radiat. Prot. Dosim., 45 (U4): 253-256. 6. Lambrechts, A., Foulquier, L. and Pally, M., 1990. Methodes d’evaluation de l’impact radi&cologique de l’accident de Tchernobyl sur le fleuve Rhone. In: Environmental contamination following a major nuclear accident. Proceedings of a Symposium, Vienna, 16-20 October 1989, jointly organized by FAO, JAEA, UNEP, WHO. IAEA-SM-30W66: 353-359. 7. Foulquier, L. and Philippot, J.C. avec la collaboration technique de Baudin-Jaulent Y., 1982. MBtrologie de l’environnement. Echantillonnage et pdparation d’organismes d‘eau douce. Measure des radionucleides emetteurs gamma. Rapport C.E.A.R-5164,53 pp. 8. Anonyme, I.P.S.N, 1989. Les etudes de site avant et aprhs Tchernobyl. Radioprotection 24 (2): 139-142. 9. Descamps, B. and Foulquier, L., 1988. Natural radioactivity in the principal constituents of French river ecosystems. Radiat. Prot. Dosim., 24(14): 143-147. 10. Metayer-Piret, M., Gerber, G.B. and Foulquier, L., 1981. Plutonium in freshwater ecosystems: a literature review. Eur. Appl. Res. Rep.: Environ. Nat. Res.Sect. l(3): 417-490. 11. Martin, J.-M. and Thomas, A.J., 1988. Contamination radioactive de l’environnement par l’industrie nucleaire. Actes du Colloque Nucleaire-SantA-SBcuritAorganis6 par le Conseil a n e r a 1 du Tam et Garonne, Montauban, 21-23 Janvier 1988, pp. 347-389. 12. Martin, J.-M. and Thomas, A.J., 1990. Origins, Concentrations and distributions of artificial radionuclides discharged by the Rhone river to the Mediterranean sea. J . Environ. Radioactivity, 11: 105-139. 13. Foulquier, L., 1987. Data concerning the radiocontamination of the freshwater ecosystems aRer the Chernobyl accident. Seminar C.E.CIJ.E.N. International Union of Radioecologists. IXth Annual meeting, Madrid, September 15-19, 1986. Extended Summaries of the Contributions, I.U.R. Secretariat ED, pp. 20-24. 14. Foulquier, L. and Baudin-Jaulent, Y., 1991. The impact of the Chernobyl accident on continental aquatic ecosystems. A literature review. In: Proceedings of Seminar of the Environmental Impact of Radionuclides Released during three Major Nuclear Accidents: Kyshtym, Windscale, Chernobyl, Luxembourg, 1-5 October 1990, pp. 679-684. 15. Foulquier, L. and Baudin-Jaulent, Y.,1992. Impact radi&cologique de I’accident de Tchernobyl sur les kosystkmes aquatiques continentaux. C.C.E. DGXI Radiation Protection, 58,392 pp. 16. Foulquier, L., Descamps, B., Lambrechts, A. and Pally, M., 1991. Analyse et evolution de l’impact de l’accident de Tchernobyl sur le fleuve Rhone. Verh. Int.

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Verein. Limnol., 24: 2352-2355. 17. Anonyme, 1992. Environnement, annexe IX du rapport d’activit6. Direction de la production et du transport, Electricit6 de France, 71 pp. 18. Foulquier, L., Lambrechts, A. and Pally, M., 1987. Impact radiobcologique d’une usine de retraitement de combustible nuclbaire sur un fleuve: le Rhone. Proceedings of an International Conference on Nuclear Fuel Reprocessing and Waste Management, Paris, August 23-27, 1987. Soci6te Francaise d’Energie Nuclbaire, pp. 1063-1071. 19. Foulquier, L., Lambrechts, A. and Pally, M., 1987. Qualitative and quantitative evaluation of long-life radionuclides in the sediments, plants and fish of the Rhone river. Proceedings of a seminar on the cycling of long-lived radionuclides in the biosphere: observation and models (Vol. 2). Madrid, 15-19 September 1986. C.C.E. and C.I.E.M.A.T., 40 pp. 20. Jeandel, C., 1982. Impact de la radioactivit6 artificielle sur l’environnement. Le plutonium et le cbsium dans les estuaires francais. 98me r6union annuelle des Sciences de la Terre. Paris, 1982. St6 Ge’ologiquede France, Mars 1982, p. 326. 21. Levy, F., Clech, A., Giordani, J.M. and Mistral, J.P., 1993. Control and discharge of radioactive liquid effluents from the Marcoule complex. Radioprotection, Fev. 93. Proceedings of the Joint Deceminary, Fribourg, 15-18 September 1992, pp. 37-41.

Freshwuter und Estuurine Rudioecokogy Edited by G . Desmet et al. 8 1997 Elsevier Science B.V. All rights reserved

48 1

The modelling concept for the radioactive contamination of waterbodies in RODOS, the decision support system for nuclear emergencies in Europe W. Raskoba, R. Helingb,A. Popovc and P. Tkalichd aForschungszentrum Karlsruhe GmbH, INR, P.0.Box 3640,D-76021 Karlsruhe, Germany "0. T.I. Dr. Trippe Ingenieurgesellschaft m.b.H.,Amalienstr. 63 165, 76133 Karlsruhe, Germany bNVKEMA, P.O. Box 9035, Arnhem, The Netherlands 'SPA Typhoon, Leninstr 82, Obninsk, Kaluga Region, 249020 Russia dZnstituteof Cybernetics, Prospect Glushkova 42, Kiev, 252 207 Ukraine

ABSTRACT Within its Radiation Protection Research Programme, the Commission of the European Communities has embarked on a major project aiming a t the development of an integrated and comprehensive real-time on-line decision support system (RODOS)for nuclear emergencies in Europe, applicable from the vicinity of the release and the early phase to far distant areas and the later stages of the accident. Since possible accidents may result not only in releases of radionuclides into the atmosphere but also into waterbodies, the direct inflow into, as well as the indirect radioactive contamination of, waterbodies has to be taken into account. For that purpose a model chain has been outlined covering the processes such as run-off of radionuclides from watersheds following deposition from the atmosphere, transport of radionuclides in large river systems (1-D) including exchange with sediments and the radionuclide behaviour in lakes (compartment or 2-Dwith respect to wind induced wave effects). Important exposure pathways which have to be taken into account are, e.g., consumption of fish, drinking water and external irradiation. The present version of the model chain has been applied for the river system Rhine and the lake IJsselmeer in The Netherlands. Based on first preliminary results, the advantages and the still open problems of the present approach will be discussed.

1. GENERAL INFORMATION

RODOS is an integrated real-time on-line decision support system for off-site emergency management after nuclear accidents. It is designed for use in

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Europe afker accidental releases of radionuclides into the atmosphere and to surface water. When completed, it will be able to make transboundary consistent predictions of the measures to be taken in the near, medium and far ranges for the protection of the public in all post-accident phases [41. Since 1990, the Commission of the European Communities (CEC),within its Radiation Protection Program, has funded the development of RODOS. At present, eighteen European institutions participate in the development with FZWINR as the coordinator of the system development. In addition, scientific co-operation has been organised with institutes in the former Soviet Republics (CIS) on the basis of an agreement between CEC and Belarus, Russia and Ukraine for the co-ordination of which FZKANR is responsible as well. Recently, Poland, Hungary, Romania and the Slovak Republic have become associates to the RODOS project. 2. OBJECTIVES AND STATUS OF THE RODOS PROJECT

The main aim of the RODOS project is to develop the RODOS decision support system to the point of practical application; in this way, it would be possible to achieve estimates, analyses and forecasts of accident consequences and protective actions and countermeasures which would be consistent throughout all accident phases and would be carried out in real time and on-line. In particular, all relevant environmental data, including meteorological and radiological information and readings, are to be processed and, by means of computer models and mathematical procedures, t o be converted into understandable, interpretable pictures of current and future radiological conditions. Simulation models for any kind of protective actions and countermeasure, such as sheltering, taking iodine tablets, evacuation, relocation, decontamination, and bans on the distribution of certain food stuffs, are designed not only to permit the extension in terms of time and space to be estimated, but, together with dose models and damage models, also to allow the advantages and disadvantages to be quantified in terms of (avoided) radiation doses or (avoided) health effects as well as the costs arising to society and to the economy. In this way, it is to become possible to arrange combinations of alternative measures in terms of feasibility and effectiveness and, thus facilitate the choice of suitable scenarios. The meaningful application of RODOS for decision support in real situations can be demonstrated only in emergency protection drills. For this purpose, the system will be coupled early to existing meteorological and radiological data networks (KFO systems, meteorological forecast data) and operated on line and in real time. The first pilot version, RODOS-PV1, for on-line test operation in nuclear power plant remote monitoring systems, is to be ready by late 1994. Subsequent testing, under realistic conditions, of RODOS-PV1, and the experience in handling the system by persons involved in the decision making process, will

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greatly contribute to the further development to maturity by late 1996 of the contents of the integrated computer programs, systems functions, and the user interface. 3. CONTAMINATION OF WATERBODIES

The evaluation of the radiological and environmental consequences of the Chernobyl accident demonstrates the significant contribution of contaminated waterbodies comparable with the extent to which the terrestrial pathways contribute to radiological effects [21. Among others, the re-mobilisation of dry and wet deposited material by long term floods and heavy rain events as well as the resuspension of suspended material during storm events resulted in the migration of radionuclides, which affected uncontaminated agricultural s e a s and also drinking water supplies. Radionuclides stored in sediments of lakes and reservoirs by accumulation caused the delay in the loss of radionuclides in the environment. To facilitate and enhance the quality of emergency actions, the mathematical description of the processes, which is indeed very complicate, may be helpful. The decision aiding system RODOS will therefore contain a chain of models, which cover all the relevant processes such as the direct inflow into rivers, the migration and the run-off of radionuclides from watersheds, the transport of radionuclides in large river systems including exchange with sediments and the behaviour of radionuclides in lakes. 4. MODEL DESCRIPTIONS

4.1. Run-off model RETRACE

Run-off is a very complex process to model. It is varying in time and space and needs a lot of different input data with a high spatial (e.g., land use, soil types, plants) and temporal (e.g., precipitation) resolution. Therefore, simplifications of the processes described in the computer codes are necessary. Run-off models contain mainly two parts, the first describing the hydrological (i.e., water) transport, and the second, treating the radiological (radionuclide transport) processes in the watersheds. In RETRACE, which is under development at SPA Typhoon, Obninsk, Russia [8],the description of the water surface flow is based on the mass conservation equation. It is assumed, that the water covers the soil surface as a thin uniform layer. The kinematic wave approach is applied to this surface water layer. The approach of the two dimensional kinematic wave equation, successfully applied in small watersheds 181, is also used for the subsurface flow. The difference in the physical behaviour of both processes is hidden in the parametric description of the velocity of the subsurface flow. The sediment transport is coupled to the kinematic wave approximation by using the equations for the two-phase flow water-sediment.

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The second part of the run-off model describes the behaviour of the radionuclides in the water-soil environment. Radionuclides associated with soil particles can occur in exchangeable and non-exchangeable forms. The exchangeable fraction contains radionuclides bound by the ion exchange mechanism, which can easily interact with water. The non-exchangeable form includes radionuclides which are nearly irreversibly fixated to soil particles or bound in insoluble complex organics [2]. The equilibrium concentration of the radionuclides sorbed on soil particles and in solution is defined by the approach of a distribution coefficient (&). The transport equations of the radionuclides are based on the conservation equation for the total activity of dissolved and sorbed components. It is assumed, that the radionuclides in the upper soil layer with a thickness of 1 mm can contribute to the run-off process by water wash-off and by erosion processes. Other processes are neglected in RETRACE in the early phase after the accident. Additionally, it is assumed, that the concentration of the solved radionuclides in the surface and the subsurface water are in equilibrium (& approach). The equations of the transport of water and sediments together with the equations of the concentration of the radionuclides in water and sediments are treated as a system of differential equations and are solved numerically in RETRACE. 4.2. River models RIVTOX and COASTOX

Two different sets of models for assessing the behaviour of radionuclides in rivers will be implemented in RODOS [ l l l . The one-dimensional model RIVTOX will be used to describe the transport in large river networks, whereas the two-dimensional computer code COASTOX will be applied for assessing the direct impact of radionuclides in rivers up to a distance of about some 10 km and t o describe the behaviour of radionuclides in lakes. The mathematical modelling of the dispersion of radionuclides in the riverflake systems has to deal with hydrodynamicalprocesses and with the transport of radionuclides in solution or sorbed on sediments. Additionally, the interaction of the radionuclides in solution with those in the solid phase, i.e., with bottom depositions and with suspended sediments, has to be taken into account. The one-dimensional computer code RnrI‘OX, which is under development at Cybernetics Centre, Kiev, Ukraine [9], describes the behaviour of the radionuclides in three different phases: in dilution, in suspended sediments and in the bottom depositions. As a first approach for the implementation in RODOS, a l-D “diffusionwavenmodel has been used to describe the cross-sectionally averaged flow in the river network. The equation has been derived from the l-D Saint-Venant’s equation and has been verified on data of the Tvertsa and Dnieper rivers 1121. The radiochemical part of RIVTOX describes the dynamics of the cross-sectionally averaged concentrations of radionuclides in solution, in suspended sediments and in bottom depositions. The equilibrium concentration in the

485

systems “solution-suspended sediments” and “solution-bottom deposition” is treated via the Kd approach, by additionally taking the exchange velocity between solution and particles into account. The set of advection diffusion equations is solved by using a further developed high accuracy method from Holly-Preissman [6], in which the Hermite cubic interpolation of 3rd orders is applied. The two-dimensional model COASTOX [9,121at present uses the steady and depth averaged NavierStokes equations to calculate the velocity field in the river and lake. The influence of wind induced waves and currents is taken into account too. The same approach as in RIVTOX has been used to simulate the radionuclide exchange in the system: solution-suspended sediments-bottom depositions. The 2-D advection-diffusion equations are solved numerically by using a finite element method or a finite difference scheme. Necessary input to COASTOX is the geometrical data of the riverAake bed in a sufficient fine spatial resolution. 4.3. Lake model

LAKECO

The box-type model LAKECO, developed by the KEMA, Arnhem, The Netherlands [5],will be used for predicting the behaviour of radionuclides in lakes and reservoirs. It calculates the concentration of the radionuclides in the water column, in sediments and in the biota dynamically. It is divided into an abiotic part, describing the change of the activity concentrations in the waterhoil column by means of linear differential equations of first order and a biotic one which predicts the transfer throughout the aquatic food chains. The processes which are taken into account are: particle scavengingkedimentation, molecular diffusion, enhanced migration of species in solution due to physical and biological mixing processes, particle reworking - also by physical and biological means - and the downward transfer of radionuclides in the seabed as a result of sedimentation. In sediments, both the fractions of solved and dissolved radionuclides are modelled. The resulting set of differential equations is solved numerically. To predict the transfer throughout the aquatic food chains, a complex dynamic model taking into account the position of the different species in the food web, has been developed. Again the set of differential equations is solved numerically. The dynamic uptake-model for the food chains is based upon studies on mercury in fish, carried out by [31. 5. APPLICATIONS OF THE AQUATIC MODELS

In order to test the aquatic model chain within the frame of the RODOS-project the first step was the application on the River Rhine catchment. As the run-off part is the most crucial one in the model chain, a first test scenario has been outlined which neglects the transport in the river net. As a first step, only the

486

averaged concentration integrated over the first month after the Chernobyl accident has been calculated. Mainly one station near Lobith, situated in The Netherlands, near the German border has been chosen for the comparative calculations (for '37Cs).[71 Comparing the measurements carried out at Lobith with the calculations a good agreement can be observed with the concentration of 137Csin suspended matter (factor of two). But the model over predicts the concentration of 137Csin solution by more than one order of magnitude. Additionally the total amount of transported sediments is too high by more than one order of magnitude. However, this is an encouraging result because there are a lot of possibilities to vary some input parameters and to extend the information on environmental data. If all the input information is once available, especially detailed soil data, one can start with parameter variation studies to improve the model. For example, the concentration of the nuclides in solution is very sensitive to the equilibrium Kd value. As this value may vary over more than one order of magnitude, it may be one of the most promising candidate for the tuning process. A further test scenario will deal with a finer resolution of the time scale, Available are daily averaged concentration values in water, which can be predicted with the model chain. Beneath of this test within the Rhine catchment, each of the models has been tested in several other environments. The l-D RIVTOX model has been applied to the Pripyad River and the Kiev Reservoirs after the Chernobyl accident. It has been used for planning purposes and the prediction of the water quality [ l l ]. The 2-D model COASTOX has been used to analyse the effectiveness of measurements proposed to reduce the transport of radionuclides from the Chernobyl site and the Zaporogskaya site by surface water pathways. Among others, the construction of dams and bottom traps for contaminated sediments has been investigated [ll The lake model LAKECO has been validated within the VAMP-project for several European lakes with varying hydrological and ecological properties [lo]

.

6. DISCUSSION AND FUTURE PLANS

The three sets of aquatic models which are under implementation in the RODOS-system are the first step towards a model hierarchy which may be improved in future if the necessity is given. There are models available of a higher complexity but these models seem to be applicable only for smaller catchments or river nets. The river network, which is connected to the run-off part, has to be provided with an adequate resolution. It must contain a sufficient number of tributaries in a certain region, to allow for a fast enough transport of the run-off water. If the run-off model has to transport the water over a greater area, in which the smaller rivers are neglected, the transport velocity of the water would be too

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slow. Additionally the capability of the water to penetrate the soil again will be overestimated. Having this in mind, the present river net model RIVTOX is designed t o contain the information of about 310 rivers tributaries and branches distributed over the whole Rhine catchment. The results of the model chain, the activity concentration in solution, in fish, in sediments, in bottom sediments and possibly in banking and flooding areas, will be the input for further dose models. To that purpose, dose assessment modules will cover the exposure pathways: internal irradiation from drinking water and consumption of foodstuffs, including fish as well as external irradiation from the ground surface. Finally, the simulation of different emergency actions will cover the management of drinking water supplies (e.g., filtering, interdiction, diversion, etc.) and the agricultural countermeasures (e.g., banning of foodstuffs, etc.). 7. ACKNOWLEDGEMENTS

This work was carried out within the framework of the “CEC/CISAgreement for International Collaboration on the Consequence of the Chernobyl Accident”. 8. REFERENCES

1. 2. 3.

4.

5.

6.

7. 8.

Borzilev, A. e t al., 1989. Forecasting of secondary radioactive contamination of the rivers in the 30th kilometers zone of the Chernobyl NPP. Meteorologica i Gidrologica, 2: 5-13 (in Russian). Bulgakov, A. et al., 1992. Prognosis of Sr-90 and Cs-137 Behaviour in Soil-Water System after the Chernobyl Accident, Ecologic and Geophysics Aspects of Nuclear Accidents. Hydrometeorological Publishing House, Moscow, pp. 2 1-42. De Vries, H. Pieters, 1989. Bioaccumulation in pike perch, data analysis on data of Lake IJsselmeer, Lake Ketelmeer, and Lake Markmeer. in: Accumulation of Heavy Metals in Organics. Delft Hydraulics and National Institute of Fishery Investigations. Ehrhardt et al., 1993. Development of RODOS, a comprehensive decision support system for nuclear emergencies in Europe -a n overview. Radiat. Prot. Dosim., 50 (2-4), 195-202. Heling, R., 1993. The Ecological Consequences of an Accidental Release of Radionuclides on the River Rhine for the Lake IJsselmeer. Unpublished internal RODOS-report, draft version. Holly, M., 1987. Physical Principles and Dispersion Equations. Development of Hydraulic Engineering, Vol. 3, pp. 1-37. Kroesbergen, L. van, E. Ballegooijen, K.B. Uunk, 1988. Radioactivity in the Dutch inland Waters aRer Chernobyl. Ministry of Tranport and Public Works, Public Works Department (in Dutch). Popov, A. and R. Borodin, 1993. Description of a Physically Based Distributed RETRACE Model to Simulate Radionuclide Transport in Runoff Water. Unpublished internal RODOS-report.

488 9. Tkalich, P., 1993.The Computer codes for Describing the Transport of Radionuclides in a River System. Unpublished internal RODOS-report. 10. VAMP Aquatic Workgroup. VAMP report: Modelling of Radionuclide Tranport into Lakes, Vienna, to be published. 11. Zhelesnyak J. et al., 1993.Radionuclides aquatic dispersion models first approaches to integration into the CEC decision support system based on post-Chernobyl experience. Radiat. Rot. Dosim., 60 (24):235-242. 12. Zhelesnyak, J. et al., 1992.Mathematical modelling of radionuclide dispersion in the PripyatDnieper aquatic system after the Chernobyl accident. Sci. Total Environ., 112:89-114.

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Freshwuter und Estuurine Rudioecology

Edited by G. Desmet et d. Q 1997 Elsevier Science B.V. All rights reserved

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Assessment of the dispersion of radionuclides in flowing water using a dynamic model H. Hofera and A. Bayerb aABB Reaktor GmbH, Abteilung Strahlenschutz, Postfach 100563, 0-68140Mannheim, Germany (Present address: Hofer & Bechtel GmbH, Postfach 1068,D-63527 Mainhausen, Germany) bBundesamt fur Strahlenschutz, Institut fur Strahlenhygiene, Postfach 1108, 0-85762 OberschleilJheim,Germany

ABSTRACT A one-dimensional model has been developed which is used to calculate the concentration of radionuclides in water, suspended matter, and sediment along a river. The model is based on three coupled differential equations, corresponding to the three interacting environmental sectors, which have to be solved numerically. In the example given -a four hour release of 137Csinto the Upper Rhine - a Runge-Kutta method was used to solve the equations. Long-term effects, such as desorption of radionuclides from sediment back into water, are investigated and areas for further development of the model are discussed. Although this dynamic model is especially suitable for short-term releases, it had to be validated using a long-term source term due to the lack of appropria t e measurements. There was satisfactory agreement between t h e available measurements and the calculated results.

1.INTRODUCTION

The model described in this paper is used to calculate the distribution of radionucPides released into flowing water in the environmental sectors’ water, suspended matter, and sediment as a function of time and site. For this purpose the river is subdivided into defined longitudinal sections along its flow direction. The model describes both the interaction of the three environmental sectors within a river section and the links of these sections (see Fig. la and lb). Mathematically, the model is represented by a system of three coupled, ordinary differential equations of the first order. In the example given it was solved by a Runge-Kutta procedure of the fourth order.

490

suswnded mafier

desorPtlon

sdwtlon

I

t

sediment

I

Fig. la. Linkage of the environmental sectors within a river section.

n-1

Fig. lb. Linkage of the river sections and connection of river sections.

2. VALIDATION OF THE MODEL

The validation of the model was based on measurements of the concentration of cobalt-60 in suspended matter in the river Weser, due to releases from the Wurgassen nuclear power plant, obtained from two different measurement

491

sites [ll . The available quarterly mean values of the '%o discharges were taken as a source term. The model is particularly suited for calculations following short-term releases. The time needed to establish the state of equilibrium regarding suspended matter is about 30 h. Thus a source term assumed to be constant over a period of 3 months (ca. 2000 h) must be regarded as a long-term source term. The measured values are available also as quarterly mean values. Accordingly the dynamic behaviour of the model could not yet be validated. For the "limited validation" there is satisfactory agreement between the available measurements and the results from model calculation 121. 3. EXAMPLE OF A CALCULATION PERFORMED BY THE MODEL

The source term assumed in the followingexample consists of a total of 3.7~10" Bq 137Cs, released into the Upper Rhine, at a uniform rate over a period of 4 h. For this short-term source term a length of river 100 km downstream of the site of the release was considered for a period of one year after the onset of release. The results of these calculations are shown in Figs. 2a-c and 3a-c.

1000 100 10 1

0,1

0,011 0

I

I

I

I

I

I

I

I

I

5

10

M

20

26 t [hl

30

35

40

46

- km -E+

1

km6O

+ km16 ++

km81

Fig. 2a. Activity concentration in water.

* km39 4+ km 102

SO

492

10000.00 1000.00 100,00

10,oo 1,OO

0

5

- km 1 -a-

km60

10

15

25

20

t

+ km 18 +-

km81

Fig. 2c. Activity concentration in sediment.

Ihl

30

35

40

iK- k m 3 9

-e-

km102

45

50

493 Ctw IBcVm31

0,100

0,o 10

0.00 1

10

I

I

1

1

2

3

4

1

1

1

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7

8

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Csm IBq/kg]

1

0,1

0,o 1

0,oo 1 0

1

5 6 t Ihl*1000

-

km 1

-+ k m 1 8

-e-

km60

+-

km81

Fig. 3b. Activity concentrations in suspended matter.

* km39 -&

k m 102

10

494

100

Cse [Sq/kgl

I ! 0

I

I

I

I

I

I

I

I

I

1

2

3

4

5

6

7

0

9

- km --Ec

1

km60

tIhl*1000

+

kml8

+

km39

+

km81

-e-

k m 102

10

Fig. 3c. Activity concentrations in sediment.

3.1. Short-term (50 h period)

The maximum values of radionuclide concentration in the 3 environmental sectors were found to occur at different times and thus at different sites. The maximum concentration in water is reached within the first section where the release occurs, amounting to 2 . 3 ~ 1 Bq 0 ~ma. As a result of dilution and adsorption, the highest concentrations within the water decrease along the further course of the river. The complete adsorption of radionuclides to suspended matter is a process requiring a certain time. Suspended matter which is subject t o motion reaches its maximum value of activity concentration about 18 h after the onset of the release, 60 km downstream of the site of release, amounting to 9 . 6 ~ 1 Bq 0 ~ kg-'. During the further course downstream the highest concentrations of radionuclides in suspended matter decrease slowly because of the dilution by non-contaminated suspended matter which counteracts the adsorption, so that the theoretical equilibrium, characterized by the Kdvalue is never reached. The sediment is primarily linked to the water by adsorption. The maximum value of activity concentration in sediments is therefore also reached within the first section, amounting to 60 Bq kg-' (referred to dry mass). The active sediment layer is not subject to motion in the model, so that the adsorption comes to an end when the radioactive wave has passed by. Comparing the

495

velocity of sediment transportation of about 3 km s-' with the velocity of water and suspended matter of about 1.2 m s-', it is obviously justified to neglect sediment transport in this context. The concentration of radionuclides in sediments remains approximately at the value reached after passage of the contaminated wave. The activity concentration in water and suspended matter also remains fairly constant after this time. This can be explained by the static sediment acting as a store of activity and therefore as a source term for the uncontaminated, mobile water and suspended matter coming from upstream. 3.2. Long-term (one-yearperiod)

The long-term effects on the radionuclide concentration in water, suspended matter, and sediment can be regarded as the continuation of the situation after the contaminated wave has passed. The long-term activity concentration in water at the site of release is lower than in the following kilometres. This can be explained by the short time that the water is in contact with the sediments in the first kilometre, which is not sufficient to desorb the theoretical maximum amount of radionuclides. For the following river sections an equilibrium is reached. The water which is already contaminated at a distance >1 km is still desorbing radionuclides, whereas the supply of radionuclides from the sediment is decreasing. The sediments of the first river section are permanently in contact with uncontaminated water, which leads to the greatest leaching out of radionuclides there. After a certain time, when the activity concentration of the sediments in the first kilometre is already low, sediments in the river-sections further downstream are leached out to a greater extent to reach a state of equilibrium. This is shown in Fig. 3c, especially for the results at 18 km and 39 km after about 2000 h and 4000 h, respectively. The maximum radionuclide concentration in sediments moves over the time period considered from the first km shortly after the onset of release to 39 km after one year. As for the short-term effects, the activity concentration in suspended matter is linked to that of water. A certain flowing-timeis required to reach a state of equilibrium, therefore the maximum radionuclide concentration in suspended matter is found at 102 km for the example given. In summary, the following can be stated: - Short-term effects - aRer the radionuclides are released into the water, with time they are partly adsorbed by suspended matter and sediments. - Long-term effects - after the passage of the contaminated wave the sediments act as a store for activity. Fresh water coming from upstream of the release site desorbs radionuclides from the sediments. These radionuclides are then partly adsorbed by suspended matter, which is transported together with the water.

496 4. OUTLOOK

The next stage in the further development of the model is to carry out a complete validation of the model as this has not yet been done, especially for the dynamic behaviour. Data for the validation can probably be obtained from the IAENCEC research programme VAMP (VAlidationof Model Predictions). Emphasis should also be made on relating the behaviour of radionuclides in sediments to that in other environmental sectors [31. For more realistic scenarios examples including tributaries and a source term consisting of a mixture of radionuclides have to be considered. 5. REFERENCES 1. 2.

3.

Mundschenk, H., 1984. a e r das Verhalten von Radionukliden in FlieRgewhsern am Beispiel von co-60 aus dem Kernkraftwerk Wurgassefleser. Deutsche Gewasserkundl. Mitteil., 28: 134. Hofer, H., 1992. Berechnung der Ausbreitung von Radionukliden in FlieRgewassern nach stiirfallbedingten Einleitungen mit Hilfe dynamischer Modelle. Diplomarbeit am Institut fur Reaktortechnik, Universittit Karlsruhe. Hofer, H. and A. Bayer, 1993. Calculation of radionuclide dispersion in flowing waters with a dynamic model. Kerntechnik, 58, No. 3.

497

Subject index Abramis brama, 3 4 0 4 4 0 acclimation, 65, 321 accumulation, 299,329435,413 accumulation rate, 236 Adige river, 236,238 adsorption, 173 adsorption coefficient see Kd adsorption sites, 106 advection, 156 advective transport, 59 A I A M principle, 84 algae, 61 algae, afinity for iodine, 247 Amazon river, natural radionuclides in, 281-289 Ambloplites rupestris, 388 amencium-241,186,194,477 Arniurus nebulosus, 376 ammonium, 52,142 ammonium in anoxic sediments, 130 anaerobic conditions see anoxic conditions Anodonta sp., 345 anoxic conditions, 52,58, 120, 130, 359 antimony-125,475 Arabidopsis thaliana, 330,335 Astacus leptodactylus, 346 Bacopa caroliniana, 200 bacteria, 353,356358 Baltic-North Sea estuary, 407 barium, 205 harium-140,78, 186 beryllium-7,473 bioaccumulation, 353,354,387392) 395 bioavailability, 299-305 hioconcentration factor, 23 1 bioindicators, 308 biological half-life, 396,403 biological half-life of radiocaesium, 376

biological half-life of tritium, 156 biological membranes, 93 BIORAD Model, 428 biosorption, 353, 354 biota, 59 bivalves, 477 Blacksistjarn lake, 225-232 Blicca bjoerkna, 340-350 bluegill see Lepomis macrochirus bog, 437 bottom sediment, resuspended, 111 bottom sediments, 109, 185,443,451 boundary layer, 56,57 brackish environments, 106 bream see Abramis brama brown trout see Salmo trutta bryophytes, 307,310,313,315 Ca2+,330 caesium-134, 131, 186, 204,217, 399, 402404,474,475 caesium-137,76,87,97, 109-113, 131, 183,186,187,204,235-239,282, 428,435,441448,474 caesium-137, contamination of fish in Kiev reservoir, 339-350 caesium-137, ecological half-life, 227, 250 caesium-137, BlacksLtjtirn lake, 225-232 caesium-137, Cyprinus carpio, 369473, 375-384 caesium-137, Danube river, 250,251, 257-258 caesium-137, Kiev reservoir, 261-266 caesium-137, Lake Constance, 217-223 caesium-137, northern Adriatic, 241-247 caesium-137, Par Pond, 193-201 caesium-137, Rochedo Reservoir, 119-126

498 caesium-137, small Swedish lakes, 167-179 caesium-137, Stella river, 97-107 caesium-137, Vorsee lake, 141-149 C A W model, 450,451,453,454 calcium, 321-327 carp see Cyprinus carpi0 carriers, 330 Catalan river, 275 catchment basins, 433439,441448, 449-459 catchment processes, 54-56 catfish see Amiurus nebulosus cell, 62 Cemit4rio lake, 288 cerium-141,185,186 cerium-144,78, 185,186 cesium see caesium channels, 6345,299,330 Chara australis, 335 charr, 66 chemical speciation, 64,299,301 Chondrostoma polylepsis polylepsis, 395-404 C1-, 330 clay minerals, 221 cobalt, 301 cobalt-57,322 cobalt-58, 109, 110,316,317,475 cobalt-60,307,314,429,474,490 committed collective doses, 81 common carp see Cyprinus carpio concentration factor, 59,61,331,395, 399,400,401,413 concentration ratio, 199 cooling pond, 375-384 copper, 311,312 Cormor river, 246 correlation analysis, 203 cost-benefit analysis, 81 countermeasures, 7 5 , 7 7 4 1 cunum-244,194 Cyperus erythrorhizos, 200 Cyprinid fish, 395-404 Cyprinus carpio, 299-305,321427, 369373,376384 Danube river, 249-254,256260 Desna river, 78,264,265

desorption, 212,309 Devoke Water, 21,23,24,32,130,136, 174,209,210,212,449-459 dietary uptake, 321 direct uptake, 321 dispersion, 156 dispersion equation, 464 distribution coefficients, 434 see also Kd distribution coefficients of radiocaesium, 129-139 Dnieperriver, 75,79,83, 183, 184, 186, 188,190,261,262-265,340,436 dose rates, 428 dose to man, 416,434 Dreissena polymorpha, 477 Dreissena sp., 345 drinking water, 78,82 Dudvah river, 112 ecological effects, 66 Elbe river, 203-205 electrochemical gradient, 330 electrochemical potential, 63,331, 333 Eleocharis acicularis, 200 elimination, 403 empirical data, uncertainty in, 22 enzyme kinetics, 64 Ephermeroptera, 346 erosion, 189, 197 Esm Iucius, 33,339-350 Esthwaite Water, 21,32,130,134, 137 Eupatorium sp., 200 eutrophic lake sediment, 141-149 exchangeability, 138 exchangeable Kd, 175 excretion, 69,369-373 exposure, 65,321 Faustino lake, 288 fertilizers, 409 fish, 425-432; see also individual types of fish fixation, 138 flu, 435 food, 59 frayed edge sites, 51,130,138,165,180, 208 free metal ion, 300 freshwater plants, 329

499 Freundlich isotherm, 53 Friuli-Venezia Giulia region, 242 Gummarus sp., 346 Garonne river, 474476 Gbsterosteidae, 346 gill membrane, 66 gills, 322,323, 373 Gobiidae, 346 Gracilaria, 243,244 Grado lagoon, 243 groundwater, 78,79,83 growth, 59,60 Cfymnocephaluscernua, 340-350

3Hsee tritium Hollands Diep, 130, 133, 137 hot particles, 186 hydraulic flushing, 56 illite, 49, 53, 179 illitic clay, 130 Ilya river, 262,264,265 immobilisation, 54 infinite bath procedure, 209 insolubilisation, 353,354 interstitial water, 57 inventory, 197,445 iodine-131, 186,246, 247,475 ion exchange, 51,106,124, 135,142, 208,466 ion pumps, 64 Iput river, 185 Irish estuaries, 419424 irrigation, 82 Isonzo river, 236,237,238,243 Jarama river, 275 Juncus effusus, 200 Kk,52,330 K-moderator, 34 Kanev reservoir, 263-265 kaolinitehllite ratios, 124, 125 K,,, 49, 57, 106, 121, 131, 255-260,263, 317,484,485,494 Ketelmeer, 52, 130, 132, 137 Kiev reservoir, 209, 210,212, 261-266, 339350,486

kinetic constants, 309,314 kinetic control, 53 kinetic models, 110 kinetics, 109, 173-182,331 Kohanovskoe lake, 174 Labe river see Elbe lagoon environment, 97,241 lake processes, 56-58 Lake Bracciano, 21, 30,32 Lake Constance, 217-223 Lake Hillesjon, 21,32,88,89,92,228,439 Lake Hoysjaen, 66 Lake IJsselmeer, 32 Lake Is0 V a l k j b i , 21, 29, 31, 32 Lake 0vre Heimdalsvatn, 21,32,38,39, 88,89,92,228 Lake Saarisjarvi, 88,89,91,92 Iargemouth bass, 195 lead-210,252,271, 291-296,441448, 473 Lepomis macrochirus, 377,388, 389,391 Loire river, 474476 Lucioperca lucioperca, 376 Lysmata seticaudata, 415 manganese-54,475 Marano lagoon, 243 mathematical modelling, 160, 173, 307318 maximum permissible level, 77 Meia-Ponte River, 120 membrane potential, 63,332,333 Meuse river, 356,357,474476 Michaelis-Menten, 64,65,302,333,334 microalgae, 329 microbial activity, 145, 353466 Micrvpterus salmoides, 195 migration, 434 mineralogical analyses, 101 models, 461,489496 molecular diffusion, 56, 57 Moselle river, 474476 mussels see Mytilus edulis Myriophyllum spicatum, 142, 145 Mytilus edulis, 407,409-416,419-424 NH;, 52, 135,142,144,145,146 Najas minor, 201

500 natural radioactivity, 267-278 natural radionuclides in the Amazon river, 281-289 Nernst potential, 331,333,334 niobium-95, 78, 186 Nitella translucens, 335 Northern Adriatic Sea, 235-239, 241-247 Odiel river, 267-278,291,461 organic carbon, 205 organic matter, 93, 146, 179, 265,355 Ottawa River, 388,389,390,391

Panicum sp., 200 Par Pond, 193 particle settlement, 57 particles, 56, 105 Passarinho lake, 288 peat bogs, 54 Perca fluviatilis, 33, 227,340-350,376 perch see Perca fluviatilis pharmacokinetic model, 64 phosphate fertilizer, 461 phosphate industry, 267-278,291-296 phosphorus plants, 409416 Piave river, 236,238 pike see Esox lucius pike-perch see Lucioperca lucioperca Pinus sp., 200 plants, 329 Platyhypnidium riparioides, 307-3 18 plutonium, 80 plutonium-238,474,477 plutonium-239, 185, 186, 194,474 plutonium-240, 194 Po river, 236,237,238,436 polonium-210,271,407, 409416, 419-424 Polygonum sp., 200 pore water, 135,147,451 potassium, 52,61433,369473,395-404 potassium-40,473 precipitation, 293 predictive power, 4-8 primary production, 355 Pripyat river, 76,77,79,183,184,186188,190,261,262-265,340,436,486 pumps, 330

radiocaesium, 93,97, 165, 173,207,235239, 329-335, 387-392, see also caesium-134, caesium-137 radiocaesium, biological half-life, 376, 396 radiocaesium, distribution coefficients of, 129-139 radiocaesium uptake, 395-404 radiocesium, modelling of in lakes, 3 radiocesium see radiocaesium radiocobalt, 66, 299-305,321427, see also cobalt-57 cobalt-58, cobalt-60 radionuclides, 425-432 radiostrontium, 207, see also strontrium-90 radon-222,83 radon-226,83,205,252,271,282,288, 461469 radon-228,204,205 Red Forest, 79 redeposition, 228 redissolution, 145 redistribution, 167-179,228 regular exchange sites, 208 remobilization, 173 resuspendable bottom sediments, 111 resuspension, 89,91, 167,225,228,244, 434,465 retention, 403 Rhine river, 436,474-476 Rhone river, 474-476 Riccia fluitans, 329-335 rivers, turbulence in, 58 roach, 33 roach see Rutilus rutilus Rochedo Reservoir, 119-126 rock bass see Ambloplites rupestris RODOS,481487 rudd see Scardinius erythrophthalmus ruffe see Gymnocephalus cernua run-off, 56,434,483,484 Runge-Kutta method, 489 ruthenium, 68

ruthenium-103,78,186,474

ruthenium-l06,78, 186,474 Rutilus rutilus, 340-350 Saarisjlirvi lake, 228 S a l k sp., 200

501

Salmo trutta, 33,66,376 Savannah River, 425 Scardinius erythrophthalmus,340-350 Scirpus cyperinus, 200 screening model, 425-432 seasonal cycling, 141 seasonal patterns, 387-392 seasonal variability moderators, 35 secondary contamination, 83 secondary sources, 80,225 sediment, 56,79,91,97, 121, 141, 173, 196, 203,207,293,295,353,359, 429,433439,442,443,449-459, 489,494 sediment cores, 219,236 sedimentation, 217 sedimentation rates, 131, 196,465 Seine river, 474-476 selectivity coefficient, 135 selectivity coefficient, K, sequential extraction, 144 shallow lakes, turbulence in, 58 Silver-llOm, 474,475 silver bream see Blicca bjoerkna size effect, 346, 347, 375 soils, 56, 173, 174 Solimoes river, 282 sorption, 51, 56, 156, 309,434 sorption sites, 49, 51 Sozh river, 183,184,186,188,190 Spanish estuaries, 461-469 stable caesium, 395-404 Stella river, 97, 100, 101, 103 Stizostedion vitreum, 392 strontium-90, 76,87,90,93, 183, 187, 194,435,474 sub-tropic aquatic environments, 120 suspended matter, 97,265,464,489 suspended particulates, 111,119 suspended sediments, 485 suspended solids, 109 Tagliamento river, 98,236,237,238, 243 T a p s river, 117,275 Tejo estuary, 208,209,212 Tejo river, 208,209,212 tench see Tinca tinca

Teterev river, 536 thorium, 473 thorium-228,204,205 thorium-232,205,282 time dependence, 176,178 Tinca tinca, 340-350 Tinto river, 267-278,291 totaI Kd, 175 total radiation dose, 82 trace metals, 353466 tritium, 151-163,250,252, 428 trophic chain, 60 trophic transfer factor, 59 trout see Salmo trutta Tupe lake, 288 turbulence, 57, 58 Typha latifolia, 200, 201 Ubort river, 185,186 ultrafiltration, 89 Ulva, 243-246 uncertainty in empirical data, 22 Unio sp., 345 unselective sites, 51 uptake, 59,60,62, 93, 299,300,316, 329435,399 uranium, 473 uranium-238,83,205,268 Uzh river, 262,264,265,436

VAMP model, 19-21,38,449 vegetation, 200 Viviparus contectus, 345 Vorsee lake, 141 walleye see Stizostedion vitreum water discharge, 77 water retention rate, 36 water supply, 83 Weser river, 490 White Oak Lake, 377,388 whitefish, 33 zeolite, 79 Zhelon river, 185 zirconium-95, 78, 186 zooplankton, 66