Barrier systems for environmental contaminant containment and treatment

BARRIER SYSTEMS for ENVIRONMENTAL CONTAMINANT CONTAINMENT and TREATMENT

BARRIER SYSTEMS for ENVIRONMENTAL CONTAMINANT CONTAINMENT and TREATMENT Edited by

Calvin C. Chien • Hilary I. Inyang Lorne G. Everett

Boca Raton London New York

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Published in 2006 by CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2006 by Taylor & Francis Group, LLC CRC Press is an imprint of Taylor & Francis Group No claim to original U.S. Government works Printed in the United States of America on acid-free paper 10 9 8 7 6 5 4 3 2 1 International Standard Book Number-10: 0-8493-4040-3 (Hardcover) International Standard Book Number-13: 978-0-8493-4040-6 (Hardcover) Library of Congress Card Number 2005047215 This book contains information obtained from authentic and highly regarded sources. Reprinted material is quoted with permission, and sources are indicated. A wide variety of references are listed. Reasonable efforts have been made to publish reliable data and information, but the author and the publisher cannot assume responsibility for the validity of all materials or for the consequences of their use. No part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers. For permission to photocopy or use material electronically from this work, please access www.copyright.com (http://www.copyright.com/) or contact the Copyright Clearance Center, Inc. (CCC) 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400. CCC is a not-for-profit organization that provides licenses and registration for a variety of users. For organizations that have been granted a photocopy license by the CCC, a separate system of payment has been arranged. Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe.

Library of Congress Cataloging-in-Publication Data Barrier systems for environmental contaminant containment and treatment / contributing editors, Calvin C. Chien, Hilary I. Inyang, Lorne G. Everett ; prepared under the auspices of U.S. Department of Energy, U.S. Environmental Protection Agency, DuPont. p. cm. Includes bibliographical references and index. ISBN 0-8493-4040-3 (alk. paper) 1. In situ remediation. 2. Sealing (Technology) I. Chien, Calvin C. II. Inyang, Hilary I. III. Everett, Lorne G. IV. United States. Dept. of Energy. V. United States. Environmental Protection Agency. VI. E.I. du Pont de Nemours & Company. TD192.8.B375 2005 628.5--dc22

2005047215

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and the CRC Press Web site at http://www.crcpress.com

Contributing Editors Calvin C. Chien, Ph.D., P.E. DuPont Fellow DuPont Wilmington, Delaware Hilary I. Inyang, Ph.D. Duke Energy Distinguished Professor and Director, Global Institute for Energy and Environmental Systems University of North Carolina, Charlotte, North Carolina Lorne G. Everett, Ph.D., D.Sc. President L. Everett and Associates, LLC Santa Barbara, California Prepared under the auspices of U.S. Department of Energy U.S. Environmental Protection Agency DuPont With contributions by renowned experts on waste containment and waste treatment science and technology 2005

Technical Review Board David E. Daniel, Ph.D., Overall Book Reviewer University of Illinois Urbana-Champaign, Illinois Skip Chamberlain U.S. Department of Energy Washington, DC Calvin C. Chien, Ph.D., P.E. DuPont Wilmington, Delaware

Lorne G. Everett, Ph.D., D.Sc. L. Everett and Associates, LLC Santa Barbara, California Brent E. Sleep, Ph.D. University of Toronto Toronto, Ontario, Canada Craig H. Benson, Ph.D., P.E. University of Wisconsin Madison, Wisconsin

Annette M. Gatchett U.S. Environmental Protection Agency Washington, DC

Ernest L. Majer, Ph.D. Lawrence Berkeley Laboratory Berkeley, California

Hilary I. Inyang, Ph.D. University of North Carolina Charlotte, North Carolina

David J. Borns, Ph.D. Sandia National Laboratories Albuquerque, New Mexico

Special Contributors Jada M. Kanak, Special Technical Assistant DuPont Wilmington, Delaware Kathy O. Adams, Contract Technical Writer DuPont Wilmington, Delaware

Introduction Significant advances in subsurface containment technology occurred in the 1990s, both with the improvement of the technology and the broader acceptance and applications as a measure for environmental remediation. Since 1995, the U.S. Department of Energy (USDOE), U.S. Environmental Protection Agency (USEPA), and DuPont have collaborated on a series of organized efforts to advance this technology. In that year, these collaborators sponsored an international expert workshop that led to the publication of the first major book on containment technology. Two international conferences were held by the same three partners in 1997 and 2001, with individuals from all over the world attending. Although subsurface containment technologies are becoming increasingly acceptable and popular in the environmental remediation field, questions remained on the prediction and verification of long-term barrier performance and this subject began to gain interest from the public, government agencies, and the U.S. Congress. With funding provided by USDOE, an executive committee, consisting of Skip Chamberlain (Chairperson, USDOE), Calvin C. Chien (DuPont), and Annette M. Gatchett (USEPA), was formed in October 2001 to plan and organize an expert workshop. Sixty invited international experts participated. The meeting was held between June 30 and July 2, 2002 in Baltimore, Maryland, and consisted of five discussion panels — three on prediction and two on verification. Each panel was led by a panel leader and a co-leader to address particular technical topics in a designated area. A designated graduate fellow, a graduate student whose research was related to these topics, recorded detailed notes for the panel discussions. The graduate fellow group was coordinated and supervised by Jada M. Kanak (DuPont). Each panel leader, assisted by the co-leader, was responsible for writing a chapter for this book, using the information generated from the panel discussions and the detailed notes recorded by the graduate fellows. The prediction chapters were reviewed and edited by Hilary I. Inyang, and Lorne G. Everett reviewed and edited the verification chapters. Calvin Chien had the responsibility for planning, coordinating, and editing the book, ensuring consistency and completeness, and resolving differences in opinions. Skip Chamberlain provided technical input and crucial support in working with experts from the national laboratories on critical issues during the preparation of the book. David E. Daniel (University of Illinois) conducted an initial review of the first draft and provided high-level comments, which were useful in performing subsequent revisions. Dr. Daniel also wrote the preface for the book, which provides an outstanding introduction of containment technology history and book structure. Relevant new information that became available during the period of preparation

and editing was identified, evaluated, and added to the book to ensure that the information is as up-to-date as possible. In addition to organizing and leading the graduate fellow group, Jada Kanak also served as a special technical assistant for book preparation. Her detailed and patient efforts in reviewing and checking all of the references, figures, and tables contributed greatly to the quality of this book. Ms. Kathy O. Adams, a long-time DuPont in-house contract technical writer, was responsible for ensuring the grammatical accuracy of the book, and did an excellent job polishing the final draft. The team from Florida State University, consisting of Norbert Barszczewski, Sheryl A. Grossman, Loreen Y. Kollar, J. Michael Kuperberg, and Laymon L. Gray, were responsible for the workshop planning and contributed greatly to the success of the meeting.

Preface The containment of buried waste, contaminated soil or groundwater, refers to in situ (in place) management of contaminants in the subsurface. Containment is achieved with individual barriers or control technologies that, together, provide a system of engineered control. Containment is potentially applicable to any circumstance in which contaminants exist in the subsurface (e.g., uncontrolled landfills or dumps, chemical spills or leaks, pond or lagoon contaminant seepage) and can provide a safe and highly cost-effective mechanism for environmental control. Containment is accomplished using physical, hydraulic, or chemical barriers that prevent or control the outward migration of contaminants. Containment has come full circle as an acceptable environmental control technology over the past 30 years. Prior to the 1980s, containment was virtually the only technology available for managing subsurface contamination. Although some wastes were exhumed and treated, more often than not, if the pollution problem was recognized at all, the problem was managed via containment. During the 1980s, new environmental regulations emphasized treatment rather than containment. Research and development during this time dramatically expanded the portfolio of options available for treating or destroying contaminants at polluted sites. Technologies such as vapor extraction, oxidation, bioremediation, surfactant flushing, and heat-induced treatment became viable, though often expensive, treatment alternatives. In the 1990s, a dose of reality swung the pendulum back toward containment. It became apparent that it was not technically feasible to return contaminated sites to pristine condition. Further, as a nation, the United States came to realize that it could not afford, nor did it need, the most sophisticated treatment technology available to manage pollution problems at every site effectively and safely. In addition, further research clearly showed that the subsurface has advantages in addressing contamination problems — natural processes such as adsorption and biodegradation can serve to contain or degrade contaminants. For certain materials such as radioactive wastes, it became apparent that the exposure risks associated with exhuming contaminants might be far greater than risks associated with managing the wastes in situ with containment. Thus, for many reasons, interest in containment was revived in the 1990s. Today, containment thrives as a viable environmental management technology, and is often the preferred choice for protecting human health and the environment. But a price was paid for putting containment “on hold” during the 1980s, when emphasis was placed on developing sophisticated treatment technologies: little research and development on containment technologies was achieved during

this time. As interest shifted back toward containment in the 1990s, the industry found itself relying largely on pre-1980s technology. Fortunately, in the past 10 years, important advances have occurred in several areas of containment, most notably in the area of permeable reactive barriers, which transform containment barriers into a passive treatment installation. In the early 1990s, the need to define the state of the art for containment was understood by three visionary organizations: DuPont, the U.S. Environmental Protection Agency, and the U.S. Department of Energy. The DuPont Corporate Remediation Group (CRG) initiated the trio’s first collaborative effort in 1992. Experts from four nations experts were invited by DuPont to work with a team at the State University of New York at Buffalo to conduct a comprehensive review of the containment technology, the technology gaps, and future direction. The product of the work, a 1993 internal report, was published in 1995 by John Wiley & Sons, New York, titled Barrier Containment Technologies for Environmental Remediation Applications, and edited by Ralph R. Rumer and Michael E. Ryan. The principal chapters of the book focused on vertical barriers (walls), bottom barriers (floors), and surface barriers (caps). The three organizations joined again and organized an expert workshop on containment technology in 1995, inviting 115 international experts. The book, Assessment of Barrier Containment Technologies: A Comprehensive Treatment for Environmental Remediation Applications, was edited by Ralph R. Rumer and James K. Mitchell and was published the next year. With the rapidly increasing use of barrier technology in remediation, the need for better understanding, prediction, and monitoring of the performance of barriers emerged. The trio organized another expert workshop on the topic in 2002, which led to the development of this book. The workshop planning committee invited many of the world’s most knowledgeable researchers and practitioners to discuss the current state of the art and debate the appropriate applications and directions for containment. The participants then went home and collectively created this book from their knowledge and exchanges. This book is essentially a diary of those discussions and assessments, recast into the form of an easily readable, comprehensive book that is rich with discussion and references to literature, as well as further detail on specific topics of interest. The first two chapters address prediction issues, Chapters 3 and 4 address monitoring techniques, and Chapter 5 addresses the largely undeveloped field of verification. The discussions in the first four chapters address caps, vertical walls, and permeable reactive barriers. Chapter 1, “Damage and System Performance Prediction,” sets the stage for how contaminants can get into the subsurface. This is an important chapter, because one cannot understand how to contain something unless one knows how the contaminants got into the subsurface in the first place, and how they might spread and threaten the environment without containment. This chapter not only describes pathways, but also introduces the essential concept of risk. No control technology is without risk. Ultimately, a low risk of adverse environmental impact

should be maintained in a way that uses resources as wisely as possible. Chapter 1 draws from concepts in reliability of structures, and couples barrier structural failure to functional failure. Relevant quantitative frameworks are presented for use in assessing the long-term performance of containment systems. Chapter 2, “Modeling of Fluid Transport through Barriers,” addresses the basis for predicting the transport of water and contaminants through barrier components. This chapter focuses on modeling the inflow of moisture to the buried waste (e.g., caps), or modeling the release of contaminants through subsurface barriers. Fluid transport rate prediction is essential to the design process, because predictions can be integrated into the overall containment system performance assessment scheme presented in Chapter 1. Chapter 2 provides details on the current state of the art for performance prediction, but also clearly delineates the limitations in modeling specific situations. Chapter 3, “Material Stability and Applications,” addresses the materials used in barriers, defining the properties of barrier materials and exploring how materials perform in the field. The materials used for barriers include a myriad of natural and man-made materials, such as natural soil, stones and cobbles, impermeable plastic lining materials, man-made filter fabrics, and chemical agents designed to sorb or degrade contaminants that might come in contact with the material. Factors such as clogging, deterioration, or alteration of physical, chemical, or hydraulic properties are explored, not only to define what is known about these materials, but also to provide a learned and balance sense of what is not known. Chapter 4, “Airborne and Surface Geophysical Method Verification,” provides a thorough description of the application of geophysical methods to subsurface barriers. Geophysical methods have been used widely to assist in identifying potential mineral resources deep within the subsurface, and in more recent years, in the shallow environment, to help with identifying contaminant plumes and other anomalies. When applied to subsurface barriers, geophysical methods are challenged beyond their traditional role of identifying gross features that might warrant more detailed exploration (e.g., via a borehole), toward identifying more subtle features, such as a leak in a subsurface barrier. The techniques described in this chapter include both near- and far-field devices, spanning equipment deployed in aircraft flying above a site to devices placed on the ground surface that probe the subsurface directly with electromagnetic or other sources of energy. The first half of this chapter describes the technologies that are available, and the second half addresses their applications to various types of barriers. The subject of Chapter 5, “Subsurface Barrier Verification,” tackles perhaps the most challenging aspect of waste containment technology, i.e., validation of field performance. Traditionally, monitoring has consisted of sampling of groundwater or soil gas from wells. Although sampling soil, water, and air can provide information about the general performance of a system, it does not provide immediate, specific information about how a particular barrier component is meeting its design goals. Further, there is little to motivate stakeholders to spend money

for performance verification, unless required for compliance with regulations. This chapter provides a comprehensive review of sensors and examples of how sensors can be used to document system performance, addressing the basic questions: where, what, how, and what-if? Ultimately, the performance verification scheme should be linked to the performance prediction process. It is perhaps this linkage that is our most important end point, and one that requires more work, particularly in terms of assessing reliability and risk associated with the use of waste containment as a technique for managing waste in the subsurface. The two well-known case studies in the United States that are presented in this chapter provide particular value to this need. That which is buried in the subsurface, out of sight and out of mind, is that which in some respects is the most challenging. Nature has placed geologic materials in the subsurface in rather unpredictable and unknowable locations, with properties that are difficult to discern. Individual barriers are constructed in more controlled and documented ways, but still with considerable uncertainty in actual characteristics. Systems comprised of multiple barriers enjoy considerable redundancy and tend not to rely on any single component for success. Scientists and engineers strive to understand, predict, design, and verify safe containment schemes, both in terms of individual barriers and more complex containment systems. This book provides a comprehensive report on the science and technology of waste containment, with a balanced presentation of what is and is not known. Subsurface containment will continue to be a widely used environmental control technology in the years ahead. This book will provide a valuable reference, helping to chart the way to successfully managing many contaminated sites. David E. Daniel University of Illinois Urbana, Illinois

Editors Calvin C. Chien is a DuPont Fellow, one of only 13 individuals serving in this capacity in DuPont. He has been working in the area of groundwater investigation and remediation since 1975. Since 1991, he has been responsible for evaluating and developing transport modeling and containment technologies. As such, Dr. Chien has played a leading role in improving the understanding of containment technology for use in environmental remediation. He orchestrated the First International Expert Workshop (1995) and the publication (based on the workshop) of the first comprehensive containment book: Assessment of Barrier Containment Technologies: A Comprehensive Treatment for Environmental Remediation Applications (1996). In 1997, he spearheaded another effort to advance the technology: the First International Containment Technology Conference. Through these efforts, he has been recognized as a leading contributor to improving the science of containment technology as well as its acceptance at the regulatory level. He has authored and co-authored many technical papers for peer-reviewed journals and books. Currently, Dr. Chien provides technical environmental support and oversight for existing and new DuPont operations in the Asia-Pacific region. His contributions in the region led the Chinese Ministry of Science and Technology to invite him to evaluate candidates for the 2005 State Natural Science Award of the People’s Republic of China. This award is the most prestigious award for scientists and engineers in China. Hilary I. Inyang is the Duke Energy Distinguished Professor of Environmental Engineering and Science, Professor of Earth Science (GIEES), and Director of the Global Institute for Energy and Environmental Systems at the University of North Carolina–Charlotte. From 1997 to 2001, he was the Chair of the Environmental Engineering Committee of the U.S. Environmental Protection Agency Science Advisory Board, and also served on the Effluent Guidelines Committee of the National Council for Environmental Policy and Technology. He has authored and co-authored more than 170 research articles, book chapters, federal design manuals, and the textbook Geoenvironmental Engineering: Principles and Applications published by Marcel Dekker (ISBN: 0-8247-0045-7). Dr. Inyang is an associate editor and editorial board member of 17 refereed international journals, and contributing editor of three books, including the United Nations Encyclopedia of Life Support Systems (Environmental Monitoring Section). He has served on more than 85 international, national, and state science/engineering panels and committees. Since 1995, he has co-chaired several international conferences on waste management and related topics, and given more than 100 invited

speeches and presentations on a variety of technical and policy issues at institutions and agencies globally. Professor Inyang holds a Ph.D. with a double major in Geotechnical Engineering and Materials, and a minor in Mineral Resources from Iowa State University, Ames; a M.S. and B.S. in Civil Engineering from North Dakota State University, Fargo; and a B.Sc. (Honors) in Geology from the University of Calabar, Nigeria. His research has been sponsored by several agencies and corporations. Dr. Inyang’s research accomplishments and contributions to geoenvironmental science and engineering have been rewarded with honors by various national and international agencies among which are Fellow of the Geological Society of London; 2001 Swiss Forum Fellow selection by the American Association for the Advancement of Science; 1991 Chancellor’s Medal for Distinguished Public Service awarded by the University of Massachusetts Lowell; and the 1992/93 Eisenhower Fellowship of the World Affairs Council to commemorate the international achievements of the late U.S. President Dwight Eisenhower. In 1999, Prof. Inyang was appointed to Concurrent Professorship of Nanjing University, China and subsequently selected as an Honorary Professor of the China University of Mining and Technology, Jiangsu, China. He is the President of the International Society of Environmental Geotechnology (ISEG) and the Global Alliance for Disaster Reduction (GADR). Lorne G. Everett is the 6th Chancellor of Lakehead University in Canada, President of L. Everett and Associates LLC, Santa Barbara, a Research Professor in the Bren School of Environmental Science & Management at UCSB (Level VII), and Past Director of the University of California Vadose Zone Monitoring Laboratory. The University of California describes full professor Level VII as “reserved for scholars of great distinction.” He has a Ph.D. in Hydrology from the University of Arizona in Tucson, and is a member of the Russian Academy of Natural Sciences. In 1996, he received a Doctor of Science Degree (Honoris Causa) from Lakehead University in Canada for Distinguished Achievement in Hydrology. In 1997, he received the Ivan A. Johnston Award for Outstanding Contributions to hydrogeology. In 1999, he received the Kapitsa Gold Medal — the highest award given by the Russian Academy for original contributions to science. In 2000, he received the Medal of Excellence from the U.S. Navy, and the Award of Merit, the highest award given by American Standards and Testing Materials (ASTM) International. In 2002, he received the C.V. Theis Award, the highest award given by the American Institute of Hydrology (AIH) for major contributions to groundwater hydrology. In 2003, he received the Canadian Golden Jubilee Medal for “Significant Contributions to Canada.” He is an internationally recognized expert who has conducted extensive research on subsurface characterization and remediation. Dr. Everett has published over 150 technical papers, holds several patents, developed 11 national ASTM vadose zone monitoring standards, and authored several books, including Vadose Zone Monitoring for Hazardous Waste Sites and Subsurface Migration of Hazardous Waste. His book, entitled Handbook of Vadose Zone Characterization and Monitoring, is a

best seller. His book Groundwater Monitoring was endorsed by the U.S. Environmental Protection Agency as establishing “the state-of-the-art used by industry today,” and is recommended by the World Health Organization for all developing countries.

Table Of Contents Chapter 1 Damage and System Performance Prediction.................................1 Hilary I. Inyang and Steven J. Piet 1.1 1.2

1.3

1.4

Overview......................................................................................................1 Long-Term Performance Analysis Framework...........................................7 1.2.1 Concepts and Analytical Framework ..............................................8 1.2.2 Types of Performance Prediction Approaches..............................11 1.2.2.1 Empirical Prediction Approaches ..................................11 1.2.2.2 Semi-Empirical Prediction Approaches.........................12 1.2.2.3 Less Empirical (Theoretical) Modeling Approach........14 Relationship of Structural Failure to Functional Failure..........................15 1.3.1 Economic or Pseudo-Economic Criteria.......................................18 1.3.2 Regulatory Criteria ........................................................................19 1.3.3 Prescriptive Design Criteria ..........................................................19 1.3.4 Risk Criteria...................................................................................20 1.3.5 Demonstrating Compliance: The Safety Case Concept ...............22 1.3.6 Mixed Criteria ...............................................................................23 1.3.7 Qualitative and Indexing Analyses................................................23 Quantification of Long-Term Damage Scenarios, Events, and Mechanisms ...............................................................................................24 1.4.1 Categories of Degradation Mechanisms .......................................24 1.4.1.1 Slow Physico-Chemical and Biological Processes........24 1.4.1.2 Intrusive Events..............................................................29 1.4.1.3 Transient Events .............................................................30 1.4.1.4 Cyclical Stressing Mechanisms .....................................32 1.4.2 Quantitative Linkage of Contaminant Release Source Terms to Risk Assessment and Compliance Limits ................................37 1.4.3 Frameworks for Assessment of Event Consequences and Connectivities Among Causes of Failure......................................42 1.4.3.1 Fault Trees......................................................................42 1.4.3.2 Event Trees.....................................................................42 1.4.4 Estimation of Long-Term Failure Probabilities ............................42 1.4.4.1 System Failure Probability.............................................43 1.4.4.2 Component Failure Probability......................................44 1.4.4.3 Random Resistance ........................................................47 1.4.4.4 Simplifications of Theory ..............................................48 1.4.4.5 The Multi-Dimensional Case.........................................51 1.4.5 Component and System Failure in Containing Contaminants .....53 1.4.6 Relating Probable Contaminant Concentrations to Risks ............54

1.5

Use of Barrier Damage and Performance Models for Temporal Scaling of Monitoring and Maintenance Needs .......................................59 1.5.1 Updating ........................................................................................59 1.5.2 Effect of Updating on System Management.................................60 1.6 Life-Cycle Decision Approach and Management.....................................61 References ...........................................................................................................62 Chapter 2 Modeling of Fluid Transport through Barriers .............................71 Brent E. Sleep, Charles D. Shackelford, and Jack C. Parker 2.1 2.2

2.3

Overview....................................................................................................71 Caps ...........................................................................................................72 2.2.1 Features, Events, and Processes Affecting Performance of Caps ...............................................................................................72 2.2.1.1 Hydrologic Cycle ...........................................................72 2.2.1.2 Layers and Features .......................................................74 2.2.2 Current State of Practice for Modeling Performance of Caps .....75 2.2.2.1 Water Balance Method...................................................75 2.2.2.2 HELP ..............................................................................81 2.2.2.3 UNSAT-H .......................................................................82 2.2.2.4 SoilCover........................................................................82 2.2.2.5 HYDRUS-2D .................................................................83 2.2.2.6 VADOSE/W ...................................................................84 2.2.2.7 TOUGH2 ........................................................................84 2.2.2.8 FEHM.............................................................................85 2.2.2.9 RAECOM.......................................................................85 2.2.3 Modeling Limitations and Research Needs for Caps...................86 2.2.3.1 Role of Modeling ...........................................................86 2.2.3.2 Data Needs .....................................................................86 2.2.3.3 Code Quality Assurance and Quality Control...............87 2.2.3.4 Verification, Validation, and Calibration........................88 2.2.4 Unresolved Modeling Challenges .................................................89 2.2.4.1 Time-Varying Material Properties and Processes..........89 2.2.4.2 Infiltration at Arid Sites .................................................90 2.2.4.3 Role of Heterogeneities .................................................90 PRBs ..........................................................................................................90 2.3.1 Features, Events, and Processes Affecting Performance of PRBs ..............................................................................................91 2.3.1.1 Groundwater Hydraulics ................................................91 2.3.1.2 Geochemical Processes ..................................................92 2.3.1.3 Reaction Kinetics ...........................................................98 2.3.2 Impacts on Downgradient Biodegradation Processes...................98 2.3.2.1 Enhancement of Geochemical Conditions Conducive to Anaerobic Biodegradation .........................................98 2.3.2.2 Overall Contaminant Concentration Reduction ............99

2.3.2.3 Production of Hydrogen.................................................99 2.3.2.4 Electron Donor Production ..........................................100 2.3.2.5 Direct Addition of Dissolved Organic Carbon............100 2.3.3 PRB System Dynamics ...............................................................101 2.3.4 Geochemical Modeling ...............................................................104 2.3.4.1 Speciation Modeling ....................................................105 2.3.4.2 Reaction Path Modeling...............................................106 2.3.4.3 Reactive Transport Modeling.......................................107 2.3.4.4 Inverse Modeling..........................................................108 2.3.5 Modeling Limitations and Research Needs of PRBs .................109 2.4 Walls and Floors......................................................................................110 2.4.1 Vertical Barriers...........................................................................110 2.4.2 Horizontal Barriers ......................................................................110 2.4.3 Current State of Practice for Modeling Performance of Walls and Floors ....................................................................................111 2.4.4 Contaminant Transport Processes ...............................................112 2.4.4.1 Aqueous-Phase Transport ............................................112 2.4.4.2 Coupled Solute Transport ............................................117 2.4.4.3 Modeling Water Flow through Barriers.......................119 2.4.4.4 Analytical Models ........................................................120 2.4.5 Modeling Limitations and Research Needs of Walls and Floors ...........................................................................................123 2.4.5.1 Input Parameters and Measurement Accuracy ............123 2.4.5.2 Time-Varying Properties and Processes ......................125 2.4.5.3 Influence of Coupled Solute Transport........................125 2.4.5.4 Membrane Behavior in Clay Soils ..............................126 2.5 Complicating Factors...............................................................................128 2.5.1 Constant Seepage Velocity Assumption......................................128 2.5.2 Constant Volumetric Water Content Assumption .......................128 2.5.3 Anion Exclusion and Effective Porosity.....................................129 2.5.4 Nonlinear Sorption ......................................................................129 2.5.5 Rate-Dependent Sorption ............................................................130 2.5.6 Anion Exchange ..........................................................................130 2.5.7 Complexation...............................................................................131 2.5.8 Organic Contaminant Biodegradation.........................................131 2.5.9 Temperature Effects.....................................................................132 References .........................................................................................................132 Chapter 3 Material Stability and Applications ............................................143 Craig H. Benson and Stephan F. Dwyer 3.1

Overview..................................................................................................143 3.1.1 The Role of Barrier Material Mineralogy and Mix Composition on Performance......................................................144 3.1.2 Approaches to Material Evaluation and Selection .....................147 3.1.3 Geosynthetics and their Durability in Barrier Systems..............149

3.2

Material Performance Factors in Caps....................................................153 3.2.1 Material Performance Factors in Composite Barriers ................155 3.2.2 Material Performance Factors in Water Balance Designs ..........160 3.2.3 Coupling of Vegetation and Material Performance Factors .......163 3.3 Material Performance Factors in PRBs ..................................................167 3.3.1 Approach to Selection of PRB Materials ...................................168 3.3.2 Evaluation of Field Performance Using Pilot Testing................170 3.3.3 Effects of Hydraulic Considerations on Reactive Material Performance.................................................................................172 3.3.4 Structural Stability Factors in Performance................................178 3.3.5 Material Durability Factors .........................................................183 3.3.5.1 Effect of Mineral Precipitation on Porosity and Hydraulic Conductivity ................................................185 3.3.5.2 Effect of Mineral Precipitation on Reactivity .............186 3.3.6 Applications of Geochemical Models in Reaction Tracking .....187 3.4 Material Performance Factors in Cutoff Walls .......................................191 3.4.1 In Situ Hydraulic Conductivity ...................................................193 3.4.2 Design Configuration ..................................................................196 3.4.3 Geosynthetics in Vertical Cutoff Walls .......................................198 3.4.4 Permeant Interaction Effects .......................................................199 References .........................................................................................................201 Chapter 4 Airborne and Surface Geophysical Method Verification............209 Ernest L. Majer 4.1

4.2

Geophysical Method Application and Use .............................................209 4.1.1 Characterization and Geophysics ................................................210 4.1.2 Performance Monitoring and Geophysics ..................................212 4.1.3 Geophysical Methods for Site Characterization and Monitoring of Subsurface Processes...........................................214 4.1.3.1 Seismic .........................................................................214 4.1.3.2 Electrical and Electromagnetic ....................................214 4.1.3.3 Natural Field and Magnetic .........................................215 4.1.3.4 Remote Sensing............................................................216 Specific Methods .....................................................................................216 4.2.1 Seismic Methods .........................................................................216 4.2.1.1 Conventional and Advanced Ray and Waveform Tomography..................................................................220 4.2.1.2 Guided/Channel Waves ................................................221 4.2.1.3 Scattered and Reflected Energy ...................................221 4.2.1.4 Cross-Well/VSP/Single Well Imaging .........................222 4.2.1.5 Summary ......................................................................224 4.2.2 Electrical and Electromagnetic Methods ....................................224 4.2.3 Natural Field and Magnetic Methods .........................................227 4.2.4 Airborne Geophysical Methods ..................................................228

4.2.5

4.3

4.4

4.5

State-of-the-Practice Remote Sensing Methods .........................231 4.2.5.1 Aerial Photography ......................................................232 4.2.5.2 Multi-Spectral Scanners ...............................................232 4.2.5.3 Thermal Scanners.........................................................233 4.2.6 State-of-the-Art Remote Sensing Technologies..........................233 4.2.6.1 Hyperspectral Imaging Sensors ...................................234 4.2.6.2 LIDAR Systems ...........................................................235 4.2.6.3 Laser-Induced Fluorescence (LIF)...............................236 4.2.6.4 Radar Systems..............................................................237 4.2.6.5 Fused Sensor Systems/Data Streams...........................238 PRBs ........................................................................................................239 4.3.1 Requirements, Site Characterization, Design Verification, and Monitoring ............................................................................239 4.3.1.1 Site Characterization ....................................................240 4.3.1.2 PRB Construction Verification.....................................241 4.3.1.3 Short-Term Monitoring ................................................242 4.3.1.4 Long-Term Monitoring ................................................242 4.3.2 Case Histories..............................................................................243 4.3.2.1 Electrical Imaging of PRB Construction and Installation (Kansas City, Missouri) ............................243 4.3.2.2 Cross-Hole GPR Investigations (Massachusetts Military Reservation, Massachusetts)..........................245 Vertical Barriers.......................................................................................246 4.4.1 Requirements, Site Characterization, Design Verification, and Monitoring ............................................................................249 4.4.1.1 Design...........................................................................249 4.4.1.2 Installation/Verification ................................................249 4.4.1.3 Short-Term Monitoring ................................................254 4.4.1.4 Long-Term Monitoring ................................................254 4.4.2 Case Studies ................................................................................254 4.4.2.1 Cross-Hole GPR...........................................................255 4.4.2.2 Seismic .........................................................................259 4.4.2.3 ERT...............................................................................260 Caps and Covers......................................................................................261 4.5.1 Requirements, Site Characterization, Design Verification, and Monitoring ............................................................................262 4.5.2 Case Histories..............................................................................263 4.5.2.1 EMI and GPR...............................................................263 4.5.2.2 Apparent Conductivity Maps.......................................267 4.5.2.3 Electromagnetic Radar for Monitoring Moisture Content .........................................................................269 4.5.2.4 Aerial Photography ......................................................272 4.5.2.5 Multi-Spectral Scanners ...............................................273 4.5.2.6 Thermal Scanners.........................................................273 4.6.2.7 HIS Imagery .................................................................274

4.6

Summary..................................................................................................274 4.6.1 Primary Needs for Advancement ................................................275 4.6.1.1 Integration ....................................................................275 4.6.1.2 Processing and Interpretation.......................................275 4.6.1.3 Code Development.......................................................276 4.6.1.4 Instrumentation.............................................................276 4.6.2 Future Developments...................................................................276 References .........................................................................................................278 Chapter 5 Subsurface Barrier Verification ...................................................287 David J. Borns, Carol Eddy-Dilek, John D. Koutsandreas, and Lorne G. Everett 5.1 5.2 5.3

5.4 5.5

5.6

5.7

Overview..................................................................................................287 Goals ........................................................................................................288 Verification Monitoring ...........................................................................289 5.3.1 Methods .......................................................................................292 5.3.1.1 Moisture Change Monitoring Methods .......................292 5.3.1.2 Moisture Sampling Methods........................................294 5.3.1.3 Vadose Zone Monitoring Considerations ....................295 Verification System Design .....................................................................296 Moving from State of the Practice to State of the Art...........................297 5.5.1 System Approach.........................................................................298 5.5.1.1 Links to Modeling and Prediction ...............................298 5.5.1.2 Optimization.................................................................299 5.5.1.3 Decision and Uncertainty Analysis..............................299 5.5.2 Smart Structures ..........................................................................300 5.5.2.1 Long-Term, Post-Closure Radiation Monitoring Systems (LPRMS)........................................................302 5.5.2.2 Environmental Systems Management, Analysis, and Reporting (E-SMART™) Network..............................304 5.5.2.3 Direct Push Technologies ............................................305 5.5.2.4 Nanotechnology Sensors..............................................307 5.5.3 Advanced Environmental Monitoring System (AEMS).............307 5.5.4 A New DOE Barrier Design Code .............................................308 Drivers for Implementation of New Approaches....................................309 5.6.1 Costs ............................................................................................309 5.6.2 Enabling Desired End States.......................................................309 Covers ......................................................................................................310 5.7.1 Moving from State of the Practice to State of the Art...............310 5.7.1.1 Methods ........................................................................310 5.7.1.2 Verification Measurement Systems..............................311 5.7.1.3 Barrier Cap Monitoring ...............................................311 5.7.2 Case History: Mixed Waste Landfill...........................................312 5.7.2.1 Cover Infiltration Monitoring ......................................313 5.7.2.2 Neutron Moisture Monitoring......................................313

5.7.2.3

Fiber Optics Distributed Temperature Moisture Monitoring....................................................................314 5.7.2.4 Shallow Vadose Zone Moisture Monitoring................314 5.7.3 Case History: Fernald On-Site Disposal Facility .......................315 5.7.4 Verification Needs .......................................................................318 5.7.4.1 Optimization and Trend Analysis ................................319 5.7.4.2 Sensors and Other Hardware .......................................320 5.8 PRBS........................................................................................................321 5.8.1 Regulatory Framework ................................................................324 5.8.2 Moving from State of the Practice to State of the Art...............325 5.8.2.1 Flow Characterization and Monitoring........................325 5.8.2.2 Verification of Geochemical Gradients and Zones......327 5.8.3 Case History: Subsurface Monitoring.........................................329 5.8.4 Verification Needs .......................................................................329 5.8.4.1 Spatial and Temporal Flow Monitoring Considerations ..............................................................330 5.8.4.2 Geochemical and Hydrological Process Monitoring Considerations ..............................................................331 5.8.4.3 Acoustic Wave Devices................................................331 5.9 Walls and Floors......................................................................................332 5.9.1 Moving from State of the Practice to State of the Art...............337 5.9.1.1 Neutron Well Logging .................................................337 5.9.1.2 Perfluorocarbon Tracer (PFT) Monitoring/ Verification ...................................................................338 5.9.2 Case History: Colloidal Silica Demonstration............................341 5.9.3 Case History: Barrier Monitoring at the Environmental Restoration Disposal Facility (ERDF) ........................................343 5.9.3.1 Study Conclusions........................................................345 5.9.3.2 Study Recommendations..............................................345 5.9.4 Verification Needs .......................................................................346 5.9.4.1 Adequacy of the Containment Region ........................347 5.9.4.2 Long-Term Performance of the Containment .............347 5.10 Conclusions..............................................................................................348 References .........................................................................................................349 Appendix A Workshop Panels .........................................................................353 Panel Panel Panel Panel Panel

1 2 3 4 5

Prediction: Materials Stability and Application.................................353 Prediction: Barrier Performance Prediction.......................................353 Prediction: Damage and System Performance Prediction.................354 Verification: Airborne and Surface/Geophysical Methods ................355 Verification: Subsurface-Based Methods ...........................................355

Index..................................................................................................................357

1

Damage and System Performance Prediction Prepared by* Hilary I. Inyang University of North Carolina at Charlotte, Charlotte, North Carolina

Steven J. Piet Idaho National Engineering and Environmental Laboratory, Idaho Falls, Idaho 1.1 OVERVIEW Long-term hazardous waste containment using physical barriers such as caps demands the estimation of system reliability, system deterioration rate, and consequences of system failure. The use of a systematic approach and a set of sequential analytical steps, such as those included in Figure 1.1, enables opportunities for system improvement to be identified. Barrier systems for buried waste or migrating contaminants are subjected to various physical, physico-chemical, and biological phenomena. The synergistic action of these phenomena ultimately damages barrier systems and produces or enlarges flow channels through which pollutants can escape. The observation that the degradation of constructed facilities increases with service life is not unique to containment systems: deterioration characterizes all constructed facilities, from roadways to pyramids. Current uncertainties pertain to the establishment of reasonably valid deterioration rates for various barrier designs, waste types, management systems, climatic and geohydrologic environments, site stability, and barrier construction materials for time frames that range from hundreds to thousands of years. The diversity of waste types and desirable service lives for facilities under various regulatory programs are summarized in Tables 1.1 and 1.2, respectively. * With contributions by James H. Clarke, Vanderbilt University, Nashville, Tennessee; John B. Gladden, Westinghouse Savannah River Company, Aiken, South Carolina; Horace K. Moo-Young, Villanova University, Villanova, Pennsylvania; Priyantha W. Jayawickrama, Texas Tech University, Lubbock, Texas; W. Barnes Johnson, U.S. Environmental Protection Agency, Washington, DC; Robert E. Melchers, University of Newcastle, Callaghan, NSW, Australia; Mark L. Mercer, U.S. Environmental Protection Agency, Washington, DC; V. Rajaram, Black and Veatch Corporation, Overland Park, Kansas; and, Paul R. Wachsmuth, University of North Carolina at Charlotte, Charlotte, North Carolina.

1

2

Barrier Systems for Environmental Contaminant Containment & Treatment Define Context social, individual, organizational, political, technological

Define System

Hazard Scenario Analysis • what can go wrong? • how can it happen? • what controls exist?

Estimate Consequences (magnitude)

Estimate Probability (of occurrence of consequences)

Define Risk Scenarios

Sensitivity Analysis

Risk Assessment compare risks against criteria

Monitor and Review

Risk Treatment • avoidance • reduction • transfer • acceptance

FIGURE 1.1 Flow chart for risk-based decision making. (From Stewart, M.G. and Melchers, R.E., 1997. Probabilistic Risk Assessment of Engineering Systems, Chapman & Hall, London. With permission.)

Estimation of the long-term deterioration pattern of barriers is necessary to improve the reliability of estimates of long-term contaminant release source terms for input into human health and ecological risk assessments, as well as facility monitoring and maintenance planning. Monitoring of barrier performance provides useful but inadequate data for performance predictions, because of limited field experience with barriers of various configurations in many environments, and because epochal events such as floods and earthquakes produce transient effects that cause deviations from performance patterns. The majority of quantitative methods that are currently used to estimate longterm barrier performance have time-invariant material characteristics and load/fluid application rates. The use of these fate and transport models, most of

Damage and System Performance Prediction

3

TABLE 1.1 Types of Hazardous Materials

Type

Typically Found in Nature?

Importance of Chemical Form to Toxicity

Does Hazard Decay Naturally?

Radioactive isotopes

Yesa

Can affect the level of exposure to the hazard by altering the ingestion or inhalation uptake of isotopes

Natural decay is fixed for each isotope

Toxic organic compoundsb

No

Affects ingestion and inhalation uptake

Decay generally slow (years, decades) and often dependent on specific chemical environment, e.g., trichloroethylene

Determines toxicity level

Toxic metals

Yes, although sometimes not in the more hazardous chemical forms

Can affect ingestion or inhalation uptake

Generally affects toxicity

Metals won’t decay, but the chemical form may naturally change into less toxic forms

Do We Know How to Destroy Hazard? Negligible prospects for in situ destruction or treatment Ex situ treatment may be practical to separate longlived isotopes from short-lived isotopes In situ decay may be deliberately enhanced by microbes

Ex situ destruction generally possible, but the associated risks and costs of transportation and destruction are high Destruction is not practical

In situ alteration of chemical form can sometimes be enhanced by microorganisms

4

Barrier Systems for Environmental Contaminant Containment & Treatment

TABLE 1.1 (continued) Types of Hazardous Materials

Type

Typically Found in Nature?

Importance of Chemical Form to Toxicity

Does Hazard Decay Naturally?

Toxic metals

Do We Know How to Destroy Hazard? Ex situ destruction generally possible, but with associated risks and costs during transportation and destruction

a

However, the specific radioactive isotopes are typically are not the specific isotopes found in nature. b There are also some toxic compounds that are neither organic nor metals, e.g., asbestos. Source: INEEL (2000). Environmental Laboratory Report INEEL/EXT-2000-01094; Piet et al. (2001). INEEL technical report INEEL/EXT-2001-01485.

TABLE 1.2 Time frames for Waste Containment Performance under Various U.S. Regulatory Programs Time Frame

Regulatory Program

10,000 years

Nuclear Regulatory Commission and EPA regulations for high-level and transuranic waste (10 CFR 60, 10 CFR 63, 40 CFR 191, 40 CFR 197) EPA regulations for near-surface uranium and thorium mill tailings (40 CFR192) and DOE policy for new land burial (DOE M 435.1) NRC regulations for near-surface burial of low-level waste (10CFR61) Baseline EPA RCRA time period for near-surface burial chemical hazards (40 CFR264); EPA can increase or decrease this value for each case Baseline EPA CERCLA time period for residual hazards (CERCLA requires a 5-year review to ensure the remedy is still protective of human health and the environment and is still performing as predicted)

1000 years 500 years 30 years Indefinite

which are based on one-dimensional differential equations, for describing contaminant advection-dispersion has simplified barrier performance analyses but does not address long-term barrier system performance adequately. As the performance

Damage and System Performance Prediction

5

analyses time frames extend from one or two decades to hundreds of years, changes in barrier material characteristics; cyclic changes, waning, or growth of stressing events; and possible exhaustion of initially present parent contaminants and/or generation of daughter contaminants combine to decrease the reliability of contaminant release estimates. Long-term performance modeling of waste containment systems and individual barriers within such systems require identifying possible damage mechanisms and assessing the system resistance in all possible ways in which the system might fail. Various techniques have been developed in practice (in different industries) and, hence, with different names, including the following: • Preliminary hazard analysis (PHA) (nuclear industry) • Walk-down analysis consisting of on-site visual inspection, particularly of pipe work (nuclear industry) • Failure modes and effects analysis (FMEA), which uses generic terms as prompts (various applications) • Failure modes, effects, and criticality analysis (FMECA), which also assesses criticality of consequences • Hazard and operability studies (HAZOP), which uses guide words as prompts (primarily chemical industry) • Incident data banks, which contain data such as accident data and nearmiss data For the range of barrier applications available now and in the future, there is a need for improved capacity to predict containment barrier damage and system performance. Damage and system performance models must be: • Responsive to the needs of a diverse set of decision makers (i.e., designers of new barriers, managers of barriers in service, regulators, funding agencies, and the public) • Integrative of the most important mechanisms of failure (i.e., both spatially uniform degradation and localized degradation; both continuously acting and discrete in time) • Comprehensive with regard to the range of performance measures relevant to a given barrier design that solves a particular problem at a particular location • Stochastic to allow evaluation of the sensitivities of parameter uncertainties compared to performance measures • Probabilistic in consideration of failure scenarios and mechanisms that may or may not occur during the service life • Validated by data to the extent practical • Adaptive to new information obtained during barrier service

6

Barrier Systems for Environmental Contaminant Containment & Treatment

• Informative regarding barrier degradation to guide barrier surveillance and maintenance, justification for reduction of surveillance and maintenance, barrier lifetime extension while in service, and future barrier designs • Graded in its implementation according to the severity and longevity of the associated risks (barriers with lower severity or shorter duration hazards do not need all of the above) Attempts to provide satisfactory system performance demands that one or more criteria be available against which to measure system performance. The setting or derivation of performance criteria is a problem with a fascinating and complex history, much of it based originally on issues associated with the nuclear industry. This history includes some deep philosophical questions, including “Who is to bear what level of risk, who is to benefit from risk-taking, and who is to pay? Where should the line be drawn between risks that are to be managed by the state and those that are to be managed by individuals, groups, or corporations? Who evaluates success or failure in risk management and how? Who decides what should be the desired trade-off between different risks?” (Hood et al., 1992). The decisions about these matters are influenced by judgments about the following (Stewart and Melchers, 1997): • Anticipation of system failure and resilience against unexpected catastrophe • Assumptions used to compute a numerical estimate of system risks • Size of uncertainties in estimating system risks • Organizational vulnerabilities to system failure • Cost of risk reduction • Size and composition of groups involved in decision-making processes • Aggregation of individual preferences (i.e., distribution of benefits and risks) • Counter-risks (i.e., alternatives may have other societal risks) Psychological aspects, such as risk perception and risk aversion, social and cultural preferences, as well as political processes and risk communication also play a part. The term “failure” can mean a variety of structural conditions or lack of capacity to meet expected performance functions when it is applied to containment systems. Structural failure of a system component or the entire system should be differentiated from functional system failure as described by Inyang (1994) and Inyang et al. (1995). Structural failure of a containment system may not necessarily lead to immediate functional failure because the former is often indexed in terms of parameters that define the stability and hydraulic characteristics of the containment system, whereas functional failure is assessed in terms of the risk of environmental and human exposure to contaminants that may be released from the system. More broadly, for a given initial hazard inventory, the

Damage and System Performance Prediction

Hazard halflife

7

Rates inventory mobilizes per year Delay time in transport through environmental media

Hazard inventory

Exposed individuals

Escaping inventory

Time barrier starts to degrade

Rate barrier degrades per year

FIGURE 1.2 Simplistic illustration of processes that influence exposure to individuals.

exposure generally depends on the five factors listed below and illustrated in Figure 1.2. Eventually, hazard either decays (with some half-life) or escapes. 1. Hazardous half-life 2. Mobilization rate/year (e.g., leaching, diffusion in the absence of a barrier) 3. Time at which barrier begins to degrade 4. Barrier degradation rate/year 5. Transport time of escaped materials between barrier and recipients Factors 2, 3, and 4 control when and how fast the hazard escapes. Factor 5 controls how much time (with additional hazard decay) will elapse before the escaped hazard impacts human health and the environment. With reference to the range of time horizons in various regulations, there is no systematic connection between the hazard timescales and regulatory timescales that are summarized in Table 1.2. Different regulations were established at different times by different legislation in response to different issues. Thus, the appropriate framework for predicting barrier system performance is not always clear: the time frames can differ greatly and the appropriate assumptions on how long to monitor and manage the barrier system can also differ.

1.2 LONG-TERM PERFORMANCE ANALYSIS FRAMEWORK It is necessary to formulate a long-term performance analysis framework that enables the consideration of factors that are significant for a given class of containment systems. The failure states of the constructed system in terms of both structural failure and functional failure need to be defined. Also, the performance assessment

8

Barrier Systems for Environmental Contaminant Containment & Treatment

framework should incorporate nodes to which pre-failure performance models can be linked.

1.2.1 CONCEPTS

AND

ANALYTICAL FRAMEWORK

Several concepts and analytical frameworks have been proposed for use in assessing the long-term performance of containment systems. The concepts pertain to the performance pattern of containment systems during service lives and postclosure time frames that can range from 30 years to thousands of years. The focus of the analyses is the formulation and use of performance prediction models that are capable of determining contaminant release rates as a function of estimated, measured, or designed magnitudes of containment system design parameters, waste characteristics, stressing events and processes, and site/hydrological conditions. The factors that need to be considered are numerous, as exemplified by the case of a near-surface barrier illustrated in Figure 1.3. Several attempts have been made to establish the expected general pattern of barrier performance over long service lives. Figure 1.4a shows the containment system performance model that is implicit to current practice. The facility is assumed to provide a constant level of service, or to be structurally sound until external monitoring data indicate the release of contaminants at unacceptable Natural boundary conditions (weather, climate, biota)

Engineered boundary conditions (design, maintenance, repair) Plants

Temperature

Dimensions, materials configuration

Wind/water erosion Precipitation Surface ecology (especially evapotranspiration barriers) Ecological

Plant/animal intrusion Soil type and thickness

Interfacial ecology (especially capillary barriers) Biochemical changes?

Structure

Plugging and surface tension

Water

Hydrology (including micropores, capillaries)

Erosion

Compaction Waste zone Subsidence

Output: Contaminant flow to the vadose zone

FIGURE 1.3 An illustration of the interaction among various processes and parameters that influence the long-term performance of near-surface containment systems.

Damage and System Performance Prediction

9

Current Methodology

Performance

Design Life

Detect only after failure (leakage through barrier)

Time

Realistic Performance

Performance

(a)

Uncertain long-term performance

Uncertain how to manage barriers & resistance to new materials and designs

Time (b)

FIGURE 1.4 Conceptual pattern of long-term performance of containment systems (a) abrupt failure pattern implicit to current practice (b) gradual degradation pattern that is more realistic.

concentrations. Figure 1.4b shows a more realistic performance pattern in which the performance degrades gradually during the immediate post-implementation period and then decays abruptly. After abrupt decay, the performance decreases much more gradually in a period that is characterized by large uncertainties. The reader should note that system damage vs. time plots have configurations that are the reverse of those of system performance (or effectiveness) vs. time plots. Thus, Figure 1.5 shows an increase in the risk of containment system failure with time. It should be noted that although the system deterioration pattern may be represented by a smooth curve, the performance pattern of a particular component of the containment system could exhibit temporal fluctuations in response to transient stressing mechanisms, the passage of contaminant fronts, and maintenance activity. In developing the conceptual framework for estimating the longterm performance pattern of containment systems, Inyang (1994) identified the various stages illustrated in Figure 1.6. Curve 1 shows the barrier degrading via continuous deterioration mechanisms. The branching to Curve 2 shows a barrier suffering from a discrete (in time) negative perturbation, such as a flood or an earthquake. The branching to Curve 3 reflects a barrier being upgraded or repaired. In the illustration, following Curve 1, the containment system effectiveness decays from an initial level of Eto, to a minimum acceptable level of Etr at time, tr . Etr corresponds to the functional performance level that is typically

10

Barrier Systems for Environmental Contaminant Containment & Treatment

Risk of failure

Acceptable risk level Particular structure deterioration Expected deterioration

Time (age of structure)

FIGURE 1.5 Conceptual degradation-time function of a containment system. (Illustrated by Melchers, R.E., 2001. Reliability Engineering and System Safety, 71(2), 201–208. With permission.)

Curve 1

System effectiveness, E (fraction)

Eto

Curve 3

Etm E1 E2 Etg Etr

Curve 2

to

tg

t2 tm

tr

Time, t (years)

FIGURE 1.6 A conceptual long-term deterioration pattern and maintenance scheme for waste containment system. (From Inyang, H.I., 1994. Proceedings of the First International Congress on Environmental Geotechnics, Calgary, Canada, pp. 273–278. With permission.)

specified by regulators or other authorities. If the facility is repaired at a time, tm, the effectiveness can abruptly increase to Etm so that an improved performance (described by Curve 3) results. Essentially, repairs postpone the attainment of Etr

Damage and System Performance Prediction

11

by slowing down the deterioration of the repaired component(s) and, hence, the system. The system can also degrade abruptly, as at tg, such that its effectiveness falls to Etg and system performance follows Curve 2 to failure at t2 (much sooner than would result from the regular deterioration pattern).

1.2.2 TYPES

OF

PERFORMANCE PREDICTION APPROACHES

In order to serve practical purposes, performance patterns need to be quantified, requiring the development of rating systems and models. Approaches to performance prediction can be categorized as empirical, semi-empirical, and less empirical (theoretical modeling). 1.2.2.1 Empirical Prediction Approaches Empirical prediction approaches involve the extrapolation of current knowledge of system behavior and/or similar system behavior to long-term system behavior. Such knowledge can also be acquired through accelerated testing in intensified environments. Another example of an empirical approach is performance indexing. In most cases, indexing criteria do not explicitly include time functions with performance factors. Table 1.3 shows the ratings of single components and composite configurations of barriers (Piet et al., 2001). In general, the scores on

TABLE 1.3 Overall Benefit of Each Barrier Configuration of Cover/Liner Materials Design Alternate

Description

Overall Benefit

Estimated Cost (dollars/ft2)

Benefit/Cost Ratio

Ranking in Group

A B C

CCL GM GCL

One-Barrier 36 64 46

Layer 0.70 0.70 0.70

51 91 66

3 1 2

D E

GM/CCL GM/GCL

Two-Barrier Layer 58 1.40 66 1.40

41 47

2 1

F G

GM/CCL/GM GM/GCL/GM

Three-Barrier Layer 71 2.10 77 2.10

34 37

2 1

CCL, single compacted clay liner; GM, single geomembrane; GCL, single geosynthetic clay liner; GM/CCL, two-component composite; GM/GCL, two-component composite; GM/CCL/GM, three-component composite liner; GM/GCL/GM, three-component composite liner. Source: Adapted with modification from Koerner, R.M. and Daniel, D.E. (1992). Civil Engineering, pp. 55–57.

12

Barrier Systems for Environmental Contaminant Containment & Treatment

TABLE 1.4 Estimated Long-Term Effectiveness of Selected Waste Containment Measures Indexing Time Increments (t years) Effectiveness, Et (%)

t0

t10

t30

Clay cap Synthetic cap Clay plus synthetic cap RCRA C composite liner system Clay liner Synthetic liner HDPE wall Slurry wall

80 90 95 98 70 85 65 70

75 85 92 95 60 75 60 60

60 75 80 85 40 35 50 20 (70e)

a b c d e

Assumes Assumes Assumes Assumes Assumes

t100 20 15 35 60 5 0 25 0

(85a) (90b) (98c)

(65d)

addition of new clay cap at 100 years. addition of new synthetic cap at 100 years. addition of new composite clay and synthetic cap at 100 years. addition of new HDPE at 100 years. addition of new slurry wall at 30 years.

Source: Inyang, H.I. and Tomassoni, G. (1992). Indexing of long-term effectiveness of waste containment systems for a regulatory impact analysis. A technical guidance document. Office of Solid Waste, U.S. Environmental Protection Agency, Washington, DC.

overall benefit or utility of a particular design increase with the number of components. Inyang and Tomassoni (1992) indexed the long-term performance pattern of waste covers for use in regulatory impact analysis. The scores are presented in Table 1.4. The reader should note that these scores are general indices and are not precise estimates of the performance of the components scored. Other researchers exemplified by Hagemeister et al. (1996) developed detailed performance indexing systems that incorporate ratings of barrier components, contaminant transport pathway factors, and human exposure potential. 1.2.2.2 Semi-Empirical Prediction Approaches These approaches involve the use of semi-empirical models to estimate the damage time functions or deterioration pattern of containment systems or specific containment system components. Using adaptations from product reliability analyses, a parameter that is generically referred to as the “failure rate” is used to quantitatively describe the effectiveness or reliability of a barrier or containment system with time. The magnitude of the failure rate is the significant determinant of the barrier degradation rate in the absence of transient events. It is tempting

Damage and System Performance Prediction

13

to erroneously assume that failure rates for containment systems are constant. In practice, the failure rates of most engineered systems are not constant with time. Generally, λ(t ) = λ 0 exp(β t )

(1.1)

where λ(t) is the time-variable failure rate of the containment system; λ0 is the initial failure rate of the containment system; β is an exponent that describes the variation (usually decay) of the failure rate with time, t. Equation (1.1) represents the general exponential form of the decay equation. The linear and Weibull forms of the equation are presented below as Equations (1.2) and (1.3), respectively. The parameters are as defined for Equation (1.1). The time parameter, t0, is the time corresponding to the origin of the initial failure, λ0. λ(t ) = λ 0 (1 + β t ) ⎛ t⎞ λ(t ) = λ 0 ⎜ ⎟ ⎝ t0 ⎠

(1.2)

β

(1.3)

For Equations (1.1) through (1.3), the value of the constant β determines the shape of the failure rate function. The failure rate is increasing with time if β > 0, it is constant if β = 0, and it is decreasing if β < 0. For more information, the reader is referred to Wolford et al. (1992), who used this approach to estimate the aging pattern of nuclear power plant equipment. Such techniques have already been successful in extending the license of 10 United States nuclear power plants by 20 years. Inyang (1994) observed that the Weibull format of failure analysis provides the curve geometries that match the expected deterioration pattern of most containment systems and proposed the use of Equation (1.4) with shape parameters ranging from 2 to 5. The use of Equation (1.4) enables long-term performance to be addressed within the context of system reliability. ⎡ ⎛ t − t ⎞β ⎤ 0 Rt = exp ⎢ − ⎜ ⎟⎠ ⎥⎥ n ⎝ ⎢ ⎣ ⎦

(1.4)

where Rt is the reliability of the containment system at a future time of reference, t is the future time of reference, and n is the scale or normalization parameter that corresponds to the time duration at which the failure probability is 0.632. Generally, the larger the magnitude of β, the greater the deterioration rate. Considering that there is a complimentary relationship between the probability of failure, Pt , and reliability, Rt , of a component or system as indicated by Equation (1.5), initial values of reliability can be established.

14

Barrier Systems for Environmental Contaminant Containment & Treatment

Rt = 1 − Pt

(1.5)

The damage functions for each system component can be generated from current knowledge, testing, and extrapolations, and can be used to determine the probability that barrier characteristics will meet specified standards at specified future times. 1.2.2.3 Less Empirical (Theoretical) Modeling Approach This approach involves modeling the stresses, deterioration processes, waste transformations and release, barrier material durability, and flaw evolution for a barrier component or system. In this approach, the failure probabilities of system components and the system itself are modeled. Interactions among various parameters that promote or negate effects are considered. Considering that various stressors and their impacts have different probabilities of occurrence within different timescales, the challenge of deciphering the interactions among parameters is quite great. Therefore, an innovation within this modeling approach is the use of modeling frameworks that enable the incorporation of various models and the establishment of dynamic linkages among them. This technique is nested in the subdiscipline of system dynamics. System dynamics is the study of dynamic feedback systems using computer modeling and simulation (Forrester, 1961). Unlike other scientists, who study the world by breaking it up into smaller and smaller pieces, system dynamicists look at things as a whole. The central concept of system dynamics is understanding how all objects in a system interact with one another. Visualization of the system is one of the assets of this modeling technique. However, beneath the visual exterior is a series of differential equations that define the behavior of the system over time. An example of software that can be used in this modeling exercise is Stella Research (Stella, 2001). The calculations are performed using numerical integration. Although the interface makes the modeling look superficial and almost trivial, a sophisticated mathematical engine performs the calculations. Using this modeling technique, it is possible to model complicated systems. A thorough understanding of the structure of these complex systems can lead to an explanation of their performance, both over time and in response to internal and external perturbations. By understanding the underlying system structure, predictions can be made relative to how the system will react to change. System dynamics models are descriptive in nature. The elements in the models must correspond to actual entities in the real world. The decision rules in the models must conform to actual practice and real-world phenomena. A new project at the Idaho National Engineering and Environmental Laboratory (INEEL) is addressing barrier degradation dynamics (Piet and Breckenridge, 2002). One component of the effort is the use of relatively simple but flexible system dynamics models to explore possible interactions of processes. These models provide a tool to explore uncertainties in scenarios and mechanisms, whereas more sophisticated models are tools for exploring sensitivities to parameter uncertainties.

Damage and System Performance Prediction

15

To illustrate the necessity of addressing interactions among various parameters, the effects of the burrowing of covers by animals on evapo-transpiration are considered. During the summer months, more water is lost from plots with animal burrows than from plots where no animal burrows are present. During the winter months, both the plots with animal burrows and the control plots gain water. In addition, water does not infiltrate below approximately 1 meter (m), even though burrow depths always exceed approximately 1.2 m. The lack of significant water infiltration at depth and the overall water loss in the lysimeter plots are occurring despite the following worst-case conditions: No vegetative cover (no water loss through transpiration) No water run off (all precipitation is contained) Burrow densities in lysimeters greater than those in natural settings Extreme rainfall events applied frequently (i.e., three 100-year storm events in three months) • Animals burrowing deeper in the lysimeters than in natural settings As part of the conclusion of the study described in the preceding paragraph, the investigators noted that “the overall water loss from soils with small-small burrows appears to be enhanced by a combination of soil turnover and subsequent drying, ventilation effects from open burrows, and high ambient temperatures” (Gee and Ward, 1997). Thus, in this case, animal intrusion had a net positive effect. Indeed, earlier work shows that soils were more dry beneath burrows than elsewhere (Cadwell et al., 1989; Link et al., 1995). Link et al. (1995) report that the increased moisture in burrows facilitated vegetation response that increased plant transpiration as plants took advantage of the moisture and sent roots to use it, leading to dry zones under the burrows. Indeed, Link et al. (1995) note that “ecologically, it is expected that a local abundance of a limiting resource, in this case moisture, would be rapidly and therefore depleted.” • • • •

1.3 RELATIONSHIP OF STRUCTURAL FAILURE TO FUNCTIONAL FAILURE In real-world situations, defining satisfactory system performance can be difficult. It is a vector with many components, governed by different criteria, and driven by different and perhaps interacting processes. These processes may not be well understood and, hence, can be represented analytically only with considerable uncertainty. This situation is not too different from that in other spheres and disciplines. It is usual in risk analysis to consider the consequences of failure, hence the recent focus of performance assessments has been on readily measurable barrier characteristics (e.g., barrier permeability) with limited focus on various combinations of outflows and inflows. Because the system properties and processes are uncertain, failure consequences can be described only with uncertainty. Moreover,

16

Barrier Systems for Environmental Contaminant Containment & Treatment

the consequences usually are the critical outcome(s) of the system because the larger community seldom has particular interest in the structural system itself. The foregoing discussion leads to the need to examine the performance factors necessary to evaluate containment systems. These factors are divided into the following two categories: • Total system (parameters that define functional performance) • Concentration of hazardous materials in surface/aquifer water • Exposure to humans (e.g., water, air, intrusion pathways) • Risk to humans • Risk to ecologies • Barrier and barrier subsystems (parameters that define structural performance) • Resistance to human intrusion • Water flux through barrier • Gas flux through barrier • Hazardous material flux through barrier • Measures of individual degradation mechanisms (e.g., erosion, subsidence) The satisfaction of both functional and structural design functions of the composite containment system requires that the various system components meet specific design functions that contribute to overall system performance. The variability in the combination of various containment system components implies that long-term performance under a given set of applied stresses will also be different. Inyang (1999) suggested the following nonexclusive criteria as indices of containment system and component performance: • Ability of the system to reduce the concentrations of aqueous phase contaminants to acceptable levels through one or more contaminant attenuation processes (e.g., sorption, precipitation) • Ability of the system to reduce the volume of contaminants that is released into protected media to acceptable levels • Ability of the system to reduce the leaching of bound contaminants from stabilized media to acceptable levels • Ability of near-surface system components to attenuate radiation to nondamaging levels Often, the locations at which measurements of contaminant volumes or release rates will be obtained are specified in documents that are used to establish the compliance of a component or system at specified time intervals. As an example, in Table 1.5, Ho et al. (2002a) summarized the design performance objectives for the Monticello Mill Tailings Repository in which performance standards are specified in terms of specific quantities of contaminants that must not be exceeded.

Damage and System Performance Prediction

17

TABLE 1.5 Summary of Performance Objectives Applicable to the Monticello Mill Tailings Repository Media All pathways

Atmosphere

Atmosphere

Standard <100 mrem/year Effective Dose Equivalent from all routine DOE activities <10 mrem/year Effective Dose Equivalent, excluding Rn Average flux of Rn-222 <20 pCi/m2/s or (see next row)

Point of Compliance

Regulation

To a member of the public

Not defined

DOE Order 5400.5 II 1.a

To a member of the public

Not defined

40 CFR 61.92

In air above landfill, averaged over entire landfill

1000 years if reasonably achievable and, in any case, for at least 200 years 1000 years if reasonably achievable and, in any case, for at least 200 years 1000 years if reasonably achievable and, in any case, for at least 200 years

40 CFR 192.02(a) and 40 CFR 192(b)(1)

Atmosphere

Annual average concentration of Rn-222 in air <0.5 pCi/L

At or above any location outside the landfill

Groundwater

Arsenic <0.05 mg/La,b Chromium <0.05 mg/La,b Lead <0.05 mg/La,b Molybdenum <0.01 mg/La,b Selenium <0.01 mg/La,b Combined Ra-226 and Ra-228 <5 pCi/La,b Combined U-234 and U-238 <30 pCi/La,b,c Gross alpha-particle activity, excluding Rn and U <15 pCi/La,b Beta particles, and photons made from manmade radionuclides <4 mrem/year

Intersection of vertical plane with uppermost aquifer at downgradient limit of disposal area plus area taken by dike or other waste barrier

Groundwater

Period of Compliance

In community water supply systems

Not defined

40 CFR 192.02(a) and 40 CFR 192(b)(2) 40 CFR 192.02(a) and 40 CFR 192.02(c)(4), and Table 1 to Subpart A of 40 CFR 192

40 CFR 141.16

18

Barrier Systems for Environmental Contaminant Containment & Treatment

TABLE 1.5 (continued) Summary of Performance Objectives Applicable to the Monticello Mill Tailings Repository Media Compacted soil layer in cover

Standard Water percolationd <1 × 107 cm/s

Point of Compliance

Period of Compliance

Hydraulic conductivity of compacted soil layer in cover

Not defined

Regulation 40 CFR 264.301

a

If background is below this level. An alternative concentration limit may be established under 40 CFR 192.02 (c)(ii)(A). c Where secular equilibrium is obtained, this criterion will be satisfied by a concentration of 0.044 milligrams per liter. For conditions of other than secular equilibrium, a corresponding value may be derived and applied, based on the measured site-specific ratio of the two isotopes of uranium. d A unit gradient flow is assumed to equate percolation to hydraulic conductivity. b

1.3.1 ECONOMIC

OR

PSEUDO-ECONOMIC CRITERIA

Economic evaluation has the advantage (and disadvantage) of forcing all parties to evaluate their objectives in monetary terms. Pseudo-economic criteria, such as utility analysis, require a similar approach but in terms of a different unit of measurement. In principle, the maximum expected net present value criterion can be stated as follows: M

max EVk =

⎛ pi ⎜ ⎜⎝

⎞

N

∑ ∑ X ⎟⎟⎠ i =1

ji

(1.6)

j =1

where k is the alternative or system configuration being considered, i is the state of the system (e.g., normal operation, one or other mode of system failure), pi is the probability of occurrence for each such state of nature, M is the number of such states, j is the attribute, N is the number of attributes, and Xji represents the various costs or benefits associated with each state. There are some very significant problems associated with determining the Xji, and these are well known in cost-benefit analysis literature (Layard, 1972; Dasgupta, 1993). Usually, the optimal decision is considered to be the maximization of the value of Equation (1.6), which then provides the possible decisions required. Typically, this translates into desired (maximum) values for the probabilities, pi. These values are obtainable through risk analysis, as are some of the values of Xji (where these are consequences). In practice, the optimization of Equation (1.6) can be constrained by regulatory requirements (Stewart and Melchers, 1997).

Damage and System Performance Prediction

19

TABLE 1.6 Typical Safety Targets for Land Use Analysis Land Use Hospitals, schools, child-care facilities, old age housing Residential, hotels, motels, holiday resorts Commercial (including retail centers, offices and entertainment centers) Sporting complexes and active open space Industrial

Individual Fatality Risk ×10–6 per year) (× 0.5 1 5 10 50

Source: Stewart, M.G. and Melchers, R.E. (1997). Probabilistic Risk Assessment of Engineering Systems, Chapman & Hall, London.

1.3.2 REGULATORY CRITERIA Typically, regulatory criteria are developed by public authorities acting broadly on behalf of the public and mandated by government. Generally, regulatory authorities develop general safety goals and set specific safety standards, monitor system performance, and prosecute if specified safety standards are violated. There are a number of possible measurement units available, including expected number of deaths, injuries or cost equivalents, short- and long-term expected health implications, and various environmental criteria. None constitutes a completely satisfactory accounting for the possible impact of a hazardous situation. However, alternatives are difficult to find or suggest. In a sense, all should be seen as convenient surrogates for much more complex accounting schemes; the associated issues are, ultimately, the same as those for economic decision criteria. Table 1.6 shows an example of a typical set of safety targets for hazardous industries where neighboring land usage may be affected. Regulatory standard enforcement can cause resentment and an adversarial situation that is not conducive to the operator or licensee committing to risk control and appropriate risk management. Enforcement also requires periodic inspection of the facility by regulatory personnel.

1.3.3 PRESCRIPTIVE DESIGN CRITERIA The easiest approach, and perhaps the most used approach, is to show compliance with existing regulations and their prescriptive instructions for design. This approach, strictly speaking, does not determine performance in the sense of performance measures noted above, but only shows that regulatory instructions for design have been met. This is often adequate, because the prevailing knowledge base is often used to establish conservative limits for design and performance parameters. However, the literature contains examples of barriers not meeting the objectives of the Resource Conservation and Recovery Act (RCRA) to protect human health, while being consistent with RCRA design guidance. Thus, for future

20

Barrier Systems for Environmental Contaminant Containment & Treatment

barriers, it cannot be simply assumed that meeting RCRA design guidance will provide the protection that regulations and the public desire if the hazards, location, or design approach vary significantly from demonstrated RCRA design guidance.

1.3.4 RISK CRITERIA A more complete and systematic approach to developing long-term performance standards is to estimate risk to human health and the environment by considering possible exposure pathways, estimating the total exposure, and then (if needed) converting to risk. This task can be performed with varying degrees of sophistication depending on the situation. The most common approach is deterministic. Under the deterministic approach, a range of standard release and pathway scenarios is constructed by the analyst, then doses are calculated under the assumption that the scenarios will occur without consideration of the likelihood of the scenarios. This approach is characteristically conservative, worst case, and tends to overestimate dose exposures to the receptors (Moore et al., 2001). An example is the use of a hydrological code, e.g., HELP, to estimate water movement through a barrier, then estimate exposure to the nearest population, convert to risk (if needed), and compare to exposure/risk requirements — all without including probabilities in any of the stages of analysis. For more complex, longer hazard, and/or higher hazard situations, probabilistic approaches have been used. “A probabilistic approach to scenarios takes the likelihood of occurrence into account, allowing a mechanism to differentiate between site characteristics and accessibility” (Moore et al., 2001). Where uncertainties in key variables are significant, stochastic approaches are used to estimate uncertainties and sensitivities. The uncertainties in key parameters are estimated and then propagated through the analysis of relevant scenarios to determine the resulting uncertainty in the relevant performance measures. The term “probabilistic” is sometimes used for such analyses because one is dealing with probabilities of a variable having a certain value. However, the term can be used as a descriptor of the approach of analyzing the probabilities of different scenarios (as used in the nuclear industry and other industries). A stochastic approach can be combined with either deterministic sets of scenarios or probabilistic sets of scenarios. For example, the United States Nuclear Regulatory Commission (USNRC) has established a set of regulatory guidelines for decommissioning sites (leaving residual hazards protected by barriers) that use stochastic parameter variations to estimate parameter uncertainties (Meyer and Gee, 1999; Meyer and Taira, 2001; Meyer and Orr, 2002). A recent powerful method of stochastic barrier analyses was performed for the Mill Tailings Repository in Utah (Ho et al., 2001a,b, 2002a,b). The FRAMES shell with HELP was used to estimate the cumulative probability distribution for the following four performance measures: • Peak Ra-226 dose • Peak Ra-226 concentration in aquifer

Damage and System Performance Prediction

21

• Water transport through cover • Radio-gas transport through cover The exposure scenarios were deterministic. The stochastic analyses allowed for the estimation of the chance that a given performance measure would be exceeded and the relative contribution of different variables to the total uncertainty was covered. Figure 1.7 provides information on the cumulative probability distribution for the peak Ra-226 dose that was determined in this analysis. The figure shows that there is 100% probability that the dose will be below the 100 mrem/year (1 mSv/year) limit. In this example, there is a 50% probability that the dose will be below 10–12 mrem/year (which is the value of a femto-Sv/year in international dose units). The approaches described above can be applied in either a static or dynamic manner. In static analyses, the probability of the occurrence of the scenarios; the boundary conditions; the mechanisms; the state of the barrier; and, hence, the failure rates are considered constant with time. In dynamic analyses, one or more of the parameters is considered to vary with time. Realistically, no barrier analysis is totally static because the boundary conditions of precipitation almost always vary over a year (or several years). Construction quality assurance/quality control (QA/QC) is often the key issue at the beginning of service life, but several Consequences

Likelihood

Insignificant (1)

Minor (2)

Moderate (3)

Major (4)

Catastrophic (5)

Almost certain (5) Likely (4) Moderate (3) Unlikely (2) Rare (1) High risk

Moderate risk

Significant risk

Low risk

FIGURE 1.7 A typical risk-consequence matrix. (From Stewart, M.G. and Melchers R.E., 1997. Probabilistic Risk Assessment of Engineering Systems, Chapman & Hall, London. With permission.)

22

Barrier Systems for Environmental Contaminant Containment & Treatment Environmental influences E1

Flux Q1(t)

Barrier layers resistance R1(t) B

A

Differential settlements

Contaminant D

Environmental influences E2

C

Barrier layers resistance R2(t)

Flux Q2(t)

FIGURE 1.8 Schematic cap containment system showing potential fluxes and some influences.

combinations of factors become the overriding issue during long service lives. Indeed, the United States Environmental Protection Agency (USEPA) found QA/QC problems at several barriers studied in 1998 (USEPA, 1998). The challenge is to estimate the state of the system toward its end of life. For illustration, consider the section ABCD through a conceptualized model of a cover system (Figure 1.8). The barrier AB is a cap composed of a number of layers of different permeabilities (and other properties) and may include a man-made membrane. It may be assumed that the properties of this latter subsystem are reasonably well known. On the other hand, it may be that CD represents a natural barrier with permeability and other properties that are known only with considerable uncertainties.

1.3.5 DEMONSTRATING COMPLIANCE: THE SAFETY CASE CONCEPT A safety case consists of a document describing how the regulatory safety goals have been met. Such a document is reviewed or audited by the regulatory authority to ensure the following: • The study deals in sufficient depth with the facility under discussion (completeness requirement). • Appropriate event probabilities and consequences have been considered. • Compliance to the relevant regulations has been achieved and documented. An important advantage is that the onus of proof is put on the licensee or operator. Safety cases are used extensively in the off-shore, chemical and petrochemical industries, particularly in Europe, and are similar to the demonstration

Damage and System Performance Prediction

23

Unacceptable region-risks cannot be justified (except in extraordinary circumstances)

ALARP region-risk reduction is impractical or costs are disproportionate to benefits gained

Acceptable region-ensure risks remain in this region

Negligible risk

FIGURE 1.9 ALARP concept. (From Stewart, M.G. and Melchers R.E., 1997. Probabilistic Risk Assessment of Engineering Systems, Chapman & Hall, London. With permission.)

of compliance for operational activities or environmental impact assessments for new systems adopted internationally.

1.3.6 MIXED CRITERIA A mixed economic and regulatory framework for decisions is the so-called ALARP (as low as reasonably practical) or the ALARA (as low as reasonably attainable) approach. Although terms such as “low,” “reasonably,” “possible,” and “attainable” are highly subjective and difficult to define, ALARP has been widely adopted (e.g., USNRC, off-shore industry members). The concept is sketched in Figure 1.9, and an overview is provided by Stewart and Melchers (1997).

1.3.7 QUALITATIVE

AND INDEXING

ANALYSES

This is the simplest level approach. Numbers are not used in qualitative analysis, only subjective assessments, perhaps obtained from interaction between risk analysts and operators. The results can then be put into a risk-consequence matrix. This approach is easy to use and useful for nontechnical audiences. However, it is difficult to use with quantitative approaches to risk assessment. The rankings cannot be converted to numbers, as the outcome can be meaningless and inconsistent. An example of a qualitative risk-consequence matrix is shown in Figure 1.7. The indexing approach involves assigning ratings that usually are not analytically derived, but represent performance assessments conducted on the basis

24

Barrier Systems for Environmental Contaminant Containment & Treatment

of experience with such systems or subjective estimates of performance probabilities. This approach was used by Einarsson and Rausand (1998) in rating the survivability of an industrial system that was subjected to a number of stressors.

1.4 QUANTIFICATION OF LONG-TERM DAMAGE SCENARIOS, EVENTS, AND MECHANISMS Establishing the quantitative relationship between containment system or component reliability and design has been targeted by many researchers, among which are Gilbert and Tang (1995), Hartley (1988), Bogardi et al. (1989), and Shackelford (1992). The limitations of current performance assessment models fall into one or more of the following categories: • Description of only statistical reliability of sample test data for initial facility design • Use of time-invariant barrier material characteristics and contaminant loading/stress levels to develop long-term performance estimates • Repetition of stress tests to a few cycles corresponding to short service lives relative to the service lives of real facilities

1.4.1 CATEGORIES

OF

DEGRADATION MECHANISMS

The potential for damage of containment systems under applied stress is determined by the interactions among three categories of factors that can change in magnitude with time: location factors, design and operational factors, and waste characteristics. While some damage phenomena occur continuously, others are transient and can cause instantaneous damage if the resistance of the system or its components is exceeded by the applied stresses. 1.4.1.1 Slow Physico-Chemical and Biological Processes Among the physico-chemical processes that can damage barriers are barrier flocculation at low depth of burial; chemical attack and photo-aging of geotextiles, slurry settlement, dissolution; and freeze-thaw action (Chamberlain and Gow, 1978; Fernandez and Quigley, 1991; Fleming and Inyang, 1995; Elias et al., 1997; Daniels et al., 1999, 2001). Liu and Gilbert (2002) identified seepage-induced fluid pressure as a potential damage mechanism for landfill cover slopes. Figure 1.10 shows experimental results obtained by Fernandez and Quigley (1991) on the effects of permeant viscosity and effective stress on the hydraulic conductivity of compacted clays with mineralogies simulative of clay barriers. Generally, the spatial scale at which physico-chemical and biological processes degrade barrier systems is microscopic, at least initially. However, manifestations such as visible flaws, increased flow of fluids through the barrier, and/or a reduction in barrier strength can eventually result. Chen et al. (2000) investigated the effects of organic fluid contamination on the compressibility of kaolinite. The

Damage and System Performance Prediction

100 10−5

% Domestic waste leachate 50

0

25

10−5

100

10−6

10−7 Double layer control Water only

10−8

Viscosity control

−9

10

−5

10

0

100

50

10−7 Water only Viscosity control

10−8

10−9

100

σ′vo = 40 kpa Reference k (water) Final k for permeant

10−6

0

% Ethanol in the permeant

(a)

(b)

0

10

−6

100

Hydraulic conductivity, k (cm/s)

Water only Viscosity control

0

50

0

100

σ′vo = 160 kpa Reference k (water) Final k for permeant

10−7

H H

H−C − C − OH Water only H H (Ethanol) є = 32

10−8

10−9

10−10

− −

10−7

10−9

% Domestic waste leachate 50

− −

Hydraulic conductivity, k (cm/s)

σ′vo = 80 kpa Reference k (water) Final k for permeant

10−8

100

Water compacted

Water compacted 10−6

50

% Ethanol in the permeant

% Domestic waste leachate 50

0

Water compacted

σ′vo = 0 kpa Reference k (water) Final k for permeant

Hydraulic conductivity, k (cm/s)

Hydraulic conductivity, k (cm/s)

Water compacted

% Domestic waste leachate 50

Viscosity control 0

50

% Ethanol in the permeant

% Ethanol in the permeant

(c)

(d)

100

FIGURE 1.10 Hydraulic conductivity of water-compacted clay permeated with municipal solid waste leachate–ethanol mixtures subsequent to prestressing water-wet clay at various levels of vertical effective stress. (From Fernandez, F. and Quigley, R.M., 1991. Canadian Geotechnical Journal, 28, 338–398. With permission.)

dielectric constant of the liquids was used as an index of physico-chemical aggressiveness. The results indicate that the kaolinite compressive index decreased from 2.8 at a dielectric constant of 1.9 for heptane, to 0.75 at a dielectric constant of 24 for ethanol. The compressive index was 2.06 for distilled water (which has a dielectric constant of about 80), but decreased slightly for formamide,

26

Barrier Systems for Environmental Contaminant Containment & Treatment

which has a dielectric constant of 110. The authors computed the attractive forces for kaolinite in the various organic fluids using the Lifshitz theory and found that the attractive force variation agreed with the compressibility results qualitatively. The reader should note that, as discussed in Chapter 3, barrier components rarely comprise only a single mineral. They are usually composite mixtures such that mineralogy, particle size distribution, and mix proportions determine their reactivity with permeants of a given chemistry under prevailing environmental conditions (Inyang et al., 1998a). As nontraditional barrier materials (e.g., paper mill sludges) are used more frequently, it is essential to consider physico-chemical interactions in barrier design and long-term performance assessment (Moo-Young and Zimmie, 1997). Physico-chemical interactions that can affect barrier performance are not limited to particulate barrier materials. Geosynthetics are known to degrade under attack by permeants with which they are not chemically compatible (Lord and Koerner, 1984). Indeed, as explained by Elias et al. (1997), the potential degradation of geosynthetics during service depends on the mineralogy of the fibers that comprise them, permeant chemistry, environmental exposure conditions, and the intensity of the stresses to which they are subjected. Indeed, tensile strength reduction factors for geosynthetics aging ranging from 1.15 to 2 are recommended. Test results and semi-empirical analytical approaches for evaluating the time-dependent mechanical response of high-density polyethylene geomembranes (HDPE) were presented by Merry and Bray (1997). Regardless of the type of physico-chemical and biological mechanisms that are known to degrade barrier materials, transport rates at the microscopic level are likely to be affected. Quantitative methods that are suitable for use in estimating transport rates of fluids through barriers at the scale in which these processes are significant were described by Lake and Rowe (2000), Bai and Inyang (1999), and Inyang et al. (2000a,b). These processes should be differentiated from the largely physical mechanisms of fluid flow through large fissures such as cracks, macropores, and inter-lift breaks in compacted soils, as well as defects in geomembranes. Jayawickrama and Lytton (1992) presented quantitative relationships for estimating flow through macropores, while Giroud (1997) comprehensively treated liquid migration through defects in composite liners that comprise geomembranes with defects. In particular, concrete covers such as those used to contain contaminants at brownfield sites as described by Inyang et al. (1998b) are susceptible to cracking. A number of investigators have presented conceptual frameworks and quantitative models for estimating liquid flow rates through cracked systems (Bernabe, 1995; Bai et al., 1996, 1997, 2000a). With appropriate boundary conditions and material characterization, these methods can be used for damaged barrier performance assessment. Additional discussion of transport mechanisms and models that apply to barriers at various scales is presented in Chapter 2. Another class of slow processes that impact the exposed surface of barriers is vegetation succession. The process of ecological succession on the exposed cap of a containment system is important for several reasons. First, without active intervention, the species complex representing the “climax” community is the

Damage and System Performance Prediction

27

one that will ultimately occur on the capping system. While the forces of natural replacement can be managed, there are forces that require active intervention (i.e., expenditure of maintenance energy) to change or arrest the natural trajectory toward the successional equilibrium. The bare soil cap, or cap planted with vegetation in most cases, represents a nonequilibrium condition. As vegetation colonizes the cap and changes over time, it produces significant changes in the soil conditions relative to the initial soil conditions. In addition to the changes noted above, root systems penetrate the soil structure, altering hydraulic properties by creating preferential flow paths through the soil and adding organic matter to the soil matrix. The death and decay of above-ground plant material deposit organic matter on the soil surface, thereby altering the evaporative properties of the soil. The increased organic content of the soil and development of preferential flow paths increases the moisture retention capacity of the soils of the cap system. Similarly, the development of a mulch or litter layer on the soil surface retards run off, increases water infiltration rates, and decreases evaporation from the soil surface. The timing of successional sequences can vary dramatically, but the attainment of the local climax condition takes a long period of time. Smith et al. (1997) reported that in areas near Oak Ridge, Tennessee, the progression from old field grassland to a shrub vegetation stage is expected to take 10 to 25 years, while the continued development to a mature forest takes on the order of 65 to 150 years. Processes in a Colorado subalpine forest can take 200 to 300 years to achieve the expected spruce-fir forest cover, and the rate of the processes is significantly influenced by such factors as soil nutrients, aspect (e.g., north or south facing slope), and rock cover in the terrain (Donnegan and Rebertus, 1998). Succession in nutrient-poor sand dune communities is similarly slow, with early successional species being lost within 100 years, while plant species were still being replaced after over 300 years. Rates of change in the plant communities tend to be most rapid in the earlier stages of the successional sequence. One highly significant effect of vegetation is the alteration of the water balance. Plants mine water and nutrients from the soil to support photosynthesis and growth. Thus, the plant root systems pump water from the soil to the atmosphere throughout the growing season. With this property in mind, much work has been performed in arid and semi-arid climates with water balance or evapotranspiration caps (DOE, 2000). In this approach, the function of the vegetation is not only to hold the surface soil in place against wind and water erosion, but also to maintain the water balance of the cap. Surface soil layers are designed by depth and texture to hold the annual input of moisture in the soil matrix, while the plants extract the moisture through the growing season, resulting in little or no deep penetration of moisture to the drainage layer. Furthermore, by seeding these capping systems with the native climax vegetation, the successional sequence is jump-started, likely minimizing potential surprises as the capping systems mature. The penetration of root systems into the subsurface is also an issue of concern. Plant roots penetrate a soil matrix in search of water and represent a powerful

28

Barrier Systems for Environmental Contaminant Containment & Treatment

force. Initial studies of plant root systems on capping systems were largely driven by concerns about root penetration into buried wastes. Many cases are documented of plant root systems penetrating into buried waste and transporting hazardous material to the surface (Arthur, 1982; Arthur and Markham, 1983). Recent capping system designs have included low permeability clay barriers between the vegetated topsoil and the buried waste. Studies have shown that plant roots can penetrate into, if not through, clay barriers. Particularly susceptible to penetration are barriers constructed of clays such as bentonite which have significant shrink-swell properties as moisture conditions change. Drying of previously hydrated clays of this type leads to cracking and permits points of entry for plant roots (Nyhan, 1989). One need only witness the ability of plants to establish in asphalt cracks and concrete pavements with the subsequent deterioration of those materials to understand that initial penetration into such clay barriers leads to further deterioration and potential localized movement of water through the barrier into the buried waste. This poses the following two problems. (i) Potential mobilization of contaminants to the surface through plant uptake — Because plant roots do not absorb some elements, a significant factor in this consideration is the nature of the waste that is buried. Root penetration into buried wastes at the Uranium Mill Tailings Remedial Action (UMTRA) site in Burrell, Pennsylvania, was deemed not to be a significant issue because the plants were not mobilizing the buried uranium mill tailing waste to an extent that resulted in significant human or ecological risks (UMTRA, 1992). Radioisotopes such as cesium and strontium, which are analogs for the biologically essential elements potassium and calcium, have significant remobilization potential if they are biologically available in the buried wastes. Another type of slow process that affects the long-term performance of containment systems is global warming because of its impacts on regional hydrology and the response of vegetation, soils, and temperature conditions to expected patterns. It should be noted that large-scale, long-duration events such as global warming may not directly affect containment system performance at initially discernable scales, but may cause significant changes in environmental conditions that, in turn, impact long-term performance. Uncertainties in the estimates of the impact of large-scale, long-duration phenomena such as global warming translate to uncertainties in their impacts on future containment system performance. Generally, a possible worse climate for the barrier should be estimated using climate change modeling and/or examining the geological and fossil record. Then, the resulting effects can be estimated by modeling how the ecosystem would respond to the new climate and/or examining natural analogs. The natural analogs can be from the site in question, or can be current ecology from a location that approximates the hypothetical new climate. Ho et al. (2002b) used this approach to compare estimates of cumulative probability distributions of a radon-226 dose from a shallow alluvial aquifer (Figure 1.11). “Natural and archeological analogs exist for ecological change, pedogenesis (soil development), and climate change. Effects of ecological change are inferred by measuring water balance parameters in plant communities representing chronosequences

Damage and System Performance Prediction

29

Landfill surface

Drainage layer Leachate collection pipe Deformed leachate collection pipe

Clay liner

FIGURE 1.11 A schematic illustration of landfill deformation due to seismic activity. (From Inyang, H.I., 1992. Journal of Environmental Systems, 21(3), 223–235. With permission.) of responses to climate shifts and secondary disturbances (e.g., fire). Pedogenic effects are inferred from measurements of key physical and hydraulic soil properties in natural and archaeological soil profiles that are considered analogous to future states of engineered soils. Analogs of local responses to future global climate change exist as proxy ecological records of similar paleoclimates” (Waugh, 2001).

Indeed, the “present” and hypothetical “future” climate cases by Waugh (2002) were the basis for the two cases by Ho et al. (2002b) in Figure 1.11. In that study, the future climate case was wetter, and the overall performance was calculated to be worse, but still acceptable. (ii) Induction of water movement into buried waste — The second and likely more significant issue associated with root penetration through the impermeable layers is the induction of water movement into the buried waste. Depending on the magnitude of the water flow and the type of barrier systems below the waste, this type of failure can result in waste mobilization downward into the vadose zone and potentially to the water table, resulting in a contamination event that requires remedial action. 1.4.1.2 Intrusive Events Just as plants grow on the caps with the root systems seeking water, various animal species also invade capping systems with the primary objective of seeking food or shelter. Both invertebrate and vertebrate species have been documented to invade waste isolation systems, resulting in the mobilization of buried materials. Bowerman and Redente (1998), Suter et al. (1993), and Smith et al. (1997) summarized experiences of animal intrusion into buried waste. Studies at Hanford Washington and Idaho National Environmental and Engineering Laboratory

30

Barrier Systems for Environmental Contaminant Containment & Treatment

(INEEL) in the U.S. documented excavation by harvester ants to depths of 2 to 4 m below the ground surface through types of cover materials ranging from topsoil to gravel. Studies at a variety of primarily arid and semi-arid sites in Washington, Idaho, New Mexico, and Colorado documented intrusion into capping systems by pocket mice, deer mice, kangaroo rats, pocket gophers, prairie dogs, and ground squirrels. These excavations represented invasions through a wide variety of cover systems with penetrations at least to 1 m and probably significantly deeper; because in one case animals assimilated radionuclides buried under 2.4 m of soil cover. These breaches of cover integrity can be complimented by slower migration of fines under overburden loads into the pore spaces of drainage layers as mathematically modeled by Bai et al. (2000b). Larger animals are also capable of invading burial sites, primarily in search of food, but sometimes in search of shelter. Foxes, coyotes, badgers, and other predators excavate the tunnels of prey species such as mice and gophers. In the southeastern region of the United States, the spread of armadillos represents the threat of disruption of surface cover systems as they search for insect prey. As is the case of plants, these organisms are part of the surrounding landscape and significant (sometimes excessive) maintenance activities are required to eliminate them or minimize the effects of their activity once the capping system is constructed. Given the long expected requirements for cap integrity, high maintenance costs are not a desirable characteristic for a capping system, as they represent a substantial mortgage cost that can and should be avoided. 1.4.1.3 Transient Events Transient events can cause catastrophic damage to containment systems. Among such events are seismic shaking, landslides, and volcanic activity. Inyang (1992) has described the damage potential of near-surface containment systems by seismic activity. Figure 1.12 shows a schematic illustration of the potential damages to landfill components by an earthquake. Excessive ground shaking can cause liquefaction-induced differential settlement of barrier layers, destruction of impoundment walls by hydrodynamic forces, interface failures in geomembrane/soil systems, and sand boiling through liner systems. Several investigators have analyzed and documented the impacts of seismic activity on containment systems and components (Matasovic et al., 1995; Daneshjoo and Hushmand, 1999; Kavazanjian and Matasovic, 2001). The distribution of such events in time and space is highly variable, owing to the differences in the characteristics of bedrock and soil cover, as well as the intensity of geodynamic activities. Thus, the potential for containment system damage by transient events varies considerably from one region to another. Figure 1.13 shows the regions of the conterminous United States with greater than 90% probability that acceleration in bedrock will exceed 0.1 g in 250 years. For regulatory purposes, this level of bedrock acceleration is generally considered to be the minimum level required to cause damage to buried and/or embedded facilities when soil cover amplification factors

Damage and System Performance Prediction

31

FIGURE 1.12 Regions in the conterminous United States with greater than 90% probability that the acceleration in bedrock will exceed 0.1 g in 250 years.

1.0

Cumulative probability

0.8 0.7 0.6

Present

0.5 0.4

Future

0.3 0.2 0.1

100 mrem/yr (DOE order 5400.5 || 1.a)

0.9

0.0 1.0E − 23 1.0E − 20 1.0E − 17 1.0E − 14 1.0E − 11 1.0E − 08 1.0E − 05 1.0E − 02 1.0E + 01 1.0E + 04 Peak cumulative dose (mrem/yr)

FIGURE 1.13 Cumulative probability distribution for peak cumulative dose for Ra-226 and its progeny from the shallow alluvial aquifer for present and future conditions. The “present” and “future” curves reflect the present and a hypothetical future climate. (From Ho, C.K. et al., 2002b. Spectrum 2002, Reno, Nevada, August 2002. With permission.)

32

Barrier Systems for Environmental Contaminant Containment & Treatment

are applied. A comprehensive listing of stressing factors and their effects on the long-term performance of containment systems is presented in Table 1.7. 1.4.1.4 Cyclical Stressing Mechanisms Several loading mechanisms of barrier systems are repetitive in nature (e.g., freeze-thaw and wet-dry cycling of cover systems). A barrier component or system that does not fail at constant loading or imposition of a single-load cycle can still be damaged by repetitive loads of a single magnitude. The potential and magnitude of future containment system damage do not depend exclusively on the level and number of repetitions of stress and intensity of physico-chemical and biological phenomena. In general, three categories of interactive factors are recognized: location factors, design and operational factors, and waste factors. A conservatively designed system is likely to resist the same level of stress better than a poorly designed system. Furthermore, a well-constructed and maintained system should perform better under stresses that are imposed. Various types of systems and barriers exhibit different levels of susceptibilities when exposed to different modes of physical stress and other damage processes. Table 1.8 shows a matrix of which stressors are relevant for which barrier systems. Each model system has characteristic materials. The matrix includes the natural subsurface for comparison; note that the natural subsurface is isolated from many stressors that have impacts on near-surface, engineered barriers. Not shown in the table is an assessment of how important a stressor may be, or when a stressor may be important. These aspects must be considered for individual barrier designs at specific locations (e.g., freeze-thaw cycles can be critical in northern climates and irrelevant in southern climates). In particular, freeze-thaw effects on the texture and hydraulic conductivity of clay barrier materials in cold regions have been intensively investigated. Chamberlain and Ayorinde (1991) summarized the results of tests performed by many investigators, largely in the laboratory. A set of tests conducted on compacted clays from four facilities produced results that exhibit permeability increases up to three orders of magnitude for 14 freeze-thaw cycles, after which further increases were negligible. In their investigation of the Waite Amulet failings soil cover system near Rouyn-Noranda in Quebec, Canada, Mohamed et al. (1993) found a 23-fold increase in cover permeability due to three freeze-thaw cycles. Experimental results suggest that the initial moisture content, soil particle size distribution, and mineralogy play a significant role in determining the magnitude of increase in soil permeability in response to freeze-thaw cycles (Benoit, 1973). Indeed, for some of the soil cores tested, freezing and thawing caused a decrease in hydraulic conductivity (e.g., soil consisting predominantly of relatively large aggregates such as 1.0 to 2.0 mm in diameter). To cover scale effects, evaluations of freeze-thaw effects have also been made at meso-scale and field scale (Miller and Lee, 1992). In their studies, Benson et al. (1995) instrumented a test pad of compact clay and performed hydraulic conductivity tests before and after winter season on block samples retrieved from the field. The results indicated that up

Damage and System Performance Prediction

33

TABLE 1.7 How Stressors May Generate Effects on Near-Surface Barriers Stressor

Mechanical Effects

Water (rainfall/snowmelt, surface water)

Hydrostatic head Erosion (run off, surface water, movement of materials within barriers, localized depressions pooling water) Ice expansion/contraction

Temperature changes

Differential thermal expansion Freeze-thaw Desiccation Ice expansion/contraction Mechanical loading of surface Movement of objects Erosion of exposed surface Delayering (lifting layers)

Wind

Mechanical loads (seismic, vibration, subsidence, impacting objects) Plants

Animals

Microbes

Puncturing Mechanical loading Settling of fines into coarse layers Macro-porosity development Evapo-transpiration

Macro-porosity Infiltration Erosion (of excavated material) Digging and exposure of buried material Plugging of capillaries

Physicochemical and Biochemical Effects Wet-dry cycles Corrosion Leaching Water influences plant, animal, microbial behavior Water transports contaminants Surface water brings seeds → plant ecology Water brings microbes → microbial ecology Influences bio-chemical reaction rates Climate changes impact biota

Bring seeds → plant ecology Bring microbes → microbial ecology Add soil → change plant growing conditions → change/hurt/help vegetation N/A

Uptake contaminated material and bring to surface Impact animal ecology (food supply) Impact microbial ecology (e.g., nutrient profiles) Evapo-transpiration Impact plant community/species Impact microbial ecology (e.g., nutrient profiles)

Bio-corrosion Bio-leaching Change surface tension, e.g., in pores and capillaries Change PRB biochemistry Soil formation → change plant biota → change animal biota

34

Barrier Systems for Environmental Contaminant Containment & Treatment

TABLE 1.7 (continued) How Stressors May Generate Effects on Near-Surface Barriers Stressor Radiation (UV, ionizing) Waste

Physicochemical and Biochemical Effects

Mechanical Effects N/A

Material property degradation

Chemical attack

Material property degradation

Water (hydrostatic head, erosion) Water (wet-dry cycles) Corrosion/other chemical attack Temperature changes, e.g., freeze-thaw cycles Wind erosion Imposed mechanical stress (subsidence, seismic, structural loads) Impacting objects, e.g., construction/operations activities, people and animals walking Plant and/or animal intrusion Biocorrosion Other microbial impacts, e.g., plugging capillaries Ultraviolet radiation Ionizing radiation Contaminant leachate interaction

X X X X X X X X X

X X X X

X X X X X X

X X

X X

X

X

Vadose Zone Itself (fate and transport, not barrier per se)

Bottom of Grouted/ Entombed Structure

Liner at Bottom of Waste Zones

Evaporation Pond Liner

Top of Grouted/ Entombed Structure

Concrete Cap

Relevant Stressors

Earthen Cap

TABLE 1.8 Relevant Stressors for Various Barrier Systems

X X X

X X X X X

X X

X X X X X

X

X

X

to 10 freeze-thaw cycles occurred in the season and that the hydraulic conductivity of the samples increased by factors ranging from 50 to 300. More recently, effort has been made as exemplified by Daniels et al. (2001) to develop quantitative schemes for interrelating field- and laboratory-based freeze-thaw permeability measurements and improving the resistance of barriers to freeze-thaw through soil stabilizer amendments. In some cases, soil strength can improve at the expense of low hydraulic conductivity (Daniels et al., 1999).

Damage and System Performance Prediction

35

Other cyclical degradation mechanisms of barrier systems include wet-dry cycling and desiccation in response to temperature and relative humidity profiles that can alternate but remain predominantly at high temperature and low humidity levels during most of the year. At the fundamental level, the swelling potential of clays has been investigated by many researchers, among whom are Blackmore and Miller (1961) and Dasog et al. (1988). From a practical standpoint, the inclusion of granular soils (sands and silts) in barrier mixtures and their compaction generally decrease shrink-swell potential. Several investigators have developed empirical methods for analyzing the relationships between the residual strength of structures and the number of load cycles. Schaff and Davidson (1997) developed Equation (1.7) to describe the pattern of the Weibull scale parameter in terms of the residual strength of components of structures under fatigue loading:

(

Rn = Ro − Ro − S p

)

⎡n⎤ ⎢N ⎥ ⎣ ⎦

v

(1.7)

where Rn is the residual strength scale parameter after n cycles of loading, Ro is the static strength scale parameter, Sp is the peak stress magnitude of the constantamplitude loading, N is the scale parameter for the fatigue life distribution, and v is the strength degradation parameter. Equation (1.7) describes the exponential line shown in Figure 1.14. The reader should note that the strength measured for a particular cycle is observed as a distribution of magnitudes. Thus, the line represents the connection of points defined by the specified statistical confidence level of strength data for each loading cycle. Kachanov (1986) developed Equation (1.8) for describing damage accumulation in materials and systems as a result of load repetition: ⎛ ΔS ⎞ ∂D =C⎜ ∂n ⎝ 1 − D ⎟⎠

m

(1.8)

In Equation (1.8), D is the damage variable, S is the amplitude range of the repeated stress, n is the number of cycles, C > 0 and m ≥ 1 are material constants. In the case of containment systems, D could be fracture intensity or macroporosity. In the field, load repetitions are not designed but observed, implying that observed data or their estimates need to be fitted to time functions for use in performance prediction equations. Quantitative techniques that are based on time-series analysis are useful in efforts to describe the loading pattern of containment systems in the field. Khalil and Moraes (1997) developed a simple method of time-series analysis that is based on the linear least squares spectral analysis (LLSSA). For a given set of loading frequencies, the best-fit sinusoidal equation is found for observed data.

36

Barrier Systems for Environmental Contaminant Containment & Treatment Static strength

Residual strength, R (n)

Residual strength relation

Peak Stress

Failed portion of distribution

FIGURE 1.14 Strength distributions associated with a residual strength Weibull relationship with number of loading cycles on materials. (From Schaff, J.R. and Davidson, B.D., 1997. Composite Materials: Fatigue and Fracture (Sixth Volume). ASTM STP 1285, pp. 179–200. With permission.)

The power of each frequency is taken as the square of the amplitude of the fit. In this method, the function described by Equation (1.9) is fitted to a time series for each frequency. By using the LLSSA, the parameters A and B can be found through Equations (1.10), (1.11), and (1.12). γ i − γ avg = A • cos ωti + B • sin ωti

A=

1⎡ Δ ⎣⎢

B=

1⎡ Δ ⎣⎢

∑ γ cos ωt ∑ sin i

∑ γ sin ωt ∑ cos i

Δ=

2

i

i

2

ωti −

∑ γ sin ωt ∑ cos ωt sin ωt ⎤⎦⎥

(1.10)

ωti −

∑ γ cos ωt ∑ cos ωt sin ωt ⎤⎦⎥

(1.11)

∑ cos ωt ∑ sin 2

i

(1.9)

2

i

i

i

i

i

i

i

i

2

ωti −

(∑ cos ωt sin ωi ) i

i

(1.12)

In the equations, Σ is the variance, γ is the parameter of interest, and t is the time. The error on each of the two parameters A and B can be estimated using Equations (1.13) and (1.14), respectively. Then, the total error of the power can be expressed as in Equation (1.15).

Damage and System Performance Prediction 2

σ

2 A

( γ − γ ) ∑ sin = (N − 2) Δ

2 B

( γ − γ ) ∑ cos = (N − 2) Δ

2

fit

2

σ

37

2

fit

(

σ 2P = 4 A2 σ 2A + B2 σ 2B

ωti

(1.13)

ωti

(1.14)

)

(1.15)

The phase of the periodicity, Ø, and its error, σØ, can be estimated using Equations (1.16) and (1.17). ⎧ tan −1 (− B /A) ⎪ Ø = ⎨ tan −1 (− B /A) − π ⎪ tan −1 (− B /A) + π ⎩ 2

A>0 A < 0, B > 0 A < 0, B < 0

⎛ Bσ ⎞ ⎛ Aσ ⎞ σφ = ⎜ 2 A 2 ⎟ − ⎜ 2 B 2 ⎟ ⎝A +B ⎠ ⎝A +B ⎠

(1.16)

2

(1.17)

With these parameters, the best-fit sinusoidal equation can be developed for data that fluctuate in cycles over time. Khalil and Moraes (1997) applied this method to a different type of problem: determination of the concentration vs. time function for methane in ice cores during the past 160,000 years (Figure 1.15).

1.4.2 QUANTITATIVE LINKAGE OF CONTAMINANT RELEASE SOURCE TERMS TO RISK ASSESSMENT AND COMPLIANCE LIMITS Risk assessments of containment facilities require estimating the level of hazard posed by a containment system to human health and the environment. The estimation of risks to human health and the environment is at the posterior end of the analyses. At the anterior end, there is the step in which estimates of the probable quantities of contaminants that will be released from the facilities are made. Such analysis is typical at the source term assessment stage illustrated in Figure 1.16 by the USNRC (2000) as adapted from Kozak et al. (1990). The overall framework for relating containment system performance (operationally defined in terms of source term concentrations) to human health and ecological risk assessment are illustrated in Figure 1.17 as developed by Nazarali et al. (1998). System failure can be defined in terms of the exceedence of a given

38

Barrier Systems for Environmental Contaminant Containment & Treatment 700

Concentration (ppbv)

600

500

400

300

200

0

40

80

120

160

Kiloyears before present

FIGURE 1.15 Methane concentration vs. time experimentally measured on ice cores. (From Khalil, M.A.K. and Moraes, F.P., 1995. Journal of the Air and Waste Management Association, 45, 62–74. With permission.)

probability of release of specific quantities of target contaminants in the future. Such a quantity can be specified on the basis of the known or assumed human health and environmental risks associated with exposures to the target contaminants at contaminant levels above the specified values. As shown in Figure 1.18, releases of a specific contaminant from a containment system over a given interval occur as a distribution. Several uncertainties plague efforts to make precise estimates of the probability of release of specific quantities of contaminants for selected future time frames. Gallegos et al. (1998) identified the following sources of uncertainty in long-term performance predictions of containment systems: • Uncertainty in the likelihood of occurrence of future events • Uncertainty in conceptual and analytical models that describe events and processes • Uncertainty in parameter values The establishment of the compliance of a containment system with selected performance criteria is characterized by the uncertainties stated above. Indeed, one of the utilities of system dynamics approaches described by Siu (1994) is that possible interactions among various performance factors can be addressed, and uncertainties can be reduced by using the evolving knowledge base.

Damage and System Performance Prediction

39 Engineered barrier performance

Infiltration

Unsaturated Vadose-zone flow

Container breach Source term detail

Waste from leach

Air transport

Facility release Engineered barrier performance Vadose-zone transport Source term

Vadose-zone transport

Saturated-zone flow

Saturated-zone transport

Surface-water transport

Pathways and dosimetry

Air transport

Dose to human

FIGURE 1.16 Conceptual model showing processes to be considered in an LLW performance assessment. (USNRC, 2000. A performance assessment methodology for low-level radioactive waste disposal facilities. Recommendations of NRC’s Performance Assessment Working Group. NUREG-1573. United States Nuclear Regulatory Commission, Office of Nuclear Material Safety and Safeguards, Washington, DC; modified from Kozak, M.W. et al., 1990. U.S. Nuclear Regulatory Commission, NUREG/CR-5532, Washington, DC.)

Two common types of probabilistic analyses can be used in assessing containment system performance. Quantified risk analysis (QRA) gives all element performances and all probability estimates as numerical point estimates. There is no estimate of the uncertainty in the result(s). QRA is widely employed in the

Transported unit concentration t = 10,000 years

Transported unit concentration t = 140 years

Transported unit concentration t = 100 years

Transported unit concentration t = 40 years

Transport

Human health

Ecological

Red-tailed hawk

Coyote

Great basin pocket mouse

Generic plant

Recreational exposure scenario unit risk

Agricultural exposure scenario unit risk

Industrial exposure scenario unit risk

Residential exposure scenario unit risk

Exposure

Risk

Risk

Risk

FIGURE 1.17 Risk calculation flow chart. (From Nazarali, A.M. et al., 1998. Proceedings of Topical Meeting on Risk-Based Performance Assessment and Decision Making, Richland/Pasco, Washington, April 5–8, pp. 143–150. With permission.)

Source concentraion t=0

Source

40 Barrier Systems for Environmental Contaminant Containment & Treatment

Damage and System Performance Prediction

41

Estimate distributions of values for parameters x, y, and z f(x)

f(y)

x

y

f(z)

z

Input distributions into model Dose = g(x, y, z)

Frequency

Produce distribution of model results

Dose

Frequency

Compare with dose limits

Dose limit a Dose a = Probability of dose limit being exceeded

FIGURE 1.18 Probabilistic approach for treating model parameter uncertainty in an LLW performance assessment. (From USNRC, 2000. A performance assessment methodology for low-level radioactive waste disposal facilities. Recommendations of NRC’s Performance Assessment Working Group. NUREG-1573. United States Nuclear Regulatory Commission, Office of Nuclear Material Safety and Safeguards, Washington, DC.)

chemical and petrochemical industries. Probabilistic risk analysis (PRA) is more advanced than QRA and has element performances treated as random variables. Occurrence rates also can be given as random variables. PRA is the method of choice in the nuclear industry. Although more complex, more explicitness is required in the analysis and outcome uncertainty is recognized. Both methods use essentially the same tools but more refined data and analysis is used in the

42

Barrier Systems for Environmental Contaminant Containment & Treatment

case of PRA. Estimates of performance (i.e., failure or success) probabilities of components need to be made. For a composite containment system that comprises many components, the following sequential steps can be taken: 1. 2. 3. 4. 5. 6. 7. 8.

Disassemble the system into components. Analyze the system (e.g., series, parallel, compound). Consider the technology and understand each component. Predict future performance of each component (with uncertainty). Reassemble the components and their future behaviors. Assess critical components vs. system behaviors. Develop future expected system performance vs. time (or a surrogate). Estimate system uncertainty vs. time.

1.4.3 FRAMEWORKS FOR ASSESSMENT OF EVENT CONSEQUENCES AND CONNECTIVITIES AMONG CAUSES OF FAILURE Two important assessment systems aid in the analysis of long-term performance characteristics of multi-component facilities and systems: fault trees and event trees. 1.4.3.1 Fault Trees The connectivity of failure causes is often represented by a fault tree (Figure 1.19). A fault tree describes the chain of events leading to system failure and is used extensively for estimating the reliability of mechanical systems such as rockets and aircraft. Fault trees form the basis for quantitative estimation of failure probabilities in systems with simple pass-fail components, using point estimates of the probability of occurrence for each failure event. They are less suited to reliability analysis for systems that are likely to fail mainly because of stochastic processes. However, Cepic and Mavko (2002) discussed the use of the dynamic fault tree method to analyze the performance of multi-component systems. 1.4.3.2 Event Trees The consequences arising from component failure usually can be represented by an event tree (Figure 1.20). Again, usually point estimates of the probability of occurrence of each event in the event tree are used to predict outcome probabilities for each of the various outcomes.

1.4.4 ESTIMATION

OF

LONG-TERM FAILURE PROBABILITIES

The use of system failure probabilities as the target of computational steps provides an opportunity for estimating the reliability of containment systems and their decay or improvement with time. It should be noted that the relationship between reliability and failure probability is complementary as expressed in Equation (1.18). The sum of system reliability, Rss, and the system failure probability, Fss,

Damage and System Performance Prediction

43

Contaminant release volume/rate exceed design value

Loss of cover system effectiveness

Liner system damage

Cover clay fails to contain infiltration

Drainage layer clogs

Vegetative cover develops infiltration channels

FIGURE 1.19 A typical fault tree for a waste containment system.

must be unity. Because the objective is to track the variability in barrier performance with time, both Rss and Fss can be considered to be time functions. Rss = 1 − Fss

(1.18)

1.4.4.1 System Failure Probability The composite containment system illustrated in Figure 1.8 can be subjected to a number of loads (i.e., structural and chemical), with a resulting condition in which contaminants have greater potential to travel through its barrier system. Any of the component barriers can have subcomponents, but in order for the barrier to fail functionally, the contaminant must penetrate all layers. Hence, in a simplified case, and as discussed by Stewart and Melchers (1997), the barrier can be considered as a system with n parallel components, with system failure Fss requiring failure Fi (i = 1, …, n) of each component barrier. Both structurally and functionally, the configuration barrier system components may be such that some components are arranged in parallel mode, series mode, or a combination of both (i.e., compound mode). For a parallel system of components, Equation (1.19) represents the relationship between the failure of components and that of the system:

44

Barrier Systems for Environmental Contaminant Containment & Treatment

Cover clay fails to contains contaminant

Vegetative layer develops large infiltration channels

Drainage layer clogs

Liner system damage Yes

Yes

No

Yes Yes

Consequences Contaminant release volume and rate exceed design value Contaminant release volume and rate do not exceed design value Contaminant release volume and rate exceed design value

No No

No

Contaminant release volume and rate do not exceed design value Contaminant release volume and rate do not exceed design value

FIGURE 1.20 A typical event tree for a waste containment system.

Fss = F1 ∩ F2 ∩ F3 ∩ etc.

(1.19)

When there are multiple failure paths perhaps through multiple barriers (Figure 1.8), failure of the whole or a significant part of the whole system, Fs, may be brought about by failure of one or more of the subsystems, Fssj : Fs = Fss1 ∪ Fss 2 ∪ Fss 3 ∪ etc.

(1.20)

where the component terms Fssj refer to any failure path and may be defined by Equation (1.19) in the case of a failure path having to cross through a barrier with multiple layers. Note also that Equations (1.19) and (1.20) define the failure domain for the system (Stewart and Melchers, 1997). 1.4.4.2 Component Failure Probability Theoretically, for a multi-component system, the system failure probability cannot be estimated precisely without computation of the failure probabilities of each of the system components. For the containment system illustrated in Figure 1.8, if contaminant flux is selected as the performance factor, the probability of failure (exceedence of a specified flux within a specified time interval) can be modeled as a random process on a barrier parameter, Q(t), because the several factors

Damage and System Performance Prediction

45

Load Q Extreme value distribution

Upcrossing event Q > r

Barrier R = r

Instantaneous distribution Realization of load Time t First exceedence time t

1

FIGURE 1.21 Realization of a continuous random process showing time to first exceedence. (From Melchers, R.E., 1999. Structural Reliability Analysis and Prediction, 2nd ed., Wiley, Chichester. With permission.)

presented in Table 1.8 have highly uncertain magnitudes. When one layer in a barrier is subject to only one flux, the flux will be a function of time. Because the flux is a complex process that is not well defined as a function of environmental influences (e.g., rainfall, temperature, water table fluctuations, ground movements, earthquakes), it is appropriate to model it as a random process, Q(t) (Figure 1.21). This is approach is not uncommon in other applications such as water resource projects. Also shown in Figure 1.21, a barrier parameter, R, must not have a value greater than r, where r is a deterministic quantity that represents the resistance offered by the containment system barrier layer(s) to the permeation of the flux Q(t) through it. Failure is defined by the upcrossing event Q(t) > r. Of particular interest is the time, t1, to the first occurrence of a failure event (i.e., the first exceedence event). This time should be long for safe containment systems, and can be estimated readily if the exact trace of fluctuating loading is known. However, because the loading is a stochastic process, the first exceedence event will be a random variable. Its estimation is a central matter in reliability theory and is further discussed by Inyang (1994), Inyang et al. (1995), and Melchers (1999). Following the analysis by Stewart and Melchers (1997), two probability density functions are shown to the left of Figure 1.21. The main one, instantaneous distribution, refers to all possible values of the load (flux). The point where the resistance, R = r, cuts across it has a small (shaded) part of the probability density function above it. This is the probability that Q(t) > r. Evidently, the shaded zone (i.e., the probability of failure) will be smaller for higher values of resistance, r. Also, the time to the first exceedence event is expected to increase with r, indicating the importance of the resistance level.

46

Barrier Systems for Environmental Contaminant Containment & Treatment Load 1 Envelope of resistance Outcrossing event

Load 2

Time t

FIGURE 1.22 Envelope of resistance showing a realization of the vector load process and an outcrossing by one load component.

The other probability density function is an extreme value distribution that refers to the distribution of peaks (e.g., the maximum value recorded in any one year, month, or other time period). The reader is referred to standard textbooks on probability for deeper treatment of extreme values distributions. More generally, more than one flux can act on a given barrier or layer with the loading described by a vector process, Q(t). The details are not of concern here, except to note that the problem becomes an outcrossing of two processes: a continuous process and a pulse process (Figure 1.22). Also, the resistance becomes an envelope in the space of Q(t). The first exceedence time is now the time when either the load process or the combined action of the two processes outcrosses the envelope of capacity (i.e., the combined process or any individually crosses from the safe domain to the failure domain). Figure 1.9 shows a particular realization of the load process. The probability that the system fails in a given time period (0, tL ) (e.g., the design life) can be stated as the probability that the system will fail when it is first loaded, denoted pf (0, tL ), and the probability that it will fail subsequently given that it has not failed earlier. This can be expressed as follows: Pf (t ) ≈ Pf (0, t L ) + [1 − Pf (0, t L )][1 − exp(− vt )]

(1.21)

where v is the outcrossing rate. The expression is approximate because the second [ ] term is based on the assumption that failure events are rare and that such events therefore can be represented by the Poisson distribution, which leads to the expression shown. If the random load processes are assumed to continue indefinitely and have a stationary statistical nature (e.g., in the simplest case, the means and variances

Damage and System Performance Prediction

47

do not change with time), then the rate at which they cross out of the safe domain (i.e., the outcrossing rate) can be estimated from the following: +

v=

∫

safe domain

⎛• ⎞ E ⎜ X n X = x ⎟ f X ( x )dx ⎝ ⎠

(1.22)

where X = X(t) is a vector process and ( )+ denotes the positive component only. The term E(XnX = x) = xn = n(t) · x(t) > 0 represents the outward normal component of the vector process at the domain boundary. Note that the integral extends over the safe domain, which is the complement of Equations (1.19) and (1.20). The result (Equation (1.21) is valid only for rare outcrossings like those that might be associated with failure due to extremely rare, high-load events. The result can be extended (i) to allow for gradual deterioration of structural strength with time with the result that pf(0, tL) and v become time dependent, and (ii) approximately for situations with outcrossings which are not rare. Approaches to evaluating expressions pf(0, tL) and v for the expected life and, hence, the reliability of the system are available through Monte Carlo simulation and further simplifications of the problem. However, in both cases, Equations (1.21) and (1.22) must allow for the resistance R = R(t) to be a random variable as a function of time or a slow stochastic process (Stewart and Melchers, 1997). 1.4.4.3 Random Resistance In practice, the actual resistance R = R(t) will not be known precisely. Moreover, it will vary from point to point across the barrier, suggesting that actual resistance should be expressed as R = R(x,y,t) and modeled as a random field (Vanmarcke, 1983). However, this represents a difficult problem. Consider first the case of a single point in (x,y) space. Then R = R(x,y,t) becomes R = R(t) and could be modeled as a random variable, expressed through a probability density function (e.g., as in Figure 1.23). It follows that the line R = r shown in Figure 1.21 is just one realization of many possible outcomes. Usually, the resistance is made up of a number of components or is the outcome of a calculation procedure involving several variables. These, too, can be uncertain and may be expressed as random variables or processes. The modeling of R = R(t), therefore, can be complex. The issues involved can be illustrated with a simple example. Consider a random variable, S, that is a function of two others, M and A, given by: S = MA

(1.23)

The probability density function fs(s) of S can be estimated from the corresponding probability density functions for M and A using Equation (1.23). In general, this

48

Barrier Systems for Environmental Contaminant Containment & Treatment Probability

Mean resistance

Resistance

FIGURE 1.23 Schematic probability density function of resistance.

will require numerical integration and, in the case of complex functional relationships, Monte Carlo simulation. However, a simpler but approximate approach is to calculate only the first two moments of S using standard expressions, as follows: μS = μM + μ A

(1.24)

VS2 ≈ VM2 + VA2

(1.25)

where V = σ/μ is the coefficient of variation. Here, μs is the mean (i.e., the expected value) and σ s2 is the variance. The latter is a first estimate of the degree of uncertainty associated with S. Extending this approach to a function that is more complex than Equation (1.23) leads directly to the so-called error propagation (or second moment) techniques already used in the environmental modeling arena, and earlier in the general system reliability evaluations (Shakshuki et al., 2002). Although these techniques are sometimes termed risk or reliability techniques, they are strictly techniques for estimating uncertainty involved in the algorithm. For the case of a random field, R = R(x,y,t), two approaches are possible. One is to use random field theory to represent R = R(x,y,t) and to apply Monte Carlo simulation in (x,y) space to estimate the outcrossing rate (Vanmarke, 1983). This is a major computational task for realistic problems. A simpler approach is to estimate the probabilistic properties of the weakest failure path using extreme value theory. The problem then reverts to the case described above, but now with minimum resistance for a given barrier area, Rmin = Rmin(t), with the associated probability density function (Melchers, 1999). 1.4.4.4 Simplifications of Theory The theory sketched above can be simplified using a small number of assumptions. The main outcome is that the formulation does not address time explicitly.

Damage and System Performance Prediction

49

Although this implies significant limitations, the approach has been applied successfully to other problems. The first assumption is that resistance remains constant with time, at least for reasonably long periods of time. A step-wise approximation could allow for deterioration provided the stationarity remains valid. The second assumption is that the load processes are stationary, that is, their statistical properties do not change with time. As a result, the outcrossing rate, v, is constant with time, meaning that the probability of failure for any given period of time is constant. When only one load is primarily of interest, the above assumptions allow that load to be represented by only its probability density function. This represents a significant computational simplification. When multiple loads act, usually one load dominates a particular failure scenario, allowing the loadings to be combined into load combinations that show the dominance of one load or high correlation between the dominant loads (such that they can be represented by the one random variable). Finally, under the above assumptions, the initial failure probability pf(0, tL) of Equation (1.21) can be subsumed into the random variable representation. Consider now the case with just one load. Let this be the extreme value during the lifetime, with associated extreme value distribution fQ( ) (in this case for the maxima). Evidently, the maximum load is applied only once and the probability of failure is, thus, directly related to the probability distribution of the maximum load as follows: Failure:

(1.26)

r
in the event that the maximum load is applied or (1.27)

Z =r−Q <0 where Z is the safety margin. It follows that the probability of failure is: ∞

p f = Prob(r < Q) = Prob(Z < 0) =

∫ f (x)dx Q

(1.28)

r

Allowing also for random strength with associated probability density, fR (r), Equation (1.28) becomes: ∞

p f = Prob( R < Q ) =

∫ F ( x) f R

Q

( x ) dx

(1.29)

−∞

where FR ( ) is the cumulative distribution function for R. It is given by: r

FR (r ) = Prob ( R < r ) =

∫ f ( x)dx R

−∞

(1.30)

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Barrier Systems for Environmental Contaminant Containment & Treatment

Equation (1.29) is known as a convolution integral and can be interpreted loosely as follows. Under the integral, the first term, given by Equation (1.30), denotes the probability of failure given that the actual load has the value Q = x. The second term is the probability that the load takes the value Q = x. This is then integrated over all possible values of x, a dummy variable. In general, it is difficult to solve Equation (1.29) in closed form. As seen below, an important exception is when R and Q are each represented by a normal distribution or, more generally, are completely described only by their means and variances. Equation (1.29) could also have been written as follows: p f = Prob ( R < Q ) = Prob ( Z < 0 ) = Prob[G ( X ) < 0 ]

(1.31)

where G( ) is known as the limit state (or performance) function, and X = (R,Q) denotes the random vector of loads and resistances in general. Expression G(X) < 0 represents the condition that the bar will fail and was noted earlier. Then, Equation (1.30) can be extended to the case where several performance functions (e.g., Equations (1.19) and (1.20)) are met. Equation (1.20), for example, becomes the following, with X collecting all of the random variables in the problem: pf = …

∫

∫

f x ( x ) dx

(1.32)

∪ Gi ( x )<0 i

where fx( ) is the joint density function of the random variables, X. The solution of Equation (1.32) is not a simple matter. One option is to use Monte Carlo simulation to perform the integration. However, in its elementary form, this method is highly inefficient. An alternative is to linearize the boundary ∪i Gi (X) = 0 of the region of integration (i.e., a first-order approximation) and simplify the form of Equation (1.32) to each random variable being represented only by its first two moments. These two simplifications allow the problem of integration to be bypassed altogether, because simple rules can be used for the addition of random variables represented by their first and second moments (i.e., mean and variance). For obvious reasons, this approach is called the first-order second moment (FOSM) method. Because of its simplicity, it is widely used. In the FOSM method, the mean and standard deviation of the safety margin (Figure 1.24) are, from probability theory rules: μ Z = μ R − μQ

(1.33)

σ 2Z = σ 2R + σ Q2

(1.34)

with, as before, failure denoted by Z < 0 and survival by Z ≥ 0 (Figure 1.24). Hence, the probability of failure becomes:

Damage and System Performance Prediction

51

fZ(z) Z<0 Failure

Z>0 Safety

σz

pf μz

0

z

βσz

FIGURE 1.24 Probability of failure and safety index. (From Melchers, R.E., 1999. Structural Reliability Analysis and Prediction, 2nd ed., Wiley, Chichester. With permission.)

⎛ 0 − μZ ⎞ = Φ −β p f = Prob ( R − Q < 0 ) = Prob ( Z < 0 ) = Φ ⎜ ⎝ σ Z ⎟⎠

( )

(1.35)

where Φ( ) is the standard normal distribution function with zero mean and unit standard deviation or variance. It is extensively tabulated in statistics texts, at least for higher probability levels. For low values of probability, more detailed tables are required (Melchers, 1999). The parameter β is known as the safety or reliability index. Evidently, β = μZ /σZ and measures, in the space of the safety margin (Figure 1.24), the distance from the mean of the safety margin to the failure condition in terms of the uncertainty, σZ, of the safety margin. Evidently, a greater β implies a lower probability of failure and vice versa (Melchers, 1999). 1.4.4.5 The Multi-Dimensional Case The above concepts carry over directly to problems involving multiple resistance parameters and multiple loads, but not load processes. For load processes, timedependent theory must be used. It is conventional to transform all of the loads to the standard normal space Y (with zero mean, unit variance). The limit state function, which must be linear, is transformed also to g(y) = 0 about the (as yet unknown) design point, y*. Where there is dependence between the variables or where they are not normal, the Nataf, Rosenblatt, or some other transformation is required (Melchers, 1999). Figure 1.25 is a sketch of the problem in two-dimensional y space, showing contours of the hill described by the joint probability density function, fY (y), of all the transformed random variables, Y. The probability of failure, pf, is represented

52

Barrier Systems for Environmental Contaminant Containment & Treatment y2

g(y) = 0 Non-linear g(y) = 0 Linearized

Failure domain

ν

Safe domain

y*

y1

0

β Contours of fy (y)

FIGURE 1.25 Space of standard normal variables and linearized limit state function. (From Melchers, R.E., 1999. Structural Reliability Analysis and Prediction, 2nd ed., Wiley, Chichester. With permission.)

by the volume under this hill in the failure region, i.e., the region for which g(y) < 0. As before, rather than address pf directly, it is convenient to work with the safety index, β. The central statement of the FOSM problem then becomes: ⎛ β = min( yT · y)1 2 = min ⎜ ⎜⎝

n

∑ i =1

⎞ yi2 ⎟ ⎟⎠

(1.36)

where yi represents the coordinates of any point on the limit state surface, g(y) = 0. This is an optimization problem and can be solved using any appropriate minimization algorithms. Figure 1.26 shows the same situation with m (i.e., multiple) limit states. In the case of a series system, series bounds can be used to collect together the probabilities estimated separately using Equation (1.36) for individual limit states. There are several such series bounds, the simplest (and least accurate) being:

Damage and System Performance Prediction

53

y2 Failure domain Df

g1(y) = 0

y1* β2

β1

g2(y) = 0

β3

0

y1

g1(y) = 0 linearized g3(y) = 0 Contours of fy(y) = 0

Safe domain

FIGURE 1.26 Series system representation in standard normal space. (From Melchers, R.E., 1999. Structural Reliability Analysis and Prediction, 2nd ed., Wiley, Chichester. With permission.)

m

( )

max p fi ≤ p f system ≤ 1 − i =1

m

m

∏ (1 − p ) ≈ ∑ p fi

i =1

fi

(1.37)

i =1

with pf system denoting the probability of failure for the structural system with m limit state functions. Bounds are available also for the intersections of two or more limit state functions (Melchers, 1999).

1.4.5 COMPONENT AND SYSTEM FAILURE IN CONTAINING CONTAMINANTS The proper reliability estimation of a system such as in Figure 1.8 is a significant task, recognizing the complex relationships governing the inputs and environmental effects. Reliability estimates are heavily dependent on the information in the tails of probability distributions, implying that a good understanding of the input and output processes exists and that they can be modeled appropriately. Although simplified models can be used, their use affects the quality of the outcomes from a reliability analysis. Other alternatives are characterized by some deficiencies: simpler methods of safety or risk assessment, modeling and information about stochastic processes, and probabilistic variables that hide these

54

Barrier Systems for Environmental Contaminant Containment & Treatment

difficulties by ignoring the uncertainties. Their application can lead to a false sense of security in future performance estimates. It follows that the simplifications introduced above in reliability theory also should be used with care. As indicated, each requires significant assumptions about the system behavior. Thus, when predicting the long-term reliability of containment systems, the time-variant approach is the most appropriate. The incompleteness of data and probabilistic models need not, however, be an insurmountable obstacle in the application of reliability theory. As discussed briefly below, experience gained in-service through monitoring and observation can be used to refine understanding of the system and characteristics of the processes involved. The tools to monitor and observe are Bayesian updating and system dynamics analysis, both of which are increasingly recognized as powerful tools in geoenvironmental engineering. A second and equally important aspect of the Bayesian method is the use of subjective probabilities in reliability analysis and elsewhere. The probability distributions and the stochastic process representations in the exposition above were assumed to be completely known. Classic statistical literature assumes that these can be inferred from observation of sufficient experiments, as in the use of monitoring data. The issue of modeling vs. monitoring with respect to containment system performance assessment has drawn attention from many researchers and practicing personnel. Inyang (2003) provided an assessment of the general utility of monitoring and modeling in environmental assessments. Following the issues discussed by Melchers (1999), it is not surprising that engineers and some applied scientists have taken a more pragmatic approach and assumed that even nonfrequent subjective information obtained from less formal observation and experience can be applied in probability theory and, hence, reliability theory. Subjective information can, as Bayes implied, be used as prior information and refined as more data become available (see below). This is an important point with respect to applying probabilistic methods for the long-term performance analysis of waste containment systems. In essence, there is convergence in utility between probabilistic analysis and the use of monitoring data, but monitoring data alone are insufficient as the bases for predictions and system management.

1.4.6 RELATING PROBABLE CONTAMINANT CONCENTRATIONS TO RISKS Within the regulatory context, the effectiveness of a waste management system (of which a containment system is a part) is most commonly appreciated in terms of ecological and human health risks. Therefore, it is necessary to establish the relationship between the failure probabilities of the containment system and human health and ecological risks. Risk assessments require the input of contaminant source terms. As a simple illustration, Reddi and Inyang (2000) developed Equation (1.38) to estimate the source term for a containment system that releases contaminants into the vadose zone. This equation is presented in conjunction with Figure 1.27.

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55

Surface impoundment

Ground surface

Long term flow channels α Dt

Liner

d q, Ca

Unsaturated geomedia

Water table Saturated geomedia

b

Leachate plume Vh, Co

Bedrock

FIGURE 1.27 An illustration of the influence of barrier damage on contaminant source term for fate and transport modeling and risk assessments. (From Reddi, L.N. and Inyang, H.I., 2000. Geoenvironmental Engineering, Principles and Applications, 1st ed., Marcel Dekker, New York. With permission.)

Co =

C a qd Vh b

(1.38)

where Co is the source term concentration per unit width of the plume for contaminant fate and transport modeling (M/L2), q is the contaminant flow rate per unit width in the vadose zone (L2/T), Ca is contaminant concentration in the vadose zone (M/L3), d is the width of the saturated zone (L), Vh is the plume velocity (L/T), and b is the plume thickness (L). Obviously, parameters Ca and q are determined mostly by containment system performance. Deterministic equations that express the flow rate and quantities of contaminants through the components of a containment system (such as those presented in Chapter 2) can be used to estimate the magnitude of these parameters. With respect to the probabilistic analysis presented below, Ca and q can be computed as quantities with specified probabilities of occurrence for use in source term estimates in ecological and human health risk assessments. If the failure is specified in terms of the maximum allowable magnitudes of Ca, q, and even Co, then the probability of exceeding the specified magnitude of any of these three parameters can be used to determine failure. In the latter case, if the probability of exceedence of a given magnitude is high enough (value to

56

Barrier Systems for Environmental Contaminant Containment & Treatment

be specified), then the system would be considered to have failed. Typically, contaminant migration models (i.e., fate and transport models) contain Co instead of Ca, thus eliminating the essential parameters that would enable a more complete appreciation of the decay, growth, or constancy of the source term with extended time. In some cases where the source (e.g., the impoundment in Figure 1.27) has been eliminated, focus on Co instead of Ca may be justified. The parameters Ca and Co can be quantitatively linked to exposure assessment equations that are usually incorporated into quantitative human health and ecological risk assessment frameworks. An example of such a framework is the total risk integrated methodology (TRIM) described by USEPA (1999) and illustrated in Figure 1.28. The exposure-event function is an expression of the microenvironmental exposure of an individual or cohort to a contaminant in an exposure medium during a time step, t. As shown in Equation (1.39), the exposure event function is the product of exposure concentration and exposure duration. It should be noted that Equation (1.39) contains the parameter Cm, which relates to Ca and Co of Equation (1.38). Essentially, the critical utility of contaminant subsurface fate and transport models is to establish the quantitative linkage between Ca, Co, and Cm. Usually, Ca and Co > Cm due to travel path attenuation factors, except for

Ambient media concentrations Ci, air (t) Ci, water (t) Ci, soil (t) etc. Averaging time

Time step Inter media transfer IFT (j, s –> m, k, t)

Time scale matching

Exposureevent function Cm (i, k, l, t)

Uncertainty variability

ETz, m (i, k, l, t)

Ez, m (t)

Time Contact medium Air Water Food Soil etc

Activity Ambient Microenvironment zone

FIGURE 1.28 An exposure-event simulation framework for the TRIM. (From USEPA, 1999. Technical Support Document EPA-453/D-99-001. Research Triangle Park, North Carolina, pp. 4.1–6.8.)

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57

unusual situations in which the contaminants accumulate at the sink where Cm is measured. The fate processes and transport rates of each contaminant that is released at initial but time-variable concentration, Ca, into the surrounding geomedia are affected by the homogeneity, isotropy, and continuity of the geomedium. In some cases, as modeled by Inyang et al. (2000a), the released contaminant can be transported away quickly because of the high permeability or high diffusion coefficient of the contaminant in the geomedium. This transport would set up a high concentration gradient between the barrier and the bounding surface of the geomedium such that faster rates of contaminant release into the geomedium would result within the limits of the contaminant concentration for the containment system. As discussed by Rowe and Fraser (1995), an impact assessment of the waste disposal facilities that comprise barrier systems is characterized by several uncertainties, some of which derive from hydrogeological factors. Upon release from a containment system into the subsurface, the transport of a contaminant to an environmental sink can be retarded or accelerated by physico-chemical processes and travel path hydrogeology. At adequate concentration and favorable pH-Eh condition, substances can precipitate out of pore solution, thereby blocking some pores and retarding contaminant transport to a sink. Shu et al. (2000) provided a phenomenological and quantitative description of pore plugging processes that can result from mineral substance precipitation. Furthermore, Mazurek et al. (1996) experimentally investigated and confirmed redox front entrapment in clay shales that resulted from contrasting solubilities of reduced and oxidized species. Coupled with mineral sorption on pore walls and co-precipitation of secondary mineral phases that were produced, the contaminant was immobilized in the clay shale. In fractured systems, contaminants can travel at high rates relative to values computed for an intact medium. In some cases, the contaminants can travel as colloids at relatively fast rates from source to sink (Roy and Dzombak, 1997). Several investigators have developed and demonstrated techniques for characterizing textural characteristics of geomedia (Malone et al., 1986; Shi et al., 1999a,b). The characterization of fluid flow channels in geomedia is not always possible at the application scale of transport models such as those analyzed by Hathorn (1993) and Inyang et al. (2000b). For a given contaminant concentration at the sink or exposure point, exposure is not time-invariant. McCurdy (1994) illustrated the fluctuations in human exposure that define the exposure profile with some measures of exposure or potential dose to an individual or cohort (Figure 1.29). The utility of this assessment is that it is possible to estimate different exposure magnitudes for different exposure profiles to contaminants released into media. The implication is that in order to specify a human exposure (and hence risk) level as a design requirement for waste containment system, an exposure profile may need to be specified. Real health risks are affected by the exposure profile. For the same contaminant concentration in the medium proximal to the waste containment system, a wide range of human health risk estimates can result.

58

Barrier Systems for Environmental Contaminant Containment & Treatment P

ci

x

C(t)

Concentration

B

R

Time

t = a ti–1 ti

t=b

Δti

FIGURE 1.29 An example of an exposure or a potential dose profile and associated measures, where B is the integrated exposure from time t = a to t = b; p is the time between peaks over x; and R is the respites between exceedences of x. (From USEPA, 1999. TRIM Technical Support Document EPA-453/D-99-001. Research Triangle Park, North Carolina, pp. 4.1–6.8; adapted from McCurdy, T.R., 1994. In McKee, D.J. (Ed.), Tropospheric Ozone: Human Health and Agricultural Impacts, Lewis, Ann Arbor, MI, pp. 85–127. With permission.)

E z,m = C m (i, k, l, t ) ETz,m (i, k, l, t )

(1.39)

where Ez,m is the exposure experienced by person, z, from exposure medium, m, during time step, t, given that person z is in exposure district i in microenvironment k conducting activity i during that time step t. For example, the exposure in air might be measured in units of mg-h/m3. Note that the exposure time does not need to be a whole time step; Cm is the concentration in exposure medium, m (e.g., air, water, soil), in exposure district, i, in microenvironment, k, associated with activity, l, during time step, t. The units of measurement for air might be mg/m3, while the units of measurement for food might be mg/kg; ETz,m is the exposure duration of individual or cohort, z, to exposure medium, m, in exposure district, i, in microenvironment, k, conducting activity, l, during time step, t; z is the individual or cohort; m is the exposure medium contacted (i.e., air, water, food); i is the exposure district; k is the microenvironment in which the exposure occurs (e.g., indoors at home, in a vehicle, indoors at work); and l is the activity

Damage and System Performance Prediction

59

code that describes what the individual is doing at the time of exposure (e.g., resting, working, preparing food, cleaning, eating).

1.5 USE OF BARRIER DAMAGE AND PERFORMANCE MODELS FOR TEMPORAL SCALING OF MONITORING AND MAINTENANCE NEEDS Monitoring the state of the system provides some level of information about its operation. For the most beneficial results, objectives should be set and the design of a monitoring program should be addressed prior to system construction. System monitoring also requires an understanding of the manner in which results might be used in a system reliability context, as described in this section. It should be noted, however, that the implementation of monitoring technologies and actual interpretation of the monitoring observations require appropriate expertise and are described in detail in Chapters 4 and 5. Monitoring approaches and technologies were also analyzed by Inyang et al. (1995).

1.5.1 UPDATING The facility risk analysis involves assumptions about the probability distributions for random variables, including means (expected values) and variations about the mean. Monitoring can provide data to allow these initial assumptions to be modified. The standard procedure in probability theory is to use the Bayes theorem because it allows incorporation of experimental observations in an existing probability density function, so-called Bayesian updating. This method can allow for imperfections in the data obtained from monitoring (e.g., known uncertainties introduced by instruments). The concept can be illustrated quite simply (Figure 1.30). Consider some resistance property, R, which might, for example, represent some characteristic permeability. Let f R′′( ) represent the original (a priori) partial differential equation of R. New data collected from monitoring usually will not fit wholly in the original partial differential equation. Let fv( ) represent the new data, here taken for simplicity as a continuous partial differential equation. Both are shown on Figure 1.30, together with the updated (posteriori) pdf f R′′( ). It should be clear that if the data have a lot of scatter [i.e., if fv( ) has a large variance], the data do not contain much useful information and do little to help in refining the original partial differential equation. Conversely, if the data have very little scatter, it is highly informative and will have a significant influence. Similarly, if there is little understanding of the variable being considered, its a priori distribution, fR′ ( ), is highly uncertain and can be said to be noninformative. The posteriori distribution will then be considerably influenced by the additional data. Typically, the new evidence is monitoring data, which can be represented as a likelihood function, L (E/λ). This likelihood function is the conditional probability of observing the set of observation outcomes, E, given that the value of the parameter about which there is uncertainty (e.g., the mean of a random variable)

60

Barrier Systems for Environmental Contaminant Containment & Treatment

Posterior f ''R

Prio f 'R Likelihood fV

FIGURE 1.30 Known (a priori) pdf for resistance fR′(r) as modified by new information fV ( ) and modified (posteriori) pdf fR″( ). (From Melchers, R.E., 1999. Structural Reliability Analysis and Prediction, 2nd ed., Wiley, Chichester. With permission.)

is λ. According to Bayes theorem, the posterior probability distribution is then given by:

( )

f" λ =

( )

f ' λ L (E | λ)

(1.40)

∞

∫ f ( λ ) L (E | λ) d λ '

0

For example, if the observation data are the number of particular values above a given level during a given time interval or as a proportion of all readings, then the likelihood function is described by the Poisson distribution and is given by:

L (E | λ) =

(

)(

exp − λTL − λTL

)

n

n!

(1.41)

Typical prior, likelihood, and posterior distributions are available in standard texts. The posterior distribution is usually highly dependent on the selection of the prior distribution. Hence, care in selecting the original probability distributions is reflected in subsequent analysis, even after updating using observations.

1.5.2 EFFECT

OF

UPDATING

ON

SYSTEM MANAGEMENT

Updating provides a better estimate of the random variables that influence the behavior of the system and, hence, the predicted probabilities of failure that should

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61

Reliability Design reliability

Acceptable reliability

Time Inspection time point

FIGURE 1.31 Schematic variation of reliability showing effect of an observation at “inspection time point.”

enable the risk assessment to be updated as more appropriate monitoring information becomes available. A simple example is sketched in Figure 1.31, which indicates the improved life expectancy of a system as a result of favorable observations leading to an improved estimate of system reliability, shown at the inspection time point.

1.6 LIFE-CYCLE DECISION APPROACH AND MANAGEMENT It is desirable to optimize the management of containment systems over time. Examples might include minimizing the total expected costs, minimizing environmental impact, or reducing the likelihood of regulatory breaches and fines to a minimum. With this approach, the possibility exists to optimize the times between discrete monitoring or the intensity of monitoring, if continuous, with respect to the desired objective (Figure 1.32). When contamination is left on-site in engineered containment systems, measures must be taken to ensure that humans and the environment will continue to be protected from harmful exposures. Monitoring, maintenance, institutional controls, and other stewardship activities may be needed for very long periods of time (hundreds to thousands of years), depending on the times over which the contaminants retain their hazardous characteristics. A report by the National Academies (National Research Council, 2000) suggests that all engineered containment systems, if left unattended, will eventually “fall” and recommends planning for fallibility. An ability to forecast system performance is needed for a number of reasons, not the least of which is the need to have a better understanding of the actual stewardship requirements associated with containment systems. This knowledge

62

Barrier Systems for Environmental Contaminant Containment & Treatment Risk of failure Acceptable risk level

Particular structure deterioration Expected deterioration

FIGURE 1.32 Life-cycle reliability and assessment, showing effect of appropriate repairs (schematic). (From Melchers, R.E., 1999. Structural Reliability Analysis and Prediction, 2nd ed., Wiley, Chichester. With permission.)

can then be factored into remedial technology evaluation and remediation decision-making. Analytical forecasting tools that enable quantification of the likelihoods of events that could lead to failure, their potential consequences, and the associated response costs are needed so that more informed decisions can be made concerning the resources that will be needed and more effective stewardship planning can occur (Clarke et al., 2002; DOE, 2002). To achieve this requires the prediction of future environmental conditions and corresponding system responses. Here, the use of natural analogue models is emerging as a valuable tool (Waugh et al., 1994). Although there is a lack of performance data that can enable prediction verification at this point in time, the use of probabilistic approaches and scenario analyses can be helpful in determining the sensitivity of containment systems to specific events (Sanchez et al., 2002). With time, the ability to predict future performance to a reasonable period (a few decades) will increase as the knowledge base increases. Improvement will occur through a combination of analytical models, natural analogs, and performance monitoring.

REFERENCES Arthur, W.J., III (1982). Radionuclide concentration sin vegetation at a solid radioactive waste disposal area in southeastern Idaho. Journal of Environmental Quality, 11, 394–399. Arthur, W.J., III and Markham, O.D. (1983). Small mammal soil burrowing as a radionuclide transport vector at a radioactive waste disposal area in southeastern Idaho. Journal of Environmental Quality, 12, 117–122. Bai, M. and Inyang, H.I. (1999). Determination of contaminant migration in a barrier zone. Proceedings of the International Symposium on Coupled Phenomena in Civil, Mining and Petroleum Engineering, Sanya, Hainan Island, P.R. China, pp. 1–15.

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Bai, M., Roegiers, J.C. and Inyang, H.I. (1996). Contaminant transport in non-isothermal fractured media. ASCE Journal of Environmental Engineering, 122(5), 416–423. Bai, M., Elsworth, D. Inyang, H.I. and Roegiers, J.C. (1997). Modeling contaminant migration with linear sorption in strongly heterogeneous media. ASCE Journal of Environmental Engineering, 123(11), 1116–1124. Bai, M., Inyang, H.I., Chien, C.C. and Bruell, C. (2000a). Factors for assessing flow and transport in fractured porous media.(Chapter 2). In Inyang, H.I. and Bruell, C.J. (Eds.), Remediation in Rock Masses, American Society of Civil Engineers, Washington, DC, pp. 12–27. Bai, M., Inyang, H.I., Meng, F., Abousleiman, Y. and Roegiers, J.-C. (2000b). Statistical modeling of particle migration in gravel packs. Proceedings of the 4th International Symposium on Environmental Geotechnology and Global Sustainable Development, Boston (Danvers), MA, pp. 593–602. Benoit, G.R. (1973). Effect of freeze-thaw cycles on aggregate stability and hydraulic conductivity of three soil aggregate sizes. Soil Science Society of America Proceedings, 37, 3–5. Benson, C.H., Abichou, T.H., Olson, M.A. and Bosscher, P.J. (1995). Winter effects on hydraulic conductivity of compacted clay. Journal of Geotechnical Engineering, ASCE, 121(1), 69–79. Bernabe, Y. (1995). The transport properties of networks of cracks and pores. Journal of Geophysical Research, 100(B3), 4231–4241. Blackmore, A.V. and Miller, R.D. (1961). Tactoid size and osmotic swelling in calcium montmorillonite. Proceedings of the Soil Science Society, 169–173. Bogardi, I., Kelly, W.E. and Bardossy, A. (1989). Reliability model for soil liners initial design. Journal of Geotechnical Engineering, 115(5), 658–669. Bowerman, A.G. and Redente, E.F. (1998). Biointrusion of protective barriers at hazardous waste sites. Journal of Environmental Quality, 27, 625–632. Cadwell, L.L., Eberhardt, L.E. and Simmons, M.A. (1989). Animal Intrusion Studies for Protective Barriers: Status Report for FY 1988. Pacific Northwest Laboratory, Richland, Washington. Cepic, M. and Mavko, B. (2002). A dynamic fault tree. Reliability Engineering A: System Safety, 75(1), 83–91. Chamberlain, E.J. and Ayorinde, O.A. (1991). Freeze–thaw effects on clay covers and liners. Proceedings of the 6th International Specialty Conference on Cold Regions Engineering, Hanover, NH, pp. 136–151. Chamberlain, E.J. and Gow, A.J. (1978). Effect of freezing and thawing on the permeability and structure of soils. International Symposium on Ground Freezing, Bochum, Germany, pp. 31–43. Chen, J., Anandarajah, A. and Inyang, H. (2000). Compressibility of contaminated clay. Proceedings of the 4th International Symposium on Environmental Geotechnology and Global Sustainable Development, Vol. 2, Boston, MA, pp. 1226–1235. Clarke, J.H., MacDonnell, M.M., Waugh, W.J., Smith, E. D, Dunn, R. J, Water, R.D. and Burns, D.E. (2002). Engineered containment and control systems: nurturing nature. Annual Meeting of the Society for Risk Analysis, December 2002. Daneshjoo, F. and Hushmand, B. (1999). Response properties of landfills during seismic loading. Proceedings, Sardinia ’99, Seventh International Waste Management and Landfill Symposium, Cagliari, Italy, Vol. 3, pp. 563–567.

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Daniels, J.L., Inyang, H.I., Howe, G.S. and Ogunro, V.O. (1999). Innovative use of triaxial cell permeameters for measuring the earthen barrier resistance to freeze-thaw degradation under field conditions. Proceedings of the International Symposium on High Altitude & Sensitive Ecological Environmental Geotechnology, Nanjing, PR China, pp. 326–333. Daniels, J.L., Inyang, H.I. and Fang, H.Y. (2001). Theoretical relationship for scaling freezing-induced damage in barrier systems under laboratory and field conditions. Proceedings of International Symposium on Application of Natural Materials for Environmental Geotechnology, Tokyo, Japan, pp. 37–44. Dasgupta, P. (1993). An Inquiry into Well-Being and Destitution, Clarendon Press, Oxford. Dasog, G.S., Acton, D.F., Mermut, A.R. and De Jong, E. (1988). Shrink-swell potential and cracking in clay soils of Saskatchewan. Canadian Journal of Soil Science, 68, 251–260. DOE (2000). Alternative Landfill Cover, Innovative Technology Summary Report, DOE/EM-0558, Office of Environmental Management, Office of Science and Technology. DOE (2002). Science and Technology Roadmap for Long-Term Stewardship, Idaho National Engineering and Environmental Laboratory. Donnegan, J.A. and Rebertus, A.J. (1998). Rates and mechanisms of subalpine forest succession along an environmental gradient. Ecology, 80, 1370–1384. Einarsson, S. and Rausand, M. (1998). An approach to vulnerability analysis of complex industrial systems. Risk and Analysis, 18, No. 5. Elias, V., DiMaggio, J.A. and DiMillio, A. (1997). FWHA technical note on the degradation-reduction factors for geosynthetics. Geotechnical Fabrics Report, 24–26. Fernandez, F. and Quigley, R.M. (1991). Controlling the destructive effects of clay-organic liquid interactions by application of effective stress. Canadian Geotechnical Journal, 28, 338–398. Fleming, L.N. and Inyang, H.I. (1995). Permeability of clay-modified fly ash under thermal gradients. Journal of Materials in Civil Engineering, 7(3), 178–182. Forrester, J.W. (1961). Industrial Dynamics. MIT Press, Cambridge, MA; currently available from Pegasus Communications, Waltham, MA. Gallegos, D.P., Brown, T.J. and Cochran, J.R. (1998). A framework for treating uncertainty to facilitate waste disposal decision making — application of the approach to GCD performance assessment. Proceedings from the Topical Meeting on Riskbased Performance Assessment and Decision Making, Richland/Pasco, Washington, pp. 229–241. Gee, G.W. and Ward, A.L. (1997). “Still in Quest of the Perfect Cap,” Landfill Capping in the Semi-Arid West: Problems, Perspectives, and Solutions, Conference Proceedings, Environmental Science and Research Foundation Report ESRF-019, May 1997, pp. 145–164. Gilbert, R.B. and Tang, W.H. (1995). Reliability-based design for waste containment systems. Proceedings of Special Conference Characterization, Containment, Remediation, and Performance in Environmental Geotechnics, 2000, New Orleans, LA, pp. 499–513. Giroud, J.P. (1997). Equations for calculating the rate of liquid migration through composite liners due to geomembrane defects. Geosynthetics International, 4(3–4), 335–348. Hagemeister, M.E., Jones, D.D. and Woldt, W.E. (1996). Hazard ranking of landfills using fuzzy composite programming. Journal of Environmental Engineering, 122(4), 248–258.

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Hartley, R.P. (1988). Assessing the reliability of flexible membrane liners. In Land Disposal of Hazardous Waste: Engineering and Environmental Issues, Halsted Press, pp. 245–258. Hathorn, W.E. (1993). A review of fluid movement in compacted clay: the case of macropore flow. Proceedings of the ASCE Hydraulics Division Conference on Engineering Hydrology, San Francisco, CA, pp. 473–478. Ho, C.K., Arnold, B.W., Cochran, J.R., Tiara, R.Y. and Webb, S.W. (2001a). Development of a Risk-Based Performance-Assessment Method for Long-Term Cover SystemsApplication to the Monticello Mill Tailings Repository, Sandia National Laboratory report SAND2001-3032, October 2001. Ho, C.K., Webb, S.W. and Arnold, B.W. (2001b). Stochastic Simulations for Risk-Based Performance Assessments of Long-Term Cover Systems, Paper 144, 2001 International Conference & Remediation Technology Conference and Exhibition, Department of Energy Report DOE/EM-0620, Orlando Florida, 10–13 June 2001. Ho, C.K., Arnold, B.W., Cochran, J.R. and Tiara, R.Y. (2002a). Risk-Based Performance Assessment of Long-Term Cover Designs for Waste Isolation and Disposal at DOE Facilities, Project AL21SS22, DOE Environmental Management Subsurface Contaminants Focus Area (SCFA) Mid-Year Review, March 2002. Ho, C.K., Arnold, B.W., Cochran, J.R. and Tiara, R.Y. (2002b). Risk-Based Performance Assessment for Long-Term Cover Systems: Sensitivity and Uncertainty Analyses, Spectrum 2002, Reno, Nevada, August 2002. Hood, C.C., Jones, D.K.C., Pidgeon, N.F., Turner, B.A., Gibson, R., Bevan-Davies, C., Funtowicz, S.O., Horlick-Jones, T., McDermid, J.A., Penning-Rowsell, E.C., Ravetz, J.R., Sime, J.D. and Wells, C. (1992). Risk Management, Risk: Analysis, Perception and Management, The Royal Society, London, pp. 135–192. INEEL (2000). Subsurface Science Initiative Strategic Plan, Idaho National Engineering and Environmental Laboratory report INEEL/EXT-2000–01094, August 2000, Rev. 0. Inyang, H.I. (1992). Aspects of landfill design for stability in seismic zones. Journal of Environmental Systems, 21(3), 223–235. Inyang, H.I. (1994). A Weibull-based reliability analysis of waste containment systems. Proceedings of the First International Congress on Environmental Geotechnics, Calgary, Canada, 273–278. Inyang, H.I. (1999). Balancing prescriptive and performance-based design specifications for waste containment systems. Journal of Environmental Engineering, June, 491. Inyang, H.I. (2003). On models, modeling and modelers in the environmental arena. Journal of Environmental Engineering, 129(6), 489–490. Inyang, H.I. and Tomassoni, G. (1992). Indexing of long-term effectiveness of waste containment systems for a regulatory impact analysis. A Technical Guidance Document, Office of Solid Waste, U.S. Environmental Protection Agency, Washington, DC, p. 29. Inyang, H.I., Betsill, J.D., Breeden, R., Chamberlain, G.H., Dutta, S., Everett, L., Fuentes, R., Hendrickson, J., Koutsandreas, J., Lesmes, D., Loomis, G., Mangion, S.M., Morgan, D., Pfeifer, C., Puls, R.W., Stamnes, R.L., Vandel, T.D. and Williams, C. (1995). Performance monitoring and evaluation. Proceedings of the Assessment of Barrier Containment Technologies, International Containment Technology Workshop, Baltimore, MD, pp. 355–400. Inyang, H.I., Daniels, J.L. and Ogunro, V. (1998b). Engineering controls for risk reduction at Brownfield sites. Geotechnical Special Publication No. 82, American Society of Civil Engineers, pp. 229–252.

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Inyang, H.I., Parikh, J.M. and Iskandar, A. (1998a). Waste containment barrier. In Encyclopedia of Environmental Analysis and Remediation, Wiley, New York, pp. 5131–5141. Inyang, H.I., Daniels, J.L. and Chien, C.C. (2000a). Methods of analysis of contaminant migration in barrier materials. In Remediation Engineering of Contaminated Soils, edited by D.L. Wise, D.J. Trantolo, E.J. Cichon, H.I. Inyang and U. Stottmeister, Marcel Dekker, New York, pp. 63–82. Inyang, H.I., Shu, Z., Bai, M. and Roegiers, J.C. (2000b). Prediction of pollutant migration in landfill sites. Proceedings 4th International Symposium on Environmental Geotechnology and Global Sustainable Development, Danvers, MA, pp. 1487–1495. Jayawickrama, P.W. and Lytton, R.L. (1992). Conductivity through macropores in compacted clay. Proceedings of the 7th International Conference on Expansive Soils, pp. 99–104. Kachanov, L.M. (1986). Introduction to Continuum Damage Mechanics, Martinus Nijhoff, Boston. Kavazanjian, E., Jr. and Matasovic, N. (2001). Seismic design of mixed and hazardous waste landfills, state of the art paper no. 11, Proceedings of the Fourth International Conference on Recent Advances in Geotechnical Earthquake Engineering (on CD ROM), University of Missouri, Rolla, San Diego, California. Khalil, M.A.K. and Moraes, F.P. (1997). Linear least squares method for time series analysis with an application to a methane time series. Journal of the Air and Waste Management Association, 45, 62–74. Koerner, R.M. and Daniel, D.E. (1992). Better cover-ups. Civil Engineering, 55–57. Kozak, M.W., Chu, M.S.Y. and Mattingly, P.A. (1990). A performance assessment methodology for low-level waste facilities. U.S. Nuclear Regulatory Commission, NUREG/CR-5532, Washington, DC. Lake, C.B. and Rowe, R.K. (2000). Diffusion of sodium and chloride through geosynthetic clay liners. Geotextiles and Geomembranes, 18, 103–131. Layard, P.R.G. (1972). Cost-Benefit Analysis: Selected Readings. Penguin, Harmondsworth. Link, S.O., Cadwell, L.L., Petersen, K.L., Sackschewsky, M.R. and Landeen, D.S. (1995). The Role of Plants and Animals in Isolation Barriers at Hanford, Washington, PNL-10788, Pacific Northwest National Laboratory, Richland, Washington, 1995. Liu, C.N and Gilbert, R.B. (2002). Distribution of seepage-induced fluid pressure in landfill covers slopes. Proceedings of the Sixth International Symposium on Environmental Geotechnology and Global Sustainable Development, Seoul, Korea, pp. 287–294. Lord, A.E. and Koerner, R.M. (1984). Fundamental aspects of chemical degradation of geomembranes. Proceedings of the International Conference on Geomembranes, Denver, CO, pp. 293–298. Malone, P.G., May, J.H., Brown, K.W. and Thomas, J.C. (1986). Use of x-ray radiographic methods in the study of clay liners. Proceedings of the National Conference on Hazardous Wastes and Hazardous Materials, Atlanta, GA, pp. 199–201. Matasovic, N., Kavazanjian, E., Jr., Augello, A.J., Bray, J.D. and Seed, R.B. (1995). Solid waste landfill damage caused by 17 January 1994 Northridge earthquake. The Northridge, California, Earthquake of 17 January 1994: California Department of Conservation, Division of Mines and Geology Special Publication 116, Sacramento, California, pp. 221–229. Mazurek, M, Alexander, W.R. and Mackenzie, A.B. (1996). Contaminant retardation in fractured shales: matrix diffusion and redox front entrapment. Journal of Contaminant Hydrology, 21, 71–84.

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McCurdy, T.R. (1994). Human exposure to ambient ozone. In: D.J. McKee (Ed.) Tropospheric Ozone: Human Health and Agricultural Impacts, Lewis, Ann Arbor, pp. 85–127. Melchers, R.E. (1999). Structural Reliability Analysis and Prediction (2nd ed.), Wiley, Chichester. Melchers, R.E. (2001). On the ALARP approach to risk management. Reliability Engineering and System Safety, 71(2), 201–208. Merry, S.M. and Bray, J.D. (1997). Time-dependent mechanical response of HDPE geomembranes. Journal of Geotechnical and Geoenvironmental Engineering, 123(1), 57–65. Meyer, P.D. and Gee, G.W. (1999). Information on Hydrologic Conceptual Models, Parameters, Uncertainty Analyses, and Data Sources for Dose Assessments at Decommissioning Sites, Nuclear Regulatory Commission report NUREG/CR-6656 or Pacific Northwest National Laboratory report PNNL-13091, November 1999. Meyer, P.D. and Orr, S. (2002). Evaluation of Hydrologic Uncertainty Assessments for Decommissioning Sites Using Complex and Simplified Models, Nuclear Regulatory Commission report NUREG/CR-6767 or Pacific Northwest National Laboratory report PNNL-13832, March 2002. Meyer, P.D. and Taira, R.Y. (2001). Hydrologic Uncertainty Assessment for Decommissioning Sites: Hypothetical Test Case Applications, Nuclear Regulatory Commission report NUREG/CR-6695 or Pacific Northwest National Laboratory report PNNL-13375, January 2001. Miller, C.J. and Lee, J.Y. (1992). Effects of freeze-thaw on clay cover liner performance. Proceedings of the Mediterranean Conference on Environmental Geotechnology, Cesme, Turkey, pp. 205–211. Mohamed, A.O., Young, R.N., Caporuscio, F., Yanful, E.K. and Bienvenu, L. (1993). Chemical interaction and cyclic freeze-thaw effects on the integrity of the soil cover for waste amulet tailings. Proceedings of the Joint CSCE-ASCE National Conference on Environmental Engineering, Montreal, Canada, pp. 259–272. Moore, B., Ditmars, J., Minsker, B. and Bachmaier, J. (2001). Performance Evaluation Using Expert Elicitation and Long Term Stewardship Monitoring Optimization for Long Term Stewardship, Paper 470, 2001 International Conference & Remediation Technology Conference and Exhibition, Department of Energy report DOE/EM-0620, Orlando, Florida, 10–13 June 2001. Moo-Young, H.K. and Zimmie, J.F. (1997). Waste minimization and reuse of paper mill sludges and landfill covers: a case of study. Journal of Waste Management and Research, 15(6), 593–605. National Research Council (2000). Long-Term Institutional Management of U.S. Department of Energy Legacy Waste Sites, National Academy Press, Washington, DC. Nazarali, A.M., Rogers, P.M. and Haass, C.C. (1998). Long-term human health impact assessment as a decision making tool in a complex system for environmental restoration and waste management. Proceedings of Topical Meeting on Risk-Based Performance Assessment and Decision Making, Richland/Pasco, Washington, April 5–8, pp. 143–150. Nyhan, J.W. (1989). Development of technology for the long-term stabilization and closure of shallow land burial sites in semiarid environments. LA-1128-MS. Los Alamos National Laboratory, Los Alamos, NM. Piet, S.J. and Breckenridge, R.B. (2002). Near-Surface Engineered Environmental Barrier Integrity, Spectrum 2002, Reno, August 2002.

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Piet, S.J., Dakins, M.E., Gibson, P.L., Joe, J.C., Kerr, T.A. and Nitschke, R.L. (2001). A Framework for Making Sustainable Cleanup Decisions Using the KONVERGENCE Model, INEEL technical report INEEL/EXT-2001–01485. Reddi, L.N. and Inyang, H.I. (2000). Geoenvironmental Engineering, Principles and Applications, 1st ed., Marcel Dekker, New York, 494 pp. Rowe, R.K. and Fraser, M.J. (1995). Effect of uncertainty in the assessment of the potential impact of waste disposal facilities. Proceedings of Geoenvironment 2000, the ASCE Geotechnical Division Special Conference, New Orleans, LA, pp. 270–284. Roy, S.B. and Dzombak, D.A. (1997). Chemical factors influencing colloid-facilitated transport of contaminants in porous media. Environmental Science and Technology, 31, 656–664. Sanchez, F., Clarke, J.H. and Parker, F.L. (2002). Evaluating requirements for stewardship of contaminated facilities. Proceedings of the Waste Management 2002 Conference, Tucson, AZ. Schaff, J.R. and Davidson, B.D. (1997). A strength-based wearout model for predicting the life of composite structures. Composite Materials: Fatigue and Fracture (Sixth Volume). ASTM STP 1285, pp. 179–200. Shackelford, C.D. (1992). Performance-based design of soil liners. Proceedings of the Mediterranean Conference on Environmental Geotechnology, Cesme, Turkey, pp. 145–153. Shakshuki, E.K., Ponnambalam, K. and Wadaj, T. (2002). Risk assessment in environmental systems. Canadian Journal of Civil Engineering, 29(1), 1–7. Shi, B., Murakami, Y., Wu, Z., Chen, J. and Inyang, H.I. (1999a). Monitoring internal failure evolution in soils using computerized x-ray tomography (CT). Engineering Geology, 54 (3–4), 321–328. Shi, B., Wu, Z., Inyang, H.I., Chen, J. and Wang, B. (1999b). Preparation of soil specimens for SEM analysis using freeze-cut-drying. Bulletin of the International Association of Engineering Geology and the Environment, 58, 1–7. Shu, Z., Bai, M., Roegiers, J-C. and Inyang, H.I. (2000). Modeling selective plugging processes by induced precipitation for enhancing oil recovery. Proceedings of the 4th International Symposium on Environmental Geotechnology and Global Sustainable Development, Boston (Danvers), MA, pp. 309–317. Siu, N. (1994). Risk assessment for dynamic systems: and overview. Reliability Engineering and System Safety, 43, pp. 43–73. Smith, E.D., Luxmore, R.J. andSuter, G.W. (1997). Natural physical and biological processes compromise the long-term performance of compacted soil caps. In: Barrier Technologies for Environmental Management, Summary of a Workshop, National Research Council, Washington DC, pp. D61–D70. STELLA (2001). Stella Research 7.0, developed by High Performance Systems, Inc., Hanover, New Hampshire, 2001 (www.hps-inc.com). Stewart, M.G. and Melchers R.E. (1997). Probabilistic Risk Assessment of Engineering Systems, Chapman & Hall, London. Suter, G.W., Luxmoore, R.J. and Smith, E.D. (1993). Compacted soil barriers at abandoned landfills will fail in the long term, Journal of Environmental Quality, 22, 217–226. UMTRA. 1992. Vegetation growh patterns on six rock covered UMTRA project disposal cells. UMTRA Project. Rep. UMTRA-DOE/AL-400677.0000. USEPA (1998). Evaluation of Subsurface Engineered Barriers at Waste Sites, Environmental Protection Agency report EPA 542-R-98–005, August 1998. (www.clu-in.com)

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USEPA (1999). Total Risk Integrated Methodology (TRIM) Technical Support Document EPA-453/D-99–001. Office of Air Quality Planning and Standards, United States Environmental Planning Agency, Research Triangle Park, North Carolina, pp. 4.1–6.8. USNRC (2000). A performance assessment methodology for low-level radioactive waste disposal facilities. Recommendations of NRC’s Performance Assessment Working Group. NUREG-1573. United States Nuclear Regulatory Commission, Office of Nuclear Material safety and Safeguards, Washington, DC. Vanmarcke, E. (1983). Random Fields: Analysis and Synthesis, MIT Press, p. 382. Waugh, W.J. (2001). Uranium Mill Tailings Covers: Evaluating Long-Term Performance, Paper 244, 2001 International Conference & Remediation Technology Conference and Exhibition, Department of Energy report DOE/EM-0620, Orlando Florida, 10–13 June 2001. Waugh, W.J. (2002). Characterization of the Environmental Envelope for the Design of Long-Term Covers, Project ID02SS21, DOE Environmental Management Subsurface Contaminants Focus Area (SCFA) Mid-Year Review, March, 2002. Waugh, W.J., Peterson, K.L., Link S.O., Bjorstad, B.N. and Gee, G.W. (1994). Natural analogs of the long-term performance of engineered covers. In: Gee, G.W. and Wing, N.R. (Eds.), In-Situ Remediation: Scientific Basis for Current and Future Technologies, Battle Press. Wolford, A.J., Atwood, C.L. and Roesner, W.S. (1992). Aging Data analysis and Risk Assessment — Development and Demonstration Study, NUREG/CR-5378 or EGG-2567, August 1992.

2

Modeling of Fluid Transport through Barriers Prepared by* Brent E. Sleep University of Toronto, Toronto, Canada

Charles D. Shackelford Colorado State University, Fort Collins, Colorado

Jack C. Parker Oak Ridge National Laboratory, Oak Ridge, Tennessee

2.1 OVERVIEW As understanding of the mechanisms of contaminant transport through barrier systems improves, the design of containment systems is moving from a prescriptive approach to a performance design approach. It is expected that reliance on models for predictive-based design will increase in the future, as the need for predicting long-term barrier system performance increases. This chapter details the mechanisms and models for predicting the performance of components of passive barriers such as caps, permeable reactive barriers (PRBs), and walls and floors. The relevant regulatory drivers and current state of practice are summarized, and research needs are identified. Chapter 1 dealt with system performance modeling while this chapter focuses on the performance of components that constitute containment systems.

* With contributions by Calvin C. Chien, DuPont, Wilmington, Delaware; Thomas O. Early, Oak Ridge National Laboratory, Oak Ridge, Tennessee; Clifford K. Ho, Sandia National Laboratories, Albuquerque, New Mexico; Richard C. Landis, DuPont, Wilmington, Delaware; Alyssa Lanier, University of Wisconsin, Madison, Wisconsin; Michael A. Malusis, GeoTrans, Inc., Westminster, Colorado; Mario Manassero, Politecnico I, Torino, Italy; Greg P. Newman, Geo-Slope International Ltd., Calgary, Canada; Robert W. Puls, U.S. Environmental Protection Agency, Ada, Oklahoma; Terrence M. Sullivan, Brookhaven National Laboratory, Upton, New York

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2.2 CAPS 2.2.1 FEATURES, EVENTS, AND PROCESSES AFFECTING PERFORMANCE OF CAPS Covers and caps are engineered structures that must perform within a larger dynamic natural system and, as such, must be designed with consideration of natural system influences. Understanding these physical processes and applying appropriate numerical analyses to these processes can help the engineer to build an appropriate overall system that will perform with the desired objective. The primary processes acting on a cap are described in the subsections below. 2.2.1.1 Hydrologic Cycle The purpose of a cap is usually to minimize water infiltration into underlying waste, and sometimes to minimize gas transport to the atmosphere. As shown in Figure 2.1, water originates as precipitation that falls on the cap. Depending on the cap slope, cap soil properties, cap moisture conditions, and the duration and magnitude of precipitation, ponding and water run off can occur. Water that does not run off of the cap is either stored in depressions in the cap surface, or infiltrated into the surface layer of the cap. Water infiltrating into the surface layer of the cap is subject to evapo-transpiration. Rates of evapo-transpiration depend on surface vegetation, soil properties, surface temperatures, soil and air relative humidities, and net solar radiation. The remainder of the precipitation not transformed to run off or evapo-transpiration remains as storage in the cap, or, if the storage capacity of the cap is exceeded, the water percolates through the cap. Contaminant vapors can migrate through caps by advection or diffusion. Advection rates depend on gas-phase permeabilities and pressure gradients across the cap. Variations in barometric pressures can increase contaminant vapor advection to the atmosphere. Vapor diffusion is driven by the gas-phase concentration gradient existing across the cap. Diffusion coefficients depend on soil porosity and water content, as well as contaminant molecular weight. It is often assumed that diffusion at the ground surface occurs across a stagnant surface boundary layer the depth of which depends on surface topography, vegetation, and wind conditions (Thibodeaux, 1981). Water percolation and contaminant transport through the cap can also be altered by human or biointrusion into the cap and other natural events, leading to disparities between probable current and future percolation rates as shown in Figure 2.2. Animal burrows or other passageways through the cap can accelerate the migration of water or contaminant vapors through the system. Natural events such as earthquakes, tornadoes, floods, and melting snow can also be disruptive to the cap. Although a great deal of uncertainty is associated with these events and processes as discussed in Chapter 1, their potential impact and consequence can be significant and should therefore be considered.

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Climate

Transpiration Precipitation Evaporation Run-on

Gas release Storage

Human intrusion/ bio-intrusion

Run-off

Lateral drainage

Waste Percolation/leaching

FIGURE 2.1 Features, events, and processes associated with a long-term cap.

100

Present

40 CFR Part 264.301

Cumulative Probability

80

60

40

Future

20

0 10−13

10−12

10−11

10−10

10−9

10−8

10−7

10−6

Percolation Flux through Cover (cm/s)

FIGURE 2.2 Cumulative probability distribution of water percolation reaching the mill tailings for present and future conditions. (From Ho, C.K. et al., 2001. Sandia National Laboratory Report SAND2001-3032; October.)

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2.2.1.2 Layers and Features In very rare cases, a cap comprises a single soil layer over waste material. Typically however, a cap is the unique combination of soils placed in layers on top of each other and in certain order that create the desired effect. This section briefly outlines the general performance objective of each potential cap layer. •

•

•

•

Ground surface layer — The top few inches of any surface soil may need to be treated as a unique soil region since, due to desiccation and drying effects, this zone generally has a much higher hydraulic conductivity than the soil a few inches below surface. This zone is especially important to include when simulating infiltration through cover systems using numerical models. Vegetation layers — It is common to include a vegetation growth layer that may or may not be part of another cover layer. In many cases, the vegetation can be a key to cap performance, but based on the analysis presented in Section 1.4.1, this should not be assumed. According to energy balance accounting, the sum of actual evaporation and transpiration are always less than the potential evaporation. This means that for near-surface processes, the availability of water limits evapo-transpiration, and water that is not transpired through vegetation is removed through evaporation. In other words, if vegetation were not present, actual evaporation would remove a similar amount of water. The transpiration process becomes important when it is necessary to draw water from deeper beneath the surface, particularly when actual evaporation has significantly diminished at the surface due to drying of soils. Vegetation is also critical for stability purposes on sloped covers, as well as erosion control. Capillary break layers — These layers are generally created with coarse materials next to fine materials because, at a common negative water pressure, two different soils have different water contents. Capillary breaks can be used in caps for various purposes. When placed beneath a compacted layer, the capillary break limits percolation through the compacted material. When placed above a compacted layer, the capillary break limits the evaporative drying of the compacted layer, because water cannot readily be drawn up in its liquid phase through the coarser capillary break layer when it is dry. For this type of cover design, a model that includes coupled vapor flow should be used to assess the impact of vapor flux on barrier layer drying in the event that upward liquid phase flow has shut down. Barrier layers — Barrier layers are generally made of well-compacted, low-permeability fine-grained soils. A barrier layer should not be placed directly at the surface, or it will be subjected to effects such as extreme drying, desiccation, and freeze-thaw. It is common to place

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•

75

a barrier layer over a coarser layer to create a capillary break effect, and then place it beneath a vegetation growth layer. It is not desired to have the root zone of the plant species extend into the barrier layer where damage can occur. While long-term barrier layer performance is unknown and cannot be predicted with precision, the use of dense, well-graded materials for these layers has shown the best resistance to long-term performance deterioration (Wilson, 2002). Storage layers — These layers are generally made of loose well graded materials such that the hydraulic conductivity is sufficient to allow water to infiltrate and subsequently be drawn back out by evaporation and/or roots. The thickness of a storage layer becomes a critical question in its functionality. The cover must be thick enough to keep nearsurface wetting and drying processes from interacting with the waste, and to withstand long-term erosion. If the cover is to limit gas fluxes as well, there must be a zone of continual near-saturation within this layer over time and over prolonged dry periods; either that, or the storage layer must protect a deeper near-saturation barrier layer. Longterm storage layer performance can be affected by coarse material breakdown, which can result in permeability loss.

2.2.2 CURRENT STATE OF PRACTICE PERFORMANCE OF CAPS

FOR

MODELING

Water movement through soils can be thought of as a three-component system consisting of the soil-atmosphere interface, the near-surface unsaturated zone, and the deeper saturated zone. In the past, groundwater modeling has primarily focused on the saturated zone, which creates a discontinuity in the natural system because the unsaturated zone and the soil-atmosphere interface are not represented. Advances in unsaturated soil technology during the past decade have led to the development of routine modeling techniques for saturated and unsaturated soil systems. However, modeling techniques for the third component, involving the detailed evaluation of the flux boundary condition imposed by the atmosphere, are not routinely available. This section discusses some of the available codes that can be used for the predictive modeling of processes associated with cap performance. A summary of the codes considered, and some of the key features and solution techniques are provided in Tables 2.1 and 2.2. Table 2.1 lists several different available software tools and their main solution processes, as well as feature overviews and source availability. Table 2.2 lists the individual program’s solution options and features that are built into the various codes. 2.2.2.1 Water Balance Method The estimation of the amount of water infiltrating through a cap is essentially the estimation of the water balance for the cap. The net percolation through the cap is the remainder from precipitation after run off, surface storage, evapo-transpiration,

1D, Transient FEM

2D, transient and steadystate FEM

VADOSE/W

Process

SoilCover

Software Name

Integrated with program QUAKE/W

Integrated with program SLOPE/W

Supplemental

Enhanced pre and postprocessor included; climate and soils database included; user support included; commercially developed for cover/cap design

Pre- and post-processor included; code unavailable. Freeware

Features/Limitations

Supplemental

Subsequent linear

Coupled, simultaneous, nonlinear

Subsequent

Oxygen flux Pressure, temperature, vapor pressure; can be linked with slope stability software and contaminant transfer software Oxygen or radon diffusion, dissolution, decay Earthquake seismic analysis using VADOSE/W generated pore pressure data Slope stability analysis using VADOSE/W generated pore pressure data

Coupled, Simultaneous, nonlinear

Technique

Pressure, temperature, vapor pressure with pseudo gas

Solved Parameters

TABLE 2.1 Available Software Overview

Full CAD data input and mesh generation; Microsoft certified for XP and lower OS

Text in Excel with dialogues; requires Excel 97 or 2000

User Interface

www.geo-slope.com

www.vadosescience.com

Availability

76 Barrier Systems for Environmental Contaminant Containment & Treatment

1D, quasi 2D, Analytical

1D, transient FEM

2D, Transient and steadystate FDM

1D, 2D, 3D, transient and steady-state IFDM

HELP

UNSAT-H

HYDRUS-2D

TOUGH 2

Subsequent nonlinear

Contaminant transfer

Coupled, Simultaneous, nonlinear

Subsequent linear

Temperature

Pressure, temperature, vapor, gas in porous or fractured media

Nonlinear

Subsequent linear

Temperature (optional) Pressure, with vapor flow

Nonlinear

Analytical

Subsequent nonlinear

Pressure with vapor

Water balance

Contaminant transfer, advection/dispersion, decay, particle tracking

Limited pre- and postprocessor available from independent suppliers. Code available; users can customize

Pre- and post-processor included; CAD mesh generation add-on

Climate and soil database included; not physically based; limited design application; assumes unit gradient Pre- and post-processor available but excluded. Code available

Integrated with program CTRAN/W

Limited CAD and text in editor

CAD and Windows dialogues

Text in editor or Windows dialogues

Text in editor or Windows dialogues

www-esd.lbl.gov/ TOUGH2

www.ussl.ars.usda.gov/ models/hydrus2d.HTM

www.hydrology.pnl.gov/ unsath.asp

www.wes.army.mil/el/ elmodels/helpinfo.html

Modeling of Fluid Transport through Barriers 77

1D steadystate radongas diffusion

RAECOM

Radon-gas concentration and flux through a multi-layer system

Multi-phase, multicomponent heat, mass, gas, air including double porosity flow; can solve contaminant flow as advection/ dispersion or particle tracking

Solved Parameters

Linear

Coupled, simultaneous, nonlinear

Technique

Can automatically optimize layer thickness

Limited pre- and postprocessor with 3D grid generator available from independent sources. Unix or PC based; code included; user can customize; USA only

Features/Limitations

Text entry

Limited CAD with text input

User Interface

RAECOM-cloned calculator available on the web: http://www.antenna.nl/ wise/uranium/ctc.html

www-lanl.gov/EES5/ fehm.html

Availability

Coupled, physical coupling between equations; simultaneous, more than one equation solved at same time (must be coupled); subsequent, more than one equation solved one after the other at each time step; supplemental, data from completed analysis used in separate analysis; linear, material properties not a function of variable being solved; nonlinear, material properties change with variable being solved, so iterations required; analytical, no partial differential equation, one pass solution.

1D, 2D, 3D, transient FEM/FVM

Process

FEHM

Software Name

TABLE 2.1 (continued) Available Software Overview

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Pressure, temperature, vapor pressure with pseudo gas Oxygen flux Pressure, temperature, vapor pressure; can be linked with slope stability software and contaminant transfer software Oxygen or radon diffusion, dissolution, decay Earthquake seismic analysis using VADOSE/W generated pore pressure data Slope stability analysis using VADOSE/W generated pore pressure data Contaminant transfer, advection/dispersion, decay, particle tracking Water balance Pressure with vapor Temperature (optional)

VADOSE/W

HELP

UNSAT-H

Solved Parameters

SoilCover

Software Name

TABLE 2.2 Available Software: Detailed Options

RE RE

A

SE

SE

RE

SE

—

E

SE

E

—

—

FF, CF

FF, CF

Soil Properties

CF

CF

FF

RE

—

Ponding

RP

RE

RE

Run Off

FF

RE

SE

Freezing

RP

RE

RE

Transpiration

RP

RP

RP

Evapor -ation

Internally calculated FF

RP

RP

A

RP

Solution Complexity

Modeling of Fluid Transport through Barriers 79

Pressure, temperature, vapor, gas in porous or fractured media Multi-phase, multi-component heat, mass, gas, air including double porosity flow; can solve contaminant flow as advection/dispersion or particle tracking Radon-gas concentration and flux through a multi-layer system

TOUGH2

FEHM

RAECOM

A

RP

RP

RE RE RE

Solution Complexity

—

SE

—

SE

Evapor -ation

—

—

—

RE

Transpiration

—

—

—

—

Freezing

—

SE

—

SE

Run Off

—

SE

—

—

Ponding

CF

CF

CF

CF

Soil Properties

RP, rigorous physically based with assumptions limited to current understanding of real physical processes; RE, rigorous physically based but with empirical components or built-in limiting assumptions; SE, semi-empirical, equation based but user sets limits or there are limited built-in assumptions; E, empirically based, extreme limiting assumptions and little physical bases for generated data; A, analytically based — no partial differential equations; FF, free-form functions, user can customize; CF, closed-form functions, curve-fit parameters.

Pressure, with vapor flow Temperature Contaminant transfer

Solved Parameters

HYDRUS-2D

Software Name

TABLE 2.2 (continued) Available Software: Detailed Options

80 Barrier Systems for Environmental Contaminant Containment & Treatment

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81

and soil storage are considered. The first method used for water balance calculations was developed by Thornthwaite and Mather (1957). This method was used by Fenn et al. (1975) to analyze leachate generation at municipal solid waste landfills. Typically, the water balance method is based on monthly climatic variables. The monthly infiltration, I (cm), into a cover is given by: I=P–R

(2.1)

where P is precipitation (cm) and R is surface run off (cm). Surface storage was not considered by Fenn et al. (1975). Run off is calculated from precipitation using a run off coefficient, C: R=CP

(2.2)

Fenn et al. (1975) provided values of C for different soil types and slopes, with values ranging from 0.05 for sand with less than a 2% slope, to 0.35 for a steeply sloped (>7%) clay layer. Thornthwaite and Mather (1957) also provided tables for determining potential evapo-transpiration (PET) as a function of mean temperature, heat index, and hours of sunlight. When PET exceeds infiltration, moisture storage in the cap is expected to decrease unless the cap was already dry. PET cannot exceed the water stored in the cap plus the infiltration for the month. When infiltration exceeds PET, evapo-transpiration is equal to PET, and excess infiltration increases the moisture storage in the cap to field capacity. Excess infiltration above the field capacity of the cap percolates through the cap. 2.2.2.2 HELP The hydrologic evaluation of landfill performance (HELP) model was developed by the United States Army Engineer Waterways Experimentation Station for the United States Environmental Protection Agency (USEPA) in 1984. The current version of the model, Version 3, was released in 1993. The HELP model is essentially a water balance model that includes subsurface water routing. It simulates both model cap and liner behavior in a landfill system. The model is referred to as a quasi-two-dimensional model, as it simulates vertical flow in barrier and waste layers (assuming unit hydraulic gradient), and horizontal flow in drainage layers (using an analytical solution of the Boussinesq equation). Calculations are performed on a daily basis, and changes in soil moisture and surface storage are tracked (Peyton and Schroeder, 1993). The HELP model considers both rain and snow infiltration and accounts for interception by vegetation, surface evaporation, and surface storage. Evapo-transpiration is modeled based on a square root of time calculation and the energy available for evaporation. The type and stage of vegetative growth is also considered in evapo-transpiration calculation.

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2.2.2.3 UNSAT-H UNSAT-H (WinUNSAT-H) is a model for calculating water and heat flow in unsaturated media. The model was developed at Pacific Northwest National Laboratory in Richland, Washington, to assess the water dynamics of nearsurface, waste disposal sites. The code is primarily used to predict deep drainage as a function of environmental conditions such as climate, soil type, and vegetation. UNSAT-H is a one-dimensional model that simulates the dynamics processes of infiltration, drainage, redistribution, surface evaporation, and uptake of water from soil by plants. It uses a finite-difference approximation to solve the onedimensional vertical form of Richards’ equation, which governs unsaturated moisture movement. UNSAT-H was designed for use in water balance studies and has capabilities to estimate evaporation resulting from meteorological surface conditions and plant transpiration. The parameters required for each material type are saturated hydraulic conductivity, volumetric moisture content at saturation, irreducible moisture content, air entry head, and inverse pore size distribution index. 2.2.2.4 SoilCover SoilCover is a soil-atmosphere flux model that links the subsurface saturated/ unsaturated groundwater system and the atmosphere above the soil in an attempt to represent the soil-atmosphere continuum. It is a one-dimensional finite element package that models transient conditions. The model uses a physically-based method for predicting the exchange of water and energy between the atmosphere and a soil surface. The theory is based on the well-known principles of Darcy’s and Fick’s Laws that describe the transport of liquid water and water vapor and Fourier’s Law that describes conductive heat flow in the soil profile below the soil-atmosphere boundary. SoilCover predicts the evaporative flux from a saturated or an unsaturated soil surface on the basis of atmospheric conditions, vegetation cover, and soil properties and conditions. The Penman–Wilson formulation is used to compute the actual rate of evaporation from the soil-atmosphere boundary, which is critical to modeling of evapo-transpirative caps (Wilson, 1990; Wilson et al., 1994). The primary features and modeling capabilities of SoilCover are as follows: •

• • • •

Specification of detailed climate data, including minimum and maximum air temperature, net radiation, minimum and maximum relative humidity, and wind speed Specification of reduced climate data, including air temperature, relative humidity, and potential evaporation (wind speed is optional) Multi-layered soil profiles Optional specification of an internal liquid source/sink node Optional specification of oxygen diffusion coefficients for monitoring oxygen flux and the concentration between soil surface and second user-specified node

Modeling of Fluid Transport through Barriers

• • • •

•

83

User-defined or SoilCover-predicted thermal and hydraulic soil property functions Internal adaptive time stepping scheme for daily simulations Relative convergence criteria for suction and temperature applied at every node Output data files providing daily profiles of volumetric and gravimetric water content, degree of saturation, matrix suction, total head, temperature, ice content, hydraulic conductivity, oxygen concentration, and vapor pressure Daily reporting of potential evaporation, surface flux, base flux, total evaporation, total run off, root flux, user-selected internal node flux and user selectable on-screen graphics during program execution showing continuous daily or cumulative fluxes in chart and table format plus daily updates of temperature and degree of saturation profiles

The program user interface occurs in Microsoft Excel™ using dialogue boxes and custom menus, and the solver is a 32-bit Fortran executable file. 2.2.2.5 HYDRUS-2D HYDRUS-2D can be used to simulate two-dimensional water flow, heat transport, and the movement of solutes involved in consecutive first-order decay reactions in variably saturated soils. HYDRUS-2D uses the Richards’ equation for simulating variably saturated flow and Fickian-based convection-dispersion equations for heat and solute transport. The water flow equation incorporates a sink term to account for water uptake by plant roots. The heat transport equations consider transport due to conduction and convection with flowing water. The solute transport equations consider convective-dispersive transport in the liquid phase, as well as diffusion in the gaseous phase. The transport equations also include provisions for nonlinear nonequilibrium reactions between the solid and liquid phases, linear equilibrium reactions between the liquid and gaseous phases, zeroorder production, and two first-order degradation reactions: one independent of other solutes and one that provides coupling between solutes involved in the sequential first-order decay reactions. The user interface includes data pre-processing and graphical presentation of the output results in the Microsoft Windows 95, 98, and NT environments. Data pre-processing involves specification of a flow region of arbitrary continuous shape by means of lines, arcs and splines, discretization of domain boundaries, and subsequent automatic generation of an unstructured finite element mesh. An alternative structured mesh for relatively simple transport domains defined by four boundary lines can also be considered. Graphical presentation of the output results consists of simple two-dimensional x–y graphs, contour and spectral maps, velocity vectors, as well as animation of both contour and spectral maps. Graphs along any cross sections or boundaries can be readily obtained. A small catalog of soil hydraulic properties is also part of the interface.

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2.2.2.6 VADOSE/W VADOSE/W is a commercially developed two-dimensional finite element code that accounts for precipitation; evaporation; snow accumulation/melt/run off; groundwater seepage; freeze-thaw; ground vapor flow; actual transpiration from plants; and gas diffusion, dissociation, and decay. It solves the same primary heat and mass differential equations as the SoilCover model except in two dimensions. The gas diffusion equation is solved at the completion of each time step once water contents and temperatures are known throughout the domain. VADOSE/W uses the Penman–Wilson method (Wilson, 1990; Wilson et al., 1994) method for computing actual evaporation at the soil surface such that actual evaporation is computed as a varying function of potential evaporation dependent on soil pore water pressure and temperature conditions and independent of soil type and drying history. The fully coupled heat and mass equations with vapor flow in VADOSE/W permit the necessary parameters at the soil surface to be available for use in the Penman–Wilson method. VADOSE/W is currently the only numerical two-dimensional cap design model capable of calculating actual evaporation based on first-principle physical relationships, not empirical formulations that are developed for unique soil types, soil moisture conditions, or climate parameters. VADOSE/W can be used wherever accurate surface boundary conditions are required. Typical applications include designing single or multi-layered soil covers over mine waste and municipal landfill disposal sites; obtaining climatecontrolled soil pore pressures on natural slopes or man-made covered slopes for use in stability analysis; and determining infiltration and evaporation as well as plant transpiration from agricultural irrigation projects. VADOSE/W comes with a built-in soil property database as well as full-year detailed climate data for over 40 sites worldwide. Climate data can be easily scaled to suite specific conditions or the user can input specific climate data. 2.2.2.7 TOUGH2 Transport of unsaturated groundwater and heat (TOUGH2) is a multi-dimensional numerical simulator that simulates the transport of air, water, and heat in porous and fractured media (Pruess, 1991). Mass and energy balances for air, water, and heat are solved simultaneously in TOUGH2 using the integrated finite difference method. The integrated finite difference formulation of TOUGH2 allows for the construction of nonuniform elements that can be used to represent irregular domains. The development of this code was originally motivated by problems involving heat-driven flow, although this code is now used in a wide range of problems involving unsaturated flow. For example, Ho and Webb (1998) used TOUGH2 to simulate the effects of heterogeneities on capillary barrier performance in landfill caps. A multi-phase approach was used to describe the movement of gaseous and liquid phases, their transport of latent and sensible heat, and phase transitions between liquid and vapor. Water vapor and air, which generally

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constitute the gas phase, are tracked and simulated separately. Liquid- and gaseous-phase flow can occur under pressure, viscous, and gravity forces according to Darcy’s Law, and interference between the phases is represented through relative permeability functions. A number of variations of the TOUGH2 code have been developed to include additional capabilities of modeling additional species, modeling fluctuating atmospheric boundary conditions, and inverse modeling. The model parameters, initial conditions, and boundary conditions are typically entered into the code through text entry into a file that is read by the code. Post-processing within TOUGH2 is limited and is typically performed by third-party software. The source code for TOUGH2, written in standard FORTRAN77, is available from the United States Department of Energy (USDOE) Office of Scientific and Technical Information Energy Science and Technology Software Center in Oak Ridge, Tennessee. 2.2.2.8 FEHM Finite element heat and mass (FEHM) is a numerical simulation code for subsurface transport processes (Zyvoloski et al., 1997). It models three-dimensional (3-D), time-dependent, multi-phase, multi-component, nonisothermal, reactive flow through porous and fractured media. It can represent complex 3-D geologic media and structures and their effects on subsurface flow and transport. FEHM uses a finite-element formulation to solve the governing equations of heat and mass transport. Simulation of additional species (e.g., organics, radionuclides) can be performed simultaneously with the solution of heat, air, and water transport. In addition, a particle-tracking module is also included that provides a more computationally efficient procedure to the solution of contaminant transport. Millions of particles can be simulated that represent the effects of advection, diffusion, dispersion, and fracture-matrix interactions on transport. The entry of model parameters, boundary conditions, and initial conditions into FEHM is performed through the creation of text files that are read by the code. FEHM does not perform any direct post-processing of the data for visualization, but the user has the option to output the data in formats that can be read by third-party software. FEHM can be obtained free of charge in the United States for most applications via the web site http://ees-www.lanl.gov/EES5/fehm/. 2.2.2.9 RAECOM Radiation attenuation effectiveness and cover optimization with moisture effects (RAECOM) is a code that simulates steady, one-dimensional radon gas diffusion through a multi-layer cover (Rogers et al., 1984). Material properties, dimensions, and diffusion coefficients can vary among the different layers, and activity and emanation coefficients can be specified. An online calculator that provides the same functional calculations as RAECOM is provided at the following web site: http://www.antenna.nl/wise/uranium/ctc.html.

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2.2.3 MODELING LIMITATIONS AND RESEARCH NEEDS FOR CAPS There are many limitations to modeling the performance of caps, including data needs; lack of quality assurance and control of models and model usage; and lack of verification, validation, and calibration. This section discusses these limitations and the associated research needs, as well as the role of modeling in designing caps. 2.2.3.1 Role of Modeling There is often a misperception of what a model can and cannot do. It is critical to get all stakeholders to understand and agree on the objectives of using the model. Many believe that if the predictions arise from a sophisticated computer code that incorporates the fundamental physics as it is currently understood, the answer must be correct. In fact, at best, the model output is a scientifically defensible, although not necessarily accurate, prediction of system behavior. This belief in modeling leads to the development and use of more sophisticated models that advance the state of the science, but do not necessarily provide more defensible predictions. In modeling cover system performance, the objective is to provide a measure of the ability of the cover to prevent water infiltration to the waste zone over long periods of time (i.e., tens of years to hundreds of years). It is not possible to precisely predict infiltration over long time periods due to the large number of uncontrolled variables (e.g., weather conditions, burrowing animals, root growth), heterogeneities in the physical properties of the system, and lack of precise understanding of the flow physics (e.g., hysteresis effects and soil characteristic curves are empirical relationships based on data). Therefore, the modeling approach should aim to demonstrate that the cover system limits infiltration to an acceptable level over a range of potential conditions. This lends itself naturally, although not exclusively, to probabilistic modeling. 2.2.3.2 Data Needs The data required for modeling cap behavior depends on the model being used. The simplest models such as the water balance method of Thornthwaite and Mather (1957) and Fenn et al. (1975) require monthly climatic data such as precipitation, mean temperature, heat index, and hours of sunlight. Soil types and cap slopes are also required to allow estimation of run off. More comprehensive water balance models such as the HELP model allow for more complex cap configurations and, thus, require specification of the different cap layers. The HELP model also simulates the surface processes in greater detail and therefore requires additional climatic data and soil properties. The climate data input to the HELP model include daily precipitation, daily mean temperature, daily solar evaporation, maximum leaf area index, growing season, and evaporative zone depth (Peyton and Schroeder, 1993). The soil properties

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required include porosity, field capacity, wilting point, hydraulic conductivity, and the United States Soil Conservation Society curve number for the surface layer. The HELP model contains a list of default soil properties, and a database of climate data for a large number of North American cities (Peyton and Schroeder, 1993). Other more rigorous models such as UNSAT-H, HYDRUS-2D, and VADOSE/W simulate unsaturated water flow by solving Richards’ equation. Simulation of unsaturated water flow with Richards’ equation requires parameter specification of the soil characteristic curves for hydraulic conductivity and moisture content as a function of suction pressure, typically represented by empirical relationships such as those developed by van Genuchten (1980) or Fredlund and Xing (1994). These parameters are required for each unique soil layer in the cover system. Saturated hydraulic conductivity and porosity are also required for each material. Other parameters, such as the air entry pressure head, residual saturation value, vertical and horizontal saturated conductivity, and anisotropy parameters may be required depending on the model. Some of the models (i.e., TOUGH2, FEHM, VADOSE/W, HYDRUS-2D) also solve the heat transport equation to track evaporation and water vapor transport. Therefore, these models require additional information regarding soil properties related to heat transport for the gas and liquid phase. Parameters that are typically needed include thermal conductivity, specific heat capacity, latent heat of vaporization, surface tension, and parameters that describe the interactions between gas and liquids under flowing conditions (e.g., relative permeability). 2.2.3.3 Code Quality Assurance and Quality Control Numerical models are nothing more than tools that solve mathematical equations that cannot be solved with conventional techniques. Typical geotechnical computer models have thousands of lines of code; it is easy to inadvertently introduce mistakes that can cause unpredictable behavior. When source code is made available to end users to change and compile, unique versions of the code that only solve specific problems commonly result, and the original verification of the original model may not apply to the slightly changed version. For this reason, regulatory authorities should consider developing a standard set of benchmark tests that model developers can use to verify and validate their codes. If small changes to the code are made, all benchmark tests must be resolved to ensure that no undesirable errors have been introduced. Benchmark testing would include solving some simple steady-state and transient seepage examples using fixed material properties where known solutions for the equation exist to validate the numerical solution of the code under the most basic conditions. More advanced benchmark tests should be available where individual theoretical components of the models could be tested in isolation from other factors (e.g., actual evaporation can be computed and compared against rigorously controlled laboratory experiments). All input data, including material properties, would be listed in the

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benchmark test documentation as would the required results. If the new model cannot perform the basic benchmark tests, it is not acceptable for use in field design. A final point to consider is the establishment of a group of individuals who can assemble the benchmark tests and can review and update the tests as new and more advanced physics are introduced. 2.2.3.4 Verification, Validation, and Calibration The verification, validation, and calibration of numerical models are key components in the modeling process and are often the most poorly implemented and misunderstood. The key questions to ask when looking at models are what equations are being solved, what assumptions have been applied to the equations, and how are the equations being solved? For example, just because a model computes evaporation does not mean that it does so based on sound physical relationships or that, if it is based on sound physics, the equations are solved properly. After a model user has an understanding of the theory and physics incorporated into a numerical code, they should satisfy themselves that the numerical solution for that set of equations is correct. This is the verification stage of the modeling process and is usually carried out by the model developer. Verification has nothing to do with site data and everything to do with correct solution of the mathematics. Verification and validation go together; where verification addresses solution techniques and validation is the process of obtaining confidence that the model applies to real situations represented by the theoretical formulations applied in the model. Validation tests if the model theories actually apply to specific real observations — whether they are laboratory experiments or field studies. It is absolutely critical to validate a model based on known closed-form solutions, known physical observations, and laboratory tests where all parameters can be controlled and adjusted individually. Models cannot be validated using field data alone because there is no direct control over or monitoring of all major model parameters. For example, if a model is validated using site data where precipitation, run off, change in water storage, and bottom drain fluxes are measured but actual surface evaporation and transpiration are not measured, then the source of discrepancies between measured and computed results cannot be determined. There could be error in the model estimate of evaporation, or there could be error in the field measurement of particular parameters. The most appropriate use for field data in modeling is calibration of a previously validated model. Calibration of a model involves making small adjustments to measured or predicted model input parameters to obtain better matches between measured and computed results data at more than one instance in time. In the ideal case, once a model is calibrated for a site, it will give reliable results for the same site if external parameters at that site change. For example, if precipitation is doubled or halved, the change in soil responses can be predicted using a calibrated model for that site only. The problem with calibration is that it only works if the model

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physics truly represent the real physical processes in the ground. If the model is rigorous enough and calibrated properly, then all physical processes measured in the ground and predicted by the model should match. Calibration of nonrigorous models such as HELP must be interpreted with caution because, in many cases, the calibration can be achieved by adjusting only a single model parameter. When this is done, the predicted and measured data only match for a single instance in time. There is no guarantee that the adjustments made to the model to fit measured data represent the true physical properties in the field. It may be possible to calibrate HELP to match measured percolation data, but it is very unlikely that parameters such as the temperature, water pressure, water stored in the soil, and the root depth match field conditions at the same instance or at some other instance in time.

2.2.4 UNRESOLVED MODELING CHALLENGES There are many challenges facing model developer users. These challenges include the difficulties in modeling systems with time-varying properties and processes, the problems encountered in modeling infiltration at arid sites, and the role of heterogeneities in modeling. 2.2.4.1 Time-Varying Material Properties and Processes A major challenge facing modelers of cap performance is the time-varying nature of climate, vegetation, and soil properties. All models of cap performance require extensive climatic data, including precipitation, temperature, and solar radiation to determine infiltration and evapo-transpiration. Although historic data are available for many locations, methods for estimating extreme values of these variables are not well developed. Physical deterioration of caps is commonplace, as they are easily impacted by surface and climate processes. Changes in vegetation have an effect on run off generation and evapo-transpiration. Establishment of shrubs and trees on caps can lead to cap penetration by roots, creating high conductivity pathways for water infiltration. Similarly, burrowing animals can create high conductivity conduits through a cap. Erosion and subsidence can seriously impact cap performance. The cracking of clay layers in caps due to freeze-thaw cycles or desiccation (e.g., Albrecht and Benson, 2001) can significantly increase the effective hydraulic conductivity of caps, leading to greatly increased water infiltration or vapor escape. Albrecht and Benson (2001) found that clay hydraulic conductivities increased by factors as high as 500 upon desiccation. Subsequent resaturation did not lead to complete healing of dessication-induced cracks. Although cap modeling can predict soil moisture levels in the cap, reliable models for changes in cap hydraulic properties due to dessication or freeze-thaw have not been developed. Many caps are expected to provide environmental protection for decades or centuries. Studies of cap stability and soil and geomembrane property stability

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over these long periods of time have not been conducted. In addition, accurate predictions of long-term climate changes and the occurrence and impact of extreme events (e.g., earthquakes, floods, hurricanes, tornadoes) are not possible. 2.2.4.2 Infiltration at Arid Sites Arid sites are characterized by levels of precipitation that are almost balanced by loss mechanisms such as evaporation, transpiration, and run off. For water balance models, the recharge is estimated by subtracting the losses from the predicted production. Thus, small errors in either estimate can lead to large errors in recharge estimates. A second issue at arid sites is that evapo-transpiration models used in the water balance models for disposal cells that are sparsely vegetated are not accurate and tend to overpredict evapo-transpiration and underpredict recharge. The use of physically based evapo-transpiration models (e.g., SoilCover, VADOSE/W) that are formulated to shut down actual evaporation as ground surfaces dry greatly improves infiltration estimates at arid sites. 2.2.4.3 Role of Heterogeneities The most commonly used models for estimating flow through cover systems assume uniform hydraulic and thermal properties for each layer of the cover system. In practice, local heterogeneities are likely to be responsible for a large portion of the flow through cover systems. The heterogeneities can arise naturally due to improper construction (e.g., leaks at seams, improper compaction) or evolve in time (Section 2.3.5.1). Currently, the capability to predict the occurrence of local heterogeneities and their impact on flow does not exist. For example, desiccation cracking is known to occur in clay barriers and leads to increased flow. However, the capability to predict crack formation; the density of cracks; the changes in hydraulic conductivity that occur due to cracking and subsequently rewetting; and, more importantly, the change in flow through the layer does not exist. For field performance, localized failure will often control infiltration through the cover system. This leads to the need to develop procedures to adequately represent these local failures using gross average properties for the layers.

2.3 PRBS In recent years, PRBs have evolved from the realm of an experimental methodology to standard practice for containment and treatment of a variety of contaminants in groundwater. Like any remedial technology, the decision to use PRBs is conditioned by the characteristics of the natural system, target contaminants, and treatment objectives. More than 60 sites have implemented this technology in the last few years to treat chlorinated solvents, fuel hydrocarbons, and various inorganic contaminants in groundwater. As with any technology used to treat or

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extract contaminants in the subsurface, successful implementation is contingent on effective site characterization, design, and construction. Recent studies on long-term PRB performance at a number of sites emphasize the following key issues for successful use of PRBs: •

•

•

Performing adequate site characterization on the scale of the PRB — Site characterization approaches, typical of Resource Conservation and Recovery Act (RCRA) facility investigations (RFIs), are not adequate. Performing additional localized characterization of the plume distribution in three spatial dimensions and with time, understanding the local hydrogeology, and knowing the site geochemistry is required. Understanding site hydrology to achieve successful implementation — PRBs must be located correctly to intercept the plume because once located in the subsurface, they cannot be moved. It is therefore imperative that the PRB captures the plume at the present time and in the future allowing for variations in flow direction, velocity, and concentrations of contaminants over time. Developing contingency plans for failure to meet design objectives — It is surprising that site owners and regulators often fail to explicitly develop contingency plans. Contingency plan development requires specification of design criteria and performance objectives and determination of what constitutes a failure in order to clearly trigger contingency plan activation.

2.3.1 FEATURES, EVENTS, AND PROCESSES AFFECTING PERFORMANCE OF PRBS Design of PRBs requires consideration of groundwater hydraulics, geochemical processes, and reaction kinetics and the interaction between these processes. 2.3.1.1 Groundwater Hydraulics As with any groundwater remediation technology, an understanding of the direction and rate of groundwater flow spatially and temporally is critically important for successful design. Groundwater hydraulics are particularly crucial for PRBs because the treatment system is immovable and passive yet must intercept the contaminant plume for effective treatment. Groundwater flow is well understood, and groundwater modeling is a mature technology (e.g., Bear and Verruijt, 1987; Anderson and Woessner, 1992). Many computer models are available in the public and commercial domains that can be utilized to perform quantitative predictions of transient 3-D groundwater flow given appropriate input. The key difficulty in modeling groundwater hydraulics is that critical variables that control groundwater flow typically exhibit a high degree of variability spatially and temporally. These variables are difficult to

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characterize with precision and sufficient resolution given physical and budgetary constraints. To assess PRB system performance, information is needed on groundwater velocities through and near the planned PRB. On the simplest level, these values can be estimated from observed hydraulic gradients and measured or estimated hydraulic conductivities. Alternatively, groundwater velocities can be determined with a numerical groundwater flow model based on estimated hydraulic property distributions and hydrologic boundary conditions (i.e., water levels and/or fluxes on model boundaries and recharge and extraction rates), which can vary temporally. In many cases, it is important to consider the effects of temporal changes in flow direction and velocity due to variations in recharge, pumping of adjacent wells, or other disturbances. It is not uncommon to observe changes in flow direction on the order of 30˚ or more over time due to transient boundary conditions. Furthermore, the PRB permeability itself can change markedly over time in some situations (e.g., due to biological fouling or chemical precipitation in or near the PRB), which can substantially impact the hydraulic regime. Understanding site stratigraphy and lithology is crucial to understanding and predicting groundwater hydraulics. If a low permeability layer exists at the site, the PRB can be keyed into this layer. If one does not exist, then a hanging wall design can be employed, but uncertainty regarding plume capture may increase. If the site has low permeability layers through which the PRB must be constructed, care must be taken during construction to avoid smearing of such layers, which could impact hydraulic contact between the formation and reactive media. A thorough understanding of site stratigraphy is important when choosing a particular construction method. For example, the use of sheet piling to construct a reactive gate may not be a good choice where low permeability layers exist because of smearing potential. 2.3.1.2 Geochemical Processes The nature and extent of geochemical processes occurring within a PRB to a large degree determine the long-term treatment performance of the barrier. The details of these processes are site specific and associated with chemical, physical, and biological factors such as the following: • • • • •

Reactive media type (e.g., zero-valent iron (ZVI), other metals, zeolite, organic materials) Influent groundwater chemistry (e.g., pH; amounts of cations, anions, and target contaminants) Microbiological environment within and around the PRB Physical conditions (e.g., temperature) The 3-D characteristics of groundwater flow within and near the PRB

There are several good sources that provide information about pilot and fullscale PRB installations worldwide. Although new PRBs continue to be deployed,

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summaries provided by the Air Force Research Laboratory (AFRL, 2000) and on the Remediation Technologies Development Forum (RTDF) web site (http://www.rtdf.org/public/permbarr/prbsumms/) identify more than 50 PRBs that have been installed. Of these, the vast majority (approximately 85%) use ZVI as the reactive medium. Other types of reactive media that have been investigated include other metallic materials (Gillham and O’Hannesin, 1992; Korte et al., 1995; Muftikian et al., 1995; Orth and McKenzie, 1995; Bostick et al., 1996; Hayes and Marcus, 1997), zeolite (Bowman et al., 2001; Rabideau and Van Benschoten, 2002), various organic materials (Benner et al., 1997), apatite (Conca et al., 2000; Fuller et al., 2002), and sodium dithionite injected as a solution (Fruchter et al., 1997). The AFRL (2000) summarizes different PRB media that have been investigated. The AFRL (2000) and the RTDF web site also document the range of contaminants that are being treated by PRBs. Chlorinated solvents such as trichloroethylene (TCE) and perchloroethylene (PCE) are the dominant target contaminants, but others include metals and radionuclides [e.g., Cr(VI), U(VI), Tc(VII)], other inorganics (e.g., NO3–, SO42–), and other organics (e.g., pesticides, toluene). Because of the dominance of ZVI as a reactive medium in PRBs, the following discussion focuses exclusively on geochemical processes occurring within it. ZVI functions as a redox medium and treats contaminants by chemical reduction. At the same time, the iron is sacrificially oxidized progressively from Fe(0) to Fe2+ and, finally, Fe3+. The oxidized species of iron potentially can react with other components in the groundwater to precipitate a variety of amorphous and crystalline phases as described below. Table 2.3 lists secondary phases that reportedly have been formed by reactions occurring in ZVI PRBs. The reaction of groundwater with ZVI causes several major compositional changes that drive the formation of these reaction products. ZVI begins to dissolve according to the following reactions: 2Fe0 + 2H2O + O2 (aq) = 2Fe2+ + 4OH– Fe0 + 2H2O = Fe2+ + H2 (aq) + 2OH– The first reaction involves the scavenging of dissolved oxygen by ZVI and is known to be a fast reaction because column and field studies show the complete absence of dissolved oxygen within a few centimeters of the influent face of a PRB. The second reaction prevails once the oxygen is gone and is slower. Both reactions result in a significant decrease in redox potential and a dramatic rise in pH, both of which are observed in typical ZVI PRBs. The magnitude of change in pH depends on the detailed chemistry of the influent groundwater, its buffering capacity, and the rate of groundwater flow through the barrier. For example, high alkalinity groundwater is more resistant to a change in pH. However, the large available mass of ZVI in PRBs tends to overwhelm any redox buffering capacity of the groundwater.

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TABLE 2.3 Examples of Precipitated Minerals Found in Fe(0) FieldInstalled PRBs and Column Studies Mineral Precipitate Group Iron oxides and oxyhydroxides

Iron sulfides Carbonates

Green Rusts

Minerals Goethite (α-FeOOH) Akaganeite (β-FeOOH) Lepidocrocite (γ-FeOOH) (Maghemite (Fe2O3)) Magnetite (Fe3O4) Amorphous iron oxyhydroxides Mackinawite (Fe9S8) Amorphous ferrous sulfide (FeS) Aragonite (CaCO3, orthorhombic) Calcite (CaCO3, hexagonal) Siderite (FeCO3) GR-I (CO32–) (Fe42+Fe23+(OH)12)(CO3 ⋅2H2O) GR-I (Cl–) (Fe32+Fe3+(OH)8Cl) GR-II (SO42–) (Fe42+Fe23+(OH)12)(SO4⋅2H2O)

Source: Liang, L., Sullivan, A.B., West, O.R., Kamolpornwijit, W. and Moline, G.R., 2003. Predicting the precipitation of mineral phases in permeable reactive barriers. Environ. Eng. Sciences. Vol 20(6): p. 635.

The oxidation of ZVI (and associated decrease in groundwater redox potential) and the dramatic pH rise are the two principal factors that result in the formation of new solid phases, many of which are iron bearing (Table 2.3). Some of these phases that contain either Fe2+ (e.g., amorphous ferrous oxyhydroxides, FeS, FeCO3) or mixed Fe2+ and Fe3+ (e.g., Fe3O4, green rust) also are effective reducing agents for metals, radionuclides, and organics in groundwater. Consequently, the formation of these reduced iron phases does not necessarily significantly diminish the reactivity of the barrier media. However, not all phases formed in a PRB are iron-bearing. For example, the increase in pH can also lead to precipitation of various carbonate minerals (e.g., calcite, aragonite) if the influent water has sufficient amounts of dissolved alkalinity and calcium. The mix of solid phases formed and their order of precipitation depend on influent groundwater chemistry, the complex interplay of changing redox potential and pH in the system as ZVI dissolves, reaction rates, factors affecting the nucleation of phases, and groundwater flow rate. The ability to predict these reactions and estimate their impact on PRB performance is discussed in Section 2.4.4. One concern associated with secondary mineral formation in PRBs is that these phases passivate the ZVI media, decreasing its reactivity and ability to treat contaminated groundwater. Farrell et al. (2000) reported an example of ZVI passivation with results of long-term column experiments in which they observed an over six-fold decrease in the reactivity of ZVI to TCE in the two-year experiment.

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TABLE 2.4 Groundwater Chemistry of Two Different PRB Sites and the Secondary Phases Observed in Each Concentration (mg/L) Chemical Constituent

Canadian Forces Base Borden

Na K Ca Mg Total Fe Cl SO4 SiO2 NO3 Alkalinity (as CaCO3) pH (unitless) Eh (mV) Dissolved oxygen

4 0.4 55 4 <0.5 3 5–10 Not available Not available 158 7.9 300 2.5-5

8.9 3.6 361 20.5 0.02 55 47 3.8 904 220 6.8 Not available Not available

Secondary minerals observed:

Traces of iron oxides CaCO3 FeCO3 (After four years of operation; no cementation; mineralization confined to within several millimeters of influent face of the PRB)

CaCO3 (aragonite) Fe2(OH)2CO3 FeCO3 Goethite Maghemite Amorphous iron oxide Green rust Mackinawite (Iron media cemented extensively at influent face)

USDOE Y-12 Plant

The authors found that the degree of passivation was related to the adhering ability of secondary minerals and not the overall mass of these phases formed. A number of PRBs have been cored and the media examined to understand the formation of secondary minerals (e.g., Puls et al., 1999a; Vogan et al., 1999; Phillips et al., 2000; Roh et al., 2000). Typically, cores are obtained by angle drilling through the vertical influent face of the barrier to provide a cross section extending into the PRB interior, capturing the precipitation that is expected to be the most significant at the sediment–ZVI interface. Analytical methods such as X-ray diffraction (XRD) and scanning electron microscopy (SEM) typically are used to examine the solid phases that have formed. Table 2.4 illustrates differences in groundwater chemistry and resultant secondary minerals observed in PRBs at the Canadian Forces Base Borden in Ontario, Canada (O’Hannesin and Gillham, 1998) and the USDOE Y-12 plant in Oak Ridge, Tennessee (Phillips et al., 2000). The low dissolved solids groundwater at the Borden site has resulted in little formation of new solid phases over a period of four years, and most precipitation

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8

9

10

11

2 F

1

0

21

22

23

24

25

2 26

2

FIGURE 2.3 Section of cemented core from a PRB at the USDOE Y-12 plant in Oak Ridge, Tennessee.

appears to be restricted to a very thin zone at the influent face of the PRB. In contrast, the highly mineralized water from the Y-12 plant resulted in much more extensive formation of secondary phases, illustrated by the cementation of reactive media (Figure 2.3). The presence of NO3– at high concentrations in the Y-12 plant groundwater is an important factor in determining the degree of reaction occurring in this PRB because NO3– is readily reduced to NH3 as iron is oxidized and, therefore, is very corrosive to ZVI. In terms of groundwater treatment, the geochemical reactions between ZVI and the target contaminants are of primary importance within PRBs. Currently, most PRBs are deployed to treat groundwater contaminated with chlorinated solvents such as TCE, PCE, and their daughter products. A discussion of several possible degradation reaction pathways for TCE is provided in AFRL (2000). The following reaction illustrates the overall reductive dechlorination process for TCE: 3Fe0 + C2HCl3 + 3H+ = 3Fe2+ + C2H4 + 3Cl– As noted in AFRL (2000), there may be a number of reaction pathways resulting in a variety of potential intermediates, but experimental and field studies indicate that the net reaction is one of iron oxidation coupled with reductive dechlorination, leading to the production of dissolved ethene (and ethane) and chloride.

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PRBs with ZVI also can be used to treat groundwater contaminated with some redox-sensitive toxic metals. For example, dissolved species such as hexavalent chromium, pertechnetate, and uranyl ions are known to react with ZVI. Examples that conceptually illustrate these reactions are as follows: Fe0 + 6H+ + CrO42– = Fe3+ + Cr(OH)2+ + 2H2O Fe0 +4H+ + TcO4– = Fe3+ + TcO2 + 2H2O 2Fe0 + 3UO22+ = 2Fe3+ + 3UO2 The reduction of these metals tends to make them less soluble and less mobile than the oxidized forms. Because these contaminants generally are present in such low concentrations in groundwater, it has not been possible to identify specific solid phases where they are located within PRBs. For example, Phillips et al. (2000) did not observe uranium-bearing phases at the Y-12 PRB. However, Fiedor et al. (1998), and Gu et al. (1998, 2002a) were able to confirm that U(VI) readily reduced to U(IV) in laboratory experiments with ZVI. Gu et al. (1998) also confirmed that precipitation, not sorption, was the overwhelmingly dominant process for immobilizing uranium. For the PRB in Elizabeth City, North Carolina, Puls et al. (1999b) report that the chromate contaminant in groundwater was reduced to the chromic (Cr3+) form in an insoluble mixed Cr–Fe hydroxide, although that assumption is based on the sharp decrease in chromium concentrations within the PRB rather than characterization of specific chromium-bearing phases. Based on their work at this PRB, Mayer et al. (2001) also assert that chromic hydroxide is the likely Cr(III)-bearing phase formed. There is no doubt that ZVI reduces these metals, but whether they are immobilized in the form of a separate reduced solid state, sorbed in phases such as iron oxyhydroxides, coprecipitated with other metals, or a combination of all of these processes has not been thoroughly studied. The final geochemical process deserving consideration is related to the potential for contaminant remobilization from an aging PRB. For contaminants such as metals and radionuclides where sorption and/or precipitation associated with reduction is the dominant process occurring, the contaminants can be released eventually through ion exchange, desorption, reoxidation, or colloidal transport. Beyond recognition of these possibilities, little formal study of this potential has been performed. Of more immediate concern, however, is that some regulatory agencies may insist on eventual excavation and removal of reactive media when precipitation and/or sorption are the dominant processes of contaminant sequestration. Currently, there is no information concerning the risk associated either with leaving the PRB in the ground or excavating it. Considering the cost associated with excavating, transporting, and disposing of spent reactive media, this deserves further investigation.

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2.3.1.3 Reaction Kinetics Reaction kinetics must be considered for chemical reactions occurring within PRBs. From a design perspective, the target contaminants (and any toxic daughter products) must have adequate residence time within the barrier to react sufficiently so that effluent concentrations meet design expectations at the downgradient point of compliance (POC). Typical values of half-lives for common organic contaminants with commercial iron tend to range from less than one to approximately 50 hours, depending on the contaminant and the source of iron used. Tabulated summaries of measured half-lives for many compounds are given by Gillham (1996) and AFRL (2000); however, in the design phase of a PRB, site-specific half-lives of target contaminants usually are determined experimentally. Residence times are also partially dependent on the architecture of the groundwater flow system within the PRB. Flow heterogeneities (e.g., preferential pathways) generally exist and can permit target contaminants to migrate through the PRB more rapidly than designed, resulting in inadequate concentration reduction. In addition, ZVI corrosion reactions and precipitation of secondary phases within a PRB can lead to progressive clogging of the media, resulting in localized flow diversion. Tracer tests have been conducted at several PRBs and illustrate the heterogeneous nature of groundwater flow that exists (e.g., Battelle, 1998). Although the impacts of heterogeneities on groundwater flow and contaminant residence times in PRBs have received only limited attention, Benner et al. (2001) modeled heterogeneous aquifer-barrier systems and provided some insights on how the effects on preferential pathways and residence time can be minimized.

2.3.2 IMPACTS

ON

DOWNGRADIENT BIODEGRADATION PROCESSES

At many sites, the rate of natural biodegradation is not sufficient to meet remedial goals, and intervention is required in the form of additional treatment to accelerate or enhance the degradation rate. ZVI treatment and natural biodegradation are compatible treatment processes for many chlorinated solvents. Both are reductive processes that follow first-order reaction kinetics, and both involve the generation of partially dechlorinated daughter products with reaction rates that are typically slower than those of the parent compound. Under appropriate circumstances, the two treatment processes may be synergistic in that the ZVI treatment can enhance or accelerate downgradient biodegradation rates by creating geochemical conditions more suitable to anaerobic bacterial metabolism. A variety of mechanisms may be operative that stimulate biological processes. 2.3.2.1 Enhancement of Geochemical Conditions Conducive to Anaerobic Biodegradation ZVI PRBs remove any dissolved oxygen or nitrates present in the upgradient groundwater. The removal of these inorganic electron acceptors lowers the oxidation/reduction potential of the groundwater, creating more favorable conditions

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for reductive biological processes. In addition, many of the organisms involved in chlorinated solvent biodegradation are obligate anaerobes that cannot survive in the presence of oxygen. 2.3.2.2 Overall Contaminant Concentration Reduction In cases where a PRB does not achieve complete treatment of the parent compounds or reaction daughter products, partial treatment reduces the total loading of chlorinated contaminants in the downgradient aquifer. Such incomplete treatment can be helpful to the downgradient biological processes in a number of ways. In aquifers that are electron donor limited, the PRB can bring down the concentration of chlorinated solvents to a point where they can be fully dechlorinated by the available electron donor supply. Some chlorinated compounds are known to inhibit reductive dechlorination processes when present above a threshold concentration. An example of this is the observed inhibitory effect of chloroform (CF) on the reductive dechlorination of chlorinated ethenes (Maymo-Gatell et al., 2001). This effect has been observed at CF concentrations above a few parts per million. 1,1,1-trichloroethane (1,1,1-TCA) and carbon tetrachloride have also been observed to inhibit methanogenesis and the dechlorination of chloroethenes, although not a severely as CF (Adamson and Parkin, 2000). The PRB can create more favorable conditions for dechlorination by reducing the concentration of such compounds to below the level where they are inhibitory. A third beneficial effect of incomplete treatment is that the effects of competing electron acceptors can be reduced or eliminated. When mixtures of chlorinated solvents are present in groundwater, the dechlorinating bacteria preferentially use the electron acceptors that yield the most energy for their metabolism. The metabolic energy available from a given half-reaction is expressed as the Gibbs free energy of reaction, in units of kilojoules per mole. The greater the Gibbs free energy available from dechlorinating a given compound, the more likely it is that the dechlorinating bacteria will preferentially use that compound as an electron acceptor. This effect can be significant in plumes with mixtures of different chlorinated compounds. 2.3.2.3 Production of Hydrogen Hydrogen gas is produced in PRBs as a product of ZVI corrosion. Hydrogen serves as the ultimate electron donor in the biological reductive dechlorination of chlorinated solvents and is known to stimulate reductive biological processes. The production of hydrogen may explain the “halo” of enhanced biological activity observed in the immediate vicinity of ZVI PRBs, both upgradient and downgradient (Gu et al., 2002b). The presence of dissolved hydrogen under strongly reducing conditions can stimulate methanogenesis, as well as biological reduction of chlorinated ethenes. Although the produced hydrogen is not expected to persist far downgradient of the PRB, the enhanced biological activity in this

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hydrogen-rich zone can have effects that extend further. Dechlorinating organisms, notably Dehalococcoides ethenogenes, are known to be mobile in groundwater systems and can be carried downgradient with the groundwater flow (Ellis et al., 2000). As such, the hydrogen-rich zone immediately downgradient of the PRB can act as a robust source of dechlorinating organisms for the downgradient plume. However, increased microbial activity can result in PRB biofouling (Gu et al., 2002b). 2.3.2.4 Electron Donor Production The ZVI reaction products from chlorinated solvent treatment include fully and partially dechlorinated simple organic compounds that can serve as electron donors for downgradient biological dechlorination processes. Examples include the production of formate from carbon tetrachloride and ethene from PCE and TCE. Similarly, the treatment of 1,1,1-TCA with ZVI yields a significant amount of ethane, with lesser amounts of ethene, cis-2-butene, and 2-butyne (Fennelly and Roberts, 1998). Typically, the daughter products of chlorinated solvents treated with ZVI are partially dechlorinated and therefore less highly oxidized than the parent compound. Some of these partially reduced daughter products can be used as electron donors in downgradient biodegradation processes, particularly in aquifers that are not strongly reduced. An example is the conversion of carbon tetrachloride to dichloromethane (DCM) in a PRB. DCM is known to biodegrade rapidly under both aerobic and anaerobic conditions. Under aerobic conditions, DCM can be biologically oxidized to carbon dioxide and hydrochloric acid. Under anaerobic conditions, DCM can be converted to acetate by fermentation (Freedman and Gossett, 1991). The generated acetate can then serve as an electron donor. Other examples of partially dechlorinated compounds that can serve as electron donors are cis-1,2-dichloroethylene (cis-1,2-DCE) and vinyl chloride, the daughter products of PCE and TCE (Bradley and Chapelle, 2000), and 1,1-DCE, the daughter product of 1,1,1-TCA. In aerobic aquifers, the biological transformation of fully chlorinated compounds such as PCE or carbon tetrachloride does not occur. Under such conditions, a PRB can convert these compounds into lesser chlorinated species, which subsequently can be biologically oxidized. 2.3.2.5 Direct Addition of Dissolved Organic Carbon The addition of organic carbon to an aquifer can significantly accelerate reductive biodegradation processes by providing a ready supply of an electron donor. In some cases, the introduction of organic carbon to the aquifer may be the sole purpose of the PRB and no other reactive media is involved. Such applications are referred to as biobarriers or bio-walls and involve the emplacement of a slow release source of organic carbon such as compost or vegetable oil. It is a matter of discussion whether such treatment should be considered a permeable barrier technology or whether it should be considered purely in the context of bioremediation.

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More commonly, the introduction of dissolved organic carbon can be an ancillary effect from ZVI emplacement, as in the case of biopolymer trenching or guar-based injection methods such as hydraulic fracturing or jetting. When trenching is used as the construction method for a PRB, a high-density biodegradable slurry is often used to hold the trench open during excavation and emplacement of the reactive media. Typically, the slurry-filled trench is filled with the granular iron or sand/iron mixture from the bottom up using a tremie. After the reactive media is emplaced, the biopolymer slurry is typically broken with an enzyme that converts it into simple soluble sugars. Complete breaking of the slurry is essential to ensure that the completed PRB will have the desired permeability. The resultant simple sugars are then dissolved in the groundwater and carried downgradient in the PRB effluent. Guar is used to suspend the granular iron during injection-based PRB emplacement methods such as jetting and hydraulic fracturing. Guar is a highly soluble food-grade starch which, when chemically cross-linked, forms a highly viscous gel. This viscous gel serves as a carrier fluid for the iron during the jetting or fracturing process. As in the case of biopolymer slurry trenching, a breaker enzyme is added to the gel/iron slurry as it is injected into the subsurface, resulting in the transformation of the cross-linked slurry into simple soluble sugars. Dissolved organic carbon introduced as a by-product of PRB construction is transient and completely consumed after a period of time. This period of time, however, may last as long as a few years depending on site-specific conditions such as groundwater velocity and the amount of biological activity. During this period, the introduced organic carbon can significantly impact downgradient groundwater quality, particularly during the transition period from pre-PRB conditions to the new post-PRB steady-state. In fact, the organic carbon can shorten the period of time necessary to reach steady-state by accelerating biodegradation and consequently accelerating the rate of desorption in the downgradient aquifer.

2.3.3 PRB SYSTEM DYNAMICS After a PRB is installed, treated groundwater begins to displace untreated groundwater in the downgradient aquifer. Notwithstanding this influx of treated water, contaminants continue to be present in the downgradient aquifer for some time after PRB installation, largely due to the slow desorption of contaminants from the aquifer solids. This desorption occurs as the downgradient aquifer transitions into a new equilibrium with the treated PRB effluent. Eventually, the reservoir of sorbed contaminants is depleted and downgradient contaminant concentrations are no longer replenished by the dissolution of sorbed contaminants. This process can take several years, depending on site-specific factors such as aquifer grain size, fraction of organic carbon (FOC), groundwater velocity, and initial contaminant concentrations. The rate of desorption is a function of the relative amounts of the compound in the dissolved phase and the sorbed phase. Like dissolution, the rate of desorption is largely driven by the concentration gradient. Desorption rate can be

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Barrier Systems for Environmental Contaminant Containment & Treatment Theoretical Desorption Curve

Normalized Concentration

1

0.8

0.6

0.4

0.2

0 Time

FIGURE 2.4 Representative desorption curve.

modeled using the Langmuir isotherm and is often represented as a graph of dissolved phase concentration vs. time. In groundwater systems, time is equivalent to the number of pore volumes of clean water that have passed through the aquifer material. A typical desorption curve is shown in Figure 2.4. Sorbed phase contaminants are largely unavailable for biodegradation. As contaminants desorb from aquifer solids and re-enter the dissolved phase, they become available to dechlorinating organisms in the downgradient aquifer. Biodegradation can accelerate the desorption process by suppressing contaminant concentrations in the dissolved phase. Downgradient biodegradation processes can be accelerated by the presence of organic carbon from PRB construction and other processes discussed later. Both the desorption of parent compounds and the subsequent biodegradation of these compounds into fully or partially dechlorinated daughter compounds impacts downgradient groundwater quality until steady-state is reached. Data from groundwater monitoring during this transient period can be confusing and can lead to erroneous conclusions about the performance of the PRB itself. For example, the persistent presence of parent compounds such as TCE or PCE due to desorption in the downgradient aquifer can be interpreted as breakthrough or leakage of these compounds through the PRB because of faulty construction such as PRB holes or gaps. Similarly, the presence of cis-1,2-DCE or vinyl chloride resulting from partial biodegradation of desorbed PCE or TCE can be incorrectly interpreted as daughter products in the PRB effluent resulting from insufficient residence time in the reactive treatment zone. It is therefore useful to model these

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Co Compliance point

Permeable barrier

Design basis Cd

Ct

FIGURE 2.5 Conceptual model of chlorinated solvent treatment using a PRB coupled with natural biodegradation.

processes to develop an estimate of the amount of time needed for the aquifer to reach steady-state at a given distance downgradient of the PRB. Figure 2.5 shows a conceptual model of a treatment train consisting of a PRB in combination with natural biodegradation processes at steady-state. The concentration of the target constituent (vertical axis) is shown vs. distance in the downgradient direction (horizontal axis). C0 represents the initial concentration in the upgradient area, which decreases in the downgradient direction at the intrinsic rate of natural biodegradation at the site. This intrinsic rate can be slow or negligible at sites where additional treatment has been deemed warranted. Ct is the target concentration that needs to be achieved prior to reaching the downgradient POC. It is not necessary to design the PRB to achieve Ct at the downgradient edge of the PRB, if space is available downgradient of the PRB for biodegradation to further reduce the concentration prior to reaching the POC. Cd is the PRB design concentration selected to achieve the target concentration at the POC, taking downgradient biodegradation into account. Consider the case of a treatment train consisting of ZVI treatment in a PRB followed by natural biological degradation for treatment of a carbon tetrachloride plume. When treated by ZVI, carbon tetrachloride can be completely transformed into the fully dechlorinated end products carbon monoxide and formate, with a partial yield of trichloromethane (TCM) (approximately 40% on a molar basis). The generated TCM can then be completely transformed into a mixture of fully dechlorinated end products and DCM, which is not further treated by the ZVI. The end result of this reaction series is the complete transformation of carbon tetrachloride and TCM, with production of DCM in the amount of approximately

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20% of the parent carbon tetrachloride on a molar basis. Biodegradation can be an effective means of treating the generated DCM daughter product, thereby achieving complete dechlorination of the parent carbon tetrachloride to nonchlorinated end products prior to reaching the POC. DCM is known to be rapidly biodegradable under a variety of environmental conditions, both aerobic and anaerobic (Cox et al., 1998). In addition to carbon tetrachloride, the design approach shown conceptually in Figure 2.5 can be used to optimize the design of PRB remedies for other chlorinated solvents where daughter products are generated that can be fully transformed in the presence of ZVI, but at a slower rate than the parent compounds. The slower reaction rates of the daughter products necessitate a longer residence time in the reactive iron zone to achieve full dechlorination, resulting in a thicker PRB and correspondingly greater cost. Examples of such compounds include PCE and TCE. In the case of PCE and TCE, the daughter compounds cis-1,2-DCE and vinyl chloride are generated as part of the ZVI-driven degradation reactions. Both of these compounds have slower reaction rates than the parent PCE or TCE. The generated vinyl chloride and cis-1,2-DCE can be fully dechlorinated in a ZVI PRB given a sufficient thickness of iron and corresponding residence time. However, significant cost savings can be realized by using the available aquifer space downgradient of the PRB as a natural bioreactor to degrade residual cis-1,2-DCE and vinyl chloride rather than increasing PRB thickness. This approach is only practicable at sites where the biodegradation rates of these daughter compounds is sufficiently rapid and where sufficient space and residence time is available downgradient of the PRB prior to reaching the POC.

2.3.4 GEOCHEMICAL MODELING The discussion in the previous section illustrates that a variety of chemical reactions occur when groundwater, with a complex mix of cations, anions, and contaminants, passes through a ZVI PRB. One method for evaluating these types of reactions and predicting their effects is through the use of geochemical models. There are several different kinds of geochemical models that can be applied to PRBs. Speciation models evaluate the state of thermodynamic equilibrium of groundwater in a static, closed system. Reaction path models add to speciation modeling the capability of considering the step-wise reaction of the water with a medium such as ZVI. These models progressively compensate for groundwater that becomes oversaturated with respect to specified phases by allowing them to precipitate to maintain a state of chemical equilibrium. Redissolution of an early formed phase also is possible if the changing groundwater composition leads to undersaturation. Coupled flow, transport, and reactive transport models potentially develop a more realistic picture of reaction processes in dynamic systems by incorporating groundwater flow, solute transport (by advection, dispersion, and diffusion), and reaction kinetics into the modeling. Inverse or mass balance modeling differs from other types of geochemical models in that it does not involve thermodynamic considerations, but rather attempts to link two related

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groundwater compositions by the dissolution and/or precipitation of phases from a user-specified list of candidate phases. There are several general resources that discuss geochemical modeling in detail (Bethke, 1996; Paschke and van der Heijde, 1996; Zhu and Anderson, 2002). Those individuals interested in the chemical, mathematical, and numerical methods behind geochemical models and information about the limitations of the thermodynamic databases commonly used should consult these sources. In addition, these sources provide listings and references to many of the most common geochemical models in use today. AFRL (2000), Yabusaki et al. (2001), and Mayer et al. (2001) are examples of studies that focus on geochemical modeling as applied to PRBs with ZVI as the reactive medium. The specific examples in the following discussion are largely summarized from these and several additional sources. 2.3.4.1 Speciation Modeling Speciation models utilize the composition of groundwater (e.g., concentrations of dissolved species, pH, redox state) and temperature as input data to examine a large number of chemical reactions that potentially interrelate the chemical constituents of the water. These models use the law of mass action to relate the various chemical species; identify the state of saturation of mineral phases; and determine the distribution of dissolved constituents among several different species (e.g., Ca2+, CaHCO3+), including conversion of redox-sensitive species to more stable forms consistent with the redox state of the system (e.g., NO3– to NH3). At the heart of speciation models is a database containing the thermodynamic properties for elements, ions in solution, solid phases, and gases from which the state of groundwater equilibrium is computed. Speciation models also incorporate corrections for the effects of ionic activity and temperature. The saturation state of a specific phase in groundwater is determined by the saturation index (SI), which is defined by the relationship: SI = log (IAP/K) where K is the equilibrium constant of the reaction controlling formation of the phase and IAP is the ion activity product for the reaction (i.e., using the actual activities of the reaction species in groundwater). A state of equilibrium for the phase in the system is defined by SI = 0; SI > 0 indicates oversaturation and SI < 0 defines a condition of undersaturation. In general, speciation models predict some mineral phases will be oversaturated in groundwater; however, many of these phases will never be found precipitating from the water. Slow kinetics is one reason. Likewise, some dissolved ions are known to inhibit the precipitation of certain phases, and this phenomenon is not captured by geochemical models. Therefore, natural groundwaters frequently are in meta-stable equilibrium with respect to some phases. For example,

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clay minerals nearly always have SI >> 0, even when similar clays are found as secondary minerals in the host rock. Phases that are known to form slowly, but are found to precipitate nonetheless complicate matters further. For example, the abiotic reduction of SO42– to S2– (with subsequent precipitation of sulfide phases) involves the transfer of eight electrons and is slow. Typically, such reactions are considered unlikely during speciation modeling. However, at the Portsmouth gaseous diffusion plant in Ohio, FeS was discovered in an ex situ, flow-through groundwater treatment canister filled with ZVI. Investigation determined that the FeS resulted from microbialcatalyzed reduction of SO42– to S2– followed by precipitation of the phase. Therefore, the potential for microbial processes should not be ignored during modeling. MINTEQA2 (Allison et al., 1991), EQ3/EQ6 (Wolery, 1992), and PHREEQC (Parkhurst and Appelo, 1999) are examples of the many geochemical models that can perform equilibrium speciation calculations for groundwaters and evaluate the saturation state for a large number of phases. AFRL (2000) contains an example of speciation modeling applied to a ZVI PRB at Naval Air Station (NAS) Moffett Field in Mountain View, California. Groundwater samples were collected from monitoring wells placed in locations upgradient of, within, and downgradient of the PRB. Using PHREEQC, it was possible to evaluate the changing saturation state of a variety of selected mineral phases for groundwater at different positions within the barrier system. For example, upgradient groundwater at this site is observed to be close to equilibrium with respect to calcite (or aragonite). However, within the PRB near the upgradient side, calcite becomes oversaturated and then becomes sharply undersaturated within the PRB further in the downgradient direction. A reasonable interpretation is that, as the water becomes oversaturated in calcite in the first few feet of the PRB, the phase precipitates. Further downgradient of the PRB, changing groundwater composition (e.g., decreasing concentrations of Ca2+ and alkalinity) result in undersaturated conditions for the phase. Analogous relationships are observed for other phases. This modeling supports the general observation that most precipitation occurs near the sediment-PRB interface. Speciation modeling is a qualitative and indirect method for evaluating the reactions that can occur within a PRB. A more direct (and quantitative) approach is through reaction path modeling. 2.3.4.2 Reaction Path Modeling The next level of complexity for geochemical models is reaction path modeling in which groundwater is permitted to react with (i.e., dissolve) a small amount of the host media (i.e., ZVI), the resultant equilibrium state of the groundwater is determined, and oversaturated phases are permitted to precipitate to achieve a more stable state of equilibrium. An early formed phase can redissolve at a later point if the groundwater becomes undersaturated because of other reactions that occur and because the phase has not become isolated from the water. Carried through many reaction steps, it can be examined how the groundwater chemically

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evolves and what phases (and their amounts) precipitate or redissolve at each step. Computing the masses of different phases both dissolving and precipitating within PRBs as a function of reaction progress can yield estimates of the rate of pore space in-filling, an important consideration in predicting the lifetime of a barrier. In an effort to match what is observed in the PRB, reaction path models permit the user to suppress the precipitation of phases that are not observed to form due to extremely slow kinetics. Reaction kinetics can be incorporated into reaction path modeling if sufficient information about reaction rate equations is available (Gunter et al., 2000). Examples of geochemical models that have the ability to perform reaction path calculations include PHREEQC (Parkhurst and Appelo, 1999), EQ3/EQ6 (Wolery, 1992), and Geochemist’s Workbench (Bethke, 1994). Reaction path modeling has been applied to the PRB at NAS Moffett Field and is reported in AFRL (2000). In contrast to results from speciation modeling at the barrier described above, reaction path modeling is able to provide a vivid conceptual picture of the complex interplay of the impacts of iron dissolution to groundwater chemistry (e.g., large, rapid increase in pH and decrease in redox potential) and associated onset of precipitation of new phases with increasing reaction progress (e.g., siderite, FeS2, aragonite and magnesite, followed by Fe(OH)3 and green rust). In the case of aragonite, magnesite, and siderite, progressive decreases in Ca2+, Mg2+, Fe2+, and alkalinity concentrations in the later stages of reaction progress lead to eventual dissolution of these early formed phases. Sequential changes in the amounts of solid phases formed and dissolved constituents in groundwater can be graphically and quantitatively tracked. In this example, a small number of plausible phases were selected by the modeler to participate in the reactions; all others were suppressed. Clearly, the degree to which the model represents what happens in the PRB is dependent on this selection process, although other factors are important as well. Although reaction kinetics can be incorporated into reaction path modeling, it is not possible to develop a temporal and spatial picture of reactions occurring within a PRB without explicitly including flow and transport. The following subsection examines this more advanced approach to geochemical modeling. 2.3.4.3 Reactive Transport Modeling Reactive transport modeling is the most sophisticated form of geochemical modeling currently in use and incorporates groundwater flow, solute transport, and geochemical reactions in a fully coupled modeling system. The primary advantage of coupled modeling is that there is an added degree of realism because the element of time is explicitly included in the simulations. As a result, reaction kinetics can be incorporated into the modeling scheme and, in principle, the changes in groundwater chemistry and phases precipitating can be seen as a function of time (and space) as a packet of water passes through a PRB. In general, the maturity of coupled codes is considerably greater than our ability to provide adequate characterization data to populate the models. Chemically,

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not only are the thermodynamic data important, but kinetic relationships for the key phases, and sorption relationships for important dissolved species are needed. In addition, hydraulic information from which the flow equations can be simulated is required. The amount and variety of data needed to take full advantage of the capabilities of modern coupled models is significant and probably not something to be expected for normal PRB design activities. However, when used as a research tool capable of capturing the important components of the site hydrology and geochemistry through sensitivity analysis, this type of modeling can be helpful in determining what level of sophistication of modeling is really necessary. PHREEQC (Parkhurst and Appelo, 1999), MIN3P (Mayer, 1999), OS3D (Steefel and Yabusaki, 1996), and the Geochemist’s Workbench (Bethke, 1994) are examples of coupled flow, transport, and geochemical models. Continuing with the example provided by the PRB at NAS Moffett Field, Yabusaki et al. (2001) presented results of a reactive transport investigation using the OS3D modeling code (Steefel and Yabusaki, 1996). For this study, onedimensional transport was used. As in the other modeling methods described above, a set of plausible phases was selected by determining if the phases were undersaturated in the background groundwater and oversaturated in the PRB. Phases such as Fe(OH)3(am), Fe(OH)2(am), siderite, aragonite, and green rust were included. Reaction rate equations were selected for the key reactions to be modeled. Hydraulic data was selected; dispersion and diffusion were ignored. Although not without some problematic results, reactive transport modeling succeeded in providing improved understanding of the inter-relationship between transport and reaction rates occurring in the field. A second example of reactive transport modeling, applied to a ZVI PRB in Elizabeth City, North Carolina, was illustrated by Mayer et al. (2001). In this example, Cr(VI) and TCE were the target contaminants. The modeling results were able to closely match the observed behavior of these contaminants within the barrier, as well as that of other groundwater chemistry parameters such as pH and various dissolved inorganic species. In addition, this modeling approach offered the possibility of hypothesizing important processes associated with more complex reactions. 2.3.4.4 Inverse Modeling All of the types of modeling discussed so far are examples of forward modeling. Inverse geochemical models use mass balance techniques to find a relationship between two related groundwater compositions and the reactions that connect them. These models can only be applied to a system (e.g., a PRB or flow-through column) where at least two groundwater samples are available, with the reasonable assumption that one groundwater directly evolved from the other. The user identifies a list of plausible phases that can relate the two groundwater samples. The model then uses analytical methods to define all combinations of these phases that, when dissolved precipitate from the initial groundwater composition, or will yield the later stage groundwater. In general, solutions to inverse modeling are

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nonunique and, being strictly a mass balance or mathematical operation, thermodynamics does not enter into the simulations. One application of this methodology that might be used to help understand possible reactions in a future PRB is a flow-through column. Because it is not thermodynamically based, issues such as reaction kinetics, inhibitions, and microbial catalysis do not enter into the modeling. If the list of plausible phases is inclusive, the combinations of phases and amounts of them can be determined mathematically to account for changes in groundwater chemistry. It is up to the user to determine which, if any, of the acceptable solutions is realistic. NETPATH (Plummer et al., 1994) and PHREEQC (Parkhurst and Appelo, 1999) are two models that perform mass balance modeling. An example of an inverse modeling example based on data from the NAS Moffett Field PRB is presented in AFRL (2000). In this example, compositions of an upgradient groundwater and of a groundwater inside the PRB 0.5 feet from the upstream side of the PRB were selected for modeling. Eight plausible phases were selected. Only ZVI was allowed to dissolve; the other phases [Fe(OH)3, siderite, marcasite, brucite, aragonite, magnesite, and CH4] were only allowed to form. Using the mass balance capability of PHREEQC, four acceptable solutions resulted that successfully related the two groundwater compositions. Based on field observations at the PRB site, one of the models was rejected, but the remaining models were considered equally reasonable. In general, one might imagine selecting the most probable model based on field observations of the identity and amounts of precipitated phases. However, when the quantity of secondary phases is small, it is difficult to obtain an accurate estimate of their abundance with standard solids characterization techniques. The relatively small number of solid samples that reasonably can be collected and analyzed from a PRB further compounds this difficulty. Therefore, no selection among the three remaining models was possible.

2.3.5 MODELING LIMITATIONS

AND

RESEARCH NEEDS

OF

PRBS

Geochemical modeling can be a powerful predictive tool when applied to PRB systems. One major advantage of working with a ZVI barrier system in comparison to normal geologic systems is the inherent simplicity of the iron medium. In effect, a single simple phase is present (Fe) that has well characterized physical, chemical, and thermodynamic properties. However, as with any natural system (especially one with flowing groundwater), the simulation of multiple heterogeneous reactions is not without complexities. Attempts to make such models more realistic (temporally and spatially) have increased the burden on the modeler to obtain appropriate data. For example, reaction rate equations, sorption relationships, hydraulic properties, and microbially catalyzed reactions are some of the complications that can be important. As noted above, the most sophisticated models used today are more mature than our ability to supply required input data at an appropriate scale. The major limitations in modeling PRBs arise from inadequate knowledge of the processes

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occurring in PRBs, especially as PRB materials age. In spite of these limitations, experience gained investigating and modeling existing PRBs improves the understanding of key processes, helps refine the selection of plausible phases, and helps focus on the most sensitive parameters to quantify.

2.4 WALLS AND FLOORS Both vertical and horizontal barriers can be used to mitigate the extent of subsurface contaminant migration. The most common type of vertical barrier is the slurry cutoff wall, whereas horizontal barriers can include constructed engineered barriers (floors) and natural geologic formations such as aquitards and aquicludes.

2.4.1 VERTICAL BARRIERS The three main types of cutoff walls used as vertical barriers for subsurface containment of contaminated groundwater are soil–bentonite (SB) walls, cement–bentonite (CB) walls, and composite slurry walls (CSWs). SB cutoff walls are constructed by displacing the bentonite slurry in an excavated trench by backfilling with a mixture of the bentonite slurry and the excavated trench spoils. CB cutoff walls are constructed using a mixture of cement and bentonite slurry to maintain the stability of the excavated trench and then allowing the mixture to set to form the cutoff wall. CSWs are constructed by inserting a geomembrane into the slurry along the centerline of the trench during construction. In most applications involving the containment of contaminated groundwater, vertical cutoff walls are keyed into naturally occurring horizontal barriers formed by low-permeability geologic formations, such as aquitards or aquicludes, to impede contaminant migration beneath the zone of contamination.

2.4.2 HORIZONTAL BARRIERS In the case where a suitable aquitard or aquiclude is too deep, the construction of a horizontal barrier beneath the zone of contamination may be required. The more common options for horizontal barrier construction based on existing technologies are permeation grouting and jet grouting. Permeation grouting involves the injection of a low viscosity slurry material into the ground through a series of overlapping injection wells. Construction of a basal barrier by permeation injection requires the grout material to penetrate the soil completely and remain in place until solidification is complete. For jet grouting, a single fluid (grout), two fluids (grout/air), or three fluids (grout/air/water) are injected into the soil under high pressure (over 300 atm) through a small orifice (1 to 2 mm diameter) to erode or cut the soil and simultaneously place and mix the grout, resulting in a homogeneous columnar mass (e.g., Kauschinger et al., 1992; Tausch, 1992). Jet grouting is feasible in virtually all soil conditions ranging from clays to gravels (Kauschinger et al., 1992). The jet grouting technique can be used to form a horizontal barrier below the waste material by drilling on a regular grid pattern to form a system of

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inter-penetrating grout discs. In this application, a borehole is driven to the required depth, and a jet grout monitor is inserted. The monitor is fitted with a high-pressure jet-cutting nozzle and can be rotated to cut a disc-shaped hole at the required depth. The monitor is raised during cutting to form a disc of the required thickness. Jet grouting can also be used to form inclined barriers (Dwyer et al., 1997). The barrier in this case consists of two honeycombed rows of interconnected vertical and inclined Portland-based grout columns forming a Vshaped trough in which the contamination is located. The inside of the cement V-trough can be lined with a low viscosity, chemically resistant polymer to form a secondary barrier to contaminant movement. This approach offers the advantage of not having to drill through the contamination. Another possible approach is to use horizontal directional drilling to form a barrier under the contamination (Sass et al., 1997). Although not yet practical, this technique potentially overcomes the shortcomings of vertical or inclined drilling and has been successful in contamination detection (Katzman, 1996; Anon, 2000).

2.4.3 CURRENT STATE OF PRACTICE FOR MODELING PERFORMANCE OF WALLS AND FLOORS Given the limitations of the prescriptive design approach, a performance-based design approach may be more appropriate to ensure successful containment. In a performance-based design, individual properties or elements of a containment system are not prescribed. Instead, the design is based on demonstration that the containment system will meet the overall objective. For example, the overall objective may be to maintain the concentration of a target pollutant at a level below risk-based standards [e.g., drinking water maximum contaminant levels (MCLs)] at a downgradient POC (e.g., fence line, monitoring well) or point of exposure (POE) (e.g., drinking water well). Predictive contaminant transport modeling will be a critical component for demonstrating successful performance in this regard. This chapter provides a comprehensive description of the current state of the art for prediction of the performance of vertical cutoff walls for waste containment. The description is focused on applications in the saturated zone, with emphasis on performance of cutoff walls for containment of aqueous phase miscible contaminants. However, given the recent interest in vadose zone walls, liquid- and gas-phase transport processes that govern the performance of vadose zone walls merit some consideration and are described in this chapter to provide a foundation for future development of design criteria and/or transport models for prediction of wall performance. Either a component approach or a system approach may be adopted when using models to assess the effectiveness of containment barriers in terms of mitigating the extent and/or impact of subsurface pollution. In the component approach, only the barrier is modeled. This approach allows for the use of relatively simple analytical models (e.g., Rabideau and Khandelwal, 1998a,b). In

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the system approach, multiple components of the flow domain, such as a vertical cutoff wall located within an aquifer, are modeled as a system resulting in the need to consider the effect of heterogeneous media. This approach generally requires the use of more complex semi-analytical or numerical models (e.g., finite difference, finite element). These two approaches differ primarily with respect to the point at which the contaminant migration is evaluated, such as the POC or POE. The component or analytical modeling approach is relatively simple to use, but is potentially conservative in that the POC typically must be assumed to be located at the outer boundary of the barrier rather than at some other location downgradient of the containment location. As a result, the design based on a component analysis may be too conservative and, therefore, ineffective in terms of cost. In most cases, environmental regulations allow for a POC at some location downgradient of the containment facility (e.g., the interface between a confined site and the upper confining layer, a property boundary, some other location) such that the impact of contamination reaching the outer boundary of the barrier is not the primary concern. In such cases, the system approach using either semianalytical or numerical models may be more appropriate (i.e., less conservative) and, therefore, may result in more cost-effective designs. However, the systems approach generally requires more input data than the component approach, tending to offset the difference in cost between the two approaches.

2.4.4 CONTAMINANT TRANSPORT PROCESSES Most barriers employed in geoenvironmental applications are designed to provide containment of dissolved contaminant plumes in groundwater. Thus, the discussion herein is limited to processes that govern the liquid-phase migration of solutes. The reader is referred to Bear (1972), Corey (1994), Pankow and Cherry (1996), and Charbeneau (2000) for information regarding the migration of immiscible fluids. 2.4.4.1 Aqueous-Phase Transport Aqueous-phase contaminant transport in porous media is controlled by a variety of physical, chemical, and biological processes. The primary physical processes governing miscible contaminant transport are advection, diffusion, and dispersion. Diffusion tends to be the dominant transport process in relatively low flow rate situations, such as those that occur through clay barriers (Rowe, 1987; Shackelford 1988, 1989). However, advection and dispersion dominate in relatively high flow rate situations, such as contaminant migration through coarse-grained aquifer materials. Processes such as adsorption, radioactive decay, precipitation, hydrolysis, and biodegradation generally are considered attenuation processes in that contaminant mass is removed from the aqueous phase. However, in some cases, some of these attenuation processes may not be effective in reducing the potential impact of

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the contaminants. For example, the radioactive decay of the initial contaminant results in by-products that also can represent a potential adverse environmental impact. Similarly, subsequent desorption of a previously adsorbed contaminant or dissolution of a previously precipitated contaminant can result in negative environmental impacts. Typically, only the physical processes of advection, diffusion, and dispersion, and the chemical processes of sorption and radioactive decay are included in practical modeling applications. Although prototype models that include the more complicated chemical processes (e.g., oxidation/reduction, precipitation, hydrolysis, complexation, biodegradation) have been formulated, these models are considered not yet suitable for routine use in practice (National Research Council, 1990). Thus, the development contained herein pertains primarily to modeling advection, dispersion, and/or diffusion with sorption and radioactive decay. For applications involving subsurface containment barriers, aqueous-miscible solute transport traditionally is described using the one-dimensional form of the advective-dispersive transport equation, in which the total flux of a solute, J, is represented as the sum of advective, diffusive, and dispersive fluxes, or:

J = J a + J d + Jm = qhC − θD *

∂C ∂C = θv S C − θD ∂x ∂x

(2.3)

where Ja is advective flux, Jd is diffusive flux, Jm is mechanical dispersive flux, qh [= khih, where kh = hydraulic gradient] is hydraulic liquid flux, C is the solute concentration, θ is the volumetric water content, which is equal to the porosity (n) for saturated media, D* is the effective diffusion coefficient, Dm is the coefficient of mechanical dispersion, vS (= qh /θ) is seepage velocity, D is the hydrodynamic dispersion coefficient, and x is the direction of transport. For onedimensional transport, the hydrodynamic dispersion coefficient, D, can be expressed as follows (Freeze and Cherry 1979, Shackelford 1993): D = D * + Dm = D * + α L vS

(2.4)

where αL is the longitudinal dispersivity of the porous medium in the direction of transport. For transport through low permeability cutoff walls, the seepage velocity, vs, is often sufficiently low that mechanical dispersion is negligible. The governing equation for transient solute transport through porous media based on conservation of mass within a representative elementary volume (REV) is as follows: ∂(θRd C ) = −∇ ⋅ J + S ∂t

(2.5)

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where Rd is the dimensionless retardation factor that accounts for instantaneous, linear, reversible adsorption of the solute to the solid phase, and S is a general source (>0)/sink (<0) term for other chemical and/or biological reactions. For example, first-order decay of a chemical species can be included through a sink term as follows (van Genuchten and Alves, 1982): S = −θΛC

(2.6)

where Λ is a lumped decay constant [T–1] given as follows (Rabideau and Khandelwal, 1998a): Λ = λ w + λ s ( Rd − 1)

(2.7)

where λw is the decay constant for first-order decay of contaminant in aqueous solution, and λs is the decay constant for first-order decay of contaminant on the solid phase. The value of Rd is equal to unity for a nonreactive solute (i.e., Rd = 1) and greater than unity for a reactive solute (i.e., Rd > 1). For linear sorption, the retardation factor is written as: Rd = 1 +

ρd Kd θ

(2.8)

where ρd is the dry bulk density of the soil, and Kd is the distribution coefficient that relates the change in adsorbed concentration of a solute to a change in the liquid-phase solute concentration at equilibrium. For organic contaminants, the distribution coefficient commonly is related to the organic carbon partition coefficient, Koc, as follows: K d = K oc ⋅ foc

(2.9)

where foc is the mass fraction of organic carbon in the soil. The lumped decay constant assumes several reduced forms depending on special conditions. For example, for nonadsorbing solutes (i.e., Rd = 1) or solutes that undergo decay only in the aqueous phase (i.e., λs = 0), Λ = λw , whereas for equal rates of decay in both the aqueous and solid phases (i.e., λw = λs = λ), Λ = λRd. Based on the assumptions that the porous medium is homogeneous, isotropic, and rigid (nondeformable); the water is incompressible; and the liquid flux is steady (i.e., vs = constant), the combination of Equations (2.3) through (2.8) results in the following form of the advection-dispersion reaction equation (ADRE) governing one-dimensional aqueous miscible transport: Rd

∂C ∂2C ∂C = D 2 − vS − ΛC ∂t ∂x ∂x

(2.10)

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Contaminated material Entrance: C(0, t)

L

Horizontal or vertical barrier

Exit: C(L, t)

Groundwater flow

FIGURE 2.6 Boundary conditions for horizontal (vertical cross-section) or vertical barrier (plan view).

Equation (2.10) is often presented in dimensionless form: ∂C * ∂2C * ∂C * = − Pe − Λ*C * 2 ∂t * ∂x * ∂x *

(2.11)

where:

C* =

vL x tD C ΛL2 ; t* = ; x * = ; Pe = s ; Λ* = 2 D D L C0 Rd L

(2.12)

where L is the barrier thickness. Solution and application of Equation (2.11) requires specification of initial and boundary conditions. Consider conditions as illustrated in Figure 2.6, which can be viewed as a vertical cross section for a horizontal barrier or a plan view of a vertical wall. A complete solution of transport in this system requires a twodimensional (or 3-D) description. However, a very common approach is to only consider one-dimensional contaminant transport through the barrier and to choose boundary conditions that are an approximation of reality. These boundary conditions consist of entrance boundary conditions on the inside of the barrier and exit boundary conditions on the outside of the barrier. The most common entrance boundary condition used is the first type, consisting of specification of a temporally constant concentration at the inlet (x = 0): C (0,t) = C0

(2.13)

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van Genuchten and Alves (1982) also give boundary conditions that represent an exponentially decaying entrance boundary concentration. Third-type boundary conditions consist of specifying that the sum of the advective and dispersive fluxes away from the boundary is constant, given by the product of temporally constant fluid velocity and contaminant concentration:

vC 0 = vC 0 (0, t ) − D

∂C ∂t

(2.14)

These boundary conditions are appropriate for advection-dominated transport typical of laboratory columns, but can give inaccurate flux predictions for the low flow conditions typical of low permeability barriers (Rabideau and Khandelwal, 1998a). Rowe and Booker (1985a) gave a modified third-type boundary condition that assumed finite initial mass in a completely mixed source zone and decreasing source concentration due to transport into the barrier. This boundary condition was also used by Rabideau and Khandelwal (1998b). The most common outlet boundary conditions used for general modeling of contaminant transport are semi-infinite boundary conditions of first type: C (∞, t ) = 0

(2.15)

∂C (∞, t ) =0 ∂x

(2.16)

or second type:

The use of a semi-infinite boundary condition implies no change in material properties and flow perpendicular to the barrier on the aquifer side of the barrier. However, in many cases such as groundwater flow beneath a liner or parallel to a vertical barrier, contaminants leaving the barrier are diluted, thus reducing the concentration at the exit boundary and increasing the concentration gradient and diffusive fluxes. In these cases, a semi-infinite exit boundary condition (of any type) is not appropriate because contaminant fluxes through the barrier would be underestimated. If the flow rate in the aquifer is rapid relative to the contaminant flux across the barrier, the contaminant concentration at the barrier-aquifer boundary can approach zero and a first type boundary condition may be appropriate: C(L,t) = 0

(2.17)

Rowe and Booker (1985a) gave boundary conditions that accounted for the rate of contaminant removal at the barrier-aquifer interface as a function of groundwater velocity, diffusion coefficient, barrier width, and aquifer depth. Equation (2.17) represents a more conservative assumption as it maximizes flux.

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When transport is advection dominated, a second-type boundary condition is sometimes applied at the barrier-aquifer interface. This application is not appropriate for systems where diffusion is significant because it assumes that diffusion across the boundary is negligible (Rabideau and Khandelwal, 1998a). 2.4.4.2 Coupled Solute Transport Although solute transport analyses for engineered soil barriers of low hydraulic conductivity typically are based on advective-dispersive theory as described above, advective-dispersive transport theory represents a limiting case of the more general coupled flux transport theory in that coupling terms (e.g., chemicoosmosis) are assumed to be negligible (e.g., Yeung, 1990; Shackelford, 1997). While advective-dispersive theory is considered acceptable for coarse-grained soils (e.g., aquifers), use of advective-dispersive transport theory for clay-rich soil barriers may not be appropriate. For example, results of several laboratory studies have shown that some clay soils have the ability to act as membranes that restrict the transport of charged solutes (i.e., ions) (e.g., Kemper and Rollins, 1966; Olsen, 1969; Kemper and Quirk, 1972; Fritz and Marine, 1983; Malusis et al., 2001; Malusis and Shackelford, 2002a). This solute restriction also results in chemico-osmosis, or the movement of liquid in response to a solute concentration gradient, but opposite to the direction of solute diffusion (Olsen, 1969; Mitchell et al., 1973; Olsen, 1985; Barbour, 1986; Barbour and Fredlund, 1989; Neuzil, 2000). Several solute transport models that account for the presence of soil membrane behavior have been developed (Bresler, 1973; Greenberg et al., 1973; Barbour and Fredlund, 1989; Yeung, 1990; Yeung and Mitchell, 1993; Malusis and Shackelford, 2002b). In all of these models, membrane behavior is represented by a chemico-osmotic efficiency coefficient, ω, or reflection coefficient, σ, that ranges from zero (ω = σ = 0) for nonmembranes to unity (ω = σ = 1) for ideal membranes that completely restrict the passage of solutes (Staverman, 1952; Kemper and Rollins, 1966; Olsen et al., 1990; Keijzer et al., 1997). Clay soils that exhibit membrane behavior typically only partially restrict the passage of solutes (i.e., 0 < ω, σ < 1) and, therefore, are considered nonideal membranes. In the absence of electrical current, the general expression for total coupled flux of a chemical species, j (neglecting mechanical dispersion), can be written as follows (Shackelford et al., 2001):

J j = J ha, j + J π, j + J d , j = (1 − ω )qhC j + qπC j − nD *

∂C j ∂x

(2.18)

where Jha,j is the hyper-filtrated advective flux of solute j, Jπ,j is the chemicoosmotic counter-advective flux of solute j, Jd,j is the diffusive flux of solute j, and qπ is chemico-osmotic liquid flux. The hyper-filtrated advective mass flux represents the traditional advective transport term that is reduced by a factor of (1 – ω)

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due to the membrane behavior of the soil [i.e., Jha,j = (1 – ω)Ja,j]. In physical terms, the factor (1 – ω) represents the process of hyper-filtration whereby solutes are filtered out of solution as the solvent passes through the membrane under an applied hydraulic gradient. The chemico-osmotic counter-advective flux represents the transport of solutes due to chemico-osmotic liquid flux opposite to the direction of diffusion (i.e., from low solute concentration to high solute concentration). The chemico-osmotic liquid flux, qπ , can be written as follows (Malusis and Shackelford, 2002c): qπ =

ωK h ∂π γ w ∂x

(2.19)

where γw is the unit weight of water and π is chemico-osmotic pressure. For dilute chemical solutions, chemico-osmotic pressure, π, is related to solute concentration in accordance with the van’t Hoff expression or (Tinoco et al., 1995): N

π = RT

∑C

i

(2.20)

i =1

where R is the universal gas constant [8.143 J/mol⋅K], T is the absolute temperature [K], N is the total number of solutes. Thus, the summation term accounts for the concentrations of all chemical species in solution, including species j. For example, if a solution contains the cation and anion of a binary, fully dissociating salt (e.g., sodium chloride), the chemico-osmotic pressure can be expressed as follows: π = RT (C a + C c )

(2.21)

where Ca and Cc are the concentrations of the salt anion and the salt cation, respectively. Fritz (1986) notes that the van’t Hoff equation is valid for concentrations up to 1.0 M for monovalent salts (e.g., sodium chloride, potassium chloride). For transient transport, the total coupled solute flux equation (Equation (2.18)) is substituted into the continuity equation (Equation (2.3)) to yield the following:

Rdj

∂C j ∂C j ∂C j ∂v = (ω − 1)vS − vπ − Cj π + ∂x ∂t ∂x ∂x ∂2C j

(2.22)

∂D * ∂C j D* 2 + − θΛC ∂x ∂x ∂x where vπ is the chemico-osmotic seepage velocity that is related to the chemicoosmotic liquid flux, qπ , or

Modeling of Fluid Transport through Barriers

vπ =

qπ ⎛ ωK h ⎞ RT = θ ⎜⎝ θgρw ⎟⎠

119 N

∑ ∂∂Cx

i

(2.23)

i =1

Equation (2.22) must be written separately for each chemical species in solution. The equations are nonlinear and require a numerical method (e.g., finite difference, finite element) to solve for the concentration distribution of a solute within a cutoff wall at any point in time. In addition, because the transport of a solute is dependent on the presence of other solutes in the system based on Equation (2.20), an iterative solution method must be utilized in conjunction with the following electro-neutrality constraint that must be satisfied at all points within the system: N

∑C Z = 0 i

i

(2.24)

i =1

where Ci is expressed in molar concentration and Zi is the ionic charge of solute i. Further information with regard to solution of the coupled solute transport equations is given by Malusis and Shackelford (2002c). 2.4.4.3 Modeling Water Flow through Barriers The simplest approach to modeling water flow through barriers is to apply Darcy’s Law, assuming one-dimensional, steady-state saturated flow. If the hydraulic head difference across the barrier is known, this approach is straightforward and can be applied to single- or multiple-layer barriers. In cases where head differences may not be known, a barrier is usually modeled as part of a larger system such as a landfill or a subsurface system. For landfills, the most commonly used model is the HELP model (Schroeder et al., 1994a,b). The HELP model is an integrated quasi- two-dimensional model that includes the cap processes discussed in Section 2.3.2, vertical flow through a waste layer, lateral flow through a drainage layer, and vertical flow through a horizontal barrier layer that can include a geomembrane. The model predicts water buildup above the barrier layer to predict leakage rates through the barrier layers. To predict leakage rates through vertical barriers installed in complex hydrogeologic settings, a variety of numerical models can be employed, with MODFLOW (McDonald and Harbaugh, 1988) being the most widely used. Particular attention must be given to grid discretization issues because barriers are often small in size in comparison to the total size of the system being simulated, and sharp hydraulic head gradients and changes in groundwater flow directions can occur in the vicinity of the barrier. When geomembranes are employed in horizontal and vertical barriers, fluid flow through defects may be the dominant mode of water flow and contaminant

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transport. Foose et al. (2001) used MODFLOW to examine several analytical models (e.g., Giroud, 1992; Rowe, 1998) for leakage rates through composite liners. They concluded that the existing analytical solutions had shortcomings and provided a series of recommendations for modification of these solutions for a variety of different conditions. 2.4.4.4 Analytical Models Shackelford (1988, 1989) identified three possible scenarios (Figure 2.7) for the design of low permeability walls based on a one-dimensional conceptualization of the system: (a) pure diffusion; (b) diffusion with advection and (c) diffusion against advection. The pure diffusion scenario represents the limiting case. Diffusive transport generally is significant through relatively thin (≤ 1 m) barriers with K ≤ 10–7 centimeters per second (cm/s) and dominant through thin barriers with K ≤ 5 × 10–8 cm/s (Shackelford, 1988, 1989). The diffusion with advection scenario occurs when water levels on the inside of the barrier exceed those on the outside. The diffusion against advection scenario occurs when the water level is drawn down on the containment side of the wall to induce inward flow and reduce the outward flux of contaminants. A variety of analytical models can be applied to predict one-dimensional contaminant transport under the scenarios illustrated in Figure 2.6 and Figure 2.7. Selection of the appropriate model involves a choice of steady-state or transient conditions and the choice of the appropriate boundary conditions. Analyses can be performed to evaluate contaminant concentrations on the aquifer side of the +x

co

+x

c < co

Diffusion

(a)

co

+x

c < co

co

c < co

Diffusion

Diffusion

Advection

Advection

(b)

(c)

FIGURE 2.7 Design scenarios for low permeability walls: (a) pure diffusion, (b) diffusion with advection, (c) diffusion against advection. (From Shackelford, C.D., 1989. Geotechnical Engineering 1989, TRB, NRC, National Academy Press, Washington, DC, pp. 169–182; Manassero, M. and Shackelford, C.D., 1994. Rivista Italiana di Geotecnica, AGI, 28(1). With permission.)

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121

barrier, or flux rates of contaminants through the barrier as a function of wall thickness; drawdown across the wall; and the associated pore water velocity, effective diffusion coefficient (influenced by soil type), and adsorption capacity of the wall. Rubin and Rabideau (2000) illustrated the impact of the Peclet number on steady-state fluxes through one-dimensional barriers with constant concentration entrance boundary condition, fixed-zero concentration exit boundary condition, and no decay. For zero concentration at the barrier-aquifer interface, the flux rate, F, through the barrier is: ⎛ ∂C ⎞ F = θ ⎜ vs C − D ∂x ⎟⎠ ⎝

(2.25)

In dimensionless form this becomes:

F* =

FL ∂C * = PeC * − θDC 0 ∂x *

(2.26)

The dimensional flux, F*, is thus the ratio of steady-state advective-dispersive flux to steady-state dispersive flux alone. When decay occurs as the contaminant is transported through the barrier, the dimensionless flux is given by (Rabideau and Khandelwal, 1998a):

F* =

⎛ Pe ⎞ exp ⎜ ⎟ Pe 2 + 4 Λ* ⎝ 2⎠ 2 sinh

(

Pe 2 + 4 Λ* 2

)

(2.27)

For the case of no decay (Rubin and Rabideau, 2000), this simplifies to: F* =

Pe 1 − exp(− Pe)

(2.28)

Consider a 1 m thick barrier with a hydraulic conductivity of 10–9 m/s, a porosity of 0.4, and an effective diffusion coefficient of 10–10 m2/s. Assuming negligible mechanical dispersion gives a Pe number of 25Δh, where Δh is the hydraulic head difference across the barrier. The impact of Δh on flux is plotted in Figure 2.8 for three different values of the dimensionless decay constant. The results for zero hydraulic head gradient correspond to diffusive transport with varying rates of decay. The figure illustrates the significance of advection and decay on contaminant flux rates.

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3.0 No decay Decay constant = 5

Dimensionless Flux, F*

2.5

Decay constant = 10 2.0 1.5 1.0 0.5 0.0 0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.10

Hydraulic Head Gradient

FIGURE 2.8 Steady-state flux across a barrier as a function of hydraulic head gradient.

In the case of a decaying contaminant source (i.e., a finite source), design should be based on a transient analysis. In many cases, the rate of increase of flux with time or the time to reach some critical concentration at the barrieraquifer interface can be estimated, necessitating the use of a transient solution. A variety of solutions have been used for transient analysis of barriers. Many of these (Shackelford, 1989, 1990; Acar and Haider, 1990) are based on the Ogata Banks solutions for transient, one-dimensional contaminant transport with typeone entrance boundary conditions, and type-one semi-infinite boundary conditions. Rabideau and Khandelwal (1998a) give transient solutions for the combination of type-one entrance boundary condition and perfect flushing exit boundary condition, as well as a variety of other boundary conditions. The combination of a first-type entrance condition and flushing exit condition again resulted in the most conservative mass flux estimates at the exit end of the barrier. In comparison, estimated flux rates from a model based on a third-type entrance boundary condition and a zero-gradient exit boundary condition were about a factor of 20 lower. When the impact of groundwater flow below a horizontal barrier or parallel to a vertical barrier is important, and the perfect flushing boundary condition is deemed to be too conservative, models that simulate the aquifer adjacent to the barrier (Figure 2.7) as a mixing zone can be used. Rowe and Booker (1985a) applied Equation (2.10) with a finite mass entrance condition to one-dimensional transport across the barrier layer. They assumed a completely mixed aquifer with known depth and seepage velocity below the barrier and developed a Laplace transform solution that was inverted using a numerical Laplace inversion routine. Manassero and Shackelford (1994) presented a steady-state solution for a similar conceptual model, but with a constant concentration entrance condition. Rabideau and Khandelwal (1998a) developed a transient model (with numerical Laplace

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123

transform inversion) similar to that of Rowe and Booker (1985a), and showed that a range of mixing zone flow rates spanned behavior from the perfect flushing condition to that of a semi-infinite boundary condition. Because transverse vertical dispersion coefficients can be quite small (on the order of molecular diffusion), definition of an appropriate mixing zone for use of one-dimensional solutions is an open question. In the case where greater accuracy in predicting contaminant transport through barriers is desired, multi-dimensional models should be used. In this case, Rowe and Booker (1985b, 1986) developed Laplace transform solutions for transport through a variety of barrier–aquifer configurations, including a system with four layers in descending order consisting of a clay layer, a sand layer, a second clay layer, and a lower sand layer. However, as with the one-dimensional analytical and quasi-analytical models, transport in the sand layers was assumed to be one-dimensional and fully mixed vertically. In many cases, horizontal and vertical barriers can include geomembranes. Inorganic contaminants have negligible diffusion rates through intact geomembranes, while organic compounds diffuse readily through geomembranes (Foose et al., 2001). Foose et al. (2001) developed simplified analytical solutions for solute transport through composite liners incorporating a geomembrane and a soil layer. Modeling the transport of contaminants through CSWs that contain geomembranes is, however, complicated by the possibility of defects in the geomembranes, particularly at joints. Estimating contaminant flux rates through poorly characterized defects in geomembranes is difficult, but necessary for a realistic prediction of contaminant flux rates into the environment. Foose et al. (2002) evaluated the impact of geomembrane defects on contaminant transport using a finite difference numerical model and demonstrated the importance of defective joints on transport through composite geosynthetic clay liners.

2.4.5 MODELING LIMITATIONS AND RESEARCH NEEDS OF WALLS AND FLOORS Limitations to modeling barrier performance include difficulties in determining input parameters, dealing with measurement accuracy and uncertainty, and timevarying properties. Models are also limited with respect to their ability to simulate coupled solute transport and membrane effects in clay soils. 2.4.5.1 Input Parameters and Measurement Accuracy Given the importance of a reliable risk analysis and of correct barrier modeling, the importance of a reliable assessment of input parameters is apparent. In fact, sufficient attention is not always given to the evaluation of these parameters, particularly to low permeability materials. The accuracy of tests for low permeability materials and the appropriate interpretation procedures after tests are complete are fundamental in order to obtain reliable results.

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As in the case of compacted clay soils, the basic parameters of CB and SB mixtures for slurry cutoff walls (SCOWs) refer to (1) hydraulic conductivity, (2) sorption and diffusion, and (3) compatibility. The main factors influencing the hydraulic conductivity of CB mixtures are the solids content, curing time, confinement stress, and stress–strain behavior. For the common basic compositions of CB mixtures, the hydraulic conductivity can vary from 10–8 to 10–9 m/s (one order of magnitude change). The use of additives can lower these values by another order of magnitude (De Paoli et al., 1991). The confinement stress history is an important factor that influences the hydraulic conductivity of CB mixtures (Manassero et al., 1995). The confinement stress in reducing hydraulic conductivity is more effective if applied at short curing times, although after 50 days it is also possible to observe hydraulic conductivity reduction due to an increase of confinement effective pressure. For confining stresses ranging from 0.1 to 10 MPa applied on 28 days cured samples, the hydraulic conductivity varies between 5 × 10–8 m/s to 5. × 10–10 m/s (Manassero et al., 1995). Stress–strain behavior can influence the in situ hydraulic conductivity of SCOWs due to the possible stress and strain induced by surrounding ground movements. The level of confinement stress can determine different kinds of mixture behavior under deviatoric stress as observed by Manassero et al. (1995). The different kinds of mixture behavior are brittle-softening, brittle-hardening, ductile-softening, and ductile-hardening. The latter is the most favorable to keep hydraulic conductivity low. On the basis of preliminary experimental results (Manassero et al., 1995) and to obtain satisfying stress–strain behavior, the minimum effective confinement stress provided to the CSW CB backfilling mixture should be higher than 0.8 qu with qu being the unconfined compressive strength of the CB mixture. Some information on physico-chemical interactions between CB mixtures and chemical compounds to be contained by a SCOW can be found in Ziegler et al. (1993), Gouvenot and Bouchelaghem (1993), Finsterwalder and Spirres (1990), Muller-Kirchenbauer et al. (1991), Jessberger (1994), and Mitchell et al. (1996). The diffusion parameters are fully comparable with the same parameters from compacted clay liners (CCLs) (on the order of 10–10 m2/s) even though the total porosity of typical CB mixtures can be 2 to 10 times greater. From preliminary experimental results, the sorption capacity of CB mixtures seems to be rather effective for some organic pollutants and for anions in solution (Fratalocchi et al., 1996). This is probably due to the alkaline environment in the pore space. However, further validation of these results is necessary. As far as compatibility problems are concerned, the cement seems to play a fundamental role because the basic role of the bentonite (i.e., to stabilize the cement suspension) is fully completed during the first curing phase. Observations after curing with a scanning electronic microscope have shown that the bentonite grains are fully wrapped by hydrated cement that carries out the role of the solid structure of the cured mixture. Both low hydraulic conductivity and high confining stress tend to reduce the sensitivity of the mixtures to chemical attack, at least

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in the short term. Jefferis (1992) and Tedd et al. (1993) showed that only strong acids and/or sulfates could cause problems for the CB mixtures in the long term. As far as the laboratory tests for compatibility assessment problems are concerned, further information is provided in Manassero et al. (1995). In terms of further development, more research is needed to evaluate the temperature effects and desiccation problems, which can be particularly serious for SCOW mixtures. The hydraulic conductivity of SB slurry trench cutoff walls can be less than 10–9 m/s. The stress state in the SB backfill can have a strong influence on inservice hydraulic conductivity. Also, contaminated permeants can increase the hydraulic conductivity of barrier soil, but the effect is less significant when the soil is under high confining pressure. To measure the hydraulic conductivity, it is possible to perform laboratory or in situ tests. The main difficulty in performing the laboratory tests is to obtain undisturbed samples. In fact, to bore into the wall after construction is difficult due to the soft consistency of the backfill. Large-scale pumping tests can be difficult to interpret due to the impact of gravity drainage from porous soils as the groundwater level is lowered within the contained area and the possibility of leakage through an underlying aquitard. 2.4.5.2 Time-Varying Properties and Processes Properties of barrier materials often change in time as barrier materials age. A comprehensive experimental study on the curing time effect and solids content of CB mixtures was carried out by Fratalocchi (1996). The decrease in the hydraulic conductivity vs. time was fitted by an exponential equation of the type: ⎛ t⎞ K = Kr ⎜ ⎟ ⎝ tr ⎠

−α

(2.29)

where K and Kr are the hydraulic conductivities at time, t and tr , respectively, and the exponent, α is the coefficient of reduction of the hydraulic conductivity in time. The α parameter for the best fitting functions has also been related to the cement to water ratio. For other types of cement and/or bentonite, an independent determination of α is recommended (Manassero, 1996). The reduction of SB SCOW hydraulic conductivity vs. time is generally quicker than for CB mixtures. Due to the short drainage paths, most of the consolidation process of an SB mixture occurs in a few months and, after this period, the hydraulic conductivity reduction is negligible. On the other hand, an increase of hydraulic conductivity in the long term can occur using compatibility problems with the pollutants to be contained. 2.4.5.3 Influence of Coupled Solute Transport Vertical cutoff walls typically are designed to prevent or minimize the spread of a miscible contaminant plume in a groundwater aquifer as shown schematically

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Barrier Systems for Environmental Contaminant Containment & Treatment

in Figure 2.7. In the absence of pumping, a hydraulic gradient is established across the wall such that advective contaminant flux, Ja, typically occurs in the same direction as the diffusive flux, Jd (i.e., positive advection) (Figure 2.7a). As a result, breakthrough of the contaminant plume through the wall cannot be prevented without active pumping within the contaminant source area to reverse the hydraulic gradient such that the advective flux occurs opposite to the direction of diffusion (i.e., negative advection) (Figure 2.7b). In this case, contaminant breakthrough can be prevented if the diffusive flux is greater than the opposing advective flux. If the soil within the wall exhibits membrane behavior (i.e., ω > 0), chemicoosmotic flux of liquid from low concentration to high concentration (i.e., from the receptor side to the source side of the wall) results in a counter-advective contaminant flux, Jπ, that opposes Jd regardless of the direction of the hydraulic gradient. The advective contaminant flux in response to the hydraulic gradient is reduced by the factor (1 – ω) due to hyper-filtration, as explained previously. Thus, membrane behavior within the cutoff wall provides additional protection against contaminant breakthrough and can reduce the need for pump and treat to establish a counter-advective hydraulic gradient. The coupled solute flux equation (Equation (2.22)) indicates that the significance of the potential benefit of membrane behavior depends on the magnitude of the chemico-osmotic efficiency coefficient, ω, for the soil. 2.4.5.4 Membrane Behavior in Clay Soils Membrane effects (e.g., hyper-filtration, chemico-osmosis) are attributed to electrostatic repulsion of charged solutes (ions) by the diffuse double layers of adjacent clay particles that extend into the pore space (e.g., Hanshaw and Coplen, 1973; Marine and Fritz, 1981; Fritz and Marine, 1983; Fritz, 1986; Keijzer et al., 1997). As stated previously, a soil membrane that completely restricts the transport of ions and, thus, exhibits a chemico-osmotic efficiency coefficient equal to unity (i.e., ω = 1) is considered an ideal membrane. In this case, the diffusive double layers of adjacent particles overlap in the pore space, leaving no free space for solute transport. However, values of ω for clay membranes typically fall within the range 0 < ω < 1 because the pores vary over a range of sizes relative to the thickness of the diffuse double layers such that not all of the pores are restrictive (Kemper and Rollins, 1966; Olsen, 1969; Bresler, 1973; Barbour, 1986; Barbour and Fredlund, 1989; Mitchell, 1993; Keijzer et al., 1997). Thus, the degree of solute restriction and the resulting value of ω is affected by a combination of physical and chemical factors, including the state of stress on the soil, the types and amounts of clay minerals in the soil, and the types and concentrations of the solutes (Kemper and Rollins, 1966; Bresler, 1973; Olsen et al., 1990; Mitchell, 1993). In general, ω increases with an increase in stress (lower porosity), an increase in the amount of high activity clay minerals, and a decrease in the valence and concentration of the solute.

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Closed Symbols: Malusis and Shackelford (2002 b) Open Symbols: Kemper and Rollins (1966) Crossed Symbols: Kemper and Quirk (1972) 1.0 Chemico-Osmotic Efficiency Coefficient, ω

0.9

n = 0.74 NaCl

0.8

n = 0.78–0.80

0.8

n = 0.86

0.7

NaCl

n = 0.80

0.6 0.5

n = 0.84 KCl

0.5

n = 0.91

0.4

n = 0.84

0.3

n = 0.84

0.2 0.2 0.1 0.0 0.0001

CsCl

0.001

0.01

0.1

1

Average Salt Concentration (M)

FIGURE 2.9 Chemico-osmotic efficiency. (From Malusis, M.A. and Shackelford, C.D., 2002b. Journal of Geotechnical and Geoenvironmental Engineering, ASCE, 128(2), 97–106. With permission.)

For example, consider the effects of salt concentration and ion valence illustrated in Figure 2.9 (also see Kemper and Rollins, 1966). The results in Figure 2.9 pertain to recent tests performed at Colorado State University on bentonitebased geosynthetic clay liner (GCL) specimens using potassium chloride solutions, as described by Malusis et al. (2001) and Malusis and Shackelford (2002a,c). The results illustrate that ω can vary over almost the entire range of 0 < ω < 1. For a given porosity (n), values of ω increase with an increase in the average salt concentration across the soil and a decrease in valence (Ca2+ vs. Na+ or K+). Both of these trends are consistent with expected behavior, in that the thickness of the diffuse double layers of adjacent clay particles within the soil pores decreases as the ion concentration and cation valence in the pore water increases (e.g., Mitchell, 1993). The results in Figure 2.9 suggest that membrane behavior can be significant in clay soils containing an appreciable amount of sodium bentonite. Sodium bentonite often is the principal clay mineral in soil-based vertical cutoff walls for waste containment due to the low hydraulic conductivity (e.g., ≤ 10–7 cm/s) typically required in these applications. Thus, consideration of membrane effects

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Barrier Systems for Environmental Contaminant Containment & Treatment

may be warranted in predictive assessments of the waste containment performance of cutoff walls.

2.5 COMPLICATING FACTORS Several factors can complicate the rather simplified modeling approach described thus far. A brief discussion of some of these factors is provided here to indicate a sense of the potential problems associated with contaminant transport modeling in environmental geotechnics.

2.5.1 CONSTANT SEEPAGE VELOCITY ASSUMPTION Shackelford (1997) has observed that a potentially significant limitation in the analytical modeling approach for modeling contaminant migration using models based on the ADRE is the assumption of a constant seepage velocity. The assumption of steady-state flow is unrealistic, particularly in relatively short-term situations. A simplified analysis of the accuracy of the constant seepage velocity assumption for flow through a compacted clay liner was presented by Shackelford (1997). While admittedly limited in application, this analysis indicates that the constant seepage velocity assumption can lead to potentially unconservative results in that the depth of penetration of the contaminant front is underestimated in the short term. Thus, care should be exercised when using models based on solution to the ADRE for modeling scenarios that do not maintain a constant seepage velocity.

2.5.2 CONSTANT VOLUMETRIC WATER CONTENT ASSUMPTION Thus far, conditions in which the volumetric water content, θ, is constant (i.e., θ ≠ f (t)) have been assumed. However, complications arise in the formulation when the conditions initially are unsaturated and θ is not maintained constant [i.e., θ = f (t)], as in the case of transient infiltration processes. In these cases, the time-dependent change in θ affects the magnitude of the seepage velocity [i.e., v = f (θ)] and the dispersion coefficient [i.e., D = f (θ)]. A number of investigators have studied diffusive transport through unsaturated soils, including sandy clay loam (Rowell et al., 1967), clay and loam (Porter et al., 1960), silt (Rowe and Badv, 1996a), sand (Lim et al., 1994; Rowe and Badv, 1996b), and gravel (Conca and Wright, 1990; Rowe and Badv, 1996b; and Badv and Rowe, 1996). The diffusion coefficient for chloride has been shown to decrease with decreasing θ. In addition, Rowe and Badv (1996b) found that the following relationship could be used to estimate the effective diffusion coefficient in unsaturated soil, Dθ*. ⎛ θ − θ min ⎞ * Dθ* = ⎜ D ⎝ n − θ min ⎟⎠

(2.30)

Modeling of Fluid Transport through Barriers

129

where θmin = minimum volumetric water content at which there is no interconnected water through which diffusion can occur. For some soils, Rowe and Badv (1996b) found that θmin ≈ 0 such that Equation (2.30) reduces to: Dθ* =

θ * D n

(2.31)

Rowe and Badv (1996b) also experimentally and theoretically examined advective-diffusive transport through layered systems consisting of a near-saturated lower permanent liner over an unsaturated layer (including silt, fine sand, fine gravel, and 38-millimeter stone) and demonstrated that conventional theory (e.g., Rowe and Booker, 1987, 1994) could be used to obtain good predictions of contaminant transport provided that allowance was made for the effect of θ on D* through Equation (2.30). For low degrees of saturation, such as for stone, dispersion was found to be significant in the unsaturated zone for q ≥ 0.12 m/year, whereas diffusion was important for q = 0.017 m/year. The modeling formulation presented thus far includes only liquid-solid partitioning. The transport of volatile organic compounds (VOCs) also can lead to gas-liquid partitioning. Gas-phase diffusion coefficients of VOCs typically are 104 to 105 times higher than the corresponding liquid-phase diffusion coefficients. A detailed description of the influence of variably saturated conditions is beyond the scope of this chapter; a comprehensive presentation on the subject is provided by Charbeneau and Daniel (1993).

2.5.3 ANION EXCLUSION

AND

EFFECTIVE POROSITY

In some clay soils, anion exclusion or negative adsorption results from the repulsion of anions from the negatively charged surfaces of clay particles (e.g., Bohn et al., 1985). The exclusion of anions from the pores of clay soils during transport contributes to an effective porosity effect in terms of anion migration. That is, not all of the pore space is available for contaminant migration. In such cases, the effective porosity effect is indicated by values of Rd < 1 for nonreactive tracers, typically anions, where the actual value for Rd equals the effective porosity ratio, ne /n, where ne is the effective porosity and n is the total porosity (Shackelford, 1995a,b; Shackelford et al., 1997a,b). For example, Wierenga and van Genuchten (1989) attributed Rd values for Cl– of 0.78 to an effective porosity effect due to anion exclusion.

2.5.4 NONLINEAR SORPTION In formulating the adsorption process, linear sorption was assumed. However, in many practical applications, the contaminant concentrations are sufficiently high such that nonlinear adsorption isotherms result. In such cases, the partitioning between liquid and solid phases is a function of the pore water concentration. In

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Barrier Systems for Environmental Contaminant Containment & Treatment

the case of nonlinear adsorption, the standard form of the ADRE (Equation (2.10)) is not strictly applicable, and more complex numerical procedures are required. Approximate methods for utilizing analytical models with nonlinear adsorption isotherms are given by Shackelford (1993) for column tests and by Manassero et al. (1997) for diffusion tests. These approximate methods simplify the analyses considerably and tend to provide reasonably good indications of the extent of contaminant migration, particularly for cases where the advective flow rates are low. However, the approximate methods can result in significant errors in estimating the distribution of contaminants.

2.5.5 RATE-DEPENDENT SORPTION The local equilibrium assumption (LEA) for adsorption in the formulation of the retardation factor generally is valid when the reaction time between the adsorbate (contaminant) and the adsorbent (soil) is fast relative to the flow rate of the pore water. Khandelwal et al. (1998) examined the transport of organic solutes through SB barrier materials and concluded that deviations from local equilibrium were not likely significant. However, for relatively high flow rates that typically occur in coarse-grained systems such as aquifers, the LEA may not be strictly valid. In such cases, kinetic or rate-dependent (nonequilibrium) adsorption reactions may be required. In general, incorporation of kinetic or rate-dependent reactions in the governing transport equations requires a numerical solution, although the semi-analytical finite-layer technique recently developed by Rabideau and Khandelwal (1998b) may be used in some cases. The existence of a rate-dependent adsorption process tends to result in less adsorption than would be predicted based on the LEA. Thus, failure to recognize the existence of rate-dependent adsorption can result in an underestimation of the actual extent of contaminant migration.

2.5.6 ANION EXCHANGE Some soils possess the ability to adsorb anions as well as cations. In fact, anion exchange capacities (AEC) have been reported for some clay minerals as shown in Table 2.5. Thus, the common assumption that anions, such as Cl– and Br–, are nonreactive (i.e., Rd = 1) during transport may not be appropriate in all soils, particularly soils that contain appreciable amounts of the clay minerals with AEC > 0 as shown in Table 2.5. Measured adsorption of anions, principally Cl– and Br–, has been reported recently on the basis of both laboratory studies (Shackelford and Redmond, 1995; Alshawabkeh and Acar, 1996) and field studies (Seaman et al., 1995). Anion adsorption generally is attributed to a pH-dependent surface charge associated with exposed hydroxyls on the edges of clay minerals (layered silicates) and/or metal hydroxides (e.g., Fe2O3). In general, the exposed hydroxyls carry either a partial positive charge (–OHδ+) at low pH or a partial negative charge (–OHδ–) at high pH that results in the ability to adsorb either anions or

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131

TABLE 2.5 The Cation and Anion Exchange Capacities of Common Soil Minerals and Organic Matter Soil Component Illite (2:1) Smectite (2:1) Vermiculite (2:1) Kaolinite (1:1) Oxides/Hydroxides Organic matter

CEC (cmol/kg)

AEC (cmol/kg)

10–40 90–120 100–150 3–15 Below 5 200–400

1 1 1 3–5 5 0

cations, respectively. The partial charges on the exposed hydroxyls result from incomplete charge balance with the interior structure of the mineral. The pH at which the net anion adsorption capacity equals the net cation adsorption capacity is referred to as the zero point of charge (ZPC) or the point of zero charge (PZC). Thus, anion adsorption is favored for pH < ZPC, whereas cation adsorption is favored for pH > ZPC. However, as indicated by Shackelford and Redmond (1995), simultaneous adsorption of both anions and cations probably occurs during solute transport in soils that exhibit a pH-dependent surface charge.

2.5.7 COMPLEXATION Analyses performed using models based on the ADRE typically neglect the potential effects of complexation. For example, when a metal, M2+, is dissolved in water, the metal may exist in several different forms or complexes, such as free metal species, M2+, or as metal hydroxides such as MOH+ and M(OH)2. These three different complexes migrate at different rates due to the difference in charges and sizes associated with each species. For example, adsorption of these three species based on consideration of charge is expected to be favored in the following order: M2+ > MOH+ > M(OH)2. However, in most simplified modeling applications, the potential transport of complexed species is simply ignored and the transport is assumed to be associated with the principal free ionic form of the species (i.e., M2+). Thus, it is important to note that an evaluation of the contaminant transport of a given species may actually encompass the transport of several different complexed species that do not migrate at the same rate.

2.5.8 ORGANIC CONTAMINANT BIODEGRADATION Certain organic contaminants can diffuse readily through both geomembranes (e.g., Britton et al., 1988; Saleem et al., 1989; Park and Nibras, 1993; Park et al., 1995; Rowe et al., 1995, 1996a) and clay (e.g., Rowe et al., 1995, 1997). Consideration of biodegradation is important for modeling the potential impact of these contaminants. Studies of biodegradation of VOCs in leachate are limited.

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However, Rowe (1995) and Rowe et al. (1996b, 1997) showed that there can be substantial degradation both within the landfill and in the soil. The rate of degradation can have a profound effect on the suitability of different liner systems (Rowe et al., 1996a).

2.5.9 TEMPERATURE EFFECTS Although most of the transport parameters are functions of temperature, and a significant amount of study has been devoted to freeze-thaw effects on the hydraulic conductivity of fine-grained soils, temperature effects generally are ignored in modeling simulations that cover long-term effects. However, in some applications, temperature effects may not be negligible. For example, the large temperature gradients typically found between landfills (approximately 60°C) and the surrounding soil (approximately 20°C) may require incorporation of heat transport to provide accurate predictions of mass transport. Therefore, the potential effects of temperature should be recognized when extrapolating results over extended periods that involve significant temperature fluctuations.

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Rogers, V.C., Nielson, K.K. and Kalkwarf, D.R. (1984). Radon Attenuation Handbook for Uranium Mill Tailings Cover Design, NUREG/CR-3533, U.S. Nuclear Regulatory Commission, Washington, DC. Rowe, R.K. (1987). Pollutant transport through barriers. Proceedings of ASCE Specialty Conference, Geotechnical Practice for Waste Disposal ’87, Ann Arbor, June, pp. 159–181. Rowe, R.K. (1995). Leachate characterization for MSW landfills. Proceedings of the 5th International Landfill Symposium, Vol. 2, Sardinia, Italy, pp. 327–344. Rowe, R.K. (1998). Geosynthetics and the minimization of contaminant migration through barrier systems beneath solid waste. Keynote Lecture, 6th International Conference on Geosynthetics, Atlanta, IFAI. Rowe, R.K. and Badv, K. (1996a). Chloride migration through clayey silt underlain by fine sand or silt. ASCE Journal of Geotechnical Engineering, 122(1), 60–68. Rowe, R.K. and Badv, K. (1996b). Advective-diffusive contaminant migration in unsaturated sand and gravel. ASCE Journal of Geotechnical Engineering, 122(12), 965–975. Rowe, R.K. and Booker, J.R. (1985a). 1-D Pollutant migration in soils of finite depth. Journal of Geotechnical Engineering, ASCE, 111(GT4), 479–499. Rowe, R.K. and Booker, J.R. (1985b). 2D pollutant migration in soils of finite depth. Canadian Geotechnical Journal, 22(4), 429–436. Rowe, R.K. and Booker, J.R. (1986). A finite layer technique for calculating 3-dimensional pollutant migration in soil. Geotechnique, 36(2), 205–214. Rowe, R.K. and Booker, J.R. (1987). An efficient analysis of pollutant migration through soil (Chapter 2). In Lewis, R.W., Hinton, E., Bettess, P. and Schrefler, B. (Eds)., Numerical Methods in Transient and Coupled Systems, Wiley, New York, pp. 13–42. Rowe, R.K. and Booker, J.R. (1994). POLLUTE v. 6 — 1D Pollutant migration through a non-homogeneous soil. Geotechnical Research Centre, University of Western Ontario, London, Canada ©1983 (1990). Rowe, R.K., Quigley, R.M. and Booker, J.R. (1995). Clayey Barrier Systems for Waste Disposal Facilities. E. & F.N. Spon, Eds., Chapman and Hall, London, 390 pp. Rowe, R.K., Hrapovic, L. and Armstrong, M.D. (1996a). Diffusion of organic pollutants through HDPE geomembrane and composite liners and its influence on groundwater quality. Proceedings of the 1st European Geosynthetics Conference, Maastricht, October, pp. 737–742. Rowe, R.K., Hrapovic, L., Kosaric, N. and Cullimore, D.R. (1996b). Biodegradation of dichloromethane in leachate. North American Water and Environment Congress ’96, Anaheim, CA, June, paper 356 (CD Rom) 6 p, Session GW-9, Groundwater Contaminant Fate and Transport. Rowe, R.K., Hrapovic, L., Kosaric, N., and Cullimore, D.R. (1997). Anaerobic degradation of dichloromethane diffusing through clay. Journal of Geotechnical Engineering, ASCE, 123(12), 1085–1095. Rowell, D.L., Martin, M.W. and Nye, P.H. (1967). The measurement and mechanism of diffusion in soil. III. The effect of moisture content and soil solution concentration on the self diffusion of ions in soils. Journal of Soil Science, 18, 204–222. Rubin, H. and Rabideau, A.J. (2000). Approximate evaluation of contaminant transport through vertical barriers. Journal of Contaminant Hydrology, 40, 311–333. Saleem, M., AsfourAfa, Dekee, D. and Harrison, B. (1989). Diffusion of organic penetrants through low density polyethylene (LDPE) films: Effect of size and shape of the penetrant molecules. Journal of Applied Polymer Science, 37(3), 617–625.

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Sass, I., Caldonazzi, O. and deBeyer, T. (1997). The application of flowmonta for environmental problems. Proceedings of the International Conference on Containment Technology. St. Petersburg (Florida), pp. 489–498. Schroeder, P.R., Aziz, N.M., Lloyd, C.M. and Zappi, P.A. (1994a). The hydrologic evaluation of landfill performance (HELP) model: User’s Guide for Version 3, EPA/600/R-94/168a, September 1994a, U.S. Environmental Protection Agency Office of Research and Development, Washington, DC. Schroeder, P.R., Dozier, T.S., Zappi, P.A., McEnroe, B.M., Sjostrom, J.W. and Peyton, R.L. (1994b). The hydrologic evaluation of landfill performance (HELP) model: engineering documentation for version 3, EPA/600/R-94/168b, September 1994. U.S. Environmental Protection Agency Office of Research and Development, Washington, DC. Seaman, J.C., Bertsch, P.M. and Miller, W.P. (1995). Ionic tracer movement through highly weathered sediments. Journal of Contaminant Hydrology, 20, 127–143. Shackelford, C.D. (1988). Diffusion as a transport process in fine-grained barrier materials. Geotechnical News, 6(2), 24–27. Shackelford, C.D. (1989). Diffusion of contaminants through waste containment barriers, Transportation Research Record No. 1219, Geotechnical Engineering 1989, TRB, NRC, National Academy Press, Washington, DC, pp. 169–182. Shackelford, C.D. (1990). Transit-time design of soil liners. Engineering Geology, 29, 79–94. Shackelford, C.D. (1993). Contaminant transport (Chapter 3). In Daniel, D.E. (Ed.), Geotechnical Practice for Waste Disposal, Chapman & Hall, London, pp. 33–65. Shackelford, C.D. (1995a). Analytical models for cumulative mass column testing. In Acar, Y.B. and Daniel, D.E. (Eds.), Geoenvironment 2000, ASCE Geotechnical Specialty Publication No. 46, ASCE, New York, 355–372. Shackelford, C.D. (1995b). Cumulative mass approach for column testing. Journal of Geotechnical Engineering, ASCE, 121(10), 696–703. Shackelford, C.D. (1997). Modeling and analysis in environmental geotechnics: An overview of practical applications. In Kamon, M., (Ed.), 2nd International Congress on Environmental Geotechnics, IS-Osaka ’96, Vol. 3, Osaka, Japan, Nov. 5–8, Balkema, Rotterdam, pp. 1375–1404. Shackelford, C.D. and Redmond, P. (1995). Solute breakthrough curves for processed kaolin at low flow rates. Journal of Geotechnical Engineering, ASCE, 121(1), 17–32. Shackelford, C.D., Cotten, T.E., Rohal, K. and Strauss, S. (1997a). Acid buffering a high pH soil for zinc diffusion. Journal of Geotechnical and Geoenvironmental Engineering, ASCE, 123(3), 260–271. Shackelford, C.D., Cotten, T.E., Davis, M.M., Strauss, S.H. and Rohal, K.M. (1997b). Characterizing zinc migration through a high pH sand-clay mixture. XIV International Conference on Soil Mechanics and Foundation Engineering, Vol. 3, Hamburg, Germany, Sept. 6–12, Balkema, Rotterdam, pp. 1935–1938. Shackelford, C.D., Malusis, M.A. and Olsen, H.W. (2001). Clay membrane barriers for waste containment. Geotechnical News, 19(2), 39–43. Staverman, A.J. (1952). Non-equilibrium thermodynamics of membrane processes. Transactions of the Faraday Society, 48(2), 176–185. Steefel, C.I. and Yabusaki, S.B. (1996). OS3D/GIMRT, Software for Multi-ComponentMulti-Dimensional Reactive Transport, User Manual and Programmer’s Guide PNL-11166, Pacific Northwest National Laboratory, Richland, WA.

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Tausch, N. (1992). Recent European developments in constructing grouted slabs. Grouting, Soil Improvement and Geosynthetics, GSP No. 30, ASCE, Vol. 1, pp. 301–312. Tedd P., Paul V, Lomax C. (1993). Investigation of an eight year old slurry trench cut-off wall. Proceedings of International Conference Green ’93, Bolton University, Bolton, Balkema, Rotterdam. Tinoco, I., Sauer, K. and Wang, J.C. (1995). Physical Chemistry, Prentice-Hall, Upper Saddle River, NJ. Thibodeaux, L.J. (1981). Estimating the air emissions of chemicals from hazardous waste landfills. Journal of Hazardous Materials, 4, 235–244. Thornthwaite, C.W. and Mather, J.R. (1957). Instruction and tables for computing potential evapo-transpiration and the water balance, Publications in Climatology, 10(3), Drexel Institute of Technology, Centerton, NJ. van Genuchten, M.T. (1980). A Closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Science Society of America Journal, 44(5), 892–898. van Genuchten, M.Th. and Alves, W.J. (1982). Analytical solutions for the one-dimensional convective-dispersive solute transport equation. Technical Bulletin No. 1661, USDA, Washington, DC. Vogan, J.L., Focht, R.M., Clark, D.K. and Graham, S.L. (1999). Performance evaluation of a permeable reactive barrier for remediation of dissolved chlorinated solvents in groundwater. Journal of Hazardous Materials, 68, 97–108. Wierenga, P.J. and van Genuchten, M.Th. (1989). Solute transport through small and large unsaturated soil columns. Ground Water, 27(1), 35–42. Wilson, G.W. (1990). Soil evaporative fluxes for geotechnical engineering problems. Ph.D Thesis, University of Saskatchewan, Saskatoon, Canada. Wilson, G.W. (2002). Can apples be compared to cover systems. Waste Geotechnics, March. Wilson, G.W., Fredlund, D.G. and Barbour, S.L. (1994). Coupled soil-atmosphere modelling for soil evaporation. Canadian Geotechnical Journal, 31(2), 151–161. Wolery, T.J. (1992). EQ3/EQ6, a software package for geochemical modeling of aqueous systems, package overview and installation guide (version 7.0) Lawrence Livermore National Laboratory, Technical Report UCRL-MA-110662(1). Yabusaki, S., Cantrell, K., Sass, B. and Steefel, C. (2001) Multicomponent reactive transport in an in situ zero-valent iron cell. Environmental Science and Technology, 35, 1493–1503. Yeung, A.T. (1990). Coupled flow equations for water, electricity and ionic contaminants through clayey soils under hydraulic, electrical, and chemical gradients. Journal of Non-Equilibrium Thermodynamics, 15, 247–267. Yeung, A.T. and Mitchell, J.K. (1993). Coupled fluid, electrical, and chemical flows in soil. Geotechnique, 43(1), 121–134. Zhu, C. and Anderson, G. (2002) Environmental Applications of Geochemical Modeling, Cambridge University Press, Cambridge. Ziegler, C., Pregl, O. and Lechner, P. (1993). Pollutant transport through sealing medium in contaminated land and sanitary landfills. Proceedings of the 4th International Landfill Symposium, Sardinia ’93, Vol. 2, S. Margherita di Pula, Environmental Sanitary Engineering Centre (CISA), Cagliari, Italy, pp. 1599–1612. Zyvoloski, G.A., Robinson, B.A., Dash, Z.V. and Trease, L.L. (1997). Summary of Models and Methods for the FEHM Application — A Finite Element Heat- and MassTransfer Code, LA-13307-MS. Los Alamos National Laboratory, Los Alamos, NM.

3

Material Stability and Applications Prepared by* Craig H. Benson University of Wisconsin at Madison, Madison, Wisconsin

Stephan F. Dwyer Sandia National Laboratories, Albuquerque, New Mexico 3.1 OVERVIEW This chapter focuses on material properties and behavior for caps, cutoff walls, and permeable reactive barriers (PRBs), with an emphasis on understanding the mechanisms and factors that affect their durability in full-scale systems. Information obtained from laboratory tests are analyzed in this context. The reader is referred to the preceding book in the containment series, Assessment of Barrier Containment Technologies (Rumer and Mitchell, 1995), as well as Daniel (1993), Gavaskar et al. (1998), LaGrega et al. (2000), Blowes et al. (2000), Naftz et al. (2002), and Reddi and Inyang (2000) for detailed information on the general characteristics of barrier materials mix design approaches and performance issues. In this chapter, the emphasis is on fundamental factors and laboratory and field observations that relate to the long-term performance of materials used in constructing various types of containment systems. The overall performance of these systems has been analyzed holistically using the systems approach in Chapter 1. Chapter 2 dealt with models of water and contaminant fate and transport through components of containment systems. It is herein recognized that material properties * With contributions by David W. Blowes, University of Waterloo, Waterloo, Ontario, Canada; David A. Carson, U.S. Environmental Protection Agency, Nashville, Tennessee; Peter W. Deming, Mueser Rutledge Consulting Engineers, New York, New York; Jeffrey C. Evans, Bucknell University, Lewisburg, Pennsylvania; Glendon W. Gee, Battelle Pacific Northwest National Laboratory, Richland, Washington; Hilary I. Inyang, University of North Carolina at Charlotte, Charlotte, North Carolina; Stephan A. Jefferis, University of Surrey, Surrey, United Kingdom; Mark R. Matsumoto, University of California at Riverside, California; Gustavo Borel Menezes, University of North Carolina at Charlotte, Charlotte, North Carolina; Stanley J. Morrison, Environmental Services Laboratory, Grand Junction, Colorado; Scott D. Warner, Geomatrix Consultants, Oakland, California; John A. Wilkens, DuPont, Wilmington, Delaware

143

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play a significant role in overall system performance. This chapter is divided into three primary subsections, each of which addresses materials performance for a specific type of containment structure.

3.1.1 THE ROLE OF BARRIER MATERIAL MINERALOGY AND MIX COMPOSITION ON PERFORMANCE Earthen materials or geomaterials are the most frequently used materials in containment system barrier construction. Generally, barrier mixes are composites of particles of various sizes and minerologies. For barriers that are designed to minimize flow rates and retard contaminant solute transport through physicochemical interactions, clays are commonly used in mixes with silts; sands; and amendments such as resins, activated carbon, slags, polymers, and ash. The clays are usually alumino-silicates native to the barrier material, or they may be added to the barrier mix in cases where the natural clay content of the barrier material is insufficient to provide the required mix characteristics. In other cases, barrier materials are fabricated and used to provide specific functions. An example is a geomembrane that can be incorporated as a component into a containment structure for fluid retention, separation of clay to minimize the chance of attack by aggressive permeants, and diversion of gas flow to desirable control points. Table 3.1 provides a general listing of various characteristics of barriers that affect classes of phenomena that relate to the most significant barrier design objectives. Some of

TABLE 3.1 Containment System Design Considerations and Material Characteristics that are Usually Evaluated in Bench-Scale Tests Physico-Chemical Design Consideration Reduction of contaminant release and transport

Phenomena of Concern Advection

Diffusion Dispersion Leachability Chemical compatibility Physical durability

Significant Barrier Material Properties Hydraulic conductivity Density Moisture content Gradation Porosity Crack density Porosity Tortuosity Crack density

Inadequate retardation Chemical attack

Density Mineralogy relative to contaminant chemistry

Radiation transport

Density, mass attenuation coefficient

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145

the barrier parameters such as hydraulic conductivity, porosity, and crack density apply to compacted, cemented, and fabricated materials. For granular barrier materials that may be compacted or cemented into barrier layers, the component material mineralogy and specific surface area are key material factors that, in combination with the emplacement density, control the initial and long-term barrier material textures when exposed to physical stresses and chemical contact. Mineralogy controls the physico-chemical interactions (including the reactivity) of a barrier component with permeating fluids under a given environmental condition. Under the most frequently encountered temperature, pressure, and pH–Eh conditions in the field, clays (comprising mostly aluminosilicates) react with permeants much more aggressively than sands (comprising mostly silica). Because of their mineralogy, the charged clay surfaces present opportunities for the chemisorption of charged contaminants such as heavy metals as summarized by Inyang (1996) in Table 3.2. For a barrier material that has favorable mineralogy (i.e., a mineralogy that favors its interaction with permeating fluids in reactions that remove solutes without degrading the barrier), the opportunity for its interaction with the permeant is enhanced if its specific surface is high. The specific surface is the ratio of surface area to weight of a material, and it is inversely proportional to the grain size of the material. For surface reactions like cation exchange and adsorption that are prevalent in barriers, their role in increasing the contaminant distribution coefficients (i.e., cleaning the permeating fluid in terms of its entry vs. exit chemistries) increases as the specific surface of the component material increases, as reflected in results plotted by Milne-Home and Schwartz (1989) presented in Figure 3.1. Often, even when a specific barrier component exhibits a desirable material characteristic, it may not be adequate with respect to another characteristic. For example, a clay mineral such as sodium montmorillonite may be sorptive enough for heavy metals but inadequate in terms of providing strength against desiccation. Yet still, cost considerations usually preclude the use of single-component barrier systems in waste containment. Essentially, most barrier materials are composites, the proportions of which are designed to optimize performance characteristics at minimal cost. In the case illustrated in Figure 3.2, D’Appolonia (1980) evaluated the effects of fines (% minus #200 sieve) on the permeability of soil-bentonite (SB) backfill candidate materials and found that for both plastic fines and nonplastic/low-plasticity fines, the permeability decreased as the fines content increased. Permeability values for the plastic fines were generally lower than those of the nonplastic/low-plasticity fines. Presumably, the plastic fines comprise more moisture-sensitive or expansive minerals than the nonplastic/low-plasticity fines. Figure 3.3 shows the effects of bentonite (montmorillonite) content on the permeability of the SB backfill candidate material mixes. A bentonite content of 3% (by dry weight) was adequate to reduce the permeability values from 5 × 10–5 to 5 × 10–3 centimeters per second (cm/s) to about 10–7 cm/s for well-graded coarse materials. In another investigation that illustrates the optimization of mix composition to obtain a favorable material characteristic, Ryan and Day (1986) evaluated the

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TABLE 3.2 Sorption Characteristics of Soil Minerals and Chemical Additives for Hazardous and Radioactive Metals Single Component Material

General Properties

Metals Tested

Test Type

Test Conditions

Results

Montmorillonite (GarciaMiragaya and Page, 1976)

CEC = 94.8 meql/L; particle size <2 μm

Cd2+

Batch

Initial pH range = 4.6–7.3

Montmorillonite from Texas (Puls and Bohn, 1988) Vermiculite (Ziper et al., 1988)

Ca — saturated

Cd2+, Zn2+, Ni2+

Batch

Initial pH = 5.5, 6.5, 7.5

K — fixed, 500–1000 μm particle size, SSA = 22.5 m2/g Fine particles

Cd2+

Batch

Initial pH = 5.0, 10–9–10–5 M

0.9 moles of Cd2+ adsorbed per kg

Cd2+, Zn2+, Ni2+

Batch

Initial pH = 5.5, 6.5, 7.5

Pb2+

Batch

Mn2+, Co2+, Ni2+, Cu2+, Pb2+

Batch

Initial pH = 3.0. 4 g of Kaolinite in 40 mL of lead solutions Initial pH = 3–8. NaNO3 used to maintain selected ionic strength

Zn2+, Cd2+, Ca2+

Batch

Adsorption followed the order: Cd > Zn > Ni. 50% of metals were adsorbed within pH range 4.49–5.80 Maximum Pb2+ adsorption decreased at high pH due to precipitation Coordination chemistry of oxides affects adsorption. 50% of Cu2+, Pb2+, Co2+, Ni2+ removed at pH 4.5, 4.8, 6.3, 6.8, respectively Selectivity order: Zn2+ > Cd2+ > Ca2+

Kaolinite (Puls and Bohn, 1988)

Kaolinite (Yong and GalvezCloutier, 1993)

Goethite (iron oxide) (Coughlin and Stone, 1995)

Goethite (iron oxide) (Kuo, 1996)

LI = 61%, SSA = 24 m2/g; 84% below 2 μm SSA = 47.5 m2/g

Initial pH = 5.3–8.3. NaNO3 used to maintain selected ionic strength

95%, 95%, and 90% of Cd2+ sorbed by Na-, Ca-, and K-montmorillonite, respectively 50% of metals were adsorbed at pH range of 4–5.81

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TABLE 3.2 (continued) Sorption Characteristics of Soil Minerals and Chemical Additives for Hazardous and Radioactive Metals Single Component Material

General Properties

Metals Tested

Test Type

Test Conditions

Fly ash (Singer and Berkgaut, 1995)

Hydrothermal ly treated, CEC = 2.5–3 meq/g

Pb2+, Sr2+, Cu2+, Zn2+, Cd2+, Cs2+

Batch

Initial pH = 5.0. Total concentration of competing ions = 0.1 N

Pyrolusite (MnO2) (Ajmal et al., 1995)

Crushed samples

Pb2+, Cd2+, Zn2+, Mg2+

Batch

Washed and dried at 40°C; pH range of about 2–8

Results Selectivity order: Pb2+ > Sr2+ > Cu2+ > Cd2+ > Zn2+ > Cs2+ at 25 mg/L lead concentration, absorbed Pb = 35 μg/g At pH = 6.5, 100% of initial 22.7 mg/L of Pb2+ was sorbed; other results show high sorption for Zn2+ and Cd2+ but low sorption for Mg2+

Source: Inyang, H.I. (1996). Sorption of inorganic chemical substances by geomaterials and additives, Report CEEST/001R-96, University of Massachusetts, Lowell, MA.

permeability ranges of three mix compositions for a fly ash cement-slurry wall, the results of which are presented in Figure 3.4. Test results developed (Fleming and Inyang, 1995) for fly ash amended materials, which may, in some cases, exhibit cementation if the ash mineralogy is favorable or some cementing agents are added, show that initial and longer term permeabilities of cemented barrier materials can be significantly influenced by reactions among the mix components. Figure 3.5 shows the conceptual textural patterns proposed by Fleming and Inyang (1995) in a comparative study of the effects of class F (nonreactive) fly ash and class C (reactive) fly ash amendment of barrier clay on changes in permeability under freeze-thaw action. The patterns are similar, but the reactive fly ash exhibits initial and final permeabilities that are lower than those of the nonreactive ash.

3.1.2 APPROACHES

TO

MATERIAL EVALUATION

AND

SELECTION

Bench-scale tests provide the best opportunity to evaluate the fundamental characteristics of barrier materials. However, holistic assessments of a barrier system performance are most meaningfully performed through a combination of benchscale testing and field quality assurance and monitoring tests. The bench-scale approach has been widely used to evaluate barrier material parameters in batch

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Montmorillonite

1000

100 Specific surface (m2/g.)

Illite

Kaolinite

3 10

2 3

2

2

11 1

1 1

1

0.1 0.1

1

3

3 2

2

Explanation American Petroleum Institute Reference clays (Patchett, 1975) Shales (Patchett, 1975) Milk River formation Mome L’Enfer, Erin formations Belly River formation (GENPAR 2) Sandstones 1 Discrete particle clays 2 Pore ilning clays 3 Pore bridging clays

10 Bulk C.E.C. (meq/100 g)

100

FIGURE 3.1 Specific surface vs. bulk cation exchange capacity for various sediments and minerals. (From Milne-Home, W.A. and Schwartz, F.W., 1989. Proceedings of the Conference on New Field Techniques for Quantifying the Physical and Chemical Properties of Heterogeneous Aquifers, Dallas, Texas, pp. 77–98. With permission.)

systems, monoliths of scaled down dimensions, or columns of media. The latter can be densely compacted, as in the case of earthen materials considered for fluid/contaminant transport barriers or loosely emplaced as in reactive columns. Most of the granular barrier material characteristics that are usually targeted are summarized in Table 3.3. Not all of these tests need to be performed for all barrier materials. Some tests, exemplified by porosimetry, are not usually performed because the influence of the pore size distribution measured is represented along with barrier material density and reactivity with specific contaminants in data obtained from column tests for contaminant retardation coefficient estimation. The tests listed in Table 3.3 have designations that vary from one country to another, although they are most standardized under the American Society for

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80 70

% Minus #200 sieve

60

Plastic fines

50 Nonplastic or low plasticity fines

40 30 20 10

0

10−9

10−8

10−7 10−6 SB Backfill permeability, cm/sec

10−5

10−4

FIGURE 3.2 Effects of fines content on the permeability of soil-bentonite backfill. (From D’Appolonia, 1982. Proceedings of the 13th Annual Geotechnical Lecture Series, Philadelphia Section, American Society of Civil Engineers, Philadelphia, PA. With permission.)

Testing Materials (ASTM) protocols. As evident in Section 3.2, fabricated materials such as geomembranes are tested under protocols that are different from those of granular barrier materials. Fundamental tests are important because they can provide data that are helpful in performing a general durability evaluation of barrier materials and understanding mechanisms that are determinants of their durability.

3.1.3 GEOSYNTHETICS

AND THEIR

DURABILITY

IN

BARRIER SYSTEMS

In general, the ability of barrier materials to retard fluid transport, resist chemical and biological attack, and maintain structural integrity under externally imposed stresses depends on their composition, emplaced thickness, and the quality assurance practices implemented during construction. Early in the development of containment system design configurations, earthen and cementitious barrier materials were used almost exclusively. A more recent development, particularly within the past two decades, is an increase in the use of geosynthetic materials to enhance containment system barrier layer performance. Both earthen and geosynthetic barrier materials have advantages and disadvantages. Earthen barriers are most commonly clayey soils that are either compacted into layers as in landfills and surface impoundments or emplaced as slurry backfill as in slurry cutoff walls. While they can retard contaminant transit through a variety of processes (e.g., sorption, induced precipitation of dissolved substances within inter-particle pore spaces), significant variability and uncertainty can exist in the

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Barrier Systems for Environmental Contaminant Containment & Treatment 10–2

Permeability of SB backfill, cm/sec.

10–3 Well-graded coarse gradations (30–70% + 20 sieve) w/10 to 25% nonplastic fines

10–4

10–5 Poorly graded silty sand w/30 to 50% nonplastic fines 10–6

10–7

10–8

10–9

Clayey silty sand w/30 to 50% fines 0

1

2

3

5

4

% Bentonite by dry weight of SB backfill

FIGURE 3.3 Effects of bentonite content on the permeability of SB backfill. (From D’Appolonia, 1982. Proceedings of the 13th Annual Geotechnical Lecture Series, Philadelphia Section, American Society of Civil Engineers, Philadelphia, PA. With permission.) Average (typ.)

Mix 3 C/W FA/C Mix 1 0.20 0.00 Mix 2 0.20 0.24 Mix 3 0.25 0.60

Mix 2 Mix 1 10–7

10–6

10–5 K, (cm/sec.)

FIGURE 3.4 The effects of cement/water ratio and fly ash/cement ratio on the permeabilities of slurry wall mixtures. (From Ryan, C.R. and Day, S.R., 1986. Proceedings of the 7th National Conference on Management of Uncontrolled Hazardous Waste Sites, Washington, DC. With permission.)

spatial distribution of barrier transport parameters such as hydraulic conductivity and diffusion coefficient. Furthermore, under aggressive chemical environments and sustained desiccation processes, earthen barriers can develop enlarged flow channels that allow contaminants in both the gaseous and liquid phases to travel through the barrier easily. Geosynthetic materials such as geomembranes have less

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151

Before freezing a. Class F fly ash-modified clay soil

b. Class C fly ash-modified clay soil Reactive ash particle Clay platelet Reacted rim Nonreactive ash particle

After freeze - thaw cycling c. Class F fly ash-modified clay soil

d. Class C fly ash-modified clay soil

Longitudinal fracture

Permeability

PCA

POA PCB POB

0

tCB tCA No. of freeze-thaw cycles or time

FIGURE 3.5 Effects of reactions among barrier constituents on the permeability of ashmodified clayey barrier soil subjected to freeze-thaw cycling. (From Fleming, L.N. and Inyang, H.I., 1995. ASCE Journal of Materials in Civil Engineering, 7(3), 178–182. With permission.)

variability in the spatial distribution of transport parameter magnitudes because they are manufactured in tightly controlled processes. Furthermore, they are less permeable to fluids and offer the opportunity to minimize the overall design thickness of a barrier layer. On the other hand, punctures, poor joints, and internal degradation can diminish their effectiveness as barrier layers. Giroud et al. (1992, 1997) have developed quantitative methods for estimating liquid transport through geomembrane defects. Geosynthetic barrier materials have been used as barrier layers that complement the functions of earthen barrier layers. Many composite cover designs such

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TABLE 3.3 General Testing Approaches and Methods for Significant Characteristics of Batch and Compacted Barrier Materials Dependent Property

Densitya Dispersivity Gradation Hydraulic conductivitya,b Moisture content Path length/tortuositya Plasticityb Pore size distribution Porosity (effective)a

Test Method(s) Soil Texture Direct measurement Indeterminate; evaluate experimentally Sieve, hydrometer tests Permeameter tests Drying tests Indeterminate; evaluate experimentally Atterberg limits Porosimetry Empirical methods, porosimetry

Soil Composition Chemical (elemental) composition Chemical tests (e.g., x-ray fluorescence) Mineralogy (crystallinity) Mineralogy tests (e.g., x-ray diffraction) a b

Denotes a property dependent on compaction. Denotes a property dependent on mineralogy.

Source: Adapted from Inyang, H.I. et al. (1998). Physico-Chemical Interactions in Waste Containment Barriers, Encyclopedia of Environmental Analysis and Remediation, Vol. 2, Wiley, New York, pp. 1158–1165.

as those consistent with the minimum design standards developed for the Resource Conservation and Recovery Act (RCRA), comprise both soil barrier layers and geosynthetic materials. Othman et al. (1997) have performed studies of the performance of such barrier configurations in the field. The results indicate that with adequate quality control, such systems can perform effectively, at least within the few decades that they have been in service. Another composite barrier system that typically produces desirably low hydraulic conductivities in barrier systems is the geosynthetic clay liner (GCL) that has been studied by many researchers (Estornell and Daniel, 1992; Rad et al., 1994; and Petrov et al., 1997). The GCL is gaining wider acceptance in the containment industry because of its cost effectiveness, relatively easy installation, and low barrier thickness. Installation methods are summarized in Section 3.4.3. Although test protocols, design methods, and quality assurance methods have been developed [Koerner and Daniel, 1997; Haxo, 1987; United States Environmental Protection Agency (USEPA), 1985], concerns about the long-term durability of geosynthetic materials in barrier systems remain. This concern is driven by the knowledge that all materials that are exposed to stressors degrade with time. Such degradation in the long term is not limited to geosynthetic materials, but extends to emplaced earthen barrier materials as well. For geosynthetic

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materials that have been effectively installed, degradation mechanisms include aging, chemical attack, and photo-oxidation. To assess the potential effectiveness of geosynthetic barriers in containment systems over 500 service time frames, Badu-Tweneboah et al. (1999) analyzed prospective effects of various degradation processes of a 1.5-millimeter (mm)-thick high-density polyethylene (HDPE) geomembrane that was installed within a landfill cover. They used data from studies performed on geomembranes and other polymeric materials to evaluate the damage potential under sustained contact with aging agents such as oxygen, microorganisms, heat, ultraviolet radiation, and radioactivity, as well as flaw development due to abrasion, thermal stresses, animal burrowing, and plant root penetration. The analysis led to the conclusion that up to 5% reduction in yield strain can occur per 25 years of service, resulting in an estimated yield strain of zero if a liner deterioration pattern is assumed or 36% of the original yield strain in 500 years if a logarithmic deterioration pattern is assumed. On the basis of their analysis, Badu-Tweneboah et al. (1999) estimated that the progressive stiffening of the geomembrane due to molecular rearrangement under induced stresses in common containment system configurations would likely result in stress cracking after 300 years of service. The challenge is to relate the damage potential to flaw sizes and numbers — a necessary step for estimating potential fluid transport rates through geosynthetic materials.

3.2 MATERIAL PERFORMANCE FACTORS IN CAPS Caps or surface barriers in general are used to isolate buried wastes or contaminated soils from the atmosphere and biota on the earth’s surface. To design an effective cap, it is necessary to consider multiple objectives, including biota intrusion (i.e., intrusion of plants, animals, and humans into the underlying waste or contaminated soils), wind and water erosion, gas control, and percolation of water into underlying waste. The material performance criteria established for each of these objectives depend on the type of waste to be contained and the risks imposed by the waste on the nearby environment. For example, stringent mix design criteria may need to be used for facilities containing long-lived and toxic radioactive wastes, whereas less stringent criteria can be applied to facilities containing largely inert construction and demolition wastes. The life span over which the cap must function is generally associated with the type of waste as well (e.g., 1,000 years for radioactive wastes or 30 years for solid wastes). In most containment applications, however, there is no intent of ever exhuming the waste. Thus, a cap must meet the performance criteria as long as the material being contained poses a risk to the surrounding environment. In most cases, this means that caps need to be designed for perpetuity and that a plan be in place to monitor and maintain the cap as needed. Percolation from the base of the cap is the primary design criterion in most cases. A capping approach that will meet a percolation criterion (e.g., <1 mm/year) is usually selected. Then, the materials and geometry (e.g., layering) are selected and configured to meet the percolation criterion, as well as the other criteria

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Barrier Systems for Environmental Contaminant Containment & Treatment

Vegetated surface layer (150 mm)

Clay liner (>600 mm)

(a) Geocomposite drain

Geomembrane

Vegetated surface layer (150 mm)

Clay liner (>600 mm)

(b)

FIGURE 3.6 Profiles of caps relying on a resistive barrier: (a) Compacted clay barrier and (b) composite barrier.

(e.g., erosion, biota intrusion, gas control). Two general cap designs are used: resistive designs and water balance designs. Examples of resistive designs are shown in Figure 3.6; examples of water balance designs are shown in Figure 3.7. Resistive designs employ a barrier system with high hydraulic impedance to limit percolation (Benson, 2001). The barrier system can consist of geomembranes, fine-grained earthen materials, asphalt layers, or combinations of these or similar materials. A drainage system is often used to limit the driving head on the barrier and ensure physical stability. The water balance approach employs the store and release principle to limit percolation to an acceptable amount (Benson, 2001). Materials are selected that have adequate capacity to store infiltrating water during wet periods without appreciable percolation. Vegetation is used to remove the stored water and return it to the atmosphere so that the cover has the capacity to store water during subsequent infiltration events. The resistive and water balance design approaches are fundamentally different. The resistive design approach is predicated on constructing and maintaining a system that blocks natural water movement. In contrast, the water balance approach

Material Stability and Applications

155

Thick layer of finer-grained soil

Waste (a)

Finer-grained soil Capillary break Coarser-grained soil

(b)

FIGURE 3.7 Schematic water balance caps: (a) Monolithic cap design and (b) two-layer capillary barrier.

uses natural processes to limit natural water movement. The natural approach used for water balance covers is considered by some to be superior. The logic is that a system that works with nature (i.e., water balance cap) is believed to be less likely to fail over the long term than a system that works against nature (i.e., resistive cap). However, currently there is no direct evidence demonstrating that one approach is superior, provided that the cap is designed and constructed properly.

3.2.1 MATERIAL PERFORMANCE FACTORS

IN

COMPOSITE BARRIERS

Resistive designs generally employ engineered materials to provide the hydraulic impedance needed to meet a percolation criterion. These materials include compacted natural clays, bentonites used alone in layers (e.g., as in a geosynthetics clay liner) or mixed with other earthen materials (e.g., a compacted mixture of sand and bentonite), polymeric sheets known as geomembranes, and asphalt and asphalt concrete layers (Koerner and Daniel, 1997). During the last decade, a wealth of experience has accrued regarding the characteristics of these materials and the elements that are required to reduce percolation to small amounts. Experience has shown that systems that rely solely on an earthen barrier (i.e., compacted

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clay barrier or GCL) are prone to failure, even after short service lives, whereas composite designs that combine a geomembrane underlain by an earthen barrier appear to function extremely well, at least for the relatively short experience record (<10 years) that currently exists (Benson, 2001, 2002). The performance of caps that rely solely on a geomembrane or asphalt layer is largely unknown. The following two examples illustrate how resistive designs that rely solely on an earthen barrier can fail soon into their service lives. One is a cap employing a compacted clay barrier consisting of 460 mm of compacted clay placed on compacted subgrade and overlain with 150 mm of topsoil vegetated with Bermuda and rye grasses. This type of cap is often the presumptive remedy (i.e., the default design) for sites in the United States Superfund program, as was the case for the cap described here. The other is a similar design, except a GCL was used instead of a compacted clay barrier, and 600 mm of “protective cover soil” was placed between the GCL and the topsoil layer. The topsoil layer was vegetated with crown vetch to minimize erosion. The clay barrier was compacted in a manner that yielded a field hydraulic conductivity of 5 x 10–8 cm/s at the time of construction (the design criterion was 10–7 cm/s). The cap was intended to transmit less than 30 mm/year of percolation. Concerns about long-term cap performance led to installation of a system for monitoring all components of the water balance (Benson, 2002; Roesler et al., 2002) and, most importantly, the percolation rate. Water balance data collected from the cap since the time of construction are shown in Figure 3.8. 2000

250

1000

200

Drying soil

150 Evapo-transpiration

No rain

Percolation

500

100

Surface runoff 0 4/1/00

8/1/00

12/1/00

4/1/01

8/1/01

FIGURE 3.8 Water balance data for the clay cap.

12/1/01

4/1/02

50 8/1/02

Soil-water storage (mm)

Water applied, evapotranspiration, surface runoff, and percolation (mm)

Applied water Soil water storage

1500

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157

Approximately 10 months after construction (September/October 2000), a period with little precipitation persisted for approximately six weeks. During this period, the cap desiccated as evidenced by the monotonic decrease in soil-water storage during this period. Prior to this period, the cap transmitted percolation at rate of approximately 30 mm/year, which is consistent with the design criterion. Afterward, the percolation rate was approximately 500 mm/year (approximately one half of annual precipitation). Inspection of the clay barrier after it desiccated showed that the barrier contained desiccation cracks (Albright and Benson, 2002; Roesler et al., 2002) that served as preferential flow paths, causing the large percolation rate increases that were measured and the stair-step character of the cumulative percolation record. Concerns about the field performance of a cap that relies solely on a GCL also led to percolation rate monitoring using two 10 m by 10 m lysimeters (Thorstad, 2002). The cumulative percolation recorded by the lysimeters is shown in Figure 3.9. Excessive percolation was first noticed during the spring thaws of 1997. The GCL was exhumed in June 1997 and inspected to determine the cause of the excessive leakage rates. GCL thinning due to pressure applied by gravel in the lysimeter was the suspected cause of the high percolation rate, but no quantitative assessment of the failure mechanisms was made. A layer of sand was added to the lysimeter above the gravel as a cushion, a new GCL was installed, and the over-lying soil layers were replaced. Percolation monitoring continued after the lysimeters were rebuilt in 1997. Approximately 15 months after reconstruction, the percolation rate became excessive again. Monitoring continued until October 1999, when one of the lysimeters (BL2) was exhumed to inspect the GCL. Monitoring of the other lysimeter (BL1) continued. Percolation recorded by lysimeter BL1 continued relatively steadily and averaged 211 mm/year. Inspection of the GCL exhumed from directly over lysimeter BL2 revealed that the bentonite was dry and cracked. No thinning due to uneven pressure applied by the underlying soil was observed. Hydraulic conductivity tests on samples of the GCL exhumed from inside and outside the lysimeter showed a saturated hydraulic conductivity ranging between 1.4 × 10–6 cm/s and 1.0 × 10–4 cm/s or as much as 50,000 times the as-built hydraulic conductivity (2 × 10–9 cm/s). Chemical analysis showed that the exchange complex of the bentonite was dominated by calcium and magnesium, whereas sodium was originally the predominant cation (Thorstad, 2002). The exchange of calcium and magnesium for sodium reduced the swell potential of the bentonite sufficiently so that cracks that formed during drier periods could not swell shut during wetter periods. As a result, the hydraulic conductivity of the GCL became unacceptably high. When lysimeter BL2 was exhumed in October 1999, it was rebuilt using a composite barrier consisting of a thin (0.5 mm) polyethylene geomembrane heat bonded to one side of the GCL. This barrier was installed with the geomembrane down, as recommended by the manufacturer. The overburden soils removed during exhumation were replaced after the new GCL was installed. Very little percolation from the new GCL has been recorded during the two years of monitoring since

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Barrier Systems for Environmental Contaminant Containment & Treatment

Vegetated surface layer (150 mm)

Protective layer (600 mm) GCL

Silty base layer (600 mm) (a)

Original BL1 Original BL2 Rebuild BL1 1st rebuild BL2 2nd rebuild BL2 1996

800

1997

1998

1999

2000

2001

Cumulative percolation (mm)

700 600 500 400 300 1st rebuild

200

2nd rebuild BL2

100 0

0

500

1000

1500

2000

Elapsed time (days) (b)

FIGURE 3.9 Profile (a) and cumulative percolation record (b) for GCL cap.

installation (2.4 mm/year on average), suggesting that the composite barrier is far superior to the GCL alone. Positive field performance of caps that employ a resistive design with a composite barrier has been reported by others as well (Melchior, 1997; Dwyer,

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159

2001; Albright and Benson, 2002). Melchior (1997) reported percolation rates between 0.8 and 3.0 mm/year for a cap in Germany employing composite barrier design. The barrier consisted of 600 mm of clay (saturated hydraulic conductivity less than 10–7 cm/s) overlain by a 1.5-mm-thick HDPE geomembrane, a sand drainage layer 250 mm thick, and a vegetated topsoil layer 750 mm thick. Dwyer (2001) reported an annual percolation rate of 0.1 mm/year for a cap in semi-arid Albuquerque, New Mexico, having a design similar to Melchior’s cap. Dwyer (2001) also reported a percolation rate of 1.8 mm/year for a similar cap in Albuquerque employing a composite barrier with a GCL as the earthen component. The USEPA’s Alternative Cover Assessment Program (ACAP) is also monitoring the percolation rate from seven caps employing composite barrier layers consisting of a geomembrane underlain by a GCL or compacted clay barrier (Albright and Benson, 2002; Roesler et al., 2002). Percolation rates from these caps are summarized in Table 3.4. The percolation rates generally are near zero in semi-arid and arid climates, and less than 4 mm/year in humid climates. Thus, the composite barrier generally seems to be effective, largely because the geomembrane is nearly impervious and the fine-grained soil beneath the geomembrane provides impedance to flow at points where the geomembrane may contain defects. The exception is the cap located in Monterey, California. This cap is located in a semi-arid environment, but is transmitting 18 mm/year of percolation (Table 3.4). The cover soil placed on the geomembrane for this cap consisted of soil from

TABLE 3.4 Summary of Precipitation and Percolation Rates from Caps with Composite Barriers Monitored by ACAP

Site Altamont, CA Apple Valley, CA Marina, CA Boardman, OR Polson, MT Cedar Rapids, IA Omaha, NE

Duration (Days)

Climate

Total Precipitation (mm)

517 156 684 485 847 381 552

Arid Arid Semi-arid Semi-arid and seasonal Semi-arid and seasonal Humid and seasonal Humid and seasonal

487 115 466 181 744 772 719

Percolation (mm/year) 0.0 0.0 18.1 0.0 0.2 0.9 3.7

(0.0%) (0.0%) (3.9%) (0.0%) (0.1%) (0.1%) (0.5%)

Percentage of precipitation in parentheses. Source: Data from Albright, W. and Benson, C. (2002). Alternative Cover Assessment Program 2002 Annual Report, Publication No. 41182, Desert Research Institute, Reno, NV; Roesler, A. et al. (2002). Field Hydrology and Model Predictions for Final Covers in the Alternative Cover Assessment Program — 2002, Geo-Engineering Report No. 02-08, University of Wisconsin, Madison, WI.

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demolition projects and contained a variety of debris, including reinforcing bars and angular chunks of concrete. These materials may have caused puncturing of the geomembrane, which may be responsible for the higher percolation rates (Roesler et al., 2002). This example illustrates an important point: caps constructed with suitable barrier materials can function poorly if other aspects of the design are not properly implemented. Although the performance record for caps with composite resistive barriers is good, the record is short relative to the life span over which the caps are intended to function. Melchior’s study has the longest record (eight years). Dwyer’s record is four years, and the monitoring is continuing at ACAP sites. In general, composite barriers that have been exhumed appear to be in excellent condition even after several years of service, including those barriers located in the arid desert in southern California (Corser and Cranston, 1991; Melchior, 1997). Additionally, several studies suggest that geomembranes should perform adequately for hundreds of years, if not longer (Hsuan and Koerner, 1998; Clarke, 2002; Rowe and Sargam, 2002). However, these predictions are primarily heuristic or based on ancillary measurements (e.g., depletion rate of anti-oxidants). The reality is that little hard data exist that can be used to make reliable predictions regarding the life span of geomembranes in composite covers. Given the dearth of information on life expectancy, this is an area in need of research given that caps employing composite barriers are ubiquitous.

3.2.2 MATERIAL PERFORMANCE FACTORS BALANCE DESIGNS

IN

WATER

Water balance designs generally employ broadly graded finer-textured soils because of their capacity to store significant amounts of water with little drainage and their ability to deform without cracking. Coarse-grained materials are also used to form capillary breaks that enhance storage in the finer layer or divert water under unsaturated conditions. The coarse material can also be used to remove water from the barrier through advective drying (Albrecht and Benson, 2002; Stormont et al., 1994). Caps that employ a single layer of fine-textured soil are generally referred to as monolithic barriers, whereas those with two or more layers with contrasting particle size are referred to as capillary barriers (Figure 3.7). The performance record for water balance designs generally is shorter than that associated with resistive designs, although a large effort has been underway in North America during the last decade to collect field data on water balance caps (Khire et al., 1997; Ward and Gee, 2000; Dwyer, 2001; Albright and Benson, 2002). Perhaps the most notable monitoring program has been conducted at the semi-arid Hanford site (south-central Washington) for a cap designed to limit percolation to <0.5 mm/year. The cap is intended to have service life of 1000 years without maintenance [United States Department of Energy (USDOE), 1999; Ward and Gee, 2000]. A full-scale test section of the cap was constructed in 1994 and

Material Stability and Applications

161

Erosionresistant gravel admix Evapo-transpiration Precipitation (P)

(a)

Upper neutron probe access tube

Runoff Lateral drainge Existing grade Vertical Waste crib drainage

(b)

1

10

Clean fill side slope (pit run gravel) Neutron probe 50 access tube 1

(c) Upper silt w/admix 1.0 m Lower silt 1.0 m Sand filter 0.15 m Gravel filter 0.3 m Basalt rock Riprap 1.5 m Drainage gravel 0.3 m min. Composite asphalt Top course (asphaltic concrete 0.1 m min. coated w/fluid Sandy soil applied asphalt (structural) fill 0.15 m min.)

50

Basalt side slope 1 2

1

In situ soil

FIGURE 3.10 Hanford cross section of Hanford cap showing (a) interactive water balance processes, (b) gravel sideslope, and (c) basalt riprap sideslope.

has been monitored under natural conditions and conditions that are extremely wet for the region. Because a 1000-year life without maintenance was required, natural construction materials that are known to have existed in place for thousands of years were selected. The top-to-bottom profile consists of a 2-m-thick layer of vegetated siltloam overlying layers of sand, gravel, basalt rock (riprap), and asphalt (Figure 3.10). Each layer serves a distinct purpose. The silt-loam is for storing infiltration (600 mm of water can be stored in the silt loam before it will drain) and provides the medium for establishing plants that are necessary for transpiration. The coarser materials placed directly below the fine soil layer create a capillary break that enhances the storage capacity of the silt-loam. Placement of the silt-loam directly over coarser materials also creates an environment that encourages plants and animals to limit their natural biological activities to the near surface, thereby reducing biointrusion into the lower layers. The coarser materials also help deter inadvertent human intruders. The asphalt layer (asphalt concrete overlain by layer of fluid-applied asphalt) acts as a secondary barrier that employs a resistive approach to impede and divert water passing through the capillary break. A shrub and grass cap was established on the cap in November 1994. Two sideslope configurations, a clean fill gravel on a 10:1 slope and a basalt riprap on a 2:1 slope, were also part of the overall design and testing.

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Barrier Systems for Environmental Contaminant Containment & Treatment

From November 1994 through October 1997, sections of the cap were subjected to an irrigation regime of three times the long-term average annual precipitation, which included a simulated 1,000-year storm event (70 mm of water) during the last week of March for three years (1995 through 1997). Percolation did not occur from the cap until the third year, and then only a small amount (less than 0.2 mm) was transmitted from one section subjected to the enhanced irrigation treatment. No drainage has occurred since then from this section or from any other portion of the cap. In fact, the percolation that was recorded has been attributed to lateral flow from water diverted off an adjacent roadway rather than flow through the cap (USDOE, 1999). Despite the large amount of water that was applied, all available stored soil water was removed from the entire soil profile by late summer each year by evapo-transpiration (Figure 3.11), which maintained the water storage in the siltloam layer well below the estimated drainage limit of 600 mm. If the silt-loam thickness was reduced from 2 m to 1.5 m, the storage data indicate that little or no percolation would be expected. However, if the silt-loam thickness was

700 Nonirrigated average Irrigated average

2.0 m silt loam

Water storage (mm water)

600

500 1.5 m silt loam Drainage under natural conditions

400

1.0 m silt loam

300

200

100

0 9/30/1994

9/29/1996

9/30/1998 Date

9/29/2000

9/30/2002

FIGURE 3.11 Temporal variation in mean soil water storage in the silt-loam in the Hanford cap. Monitoring was interrupted 1998–2000. Horizontal dashed lines represent estimated storage limits for caps with silt-loam layers 2 m, 1.5 m, and 1.0 m thick. (From USDOE, 1999. 200-BP-1 Prototype Barrier Treatability Test Report. DOE/RL-99-11, U.S. Department of Energy, Richland, WA; Ward, A. and Gee, G., 2000. In Looney, B. and Falta, R. (Eds.), Vadose Zone Science and Technology Solutions, Battelle Press, Columbus, OH, pp. 1415–1423. With permission.)

Material Stability and Applications

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reduced to 1 m, it appears that the cap would not perform well under extremely wet conditions. The cap tested at Hanford represents perhaps the most sophisticated and redundant type of water balance design ever considered. The level of complexity associated with the cap is needed for the radioactive wastes that it is designed to isolate. For many sites (e.g., municipal solid wastes, demolition debris, contaminated soils), however, less sophisticated water balance caps are needed. An assessment of more typical water balance caps is being conducted by ACAP under natural climatic conditions (Bolen et al., 2001; Albright and Benson, 2002). The caps tested by ACAP are intended to meet a target percolation rate that ranges between 3 and 30 mm/year depending on the type of waste, the regulations in place at each site, and the climate (semi-arid or arid vs. humid). Laboratory measurements of unsaturated and saturated soil properties were used in conjunction with common methods accepted in practice to design each cap (Bolen et al., 2001). Typically, an unusually wet condition was used for the design calculations. Percolation rates measured for the ACAP water balance caps as of April 2002 are summarized in Table 3.5, along with the design percolation rates. Nine monolithic barriers and five capillary barriers are being evaluated. The design criterion is being achieved at eight of the 10 semi-arid sites, but at none of the humid sites. The factors contributing to the higher than anticipated percolation rates are currently under evaluation, but the data do illustrate that water balance caps do not necessarily perform as intended. One key factor contributing to the higher than anticipated percolation rates appears to be the influence of pedogenesis on hydraulic properties near the surface. Samples are currently being collected from the surface of each test section as large undisturbed blocks to characterize the hydraulic property changes that have occurred. A summary of the saturated hydraulic conductivity measurements obtained to date is provided in Table 3.6. The saturated hydraulic conductivity has increased due to factors such as desiccation and root penetration at three of the four sites for which tests have been conducted. At the fourth site, the hydraulic conductivity has remained about the same. Understanding how the hydraulic properties change over time is critical to predicting how water balance caps will perform over the long term. Long-term performance prediction is an issue in need of research before water balance caps can be considered a long-term solution for containment. Another important issue probably contributing to higher than anticipated percolation rates is scaling between hydraulic properties measured in the laboratory and those operative in the field. Additional study of scaling issues and how they can be incorporated in design is needed to understand long-term cap performance.

3.2.3 COUPLING OF VEGETATION PERFORMANCE FACTORS

AND

MATERIAL

Vegetation is not a cap material per se like soils and geosynthetics, but it is critical to the long-term behavior of most caps, as discussed in detail in Chapter 1.

3 3 3 3 3 30 3 3

3 3 3 3 Semi-arid and seasonal Semi-arid and seasonal Semi-arid and seasonal Semi-arid and seasonal Semi-arid Humid Humid and seasonal Humid and seasonal Humid and seasonal

552

Arid Arid Semi-arid Semi-arid and seasonal

Climate

847 905 485 485 607 722 381 552

517 156 684 847

Duration (Days)

Percentage of precipitation in parentheses.

Monticello, UT Albany, GA Cedar Rapids, IA Omaha, NE

Polson, MT Helena, MT Boardman, OR

Altamont, CA Apple Valley, CA Marina, CA Sacramento, CA

Site

Design Criterion (mm/year) Monolithic barrier Monolithic barrier Capillary barrier Monolithic barrier 1080 mm thick Monolithic barrier 2450 mm thick Capillary barrier Monolithic barrier Monolithic barrier 1220 mm thick Monolithic barrier 1840 mm thick Capillary barrier Monolithic barrier with trees Monolithic barrier with trees Capillary barrier, 760 mm storage layer Capillary barrier, 1060 mm storage layer

Cover Type

719

744 385 181 181 514 1983 772 719

487 115 466 744

Total Precipitation (mm)

(0.3%) (0.0%) (13.3%) (11.1%) (0.7%) (0.1%) (0.0%) (0.0%) (0.0%) (0.0%) (7.2%) (15.6%) (0.5%) 3.7 (0.5%)

1.0 0.0 61.8 48.4 3.1 0.2 0.0 0.0 0.0 0.0 91.3 143.1 3.7

Percolation (mm/year)

TABLE 3.5 Design and Measured Percolation Rates and Precipitation Summary for Water Balance Caps Monitored by ACAP

164 Barrier Systems for Environmental Contaminant Containment & Treatment

Material Stability and Applications

165

TABLE 3.6 Summary of Saturated Hydraulic Conductivities of Samples Retrieved from the Surface of Covers being Monitored by ACAP Geometric Mean Hydraulic Conductivity (cm/s) Site Albany, GA Cedar Rapids, IA Helena, MT Polson, MT

End of Construction 1.9 1.5 5.0 4.9

× × × ×

10–7 10–5 10–7 10–5

Summer 2002 2.8 4.6 1.6 1.3

× × × ×

10–5 10–4 10–7 10–4

Vegetation reduces erosion and, for water balance caps, is mostly responsible for removing water stored in the cap. There are three important factors that affect the success associated with establishing vegetation: proper preparation of the cap surface (e.g., not over-compacted), provision of nutrients, and selection of vegetation that is consistent with the surrounding environment (e.g., a heavy grass cover should not be used for a water balance cap in the desert of Las Vegas, Nevada). When these issues are considered during design and construction, vegetation has largely been successful. For example, at the Hanford site, the survival rate of transplanted shrubs has been remarkably high (97% for sagebrush and 57% for rabbitbrush). Heavy invasions of tumbleweed have occurred (e.g., in 1995), but have not persisted. Grass cover consisting of 12 varieties of annuals and perennials, including cheatgrass, several bluegrasses, and bunch grasses, currently dominates the surface. Approximately 75% of the surface remains covered by vegetation requiring no maintenance, which is a value typical of shrub-steppe plant communities (Gee et al., 1996). A similar example is shown in Figure 3.12 for the water balance caps at the ACAP site in Sacramento, California. Within one year of construction, a healthy cover of grasses and forbs was established with a leaf area index on the order of 1.4 (Roesler et al., 2002). Characterizing the transpiration that can be expected from vegetation is a more challenging issue (Figure 3.13). Figure 3.13 shows water balance quantities for the thinner (1,080 mm) monolithic water balance cap in Sacramento being monitored by ACAP (test section on right-hand side of photographs shown in Figure 3.12). During the first growing season after construction (2000), the vegetation was able to extract the water and deplete the soil-water storage to the wilting point (approximately 180 mm), thereby providing an adequate soil reservoir for storing water during the subsequent winter. However, the vegetation was far less effective in extracting the water in Spring 2001, even though the precipitation record was similar in both years, the water stored at the end of both wet seasons was comparable (approximately 400 mm), and the vegetation

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Barrier Systems for Environmental Contaminant Containment & Treatment

(a)

(b)

FIGURE 3.12 ACAP test sections in Sacramento, CA, at the end of construction (a) and one year after construction (b).

appeared no different during either growing season. Despite these similar conditions, the vegetation removed approximately 140 mm less water during the 2001 growing season. Inadequate water removal resulted in inadequate storage capacity the following wet season. As a result, the storage capacity (approximately 430 mm) was quickly exceeded during the wet period, and most of the water that infiltrated the cap surface became percolation. The inadequate transpiration observed during the 2000 growing season did not persist. During the 2001 growing season, the vegetation removed all of the available stored water. However, the reason for these differences remains a mystery, and efforts are currently underway to better understand why transpiration was greatly lower in 2001. This example illustrates, however, that characterizing and understanding the characteristics of vegetation is as important as understanding other materials used for caps, particularly for water balance caps that rely on transpiration as a critical barrier system process.

Material Stability and Applications

167 200

1080-mm monolithic cover

Precipitation

1200

150

Evapo-transpiration

1000 800

100 Percolation

600 Surface runoff 400

50 Soil-water storage

200 0 7/1/99

Percolation and surface runoff (mm)

Cumulative precipitation, evapo-transpiration, and soil-water storage (mm)

1400

3/31/00

12/30/00

9/30/01

7/1/02

0

FIGURE 3.13 Water balance quantities for thin cover (1080 mm thick) monolithic water balance covers being monitored by ACAP in Sacramento, CA. (Data from Roesler et al., 2002. Field Hydrology and Model Predictions for Final Covers in the Alternative Cover Assessment Program — 2002, Geo-Engineering Report No. 02-08, University of Wisconsin, Madison, WI; Albright, W. and Benson, C., 2002. Alternative Cover Assessment Program 2002 Annual Report, Publication No. 41182, Desert Research Institute, Reno, NV.)

3.3 MATERIAL PERFORMANCE FACTORS IN PRBS In contrast to most containment systems, which are usually designed to impede the flow of water, PRBs provide containment by treating contaminated water that passes through them. PRBs rely on a reactive material placed in the subsurface (or manipulation of the physico-chemical properties of the subsurface environment) to treat contaminated groundwater (Figure 3.14). As contaminated water passes though the PRB, reactions occur between the contaminants and the reactive medium, resulting in effluent that meets a target concentration, such as a maximum contaminant level (MCL) (depicted as “remediated water” in Figure 3.14). A variety of reactive media are used for PRBs, including granular iron metal, granular activated carbon, zeolitic minerals, compost, limestone, and other “solid” materials placed in the subsurface to promote the physical, chemical, and biological conditions necessary for contaminated groundwater treatment. A summary of many of the materials being used is provided in Table 3.7. A photograph of granular iron and clinoptilolite is shown in Figure 3.15. The most commonly used treatment material is granular iron metal, which is effective for treating groundwater affected by both organic and inorganic constituents (Gillham and O’Hannesin, 1994). Although the proportion of all PRB applications using granular iron has not been computed, a reliable estimate is that 70% to 90% of PRBs installed as tests or full-scale applications have used

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Barrier Systems for Environmental Contaminant Containment & Treatment

(a) Waste area

ARTZ Groundwater Flow direction

Aquifer

Plume

Remediated water

FIGURE 3.14 Schematic of a PRB used to intercept and treat a plume of contaminated groundwater.

TABLE 3.7 List of Reactive Materials that have been Used in PRBs Treatment Materials Zero-valent metals (including iron) (may or may not include metal couples) Ferric oxides Zeolites Activated carbon Limestone Compost Alumina Peat, humate Sawdust, compost Oxygen Phosphates

Contaminants Treated Methanes, ethanes, ethenes, propanes, chlorinated pesticides, freons, nitrobenzene, certain metals (Cr, U, As, Tc, Pb, Cd) Mo, U, Hg, As, P, Se Sr, Pb, Al, Ba, Cd, Mn, Ni, Hg, certain organics Mo, U, Tc, chlorinated VOCs, BTEX Cr, Mo, U, acidic water Metals, acidic water As Mo, U, Cr, As, Pb Nitrate Aromatic hydrocarbons, MTBE, vinyl chloride Mo, U, Tc, Pb, Cd, Zn

granular iron as the reactive medium. Other materials, such as granular activated carbon (GAC), compost, crushed limestone, alumino-silicates such as zeolitic minerals, and other materials are less used thus far, but are being tested in a variety of diverse applications.

3.3.1 APPROACH

TO

SELECTION

OF

PRB MATERIALS

The criteria for selecting a reactive material are described by Blowes et al. (2000) and include an assessment of the range of materials that can be used to remove contaminants and an assessment of the duration of material reactivity. These criteria, coupled with an assessment of the potential for the release of hazardous

Material Stability and Applications

169

FIGURE 3.15 Examples of reactive media used in PRB applications: granular iron metal (left) and the zeolite clinoptilolite (right). U.S. quarter shown for scale.

materials or contaminant by-products (e.g., release of vinyl chloride due to the reductive dechlorination of dichloroethylene), can be used to assess the potential of the barrier material to provide adequate groundwater treatment. Interactions between natural groundwater constituents can result in extensive formation of secondary mineral precipitates within the barrier. These precipitates can hinder barrier performance by clogging the pore space and reducing barrier permeability, or by obscuring reactive particle surfaces. The assessment can be combined with an understanding of contaminant concentrations, groundwater geochemistry, and site hydrogeology to determine whether a practical remedial system can be constructed. Then, a preliminary cost estimate can be developed and compared to remedial alternative estimates. Implementation of a remedial system employing a PRB can proceed through a series of steps, with accompanying decision points leading to the installation of an optimized system. These steps start with a theoretical assessment of the potential for treatment using existing PRB materials. State and federal guidance manuals have documented the PRB materials that were employed at existing PRB installations, the contaminants that were treated, and the contaminant removal that was attained [e.g., Interstate Technology Regulatory Council (ITRC), 1999a,b]. This information can be used in conjunction with theoretical calculations, such as the use of geochemical speciation/mass transfer computer codes or the use of

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Barrier Systems for Environmental Contaminant Containment & Treatment

pH–Eh diagrams to assess the potential for contaminant removal. If contaminant removal is possible, then laboratory treatability testing is considered. Laboratory treatability tests can be used to assess the potential for contaminant removal and develop reaction parameters to assist in barrier design. Batch experiments can be conducted to determine contaminant reactivity and measure reaction rates under static conditions. Column experiments can be used to measure rates of contaminant removal under dynamic flow conditions and assess the potential for the precipitation of secondary minerals and barrier clogging. Where possible, mineralogical examination of column materials following the testing program can be used to verify the presence and structure of secondary precipitates to assess the stability of these precipitates within the barrier and evaluate the potential for barrier clogging. Complementary geochemical modeling, including reactive transport modeling, can be used to develop design parameters at this stage. The geochemical modeling, coupled with groundwater flow and transport modeling, can be used to provide preliminary estimates of barrier performance and longevity and to design parameters for pilot- or full-scale installations.

3.3.2 EVALUATION OF FIELD PERFORMANCE USING PILOT TESTING The decision whether to conduct a pilot-scale test or move directly to full-scale implementation depends on the history of the technology and the confidence of the client and regulators. Many PRB technologies have been demonstrated sufficiently to satisfy regulators that the treatment processes are well understood and the installation success depends on site-specific processes. Pilot-scale installations vary in scale and degree of monitoring, from small-scale column experiments conducted ex situ at a field site to large-scale installations that ultimately form a portion of a full-scale PRB. The key objective of the pilot-scale installation is to simulate conditions in a full-scale system as closely as possible. Using the candidate reactive materials and natural aquifer materials in contact with site groundwater and typical contaminant concentrations provides a close approximation to the characteristics of full-scale systems. The small size of pilot installations provides an opportunity for monitoring at a level of detail that is sufficient to provide design parameters for the full-scale installation. Pilot-scale installations should be sufficiently versatile so that variability in treatment media and groundwater flow rates can be assessed. The results of the pilot-scale installation can be used to confirm contaminant reactivity and assess the potential for negative secondary reactions such as scaling or clogging. The pilot-scale system should also have well-defined dimensions and performance characteristics to simplify scaling up to the final remedial system. One type of cost-effective in situ pilot test is conducted with a reactive test well (RTW) consisting of reactive material placed in a 300-mm-diameter borehole (Figure 3.16). One or more 25-mm-diameter polyvinyl chloride (PVC) casings

Material Stability and Applications

171 Groundwater samples

Bentonite seal Reactive material in 300-mm borehole Groundwater

Slotted well casing

FIGURE 3.16 RTW using passive groundwater flow.

are placed along the central axis of the borehole for groundwater sampling. Several well casings with slots at different depths can be used to obtain multiple samples at different depths. A peristaltic pump is used to collect low-flow samples from the slotted section of each casing for analysis. RTWs were first used to test the efficacy of different reactive media for removing arsenic from groundwater at a DuPont site in East Chicago, Indiana. Data collected from the RTWs over a nine-month period were used to select PRB material. Basic oxygen furnace (BOF) slag was selected for use in the PRB based on data collected from RTWs, whereas laboratory studies indicated that another material was more appropriate. The coaxial configuration of the RTW ensures that groundwater passed through approximately 75 mm of reactive material before sampling regardless of the local groundwater flow direction. For accelerated tests, groundwater can be continually extracted through the casing. Because RTWs are simpler and less costly than a full-scale pilot wall, multiple RTWs can be installed at a given site to test different materials or act as controls. RTWs also have several advantages over ex situ field demonstrations (Table 3.8). Installation quality is important in a RTW providing reliable data. The drilling process should not create a smear zone at the well interface that might impede flow. Centrality of the well casing is also important so that the flow path through the reactive medium is the same at all points in the well. A centralizer consisting of a plastic disk with threads that match the well string is generally placed at the bottom of a RTW, along with conventional stainless-steel centralizers along

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Barrier Systems for Environmental Contaminant Containment & Treatment

TABLE 3.8 Comparison of Reactive Test Wells vs. Ex Situ Field Tests Parameter

Groundwater chemistry Contaminant losses in system Potential data quality Flow rate through bed

In Situ Reactive Test Well

Ex Situ Packed Columns

Key Technical Parameters Actual Essentially none High Natural (uncontrolled, cross-flow); or enhanced (pumped), radial flow

Can be different Can be significant Varies significantly Controlled, precise, axial

System complexity Effluent disposal Multiple location tests Duration limit Weather protection required

Logistical Parameters Low None Concurrent Unlimited, at low cost None

Medium to high Problematic Sequential Limited by cost, etc. Can be significant

Final wall approximation Technical certainty Special potential

Overall Assessment Very close; a mini-wall High Long-term performance evaluation

Approximation Varies significantly Precise flow control

the length of the well casing (Figure 3.17). The stainless-steel centralizers are installed above the slotted section so that the water being sampled is not exposed to any extraneous reactivity. Data from a RTW can be interpreted at several levels, from strict demonstration of contaminant removal to development of break-through and capacity correlations and projections of service life. By manipulating flow rates, kinetic expressions can also be developed. A passive RTW (i.e., operating under natural groundwater flow conditions) can provide an assessment of effectiveness in nearly real time, i.e., one month of field data is equivalent to one month of ultimate PRB exposure. To project the ultimate life of a PRB, an extractive RTW can be employed. In this technique, groundwater is pumped out of the central casing at an accelerated rate, analogous to using higher throughputs in a laboratory column. Avoiding kinetic limitations (i.e., from an extraction rate that is too high) with an extractive RTW is important unless a kinetic study is intended. An appropriate rate should be determined in the laboratory and then translated to the field test.

3.3.3 EFFECTS OF HYDRAULIC CONSIDERATIONS MATERIAL PERFORMANCE

ON

REACTIVE

To date, PRB research has focused mostly on the reaction mechanisms, kinetics, and conversion efficiency associated with the reactive materials (Tratnyek et al., 2003). Much less effort has focused on factors that affect PRB hydraulics, even

Material Stability and Applications

173

FIGURE 3.17 Centralizers for maintaining casing position in a RTW: Base centralizer (left) and stainless steel centralizer (right).

though hydraulic factors can have as large an impact on PRB effectiveness (Eykholt et al., 1999; Elder et al., 2002). As more PRB systems are implemented and monitored, performance data suggest that hydraulic characteristics of PRB materials need to receive greater attention during design. Recent reviews of PRB applications have suggested that most cases of unintended performance are due largely to inadequate hydraulic performance. Few cases are related to inadequacies in the chemical treatment methodology (Warner and Sorel, 2001; Battelle, 2002). These findings indicate that designers need to consider hydraulics as a critical factor affecting successful PRB deployment, and approach hydraulic design with the same level of care as reaction effectiveness. Hydraulic aspects that can have a large impact on PRB effectiveness are aquifer material heterogeneity and spatial variability of the groundwater flow field. The importance of geological heterogeneities and the need for characterization was illustrated in a recent case study of a PRB constructed near Kansas City, Missouri (Laase et al., 2000). The PRB was installed in an alluvial aquifer to intercept a plume containing trichloroethylene (TCE). Data from a hydrogeological study were used as input to a groundwater model used to select PRB orientation and breadth. The breadth was to be sufficiently

174

Barrier Systems for Environmental Contaminant Containment & Treatment

Plume

N

PRB Flow

FIGURE 3.18 Schematic of plume bypassing southern end of PRB installed near Kansas City. (Adapted from Laase, A. et al., 2000. In Wickramanayake, G. et al. (Eds.), Chemical Oxidation and Reactive Barriers, Remediation of Chlorinated and Recalcitrant Compounds, Battelle Press, Columbus, OH, pp. 417–424).

large to capture the entire width of the plume. An extensive set of monitoring wells (12 upgradient, 16 downgradient, and 10 adjacent to the ends of the PRB) was installed to monitor influent and effluent conditions and check for bypassing. Data from the monitoring program showed that the wall was not functioning as intended. While the reaction mechanisms appeared to have been accounted for properly, a sandy gravel region toward the southern end of wall was not detected during hydrogeological characterization and caused a portion of the plume to bypass the PRB, as shown in Figure 3.18. In addition, reversals in the hydraulic gradient during recharge events caused the southerly extent of the plume to curl northward and, at times, flow backward through the PRB. Bypassing was occurring along the northern end of the PRB as well. Few PRBs are monitored as closely as the PRB in Kansas City. Thus, the frequency of problems caused by heterogeneity is unknown. However, a recent modeling study by Elder et al. (2001, 2002) suggests that geological heterogeneity may be having a much larger impact on PRB effectiveness than previously thought. Elder et al. (2001, 2002) constructed a series of heterogeneous aquifers containing PRBs and simulated flow and transport through the aquifer and PRB. Because a model was used, effluent concentrations were characterized in far greater detail than is possible in the field, even with a dense network of monitoring wells. Typical results reported by Elder et al. (2001, 2002) are shown in Figure 3.19. The simulation consisted of a TCE source with a uniform concentration of 1000

Material Stability and Applications

175

Elevation (m)

(a) Source concentrations 10 8 6 4 2 0 0

5

10

15

20

25

30

35

40

45

40

45

40

45

Lateral distance (m) (b) Influent concentrations

Elevation (m)

10 8 6 4 2

Boundary of PRB

Monitoring well screens

0 0

5

10

15

20

25

30

35

Lateral distance (m) (c) Effluent concentrations

Elevation (m)

10 8 6 4 2

Boundary of PRB

Monitoring well screens

0 0

5

10

15

20

25

30

35

Lateral distance (m)

01 0.

0. 1

1

5

10

0 10

0 50

10

00

TCE Concentration (mg/L)

FIGURE 3.19 Concentrations at source (a), influent face of PRB (b), and effluent face of PRB (c) in a heterogeneous aquifer. (Adapted from Elder, C. et al., 2002. Water Resources Research, 38(8), 27-1 to 27-2).

micrograms per liter (μg/L) located 20 m upgradient of the PRB. By the time the plume reached the PRB, dispersion induced by aquifer heterogeneities caused the TCE concentration to range from 0.1 to 1000 μg/L. As groundwater flowed through the wall, the TCE concentration decreased, but not always below the target level (5 μg/L). In fact, the effluent concentration was as high as 500 μg/L

176

Barrier Systems for Environmental Contaminant Containment & Treatment

in some locations. These high concentrations were due to preferential flow through the wall as a result of heterogeneity in the adjacent aquifer materials. Elder et al. (2001) assessed whether the range in effluent concentrations, as well as the peak effluent concentrations, could be detected using typical PRB monitoring schemes. Most monitoring schemes were found to be too sparse to capture most of the variability, and effluent concentrations detected by typical systems were found to underestimate peak effluent concentrations by an order of magnitude or more. The findings reported in Elder et al. (2001, 2002) illustrate the need for better characterization of PRB flow rates and flow paths. A variety of methods can be used for characterization. Tracer tests have been used to establish groundwater flux and flow paths through PRBs. Dissolved tracers are well suited to determining the direction of groundwater flow, but are limited by the number of injection wells that can be used without overlapping tracer plumes. In addition, flow velocities obtained from tracer studies are sensitive to the number and distribution of monitoring points and to chemical dispersion. Accurate determinations of dispersion are often lacking, particularly within a PRB where settling or other construction-related effects can be significant. Another method is the use of downhole flow sensors. These instruments rely on dispersion of a heat pulse or measurement of colloidal particle velocities to determine groundwater flow velocities. Velocities measured with this technique often vary considerably within an individual well and between wells and may differ from those in the aquifer due to the effects of an open borehole. In situ sensors embedded in the aquifer can eliminate the effects of an open borehole, but the higher cost associated with dedicated sensors generally limits their application to a few points within or near a PRB. Even so, the extent of representation of velocities from flow sensors is unclear. In a comparison of three different downhole flow sensors, Wilson et al. (2001) concluded that the three methods “rarely measured the same velocities and flow directions at the same measurement stations” and that repeat measurements “failed to consistently reproduce either flow direction, flow magnitude, or both.” A promising method that can be used to evaluate the average velocity in an operating PRB using granular iron is reaction path monitoring. Geochemical reactions within a granular iron PRB cause the precipitation of solids containing the major constituents in the groundwater (e.g., calcium, magnesium, manganese, carbonate), as well as contaminants (e.g., arsenic, molybdenum, selenium, uranium, vanadium, zinc). More detail on these processes is contained in Section 2.3. Reaction path monitoring involves estimating a time-averaged groundwater velocity from constituent concentrations in the aqueous and solid phases. The following is an example of the method used for a PRB installed downgradient from a former uranium ore-processing mill in Monticello, Utah. The PRB is 31.4 m long, 2.2 m wide, and 4 m deep, and contains about 250 milligrams (mg) of granular iron (Figure 3.20). Two SB cutoff walls with a combined length of 103 m form a funnel that directs groundwater into the PRB. The PRB is divided into three panels: (1) 0.5 m wide panel of pea gravel mixed with 13% granular

Material Stability and Applications

177

North slurry wall (29.6 m)

Groundwater flow

PRB (31.4 m)

South slurry wall (73.2 m) 0.5 m of gravel/ZVI 1.2 m of 100% ZVI 0.5 m of gravel with air-sparging pipe

FIGURE 3.20 Schematic of groundwater cutoff walls and PRB installed at Monticello, Utah, site. (ZVI, zero-valent iron.)

iron (based on volume) at the upgradient face, (2) 1.2 m wide central portion containing 100% granular iron, and (3) 0.5-m-wide downgradient panel that contains only pea gravel. The PRB was placed within a groundwater plume emanating from the former mill site. Groundwater entering the PRB has a uranium concentration of about 0.4 mg/L. The plume also contained arsenic (0.01 mg/L), molybdenum (0.06 mg/L), nitrate (61 mg/L), selenium (0.02 mg/L), and vanadium (0.4 mg/L) as it entered the PRB. The PRB was very effective at treating each of these contaminants. Concentrations of all contaminants decreased to low levels in the PRB during 2.7 years of its operation (Morrison et al., 2001).

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Barrier Systems for Environmental Contaminant Containment & Treatment

Solid phases in the gravel-iron panel and the iron-only panel were sampled using direct-push coring in February 2002. Cores were collected at 70 random locations within 10 evenly spaced PRB segments (Figure 3.21). The cores were cut into 4.1-cm lengths; 614 samples were collected, of which 279 were digested and analyzed for calcium, uranium, and vanadium. Constituent concentrations dissolved in the groundwater were also measured at 10 evenly spaced time intervals from six wells upgradient and six wells downgradient of the gravel-iron panel. Core analysis showed that nearly all the uranium (Figure 3.22) and vanadium were deposited in the gravel-iron panel. In contrast, calcium was deposited in both iron-containing panels (Figure 3.23). The distribution of calcium is more pervasive and indicates a slower rate of transfer to the solid phase. Calcium, uranium, and vanadium are distributed along the entire length of the PRB, indicating that the entire mass of iron is being used to treat the contaminated groundwater, and that groundwater has not flowed preferentially through specific portions of the PRB. Mean concentration differences (ΔCw) were calculated from the aqueous phase concentrations (Table 3.9). The mean groundwater flux (Qw) was then computed for each solid phase species using:

Qw =

Cs M g Δt ΔC w

(3.1)

where Cs is the mean solid-phase concentration, Mg is the mass of solid material initially in the zone (70.2 mg), and Δt is the deposition period (2.7 years). The mean groundwater fluxes computed following this approach using uranium and calcium data are summarized in Table 3.9. The mean groundwater flux (24 L/min) through the gravel-iron panel zone calculated using the calcium data was identical to that calculated using uranium and was considerably less than the design value of 189 L/min.

3.3.4 STRUCTURAL STABILITY FACTORS

IN

PERFORMANCE

Little post-construction assessment occurs regarding the integrity of the in-place reactive medium from the perspective of sustainability (e.g., reactivity, conductivity) or structural stability (e.g., settlement, movement, strength). Properties such as density or specific gravity, shape, and water content can affect the inplace density, porosity, and hydraulic conductivity. In addition, when two or more materials are used in a PRB or the PRB contains multiple sections of materials, mixing uniformity or complete separation must be ensured. For example, the specific gravity of the reactive materials must be considered so that a construction procedure can be developed that will promote uniform mixing.

Material Stability and Applications

179

Flow ZVI

Gravel/ZVI 30

25

Meters

20

15

10

5

0 0

0.5

1.0

1.5

Meters Core Well

FIGURE 3.21 Locations of cores for solid-phase samples and monitoring wells for aqueous phase analyses in PRB installed at Monticello, Utah, site.

180

Barrier Systems for Environmental Contaminant Containment & Treatment Flow ZVI

Gravel/ZVI

30

70.0

596.9 119.0

319.3

0.1 0.1

0.1

144.4 112.6 89.3

0.9

0.1

0.1

20 0

25

6.3

206.5 147.1

1.7

190.3 437.0 251.8 20

Meters

396.8

0.1

0.2

0.1

384.4

0.1

1.0

0.2

371.0 269.0 0.1

558.4

1.1

0.0

0.4

334.5

200

343.5 539.5

15

0.4

0.0

0.1

0.1

350.0

92.7 249.8

156.6

10

0.2 1.0

0.5

0.0 172.4 226.0 2

5

288.8 807.5 330.2

0.9

00

0.0

0.0

0.1 0.0

0.0

0.0

10.5

0.1 0.0

0.0

0.1

0.0

0.0

0.1 0 0

0.5

1.0 Meters

1.5

FIGURE 3.22 Distribution of uranium in the solid phase (mg/kg) in PRB installed at Monticello, Utah, site. Contour interval is 50 mg/kg.

Material Stability and Applications

181

Flow ZVI

Gravel/ZVI 44.1

46.8

14.1

10.3

24.8

35.5

13.9 20.5 33.2 20.4

25.9

26.5

22.9

30

20 30.7 25.7

21.9 15.2

29.0

32.3

2.1

16.0

14.8

15.1

10

25

11.5

26.9 27.1 23.1

20

5.3

11.5

20 15.4 33.5

Meters

30.3 29.1

30

25.9

25.7 45.3

15

16.8 17.8 23.5

12.0

40

23.8

27.7 11.4

20

30

20

37.6 26.0

35.6

10

17.3

28.3

11.5

23.0 24.8 7.3 8.8

10

30

13.3 22.2 20

37.8 5 17.2

25.3

30.5

25.9 24.8

19.7

29.8

11.0 6.0

9.9

8.2

8.7

0.8

17.1 0 0

0.5

1.0 Meters

1.5

FIGURE 3.23 Distribution of uranium in the solid phase (g/kg) in PRB installed at Monticello, Utah, site. Contour interval is 2 g/kg.

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Barrier Systems for Environmental Contaminant Containment & Treatment

TABLE 3.9 Masses and Concentrations of Calcium and Uranium and Calculated Groundwater Flux for the Gravel-Granular Iron Panel in the Monticello PRB Component in Analysis Mean solid-phase concentration (Cs) (mg/kg) Mean groundwater concentration gradient (ΔCw) (mg/L)a Calculated groundwater flux (Qw) (L/min) Total mass (kg) Total mineral mass (kg)b Total volume of mineral deposited (L)b a b

Ca

U

22,700 47.0 24 1600 4000 1500

162 0.334 24 11.4 12.9 1.6

Mean difference between influent and effluent in the gravel-iron panel. Calcium as calcite (CaCO3) and uranium as uraninite (UO2).

TABLE 3.10 Specific Gravities for Common Reactive Media Used in PRBs Material Granular iron Clinoptilolite Well sorted sand GAC

Specific Gravity 7.5–7.9 2.0–2.5 2.5–2.8 1.4–1.5

Specific gravities of typical reactive media are summarized in Table 3.10 and differ by as much as a factor of 5.6. Differences in specific gravity can cause segregation of materials as they settle, resulting in zones with too little or no reactive material. These factors are particularly important if a mixture of materials is placed in water or a slurry. The relative strength of the reactive material (both the shear strength of the medium and the crush strength of individual particles) can also be important. Granular iron forms a relatively dense section with high shear strength, low compressibility, and high hydraulic conductivity, although corrosion and mineralization can affect these properties over time. In contrast, zeolites are weaker, more friable, and crush more readily, which can lead to the creation of fines that fill pore spaces and lower hydraulic conductivity. The lower shear strength and higher compressibility of some reactive materials such as mixtures with predominantly organic material can be insufficient to resist the earth pressures at depth in some PRBs, resulting in a wall that is too thin due to lateral compression. Additionally, a highly compressible medium can compress so much under lateral earth pressures that its hydraulic conductivity becomes too low.

Material Stability and Applications

183

The shear strength and compressibility of the reactive material can also affect future site uses, particularly in urban settings. For example, a PRB containing a reactive medium that is too weak or too compressible can preclude development adjacent to or above the PRB because the PRB and the surrounding ground will not support the loads associated with the structure being considered. Thus, future land uses should be considered when a reactive medium is selected to ensure compatibility.

3.3.5 MATERIAL DURABILITY FACTORS A variety of chemical reactions occur in a PRB as groundwater contacts the reactive medium. Some of these reactions relate directly to treating the contaminants in groundwater. Others occur due to interactions between the reactive medium, groundwater, and the natural solutes in the groundwater. In a PRB using ZVI as the reactive medium, iron corrosion causes a variety of chemical reactions to occur, some of which can result in secondary mineral precipitation that can plug the PRB or passivate the iron. This section on mineralization and fouling focuses on PRBs employing ZVI because they are by far the most common PRBs. A summary of some of the reactions reported for iron is provided in Table 3.11. Not all reactions occur in a given PRB system. The set of relevant reactions for a specific PRB depends on groundwater quality, contaminants present, and level of microbial activity. The corrosion/precipitation process, illustrated in Figure 3.24, leads to a buildup of precipitates on the surface of the reactive medium. Even in pure water, iron undergoes a series of corrosion and precipitation reactions that form iron oxyhydroxide surface coatings. In groundwater, siderite (FeCO3), aragonite (CaCO3), and magnesite (MgCO3) generally form as well. The presence of other naturally occurring carbonate (CO32–), sulfate (SO42–), and chloride (Cl–) ions also leads to the formation of green rusts. The types of precipitates that form and cover the iron surface have important implications in the contaminant removal process. Removal of halocarbons such as TCE, and reducible metals such as chromium and uranium, depends on the donation of electrons resulting from iron oxidation. When iron is in its fully oxidized state, it cannot donate any more electrons and the reduction of TCE or chromium no longer occurs. Generally, iron must be in a zero-valent or +2 oxidation state for an iron-related redox reaction to occur. Fully oxidized iron oxides such as FeOOH and Fe2O3 do not oxidize further. Coating the granular iron with these oxides leads to passivation or the loss of reactivity. Many of the iron oxides and other precipitates listed in Table 3.11 have been observed in laboratory and field studies of PRBs using granular iron. Roh et al. (2000) found green rusts, iron hydroxides, and goethite in laboratory column studies conducted with waters from Portsmouth, Ohio, and Oak Ridge, Tennessee. After 15 months of operation, examination of a field-scale barrier at the Y-12 plant site in Oak Ridge (Tennessee) yielded buildup of significant precipitates where the groundwater first enters the barrier (Phillips et al., 2000). CaCO3, FeCO3, goethite (α-FeOOH), akaganeite (β-FeOOH), and mackinawite (FeS)

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Barrier Systems for Environmental Contaminant Containment & Treatment

TABLE 3.11 Corrosion and Precipitation Reactions Common for Granular Iron PRBs Fe 0 + 2H 2O → Fe 2+ + H 2 + 2OH − 2Fe 0 + O 2 + 2H 2O → Fe 2+ + H 2 + 4OH − Fe 0 + R − Cl+ H 2O → Fe 2+ + R − H+ OH − + Cl − + 3+ 3+ Fe 0 + CrO 2− 4 + H → Fe + Cr + 4 H 2 O

Fe 2+ → Fe3+ + e −

( )

Fe 2+ + 2 OH − → Fe OH

( )

2

( )

−

Fe OH + OH → Fe OH + e − 2

( )

3

(

)

3Fe OH → Fe3O 4 magnetite + 2H 2O+ H 2 2

(

)

3Fe 2+ + 4 H 2O → Fe3O 4 magnetite + 6H + + H 2

( )

(

)

Fe OH → FeOOH goethite,lepidocrocite + H + + e − 2

( )

( ) (

)

4 Fe OH + Cl − → Fe3II Fe III OH Cl GRI + e − 2

8

( ) (

)

4 Fe 0 + 8H 2O+ Cl − → Fe3II Fe III OH Cl GRI + 8H + + 9e − 8

( )

2

( )

2

( )

6Fe OH + CO32− → Fe 4II Fe 2III OH

12

( )

6Fe OH + HCO3− → Fe 4II Fe 2III OH

(

)

CO3 GRI + 2e −

12

(

)

CO3 GRI + H + + e −

( )

(

)

6Fe 0 +12H 2O+ HCO3− → Fe3II Fe III OH CO3 GRI +13 H + +14 e − 8

( )

2

( )

2

( )

6Fe OH + SO 24− → Fe 4II Fe 2III OH

12

(

)

SO 4 GRII + 2 e −

( )

6Fe OH +12H 2O+ SO 24− → Fe 4II Fe 2III OH

(

12

(

)

SO 4 GRII +12H + +14 e −

)

4 Fe 2+ + O 2 + 4 H 2O → 2Fe 2O3 hematite, maghemite + 8H + HCO3− + OH − → CO32− + H 2O

(

Fe 2+ + CO32− → FeCO3 siderite

)

SO 24− + 4 H 2 → S2− + 4 H 2O (biologically mediated)

(

Fe 2+ + S2− → FeS mackinawite

)

Material Stability and Applications

185

Example Reactions Fe0

Fe2+

• Fe0 + 2H2O → Fe2+ + H2 + 2OH− • 2Fe0 + O2 + 2H2O → 2Fe2+ + 40H− + H2

e−

• Fe0 + R−Cl + H2O → Fe2+ + R−H + OH− + Cl− • Fe0 + CrO42− + 8H+ → Fe3+ + Cr3+ + 4H2O

H2O O2 CrO4− TCE

• Release of OH−, pH increases • Increasing pH causes alkalinity to shift to more CO32− • Precipitation and complexation of cations, Fe2+, Fe3+, Ca2+, Mg2+, etc. favored • H2 generated as gas, important for anaerobic biological activity

FIGURE 3.24 Example reaction occurring as corrosion and precipitation occurs in presence of granular iron.

were identified within the barrier. Cementation of the granular iron was also observed where the groundwater entered the barrier. Sass et al. (2001) report primary corrosion coatings of magnetite (Fe3O4) and hematite (α-Fe2O3) with various forms of amorphous iron hydroxides [Fe(OH)2 and Fe(OH)3] and small amounts of CaCO3 and marcasite (FeS2). Core sample analysis of the iron cell from a pilot field study at Moffett Field (Mountain View, California) also found dominance of Fe3O4 with small amounts of α-Fe2O3 or maghemite, CaCO3, and FeS2. 3.3.5.1 Effect of Mineral Precipitation on Porosity and Hydraulic Conductivity The precipitation of secondary minerals reduces the porosity and decreases the hydraulic conductivity of the reactive medium (Mackenzie et al., 1999). Hydrogen gas generation and build up can also occlude pores, leading to an apparent loss of porosity and reduction in hydraulic conductivity. Yabusaki et al. (2001) used a geochemical transport model to predict mineral precipitation and porosity reductions of the PRB at Moffett Field. They predicted the porosity would decrease at a rate of 1.5% to 3.0% per year, primarily due to formation of CaCO3 and FeCO3 near the upgradient face of the reactive zone in the PRB. Calibration of the geochemical transport model to field data from the Moffett Field PRB

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indicated that that a Darcy flux of 0.04 m/day best fit the field data after one year of operation, whereas the Darcy flux was believed to be 0.064 m/day at the time of construction. Comparison of these Darcy fluxes suggests that the PRB hydraulic conductivity may have decreased by about 50% as a result of mineral deposition. However, this hypothesis has not yet been confirmed with actual field measurements of hydraulic conductivity. Gillham et al. (2001) reported on similar levels of fouling in a PRB containing granular iron. They found a decrease in porosity of 5% to 15% as a result of hydrogen gas evolution and an additional 17% to 22% due to mineral precipitation. They also reported that the hydraulic conductivity decreased approximately one order of one magnitude as a result of hydrogen gas that formed when the PRB was first installed, but found no decrease in hydraulic conductivity due to mineral precipitates. 3.3.5.2 Effect of Mineral Precipitation on Reactivity Mineral formation can also result in loss of reactivity (i.e., the rate at which reactions occur). For granular iron PRBs, loss of reactivity is referred to as passivation (i.e., the loss of redox reactivity). Passivation occurs when the iron surface is coated by iron corrosion products and other precipitates. These materials provide resistance to mass transfer to and from the iron surface, impeding the corrosion reaction rate. A classic example of iron passivation is the coating of iron (III) oxide that forms when steel structural members oxidize. The coating protects the steel by minimizing the rate at which the iron corrodes in the atmosphere. Similarly, in PRBs with granular iron, oxide coatings can minimize the rate of corrosion either by dissolved oxygen or water. However, in a PRB, a reduction in the corrosion rate is detrimental because it corresponds to a reduction in the rate of contaminant treatment. The potential for passivation of granular iron by the iron (III) hydroxides goethite, hematite, lepidocrocite, and maghemite has been suggested because these fully oxidized iron corrosion products inhibit electron transfer and hydrogen formation reactions. However, there has been little experimental evidence indicating that these iron corrosion products actually form in PRBs. In contrast, field studies have shown that mixed valent iron oxides, such as magnetite and green rusts, are the more prevalent iron corrosion products. Because these iron corrosion products are able to promote reduction and hydrogenation reactions, remediation reactions are able to proceed in their presence. Despite the positive field data, recent studies do suggest that passivation occurs in granular iron permeated with typical groundwaters. Farrell et al. (2000) found that the TCE degradation rate decreased during a long-term column test. After nearly two years of operation, the effective half-life for TCE dechlorination increased from 400 to 2,500 per minute. The decrease in reaction rate was proportional to the amount of iron corrosion products in the column. Lower TCE degradation rates were observed where precipitate buildup was highest. In addition,

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while Fe3O4 was found throughout the column, magehmite (Fe2O3) was found only in the initial portions of the column, where the decrease in reaction rate was largest. Reduction reactions critical to TCE degradation do not occur with Fe2O3, which is composed of fully oxidized iron, but do occur with magnetite. Köber et al. (2002) also observed a drop in the first-order reaction rate constants for perchloroethylene (PCE), TCE, cis-1,2-dichloroethylene (cis-DCE), and vinyl chloride in a column test where 379 pore volumes of groundwater had passed through the granular iron. The reduction in reaction rates for PCE, cis-DCE, and vinyl chloride were so significant that treatment efficiency decreased to less than 10% by the end of the experiment. The reduction in treatment efficiency was attributed to the loss of reactivity caused by iron and calcium carbonate precipitates.

3.3.6 APPLICATIONS OF GEOCHEMICAL MODELS IN REACTION TRACKING Although field and laboratory studies now show that mineral precipitation and hydrogen gas evolution in PRBs can cause an apparent reduction in porosity and hydraulic conductivity, little is known about the rate at which these changes occur or their long-term effects on PRB performance. One approach currently under development is the use of geochemical transport models such as OS3D (Yabusaki et al., 2001), MIN3P (Mayer et al., 2001, 2002), or RT3D (Clement, 1997; Mergener et al., 2002). Geochemical transport models combine algorithms that simulate flow under realistic aquifer conditions, advection, dispersion, and the kinetics of geochemical reactions. They can be used to predict the temporal and spatial distribution of mineral precipitation and gas evolution and the effects that these processes have on hydraulic conductivity. The following is a sample application of a geochemical transport model developed by Mergener et al. (2002) specifically for evaluating PRB fouling due to mineral precipitation and hydrogen gas evolution. The model simulates flow, transport, and geochemical processes in a three-dimensional (3-D) domain comprised of an aquifer and PRB. The distribution of hydraulic conductivity in the domain can be heterogeneous so that a realistic distribution of flow rates and residence times in the PRB can be simulated. Incorporating heterogeneity is essential (Bilbrey and Shafer, 2001; Elder et al., 2002; Wilkin et al., 2002). Variations in flow velocity affect the rate at which dissolved constituents enter various portions of the wall and the rate and location of mineral deposition (i.e., solutes may move faster or slower than the rate at which precipitation occurs, resulting in variable mineral distribution in the pore space due to geochemical and hydraulic effects) (Mayer et al., 2001; Li, 2002; Mergener et al., 2002). The model is based on the reactive transport model RT3D (Clement, 1997), which is a 3-D multi-component reactive transport model in the public domain that simulates advective-dispersive transport of multiple aqueous and immobile species in saturated porous media. The head solution from the 3-D groundwater

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flow simulator MODFLOW is used as input to RT3D. Mergener et al. (2002) incorporated geochemical processes occurring within a PRB using the “userdefined” reaction sub-module in RT3D. Emphasis was placed on making the model efficient so that practical 3-D problems could be simulated with reasonable run times, which led to some simplifications relative to other more fully developed proprietary codes (e.g., MIN3P by Mayer et al., 2002). However, the code captures the key mechanisms affecting fouling. Groundwater entering the PRB is assumed to be in chemical equilibrium, and only geochemical reactions within the PRB are considered. Water, oxygen, sulfate, and nitrate contribute to iron corrosion. Corrosion causes the pH to increase, a corresponding shift in the carbonate-bicarbonate equilibrium, release of hydrogen gas, and precipitation of secondary minerals such as CaCO3, MgCO3, dolomite, brucite, pyrochorite, rhodochrosite, FeCO3, ferrous hydroxide, and ferrous sulfide. Corrosion caused by reduction of chlorinated compounds or toxic heavy metals generally is not included. Even though it is intrinsic to the remediation process, corrosion by contaminants generally is negligible relative to that due to other corrosion processes (Phillips et al., 2000; Morrison et al., 2001; Yabusaki et al., 2001). A listing of the reduction-corrosion reactions included in the model is presented in Table 3.12. All of the reactions are assumed to occur in parallel. The aqueous species and reactions that have been incorporated generate the predominant secondary minerals responsible for fouling (Schuhmacher et al., 1997; Puls et al., 1999; Blowes et al., 2000; Phillips et al., 2000; Mayer et al., 2001). Corrosion reaction kinetics are described by first-order rate laws that are a function of reacting species concentration and reactive medium surface area. Reaction rates based on transition state theory are used to describe the precipitation of secondary minerals. The kinetic model is assumed to be spatially homogeneous and time-invariant when the PRB is installed. Spatial and temporal variabilities evolve as concentrations in the PRB change in response to flow rate variability. The following example corresponds to the heterogeneous aquifer shown in Figure 3.25, which contains a fully penetrating 100% granular iron PRB (Figure 3.21) oriented orthogonal to the regional gradient. Groundwater entering the wall was assumed to be anoxic (dissolved oxygen concentration = 10–8 M) and to contain the following dissolved species: Fe2+, 10–10 M; Ca2+, 10–3 M; Mg2+, 10–3 M; OH–, 10–7 M; HCO3–, 10–3 M; CO32–, 10–7 M; NO3–, 10–3 M; SO42–, 10–3 M. The initial porosity of the PRB was 0.6. Reductions in porosity predicted by the model for conditions after 10 years of service are shown in Figure 3.26. Reductions in porosity as large as 0.10 (corresponding to one sixth of the pore space) were common (Figure 3.26). CaCO3, MgCO3, and FeCO3 are the primary minerals that formed near the front of the wall, whereas ferrous hydroxide precipitation increased with wall distance (Li, 2002). Material distribution was heterogeneous, as shown by the spatially variable reduction in porosity and largely depended on the distribution of flow velocity in the PRB. Pockets of CaCO3, MgCO3, and FeCO3 formed in the interior of the wall along flow paths where the velocity was higher. In addition, the greatest

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TABLE 3.12 Geochemical Reactions in Fouling Model Developed by Mergener et al. (2002) Reaction Type Iron corrosion

Geochemical Reaction

Mineral Formed —

Fe 0 + H 2O + 0.5O 2 → Fe 2+ + 2OH −

—

Fe 0 + 2H 2O → Fe 2+ + H 2 + 2OH −

—

4 Fe 0 + 7H 2O + NO3− → 4 Fe 2+ + 10OH − + NH 4+

—

4 Fe 0 + 4 H 2O + SO 24− → 4 Fe 2+ + 8OH − + S2−

—

HCO3− + OH − ↔ CO32− + H 2O Microbial sulfate reduction

—

SO 24− + 4 H 2 → S2− + 4 H 2O CaCO3 ↔ Ca 2+ + CO32−

Aragonite

MgCO3 ↔ Mg2+ + CO32− CaMg(CO3 )2 ↔ Ca

Mineral precipitation

2+

Magnesite 2+

+ Mg + 2CO

2− 3

Dolomite

Mg(OH)2 ↔ Mg2+ + 2OH −

Brucite

Mn(OH)2 ↔ Mn 2+ + 2OH −

Pyrochroite

MnCO3 ↔ Mn 2+ + CO32−

Rhodochrosite

2+

FeCO3 ↔ Fe + CO

2− 3

Siderite

Fe(OH)2 ↔ Fe 2+ + 2OH −

Ferrous hydroxide

FeS ↔ Fe 2+ + S2−

Ferrous sulfide

reductions in porosity occurred in regions of the PRB where the Darcy velocities were highest (Figure 3.27) because these regions received more groundwater and thus more dissolved constituents. The importance of flow field heterogeneity is evident in Figure 3.26 and Figure 3.27. If the flow field is assumed to be uniform, the porosity reductions would be uniform and focused on the front of the wall, resulting in uniform changes in PRB hydraulics and reactivity. In contrast, realistic spatial variations in porosity reduction would result in reorientation of flow paths, changes in residence time, and changes in treatment effectiveness. These variations would reduce the overall PRB hydraulic conductivity, yielding a reduction in flow rate, evolution of backwater, and bypassing. Although models such as these can provide estimates of the spatial and temporal distribution of PRB fouling, their accuracy is sensitive to the kinetic

20

10 5 0

3 La 0 te ra 40 ld i s t 50 an ce 6 (m 0 ) 70

Barrier Systems for Environmental Contaminant Containment & Treatment

10

Elevation (m)

190

0

10

20

30

40

50

60

70

80

90

Longitudinal distance (m) Hydraulic conductivity (cm/s)

10–5

10–4

10–3

10–2

10–1

FIGURE 3.25 Hydraulic conductivity distribution and location of PRB in a heterogeneous aquifer model. (From Elder, C. et al., 2002. Water Resources Research, 38(8), 27-1 to 27-2.)

Elevation (m)

10

5

20 0 1

0

0

X

)

(m

)

10 istance (m

Lateral d

Porosity reduction Groundwater flow

0.01 0.05 0.09 0.13

FIGURE 3.26 Predicted reductions in porosity of PRB after 10 years of operation.

models and the reaction rate coefficients used as input. Currently, existing models provide an estimate of changes that are likely to occur in a PRB over time. More field data are needed, however, to improve and calibrate the models before they can be considered as predictive tools. A variety of characterization techniques are available, ranging from optical microscopy to the examination of the reaction products. Optical and scanning electron microscopy can be used to observe the distribution and structure of reaction products and secondary precipitates. Energy

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0.07

Porosity reduction

0.06

0.05 Entrance face Mid-plane Exit face 0.04

0.03 0.0

0.1

0.2

0.3

0.4

0.5

Darcy velocity (m/d)

FIGURE 3.27 Reductions in porosity in PRB as a function of Darcy velocity (5 years of service).

dispersive x-ray analysis (EDXA) provides qualitative chemical analysis, whereas electron microprobe analysis provides quantitative measurements of the elemental abundance. X-ray photoelectron spectroscopy (XPS) provides chemical state information, and surface ionization mass spectrometry (SIMS) provides detailed information on the distribution of reaction products on the mineral surface. Blowes et al. (1997) used optical and electron microscopy coupled with EDXA analyses and X-ray diffraction studies to identify the reaction products from batch studies in which hexavalent chromium reacted with ZVI. Pratt et al. (1997) used XPS to determine the oxidation state in precipitates on the surfaces of ZVI grains taken from a column experiment in which Cr(VI) was treated using ZVI. The XPS results confirmed that chromium on the iron surfaces was exclusively in the Cr(III) oxidation state. Auger electron spectroscopy (AES) was used to examine the structure of the (Fe,Cr) (OH)3 precipitates.

3.4 MATERIAL PERFORMANCE FACTORS IN CUTOFF WALLS In contrast to PRBs, cutoff walls are used to block flow. Cutoff walls continue to be widely used as components in site remediation systems despite limited research on their long-term performance and considerable uncertainty regarding their effectiveness. A variety of materials can be used to construct cutoff walls. Inyang (1992) reviewed and summarized the recommended ranges of material characteristics for cutoff walls as presented in Table 3.13. SB cutoff walls have been and continue

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TABLE 3.13 Recommended Ranges of Material Properties for Cutoff Walls Bentonite Slurry Freshly Hydrated

Parameter Density (g/cm3) (pcf) Apparent viscosity (seconds marsh) (centipose) Plastic viscosity Filtrate loss (mL)

pH Water content (% by weight) Cement water ratio Bentonite content (% by weight) Other ingredients (% by weight)

Gel strengths 10 seconds, Pascal 10 minutes, Pascal 10 minutes, lb/100 ft2 (24 dynes/cm2) Strain at failure (%)

During Excavation

Cement–Bentonite Slurry Freshly Hydrated

During Excavation

1.01–1.04 (1,2) 65 (3)

1.10–1.24 (2) 69–85 (4)

1.03–1.4 (8)

≥1.12 (10)

38–45 (1,5) –15 <20a (7) <30 (7); range 15–30 (3)

38–68 (6)

40–45 (8) –15 (7) 9 (7) 100–300 (3,7)

38–80 (8) >130 (7) 30–50 (7,10)

7.5–12 (6) –93–97

— Range 15–70 (6); apparent average 40–60 (6) 10.5–12 (6) –78–82 (7)

—

—

—

0.16–0.35 (9,10)

Sand ∼ 1 (3)

Sand <5a (3)

Cement 18 (7)

—

Solids ∼ 2 (6)

Solids 3–16 (6)

Solids 15–30 (7)

30–45 (7)

7–30 (6) 5–15 (2)

–20–40 (6) —

15 (7) 18 (7) —

10 (7) 22 (7) —

—

—

≥ 15 (9)

—

12–13 (7) 76 (7)

55–70 (7)

4–7 (6)

References: (1) Case International Company, 1992; (2) Xanthakos, 1979; (3) Millet and Perez, 1981; (4) U.S. Army Corps of Engineers, 1976; (5) Guertin and McTigue, 1982; (6) Boyes, 1975; (7) Jefferis, 1981; (8) Ryan, 1976; (9) Ryan and Day, 1986; (10) PCA, 1984. a

Specification for construction of tremie concrete diaphragm walls.

Source: Inyang, H.I. (1992). Selection and design of slurry walls as barriers to control pollutant migration, Office of Solid Waste and Emergency Response, U.S. Environmental Protection Agency, Washington, DC.

to be used widely in the United States, where barriers with a hydraulic conductivity less than 1 × 10–7 cm/s are needed. Soil-cement–bentonite (SCB) cutoff walls are also used, albeit much less frequently, where a wall with higher unconfined compressive strength is desired along with a hydraulic conductivity less

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than 1 × 10–7 cm/s. SCB cutoff walls essentially are SB cutoff walls with cement added to increase the compressive strength of the backfill. Cement–bentonite (CB) cutoff walls are used occasionally in the United States where unconfined compressive strength is desired and a higher hydraulic conductivity is permissible (typically <1 × 10–5 cm/s). In Europe, the most common cutoff wall is a cement–bentonite-slag (CB-slag) cutoff wall, which has substantial unconfined compressive strength and a hydraulic conductivity less than 1 × 10–7 cm/s after about six months of curing (Jefferis, 1981). Use of CB-slag cutoff walls has become more common in the United States in recent years as well (Evans et al., 2002). Composite cutoff walls employing geomembranes in conjunction with SB or CB backfill are used only occasionally. These types of walls have not been widely embraced because of the increased cost and the regulatory acceptance of conventional cutoff wall materials.

3.4.1 IN SITU HYDRAULIC CONDUCTIVITY Beyond barrier material characteristics, several factors control the ability of cutoff walls to contain contaminants in the field. The most significant of these factors are wall defects and windows beneath the bottom of the wall. The genesis of a wall defect is varied. In some cases, granular materials can cave into the slurry during wall construction, thereby creating permeable zones in the wall. In other cases, prevalent in dry climates, seasonal or artificially induced fluctuations in the water table around walls can facilitate desiccation-induced cracking of previously submerged wall portions. Cracks and fissures can develop and lead to the fluid flow patterns depicted by Bai et al. (1996) in Figure 3.28 when the water table rises again. Demonstrating that a cutoff wall meets its objectives as a flow barrier remains a key unresolved issue, even though studies have shown that a few permeable defects can have a significant impact on cutoff wall effectiveness (Tachavises and Benson, 1997; Lee and Benson, 2000). For example, Tachavises (1998) evaluated the importance of hydraulic defects in cutoff walls using a 3-D groundwater flow model (Figure 3.29). A horizontal wall having a breadth (WSB) of 500 m and thickness of 1 m was placed in the center of a permeable 40 m thick aquifer (hydraulic conductivity, KA = 10–4 m/s) underlain by a tight confining unit (hydraulic conductivity, KC = 10–10 m/s) 30 m thick. The regional gradient (iREG) in the aquifer was assumed to be 0.001 and the hydraulic conductivity of the wall backfill (KSB) was assumed to be 10–9 m/s. The domain was made 3000 m wide and 1500 m long to prevent the boundaries from influencing the solution. Small permeable windows were placed in the cutoff wall to evaluate how they influence wall effectiveness (EW), defined as the groundwater flow rate through the portion of the aquifer containing the wall before the wall was placed (QAQW) divided by the groundwater flow rate past the wall (QAQW), i.e., EW = QAQW/QW. Walls that are more effective have higher values of wall effectiveness, and walls that have no impact on groundwater flow have an effectiveness of 1.0. Wall effectiveness is shown in Figure 3.30 as a function of the area of the window

194

Barrier Systems for Environmental Contaminant Containment & Treatment Fracture

Fracture

Matrix

Matrix

Matrix

Matrix

(a) Matrix diffusion

(b) Matrix replenishment

FIGURE 3.28 Conceptual patterns of fluid flow through fractured media. (Adapted from Bai, M. et al., 1996. ASCE Journal of Environmental Engineering, 122(5), 416–423.)

(Aw) relative to the cross sectional area of the wall (A). For the scenario that was simulated, EW = 100 for a wall without windows (i.e., the wall reduced flow within its breadth by a factor of 100), the effectiveness dropped appreciably as the area of windows increased. If windows comprise more than 1% of the area of the wall, the cutoff wall is rendered completely ineffective (Ew = 1). Despite the dramatic effect that small defects can have on the overall effectiveness of a cutoff wall, the ability to test a completed cutoff wall as a system is limited. The overall integrity of a wall is usually extrapolated based on data from a series of measurements obtained in the laboratory on small specimens prepared from disturbed samples collected during construction. Undisturbed specimens are tested in some cases, and on occasion field tests are conducted. Further complicating the issue is the ill-defined state of stress in cutoff walls. Nevertheless, inferences based on even the best testing methods can be misleading if the method provides a point measurement of hydraulic conductivity rather than the overall hydraulic conductivity of the wall. An accepted procedure for measuring the overall hydraulic conductivity of a cutoff wall has not been developed because of several complicating issues. Cutoff walls are often very long and enclose a huge volume of the subsurface. In addition, the environment on both sides of the cutoff wall often is contaminated and leakage into the containment system can come from the underlying floor (e.g., aquitard

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Groundwater passing through aquifer and around wall

Groundwater focusing on the wall

Cutoff wall

40 m

30 m Aquifer (KA)

Confining layer (KC) No flow

FIGURE 3.29 Schematic of 3-D model used by Tachavises (1998) to evaluate the effect of defects on the effectiveness of groundwater cutoff walls.

into which the wall is keyed) or from the overlying cap, which confounds how much water is actually passing through the wall. The drainage of aquifer materials during a pump test can also confound the volume of water passing through the wall. As a result of these complexities, methods to verify the overall hydraulic conductivity of cutoff walls have largely been unsuccessful. One large-scale method that provides an indication of overall hydraulic conductivity is the in situ test box. A box-shaped loop is constructed in the wall with one side of the box forming part of the actual wall. A well is then set within the box for extracting or injecting water, and piezometers are placed inside and outside of the box to measure groundwater levels. Pumping is continued until equilibrium is established, and then the overall hydraulic conductivity is computed from the measured water levels, flow rate, and box geometry. Several months of low flow pumping may be required until equilibrium is established. The test box should be of sufficient size (at least 5 m by 5 m) to represent a typical wall section and reduce the potential for slurry to plug pores in the box interior. The top of the box may need to be capped to prevent groundwater infiltration. Leakage from the floor still remains a potential confounding issue with this method.

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Barrier Systems for Environmental Contaminant Containment & Treatment 1000

No window

KC = 10–10 m/s

EW = QAQW/QW

100

KA = 10–4 m/s KSB = 10–9 m/s KW = KA 10

1 0.0001

0.01

1

100

AW/A (%)

FIGURE 3.30 Wall effectiveness as a function of relative area of a fully penetrating permeable window. (From Tachavises, 1998. Flow rates past vertical cut-off walls: influential factors and their impact on wall selection. Ph.D. dissertation, University of Wisconsin–Madison. With permission.)

3.4.2 DESIGN CONFIGURATION Another important factor that can significantly influence cutoff wall effectiveness is the integrity of the key into the underlying floor or aquitard. A risk always exists that a wall is not properly keyed because of local variations in the soil profile, errors in measuring the trench depth, or poor assessments of the penetration depth into the aquitard. Independent monitoring of wall depth and excavation materials must be made during construction to ensure that an appropriate key is achieved. Tachavises (1998) used his 3-D flow model to evaluate a scenario where a portion of the wall was unkeyed, forming a gap between the bottom of the wall and the top of the aquitard. The gap was assumed to be filled with aquifer material. Gaps of different widths (WG) and heights (LG) were evaluated. Some typical results are shown in Figure 3.31, which depicts wall effectiveness (EW) as a function of gap thickness (LG) and the ratio of gap width relative to wall width (WG /WSB). Even if the bottom of the wall is close, but not keyed into the confining unit, the wall can be practically ineffective. For example, a 50-mm gap between the bottom of the wall and the top of the confining unit can reduce the effectiveness from 100 to nearly 2. Even narrow zones that are poorly keyed can reduce cutoff wall effectiveness. In particular, missing keys reduce effectiveness appreciably

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1000 iREG

WSB KSB

30 m LG 30 m

EW = QAQW/QW

No gap

KG

Longitudinal section

100

WM KA 40 m

WG

KC 30 m

Transverse section

1 0.225 LG (m)

0.125

10

0.05

1 0.01

KA = 10−4 m/s

KSB = 10−9 m/s

KC = 10−10 m/s iREG = 0.001

KG = KA 0.1

1

10

100

WG/WSB (%)

FIGURE 3.31 Wall effectiveness as a function of size of the gap between the base of the wall and the top of the confining unit. (From Tachavises, 1998. Flow rates past vertical cut-off walls: influential factors and their impact on wall selection. Ph.D. dissertation, University of Wisconsin–Madison. With permission.)

unless the unkeyed region comprises less than 0.1% of the wall and the gap between the base of the wall and the confining unit is narrow. Despite analyses such as those reported by Tachavises (1998), poor keys are a common problem afflicting groundwater cutoff walls. The following case history from Benson (2002) provides an example. A SB cutoff wall was installed in the western United States to isolate a lagoon from surrounding groundwater. The lagoon and wall were installed in alluvium consisting of sands and gravels overlain with a thin fine-grained surface layer. The wall, which had a thickness of 0.6 m and backfill with a hydraulic conductivity of 5 × 10–7 cm/s, was constructed along the perimeter (1.9 km) of the lagoon. Specifications for the project required that the bottom of the wall be keyed 1 m into the underlying bedrock, which was comprised of inter-bedded highly plastic claystone and sandstone. The lagoon was constructed by excavating the alluvium to the underlying rock. The thickness of the alluvium ranged from 7 to 10 m. After the lagoon was completed and the dewatering system was removed, excessive leakage became readily apparent. A pump test was conducted to determine the seepage rate past the wall. A variable-speed pump was installed in the lagoon, and the pumping rate was adjusted until the pump discharge was sufficient to maintain a constant water level in the lagoon. The leakage rate was determined to be 1000 m3/day or approximately 0.06 m3/day/m2-wall. For unit gradient conditions, this flow rate corresponds to a hydraulic conductivity of more than 100 times the hydraulic conductivity of the backfill.

CL

GW, SP

SW GP SW

SP Sandstone

Sandstone Claystone

SP SP SW

Sandstone

Claystone Claystone, Silty-claystone

SW

CL, SC

SM SP

CL SP SWSM

560

SW GW

SM

GP SP SM GW Siltyclaystone

GW

565

555 Sandstone Claystone, siltyclaystone

Elevation (m)

CH SC

Bottom of trench

STA. 1 + 573 m

STA. 1 + 492 m

Ground surface

STA. 1 + 694 m

Barrier Systems for Environmental Contaminant Containment & Treatment

STA. 1 + 307 m

198

550

545

FIGURE 3.32 Cross-section showing stratigraphy and location of bottom of trench along the alignment of the cutoff wall. SC = clayey sand, sand-clay mixtures; CH = fat clay, inorganic clays of high plasticity; GW = well-graded gravels, gravel sand mixtures, little or no fines; SP = poorly graded sands, gravelly sand mixtures, little or no fines; CL = lean clay, inorganic clay of low to medium plasticity, gravelly clays, sandy clays, silty clays; SW = well-graded sand, gravelly sands, little or no fines; GP = poorly graded gravel, gravel-sand mixtures, little or no fines; SM = silty sands, sand-silt mixtures.

A forensic investigation was undertaken to determine the source of the excessive leakage. Paired piezometers were installed, additional pumping tests were conducted, and drilling was performed to define the vertical extent of the wall. Undisturbed samples of the underlying rock were also collected for hydraulic conductivity testing. Results of the tests showed that the hydraulic conductivity of the sandstone was approximately 2 × 10–4 cm/s, whereas that of the claystone was approximately 3 × 10–9 cm/s. Results of the forensic investigation pointed at the key as the source of leakage. A cross section obtained from the drilling program is shown in Figure 3.32. This cross section is typical of the wall condition. Most of the wall bottom rests in the permeable sandstone or alluvium rather than the relatively impervious claystone. Analysis of the entire cross section showed that 48% of the wall was not keyed into the claystone. Based on the curves shown in Figure 3.31, excessive leakage rates are anticipated for this wall. For LG = 1 m and WG/WSB ≈ 50%, the wall effectiveness is approximately 1.3.

3.4.3 GEOSYNTHETICS

IN

VERTICAL CUTOFF WALLS

The use of geosynthetic materials, particularly geomembranes in slurry trench cutoff walls is relatively new in the United States, although it has been more

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199

widely used in Europe. The inclusion of a geomembrane sheet in cutoff walls is driven by the need to enhance the factor of safety against the hydraulic effects of construction-induced and service-related flaws that often develop in SB, SC, CB, SCB, and other backfilled materials in which soil is a principal component. Construction flaws generally enhance cutoff wall permeability to fluids at specific locations such that a wide variability can exist in the spatial distribution of the permeability magnitudes across the wall. The high permeability zones can be generated by any or combinations of the following mechanisms: • Collapse of coarse-grained wall materials into the trench during construction or backfilling operations • Accumulation of sand or debris at the bottom of the slurry such that the wall is not properly keyed into a basal low permeable stratum • Poor and variable mixing of backfill resulting in permeability zonation in the backfilled barrier material • Existence of large aggregates of rocks or objects in the backfilled materials During service, fluctuations in water table elevation around a cutoff wall can produce cycles of desiccation and saturation that cause wall cracks. Geomembrane sheets can bridge the flawed sections of the wall such that the flow characteristics of the composite wall are more uniform spatially. Most of the geomembranes that are used in vertical walls are compositionally thick (approximately 2.5 mm) HDPE, the long-term durability of which is discussed in Section 3.3. The geomembrane is usually emplaced as panels and made to interlock into continuous sheets using various optional connections. The design depth of each wall is the primary determinant of the installation method. Koerner and Guglielmetti (1996) summarized common installation techniques (Table 3.14). In general, cutoff walls that include geomembranes are expected to perform better than soil and cement walls because of the lower permeability of geomembranes to fluids and greater resistance to chemical attack in most cases.

3.4.4 PERMEANT INTERACTION EFFECTS There are no standard methods for determining or evaluating the longevity of cutoff wall materials. Some work has been done to evaluate the effects of chemical incompatibility, but most of this work has been conducted over time frames that are too short to provide a realistic assessment of the long-term effects that contaminated groundwater can cause in cutoff wall materials. In addition, limited studies have been conducted on other mechanisms that might cause long-term degradation of cutoff wall materials (e.g., wetting and drying, frost action, differential settlements and distortion). Analyzing groundwater quality data collected adjacent to in-place walls has been suggested as a method of assessing long-term cutoff wall performance. However, the complexity associated with most systems, which often integrate caps, floors, and a cutoff wall, usually prevents drawing definitive conclusions regarding field performance from groundwater quality data.

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TABLE 3.14 Current Installation Methods for Geomembrane Vertical Walls

Method No.

Typical Trench Width mm (in)

Typical Trench Depth mm (in)

Method or Technique

Geomembrane Configuration

Trench Support

1

Trenching machine

Continuous

None

300–600 (12–24)

1.5–4.5 (5–15)

2

Vibrated insertion plate Slurry supported

Panels

None

100–150 (4–6)

1.5–6.0 (5–20)

Panels

Slurry

600–900 (24–36)

No limit, except for trench stability

4

Segmented trench box

Panels or continuous

None

900–1200 (36–48)

3.9–9.0 (10–30)

5

Vibrating beam

Panels

Slurry

150–220 (6–9)

No limit

3

Typical Backfill Type Sand or native soil Native soil SB, SC, CB, SCB, sand, or native soil Sand or native soil SB, SC, CB, or SCB slurry

Source: After Koerner, R.M. and Guglielmetti, J.L. (1996). In Rumer, R.R. and Mitchell, J.K. (Eds.), Assessment of Barrier Containment Technologies, National Technical Information Service, Springfield, VA, pp. 95–118.

The effects of many chemical permeants may not be evident until many years after installation. In some cases, an initial reduction in hydraulic conductivity may occur, but then it is usually followed by an increase at much longer times. The long-term effects of chemical interactions can be illustrated by analyzing the cutoff wall as a one-dimensional, two-compartment plug-flow system as illustrated in Figure 3.33a (Jefferis, 2001). The compartments are separated by a reaction front and correspond to sections of the wall that have been affected and unaffected by chemical permeation. The upstream compartment is assumed to be in chemical equilibrium with the site groundwater and has a hydraulic conductivity of kr . The downstream compartment is ahead of the reaction front, and its hydraulic conductivity (ku) is representative of the as-built condition. The overall hydraulic conductivity (ko) is the thickness-weighted harmonic mean of kr and ku. The velocity of the reaction front is proportional to the average hydraulic gradient across the wall and ko and is inversely proportional to the retardation

Material Stability and Applications

kr

kο

X

L ku

Overall permeability/ unreacted permeability, kο/ku

Direction of groundwater flow

201

104

kr/ku

103

1000

102

100

10

10−1

10 5 1 0.5 0.1

10−2

0.01

1

10

−3

0.001

−4

10

0

0.2

0.4

0.6

0.8

1

1.2

Permeation time/ Time for full reaction, t/t f , (a)

(b)

FIGURE 3.33 Schematic of two-compartment model and change in hydraulic conductivity of cutoff wall over time as contaminants react with backfill material.

factor and the porosity of the wall. The effects of diffusion and rate limitations on ion exchange are ignored. This two-compartment model was used to create a set of curves relating overall hydraulic conductivity to time of permeation for different values of the ratio kr /ku (Figure 3.33b). A key feature of these curves is that, for any reaction that significantly increases the hydraulic conductivity (e.g., kr /ku > 10), predicting the final hydraulic conductivity is impossible until the reaction front has passed completely through the barrier. Thus, short-term data from laboratory tests or in situ monitoring programs cannot be used exclusively as an indicator of long-term conditions. Another aspect of chemical interactions with barrier materials in situ that has received little attention is volume change, although this phenomenon has been studied under batch conditions in the laboratory (Chen et al., 2000; Murray and Quirk, 1982). Reactions that cause barrier material expansion are likely to be resisted by passive resistance provided by the surrounding soil, but shrinkage may be more significant as it can lead to the opening of cracks that transmit preferential flow. Unfortunately, small-scale laboratory tests are poor indicators of the effects of cracking. Further work is needed in this area, preferably at field scale.

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Albright, W. and Benson, C. (2002). Alternative Cover Assessment Program 2002 Annual Report, Publication No. 41182, Desert Research Institute, Reno, Nevada. Badu-Tweneboah, K., Tisinger, L.G., Giroud, J.P. and Smith, B.S. (1999). Assessment of the long-term performance of polyethylene geomembrane and containers in a lowlevel radioactive waste disposal landfill. Proceedings of the Geosynthetics ’99 Conference on Specifying Geosynthetics and Developing Design Details, Boston, MA, pp. 1055–1070. Bai, M., Roegiers, J.-C. and Inyang, H.I. (1996). Contaminant transport in non-isothermal fractured media. ASCE Journal of Environmental Engineering, 122(5), pp. 416–423. Battelle (2002). Final Report, Evaluating the Longevity and Hydraulic Performance of Permeable Barriers at Defense Sites, prepared for Navy Facilities Engineering Support Center, Port Hueneme, California, by Battelle Memorial Institute. Benson, C. (2001). Waste Containment: Strategies and Performance. Australian Geomechanics, 36(4), 1–25. Benson, C. (2002). Containment systems: lessons learned from north American failures. In de Mello, L. and Almeida, M. (Eds.), International Congress on Environmental Geotechnics, Balkema, Rotterdam. Bilbrey, L. and Shafer, J. (2001). Funnel-and-gate performance in a moderately heterogeneous flow domain. Ground Water Monitoring and Remediation, 21(3), 144–151. Blowes, D., Ptacek, C. and Jambor, J. (1997). In situ remediation of Cr(VI) contaminated groundwater using permeable reactive walls: Laboratory studies. Environmental Science and Technology, 31(12), 3348–3357. Blowes, D., Ptacek, C., Benner, S., McRae, C. Bennett, T. and Puls, R. (2000). Treatment of Inorganic Contaminants Using Permeable Reactive Barriers. Journal of Contaminant Hydrology, 45, 123–137. Bolen, M., Roesler, A., Benson, C. and Albright, W. (2001). Alternative Cover Assessment Program: Phase II Report, Geo-Engineering Report No. 01–10, University of Wisconsin, Madison. Boyes, R.G.H. (1975). Structural and Cut-Off Diaphragm Walls, Applied Science Publishers, London. Case International Company (1982). Case Slurry Wall Notebook, Manufacturers Data, Case International, Houston. Chen, J., Anadarajah, A. and Inyang, H.I. (2000). Pore fluid properties and compressibility of kaolinite. ASCE Journal of Geotechnical and Geoenvironmental Engineering, 126(9), 798–807. Clarke, R. (2002). Service life of landfill liner and cap components. In de Mello, L. and Almeida, M. (Eds.), Proceedings of the 4th International Congress on Environmental Geotechnics, Balkema, Rotterdam, pp. 933–946. Clement, T. (1997). A Modular Computer Model for Simulating Reactive Multi-species Transport in 3-dimensional Ground Water Systems, Pacific Northwest Laboratory, PNNL-SA-28967, Richland, WA. Corser, P. and Cranston, M. (1991). Observations on the performance of composite clay liners and covers. Proceedings of the Geosynthetic Design and Performance, Vancouver Geotechnical Society, Vancouver, BC, May 24, p. 16. Coughlin, B.R. and Stone, A.T. (1995). Nonreversible adsorption of divalent metal ions (MnII, CoII, NiII, CuII and PbII) onto goethite: Effects of acidification, FeII addition, and picolinic acid addition. Environmental Science and Technology, 29, 2445–2455. D’Appolonia, D. (1980). Soil-bentonite slurry trench cutoff walls. Journal of Geotechnical Engineering Division, ASCE, 106(4), 399–417.

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D’Appolonia, D. (1982). Slurry trench cut-off walls for hazardous waste isolation. Proceedings of the 13th Annual Geotechnical Lecture Series, Philadelphia Section, American Society of Civil Engineers, Philadelphia, PA. Daniel, D. (1993). Geotechnical Practice for Waste Disposal, Chapman and Hall, London. Dwyer, S. (2001). Finding a Better Cover, Civil Engineering, ASCE, 71(1), 58–63. Elder, C., Benson, C. and Eykholt, G. (2001). Economic and performance based design of monitoring systems for PRBs, Proceedings of the 2001 International Containment and Remediation Technology Conference and Exhibition, Institute for International Cooperative Environmental Research, Florida State University, Tallahassee, FL, pp. 1–5. Elder, C., Benson, C. and Eykholt, G. (2002). Effects of heterogeneity on influent and effluent concentrations from horizontal permeable reactive barriers. Water Resources Research, 38(8), 27-1 to 27-2. Estornell, P. and Daniel, D.E. (1992). Hydraulic conductivity of three geosynthetic clay liners. Journal of Geotechnical Engineering, ASCE, 118(10), 1592–1606. Evans, J., Dawson, A. and Opdyke, S. (2002). Slurry walls for groundwater control: A comparison of UK and US practice. Proceedings of the 19th Central Pennsylvania Geotechnical Seminar: Current Trends in Geotechnical Engineering, Hershey, PA. Eykholt, G., Elder, C. and Benson, C. (1999). Effects of aquifer heterogeneity and reaction mechanisms uncertainty on a reactive barrier. Journal of Hazardous Materials, 68, 73–96. Farrell, J., Kason, M., Melitas, N. and Li, T. (2000). Investigation of the long-term performance of zero-valent iron for reductive dechlorination of trichloroethylene. Environmental Science and Technology, 34(3), 514–521. Fleming, L.N. and Inyang, H.I. (1995). Permeability of clay-modified fly ash under thermal gradients. ASCE Journal of Materials in Civil Engineering, 7(3), 178–182. Garcia-Miragaya, J. and Page, A.L. (1976). Influence of exchangeable cations on the sorption of trace amounts of cadmium by montmorillonite. Journal of the Soil Science Society of America, 41, 718–721. Gavaskar, A., Gupta, N., Sass, B., Janosy, R. and O’Sullivan, D. (1998). Permeable Reactive Barriers for Groundwater Remediation, Design, Construction and Monitoring, Battelle Press, Columbus, OH. Gee, G., Ward, A., Gilmore, B., Link, S., Dennis, G. and O’Neil, T. (1996). Hanford Protective Barrier Status Report: FY 1996, PNNL-11367, Pacific Northwest National Laboratory, Richland, WA. Gillham, R. and O’Hannesin, S. (1994). Enhanced degradation of halogenated aliphatics by zero-valent iron. Ground Water, 32(6), 958–967. Gillham, R.W., Ritter, K., Zhang, Y., Odziemkowski, M.S. (2001) Factors in the long-term performance of granular iron PRBs. Proceedings of the 2001 International Containment and Remediation Technology Conference and Exhibition, Institute for International Cooperative Environmental Research, Florida State University, Tallahassee, FL. Giroud, J.P., Badu-Tweneboah, K. and Bonaparte, R. (1992). Rate of leakage through a composite liner due to geomembrane defects. Geotextiles and Geomembranes, 11(1), 1–28. Giroud, J.P., King, T.D, Snaglerat, T.R., Hadj-Hamou, T. and Khire, M.V. (1997). Rate of liquid migration through defects in a geomembrane placed on a semi-permeable medium. Geosynthetics International, 4(3–4), 349–372.

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Guertin, J.D. and McTigue, W.H. (1982). Preventing groundwater into completed transportation tunnels and recommended practice: Volume 2. U.S. Department of Transportation, Federal Highway Administration, Washington, DC. Haxo, H.E. (1987). Assessment of techniques for in situ repair of flexible membrane liners, EPA 600/2–87–038, U.S. Environmental Protection Agency, Cincinnati, OH. Hsuan, Y. and Koerner, R. (1998). Antioxidant depletion lifetime in high density polyethylene geomembranes. Journal of Geotechnical and Geoenvironmental Engineering, 124(6), 532–541. Inyang, H.I. (1992). Selection and design of slurry walls as barriers to control pollutant migration, Office of Solid Waste and Emergency Response, U.S. Environmental Protection Agency, Washington, DC, 37 pp. Inyang, H.I. (1996). Sorption of inorganic chemical substances by geomaterials and additives, Report CEEST/001R-96, University of Massachusetts, Lowell, MA. Sponsored by the Contaminant Transport Modeling Team, DuPont Company, 59 pp. Inyang, H.I., Iskandar, A. and Parikh, J.M. (1998). Physico-Chemical Interactions in Waste Containment Barriers, Encyclopedia or Environmental Analysis and Remediation, Vol. 2, Wiley, New York, pp. 1158–1165. ITRC (1999a). Interstate Technology and Regulatory Cooperation Work Group Permeable Reactive Barriers Work Team, Regulatory Guidance for Permeable Reactive Barriers Designed to Remediate Inorganic and Radionuclide Contamination. ITRC (1999b). Interstate Technology and Regulatory Cooperation Work Group Permeable Reactive Barriers Work Team, Regulatory Guidance for Permeable Reactive Barriers Designed to Remediate Chlorinated Solvent Contamination, 2nd edition. Jefferis, S. (1981). Bentonite–cement slurries for hydraulic cut-offs. Proceedings of the Tenth International Conference on Soil Mechanics and Foundation Engineering, Vol. 1, Balkema, Rotterdam, pp. 425–440. Jefferis, S. (2001). Permeability: A dynamic property of barrier materials. Proceedings of the 2001 International Containment and Remediation Technology Conference and Exhibition, Institute for International Cooperative Environmental Research, Florida State University, Tallahassee, FL, pp. 1–5. Khire, M., Benson, C. and Bosscher, P. (1997). Water balance modeling of earthen landfill covers. Journal of Geotechnical and Geoenvironmental Engineering, ASCE, 123(8), 744–754. Köber, R., Schlicker, O., Ebert, M. and Dahmke, A. (2002). Degradation of chlorinated ethylenes by Fe0: Inhibition processes and mineral precipitation. Environmental Geology, 41, 644–652. Koerner, R.M. and Daniel, D.E. (1997). Final Covers for Solid Waste Landfills and Abandoned Dumps, ASCE Press, Reston, VA, 256 pp. Koerner, R.M. and Guglielmetti, J.L. (1996). Vertical barriers: Geomembranes. In Rumer, R.R. and Mitchell, J.K. (Eds.), Assessment of Barrier Containment Technologies, National Technical Information Service, Springfield, VA, pp. 95–118. Kuo, S. (1996). Concurrent sorption of phosphate and zinc, cadmium, or calcium by hydrous ferric oxide. Journal of the Soil Science Society of America, 50, 1412–1419. Laase, A., Korte, N., Baker, J., Dieckmann, P., Vogan, J. and Focht, R. (2000). Evaluation of the Kansas City plant iron wall. In Wickramanayake, G. et al. (Eds.), Chemical Oxidation and Reactive Barriers, Remediation of Chlorinated and Recalcitrant Compounds, Battelle Press, Columbus, OH, pp. 417–424. LaGrega, M., Buckingham, P. and Evans, J. (2000). Hazardous Waste Management, 2nd ed., McGraw-Hill, New York.

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Lee, T. and Benson, C. (2000). Flow paste bench-scale vertical cut-off walls. Journal of Geotechnical and Geoenvironmental Engineering, ASCE, 126(6), 511–520. Li, L. (2002). Modeling fouling and its impact on long-term performance of granular iron PRBs, PhD Preliminary Exam Report, University of Wisconsin–Madison. Mackenzie, P., Horney, D. and Sivavec, T. (1999). Mineral precipitation and porosity losses in granular iron columns. Journal of Hazardous Materials, 68, 1–17. Mayer, K. Blowes, D. and Frind, E. (2001). Reactive transport modeling of an in situ reactive barrier for the treatment of hexavalent chromium and trichloroethylene in ground water. Water Resources Research, 37(12), 3091–3103. Mayer, K. Frind, E. and Blowes, D. (2002). Multicomponent reactive transport modeling in variably saturated porous media using a generalized formulation for kinetically controlled reactions. Water Resources Research, 38, 1174. Melchior, S. (1997). In situ studies on the performance of landfill caps. Proceedings of the International Containment Technology Conference, St. Petersburg, FL, pp. 365–373. Mergener, E., Li, L. and Benson, C. (2002). Assessing Clogging of PRBs Using a Geochemical Model, Geo Engineering Report No. 02–10, Dept. of Civil and Environmental Engineering, University of Wisconsin–Madison. Millet, R.A. and Perez, J.Y. (1981). Current USA practice: Slurry wall specifications. Journal of Geotechnical Engineering Division, ASCE, 107(8), 1041–1056. Milne-Home, W.A. and Schwartz, F.W. (1989). Empirical approaches for estimating flow and transport parameters, Proceedings of the Conference on New Field Techniques for Quantifying the Physical and Chemical Properties of Heterogeneous Aquifers, Dallas, TX, pp. 77–98. Morrison, S., Metzler, D. and Carpenter, C. (2001). Uranium precipitation in a PRB by progressive irreversible dissolution of zerovalent iron. Environmental Science and Technology, 33(16), 2793–2799. Murray, R.S. and Quirk, J.P. (1982). The physical swelling of clay in solvents. Soil Science Society of America Journal, 46, 865–868. Naftz, D., Morrison, S., Fuller, C. and Davis, J. (2002). Handbook of Groundwater Remediation Using Permeable Reactive Barriers, Academic Press, Amsterdam. Othman, M.A., Bonaparte, R. and Gross, B.A. (1997). Preliminary results of study of composite liner field performance. Proceedings of GRI-10 Conference on Field Performance, of Geosynthetics and Geosynthetic Related systems, G11 Publications, Philadelphia, PA, pp. 115–142. PCA (1984). Cement-bentonite slurry trench cutoff walls, Portland Cement Association Concrete Information Series, 11 pp. Petrov, R.J., Rowe, R.K. and Quigley, R.M. (1997). Selected factors influencing GCL hydraulic conductivity. Journal of Geotechnical and Geoenvironmental Engineering, ASCE, 123(8), 683–695. Phillips, D., Gu, B., Watson, D., Roh, Y., Liang, L, Lee, S. (2000). Performance evaluation of a zerovalent iron reactive barrier: mineralogical characteristics. Environmental Science and Technology, 34(19), 4169–4176. Pratt, A., Blowes, D. and Ptacek, C. (1997). Products of chromate reduction on proposed subsurface remediation material. Environmental Science and Technology, 31(9), 2492–2498. Puls, R.W. and Bohn, H.L. (1988). Sorption of cadmium, nickel and zinc by kaolinite and montmorillonite suspensions. Journal of the Soil Science Society of America, 52, 1289–1292.

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Puls, R., Blowes, D. and Gillham, R. (1999). Long-term performance monitoring for a permeable reactive barrier at the U.S. Coast Guard support center, Elizabeth City, North Carolina. Journal of Hazardous Materials, 68, 109–124. Rad, N.S., Jacobson, B.D. and Bachus, R.C. (1994). Compatibility of geosynthetic clay liners with organic and inorganic permeants. Proceedings of the 5th International Conference on Geotextiles, Geomembranes and Related Products, Singapore, pp. 1165–1168. Reddi, L.N. and Inyang, H.I. (2000). Geoenvironmental Engineering: Principles and Applications, 1st ed., Marcel Dekker, New York, 494 pp. Roesler, A., Benson, C. and Albright, W. (2002). Field Hydrology and Model Predictions for Final Covers in the Alternative Cover Assessment Program — 2002, GeoEngineering Report No. 02–08, University of Wisconsin, Madison. Roh, Y., Lee, S., Elless, M. (2000). Characterization of corrosion products in the permeable reactive barrier. Environmental Geology, 40(1–2), 184–194. Rowe, R. and Sargam, H. (2002). Durability of HDPE geomembranes. Geotextiles and Geomembranes, 20, 77–95. Rumer, R. and Mitchell, J. (1995). Assessment of Barrier Technologies, A Comprehensive Treatment for Environmental Remediation Applications, National Technical Information Service, Springfield, VA. Ryan, C.R. (1976). Slurry Cutoff Walls: Design and Construction, Geo-Con Inc., Pittsburgh. Ryan, C.R. and Day, S.R. (1986). Performance evaluation of cement-bentonite slurry wall mix design. Proceedings of the 7th National Conference on Management of Uncontrolled Hazardous Waste Sites, Washington, DC. Sass, B., Gavaskar, A., Yoon, W.S. and Reeter, C. (2001). Analysis of corrosion compounds associated with permeable reactive barriers and their impact on barrier longevity. 221st National Meeting, American Chemical Society. San Diego, CA. Preprint Extended Abstracts, Division of Environmental Chemistry, 41(1), pp. 1161–1166. Schuhmacher, T., Odziemkowski, M., Reardon, E. and Gillham, R. (1997). Identification of precipitates formed on zero-valent iron in anaerobic aqueous solutions. Proceedings of the International Containment Technology Conference, St. Petersburg, FL, pp. 801–805. Singer, A. and Berkgaut, V. (1995). Cation exchange properties of hydrothermally treated coal fly ash. Environmental Science and Technology, 29, 1748–1753. Stormont, J., Ankeny, M. and Tansey, M. (1994). Water removal from a dry barrier cover system. In Gee, G. and Wing, N. (Eds.), In-Situ Remediation: Scientific Basis for Current and Future Technologies, Battelle Press, Columbus, OH, pp. 325–345. Tachavises, C. (1998). Flow rates past vertical cut-off walls: influential factors and their impact on wall selection. Ph.D. dissertation, University of Wisconsin–Madison. Tachavises, C. and Benson, C. (1997). Hydraulic importance of defects in vertical groundwater cutoff walls. In Evans, J. (Ed.), In Situ Remediation of the Geoenvironment, GSP No. 71, ASCE, Reston, VA, p. 168–180. Thorstad, P. (2002). Failure of a geosynthetic clay liner in a landfill cap. M.S. Thesis, University of Wisconsin–Madison. Tratnyek, P.G., Scherer, M.M., Johnson, T.J. and Matheson, L.J. (2003). Permeable reactive barriers of iron and other zero-valent metals. In Tarr, M.A. (Ed.), Chemical Degradation Methods for Wastes and Pollutants: Environmental and Industrial Applications, Marcel Dekker: New York. USACE (1976). Excerpt from Lake Chicot P.S. (Mississippi) Bid Package, Vicksburg District, Section 2 Slurry Trench, USACE.

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USDOE (1999). 200-BP-1 Prototype Barrier Treatability Test Report. DOE/RL-99–11, U.S. Department of Energy, Richland, WA. USEPA (1985). Draft minimum technology guidance on double liner systems for landfills and surface impoundments — Design, construction and operation, EPA 530/SW85–014, Office of Solid Waste, U.S. Environmental Protection Agency, Washington, DC. Ward, A. and Gee, G. (2000). Hanford site surface barrier technology. In Looney, B. and Falta, R. (Eds.), Vadose Zone Science and Technology Solutions, Battelle Press, Columbus, OH. pp. 1415–1423. Warner, S. and Sorel, D. (2001). ASCE National Convention, Special Symposium on Innovative DNAPL Characterization and Remediation Methods, American Society of Civil Engineers, Washington, DC. Wilkin, R., Puls, R. and Sewell, G. (2002). Long-Term Performance of PRBs Using ZeroValent Ion: An Evaluation at Two Sites, USEPA Environmental Research Brief, 18 pp. Wilson, J., Mandell, W., Paillet, F., Bayless, E., Hanson, R., Kearl, P., Kerfoot, W., Newhouse, M. and Pedler, W. (2001). An Evaluation of borehole flowmeters used to measure horizontal ground-water flow in limestones of Indiana, Kentucky, and Tennessee, 1999. Water-Resources Invest. Rep. 01–4139, U.S. Geological Survey, Indianapolis, IN, 129 pp. Xanthakos, P.P. (1979). Slurry Walls, McGraw-Hill, New York. Yabusaki, S.B., Cantrell, K., Sass, B. and Steefel, C.I. (2001). Multicomponent reactive transport in an in situ zero-valent iron cell. Environmental Science and Technology, 35(7), 1493–1503. Yong, R.N. and Galvez-Cloutier, R. (1993). pH control on lead accumulation mechanisms in kaolinite-lead contaminant interaction, Proceedings of the International Conference on the Environment and Geotechnics, Paris, France, pp. 1–8. Ziper, C., Komarneni, S. and Baker, D.E. (1988). Specific cadmium sorption in relation to the crystal chemistry of clay minerals. Journal of the Soil Science Society of America, 52, pp. 49–53.

4

Airborne and Surface Geophysical Method Verification Prepared by* Ernest L. Majer Lawrence Berkeley National Laboratory, Berkeley, California

4.1 GEOPHYSICAL METHOD APPLICATION AND USE The complexity of using geophysical and remote sensing methods for hazardous waste containment transcends the already challenging problems associated with mineral exploration and groundwater and petroleum exploration and production. Hydrologists and petroleum reservoir engineers have studied the flow of water, oil, and gas in porous permeable rocks and unconsolidated sediments for many years. The oil industry has developed first-order methods of analysis that are remarkably successful in assessing the potential of an aquifer or reservoir to supply a given fluid or gas for some period of time. However, these analyses seem almost trivial compared to the task of finding, monitoring, and removing subsurface contaminants. In terms of monitoring barriers the task may or may not be as challenging as finding and characterizing subsurface contaminants. This is due to several different issues specific to barriers. If one is trying to see a change in the properties of a barrier it is not as challenging as seeing absolute changes. If one is trying to characterize or find a leak in the barrier this may be just as difficult as finding a contaminant. The issue is particularly challenging because of the following: * With contributions by Randolph J. Cumbest, Westinghouse Savannah River Company, Aiken, South Carolina; Bruce Davis, National Aeronautics and Space Administration, Stennis Space Center, Mississippi; William E. Doll, Oak Ridge National Laboratory, Oak Ridge, Tennessee; Leland Estep, Lockheed Martin, Midland, Texas; Susan S. Hubbard, Lawrence Berkeley National Laboratory, Berkeley, California; John D. Koutsandreas, Florida State University, Tallahassee, Florida; David P. Lesmes, Boston College, Chestnut Hill, Massachussetts; H. Frank Morrison, University of California, Berkeley, California; Lee D. Slater, University of Missouri at Kansas City, Kansas City, Missouri; Anderson L. Ward, Battelle Pacific Northwest Laboratory, Richland, Washington; Chester Weiss, Sandia National Laboratories, Albuquerque, New Mexico.

209

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In traditional oil and gas subsurface applications, a 50% recovery rate is considered a great success. The great majority of geophysical and remote sensing methods were developed with this level of sensitivity. In remediation applications, this recovery rate is usually not sufficient. Although oil and gas applications are multi-phase, the variations in the properties are not as large as in near-surface, partially saturated systems encountered in the vadose zone or even in saturated environments (i.e., groundwater contaminants can be particles, chemicals that dissolve in water, or liquids or gases that are only partially soluble in water). Under certain conditions, some contaminants can move through unsaturated soils and rocks as vapor. Contaminants can also interact strongly with the minerals in the subsurface. Clays can absorb some contaminants while some may form chemical complexes with other groundwater chemicals. Immiscible dense liquids can settle vertically, while some may become nutrients for microbes that are present naturally or have been introduced. All of these interactions may or may not affect the geophysical signals. A variety of methods exist that could be classified as geophysical techniques; however, this chapter focuses on geophysical methods that are used to infer volumetric (average over a volume of material rather than at a point) rather than point properties, i.e., crosshole, surface, and surface to borehole methods rather than well-logging techniques which usually only measure a few centimeters to a meter away from the borehole. The methods are assumed to be applied from the surface and boreholes or by placing sensors and/or sources in or near the barriers, thus imaging the volume or planes between the surface and borehole, the volume from the surface to the borehole, or a volume from the surface to a reflector or other target in the subsurface. Last but not least, two main applications are assumed with respect to barriers: (1) the initial and subsequent characterization of the subsurface volume to be contained, and (2) the verification of the integrity and performance of the barriers. These issues are linked and must be addressed to validate overall system performance.

4.1.1 CHARACTERIZATION

AND

GEOPHYSICS

A simple definition of characterization is mapping the distribution of contaminant sources and effluents as well as the physical, chemical, and biological properties of the subsurface materials that control their distribution, concentration, and movement. Some of the physical properties required are lithology, fault/fracture properties, porosity, permeability, grain size, and fluid type and saturation. Rock or soil types, mineralogy and distribution, and types of clay minerals are also needed to model chemical processes. Chemical state, temperature, fluid saturation, and other factors that affect the presence and amount of nutrients are also needed to determine microbe behavior. Characterization as defined here is the essential first step toward containment and/or remediation, but all too often the term is used only to describe the extent of the contamination itself, usually over

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a small area or volume that is relatively small compared to the entire groundwater system in which it resides. This concept of total system characterization is critical in containment applications because, as will be seen, the application of geophysical methods for containment depends on detecting changes from background or initial conditions. As a result, characterization efforts are currently often limited to determining the nature and extent of the toxic materials and not defining the whole regime in which they are traveling, interacting, and evolving. This limited definition can be useful in small-scale sites where the solution is excavation, but it is only half of the story at thousands of larger scale sites. The additional concept that the distribution of properties and processes should also be characterized is just now being incorporated into idealized or conceptual models of hypothetical sites in anticipation of when actual site data permit contaminant fate and transport simulation and eventual remediation. Only in the last five years have geophysical methods been used to measure the spatial distribution of the properties at actual sites to provide constraints for ground water models in a quantitative sense (Hubbard et al., 2001, 2003; Grote et al., 2003). If the subsurface were uniform or even uniformly layered, drilling on a loose grid of holes would probably suffice to characterize the site. Unfortunately, the subsurface is generally heterogeneous, and a program based on drill-hole samples and measurements would provide incomplete or, at worst, misleading information. Thus, volumetric information (information connecting the actual points of measurements) is needed. Geophysical methods are needed to: (1) provide the spatial distribution of certain physical properties that are essential for site characterization; (2) map the distribution of some contaminants; and, in some cases, (3) detect chemical changes associated with contaminant interaction with the subsurface and barriers. Indeed, a useful definition of applied geophysics is that it is the science of using physical measurements or experiments on the surface (or from boreholes drilled from the surface) to determine the physical properties and processes in the subsurface. Geophysics is ideally suited for extrapolating measurements obtained from a borehole to the large-scale volume away from the borehole (Peterson et al., 1985; Parra, 1991; Krohn, 1992; Sheets and Hendrickx, 1995; Majer et al., 1997). In this application, geophysical measurements obtained from the surface or between boreholes can be used to assess the continuity and homogeneity of the intervening material. Geophysics can also serve to map the subsurface in the absence of boreholes and can be used to detect the unexpected such as a change in lithology, fractures, or fast paths (Leary and Henyey, 1985, Davis and Annan, 1989, Hendrickx et al., 2002, Hubbard et al., 2002, 2003). Failure to be aware of such gross heterogeneity has a major impact on hydrologic flow models and contaminant transport (Majer et al., 1997). Finally, geophysical methods could be used to delineate contaminants if the waste was buried in containers because the waste containers produce a geophysical anomaly or the waste alters the properties of the medium (Doll et al., 2000). Table 4.1 shows the different resolution of the seismic and electrical methods and their expected use and application.

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TABLE 4.1 Possible Surface Geophysical Methods for Verification of Subsurface Barriers Method

Seismic

Electrical (electromagnetic, induced polarization, self potential, DC resistivity) Radar

Radar zero off-set (ZOP) velocities Radar tomographic velocity

Purpose

Success

Surface Methods Host Fair characterization, caps and walls Host Good characterization, caps and walls Host Good characterization, caps and walls Borehole Methods Barrier detection Excellent Barrier detection

Excellent

Radar tomographic amplitudes Radar well-to-well reflection Electrical resistance tomography Electrical resistance tomography

Barrier detection

Excellent

Barrier detection

Poor

Barrier detection

Good

Leak detection

Excellent

Seismic ZOP and tomography

Barrier detection

Poor

a

Comments

Use for structure and lithology of interior Fluid content and conductivity

Expected Resolutiona

0.5–5 m

1.0–10 m

Water content and lithology

0.5–2.0 m

Processed for differences Processed for differences Processed for differences Low signal-tonoise ratio

0.25 m 0.25 m 0.25 m

0.5 m Differences during salt water flood Injected air destroyed signal

0.25 m

Estimated only for successful borehole methods.

4.1.2 PERFORMANCE MONITORING

AND

GEOPHYSICS

An important need for geophysics is for monitoring the processes that are implemented to remove, contain, or treat contaminants. In the case of containments, the ability of geophysical methods to monitor the emplacement and performance of the barriers primarily depends on the geophysical contrasts of the barrier and subsurface. However, in some cases, even though the barrier does not look any different than the surrounding properties, geophysics could possibly monitor changes in the barrier properties relative to the native materials, monitor flow

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paths within the contained zone, and/or detect processes occurring due to the presence of contaminants. Once a site has been characterized and modeled and a remediation process designed and implemented, it is necessary to assess the effectiveness of the remediation operation. Geophysical methods are ideally suited to this task, because it is often easier to monitor changes in some portion of the subsurface than it is to uniquely determine the subsurface properties themselves, i.e., time-lapse monitoring (Dailey and Ramirez, 2000). An example of time-lapse data is given in Figure 4.1. This is a plan view of a site where moisture monitoring is performed by observing the changes in signals from ground-penetrating radar (GPR) (Grote et al., 2003). As seen in the differences 900 MHz: Time 1 60

20 12 m

Vine number

WET 40

DRY 0

155

105 Row number

900 MHz: Time 2

55 30 m

60

Vine number

WET 40

20 DRY 0

155

105

55

Row number 0.10

0.20 Volumetric water content

FIGURE 4.1 Comparison of volumetric water content estimates obtained from 900-MHz common off-set GPR ground wave data during two different times of the year over a natural field study site. These images reveal a persistence of near-surface water content spatial distribution at the site, which was interpreted to be controlled by near-surface soil texture.

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between the two plan views of the radar reflectivity, it is easy to determine where moisture changes occur. Some of the information provided by geophysical methods is indirect, but the parameters measured can be related to the rock/soil properties needed. For example, the distribution of electrical conductivity is not a parameter that is directly useful in hydrological modeling, but when conductivity is used to obtain information on porosity, saturation, pore fluid salinity, and clay content then it becomes a vital parameter needed for characterization. The relationship between the properties measured with geophysics and the hydrologic or mineralogic properties is, in most cases, site-specific. To be effective, site characterization requires close integration of the geologic, hydrologic, chemical, and geophysical data.

4.1.3 GEOPHYSICAL METHODS FOR SITE CHARACTERIZATION AND MONITORING OF SUBSURFACE PROCESSES The geophysical methods most directly applicable for characterizing and monitoring hazardous waste sites can be divided into the following general categories: seismic; electrical and electromagnetic; natural field and magnetic (e.g., gravity, tilt); and remote sensing methods. These categories were chosen for the different properties that are fundamentally sensed. Well-logging applications are considered here as point measurements and are not included in the detailed discussions that follow. This is not to imply that well logging should not be included in a geophysical program. The opposite is true. Well logging is fundamental to all databases and should be the rule, not the exception. 4.1.3.1 Seismic Seismic methods are used to measure the distribution of elastic wave velocity (compressional and shear) and the attenuation of the different seismic waves in the ground. Seismic velocity depends on many factors, but the primary factors affecting seismic measurements are porosity, mechanical compressibility, shear strength, fracture content, density, fluid saturation, and clay content. Some of these parameters are directly related to important hydrologic properties and others are used to map the distribution of soil and rock types. The most common use of seismic methods is mapping interfaces between materials of different seismic velocities to provide high-resolution images of the locations of lithologic properties and thus infer main flow channels and soil types. Cross-hole seismic tomography is now used for petroleum reservoir characterization and will be equally important in hazardous waste site characterization. 4.1.3.2 Electrical and Electromagnetic Electrical and electromagnetic methods are used to measure the distribution of electrical conductivity and the dielectric constant of the ground. Electrical conductivity of soils and rocks depends entirely on the conduction paths created by

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fluids in the pore spaces and is determined by porosity, saturation, pore fluid salinity, and clay content. In certain cases where the contaminants are ionic solutions, the electrical conductivity directly maps contaminant distribution (Endres et al., 2000). However, in most cases, the conductivity is used to extrapolate hydrologic measurements obtained from boreholes. The presence of clays that is so important in fluid flow and chemical absorption models brings about a distinctive frequency-dependent conductivity — the induced polarization effect. This effect is of immense value in monitoring site remediation processes because many processes involve injecting materials that profoundly alter this effect (Slater and Binley, 2003). A separate electrical property of soils and rock is the streaming potential effect, which is but one aspect of a whole class of interactions called coupled flow phenomena. Basically, driving forces of temperature gradients, hydraulic pressure gradients, chemical potentials, and voltage gradients produce flows of heat, fluid, chemicals, and electric current (Slater and Binley, 2003). These flows are coupled in the ground in the sense that not only does a pressure gradient produce a fluid flow but it also produces an electrical current flow — the streaming potential. Similarly, temperature gradients drive currents to produce thermoelectric effects. Another cross-coupling term of immense potential in contaminant studies is electro-osmosis, which is a flow of fluid produced by a voltage gradient. This phenomenon has been used in geotechnical engineering applications to stabilize embankments and assist in pile driving. It could be used to alter subsurface flow patterns by directing a particular contaminant plume to an extraction or treatment region. Because electro-osmosis depends on fluid conductivity, rock permeability, and the configuration of the imposed voltage gradients, the site must be well characterized in fluid conductivity and permeability before the design of a practical system can be implemented. 4.1.3.3 Natural Field and Magnetic Natural field methods consist of gravity, magnetic, and tilt methods. High accuracy measurements of gravity over the surface of the Earth (i.e., microgravity surveys) yield a measure of the subsurface density distribution, which, in turn, depends on the distribution of porosity, water content, and rock type. Borehole gravity measurements yield direct average volume values of density. Similarly, high accuracy measurements of magnetic field can be used to infer the distribution of magnetic minerals, usually magnetite, which, in turn, is related to rock type and certain sedimentary depositional environments where heavy minerals settle out of fluid flows. Tilt measurements have recently been used to measure deformation associated with fluid withdrawal and injection. By monitoring the rate of tilt or deformation, the rate of fluid movement can be inferred and an average permeability for the formation can be determined. Tilt and strain methods are low resolution, but for near-surface application they can be of some use in barrier monitoring. If gross changes in the density or geometry of the barrier changes on the order of a few percent, then these methods may be applicable. The drawback

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to achieving the necessary resolution is the installation of the gravity meters or tilt meters. Careful attention to stability and repeatability of the data must be maintained in addition to thermal stability and leveling. General directions of fluid movement, steam injections, or other density changes can also be monitored. In magnetic surveys, the distribution of the magnetization of the earth is measured from the surface, but these methods usually lack resolution for detailed subsurface studies. Borehole magnetometers are now being used to supplement more conventional well-logging tools to search for lithologic changes and chemicals/minerals that cause magnetization to change. 4.1.3.4 Remote Sensing Remote sensing is defined as the noninvasive observation of natural phenomena. It involves collecting information about an object by detecting differences between the object and the surroundings without being in physical contact with the object of observation. The differences that can be detected between objects of interest and their background involve shifts in various fields as observation moves from the background to an object of interest. Electromagnetic, acoustic, potential, and radiological are typical fields sampled by remote sensors for object detection. These types of sensors mounted on spaced-based (satellite) or airborne platforms can be used to rapidly and noninvasively characterize and monitor features and events on the earth’s surface with broad coverage and high resolution. Space-based or airborne hyperspectral, thermal, radar, and/or radiation sensors can provide a cost-effective alternative to traditional approaches. The spatially synoptic look achieved by remote sensing methods can improve the accuracy of area interpolations generated by point-sampled data. Ideally, the characterization and monitoring of waste sites and their containment systems would include remote sensing data, ground-based geophysical measurements, and point-sampled data. These data streams could then be integrated in a geographic information system (GIS) database with ancillary data concerning the barrier construction, geology, watershed hydrology, and climatology of the site.

4.2 SPECIFIC METHODS Although each method has generally been described, there are subsets of each method for specific applications. For example, seismic methods can be categorized further into active and passive methods, and even further into surface and borehole methods or some combination. Specific methods that are most applicable to environmental remediation needs are described below.

4.2.1 SEISMIC METHODS Seismic methods can be divided into passive and active methods. Passive methods involve listening to seismic energy being created by stress changes or natural seismicity such as micro-earthquakes or acoustic emissions near the boreholes

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or underground openings. Acoustic emissions for purposes described here are of secondary use. When monitoring a barrier, however, the barrier may emit acoustic emissions if it is brittle and possibly failing. Monitoring would involve a simple process of emplacing sensors in or near the barrier and monitoring for discrete events above a certain threshold. Active methods involve introducing energy into the ground with either an impact or controlled swept frequency source and observing how the seismic waveforms change due to heterogeneity or anisotropy in the subsurface or barrier. Both the direct and reflected arrivals of seismic waves (i.e., travel time and amplitude) can be used for this process. More sophisticated uses can involve guided wave energy in the barrier either during emplacement or for monitoring. Seismic reflection methods are used extensively in the petroleum industry for structural delineation and lithologic definition. New and sophisticated three-dimensional (3-D) surface and borehole methods have dramatically improved imaging capabilities for the petroleum industry, and can potentially be applied to remediation with proper instrumentation. The utility of seismic techniques also depends on the resolution obtainable in a given soil or rock type. For this reason, this discussion focuses on the seismic methods that have the highest resolution. Figure 4.2 shows the typical field configuration of a seismic surface and a cross-borehole configuration of a seismic survey. These configurations can be generalized to other techniques such as radar and electrical methods. Knowing the location of the source and receiver, the data can be inverted to derive the properties of the earth. A typical set-up of a surface geophysical survey (top image of Figure 4.2) consists of a source and receiver on the surface and documentation of the different arrivals from the source. This example is typical for a radar or seismic survey (Hubbard et al., 2003). The bottom figure shows a typical example of a crossborehole survey with different sources and receivers at different points so that a tomographic and/or a reflection image between the boreholes is obtained. The goal of seismic surveys is to describe or map the velocity and attenuation of seismic waves through the volume of interest. In general, this process is referred to as imaging, although the extent to which a complete or 3-D image can be formed depends on the availability of a suitable distribution of source–receiver combinations and the frequency content of the seismic waves. When a cross section of seismic parameters can be determined, the process is also referred to as tomography. Surface methods depend on sources and receivers distributed on the surface. Combined with sources and/or receivers in boreholes or the barriers themselves, a true 3-D image can be formed. Figure 4.3 shows typical images from a surface radar survey and a cross-borehole tomographic survey. Shown are the source and receiver pairs and the ray path coverage, very similar to seismic geometry. Seismic imaging could play an important role in site characterization, performance confirmation, and monitoring tasks. It could be used to estimate and extrapolate the extent and shape of soil property distributions that are measured only at discrete points with borehole methods. It can also be effectively used to detect features not mapped in the exploratory or initial phase of remediation and

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6

0

1

2

3

4

5

6

Locations 7 of sources

7

6 7

8

Locations of 8 receivers

9

9

10

10

11 0 1 2 3 4 5 6 7 Example of tomographic data acquisition geometry 11

Air TX ε1

Air wave Critically Ground wave refracted wave

RX ε1 > ε1

Reflected wave

ε2

Refracted wave

FIGURE 4.2 A typical set-up of a surface geophysical survey (top) where one places a source and a receiver and records the different arrivals from the source, this example is for a radar or seismic survey (Hubbard et al., 2003). The bottom figure shows a typical example of a cross-borehole survey with different sources and receivers at different points so that one obtains a tomographic or reflection image between the boreholes.

to monitor changes in properties in the site area from measurements obtained entirely outside the critical volume. The transmission and attenuation of seismic waves through the subsurface depends on the elastic parameters, which depend on, among other things, the state of stress and strain, porosity, clay content, grain size, and fluid saturation. As recent research shows, high frequency seismic wave propagation is sensitive to discontinuities (fractures or joints) in the media (Majer et al., 1997). Seismic tomography can, therefore, be used to detect changes in the soil column condition, locate major preexisting and new features, and measure overall changes in the widths of these features. The methods that can be used for these studies use sources on the surface and detectors either in a borehole [referred to as vertical seismic profiling (VSP)] or in cross-hole configurations with both sources and receivers in boreholes. VSP techniques are primarily used for elucidating subsurface structures and determining seismic velocities of the various rock and/or soil horizons. In addition to the more conventional uses of VSP, the

5m 32

W 34

36 2200 2100 2000 1900 1800 1700 1600

36

Velocity 5 4 3 2 1 0

38 40

5 4 3 2 1 0

38 40

38

7 6 5 4 3 2 1 0

40

FIGURE 4.3 A typical example of data from a surface reflection survey showing the lithology (left-hand side). The figure on the right shows typical results from a crosswell tomographic survey correlated with the lithology.

10 m

34

36

400-207 (60 ft S of 407)

30

32

34

Silty-sandy zone

Days

28

30

32

10 m

E 26

28

30

Silts

24 26

28

Aqulard

22 24

26

Silt

MW155 (62 ft E of 406)

20 22

24

Sands

20

22

Gravels

20

Yellow unconformity

408-407 7 6 5 4 3 2 1 0

Sands

C02-C03aa

407-406 5 4 3 2 1 0

Mappaturg scarp

400-038 (49 ft N of 406)

5 4 3 2 1 0

Surface reconnaissance line 1100

P4G3

Airborne and Surface Geophysical Method Verification 219

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use of three-component VSPs for detecting and characterizing 3-D features has become routine in the oil industry. In the last several years, the petroleum and gas industry have started to extend the traditional uses of subsurface imaging from defining static properties to mapping changes in the reservoir conditions and monitoring production. To achieve accurate monitoring for the petroleum industry, new methods using multicomponent (P- and S-wave) seismic surveys have been developed to map subsurface anisotropy and heterogeneities from the surface and between boreholes (Daley et al., 1988a,b; Majer et al., 1988, 1997). The key to using the data, however, is the ability to relate the physical parameters measured using geophysical techniques to the parameters of interest to the hydrologist or reservoir engineer. An example is the relationship of seismic velocity to permeability. From past work in a variety of complex lithologies (Majer et al., 1988; Majer and Geller, 1992; Tura et al., 1992; Tura and Johnson, 1993; Geller and Myer, 1995; Hubbard et al., 2001; Geller et al., 2000), recent advances in wave propagation theory (e.g., shear wave splitting, fracture stiffness, guided waves, scattering, cross-well seismic reflection, amplitude and frequency variation with azimuth) must be integrated into the techniques employed in the petroleum industry and geotechnical fields to fully utilize the potential of seismic techniques at any scale. The conventional field and analysis techniques [e.g., lower frequency VSP and surface reflection less than 100 hertz (Hz)] do not detect thin features such as fractures or steeply dipping or near vertical faults, low velocity zones, zones of small or high seismic velocity contrasts, not to mention resolution on the scale to characterize process behavior. To a large degree, the information contained in the cross-well/tomographic techniques offers promise of higher resolution, especially if more than first arrival analysis is performed, and the elastic solution as well as the acoustic case are included (i.e., S and P waves). Frequency effects must be investigated especially when layered complex media exist. Using seismic tomography/cross-well techniques as a tool for resolving heterogeneity within bedded and fractured structures remains in development. In terms of processing/inversion schemes for highfrequency seismic data, the following four main approaches are possible: • • • •

Conventional and advanced ray and waveform tomography Guided/channel waves Scattered and reflected energy from voids/high contrast anomalies Cross-well/VSP/single well imaging employing azimuthal frequency and time-varying effects

4.2.1.1 Conventional and Advanced Ray and Waveform Tomography Like most inverse problems, the quality of the solution depends directly on the completeness and accuracy of available solutions to the forward problem. Conventional and advanced ray and waveform tomography include such simple

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approaches as algebraic reconstruction tomography (ART), simultaneous iterative reconstruction tomography (SIRT), and singular value decomposition (SVD) using first arrival data. Given sufficient data quality, these methods may be all that are necessary. Ray and waveform tomography approaches also consider more advanced analysis methods such as waveform tomography using exact and Fresnel approximations and amplitude tomography as well as ensemble averaging techniques. Conjugate gradient methods that can handle complicated structure and low velocity/high contrast zones can also be considered. 4.2.1.2 Guided/Channel Waves Guided wave continuity logging is emerging as a new tool in the oil and gas industry (Krohn, 1992; Nihei et al., 1999), and it likely will evolve into a powerful method for shallow subsurface environmental characterization (Liu et al., 1991). For example, the complex geometry and fracturing of the basalts at the Idaho National Engineering and Environmental Laboratory (INEEL), Idaho, may support Rayleigh interface waves that propagate along horizontal fractures (Gu et al., 1996), and a new type of channel wave that propagates in the fluid-saturated rubblized zones on the tops and bottoms of the flows. Unlike body waves that spread in three dimensions, channel waves are confined by the structure into two dimensions, resulting in less geometric spreading. Recent results by Nihei et al. (1999) support that channel waves can play an important role in the attenuation mechanism of seismic energy, thus being a diagnostic of fracture properties. Therefore, these waves can be used to probe geologic structures between wells spaced over substantial distances. 4.2.1.3 Scattered and Reflected Energy The third approach to consider is using scattered energy, particularly for detecting voids and high-contrast heterogeneity. As in the case of guided wave analysis, scattered wave field analysis needs full waveform data as opposed to only arrival times and amplitudes. This approach remains in the theoretical stage; practical application, although very powerful, is still not routine. The exact solution for scattering elastic waves by a homogeneous spherical obstacle is available and includes a complete analytical treatment of the problem and the implementation of the results in stable efficient computer codes (Korneev and Johnson, 1993a,b,c). The solutions were developed for incident P and S waves of arbitrary frequency and for obstacles having arbitrary properties, including the cases of solid, fluid, and empty obstacles. While a sphere may not be an accurate representation of many of the underground structures of interest, the solution to the problem of scattering by a sphere has fairly general applicability. A possible route of investigation could be the numerous advances obtained for this type of problem, which are an extension of the elastic inversion method found in Tura et al. (1992) and Tura and Johnson (1993). (This last paper contains a list of related work.) An investigation of the reliability of solutions to the inverse scattering problem could

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make use of the developments in general inverse theory that are found in Vasco (1993) and Vasco et al. (1993). 4.2.1.4 Cross-Well/VSP/Single Well Imaging Last but not least, cross-well/VSP/single well reflection methods are fairly new approaches, where reflection-processing methods developed for surface reflection techniques are used to image reflectors between and possibly below boreholes. These methods are applicable in layered sections with good impedance contrasts. However, if sufficient well coverage exists, a 3-D approach with varying azimuthal coverage using three-component data can provide useful information on media complexity, especially in fractured media. In the cross-well method, the source is activated at various levels in one hole and the receiver is placed at similar levels in the other hole, creating a crossing grid of ray paths for tomographic inversion. Usually in the radar and seismic cases, the first arrival times for each source-receiver pair are used for a tomographic image. The two-dimensional cross section between wells is divided into square pixels and the velocity (in the seismic case) is estimated in each pixel. The resolution of each pixel is dependent on the ray density in the seismic or radar case (Peterson et. al., 1985) and on the frequency content in the electromagnetic or DC resistivity. The data can also be inverted for attenuation. In this analysis, the amplitude of the first arrival is computed for each trace with sufficient signal-to-noise ratio. The two-dimensional cross section between wells is then divided into pixels, and each pixel is inverted for amplitude attenuation in decibels per meter (dB/m). Cross-well seismic as well as radar surveys have been used for many years to tomographically image P-wave velocity between wells (e.g., Mason, 1981; Peterson et al., 1985). More recently, cross-well S waves have also been used to map S-wave velocity (Harris et al., 1995), and both P- and S-wave cross-well reflectivities have been analyzed for structural delineation. Until about five years ago, nearly all cross-well seismic tomography was performed in sedimentary formations important to oil and gas exploitation. A seismic source used in the oil industry but not yet applied to environmental problems is the orbital vibrator. The operating principle of the orbital vibrator is rotation of an eccentric mass in the horizontal plane at increasing speeds, generating a swept frequency signal of clockwise and counter-clockwise polarizations (Daley and Cox, 1999). The orbital vibrator has a high frequency (now up to 750 Hz) and high power, is small (3.5 inches in diameter, 18 inches long), and puts out both P-wave and S-wave energy. It is easy to deploy and can work in fluid-filled holes. The orbital vibrator propagated P waves up to 100 m in a fractured basalt aquifer (Daley et al., 1999), significantly farther than a piezoelectric source used at the same site (albeit with a lower frequency band than the piezoelectric source). Tests using this source have been successful in acquiring P- and S-wave tomography data using fluid-coupled hydrophone sensors. In the case of direct current (DC) resistivity, multiple electrodes are placed in the subsurface either in uncased holes or with electrodes on the exterior of polyvinyl chloride (PVC) or fiberglass holes.

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Each electrode acts as a source or receiver, making data collection very efficient. Electromagnetic sources and receivers have been developed and are in routine use in the oil industry, but not efficiently downsized for the environmental field. The application of cross-well seismic methods to crystalline rock is often a more difficult problem than the application in sedimentary rock. The advantage of seismic imaging is the ability to detect or image features away from the borehole. Cross-well seismic imaging in fractured crystalline rock has been used to define the spatial distribution of velocity and attenuation that is related to fracture zones determined from other borehole techniques (e.g., Vasco et al., 1993; Cao and Greenhalgh, 1997). In fractured media, an important property defining the rock is fracture anisotropy. Anisotropy will also play an important role in imaging waste sites, as will heterogeneity in general. Imaging using P and S waves in borehole seismic studies is not a new idea (Stewart et al., 1981). It is becoming increasingly apparent, however, that to utilize the full potential of the seismic methods for characterizing fractured media, three-component data should be acquired. In imaging barrier sites and contaminated sites this is rare. Crampin noted the importance of using three-component data in VSP work, particularly for fracture detection (Crampin, 1978, 1981, 1984a,b, 1985). These authors and others have pointed out the phenomenon of shear wave splitting and the anisotropy effects of horizontal and vertical shear component waves in addition to primary and secondary wave anisotropy (Leary and Henyey, 1985). In addition to Crampin’s theoretical work on shear wave splitting (1978, 1985), laboratory (Pyrak-Nolte et al., 1990a,b) and theoretical work (Schoenberg, 1980, 1983) explain shear wave anisotropy in terms of fracture stiffness. The fracture stiffness theory differs from Crampin’s theory in that at a fracture or a nonwelded interface, the displacement across the surface is not required to be continuous as a seismic wave passes. The only solution boundary condition to the wave equation is that the stress must remain continuous across an interface. This displacement discontinuity is taken to be linearly related to the stress through the stiffness of the discontinuity. The implication of the fracture stiffness theory is that for very thin discontinuities (e.g., fractures), there can be significant effect on the propagation of a wave. Fracture sites, such as in basalt and other hard rocks, are of interest to barriers and their integrity. This implication applies to voids or any feature that represent discontinuity in the subsurface. Usually one thinks of seismic resolution in terms of wavelength as compared to the thickness and lateral extent of a bed or other feature. In the stiffness theory, the lateral extent is still important, but if the stiffness of the feature is small enough (i.e., a sand-filled void), the thickness of the feature can be much less than the seismic wavelength. In the case of unconsolidated sediments, a coupled solution must be found that takes into account the pore fluid (or gas) and matrix interactions. The situation becomes even more complicated when clay content is introduced into the matrix. At this point, multi-phase models must be considered to account for the observed effects. One such approach was tried for acoustic velocities in shale (Minear, 1982) where a two-phase model following Kuster and Tokoz (1974) was used. One phase was assumed to be the solid rock matrix and the other phase clay

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Barrier Systems for Environmental Contaminant Containment & Treatment

inclusions. This approach was attempted in order to explain deviations from what conventional theory would predict. Marion (1990) and Marion et al. (1992) developed relationships between seismic P-wave velocity and sand-clay mixtures using laboratory measurements. In this work, it was possible to establish an empirical relationship between porosity and sand-clay content. Klimentos and McCann (1990) developed empirical relationships between P-wave attenuation, porosity, and permeability in sandstone. Partially saturated materials pose a further complication. Anderson and Hampton (1980a,b) performed considerable work in both theory and measurement to reach an understanding of seismic wave propagation in gas-bearing sediments. Bedford and Stern (1983) also developed models for wave propagation in sediments. Ito et al. (1986) and Mochizuki (1982) also developed relationships between seismic velocity and attenuation for partially saturated material. Parra (1991) analyzed elastic wave propagation in stratified fluidfilled media to examine the effect of porosity and permeability. He extended Biot’s theory to include a point force in fluid-filled porous media. In a related study, Yamamoto et al. (1994) used variations in seismic velocities at different frequencies to map porosity variations. These are just a few empirical and model studies that have been conducted to relate seismic properties to physical parameters. These applications have been almost entirely for the petroleum industry. 4.2.1.5 Summary In summary, seismic methods historically have been used to image subsurface elastic properties. Only in recent years have researchers focused on relating seismic attributes to physical/chemical and microbial attributes at the scales proposed for remediation (Hubbard et al., 1997, 1999; Chen et al., 1999). Seismic data are well suited for extrapolating measurements obtained from a borehole to the large-scale volume away from the hole. In this application, measurements obtained from the surface or between holes can be used to assess the continuity and homogeneity of the intervening material. Therefore, field and modeling studies have shown that such features as anisotropy, fluid content, and heterogeneity have a measurable effect on the propagation of seismic waves. It appears possible to use shear wave anisotropy and 3-D tomography to map the orientation, density, and spacing of these features in the field and to give the hydrologist/reservoir engineer useful information on the fluid flow regime. A few percent change in properties produces effects that are easily detectable. These seismic methods are particularly informative if used in conjunction with the electrical methods discussed below.

4.2.2 ELECTRICAL

AND

ELECTROMAGNETIC METHODS

Electrical methods seem particularly promising in mapping and monitoring the groundwater regime of a site because the electrical conductivity of the subsurface depends almost entirely on the fluid saturation, salinity (conductivity), and distribution. Electrical and electromagnetic methods traditionally have been used to

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detect the presence of good electrical conductors (e.g., sulfide ore bodies) or determine the electrical layering in groundwater or petroleum exploration. Quantitative interpretation in terms of rock properties or even accurate mapping of the subsurface distribution of electrical conductivity (imaging) is not as advanced as that conducted seismologically. Only recently have numerical and theoretical studies advanced to the point where quantitative imaging complementary to seismic imaging can be expected. The electrical conductivity of rocks and unconsolidated sediments in the upper part of the Earth’s crust is governed by the water content and the nature of the water paths through the rock. Electrical current is carried by ions in the water; therefore, the bulk resistivity depends on the ionic concentration, ionic mobility, and the saturation and degree of connected pores. Conductivity is also temperature and pressure dependent because as the temperature increases, ion mobility increases and the pressure affects the apertures of the conduction paths. Most studies on the electrical conductivity of rocks and soils have involved sedimentary rocks because of their importance in petroleum and groundwater exploration. Archie (1942, 1947) established an empirical relationship between the pore fluid resistivity, Rp (inverse of conductivity); the porosity, P; and the formation resistivity, Rf, that is now referred to as Archie’s Law: Rf = A × Rp × P –m

(4.1)

where A and m are constants for a given rock type. For a wide range of sedimentary rocks and some volcanic and intrusive rocks as well, the constant, A, is close to unity and m is close to 2.0. Fluid saturation has a dramatic effect on the conductivity of porous materials (Telford et al., 1976). As water is withdrawn from a saturated rock, the large pores empty first; however, because small water passageways mainly control the resistivity, the bulk resistivity increases slowly. The dependence is roughly proportional to one over saturation squared. As desaturation progresses, critical saturation is reached when there is no longer any water to conduct along some pores. This breaking of conduction paths leads to a much more rapid increase in resistivity, roughly proportional to one over saturation to the fourth power. The critical saturation depends on the rock type (the nature of the porosity) and can depend strongly on the role of fast paths that are present. Combined with seismic velocity and attenuation, electrical measurements are valuable for monitoring resaturation progress at a site. An important and little studied aspect of rock and soil conductivity is the role of fast paths on the resultant bulk properties, particularly in barrier monitoring applications. Laboratory studies concentrate on small intact samples that, almost by definition, do not include open voids or joints. Field studies using surface resistivity measuring arrays are usually too strongly influenced by the inhomogeneous nature of the near surface to allow any distinction between voids and pore porosity of a particular rock unit. With the increased measurement accuracy and resolution provided by subsurface techniques and the interest in monitoring

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time changes in resistivity, it is now possible to investigate more closely the role of porosity on the electrical conductivity of large masses. It is well known that hydraulic conductivity is strongly influenced by the mean width, orientation, and spatial distribution of the fluid paths. Also, as noted in the preceding section, seismic velocities are strongly affected by discontinuities. However, expressions for the electrical conductivity of such material and taking advantage of this valuable physical property for characterizing and monitoring large subsurface volumes of soil remain to be developed. Channeling plays an important role in rock resistivity and is practically demonstrated in the work by Brace and Orange (1968a,b). Their work on the effects of confining pressure on the resistivity of a water-saturated granite showed that, at low pressures, the resistivity increased as the confining pressure increased. They attributed this effect to the closure of fracture porosity. A resistivity increase of a factor of 10 as the pressure increases could easily be explained by the disappearance of only 0.1% fracture porosity in a granite of 1.0% pore porosity. The electrical conductivity of the ground can be measured in two ways. In the first, referred to as the DC resistivity method, current is injected into the ground through pairs of electrodes and the resulting voltage drops are measured in the vicinity with other pairs of electrodes. Any or all of the electrodes can be placed in the subsurface, although traditionally surface arrays have been employed. Electrical resistivity tomography (ERT) uses electrodes in the subsurface to measure resistivity between the boreholes (Daily and Ramirez, 2000). Measurements of voltage and current for different electrode geometries are then used to infer the subsurface distribution of conductivity. These methods are indirect, but ideally suited to measure the properties of a region for which it is impossible to gain direct access. The resulting interpretation of the conductivity distribution is not unique nor does it provide high resolution of subsurface features. In many applications, this latter property is an advantage because the measurements yield bulk average values of the conductivity that often include features that are not included in hand samples or borehole logging measurements. The electrical conductivity can also be measured inductively. Instead of injecting a DC current into the ground, currents can be induced to flow by a changing magnetic field. The source of the changing magnetic field could be a loop of wire carrying alternating current or a long grounded wire carrying alternating current rather than direct current or the Earth’s natural electromagnetic field. The currents induced in the ground are measured either by detecting the magnetic fields they produce or measuring the voltage drops in pairs of electrodes. Sources and receivers can be on the surface, below the ground, or a combination of both. In these inductive or electromagnetic methods, the interpretation depends both on transmitter-receiver geometry and frequency used. In principle, the interpretation should be more definitive than with DC resistivity methods. Rigorous confirmation of this statement in heterogeneous media awaits the development of generalized inversion techniques for electromagnetic methods. Electromagnetic methods offer some proven advantages over DC methods. Measurements can be obtained without contacting the ground; measurements are

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insensitive to high resistivity zones; the investigation depth can be controlled by the frequency of operation so that large transmitter-receiver spacings are not required; and, because of the transmitter source field fall-off, the methods are not sensitive to conductivity inhomogeneities far from the zone of interest. The resolution of subsurface features with electromagnetic methods is limited because the frequencies that are low enough to penetrate to the desired depth cannot have a wavelength short enough to define structural features. The problem is compounded by surface layers that are invariably conductive, highly variable in thickness, and often act like shields to the subsurface. To overcome these problems, promising borehole electromagnetic methods exist. Pulsed borehole radar is an example of an electromagnetic technique that uses high frequencies (Hubbard and Rubin, 2000). Radar is becoming prevalent in a variety of environmental applications due to its ease of use and sometimes straightforward interpretation (Grote et al., 2003). If the ground conductivity is sufficiently low, megahertz radar waves can penetrate up to 100 m and can respond to dielectric contrasts within the rock mass as well as conductivity anomalies. Radar has been used successfully at some toxic waste sites to map buried objects and determine fine-scale structural features and map fluid flow in the vadose zone at a submeter scale (Hubbard and Rubin, 2000). In typical soils the range of radar can be from a few meters (using 500 MHz) to tens of meters (using 50 to 100 Hz) (Hubbard and Rubin, 2000). In more conductive rocks, the frequency of the electromagnetic fields must be reduced to achieve significant penetration. Then, the resolution decreases as the fields become diffusive in nature. The traditional low-frequency implementation of electromagnetic methods (less than a few kilohertz) for ore prospecting relies on quasi-static magnetic induction theory and basically ignores the wave propagation properties of the fields. In subsurface applications, especially in single- and cross-hole modes, there are exciting possibilities for electromagnetic methods in the frequency band between the prospecting and radar frequencies (i.e., the mid-frequency band).

4.2.3 NATURAL FIELD

AND

MAGNETIC METHODS

Dramatic developments have occurred in natural electromagnetic field methods, particularly magnetotellurics. Although magnetotellurics may not have the resolution for fine-scale studies, it is mentioned here for completeness. In magnetotellurics, the impedance of the ground is measured as a function of frequency. This impedance function is then interpreted in terms of a model of the earth. Traditionally, magnetotellurics has been plagued with problems in data quality and interpretation when the simple layered models used are inadequate. The data quality problem has been solved by using the remote reference method developed by Goubau et al. (1978) and improved instrumentation (sensors and high dynamic range acquisition systems now permit high-accuracy surveys that were previously not possible). Field evidence shows data errors of less than 1% in some frequency bands (Nichols et al., 1985). Interpretation has been a problem because the impedance was not sampled at adequate intervals on the surface. The electric fields

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change rapidly in response to near-surface resistivity variations and bias the impedances that, in effect, mask the deep structure that is sought. This bias can be treated by conducting dense station sampling using larger lines for the electric field measurements or, preferably, both. Many of these issues are being overcome with advanced computational methods and joint inversion of data (Gasperikova et al., 2003). In principle, the electric fields could be measured over a grid on the surface, with magnetic fields measured at the grid nodes and the conductivity distribution recovered accurately and unambiguously. Equipment is now available for such surveys but has not yet been tested.

4.2.4 AIRBORNE GEOPHYSICAL METHODS Airborne geophysical methods hold a middle ground between the ground-based geophysical methods described above and conventional remote sensing methods described in Section 4.2.5. Remote sensing is generally used to refer to multispectral, hyperspectral, thermal, or radar systems, which are typically obtained by satellites or aircraft at several hundred meters altitude. Airborne geophysical data include magnetic, electromagnetic, and GPR data, typically acquired at sensor altitudes ranging from 50 m to about 1 m. Conventional methods and applications for airborne geophysics are described by the National Research Council (1995). These airborne magnetic and electromagnetic systems have been used to image United States Department of Energy (USDOE) waste areas and caps (Doll et al., 2000). Recently, airborne magnetic and electromagnetic systems have been developed in which the sensors are housed in booms that are mounted directly to the helicopter. This technique allows airborne data to be acquired at altitudes as low as 1 to 2 m above ground level (AGL), where topography, cultural features, and vegetation permit. The boom-mounted systems have been used to detect and map unexploded ordnance and other metallic objects and can successfully map these objects with < 0.2 m accuracy when the unexploded shells are as small as 3 to 5 kg (i.e., the size of a small soup can). The Oak Ridge Airborne Geophysical System-Arrowhead (ORAGSArrowhead) is a production-level magnetometer system that is typically operated at altitudes of 1.5 to 3.0 m AGL, depending on site conditions (Figure 4.4). The sidebooms and foreboom house a total of eight cesium vapor magnetometers at a nominal spacing of 1.7 m, with two magnetometers each at the ends of the side booms and four spaced evenly across the V-shaped foreboom. The sensor positioning is designed to minimize noise from the helicopter rotor and other sources while maintaining a weight distribution that optimizes flight performance and, above all, safety. All data are recorded on a personal computer based console that samples the magnetometers and keys analog inputs (e.g., fluxgate) at 1.2 kHz and records laser-derived altitude and global positioning system (GPS) position at the full output rates of those devices. The magnetometer data are downsampled, typically to 120 Hz, and the other data are interpolated to the same sample frequency as the downsampled magnetometer data. Navigation is directed by an Agnav RT-DGPS system with Racal satellite real-time correction. Aircraft position

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FIGURE 4.4 The ORAGS-Arrowhead total field magnetometer system in operation.

is recorded on the system console and updated by post-processing with a DGPS base station to provide an accuracy of 0.2 m or better. Under optimal flight conditions, the system acquires data over a 12 m swath with a 1.75-m sensor spacing at a flight height of 1.5 m AGL. An Ashtech ADU-2 GPS-based system is used to monitor the altitude of the system to provide accurate sensor positioning. The ORAGS systems are typically operated at an air speed of 50 knots, allowing full coverage acquisition of a rate of about 50 to 70 acres per hour under favorable conditions. Figure 4.5 shows an analytic signal map for a site in Maryland where previous ground-based geophysical surveys were conducted. The airborne data set delineated a spider web of underground pipes that was overlooked during groundbased survey preparation and interpretation. Such a network of conductors almost certainly had a negative impact on the processing and interpretation of the ground surveys. The conductor network would not have been detected with a conventional airborne survey at conventional altitudes. Another ORAGS system is the ORAGS-Hammerhead system, which is useful for defining the boundaries and infrastructure of landfill sites that contain ferrous waste materials or containers. This system provides considerably more detail than a conventional towed-bird system. Oak Ridge National Laboratory (ORNL) and partners have recently completed a successful demonstration of an airborne timedomain electromagnetic prototype system, the ORAGS-TEM (Transient Electrical Methods) system, as an electromagnetic complement to the ORAGS-Hammerhead system. A photograph of the system is shown in Figure 4.6, and data acquired

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N

100

0

100 200 Meters

300

23.7 22.4 21.2 19.9 18.6 17.3 16.0 14.7 13.5 12.2 10.9 9.6 8.3 7.1 5.8 4.5 3.2 1.9 0.6 nT/m

FIGURE 4.5 Analytic signal map for a site in Maryland showing anomalies associated with a network of piping that had been overlooked in more localized ground-based surveys.

FIGURE 4.6 ORAGS-TEM system in transit near the Black Hills, South Dakota.

Airborne and Surface Geophysical Method Verification

9.0 7.9 6.9 5.9 4.9 3.8 2.8 1.8 0.8 −0.3 −1.3 −2.3 −3.3 −4.4 −5.4 −6.4 −7.4 −8.5 −9.5 mV

400750 400800 400850 400900

137450 137400 137350 137300 137250 137200 137150

137150 137200 137250 137300 137350 137400 137450

400750 400800 400850 400900 137450 137400 137350 137300 137250 137200 137150

137150 137200 137250 137300 137350 137400 137450

400750 400800 400850 400900

231

9.49 8.97 8.46 7.95 7.44 6.92 6.41 5.90 5.38 4.87 4.36 3.85 3.33 2.82 2.31 1.79 1.28 0.77 0.26 nT/m

400750 400800 400850 400900

FIGURE 4.7 Comparison of (a) ORAGS-TEM measurements and (b) an analytic signal map derived from ORAGS-Arrowhead magnetic measurements for a bombing target in South Dakota. TEM represent the first-time gate only, and data were acquired at 3 m nominal flight line spacing and 1.5–2 m altitude. Magnetometer results used the 8-sensor magnetometer system at the same altitude and 12 m flight-line spacing. The response of both systems to an east-trending barbed wire fence is seen across the center of the diagrams. The individual anomalies are associated with M-38 practice bombs, or their fragments. These are sand- or cement-filled devices with a mass of 10–15 kg when intact. Horizontal scale is in meters. (See color version insert of this figure.)

with the system are compared with data from the ORAGS-Arrowhead magnetic system in Figure 4.7. The system records the entire decay curve for each transmission, as does the EM-643 ground-based system. It is possible that the TEM system can be adapted to provide resistivities through an appropriate calibration procedure, but this possibility is only beginning to be investigated. In its current form, the TEM system responds to nonferrous metallic objects, ferrous materials, and some nonmetallic objects. Therefore, it is an appropriate tool for mapping materials in waste sites. If the TEM system can be successfully demonstrated as a tool for measuring resistivities, it could be suitable for time-lapse measurements of moisture or other resistivity-dependent effects that should be monitored at landfills or similar areas.

4.2.5 STATE-OF-THE-PRACTICE REMOTE SENSING METHODS Despite the fact that geophysics has been used successfully for many years in mineral, petroleum, and geothermal exploration, it has not been used effectively

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in remediation situations. By and large, the examples of geophysics applied to these problems that have appeared in the literature are very basic and display a level of application that characterized geophysics 15 to 20 years ago. Descriptions of the state of the practice of remote sensing methods are described in the subsections below. 4.2.5.1 Aerial Photography Aerial photography is a useful tool due to its well-understood technology and the many historical records of sites that contain aerial photos. Traditional aerial photos provide high spatial resolution imagery using black and white, natural color, or color infrared (CIR) film. Black and white film can still be useful in cases where high contrast differences enhance detection or location of a target area. Natural color aerial photos are often used to overlay data layers when using a GIS system. CIR imagery captures a scene in the near infrared (NIR) bands of the electromagnetic spectrum. The color imagery produced consists of false color images in which the colors serve to separate scene elements that reflect NIR radiant energy differently. CIR photos have been used to detect vegetation stress, which can be important in identifying plants that have become damaged due to leachate exposure. Moreover, CIR aerial photos can detect waterlogged areas and separate out conifers from certain deciduous species (Jensen, 1968). For either film or digital camera technology, a current aerial photo allows the investigator a synoptic view of site geographic/environmental features as well as its cultural aspects. A significant aspect of aerial photos is the historical record that aerial photos represent. For example, many waste sites have had poor or little documentation on their location or contents. Aerial photographs can also be used to construct digital elevation models (DEMs). Often stereo aerial photo capability is part of a standard collection procedure by many aerial photo firms. Pairs of images are acquired with 60% overlap, which allows for stereo pair generation. Standard photogrammetry is employed to convert the information in the stereo pairs to digital contour maps and/or DEMs. For each picture element (or pixel) that comprises an image, an elevation datum can be assigned to it. The DEM can be used to set up a baseline for a waste site cap. Later, DEMs generated can be used to determine relative subsidence of the cap with respect to the baseline imagery, which could be an early sign of cap compromise. 4.2.5.2 Multi-Spectral Scanners Multi-spectral scanners (MSS) are commonly used sensors for collecting imagery in diverse application areas. The National Aeronautics and Space Administration (NASA) Landsat satellite program established in the 1970s used filmless multispectral imagers. As the Landsat program evolved, improved technologies were used to enhance the quality of the imagery produced by the sensor. In the 1980s

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and 1990s, the number of spectral channels grew for both airborne and satelliteborne sensors while retaining good spatial resolution. MSS sensors have decided advantages over photographic systems. For example, film technology limits the spectral range that can be covered by film-based photographic systems, which are more difficult to calibrate to radiometric units than is digital data. The useable spectral range for film is about 300 nm to 900 nm, with wide spectral bandwidths. Where photographic systems generally need to use separate optical systems to break out the different spectral bands, MSS systems can use the same optical train to record data from each optical band. Finally, if the aerial photo film will be analyzed in an electronic computer, it must be digitized, i.e., scanned by an aerial photo film scanner and saved as digital number data. The process of scanning not only degrades the spatial accuracy inherent in the film, it is an extra step that is not needed with digital data (Lillesand and Kiefer, 1994). 4.2.5.3 Thermal Scanners Thermal scanners record radiant emissions that span a range of thermal infrared (TIR) wavelengths. The TIR scanner integrates all of the emissions over these wavelengths and composes an image of them using detectors specifically developed for use in the TIR region of the spectrum. Often, the wavelengths integrated over the span range from 8 μm to 12 or 14 μm due to the atmospheric transmission window for these wavelengths. The blue/green colors show cooler areas, while the orange/red show warmer areas. The temperature regime of a landscape varies naturally with the amount of solar insulation. That is, solar input to a landscape differentially heats the constituent materials present (Elachi, 1987). Depending on the application, the proper interpretation of thermal imagery must consider diurnal heating effects. Often pre-dawn imagery is requested because it tends to minimize the thermal shadow effects and differences in the slope of the land effects in the imagery. The optimum time for data collection depends on the specific application and target characteristics.

4.2.6 STATE-OF-THE-ART REMOTE SENSING TECHNOLOGIES Remote sensing systems, techniques, and practice are developing at a rapid pace. The use of hyperspectral sensors, light detection and ranging (LIDAR) topographic systems, LIDAR fluorescence, satellite and airborne radar sensors, and sensor fusion approaches are rapidly moving from the research arena to applications. However, the exciting new developments in geophysics, especially new methods of imaging the subsurface properties, have not been fully applied in waste studies. The subsections below reiterate the point that, in addition to monitoring the emplacement, effectiveness, and performance of barriers, geophysics should be used in a total system performance mode to monitor the total fluid matrix system that includes not only the barrier but also the zone being contained.

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4.2.6.1 Hyperspectral Imaging Sensors A hyperspectral imaging spectrometer (HIS) or hyperspectral scanner acquires a series of images of the same scene in a range of colors (i.e., wavelengths or spectral channels) similar to that of a MSS sensor. The primary difference is in the narrowness of the bandwidths of the spectral channels and their number. A hyperspectral scanner attempts to perform laboratory quality spectroscopy of a landscape from an aircraft. Hence, the basic MSS technology has been enhanced and extended to handle and process the extracted spectral channels and concomitant data load. HIS imagery is often thought of as forming a cube of data (Lillesand and Kiefer, 1994) because of the many bands of data forming a stack of images — one image of the same scene for each band. For large areas imaged and, in some cases, 200+ bands of spectral data, the data load can become onerous. Nonetheless, the spectral information concerning the scene can be invaluable in determining or classifying unknowns in the landscape, much as spectroscopy is used to determine unknown compounds in a chemical laboratory. Figure 4.8 shows a HIS cube. Currently, the premier HIS instrument is the NASA Jet Propulsion Laboratory Advanced Infra-Red Imaging Spectrometer (AVIRIS). This system is flown typically on an ER-2 aircraft at an altitude of 20 km, producing a ground cell size or pixel size of 20 m. Alternatively, the AVIRIS can fly on a slower Twin Otter platform at 2 km and produce 2- to 3-m pixels. The AVIRIS possesses 224 contiguous spectral channels that span 0.4 to 2.45 μm. These spectral channels are about 10 nm wide. Figure 4.9 displays an AVIRIS image of Summitville, Colorado. The Summitville Mine is shown in the picture as is the mapping of

FIGURE 4.8 HIS (AVIRIS) image cube of Moffett Field, California. (See color version insert of this figure.)

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Summitville, Colorado Mining District Fe-Mineral Map AVIRIS Sept. 3, 1993 U.S. Geological Survey

Summitville Mine Crospy Mountain N

Alum Creek

Wightman Fork Bitter Creek

Alamosa River

1 KM

Reynolds Tunnel Sludge

K–Jarosite

Na–Jarosite

Hematite

Fe–hydroxide

Goethite

Ferrihydrite

not mapped

FIGURE 4.9 AVIRIS HIS mapping of Summitville, CO, area. (See color version insert of this figure.)

iron-bearing minerals made possible by the detailed spectroscopic nature of the AVIRIS imagery. 4.2.6.2 LIDAR Systems LIDAR remote sensing systems are active sensors. That is, LIDAR sensors provide their own illumination rather than relying on the sun for illumination. The basic principle of an airborne topographic LIDAR is time of flight of a round

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trip of a light pulse to the ground and its return back to a LIDAR receiver. Because the airframe position can be known to centimeter-level accuracies, by extension, the point of the ground can be literally surveyed into the system. Thus, as the airframe flies, a dense set of laser pulses is scanned perpendicular to the direction of airframe motion and height and geographic position information for each ground return pulse are recorded (Measures, 1984). Another aspect of LIDAR remote sensors is the recording of the intensity of the ground returning pulse as well as its travel time to the target (time of flight). Because the reflectance of vegetation and earth materials vary from one another at the wavelength of the LIDAR illumination, reflectance can be used to aid in separating out or classifying a terrain. 4.2.6.3 Laser-Induced Fluorescence (LIF) Lasers can be used in remote sensing systems to invoke a fluorescence response in different materials termed laser-induced fluorescence (LIF). The evolved fluorescence is detected by a receiver and used to target or, in some cases, image the irradiated object. Potential applications include pollutant/contaminant studies and vegetation stress studies. LIF involves the use of laser pulses at a specified wavelength to pump target molecules to excited states, followed by de-excitation and concomitant release of radiation or, in this case, fluorescence at longer wavelengths (Goulas et al., 1997). For example, uranium (in the form of uranyl oxide) can be stimulated by a laser to produce a fluorescent spectrum. Thus, LIF can be used to detect uranium-bearing leachates or contamination hot spots on a cap or in the surrounding cap environment. When laser light energy is absorbed by the chloroplast (i.e., the plant organelle that houses chlorophyll), the light energy excites an electron from a ground state to a first excited state. Plants that exhibit stress due to environmental factors exhibit a decrease in the efficiency of photosynthesis (Bongi et al., 1994; Moya et al., 1992). It has been shown that when photosynthesis is reduced, the amount of heat energy increases by a factor of about five and the amount of chlorophyll fluorescence by a factor of six (Noonan, 1998). However, it is important to realize that many factors can cause stress in plants. Moreover, chlorophyll concentrations have been known to alter because of shifts in lighting or season. So, although stress can be indicated by LIF, the cause of the stress must be resolved by supplementary information. Laser-induced fluorescence imaging (LIFI) is a project operated by the USDOE that uses a camera to detect the fluorescence induced by a co-located laser transmitter from selected targets (DiBenedetto et al., 1995). Contaminantinduced plant stress can be imaged and mapped by the LIFI instrument, as can uranyl-bearing soils or leachates. It is possible to detect heavy metals and volatile organic compounds that are often associated with landfills. A handheld version of the LIFI system was field tested at the ORNL K-25 site and was able to detect uranium during decontamination and decommissioning activities and on selected

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surfaces. Also, the LIFI was able to detect chromium-induced stress in plants at the site. A helicopter version of the LIFI is planned. 4.2.6.4 Radar Systems Radar systems are active sensors like LIDAR systems, but radar uses microwaves rather than light waves to probe areas of interest, which is an advantage because microwaves penetrate clouds and rain. Like LIDAR systems, radar systems use pulse transmissions of microwaves and record round-trip flight times from the radar transmitter to the target and back. Generally, microwaves penetrate more deeply into vegetation than very near infrared (VNIR) wavelengths. Penetration depth depends on the actual microwave wavelength and the moisture content of the vegetation. Radar returns are processed not only for their range information but also for the intensity of their scatter and volumetric returns. In VNIR wavelengths, scattering depends on the atomic/molecular makeup of the material irradiated. However, microwave scattering intensity depends on the following: (1) larger scale (on the order of centimeters) surface roughness features, (2) the dielectric of the landscape material (which can be a function of moisture present), (3) the polarization (horizontal or vertical electric field orientation) of the radar transmission, and (4) the angle the incident wave makes with the landscape element. Volumetric return refers to the total return from large-scale landscape elements like a forest canopy. Thus, total radar intensity return is the sum of the surface and volumetric returns. Hence, tonal values in a radar image are related to the intensity of the radar return. Specifically, the greater the backscatter values, the brighter the tonal value of a landscape element (Toomay, 1982). Two different radar technologies are often employed when collecting remote sensing data: side-looking airborne radar (SLAR) and synthetic aperture radar (SAR). SLAR represents the first imaging radar used. SLARs are often referred to as real aperture radars because the along-track resolution depends on the size of the physical antenna of the radar system. However, SLARs are inherently limited in their resolution by the antenna size that an airframe can support. SAR technology overcomes this limitation. Moreover, a SAR system, due to the virtual antenna, can work at longer wavelengths than a SLAR system. The greater range of wavelengths available to a SAR system increases its flexibility and value for applications. Typical satellite radar systems are the Japanese Earth Resources Satellite (JERS), European Resources Satellite (ERS-1 and ERS-2), and the Canadian Radarsat. Table 4.2 includes a brief summary of system specifications of interest. Note the evolution in the spatial resolution capability of these sensors. The 3-m resolution of Radarsat-2 means that the variety of applications for which the data can be used is significantly increased. Radar imagery can contribute significantly to site monitoring. Not only can DEMs be constructed from data, radar backscatter imagery can be used to look through vegetation to reveal the ground surface beneath. Texture and backscatter

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TABLE 4.2 Prominent Radar Resources Satellite System Characteristics Name JERS ERS Radarsat Radarsat-2 (2003 launch)

Band

Spatial Resolution

Swath Width

Revisit Time

L C C C

18 m 10–30 m 8–100 m 3, 28, 100 m

75 km 100 km 45–500 km 20, 100, 500 km

44 days 35 days 3–24 days 3–24 days

Note the evolution in the spatial resolution capability of these sensors. The 3-m resolution of Radarsat-2 will mean the variety of applications for which the data can be used is significantly increased.

changes indicate moisture shifts across the cap and surrounding areas, which could be the harbinger of the onset of closure cap compromise or a true breach. Moreover, DEM and geomorphology differences (slope analysis) from some earlier baseline data add an important information layer to the site assessment. Radar imagery has been used to detect plant biomass and perform plant classifications (e.g., Ranson and Sun, 1994; Rignot et al., 1994; Dobson et al., 1998). Additionally, then, radar imagery can be used to detect changes in the composition of plant communities or plant biomass shifts that could be due to contaminant exposure. 4.2.6.5 Fused Sensor Systems/Data Streams Fused sensor approaches include sensor systems that are flown on the same platform over a target area, sensors on different platforms used simultaneously over a site, and sensors on different platforms used at different times over a site. The latter case often is the rule for GIS data layer accumulation for a given site. It is clear that data provided by multiple sensors, whether performing a simultaneous data collect or not, are more valuable than data provided by a single sensor. Further, ancillary data concerning the construction, geology, watershed, and climatology of the site provide crucial data layers for input to the site GIS database. This is the systems approach to interrogating and monitoring waste sites. The confluence of remote sensing/geophysical and ancillary data streams inform one another and end users of conditions present at a given target area. Examples of investigators using multiple data streams to successfully characterize a site include Vincent (1995), who used both aerial photos and MSS data for assessing waste sites. Van Eeckhout et al. (1996) used aerial photos (some historical) and CIR photos to assess three landfill sites in New Mexico. Well et al. (1995) used both TIR and GPR with good results to investigate hazardous waste sites. Smyre et al. (1998) used aerial photos (some historical), CIR, TIR, MSS, magnetic, electromagnetic, and gamma ray data collection to assess an ORNL site.

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4.3 PRBS In this section, the potential application of geophysical methods for assisting in the evaluation and monitoring of a PRB is discussed. A PRB presents an enticing geophysical target, although reported geophysical applications are currently few. The granular reactive iron media used to construct a PRB has unique geophysical properties. Electronic conduction in iron results in high electrical conductivity relative to near-surface geological formations. The electrical conductivity (inverse of resistivity) of iron is 1 × 107 siemens per meter (S/m) (Carmichael, 1989), whereas that of near-surface earth materials is typically less than 1 S/m. Iron has high magnetic susceptibility and will locally perturb the earth’s magnetic field. Endres et al. (2000) investigated the electrical and magnetic properties of granular reactive iron mixed with sand. Laboratory measurements, reproduced in Figure 4.10a and Figure 4.10b, illustrate the strong dependence of electrical conductivity and magnetic susceptibility on the volume of granular iron. Note that the conductivity of the granular iron does not approach the reference value for the electrical conductivity of iron, presumably due to the absence of continuous electronic conduction paths in the granular media used in this study. PRB emplacement in the subsurface also creates an interface between iron and the sediment at which charge transfer must switch between electronic and electrolytic conduction, making the PRB an intriguing target for the induced polarization geophysical method that is sensitive to the electrochemistry of a metal–fluid interface. Iron also has seismic properties distinctly different from most nearsurface earth materials. The acoustic velocity of iron in solid form is 5900 m/s (McIntire, 1991), whereas it is typically less than 1500 m/s in near-surface unconsolidated sediments in a diffuse form. Seismic methods can also then assist in PRB investigations through characterization if it does present a seismic anomaly or through general characterization structure.

4.3.1 REQUIREMENTS, SITE CHARACTERIZATION, DESIGN VERIFICATION, AND MONITORING In this section, the utility of geophysical methods to PRBs is considered in respect to the following four objectives: site characterization, PRB construction verification, short-term monitoring of PRB performance, and long-term monitoring of PRB performance. Case studies that illustrate the current state of the art of geophysical methods in PRB evaluation are subsequently presented. Finally, future directions and recommendations for research are presented. The potential application of geophysical methods emerges at the design, installation/verification, and monitoring stages of the PRB life span. PRB assessment effectiveness is required over both the short term after PRB construction and over the longterm design life. Short- and long-term monitoring issues are thus treated separately in the subsections below.

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FIGURE 4.10 a (a) Electrical conductivity of sand-granulated iron mixtures with varying iron content of solids. Mixtures were saturated with 0.01 M KCl solution. (b) Magnetic susceptibility of iron mixtures as a function of total volumetric content. (Reproduced from Endres, A.L. et al., 2000. Proceedings of the Seventh International Symposium on Borehole Geophysics for Minerals, Geotechnical and Groundwater Applications, Mineral and Geotechnical Logging Society, Golden, CO, pp. 1–8. With permission.) b (a) Schematic of electrical charge transfer mechanisms in earth containing metal minerals. (b) Simple circuit model for this system: Rnm represents the resistance exerted by the conduction path associated with free electrolyte, Rm represents the resistance exerted by conduction across a metal–fluid pathway (electronic and ohmic), and W is a Warburg impedance that depends on frequency (ω).

4.3.1.1 Site Characterization PRB performance depends on successful characterization of site geology and hydrogeology. Fundamental PRB design criteria necessitate quantification of the hydraulic properties of the host material. Estimates of hydraulic conductivity (K)

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are required to determine PRB design thickness. Geophysical methods are routinely used to qualitatively characterize variability in subsurface lithology. Lowpermeability clay formations are distinguishable from hydraulically conductive sand units. Although direct quantification of K from geophysical methods is currently unachievable, recent advances illustrate the value of geophysical imaging for providing spatially extensive representations of K variation (for review see Hubbard and Rubin, 2000). This information can aid in the identification of lithologic variability at the immediate PRB installation site and define preferential flow zones that could complicate contaminant plume transport upgradient of the barrier. Such techniques require ground-truth verification from whatever borehole records are available at the study site. Effective PRB performance necessitates accurate barrier emplacement in the immediate path of the contaminant plume under remediation. This implies that the plume geometry be well characterized. Direct geophysical detection of chlorinated solvents and heavy metals at typical site concentrations is unlikely. Geophysical monitoring of the transport of tracer evolution injected upgradient of a proposed PRB installation can determine whether the barrier is well placed to capture the plume. Tracking electrically conductive tracers using electrical resistivity, electromagnetic, and GPR methods has been applied to characterize vadose zone transport (Daily et al., 1992, Hubbard et al., 2002) and groundwater flow (White, 1988, 1994). These methods are deployable using surface and/or borehole instrumentation. Borehole methods are expensive but enhance resolution of tracer transport at depth. The results of geophysical tracer tests could assist in designing geochemical monitoring well networks by identifying preferential flow paths and likely flow rates. 4.3.1.2 PRB Construction Verification The granular reactive iron used in PRB construction profoundly affects the electrical and magnetic properties of the subsurface relative to the pre-installation condition. Thus, geophysical methods have a high potential for PRB construction verification. Geophysical imaging of subsurface conductivity structure using resistivity, electromagnetic, or GPR techniques offers the possibility of defining the continuity and uniformity (thickness) of the wall, as well as detecting the location of flaws in barrier construction. Cross-borehole electrical resistivity tomography was used to examine the subsurface distribution of granular iron installed at the USDOE Kansas City facility in Missouri (Slater and Binley, 2003). Joesten et al. (2001) used cross-borehole GPR to image differences in radar wave attenuation amplitude caused by PRB construction at the Massachusetts Military Reservation in Massachusetts. Endres et al. (2000) showed that downhole electromagnetic tools are sensitive to the presence of granular iron injected into a formation and offer a potential approach to PRB construction verification. Tomographic electromagnetic and seismic methods are also potentially valuable methods in PRB verification. Optimal implementation of geophysical methods in verification requires changes to current installation practice. Geophysical imaging is often effective

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when an image can be compared with an image from that of a pre-existing condition. In the case of the PRB, differences in the electrical structure caused by the emplacement of reactive iron are of interest, necessitating geophysical data collection prior to PRB construction. Ideally, boreholes for geophysical data acquisition would be drilled prior to any subsurface disturbance to permit acquisition of a representative background data set. The geometry of a typical PRB is well suited to cross-borehole geophysical imaging. Instrumentation can be placed in boreholes drilled immediately upgradient and downgradient of the barrier, providing a two-dimensional cross-sectional image of the barrier wall (Joesten et al., 2001; Slater and Binley, 2003). A closely spaced nest of boreholes permits 3-D imaging of the barrier installation (Slater and Binley, 2003). 4.3.1.3 Short-Term Monitoring Short-term PRB monitoring primarily focuses on the wall efficiency to degrade and remove contaminants. The relatively low contaminant concentration typically encountered at a PRB installation site is unlikely to be detectable with geophysical methods. Short-term monitoring is also concerned with possible disruption of the natural flow regime due to PRB emplacement. Most critical is that plume transport following PRB construction is consistent with that predicted from the site characterization phase. A geophysical tracer test could be an effective noninvasive method for assessing plume transport immediately after construction. The use of electrical resistivity, electromagnetic, or GPR to track an electrically conductive tracer appears to be a promising technology and could be used in decision-making regarding final placement of geochemical monitoring wells required for longterm performance evaluation. 4.3.1.4 Long-Term Monitoring The long-term performance of PRBs is highly uncertain but operational life, its period of effectiveness, is expected by the user to exceed ten years. Monitoring strategies are required to determine deterioration in barrier performance as reactive iron is oxidized during hydrocarbon degradation. The exact mechanism of degradation of chlorinated compounds is not fully understood, and a variety of pathways are likely involved (Gavaskar et al., 1998). A fundamental aspect of PRB performance is that degradation of chlorinated organics is a surface phenomenon and the available specific surface area of the reactive medium governs the rate (Gavaskar et al., 1998). Clogging of the barrier and the resulting permeability reduction are also current concerns relating to reduction in PRB performance and can be significant issues. Clogging at the influent end of the PRB could potentially result from formation of iron precipitates under highly oxygenated conditions (Gavaskar et al., 1998). In addition, deposition of inorganic suspended sediments on the granular iron can also reduce permeability and performance. The presence of granular iron modifies the subsurface electrical properties due to the following charge transfer mechanisms: electronic conduction in the

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metal and polarization of charges at the interface between a metal and the porefilling electrolyte. Figure 4.10a is a simple conceptual illustration of the key charge transfer mechanisms in a medium containing metal particles. Figure 4.10b is a circuit analogue of this system. A frequency-dependent interfacial (Warburg) impedance (W) is often used to simulate the electrical response of a metal–fluid interface (e.g., Pelton et al., 1978). The magnitude of this interfacial impedance is measured with the induced polarization method. The frequency dependence of this impedance is also determined when spectral (multi-frequency) induced polarization measurements are made. The chemistry of the metal–fluid interface exerts a strong control on the induced polarization response (Olhoeft, 1985). Oxidation of the granular iron surface as a result of continued chlorinated solvent degradation might modify the induced polarization response of a PRB. Precipitation onto the granular iron does reduce the surface area of the metal–fluid interface and will presumably modify its impedance. It will also change the charge and the surface complexation of the interface. Induced polarization is thus considered a promising technology for long-term PRB monitoring. Self-potential is another geophysical method that is sensitive to interface chemistry. Small intrinsic voltages exist where ionic concentration gradients occur. These gradients can result from physical movement of charge by fluid flow, charge diffusion at chemical interfaces, or thermal effects. Changes in electrochemistry at the iron–fluid interface can result in characteristic self-potential signals. Extensive laboratory research is required to determine the induced polarization and self-potential signal as chlorinated solvent treatment by granular iron progresses.

4.3.2 CASE HISTORIES Few published examples of the application of geophysical methods to PRB investigations exist. The case studies that follow focus on the issue of construction verification. These examples illustrate the potential that geophysical imaging technologies offer with respect to noninvasive PRB construction evaluation. Applications of geophysical methods to site characterization and PRB monitoring (either short or long term) are currently unreported. 4.3.2.1 Electrical Imaging of PRB Construction and Installation (Kansas City, Missouri) Slater and Binley (2003) report the results of cross-borehole resistivity and induced polarization imaging on a PRB installation at the USDOE Kansas City plant. This PRB was constructed as a continuous 40 m long by 1.8-m-wide trench. The first 1.8 m of the trench immediately above bedrock was filled with 100% ZVI. The remainder of the trench was filled with 0.6 m of zero-valent iron and 1.2 m of sand. Figure 4.11a shows the cross-sectional geometry of the barrier and site geology. Superimposed is the position of electrodes and the finite element mesh used to reconstruct the conductivity distribution between wells with electrical

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imaging. Figure 4.11b is a plan view of the site showing 16 boreholes drilled to bedrock and installed with electrode arrays as per Figure 4.11a. Each borehole pair represents a two-dimensional panel for imaging the cross-sectional electrical structure of the barrier. Two sets of four boreholes were used to investigate barrier integrity with 3-D electrical imaging (Figure 4.12). Two-dimensional electrical images were obtained between boreholes 5 and 6. Both the resistivity and induced polarization parameters illustrate high contrasts with background geology and accurately resolve PRB structure compared to the design structure in Figure 4.12 and Figure 4.13. These images clearly illustrate the capability of electrical resistivity and induced polarization imaging for in situ PRB resolution. The resistivity response results from electronic conduction in the highly conductive granular iron. The induced polarization response results from the impedance at the metal–fluid interface. Results of 3-D PRB visualization using resistivity measurements are illustrated at two locations on the barrier in Figure 4.13. The images illustrate variability in the in situ PRB structure, particularly in

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the vicinity of BH 5, where the integrity of the upper thin section is compromised (Figure 4.12a). 4.3.2.2 Cross-Hole GPR Investigations (Massachusetts Military Reservation, Massachusetts) Joesten et al. (2001) conducted cross-hole GPR imaging to monitor pilot-scale testing of a hydraulic fracture method to install a PRB in unconsolidated sediments at depth. They also conducted numerical modeling of cross-hole radar pulses to assist in the interpretation of the barrier structure from the radar data. Design specifications called for the installation of two iron walls 5 m apart, 12 m long, and at a depth of 24 to 37 m. This installation depth precluded standard PRB installation procedures and emphasized the need for a noninvasive method of emplacement evaluation. The application of GPR was based on the large reduction in transmitted wave amplitude associated with emplacement of highly conductive iron. Numerical finite difference modeling was used to predict the effects of holes and wall edges on the transmission amplitude of the radar pulse. Figure 4.14

Barrier Systems for Environmental Contaminant Containment & Treatment

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compares the modeled response of a 3.1 m tall wall with the transmission amplitude data collected after PRB installation. The model result is a close fit to the general shape of the field data, suggesting that the top of the wall and wall height are well defined by the geophysical data. The results from cross-hole radar amplitude measurements between 14 boreholes were combined to define variability in cross-sectional amplitude attenuation along the length of the two walls (Figure 4.15). Contour plots defined irregularly shaped walls about 8 m wide. Small-scale structure was tentatively interpreted as stringers of iron possibly attributable to iron particles moving into higher permeability formations. This study illustrates the potentially high spatial PRB resolution obtainable with radar data.

4.4 VERTICAL BARRIERS Constructed horizontal barriers are not included in this discussion. It is assumed that horizontal barriers are natural aquitards. The goal of vertical barriers is to prevent groundwater from either entering or leaving a volume of interest, such that the contamination can be remediated or isolated. Therefore, such issues as the location of the barrier, thickness, life

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FIGURE 4.14 Comparison of normalized model wall amplitude for a 3.1 m wall and normalized field data amplitude from the cross-well radar survey at Massachusetts Military Reservation. (After Lane et al., USGS Water Resources Investigation Report 00-4145, 17 p. 2001.)

expectancy, and integrity are all important. Just as important is the environment in which the barrier is being emplaced. If there is no floor to the containment system, then there is the possibility that the barrier may be of little use. The ability of geophysical methods to characterize and monitor the containment system (wall plus floor) primarily depends on the contrasts in the elastic, electrical, density, and magnetic properties between the native materials and containment system. A variety of different materials are used for barriers, from various grouts to constructed barriers. Unfortunately, there is a lack of information on the geophysical properties of many of these barrier materials. On the other hand, barriers made of metal sheets and more conventional materials can be considered, and, in a general sense, geophysical monitoring methods can be designed for almost all barriers. In addition to characterizing and monitoring the actual barrier (wall plus floor), it is important to note that the volume inside of the containment system can be characterized and monitored to determine if the system is performing as designed. For example, if the barrier does not have a geophysical contrast, a leak can be detected if the flow or concentration of contaminants is causing an anomalous signal. Then, the total system can be monitored. As described in this section, the most effective approach is to combine geophysical methods in a timelapse sense to detect changes.

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4.4.1 REQUIREMENTS, SITE CHARACTERIZATION, DESIGN VERIFICATION, AND MONITORING The potential application of geophysical methods emerges at the design, installation/verification, and monitoring stages of the walls and floor. Barrier effectiveness assessments are required in the short term, after construction, and over the long-term design life. Short- and long-term monitoring issues are thus treated separately in the following subsections. 4.4.1.1 Design The design and performance of the barrier depends on successful characterization of site geology and hydrogeology. The design of the containment system depends mainly on the in situ flow and transport properties, contaminant to be contained, and the expected life of the barrier. Geophysical methods are routinely used to qualitatively characterize variability in subsurface lithology. Low-permeability clay formations are distinguishable from hydraulically conductive sand units. Although direct quantification of permeability using geophysical methods is currently unachievable, recent advances illustrate the value of geophysical imaging for providing spatially extensive representations of permeability variation (for review see Hubbard and Rubin, 2000). 4.4.1.2 Installation/Verification Effective performance necessitates accurate barrier emplacement in the path of the contaminant plume under remediation. This implies that the plume geometry be well characterized. One of the most effective methods of characterizing vertical barriers is with cross-well methods. Although surface imaging methods have been widely developed and used, the resolution is limited compared to the requirements of most remediation applications. Therefore, the need for higher resolution imaging has led to borehole techniques that place sources and sensors in wells. Crosswell seismic, electromagnetic, radar, and ERT are all in use now. In a cross-well configuration, a source is put in one hole and receivers in another. Figure 4.16 shows an example of how high-resolution cross-well seismic and radar methods were used to infer flow properties at the USDOE bacterial transport site in Oyster, Virginia (De Flaun et al., 2001). This was crucial information in designing bacterial injection experiments at this site. Direct geophysical detection of chlorinated solvents and metal species at typical site concentrations is unlikely; however, progress is being made in the direct detection of free product nonaqueous phase liquids (NAPLs) (Geller et al., 2001). Figure 4.17 shows the results of characterizing a chlorinated solvent site with cross-well seismic methods (Geller et al., 2002). The radar also showed the structure in this saturated soil, and the seismic showed attenuation of signal due to the presence of NAPLs. Figure 4.18 and Figure 4.19 show examples of using seismic and radar methods to map different but complementary properties (Majer et al., 2002). In Figure 4.18, the cross-well radar tomography is showing the

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FIGURE 4.16 An example of how high resolution cross-well seismic and radar were combined to infer transport properties in a sandy aquifer at the USDOE bacterial transport site in Oyster, Virginia. (From De Flaun, M. et al., 2001. EOS, 82(38), 417–425, LBNL48440. With permission.)

moisture content in the sediments at the USDOE Hanford site (note the correlation with the neutron log data). The seismic (Figure 4.19) is showing the heterogeneous porosity within the sediments. In any case, state-of-the-art methods are now beginning to be applied for initial characterization. Additional methods include surface seismic, surface radar, and high-resolution electrical methods such as cross-well electromagnetic. ERT, gravity, and magnetic are generally too low in resolution to be of use for anything other than broad site characterization. Depending on the contrast between the barrier and the contained volume, geophysical methods may or may not be applicable to confirm the location of the emplaced barrier. Geophysical imaging of a subsurface conductivity structure using seismic, resistivity, electromagnetic, or GPR techniques offers the possibility of defining the continuity and uniformity (thickness) of the wall, as well as detecting the location of flaws in barrier construction. These techniques must be implemented in the cross-well or surface to well configuration. Therefore, optimal implementation of geophysical methods in verification requires changes to current installation practice. Either sensor can be emplaced with cone penetrometer

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technology (CPT) in dedicated boreholes or in the wall itself. It is assumed that the floor can be characterized with high resolution seismic or radar techniques. Geophysical imaging is often effective when an image can be compared with an image from that of a pre-existing condition. In the case of vertical barriers, the barrier provides a significant contrast to the surrounding medium. If the

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geophysical methods are used in a time-lapse mode, then the barrier can be quite visible. Such methods as cross-well and surface to borehole can be useful in identifying the general geometry of the wall. If a time-lapse mode is used, geophysical data collection is required prior to construction. Ideally, boreholes for geophysical data acquisition would be drilled prior to any subsurface disturbance to permit acquisition of a representative background data set. The geometry of a typical vertical wall is suited to cross-borehole geophysical imaging. Instrumentation can be placed in boreholes drilled immediately upgradient and downgradient of the barrier, providing a two-dimensional cross-sectional image of the barrier wall. A closely spaced nest of boreholes permits 3-D imaging of the barrier installation. 4.4.1.3 Short-Term Monitoring Short-term monitoring primarily focuses on the efficiency of the wall in initial performance due to construction and contaminant degradation and removal. Contaminant concentrations typically encountered at a site with a vertical wall may be unlikely to be detectable with geophysical methods, but free product dense nonaqueous phase liquids (DNAPLs) or drums of material may be detectable and monitored during remediation with some methods. Short-term monitoring also focuses on possible leaks from initial construction or flaws not detected during emplacement. The allowable leak depends on the contaminant level and type. This, in turn, dictates the geophysical method(s) that can be applied to detect the leak. A geophysical tracer test could be an effective noninvasive method for assessing plume transport immediately after construction. Electrical resistivity, electromagnetic, or GPR tracking of an electrically conductive tracer appears to be a promising technology. This technique could be used in decision-making regarding final placement of geochemical monitoring wells required for longterm performance evaluations. 4.4.1.4 Long-Term Monitoring The long-term performance of vertical walls is somewhat established, but while operational life is hoped to exceed 30 years, as of yet there is minimal experience with these time periods. Monitoring strategies are required to determine deterioration in barrier performance. If sensors are placed within the barrier during construction, the electrical and structural properties could be measured over time. Again, depending on the physical, chemical, and geometric properties of the barrier, the exact method varies. One possible simple method to determine a leak is self-potential. Flow through the barrier (in this case, a leak) can cause either streaming potential or self-potential (if it is a rusting wall) effects.

4.4.2 CASE STUDIES Excluding tanks and ponds, a great deal of work using geophysical methods for characterizing and monitoring vertical barriers has not been conducted. Daily and

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Ramirez (2000) used ERT in a full-scale test to image a thin wall grout barrier installed by high-pressure jetting and a thick polymer wall installed by lowpressure injection at Brookhaven National Laboratory in New York. In another case, ERT, radar, and seismic methods were used to monitor and characterize vertical grout wall emplacements at a test site in Dover, Delaware (Pellerin et al., 1998). The latter is discussed in detail below and is modified from Pellerin et al. (1998). During 1997, a suite of cross-hole geophysical surveys was completed at the Dover national test site at Dover Air Force Base to demonstrate the efficiency and accuracy of geophysical methods in determining the areal extent of cement–bentonite subsurface barriers. Two barriers were emplaced as vertical walls that were keyed into a clay aquitard using a modified jetting technique. These barriers were denoted as the shallow active and deep passive barriers and extended to 7 and 16 m below ground surface, respectively. The active and passive descriptors referred to the hydraulic and gaseous tracer work performed at the sites. Before initiation of the barrier study, an extensive geophysical site characterization study was performed at the site. Surface GPR, ERT, and borehole electromagnetic data were reviewed for parameters of interest to the barrier verification study. Site characterization data were used to estimate the physical properties of the background host, and laboratory measurements were performed to estimate the properties of the grout. Based on these data, numerical models were computed for survey design and interpretation. After barrier emplacement, all geophysical methods were deployed between boreholes surrounding or internal to the barrier enclosure or permanently emplaced vertical barrier. The locations of all of the geophysical access boreholes and vertical barriers installed at the shallow active barrier and the deep passive barrier are shown in Figure 4.20. The vertical barrier consisted of stainless-steel electrodes and multi-conductor cables grouted in place using a neat Portland cement. Half of the electrical resistivity electrodes at the deep passive barrier were part of the boreholes, while the other half were installed as permanently emplaced barriers. All electrodes for the shallow active barrier were installed as vertical barriers independent of the boreholes. Figure 4.20 shows the borehole/vertical barrier locations for the data that are presented. Preliminary results indicated that the GPR and ERT methods were successful at imaging the areal extent of the barrier and at detecting leaks through the barriers using combined time-lapse acquisition modes and tracer tests. The demonstrated methodologies summarized in the subsections below include cross-hole GPR, seismic, and ERT methods. 4.4.2.1 Cross-Hole GPR To increase resolution, cross-hole data were acquired prior to and after the grout injection, and then were differenced by subtracting data sets collected at one time from data sets collected at a different time. The cross-hole GPR data were acquired with the Sensors & Software pulse EKKO 100 Borehole System prior

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to grout injection in June 1997 and after grout injection in July 1997. The crosshole GPR data were acquired using both the zero off-set profile (ZOP) (i.e., constant transmitter-receiver off-set) and the multiple off-set profile (MOP) (i.e., variable transmitter-receiver off-set) modes from borehole pairs located at both the shallow active barrier and the deep passive barrier. The ZOP data are rapid and simple to collect for interpretation of both reflection and transmission modes. The MOP data, which are slow to acquire, are needed to construct tomograms of the barrier walls. The survey design was appropriate for a transmission survey; the holes were spaced close to the barrier with a wide off-set. Although configuration allowed for a measurable signal to be propagated across the attenuating barrier, but the wide off-set prohibited separation of the first wave reflected off the barrier from the direct arrival wave traveling from the transmitter borehole to receiver borehole. The GPR data were acquired using both 100 and 200 megahertz (MHz) antennas. The 100 MHz measurements were collected at 0.25-m intervals along the length of the boreholes while the 200 MHz data were acquired at 0.125-m intervals along the boreholes. A velocity analysis of GPR data is presented for the deep passive barrier in Figure 4.21. Data are shown as the difference in travel time of the first arrival as a function of depth for the two holes that straddle the barrier and two that are on the same side of the barrier. The deep passive barrier is in the vadose and saturated zones, and the GPR response is quite different, depending on the hydrological domain within which the signal propagates. In the vadose zone, the grout displaced air in the pore space, which resulted in a slower wave propagation. In the saturated zone, the grout displaced water in the pore space, resulting in a faster media. Figure 4.21 shows the difference in travel time when the barrier is present (left) and when no barrier is present (right). The ZOP GPR data collected within the shallow active barrier are shown in Figure 4.22. The amplitude spectrum of the first arrival between holes SA-09 and SA-05 is shown on the left before injection and after injection, as well as the

2 0 −2 −4 −6 −8 −2 0 2 4 6 8 10 12 14 16 18 Depth (m)

DP 06 – DP 05 Difference in travel time

Difference in travel time

DP 09 – DP 01 4

4 2 0 −2 −4 −6 −8 −2 0 2 4 6 8 10 12 14 16 18 Depth (m)

FIGURE 4.21 Travel time analysis of GPR data across well pair DP-09/DP-01, where the barrier penetrates the saturation zone and well pair DP-05/DP-06, where no barrier is present. (From Pellerin, L. et al., 1998. EEGS 11.)

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1.8 1.2 0.6 0.0 −0.6 −1.2 −1.8 −2.4 −3.0 0

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8

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20 40 60 80 100 120 140 160 180 200

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FIGURE 4.22 Spectral analysis of first arrival amplitude for the difference between before injection and after injection, and travel time analysis of GPR data across well pair between holes SA-05 and SA-09. (From Pellerin, L. et al., 1998. EEGS 11.)

differenced data. A velocity analysis is also shown as differenced before and after injection in travel time for the same borehole pair. Borehole SA-05 has been completed with grout, as can be seen in the low-amplitude strip of the left side in the before and after sections. The before injection shows an attenuating region in blue at 4 to 5 m corresponding to the clay layer. After injection, the section from 1 to 5 m attenuates the signal, indicating the presence of the barrier. It is interesting to note that after injection there is still a hint of the structure of the stratigraphy. The colors are reversed in the difference data; no change is shown in blue. The difference in travel time is roughly 3 nanoseconds (ns), as predicted in the sensitivity study, indicating a slowing of the wave as it propagates through the relatively wet barrier. A flaw evident at a depth of 3 m has been verified in the excavation. Figure 4.23 shows a velocity tomogram of the wall between boreholes SA-06 and SA-09.The pre-injection tomogram shows three major velocity zones: sand (velocity approximately 0.11 m/ns), clay (velocity approximately 0.55 m/ns), and sand again. A transition layer can be observed between 2.5 and 3.5 m with a velocity of 0.075 m/ns. This is the area where a drop to zero in the velocity difference tomogram can be observed. This drop may correspond to an area where the barrier is substandard.

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FIGURE 4.23 Radar velocity tomograms before injection and the velocity difference tomogram from data acquired after injection. (From Pellerin, L. et al., 1998. EEGS 11.)

4.4.2.2 Seismic Modeling has shown that cross-well seismic and single well reflection seismic methods should both work as well as radar in detecting the barrier. However, the seismic technique is primarily a saturated zone technique, and propagating energy into the vadose zone was problematic. Further problems with the seismic methods in the saturated zone were because of air being injected into the subsurface during barrier emplacement, resulting in a highly scattered post-injection seismic signal, even though the pre-injection signal was quite strong.

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4.4.2.3 ERT The ERT data were acquired using the ERT system of Daily and Ramirez (2000) after grout injection in July 1997 and during a flood test in August 1997. Because of scheduling problems, no measurements were obtained before injection; therefore, no difference data are available. The ERT measurements were obtained from vertical electrical array (VEA) pairs with the electrodes spaced 1 m apart downhole to a depth of 15 m at the deep passive barrier, and 6 m at the shallow active barrier during the flood test. ERT results between the plane defined between ERT-02 and ERT-03 at the deep passive barrier are presented in Figure 4.24. Because it was not possible to collect pre-injection data, only post-injection data was used to image the barrier. The barrier is a conductive anomaly vertically up the center of Figure 4.24. The results showed that the barrier does not appear to have a uniform thickness. Also imaged are lower clay layers in the section as seen in red. The top few meters of the image plane appear more conductive over a wider region than lower down on the image plane. This could be because of grout infiltrating the surface during barrier injection. The top three images show the horizontal planes through the barrier; the three bottom figures show the vertical planes outside of the barrier (Pellerin et al., 1998).

Depth (m)

Electrical resistivity tomogram after injection at deep passive site 0

5 8/19/97 1137

8/19/97 1418

8/20/97

10

15 ERT03 0

0 0 0 0 0 0 0

ERT02

50 100 150 200 Resistivity (ohm-m)

250

Resistivity ratios 0.5 0.6 0.7 0.8 0.9 1.0

FIGURE 4.24 Reconstructed time-lapse 2-D ERT images of the deep passive box between holes ERT-02 and ERT-03 (left-hand side) and reconstructed 3-D ERT image of the flood test at the shallow active box (right-hand side). The top three images on the right show the horizontal planes through the barrier while the three bottom figures show the vertical planes outside of the barrier. (From Pellerin, L. et al., 1998. EEGS 11.)

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In addition to directly imaging the barrier, a test was performed to map leaks and hence flaws of the barrier. Baseline ERT were obtained just before filling the shallow active barrier with groundwater whose conductivity was enhanced by the addition of sodium chloride. Several data sets were obtained while filling the barrier, and one data set was obtained after the barrier was filled. The right-hand side of Figure 4.24 is a reconstruction of before and after data. The top three figures are images of the horizontal planes through the barrier where the saltwater tracer is easily delineated. The lower three pictures show the vertical planes defined by the emplaced barrier outside of the barrier. It is clear that much of the salt water has migrated outside of the barrier. These flaws are also seen with the hydraulic and vapor tracers. Cross-hole GPR data were used successfully to determine the presence of the barrier and the detection of flaws. From a practical point of view, reflection mode is the preferred data acquisition mode because it does not require boreholes to be placed inside of the barrier enclosure. However, the GPR data were not interpretable in reflection mode because data were acquired with the close coupling to the barrier and large off-set was necessary for the transmission interpretation. Analysis of the cross-hole GPR data suggested that the boreholes should be placed a greater distance from the barrier walls with a ratio of 3:1 to 5:1 offset from the barrier: distance between boreholes in order to enable analysis of reflection mode arrivals. The radar velocity tomograms, as well as the ZOP amplitude and travel time analysis taken before and after barrier injection, showed significant differences. The differences are attributed to the presence of the barrier due to the contrast in conductivity and permittivity dielectric with the host medium. The ERT acquisition system illustrated the use of time-lapse ERT coupled with a tracer test to detect leaks through failed barriers. Nevertheless, to increase the resolution of the reconstruction, it is necessary to obtain baseline data, and it would be better to move the emplaced array farther away from the barrier.

4.5 CAPS AND COVERS Stakeholders, regulators, and end users have recognized the difficulty in projecting long-term, field-scale barrier performance from short-term, point measurements. Thus, there is a need for cost-effective, robust and long-lived monitoring technologies to verify field-scale performance. Noninvasive techniques offer significant advantages over traditional methods. In the application of geophysics to caps and barriers noninvasive surface-based geophysical methods are particularly effective. The high speed of data acquisition leads to lower costs and high sampling resolution, and the integration of multiple spatial scales provides information that is more useful for monitoring field-scale performance. Furthermore, the nonintrusive nature minimizes damage to barrier integrity from sensor installation or degradation.

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4.5.1 REQUIREMENTS, SITE CHARACTERIZATION, DESIGN VERIFICATION, AND MONITORING The lack of cost-effective and robust monitoring technologies to evaluate longterm, field-scale performance, and the difficulty in projecting long-term, field-scale performance from short-term point measurements is a major challenge to barrier deployment. Monitoring moisture dynamics in the near-surface layers of multilayered barriers is one of the few viable options for long-term barrier monitoring. Given the size of a typical barrier, techniques that make short-term point-scale measurements have limited application. The most desirable are those technologies capable of providing long-term, spatially continuous measurements of near-surface moisture conditions over a range of spatial scales. Of the technologies currently available, nonintrusive geophysical methods are perhaps the most attractive. Unlike many of the traditional monitoring techniques, nonintrusive methods do not impair the integrity of the protective cover, are immune to the effects of sensor degradation, and typically provide measurements at scales ranging from a point to the field scale. The potential of nonintrusive tools like electromagnetic induction (EMI) and GPR for obtaining information about soil-water content in the near surface is well recognized. EMI provides distributions of bulk apparent electrical conductivity, ECa, while GPR provides distributions of electromagnetic velocity, v, from which the apparent dielectric permittivity, κ, is inferred. Both ECa and κ are highly correlated with soil-water content, θ. The potential for nonintrusive EMI to monitor changes induced by changes in θ in the top few meters of variably saturated soils has long been recognized (Kachanoski et al., 1988; Sheets and Hendrickx, 1995). This technique has also been used successfully in aerial surveys to rapidly map large areas of electrical conductivity (Cook and Kilty, 1992; Doll et al., 2000), making it an attractive option for monitoring large numbers of fieldscale barriers. The potential of surface GPR for measuring near-surface water content is also well recognized (Du and Rummel, 1994; Chanzy et al., 1996; Hubbard et al., 1997; Huisman et al., 2001). In engineered barriers, variations in texture and pore water concentration of electrolytes are small, and spatial variations in the bulk apparent electrical conductivity, ECa, depend primarily on ~ changes in θ. Thus, θ in the storage layer of barrier can be inferred from ECa using Rhoades et al. (1976): θ=

EC a − EC s EC w T

(4.2)

where ECs is the apparent electrical conductivity of the solid phase, ECw is the pore water conductivity, and T is the transmission coefficient (linearly related to θ and to the tortuosity of the water film through which current flows in the liquid phase). Thus, temporal changes in soil-water storage, ΔW, can be determined from multi-temporal measurements of ECa knowing the depth of penetration of the electromagnetic measurement as ΔW = L⋅{θ(ti) – θ(t–1)}. Alternatively, ECa

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profiles can be inverted to obtain depth profiles of water content (Hendrickx et al., 2002). Equation (4.2) is generally linear for 0.0 ≤ θ ≤ 0.40 m3 m–3, but becomes nonlinear for θ > 0.40 m3 m–3 (Kachanoski et al., 1988; Sheets and Hendrickx, 1995). The W(ECa) relationship should therefore be linear for the range of storage observed in typical soils used to construct barriers in arid environments. Both EMI and GPR have the potential to acquire data quickly and with sufficient spatial resolution to provide detailed subsurface moisture conditions over large spatial scales. However, a few studies have investigated the use of EMI to monitor long-term trends in water content over large areas in arid environments. To date, there are no published accounts of the use of EMI to monitor water storage in surface barriers (Ward and Gee, 2001). The same can be said about GPR for which there are no published studies of its use to monitor spatial and temporal changes in θ or soil-water storage, W, in engineered barriers. Successful application of these techniques to field-scale monitoring requires a better understanding of the nonlinear dependence of large-scale processes on θ and its variability across multiple scales (Huisman et al., 2001). This need is the basis of this section, which describes the use of nonintrusive geophysical techniques to monitor the spatial and temporal variability of W, from which hydrologic performance of surface barriers might be inferred.

4.5.2 CASE HISTORIES Several case histories are presented to illustrate how geophysical methods can be used to monitor moisture content in constructed and natural barriers. 4.5.2.1 EMI and GPR A study was conducted on a prototype Hanford barrier located at the USDOE Hanford site in southeastern Washington (Ward et al., 2003). The objective of the study was to investigate the relationship between the response of EMI and GPR to spatial and temporal variations in soil-water storage in a field-scale barrier. The prototype is a vegetated capillary barrier comprised of eight distinct layers of natural materials that has been monitored continuously for the last eight years (Ward and Gee, 1997, 2001). At the surface is a 1-m-thick layer of silt-loam with 15% pea gravel, underlain by 1 m of silt-loam, followed by a coarsely graded filter of sand and gravel (Figure 4.25). The total thickness of the cover is about 4.4 m, including the lowermost 0.15-m-thick asphalt concrete layer, which should form an ideal reflector for most nonintrusive geophysical instruments. The barrier is equipped with a variety of performance monitoring systems, including a drainage monitoring system, access tubes for neutron probes and capacitance probes for measuring water content, time domain reflectometry (TDR) probes for measuring water content, heat dissipation units for measuring soil-water suction, and soil temperature probes (Ward and Gee, 1997, 2001). Geophysical surveys were conducted in two phases using surface-deployed EMI and GPR (Table 4.3). The first phase was conducted in September 1994 and

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West Access roadway Upper silt-loam w/pea gravel admix 1.0 m

Basalt sideslope

50

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1 Lower silt-loam 1.0 m

2

Sand filter 0.15 m Gravel filter 0.3 m

1

Basalt riprap 1.5 m Drainage gravel 0.3 m Composite asphalt 0.15 m (asphalt with fluid-applied asphalt and curbed)

Top course 0.1 m

Sandy soil (structural) fill

In situ soil

E9812066.2

FIGURE 4.25 Cross section of the northeastern quadrant of the prototype Hanford Barrier showing the layer sequence and riprap side slope. (From Clement, W.P. and Ward, A.L., Using ground penetrating radar to measure soil moisture content. Handbook of Agricultural Geophysics, Allred, B.J., Daniels, J.J., and Ehsani, M.R., Eds., CRC Press, Boca Raton, 2003.)

TABLE 4.3 Dates of Electromagnetic Surveys at the Prototype Hanford Barrier Survey No.

Survey Date

Methods

1 2 3 4 5

September 30, 1994 March 9, 2001 May 22, 2001 September 19, 2001 January 9, 2002

EM38, EM31 GPR, EM31 GPR, EM31 GPR, EM31 GPR, EM31

the second over 10 months starting in March 2001. In the first phase, EMI measurements were obtained on a 3 m by 3 m grid with the Geonics™ EM-38 and EM-31 ground conductivity meters (Geonics, Mississauga, Ontario, Canada). Measurements with the EM-38 were obtained using both vertical and horizontal dipole orientations to achieve penetration depths of 0.75 m and 1.5 m, respectively. Measurements were also made at elevations of 0, 26, 54, 74, 94, 109, and 124 cm above the barrier surface to allow estimation of the variations in ECa with depth, z. The EM-31 survey was conducted with a vertical dipole orientation resulting in a penetration depth of 6.0 m. Measurements for determining the ECa(z) were made using the same protocol as the EM-38 and from three additional elevations: 154, 176, and 204 cm. Spatial and temporal variations in bulk apparent

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electrical conductivity were correlated with water content and storage. Neutron probe measurements of θ(z) were used for comparison. In the second phase, surveys were conducted with EMI and GPR. The GPR surveys were conducted using two acquisition geometries. The first geometry was the common midpoint (CMP) method (Weiler et al., 1998; Greaves et al., 1996). The CMP profiles were acquired starting with an initial antenna separation of 0.1 m and subsequently increasing the separation by moving each antenna 0.05 m away from each other (Figure 4.26). The wide off-set reflection geometry was N2

N1 26 25 24 23 22

E4 E4 E3 E3

N

21 20 19 18 17 16 15 14 13

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12 6 5 4 2

E1

11 10 9 8 7 6 5 4 3

1 2

3

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2 1 8 9 10 11 12 13

FIGURE 4.26 Plan view of barrier surface showing 3 by 3 m grid on which the geophysical surveys were made. EMI measurements can be taken in only a few areas, identified by (••), without interference from buried instruments and cables. (From Clement, W.P. and Ward, A.L., Using ground penetrating radar to measure soil moisture content. Handbook of Agricultural Geophysics, Allred, B.J., Daniels, J.J., and Ehsani, M.R., Eds., CRC Press, Boca Raton, 2003.)

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the second configuration. In this configuration, the off-set between the antennas is much wider than in typical GPR reflection profiles. The CMP gathers were used to determine the subsurface electromagnetic velocity and the optimal offset for separating the air and ground waves. The optimal spacing was used to ensure unambiguous identification of the airwave, the direct ground arrival, and the reflection from deep reflectors. Measurements were obtained with an initial spacing of 1.0 m, with subsequent readings taken after moving the receiving antenna away in 0.1-m increments until the optimal off-set was reached. An optimal off-set of 3.5 m was determined from the CMP survey. Both antennas were then moved with a constant step size of 0.25 m per trace while maintaining a constant separation of 3.5 m. Data from both geometries were filtered to remove low-frequency electronic and noise to increase the signal to noise ratio of the arrivals. The GPR surveys were conducted with a PulseEKKO™ 1000 GPR system with a 200 V transmitter (Sensors and Software, Mississauga, Ontario, Canada) with two sets of antennae with center frequencies of 100 and 200 MHz. After the first survey, data from the 200 MHz antennae proved inappropriate for the site conditions, and subsequent measurements were made with the 100 MHz. The GPR data were processed using a combination of ground wave analysis and normal move-out analysis of the reflections (Yilmaz, 1987). Calculation of θ was a three-step process. First, the velocities of the air and ground waves to depth L were calculated simply as v = L⋅t–1. The apparent dielectric permittivity was calculated from the air and ground wave travel time picks as follows (Huisman et al., 2001):

(

)

⎡ c t ground − tair + x ⎤ ⎥ κ=⎢ x ⎢⎣ ⎥⎦

2

(4.3)

where c is the electromagnetic velocity in air, x is antenna separation (3.5 m), tground is the arrival time of the ground wave, and tair is the arrival time– of the air wave. In the final step, κ was converted to a mean water content, θ, over the sampling depth using the θ(κ) derived by Topp et al. (1980). Water storage over – the GPR sampling depth, L, was calculated simply as θL. The penetration depth of the ground wave decreases with increasing antenna frequency, f, and increasing θ and is determined from the wavelength of the ground wave, λ (Du and Rummel, 1994). The penetration depth can be expected to vary between 0.5λ and λ with λ = c/(f ⋅ κ1/2). Use of 100 MHz antennae in this study suggested a penetration depth of between 0.6 and 1.2 m, well within the thickness of the silt-loam layer (Figure 4.25). Soil-water content was also measured using remote-shorting TDR to a depth of 1.8 m and with a neutron probe to a depth of 1.9 m (Ward et al., 2002). Figure 4.26 is a plan view schematic of the barrier surface, including the locations of surface and near-surface subsurface infrastructure. During each EMI survey, the 78 m by 40 m surface was mapped on a 3 m by 3 m grid for a total

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of 338 grid points. In addition, EM-31 surveys were conducted along transect N1 from south to north and along N2 from north to south. During the GPR surveys, CMP gathers were collected to allow identification of the air and ground waves and determine the optimal off-set for the wide off-set reflection surveys. A set of wide off-set reflection surveys was conducted along east-west transects E1, E2, and E3 and along north-south transects N1 and N2. 4.5.2.2 Apparent Conductivity Maps The presence of metallic components at and below the surface suggested that electromagnetic measurements might be adversely affected at some locations. However, the extent of the interference could not be determined a priori and in the 1994 survey both the EM-38 and EM-31 conductivity meters were used. In the 2001–2002 surveys, only the EM-31 meter was used. Maps of apparent electrical conductivity were prepared from the quadrature component of the EM-38 and EM-31 data. Figure 4.27 compares the EM-31 data from the September 1994 and September 2001 surveys. All of the data sets show anomalous readings, including ECa < 0 mS/m and ECa > 25 mS/m outside the expected range determined from independent measurements of θ and ECs. Areas of high ECa extend in an east–west direction at a northing of 26 m and 63 m and in a north–south direction down the middle of the barrier. These anomalies are most likely due to metallic components (i.e., sensors, cables, and access tubes) of the monitoring stations in the barrier. Buried ferrous materials can influence electromagnetic measurements by reducing the quadrature and in-phase response for all coil configurations. In an otherwise resistive soil, ferrous materials caused negative quadrature and in-phase measurements at low frequencies. After the initial survey in 1994, many of the cables, particularly down the middle of the plot, were encased in PVC conduit. This, plus generally drier conditions, caused a decline in ECa between the 1994 and 2001 surveys. The relationship between ECa (W) derived from the filtered EM-31 data and W derived from neutron probe measurements was good (Figure 4.28). Water content in the top 1.9 m of soil was measured by neutron probe in vertical access tubes. Water between the capillary break (2.0 m) and the in situ soil beneath the asphalt layer was measured by neutron probe in horizontal access tubes (Figure 4.26). Apparent conductivities were standardized to 25°C using soil temperature data from the barrier and the relationship described by Sheets and Hendrickx (1995). Apparent conductivity maps from the 2001–2002 survey suggest that irrigation on the north end of the barrier between November 1994 and September 1997 might have caused an increase in conductivity from the initial condition in 1994. The small size of the data set may limit use of this relationship for predicting the full range of W from ECa measurements. However, it does suggest that the method may hold promise for field-scale water storage monitoring. The mobility of these instruments, the speed with which measurements can be made, and the success of aerial EMI surveys in mapping large areas makes EMI an attractive option for monitoring large numbers of field-scale barriers. However, it is clear

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FIGURE 4.27 The quadrature component of the EM-31 surveys. (a) September 30, 1994; (b) September 18, 2001. (From Clement, W.P. and Ward, A.L., Using ground penetrating radar to measure soil moisture content. Handbook of Agricultural Geophysics, Allred, B.J., Daniels, J.J., and Ehsani, M.R., Eds., CRC Press, Boca Raton, 2003.)

that a larger data set is required to increase the robustness of ECa(W). Once this has been accomplished, it is quite reasonable to expect that a relationship developed for one cover design would be applicable to other covers constructed from the same materials and in a similar fashion. The above approach is ideal for detecting lateral variations in ECa and provides a measurement averaged over the depth of a profile. More information can be derived from maps of the vertical changes in ECa. However, derivation of the ECa profile from surface measurements requires solution of the inverse problem, a typically ill-posed problem. Such analyses, based on the assumption of linearity, have been reported (Wollenhaupt et al., 1986; Cook and Walker, 1992). More recently, linear and nonlinear methods combined with Tikhonov regularization have been proposed for the inversion of ECa profiles (Hendrickx et al., 2002). To

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250 W = 0.0574 ECa + 8.7505 R2 = 0.6155 Soil-water storage (mm)

200

150

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0 12

14

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ECa (mS m–1)

FIGURE 4.28 The relationship between soil-water storage and the standardized apparent electrical conductivity, EC, derived from EM-31 measurements.

verify the utility of these methods, EM-38 measurements obtained at different elevations were inverted using Tikhonov regularization. The data collected in the 2001–2002 surveys were not amenable to this analysis. Profiles derived from EM-38 and a combination of EM-38 and EM-31 were characterized by large fitting errors. The high fitting error may have been caused by the sensitivity of the EM-38 to ferrous components, the effect of which would increase as the height of measurement increased. The inversion of EM-31 data only showed a relatively constant ECa of about 10 mS/m in the top 2 m followed by a rapid decrease with depth. Joint inversion of EM-38 and EM-31 data showed an increase in ECa not supported by observed θ(z) profiles. However, this trend is consistent with layer sequence of the barrier in which a 2 m layer of more conductive siltloam is underlain by less conductive layers of sand, gravel, and basalt and riprap. 4.5.2.3 Electromagnetic Radar for Monitoring Moisture Content Figure 4.29 compares the CMP profile with the calculated velocity at the eastern intersection of transects E1 and N1 (easting of 26 m) in March 2001 and May 2001. The ground wave in March was quite strong (Figure 4.29) and the 86 ns travel time projected to a 10-m antenna separation was practically identical to the 88 ns observed later in January 2002 when the mean water contents were similar. Although the ground wave from May was weaker, calculation of travel time was still possible (Figure 4.29). The travel time at the 10-m antenna separation was approximately 75 ns, suggesting a higher velocity or lower water content and storage compared to March. Mean velocities derived from ground wave analysis were 0.119 m/ns in March, 0.115 m/ns in January, and 0.147 m/ns in May.

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100

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FIGURE 4.29 CMP gathering and velocity analysis at the intersection of transects N1 and E1 in (a) March 2001 and (b) May 2001. Note the changes in the ground wave and reflection character. The vertical white line in each plot shows the optimal antenna separation. (From Clement, W.P. and Ward, A.L., Using ground penetrating radar to measure soil moisture content. Handbook of Agricultural Geophysics, Allred, B.J., Daniels, J.J., and Ehsani, M.R., Eds., CRC Press, Boca Raton, 2003.) (See color version insert for this figure.)

Normal move-out velocity analysis is only appropriate for reflections so that velocities of the direct air and ground waves are improperly determined. The lighter regions at the top of the electromagnetic velocity plot above 40 ns are from the air and ground arrivals. The normal move-out velocity analysis indicates

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velocities of 0.105 m/ns in March and 0.120 m/ns in May. Although the velocity plots are quite similar, the green anomaly between 60 and 100 ns in the May plot is shifted to slightly faster velocities compared to the March plot. Although this electromagnetic velocity shift is small, it is indicative of a higher velocity in the material above the reflector. The increase in electromagnetic velocity, although small, is consistent with the electromagnetic velocity increase observed in the ground wave arrival analysis. The wide off-set reflection profiles also showed strong ground waves in March and January. Ground waves in May and September, although more difficult to identify, were determined from a walk-away start of each survey. These data also show larger ground wave arrival times (35 to 40 ns) or slower velocities in March and January than in May and September (30 ns). The higher velocities observed in May and September relative to those in March and January are consistent with the CMP ground wave analysis and show a temporal change in velocity. These changes are indicative of changes in water content in the silt-loam layer. Velocities were converted to κ with Equation (4.3) and to θ with Topp’s equation. Figure 4.30 shows plots of the temporal changes in velocity of the ground wave and the water content along the transect E1. There was a notable increase in velocity and a decrease in θ from March 2001 to May 2001. There was a subsequent decrease in velocity and an increase in θ from September 2001 to January 2002. These data also show a negative gradient in moisture content from west to east. At this point, the nature of the gradient is unknown, but it is hypothesized to be because of drier conditions on the east side of the barrier (Figure 4.29) caused by advective drying near the riprap sideslope. Until now, there were no data to confirm or reject this hypothesis apart from differences in drainage amounts from the sideslopes (Ward et al., 2002). In order to validate the trends in θ, water storage was calculated for each transect and compared to data from the TDR and neutron probe. As with the EMI measurements, the data set for validation was quite limited. Nevertheless, the radar data showed linear relationships between water storage derived for GPR measurements, WGPR, as well as that measured by neutron probe, WNP . The relationship between WGPR and WTDR is somewhat better with the coefficient of determination being about twice that for the WGPR and WNP relationship. A plot of W derived from the three methods showed that the neutron probe generally underestimated θ and W relative to GPR and TDR. This is not surprising because GPR and TDR measures essentially the same variable, κ, while the neutron probe responds to the presence of hydrogen, which is assumed to exist only because of the presence of water. The strength of the relationship between GPR and TDR confirms that generalized TDR calibrations may be useful for the range of soil textures found in multi-layered barriers at arid sites. Significant improvements in the relationship can be expected with site-specific calibration. Of course, the relationship between κ and θ and hence the applicability of GPR might be less appropriate for heavier soils used to construct barriers in wetter environments.

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FIGURE 4.30 Dynamics of radar velocity and soil moisture along transect E1. (a) March 2001, (b) May 2001. (March — red; May —green; September — yellow; January — blue). (From Clement, W.P. and Ward, A.L., Using ground penetrating radar to measure soil moisture content. Handbook of Agricultural Geophysics, Allred, B.J., Daniels, J.J., and Ehsani, M.R., Eds., CRC Press, Boca Raton, 2003.)

4.5.2.4 Aerial Photography The following studies illustrate the use of aerial photography in characterizing and monitoring contaminated sites: • Vincent (1995) used stereo aerial photos to compute a DEM of a landfill site. The DEM was used to compute the volume of standing water that could be stored in cap depressions. The DEM was also used to compute potential surface water run off.

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• Stohr et al. (1996) discusses the use of DEM extraction from a stereo pair in aerial photos and the subsequent use of DEM in monitoring closed landfill sites. The authors compare the results from the DEM and field-surveyed contours. Depths of 15 and 30 cm depressions were correctly located and computed by the DEM. All results fell within a contour interval of 0.15 m. • Van Eeckhout et al. (1996) used historic aerial photos over Los Alamos National Laboratory (LANL) in New Mexico, from 1947 to 1991, to detail and map surface-, trench-, and pit-buried wastes. Also, drainage patterns of surface water run off were mapped as possible regions of contaminant movement. 4.5.2.5 Multi-Spectral Scanners MSS technologies have been used to provide valuable imagery for a multiplicity of applications, such as the following: • Vincent (1995) used MSS imagery to map changes in chemical constituents over a landfill. The author suggests that the data can be used for mapping stressed vegetation, clay horizons, and iron oxides associated with contaminated groundwater. • Smyre et al. (1998) used a MSS sensor at the ORNL K-25 site to collect VNIR imagery. The imagery was used to detect vegetative stress due to soil or groundwater contamination. The data were used to provide land cover and land use classification information for input into a regional database. • Polosa (1995) used Landsat multi-spectral™ scenes to detect landfills that were abandoned. Some of the sites were relatively small. Using ancillary supporting data, the author was successful in demonstrating mapping of such sites. • The Federal Energy Technology Center (1997) used SPOT satellite imagery and airborne scanner imagery to detect buried trenches and seepages from capped waste sites. Hydrologic information was merged with the MSS imagery in a GIS system to plan soil sampling strategies. 4.5.2.6 Thermal Scanners Examples of the use of thermal remote sensing imagery include the following: • Ziloli et al. (1992) used a thermal camera to image thermal contrasts in and around waste sites. Their results demonstrated that TIR imagery was useful for differentiating between consolidated wastes and waste sections where methane gas conversion was occurring. Also, a distinction between water contaminated with acid slime and uncontaminated water due to a change in thermal capacity can be detected by thermal imagery.

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• Van Eeckhout et al. (1996) used TIR imagery over LANL waste. The TIR imagery was used as a GIS data layer. The imagery was valuable for extracting the location of waste trenches and finding disturbed ground. In general, because there was different packing of the soil in the trench areas, the soil moisture in these trenches tended to be twice that of the surrounding background areas. This had the effect of lowering the temperature of these trench areas. • Smyre et al. (1998) used pre-dawn and daytime TIR airborne imagery to delineate the hydrology of an area, including the identification of seep and spring locations. Also, the TIR imagery was useful in mapping different land cover materials and detecting waste trenches and zones of disturbance from digging. 4.6.2.7 HIS Imagery The following examples illustrate how HIS imagery has been used to characterize and monitor waste sites: • Mackey et al. (1995) used HIS data for the Savannah River site in Aiken, South Carolina. The imaging spectrometer used 85 bands that covered the 466 to 880 nm range. The investigators used a narrow band normalized difference vegetation index (NDVI) to map biomass over the relevant region. Some problems arose because no coeval ground data was collected to aid in calibrating the acquired HIS imagery. However, the results clearly showed that HIS data was useful in monitoring landfill areas at the site where leachate effects on vegetation could be mapped. • As part of a NASA Stennis co-sponsored project, MTL Systems and the University of South Carolina combined to analyze AVIRIS image cubes over the Savannah River site to determine their value in monitoring the integrity of waste site caps. The study showed that hyperspectral data, when analyzed appropriately, provides valuable information on vegetation stress growing over or downslope from compromised caps. Additionally, based on associated work with soil disturbances due to erosion or bioturbation (Kelch et al., 1999), it is suggested that HIS imagery is able to discriminate such disturbances for a wide range of soil types.

4.6 SUMMARY Despite geophysics being used successfully for many years in mineral, petroleum, and geothermal exploration, it has not been used effectively in remediation situations. By and large, the examples of geophysics applied to problems appearing in literature are individual examples of specific applications. Exciting new developments in geophysics, especially new methods of imaging subsurface properties,

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seem to be lagging for environmental applications. Further work should focus on incorporating geophysical mapping of subsurface properties into site characterization programs.

4.6.1 PRIMARY NEEDS

FOR

ADVANCEMENT

The four main needs for advancement are integration, processing and interpretation, code development, and instrumentation. 4.6.1.1 Integration The primary and greatest need is data integration to determine which methods are appropriate for any particular application. If the state of practice of geophysical methods in the environmental industry is compared to the oil and gas industry, a need for case histories of geophysical method use in a variety of geologic settings can be identified. Before the successes of geophysics in other industries, there were many failures. Geophysics requires knowledge of the appropriate application. No method works everywhere. We must learn when and how to use the different methods, which will only occur through experience during use and application. In some cases, utility will become quickly evident (no data or poor data). Issues of resolution, investigation depth, and the linkage to various properties and processes can then be more easily derived. To optimize not only the geophysical methods themselves but also their use, an approach that differs from past practice must be employed. Integration is a concept that is easy to visualize but difficult to achieve. Integration must occur at a variety of levels, from data collection to final interpretation and processing. Not only must the geophysics be integrated as a process, but it must also be integrated into the entire system of site remediation along with other disciplines. 4.6.1.2 Processing and Interpretation Individually, a wide range of processing and interpretation packages exists for processing and interpreting data. Methods are needed for using combined data sets to derive physical properties and either directly or indirectly relate data to chemical and microbial properties. Stated in another way, a map of seismic velocity, radar images, and conductivity is of no use to the engineer unless it can be transformed into a property of interest. A 3-D image of the distribution of such properties as moisture content, the contaminant of interest, or a remediation tool (e.g., steam, water, microbes) is ideal. Therefore, future work should focus on integrating the various methods and interpretations. A statistical approach can be taken by gathering sufficient data to derive meaningful correlation between the geophysical parameters and a property of interest. This could be achieved using both laboratory and field studies, although issues of scaling are important to address when using these data, or an analytical approach can be taken by developing theories on the various hypotheses of geophysical properties related

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to some other property. Although it was empirically derived, Archie’s law relating porosity and matrix properties to resistivity is an example. 4.6.1.3 Code Development Code development is a continuing process driven by the data and needs of a particular problem. Current code development needs are joint inversion schemes utilizing different types of data (e.g., data obeying the diffusion and wave equation) and codes that can model and handle true 3-D data types (e.g., single-well seismic and electromagnetic). Once the appropriate driver exists from the application and data needs and after a specific application can be identified, many different activities in code development can be listed. 4.6.1.4 Instrumentation Recent advances in high-resolution instrumentation have addressed many of the problems associated with deploying modern geophysical methods for environmental applications. Ten years ago, there was a dearth of instrumentation that could take advantage of the powerful data processing approaches being deployed for oil and gas. To a large extent, a wide range of commercially available methods is ready to be applied at environmental cleanup sites, especially for the inductive and DC electrical methods. However, a need exists for cost-effective instrumentation as applied to vadose zone issues. It should be noted for demonstrations where the prime objective is not minimizing cost but investigating applications, a wide range of systems are ready to be applied (e.g., electrical methods, magnetic, and deformation).

4.6.2 FUTURE DEVELOPMENTS The preceding sections illustrate that geophysical methods are promising technologies for enhancing construction and performance evaluations. Applications to site characterization prior to and during construction were also identified. The barrier/host is a complex dynamic system. Enhanced communication between the containment engineer and geophysicist is required in order for the geophysicist to better understand what needs to be monitored and what changes in subsurface geophysical properties are likely. For example, in a PRB emplacement, the distinct electrical properties of granular iron encourage further work with technologies that are sensitive to the subsurface electrical conductivity. Imaging technologies that sense conductivity structure (i.e., electrical resistivity, electromagnetic, and GPR) should be developed as noninvasive tools for assessing construction verification. In a vertical grout emplacement, the interaction and curing of the grout offers challenges and opportunities in not only monitoring the emplacement but also in assessing the performance as a function of time. The case studies previously described demonstrate the potential of these methods. However, numerical, laboratory, and field studies could optimize these technologies as applied to construction verification.

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Future developments in remote sensing that could improve the monitoring of waste sites include ultra-spectral airborne sensors (UIS), HIS thermal sensors, LIDAR technology, interference synthetic aperture radar (IFSAR or InSAR) technology (including polarimetric approaches), and open-path Fourier transform infrared (OPFTIR) spectroscopy. The capabilities of these new remote sensing systems and potential applications are described below. • Developments in UIS, which is an extension of HIS technology, are underway. Whereas the present state-of-the-art hyperspectral sensors cover the range of 400 to 2500 nm with 224 channels that are approximately 10 nm wide, a UIS would provide channels that would number in the thousands with very narrow bandwidths. The advanced UIS would truly emulate an airborne chemical laboratory spectrometer. Given an adequate atmospheric correction, landscape chemistries could be interrogated to allow accurate assessments of leachate species. • HIS thermal sensors represent a research area that is rapidly achieving operational status. The emissivity channels would number in the hundreds. This spectral definition would become available and would boost the application of thermal technology to landfill monitoring significantly. An example of a TIR HIS is the SEBASS sensor (Vaughan and Calvin, 2001). The SEBASS covers both the 3 to 5 μm and 8 to 12 μm range with 128 bands in each spectral emission region. It provides a 2-m ground sample cell and has a 256-m swath. Moreover, the availability of portable TIR spectrometers (Korb et al., 1996) allows for field measurements to be obtained to calibrate and validate airborne TIR HIS data. • A scanned, multi-wavelength, airborne LIDAR sensor system would be capable of emitting several user-selected, narrow laser wavelengths at once to interrogate the environment. The return intensity of the landscape-reflected LIDAR pulses would be captured by the system receiver and would be used to create a multi-spectral reflectance image. Because this would be an active system, it could be used at night and under cloudy conditions as long as the sensor was flown under the cloud deck. Furthermore, landscape elevations could be extracted from the data to give highly accurate DEMs that could be used to orthorectify the multi-spectral image obtained from the pulse-return intensities. Finally, with an additional receiver tuned to receive stimulated fluorescence emissions due to the LIDAR excitations, the fluorescent spectroscopy of the landscape materials could be analyzed. This is important because chemical species and vegetation stress could be detected across a selected site. • IFSAR technology consists of radar sensors using coherent returns from two radar systems along a common time baseline to beat one signal against another. This process creates an image interferogram of the given scene. The interferogram provides spatial shift/change information of

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the imaged scene. This technology could be used to assess small changes (millimeter range) in elevation or lateral dislocations in a closure cap. IFSAR technology is relatively operational and could be utilized for waste site monitoring. The difficulty is the cost of the data and the relative scarcity of usable radar sensor systems at present. • OPFTIR spectroscopy can be used to measure and monitor chemical contaminants and fugitive emissions in situ at landfill sites. In fact, the United States Environmental Protection Agency (USEPA) has been interested in composing an infrared spectral database to support OPFTIR remote sensing (Chu et al., 1999). A definitive set of spectral reference data is required because published molar absorptivity values can vary significantly. These systems have been used at Superfund sites and have performed well. The sensors can detect contaminants at the parts per billion level. However, these systems can suffer from atmospheric noise sources (e.g., strong absorption bands of water vapor and carbon dioxide) and detector limitations.

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Klimentos, T. and McCann, C. (1990). Relationships among compressional wave attenuation, porosity, clay content, and permeability in sandstones. Geophysics, 55(8), 998–1014. Korb, A., Dybwad, P., Wadworth, W. and Salisbury, J. (1996). Portable FTIR spectroradiometer for field measurements of radiance and emissivity. Applied Optics, 35, 1679–1692. Korneev, V.A. and Johnson, L.R. (1993a). Scattering of elastic waves by a spherical inclusion — 1. Theory and numerical results. Geophysics Journal International, 115, 230–250. Korneev, V.A. and Johnson, L.R. (1993b). Scattering of elastic waves by a spherical inclusion - 2. Limitations of asymptotic solutions. Geophysical Journal International, 115, 251–263. Korneev, V.A. and Johnson, L.R. (1993c). Elastic scattering by a spherical inclusion. Bulletin of the Seismic Society of America, unpublished. Krohn, C.E. (1992). Cross-well continuity logging using seismic guided waves. The Leading Edge, 11(7), 39–45. Kuster, G.T. and Tokoz, M.N. (1974). Velocity and attenuation of seismic waves in twophase media: Part 1: Theoretical formulations. Geophysics, 39, 587–606. Lane, J.W., Joester, P.K., Savoie, J.G. Cross-Hole Radar Scanning of Two Vertical, Permeable, Reactive-Iron Walls at Massachusetts Military Reservation, Cape Cod, MA, USGS Water Resources Investigation Report 00-4145, 17 p. Leary, P.C. and Henyey, T.L. (1985). Anisotropy and fracture zones about a geothermal well from P-wave velocity profiles. Geophysics, 50(1), 25–36. Lillesand, T. and Kiefer, R. (1994). Remote Sensing and Image Interpretation, Wiley, New York. Liu, E., Crampin, S. and Queen, J.H. (1991). Fracture detection using crosshole surveys and reverse vertical seismic profiles at the Conoco borehole test facility, Oklahoma. Geophysical Journal International, 107, 449–463. Mackey, H., Jensen, J., He, K. and Graves, D. (1995). Technological transfer of high spectral resolution remote sensing imaging spectrometer on the Savannah River site for environmental applications. http://www.cla.sc.edu/GEOG/rslab/vip/west/west.html Majer, E.L. and Geller, J.T. (1992). Joint hydrologic, geologic and seismic characterization of soil in the lab and in the field. EOS, Transactions American Geophysical Union, 73(43), 171. Majer, E.L., McEvilly, T.V., Eastwood, F.W. and Myer, L.R. (1988). Fracture detection using P- and S-wave vertical seismic profiling at the Geyser’s. Geophysics, 53(1), 76–84. Majer, E.L., Peterson J., Daley, T.M., Kaelin, B, Queen, J., D’Onfro, J. and Rizer, W. (1997). Fracture detection using crosswell and single well surveys. Geophysics, 62(2), 495. Majer, E.L., Williams, K.H., Peterson, J.E. and Daley, T.E. (2002). High resolution imaging of vadose zone transport using crosswell radar and seismic methods, Report LBNL-49022. Marion, D. (1990). Acoustical, mechanical and transport properties of sediments and granular materials. Ph.D. thesis, Stanford University, California. Marion, D., Nur, A., Yin, H. and Han, D. (1992). Compressional velocity and porosity in sand-clay mixtures. Geophysics, 57(4), 554–563. Mason, I.M. (1981). Algebraic reconstruction of a two-dimensional velocity inhomogeneity in the High Hazles seam of Thorsby colliery. Geophysics, 46, 298. McIntire, P. (1991). Nondestructive Testing Handbook, 2nd ed., Ultrasonic Testing ASNT, 7.

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Measures, R. (1984). Laser Remote Sensing, Wiley-Interscience, New York. Minear, J.W. (1982). Clay Models and Acoustic Velocities, SPE Publication, 11: p. 11031. Mochizuki, S. (1982). Attenuation in partially saturated rock. Journal of Geophysical Research, 87(B10), 8598–8604. Moya, I., Guyot, G. and Goulas, Y. (1992). Remotely sensed blue and red fluorescence emission for monitoring vegetation. ISPRS Journal of Photogrammetry and Remote Sensing, 47, 205–231. National Research Council (1995). Airborne Geophysics and Precise Positioning, Academy Press, Washington DC, 111 pp. Nichols, E., Morrison, H.F. and Clarke, J. (1985). Signals and noise in magnetotellurics. presented at the 55th Annual Society of Exploration Geologists Meeting, Washington, DC, October 6–10. Nihei, K.T., Yi, W., Myer, L.R. and Cook, N.G.W. (1999). Fracture channel waves. Journal of Geophysical Research, 104(B3), 4769–4781. Noonan, M. (1998). Remote sensing of the physiological status of vegetation using laser induced red and blue fluorescence. White paper report, University of Queensland. Olhoeft, G.R. (1985). Low-frequency electrical properties. Geophysics, 50, 2492–2503. Parra, J.O. (1991). Analysis of elastic wave propagation in stratified fluid-filled porous media for interwell seismic applications. Journal of the Acoustical Society of America, 90(5), 2557–2575. Pellerin, L., Gilbert, F., Hubbard, S., Peterson, J, and Dailey, W. (1998). Geophysical Verification of Subsurface Barriers. EEGS 11. Pelton, W.H., Ward, S.H., Hallof, P.G., Sill, W.R. and Nelson, P.H. (1978). Mineral discrimination and removal of inductive coupling with multifrequency IP. Geophysics, 43, 588–609. Peterson, J.E., Paulsson, B.N.P. and McEvilly, T.V. (1985). Application of tomographic reconstruction techniques to crosshole seismic data. Geophysics, 50(10), 1566–1580. Polosa, R. (1995). Knowledge-based interpretation of Landsat TM scenes detects abandoned landfills. International Journal of Rock Mechanics and Mining Sciences, 32(40), 163A. Pyrak-Nolte, L.J., Myer, L.R. and Cook, N.G.W. (1990a). Anisotropy in seismic velocities and amplitudes from multiple parallel fractures. Journal of Geophysical Research, 95(B7), 11345–11358. Pyrak-Nolte, L.J., Myer, L.R. and Cook, N.G.W. (1990b). Transmission of seismic waves across single fractures. Journal of Geophysical Research, 95(B6), 8617–8638. Ranson, J. and Sun, G. (1994). Mapping Biomass of a northern forest using multifrequency SAR data. IEEE IGARS, Raw Materials (Hanover), 32(3), 388–396. Rignot, E., Williams, C., Way, J. and Viereck, L. (1994). Radar estimates of aboveground biomass in boreal forests of interior Alaska. IEEE IGARS, 32(5), 1117–1124. Rhoades, J.D., Raats, P.A.C. and Prather, R.J. (1976). Effects of liquid-phase electrical conductivity, water content, and surface conductivity on bulk soil electrical conductivity. Soil Science Society of America Journal, 40, 651–655. Schoenberg, M. (1980). Elastic wave behavior across linear slip interfaces. Journal of the Acoustical Society of America, 68(5), 1516–1521. Schoenberg, M. (1983). Reflection of elastic waves from periodically stratified media with interfacial slip. Geophysical Prospecting, 31, 265–292. Sheets, D.K. and Hendrickx, J.M.H. (1995). Noninvasive soil water content measurement using electromagnetic induction. Water Resources Research, 31, 2401–2409.

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5

Subsurface Barrier Verification Prepared by* David J. Borns Sandia National Laboratories, Albuquerque, New Mexico

Carol Eddy-Dilek Westinghouse Savannah River Company, Oxford, Ohio

John D. Koutsandreas Florida State University, Tallahassee, Florida

Lorne G. Everett L. Everett and Associates, LLC, Santa Barbara, California 5.1 OVERVIEW Waste containment system performance data are needed to conduct assessments that reveal the integrity of the barrier and verify that the operational aspects of the systems are functioning as designed. Biological, chemical, and physical phenomena in the subsurface or some combination thereof can impact the performance of subsurface barriers. To confirm the performance of the barrier and possibly determine where a failure has occurred, a well-planned and implemented monitoring system is required. The design service life of a containment system can range from as little as 10 years for slurry walls to more than 1000 years for radioactive waste storage structures. The longer the service life of a containment system, the greater the * With contributions by William R. Berti, DuPont Central Research and Development, Newark, Delaware; Skip Chamberlain, U.S. Department of Energy, Washington, DC; Thomas W. Fogwell, Fluor Hanford, Richland, Washington; John H. Heiser, Brookhaven National Laboratory, Upton, New York; John B. Jones, U.S. Department of Energy, North Las Vegas, Nevada; Eric R. Lindgren, Sandia National Laboratories, Albuquerque, New Mexico; William E. Lowry, Science and Engineering Associates, Inc., Santa Fe, New Mexico; Keri H. Moore, National Research Council, Washington, DC; Horace K. Moo-Young, Jr., Villanova University, Villanova, Pennsylvania; Michael G. Serrato, Westinghouse Savannah River Company, Aiken, South Carolina; Matthew C. Spansky, Westinghouse Savannah River Company, Aiken, South Carolina;

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probability of system failure. Because most components of containment systems exist underground, direct visual inspection is not tenable as a monitoring method. Thus, several traditional and evolving techniques of indirect and direct observations need to be employed to obtain performance data. In terms of containment system effectiveness, two types of failure categories can be identified: structural failure and functional failure. Structural failure can occur without functional failure, although it can eventually lead to functional failure. Thus, verification monitoring of barrier structural and/or functional failures is essential over the life of the barrier. Long-term monitoring is an important aspect in determining the integrity of the barrier over the lengthy lifetimes of many contaminants. This chapter discusses the state-of-the-art monitoring technologies and recommends innovative methods such as in situ sensors to improve and reduce the cost of barrier monitoring.

5.2 GOALS Subsurface verification is integral to achieving acceptance of covers, permeable reactive barriers (PRBs), and subsurface barriers such as walls and floors. The roles of subsurface verification in this process of acceptance are as follows: • • • • • •

Meet or exceed regulatory requirements Verify performance of engineered barriers Verify conceptual models of contaminant fate and transport Verify models for containment systems Conduct long-term performance monitoring Ensure identification of trigger levels for contingency actions

At present, there are no specific regulations under the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) or the Resource Conservation and Recovery Act (RCRA), and there is no regulatory guidance on subsurface barrier integrity or performance validation. The only regulatory standard for barriers is the RCRA requirement (40 CFR 264, Subpart N, Landfills) of a 10–7 cm/s hydraulic conductivity at a thickness of 0.91 m. Additional standards may be added in the near term because the United States Environmental Protection Agency (USEPA) Office of Emergency and Remedial Response has launched the Superfund Initiative on Long Term Reliability of Containment (Betsill and Gruebel, 1995). The USEPA is scheduled to work with other U.S. agencies to develop technical guidance and methodologies to evaluate containment technologies. The American Society for Testing and Materials International (ASTM) has standards pertaining to barrier monitoring. Reference to these standards should be made when considering potential methods. The ASTM D18.21.02 committee, chaired by Lorne G. Everett, on vadose zone monitoring standards is responsible for publishing the list of vadose zone standards provided in Table 5.1.

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TABLE 5.1 ASTM International Vadose Zone Monitoring Standards Vadose zone terminology (final) Soil pore-liquid monitoring (D 4696-92) Soil core monitoring (D 4700-91) Matrix potential determination (D 3404-91) Neutron moderation (D 5220-92/97) Soil gas monitoring (D 5314-93) Hydraulic conductivity (D 5126-90) Decontamination of field equipment (D 5088-90) Flux determination by time domain reflectometry (D 6565) Determining unsaturated and saturated hydraulic conductivity in porous media by steadystate centrifugation (D 6527) Horizontal applications of neutron moderation (D 6031) Frequency domain capacitance (Z4302Z) Field screening guidance standard (final) Water content determination (draft) Vadose zone borehole flow rate capacity test (draft) Air permeability determination (outline) Thermalcouple psychrometers (outline)

5.3 VERIFICATION MONITORING Monitoring plays a key role at all stages in environmental management — from initial site discovery to site closure. Monitoring programs are essential in facilitating site characterization and risk assessment, adequately conducting experimentation and evaluation, producing the data necessary for the performance evaluation, determining whether residual contamination exists that will prevent site closure, and verifying the effectiveness of containment structures. The focus of monitoring programs is necessarily site and time specific. For example, a soil remedial action may primarily require sampling during excavation and immediately after remediation work is complete (site closure). For sediment and groundwater remedial actions, longer-term monitoring programs might be developed that have their roots in initial site characterization activities, continue through remediation, and extend for significant periods of time beyond termination of active remediation. In the case of groundwater, most sites begin with an inherited set of monitoring points already established and so part of the monitoring design process also includes determining to what extent the existing network can be used or must be abandoned or expanded. Depending on the selected remedial action (Table 5.2), monitoring programs can represent the majority of remedial action costs (e.g., monitored natural attenuation) or only a small percentage. Traditional characterization and verification monitoring programs tend to prespecify sample numbers, locations, sampling frequency, and analytics (i.e., offsite laboratory analyses). This traditional type of data collection presents several

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TABLE 5.2 Progressive Monitoring Steps for a Remediation by Natural Attenuation Program Step I II

Establish point of compliance Define what is to be monitored

III

Establish the time period for monitoring

IV

Define how monitoring is to be done

Description

Parties Involved

Specify point of compliance and the point at which monitoring must be conducted Demonstrate that natural attenuation is occurring according to expectations accomplished by including steps to: 1. Identify any potentially toxic transformation products; Determine if a plume is expanding (either downgradient, laterally or vertically) 2. Ensure no impact to down gradient receptors 3. Detect new releases of contaminants to the environment that could impact the effectiveness of the natural attenuation remedy 4. Demonstrate the efficacy of institutional controls that were put in place to protect potential receptors 5. Detect changes in environmental conditions (e.g., hydrogeologic, geochemical, microbiological, or other changes) that may reduce the efficacy of any of the natural attenuation processes 6. Verify attainment of cleanup objectives Continue as long as contamination remains above required cleanup levels, continue for a specified period (e.g., 1–3 years) after cleanup levels have been achieved to ensure that concentration levels are stable and remain below target levels. Demonstrate of the monitoring approach being appropriate and verifiables accomplished by including steps to: 1. Specify methods for statistical analysis of data, e.g., established tolerances, seasonal and spatial variability 2. Establish performance standards: • Information on the types of data useful for monitoring natural attenuation performance in the ORD publications (EPA/540/R-97/504, EPA/600/R-94/162) • EPA/600/R-94/123: a detailed document on collection and evaluation of performance monitoring data for pump-and-treat remediation systems

Regional administrator Site operator and regional administrator (USEPA or the state-implementing agency)

Regional administrator (USEPA or the stateimplementing agency) Site operator and regional administrator (USEPA or the stateimplementing agency)

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TABLE 5.2 (continued) Progressive Monitoring Steps for a Remediation by Natural Attenuation Program Step

Description

V

Define action levels or process to be observed for monitoring

VI

Define actions to be accomplished when action levels or processes are observed

• Standard test methods such as described in EPA SW-846, “Test Methods for Evaluating Solid Waste - Physical/Chemical Methods” or EPA publication, “Methods of Chemical Analysis for Water and Wastes” 3. Establish a time interval agreed upon by regional administrator or agency, including reporting maps, tabulation of data and statistical analysis, identification of trends, recommendations for changes in approach, evaluation of whether contaminants have behaved as predicted, and whether other remedies are required Establish metrics for the monitoring system: 1. Establish background levels 2. Define what criteria shows that a plume is expanding or diminishing 3. Define what criteria shows that the conceptual model is applicable to a site 4. Determine the metrics of cleanup objectives and effectiveness Establishment of action plan to follow attainment of metric: 1. Observe requirement to report to responsible party or agency statistically significant variance compared to background 2. Identify extent and nature of nonpredicted behavior (e.g., release) 3. Re-evaluate conceptual model and evaluate feasible corrective actions from previous and evolving contingency plan

Parties Involved

Site operator and regional administrator (USEPA or the stateimplementing agency)

Site Operator will provide details of the monitoring program; should be provided to USEPA or the state-implementing agency as part of any proposed monitored natural attenuation remedy

limitations, particularly in the context of subsurface characterization and monitoring. The costs are sometimes prohibitive, driven both by sample analytical costs and the capital investment required for monitoring wells. High monitoring costs, particularly for monitoring programs that extend over time, result in pressures to limit data collection. Limited data collection, in turn, results in decisionmaking that relies on data sets too sparse to adequately address the inherent heterogeneities and uncertainties associated with subsurface barrier systems. Finally, by prespecifying sample numbers and locations and relying on off-site

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laboratory analyses with long turnaround times for analytical results, traditional characterization and monitoring programs are ill equipped to handle unexpected results. Fortunately over the last several years, technological advances have occurred in sensors, field analytics, and sample collection technologies that can help to lower costs and/or increase the effectiveness of monitoring programs (see Box 5.1). New approaches for designing and implementing environmental data collection programs have also been developed. A few of those innovative barriermonitoring technologies are discussed in the subsections below. BOX 5.1 Rapid Field Characterization of Sediments Rapid field characterization techniques have been developed to speed assessment and reduce costs. These are field-transportable screening tools that provide measurements of chemical, biological, or physical parameters on a real-time or near real-time basis. Specific advantages include the ability to get rapid results to guide sampling locations, the potential for high data mapping density, and a reduced cost per sample. The approaches do have limitations including the nonspecific nature of some tests, sensitivity to sample matrix effects, and some loss in accuracy over conventional laboratory analyses. A variety of tools has been suggested for the rapid characterization of sediments, as shown in the table below. Screening-Level Analyses Recommended by the Assessment and Remediation of Contaminated Sediments Program for Freshwater Sediments Analytical Technique

Parameter(s)

X-ray fluorescence spectrometry (XRF) UV fluorescence spectroscopy (UVF) Immunoassays Microtox

Metals Polycyclic aromatic hydrocarbons (PAHs) PCBs, pesticides, PAHs Acute toxicity

5.3.1 METHODS Methods for barrier monitoring generally fall into broad classes such as measurement of moisture change, collection of moisture and gas samples, temperature, flow/velocity, barometric pressure, and settlement. An in-depth evaluation of barrier-monitoring science and technology is provided in the National Department of Energy Vadose Zone Science and Technology Roadmap [Idaho National Environmental Engineering Laboratory (INEEL), 2001]. 5.3.1.1 Moisture Change Monitoring Methods A number of methods are available for barrier-monitoring moisture change in soils (Everett et al., 1984; Wilson et al., 1995; Looney and Falta, 2000a,b). Many of these measurement techniques require laboratory testing to develop calibration curves relating instrument output to soil moisture content. Several of the more commonly used methods are described below.

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•

•

•

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Neutron probe — The neutron probe contains a source of neutrons and detectors to measure backscattered neutrons. The magnitude and energy of backscattering is primarily a function of the hydrogen content of the material surrounding the probe. To take readings, the neutron probe is lowered into the pipe and a continuous record of the response is obtained. Changes in the readings over time at a particular depth indicate changes in the number of hydrogen atoms, i.e., water content. The neutron probe must be calibrated for specific soils. This method is discussed in more detail in Section 5.9.1.1. Time domain reflectometer — In this method, an electromagnetic wave is transmitted along a transmission cable buried in soil. At the end of the cable, a portion of the signal is reflected. The amplitude and travel time of the reflected portion depend on the dielectric properties of the soil, which in turn are strongly dependent on soil moisture content. The output is typically monitored on an oscilloscope or cable tester. These probes can be monitored remotely and have no direct analytical costs associated with them other than initial calibration. This tends to minimize life-cycle costs. Thermocouple psychrometer — This instrument measures relative humidity within the soil pores, from which soil water potential and therefore moisture content can be calculated. Humidity is determined by the observed difference in temperatures between two thermocouples, one of which is exposed to the humidity in the surrounding soil and experiences cooling; the other thermocouple is located adjacent to the first but is isolated from the humidity. Moisture content is determined from relative humidity on the basis of laboratory calibration. Electromagnetic Induction (EMI) — EMI is a standard geophysical technique (Chapter 4) that is used to measure the conductivity of soil mass. At the ground surface, a transmitter coil generates an electromagnetic field that induces eddy currents in the underlying subgrade. Secondary electromagnetic fields created by the eddy currents are measured by a receiver coil that produces an output voltage related to the subsurface conductivity. EMI is a rapid technique that is often used to delineate contaminant plumes, buried wastes, and other features that have conductivity contrasts with the surrounding soil. Electrical resistivity tomography (ERT) — ERT is based on a large number of soil resistance measurements (Chapter 4) analyzed by mathematical methods (e.g., finite difference models employing inversion techniques). Each resistance measurement involves several electrodes, some to apply a current through the soil and some to measure the voltage drop. The location and spacing of the electrodes determines the soil volume being measured; in general, larger electrode spacings are used at greater depth. Commonly, a linear series of electrodes is placed on the ground surface or beneath a landfill. An automatic monitoring

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•

system excites various pairs of electrodes according to a programmed sequence and measures the resistance between other pairs. When all desired combinations have been read, the resulting data are analyzed. The result is a two-dimensional contour map (i.e., a vertical or horizontal slice) of soil resistivity along the electrode line. Changes in moisture content over time appear as changes in resistivity. Laboratory calibration of subgrade soil is required to develop quantitative relationships. High-resolution resistivity has shown particular merit in both cap and subsurface liner monitoring but is not developed to a stage where it can be recommended in the near term. Fiber-optic cable — These systems could be considered as one of the latest improvements in vadose zone sensor systems. Fiber-optic systems already are measuring strain, temperature, acoustics, moisture, pH, flow, and chemicals. Fiber-optic cable could be included in the future applications of a monitoring system. The cable could be deployed in the perforated stainless-steel tubing laid down below the bottom liner during construction. Consideration could be given to including fiber-optic cable in the horizontal and vertical monitoring orientations. The cost advantages expected with the use of fiber-optic sensors are substantial. The risk of causing preferential flow paths associated with installing a very small diameter fiber cable is small relative to the other technologies.

5.3.1.2 Moisture Sampling Methods There are processes other than leakage through the barrier liner system that could cause changes in moisture content of the vadose zone. Examples include moisture release from the admix layer as it consolidates under the load of the waste, and vapor migration due to temperature changes caused by excavation, lateral moisture, or vapor movement into the trench (from outside the trench), and removal of subgrade soils. Moisture change resulting from such processes could be difficult to distinguish from leachate. In addition, those methods described above in Section 5.3.1.1 that use electrical properties of the soil would be influenced by dissolved constituents as well as moisture content alone. In spite of these limitations, in the case of a RCRA cap, which is designed as an impermeable cap, elevated moisture migration rates alone can be used as an indicator of increased infiltration through the cap. To determine whether moisture is the result of leakage through the barrier liner, samples are collected and analyzed for constituents known to occur in the waste material. A number of techniques are available and are described in the literature (Everett, 1980; Everett et al., 1984; Wilson et al., 1995; Looney and Falta, 2000a,b). •

Suction lysimeter — The suction lysimeter consists of a porous cup or plate attached to a small diameter tube leading to a sampling chamber.

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•

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The lysimeter is buried in the soil at the location where a sample is desired, and the tubing leads to an accessible location. To obtain a sample, a reduced pressure is applied to the lysimeter. Water in the soil matrix is sucked into the lysimeter and accumulates in the sampling chamber. There are various modifications utilizing additional tubes, check valves, and other components to allow samples to be retrieved from depth, but the basic operating principle is the same. Absorbent pads — This method uses pads of absorbent material, such as felt, to collect soil moisture. One commercially available system (Flute) that has been used to collect samples beneath a radioactive waste landfill at Los Alamos National Laboratory (New Mexico), uses a cylindrical flexible membrane that holds the pads. The membrane is initially inside out, or inverted, and is everted as it is placed in the borehole so that the pads contact the borehole wall. After a period of time, when the pads have reached equilibrium with the surrounding material, the membrane is withdrawn, being inverted again during this process so that the pads are not contaminated. In soil materials, where an open borehole cannot be maintained over the long term, a permeable casing is required. Sodium iodide gamma detector — This is a radiation-measuring instrument that is lowered down an access pipe. Rather than returning a sample to the ground surface, the detector measures the radioactivity of the surrounding soil. This method identifies contaminants that are gamma emitters in sufficient concentrations to be clearly detectable. For additional details, refer to the discussion in Section 5.5.2.1. Basin lysimeter — The basin lysimeter consists of a broad, shallow basin a few meters in dimension. It is lined with a geomembrane and backfilled with vadose zone soil. The floor of the basin slopes to a collection point, and a pipe leads from this point up to the ground surface. When a sample is required, a sampling pump is lowered down the pipe, where quantifiable measurements can be obtained.

5.3.1.3 Vadose Zone Monitoring Considerations To monitor flow and transport in covers, walls and floors, point-type probes such as tensiometers, time-domain reflectometry probes (TDR), suction lysimeters, and thermistors can be used as well as geophysical imaging methods such as seismic surveys, ground penetrating radar (GPR), and three-dimensional (3-D) ERT (Hubbard et al., 1997). Point-type probes may or may not intersect single flow paths (Figure 5.1). The shortcoming of point-type probe measurements is the difficulty of combining their responses in a meaningful way, such as integrating or volume averaging responses from a number of point measurements. Geophysical imaging methods complement point-type measurements by providing a spatially distributed view of subsurface conditions. Each measurement represents an average over space and time; however, the volume affected cannot be determined.

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1 2 3

1

1. Tenslometers, ER probes, TDR provide local (6–20 om) measurements 2. Vacuum water sampling and neutron logging affect the 30–40 om near borehole 3. Cross-hole radar and 3D ER; tomography are effective within the zone of up to 10–12 m

2

3

Preferred water

FIGURE 5.1 Schematic of the performance of local-type and cross-borehole monitoring methods in a heterogeneous formation (In Situ Remote Sensors and Networks, 1999e).

The shortcomings of geophysical methods are their lack of spatial resolution in detecting small barrier leaks, and the difficulty of correlating values such as electromagnetic responses and seismic velocities to hydrogeologic parameters governing fluid flow. Neither method can be used to observe flow in single fractures of fluid movement at the fracture matrix interface in sufficient detail to accurately represent transport through barriers.

5.4 VERIFICATION SYSTEM DESIGN One of the key issues discussed at the workshop was integrating the verification system design into the overall barrier design. The barrier must have a set of performance requirements that are site specific and risk based. Without a riskbased performance objective, the barrier is either intact and good or breached and unusable. As stated previously, none of the regulatory agencies has a set of criteria for a barrier. De facto, the regulators take a risk-based approach to approving such structures. Risk-based performance objectives are crucial to the successful deployment of subsurface barriers. This fact is demonstrated when comparing two identical failures in a barrier at distinctly different locations. Suppose an obstruction blocks the flow of grout during installation of a barrier wall, resulting in a 1 m2 hole in the barrier wall. In one case the hole occurs within 1.2 m of the uppermost (shallowest) region of the barrier. In the other case, the hole is located at the bottom region of the barrier. Water flux through the waste site would result in contaminant mobilization

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and transport with the water. Water flow would occur mostly in a vertical direction due to gravity. Near the surface of the barrier, horizontal spread would be minimal and the likelihood that water will transport out of a hole near the top of the barrier is small. At the bottom of the barrier, water would collect and any hole in this region would serve as a drain, similar to a bathtub. These two nearly identical flaws in the barrier have extremely different consequences. One would require repair and the other could be ignored entirely. When designing a verification/monitoring system, it is crucial that a set of failure criteria be established. This may necessitate implementing an iterative approach to barrier and verification designs. Once the performance requirements are established for the barrier and a conceptual model is developed, a conceptual verification system can be designed. The conceptual barrier design may need to be modified to accept the verification design (e.g., use of plastic components instead of metal to allow for the use of ground penetrating radar). Once conceptual models for both have been developed, the failure mechanisms of the barrier need to be identified. Using risk assessment models, the failure scenarios can be simulated to determine what constitutes unacceptable failure of the barrier. Depending on the results, the verification/monitoring system may require changes, which can result in further modifications to the barrier design and so forth. This process continues until an acceptable combination of barrier design and verification/monitoring system is achieved.

5.5 MOVING FROM STATE OF THE PRACTICE TO STATE OF THE ART Subsurface verification suggests that containment design and implementation move toward the state of the art rapidly from the current state of the practice. In 1976, Everett et al. recommended neutron probes and suction lysimeters for cap and floor barrier monitoring. Thirty years later, these same two techniques are still primarily used for barriers in California. The basic steps to accomplish this badly needed state-of-the-art transition are twofold: 1. Take a full system approach in which design, implementation, characterization, and verification are iterative, inter-connected, and ongoing. This integrated approach includes optimizing the verification activities, defining the performance goals and action levels, and using methods to quantify uncertainty. 2. Move implementation toward the smart structure approach now used in buildings, bridges, roads, and other structures in which sensors and telemetry are incorporated during construction. This smart structure approach will affect a lowering of cost through in situ analysis and help achieve the end state at many sites that are expected to have no on-site restoration personnel.

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5.5.1 SYSTEM APPROACH The technical process of total system performance assessment (i.e., integration design, prediction, and data collection) may appear complex initially. However, such processes are used in our everyday lives (e.g., buying a car, selecting an area where to live, choosing a career). The approach here is to build on the familiar everyday aspects to develop a process that can be rigorously and defensibly applied to environmental remediation (Borns, 1997). The predictive tools and data needs from subsurface monitoring programs for boosting long-term containment system performance are part of an integrated system of data collection, decision analysis, and uncertainty analysis. The engineering process of decision analysis and uncertainty analysis bridges the gap of predictive tools used between the engineering design and the long-term performance assessment methods (tens of years to thousands of years of performance). Decision analysis and uncertainty analysis also provide a basis for an integrated and interactive approach using design, predictive models, and the analysis of the accumulated data at different stages of the project. All projects, engineering and environmental, have built-in decision processes that involve varying risk-reward scenarios (Lockhart and Roberds, 1996). These processes can be based on intuitive, analytic, numerical, and expert judgment approaches. Developers, end-users, and stakeholders evaluating in situ stabilization and containment systems are faced with a similar problem of selection. However, the time periods of predicted performance are longer, and the consequences of failure are higher than these everyday examples of system prediction. The predictive tools and the data, which are used to ascertain long-term performance, are required to be rigorous, documented, and defensible. Such predictions of long-term performance are based on conceptual models of system design and the geological environment (natural system) that encompasses the system. These conceptual models and the adequacy of the performance prediction reflect the uncertainties and data quality that describe natural and designed containment system performance. 5.5.1.1 Links to Modeling and Prediction An example of the important link among landfill design, modeling, and performance assessment is in the realm of permeable reactive barriers. Morrison et al. (2001) described the importance of reaction path modeling to predict and verify PRB performance. Similarly, Roh et al. (2000) demonstrated the importance of modeling the corrosion, precipitation, redox reactions, and sorption in predicting PRB material performance. Hydrologic modeling was identified by Gupta and Fox (1999) as essential for barrier design (including location, width, and material selection) and for evaluating scenarios for performance predictions. These separate modeling activities should be linked into a system with the data flowing from the subsurface or other verification activities. The overall system can be linked as in Figure 5.2.

Subsurface Barrier Verification Project description Stakeholders

Decision criteria

Project alternatives

Screening & trade-offs

Potential Potential consequences

Optimum decision

Implementation & feedback

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Data

Conceptual Models

Data

Mathematical Models

Parameter Definitions

Sensitivity studies Potential Consequences

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FIGURE 5.2 The decision–analysis process of Lockhart and Roberds (1996) (Civil Engineering, April, 62–64).

5.5.1.2 Optimization The integration of verification data and modeling permits another important step, which is the optimization of the integrated system. An optimization approach for verification is a set of tools, at this time conceived to be computer programs, that tells the PRB user or designer where and how often measurements or samples need to be obtained to determine (1) whether the remedial system is operating properly, and (2) if risks have increased. The goal is to monitor in space and time to achieve the following: •

•

Meet regulatory requirements and/or assess residual risks using a minimum number of monitoring stations located where the contaminant or surrogate variable is most likely to be. Sample at a frequency that captures contaminant movement to confirm that all processes are operating effectively or trigger any necessary contingency action.

Gupta and Fox (1999) describe how hydrologic data combined with modeling define the optimal monitoring well locations and range of variation in flow direction and flux needed for verification. 5.5.1.3 Decision and Uncertainty Analysis The decision analysis process (Figure 5.2) of Lockhart and Roberds (1996) can be used as an example to identify the predictive tools and data needs for subsurface containment projects. This process also provides a basis for implementing an integrated and interactive approach using design, predictive models, and the analysis of the accumulated data at different project stages. The tables are provided to give an understanding of the types of parameters and processes that need to be determined to apply risk decision analysis processes to a given problem. The evaluation of remediation sites demonstrates the difficulties in obtaining data and the uncertainties of important parameters. Water balance modeling,

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which is a significant component in transport modeling, provides an example of the difficulties in evaluation. Such difficulties are due to the level of understanding of the process and the adequacy of the data to support the evaluation. For water balance modeling, it must be recognized that evaporation (or evapo-transpiration) cannot be reliably calculated in either humid or arid environments. The best estimates for the evaporation parameters are for humid environments. Even for the best of these estimates, a great deal of empirical judgment is required, and the uncertainties are large. The resulting recharge estimates are in error by as much as 100% or more. It is virtually impossible to calculate evaporation for arid environments. Errors of two to three orders of magnitude or more are not uncommon. Because the understanding of processes is incomplete and because of the high degree of uncertainty for important parameters, there is no preferred code or set of codes for hydrologic modeling at arid sites. Hydrologic models for arid sites are still being tested and calibrated.

5.5.2 SMART STRUCTURES As barriers have become more complex, there is an ever-increasing need to build intelligence into them so that they can sense and react to environmental changes and impacts. To achieve this, a nervous system is required that performs in a manner analogous to those living things sensing the environment, conveying the information to central processing unit (the brain), and reacting appropriately. A number of sensor technologies are being modified for use in verification monitoring systems for barriers. These sensors can be embedded into the barriers or in close proximity to the barriers, resulting in smart barriers with a built-in nervous system. These smart barrier systems offer the prospect of adding effective monitoring systems that are responsive to barriers but also are able to localize failures and take appropriate action (Borns, 1997). Sensors incorporated into barrier construction have the following advantages: •

• • •

• •

They are inexpensive and can be placed in numerous positions where previously only one data point was captured through expensive monitoring wells. They can be designed to change out easily upon failure. They reduce the sampling waste created in conventional monitoring programs. They can be placed in difficult to reach locations and possibly eliminate exposure to contaminated mediums for field workers who would normally have to collect samples. Through the iterative process, they improve the model. Because most barriers will outlive most monitoring sensors, Everett and Fogwell (2003) have stressed the importance of long-term access to critical subsurface monitoring locations. These locations for caps and liners are discussed later in this chapter.

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One of the most effective monitoring technologies currently being employed is fiber optics. Fiber-optic systems involve fiber-optic sensors and communication links that allow the measurements of critical parameters of materials, structures, liquids, and gasses. Surrogate parameters are good indicators of barrier performance and are easily achievable with fiber-optic sensors. Surrogate measurements such as moisture, pH, temperature, flow/velocity, and barometric pressure are good indicators of barrier failures. The monitored moisture data facilitates sitespecific understanding of the transport pathways and processes that influence contaminant movement. The technical discussions of how fiber-optic sensors operate are not discussed in this chapter because a number of manufacturing options exist. Simply stated, fiber-optic sensors rely on the interaction of a light beam in the core of the fiberoptic cable with the parameter to be measured or some interaction thereof. The cladding on the fiber-optic cable can also be treated to produce the desired results. The advantages of this technology include lightweight systems, immunity to electromagnetic interference, and the ability to be imbedded into hostile environments with extremely high bandwidth capability. Fiber-optic sensor systems can sense environmental changes within or around the barriers, interpret the measurements, and initiate an appropriate reaction to these changes. Some of the parameters that are being measured using this technology include strain, temperatures, acoustics, moisture, pH, flow, and chemicals (Udd, 1995). Representative distributed fiber-optic sensors allow measurements of specific parameters and can help determine the location of where the measured-induced change occurs (Udd, 1995). Distributed chemical sensors can be constructed by coating an optical fiber with indicator chemicals. The chemical to be sensed diffuses into the cladding, modifying the absorption of the dye and accordingly changing the attenuation of the fiber laser or light beam, which represents the chemical to be measured. Additional information can be found in the bibliography of Udd (1995). For example, fiber-optic sensors have the potential to enable smart barriers that would be difficult or impossible to implement using conventional electronic technology. High priority barrier-monitoring parameters discussed at the LongTerm Monitoring Sensor and Analytical Methods Workshop sponsored by the United States Department of Energy (USDOE) and its Characterization, Monitoring, and Sensors Technology (CMST) Program include moisture content, moisture flux, and moisture potential (USDOE/CMST, 2001). Engineering goals for long-term monitoring sensors include making the sensors easy to understand, install, calibrate, operate, and maintain with a capability to service. Monitoring systems could easily be automated with data transmission via telemetry for remote control and data processing capability. Many sensors that meet short-term needs for barrier performance could be used as springboards for long-term monitoring sensor development. Most costs would be significantly less than the current baseline cost for a deployable system with a replacement cycle every two years (USDOE/CMST, 2001).

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5.5.2.1 Long-Term, Post-Closure Radiation Monitoring Systems (LPRMS) An example of a new monitoring approach is the LPRMS that uses commercially available components in a reliable, low-cost, multipoint system for real-time, long-term, unattended monitoring of closed waste sites. The system measures a wide range of radionuclides and activity levels applicable to a large number of USDOE sites. The LPRMS is designed for gamma detection in subsurface soils. The radiation probe consists of a sealed assembly that contains a butt-coupled, thalliumdoped sodium iodide NaI (TI) scintillator/photomultiplier tube (PMT) and a multi-channel analyzer (MCA). This assembly, termed the nanoprobe, can be dropped into polyvinyl chloride (PVC) casings that are pushed into the soil using cone penetrometer technology (CPT). At the surface, solar-powered remote stations (Figure 5.3) at each measurement location incorporate the system power supply and a cell phone modem to communicate to an off-site host computer, which can be located hundreds or thousands of miles away. A large number of remote stations can each operate independently (Figure 5.4) and, without human intervention, send their daily or weekly results to the host computer for analysis, REMOTE DETECTOR STATION Cell phone modem antenna 824–896 MHz Mast Battery charge controller

System Architecture Solar panel Modem power switch & RS485 to RS232 converter Environmental enclosure Excess nanoprobe cable storage

Cell phone modem Deep cycle battery Enclosure to well cover adapter and gasket 4" Schedule 40 steel protective well cover 2" schedule 80 PVC well casing

Split cable grip

48 to 54"

Land line to host computer

OFF-SITE HOST COMPUTER

Concrete pad

Power & digital Communication Cable

Cell phone communication tower

PVC Pipe (installed using CPT) 1.5" × 6" NaI detector PMT and MCA

Modem

6-17

FIGURE 5.3 Conceptual drawing of installed system (In Situ Remote Sensing and Networks, 1999a).

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Cell phone communication tower

Remote detector stations

Antenna Solar panel Environmental enclosure

PVC Casing

NaI detector and MCA

FIGURE 5.4 Schematic of System Components (In Situ Remote Sensing and Networks, 1999a).

data trending, and alarming. If required, the nanoprobes are easily serviceable through retrieval from the PVC casing for repair or replacement. This system is designed to be capable of monitoring large numbers of permanently installed probes over long-term periods. The above ground location of most of the electronic components and the absence of below ground components that require maintenance minimizes long-term costs. This technology can remain unattended for long time periods while providing automated data generation, analysis, formatting, and reporting from many monitoring locations. Additional advantages are as follows: •

•

Real-time detection of nine typical (within USDOE) radionuclides in the media surrounding the sensor eliminates the long turnaround time encountered with conventional sampling and laboratory analysis. Sensor-based automated data generation, although not currently as sensitive as typical laboratory analysis, reduces the potential for error

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•

from manual sampling, sample tracking, laboratory data generation, analysis, and reporting. Minimal long-term manpower is required to operate the LPRMS when compared with the baseline conventional sampling program.

5.5.2.2 Environmental Systems Management, Analysis, and Reporting (E-SMART™) Network Another example of an intelligent new verification system is the E-SMART network. The E-SMART network installation includes the application of sensors that detect and measure contaminants in groundwater and soil gas as well as physical parameters such as barometric pressure, pH, and temperature. Conventional monitoring systems suffer from limited expandability. The goal of the E-SMART network is to eliminate these incompatibilities by defining an open standard for constructing modular monitoring networks. This vision of compatible environmental sensors, sampling devices, control systems, and data analysis systems is shown in Figure 5.5. The E-SMART network integrates diverse monitoring and control technologies by using a modular, “building block” design approach to allow for flexible system configuration. The network treats each smart device — whether a sensor, sampler, or actuator — as a black box that obeys the standard communication protocols and electrical interfaces for the network. This approach allows multiple vendors to produce different sensors that meet the same functional specification and that can be interchanged without impacting operation. Each E-SMART sensor or actuator contains its own microprocessor brain that provides it with a means of storing calibration, control, status, and quality

E-Smart network Sampler management system

Workstation

Plume

Smart sensors

FIGURE 5.5 E-SMART Vision (In Situ Remote Sensing and Networks, 1999b).

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assurance data. This brain communicates using the network protocol, manages data, and controls operation of the smart device. Because the sensor manufacturer embeds the sensor-specific information within the smart device, the E-SMART user is not required to develop calibration or control programs for specific sensors. 5.5.2.3 Direct Push Technologies Direct push technologies have proven to be effective site characterization and verification tools in recent demonstrations at the USDOE Hanford site (Washington) and U.S. Air Force sites at Harrison Air Force Base (AFB) (Indiana) (closed since 1995), Misawa Air Base (Japan), and Kirtland AFB (New Mexico). CPT has met refusal in some geologies before being advanced to the desired depths at dense nonaqueous phase liquid (DNAPL) sites. A sonic CPT system combines the speed and high penetration capabilities of sonic drilling with the economic, continuous data logging of CPT, thus allowing access through difficult strata. An important application of CPT is to install monitoring points. Percussiondriven probes have been enhanced by integration with a laser-induced fluorescence spectrometer and other sensors, providing a less expensive and more easily deployed system. Successful integration of real-time DNAPL chemical sensing and geophysical instrumentation with horizontal directional drilling technology will allow characterization of DNAPL-contaminated strata without introducing a vertical conduit to underlying formations and other obstacles such as buildings and barrier floors. Direct push technology is an excellent platform for making continuous measurements of contamination: it is useful in pushing sensing systems into the subsurface; for installing monitoring wells and points; and for obtaining gas, water, and soil samples for environmental testing. CPT-associated sensor technologies such as soil strength stain gauges, resistivity, soil moisture, pore pressure, gas chromatography/mass spectrometry (GC/MS), multi-gas and organic vapor monitoring, and laser-induced fluorescence (LIF) (Kram et al., 2001a,b), provide enhanced site characterization, and, while still on-site, can quickly and cost efficiently install monitoring wells. Kram’s group (Kram and Keller, 2004a,b; Kram et al., 2004) has optimized several laser excitation sources for specific carbon ranges using LIF, allowing real-time profiling of petroleum hydrocarbon and some DNAPLs. By including a CPT well installation component during verification, plume delineation efforts can be accomplished within one field mobilization. When compared with conventional approaches, this seamless method of optimizing well placement reduces time and avoids additional data review, permitting, and mobilization/demobilization costs. Recent work by the U.S. Navy (Kram and Keller, 2004a,b; Kram et al., 2004) compares conventional well performance with pre-packed direct-push well installations. If successful, this approach referred to as a Site Characterization and Analysis Penetrometer System (SCAPS) and shown in Figure 5.6 will result in significant verification monitoring cost savings.

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SCAPS-Site characterization and penetration system

Shaw The Shaw Group Inc.

20-ton push truck VEHICLE • Push probe configurations -Sensors -Sampling • Grouting capability • Equipment decontamination • Hazardous environment protection DATA ACQUISITION AND ANALYSIS • Acquisition • Sensors • Analysis • Visualization

FIGURE 5.6 SCAPS.

Data processing space Trailer

Pipe handling space

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5.5.2.4 Nanotechnology Sensors Nanotechnology enables the creation of functional materials, devices, and systems by controlling matter at the atomic and molecular scales to exploit novel properties and phenomena. Most chemical and biological sensors, as well as some physical sensors, depend on interactions occurring at these levels. Potential applications under development include chemical sensors and probe tips. Nanotechnology such as carbon nanotechnology will impact almost every aspect of our lives including fuel cells, portable X-ray machines, extremely lightweight strong fabrics, and artificial muscles. The discovery of carbon nanotubes (CNT) — extremely narrow, hollow cylinders made of carbon atoms — by Sir Harold Kroto (Florida State University Nobel laureate) and his colleagues initiated an entirely new field of chemistry research aimed at understanding the properties of these unusual molecules. The characteristics of and the ability to grow CNTs at specific locations and manipulate them afterward make it likely that the tubes will have considerable impact on electronics and sensors (Smith and Nagel, 2003). High levels of integration made possible by nanotechnology give the sensor the ability to be the device and possibly also the system. Nanotechnology takes the complexity out of the system and puts it into the material. Fluorescence and other means of single molecule detection are being developed. Nanotechnology will enable the design of sensors that are much smaller, less power hungry, and more sensitive than current micro- or macro-sensors. Sensing applications will thus enjoy benefits far beyond those offered by micro-electromechanical systems (MEMS) and other types of micro-sensors. The ability to install hundreds of sensors in a small space allows malfunctioning devices to be ignored in favor of the remaining good ones, thus prolonging a system’s useful lifetime. Examples of current work include development of a miniaturized gas ionization detector that could be used for gas chromatography. Nanotube hydrogen sensors have been incorporated in a wireless sensor network to detect hydrogen concentrations in the atmosphere. In addition, a chemical sensor based on CNT has been developed for gaseous molecules such as nitrogen dioxide (NO2) and ammonia (NH3). Nanotechnology is certain to improve existing sensor applications and be a strong force in developing new ones. Nanoscale materials and devices are beginning to be integrated into real-world systems, and the future looks bright in particular for integrating the wireless smart sensors into hazardous waste barriers and containment systems.

5.5.3 ADVANCED ENVIRONMENTAL MONITORING SYSTEM (AEMS) Toshiba Corporation is providing technical coordination to an international consortium of academic institutions and companies working to develop AEMS, a continuous, automated monitoring of groundwater pollutants. The consortium seeks to bring the know-how of its member organizations to the development and commercialization of a system providing enhanced monitoring and identification

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of pollutants in the groundwater and subsoil below manufacturing facilities, including pharmaceutical, chemical, and food-processing facilities. AEMS is expected to detect and identify leaks of contaminants at the source and in real time to support the very earliest deployment of measures to clean up polluted groundwater and soil. In practical applications, AEMS will comprise an array of on-site biosensor systems installed in wells drilled around a monitored barrier. These wells feed groundwater samples to the systems and provide the means for continuous monitoring of groundwater contamination around the designated area. The biosensor is bio-mimetic and consists of two layers of artificial lipid membranes that are used to evaluate the toxicity of chemicals in the groundwater. The membranes generate specific responses to different types of organic compounds in pollutants, allowing identification of hazardous substances. The sensitivity of the biosensor has been improved to the point where it is capable of detecting hazardous substances, such as trichloroethylene (TCE), in concentrations as low as one part per billion (10–9 or 0.001 milligrams per liter).

5.5.4 A NEW DOE BARRIER DESIGN CODE Under the direction of Dr. Thomas W. Fogwell, Scientific Director at Fluor Hanford, Richland, Washington, a modification of the transport modeling code, STOMP (Subsurface Transport Over Multiple Phases), is in development in support of surface barrier designs. The need for a new code is driven by design requirements for approximately 200 new surface barriers needed to close many of the waste sites on the Hanford Central Plateau. Several different surface barrier designs have been proposed based on a graded approach that fits degree of protection with site risk. There is a clear need to be able to evaluate and compare design alternatives, while considering waste site-specific needs in view of technical, regulatory and economic issues. Because all of the designs cannot be built and evaluated over the appropriate spatial and temporal scales, computational models offer an opportunity to perform side-by-side comparisons over the design life for a range of conditions. The overall objectives of this work are as follows: • •

•

•

•

Extend the plant-soil atmosphere dynamics module to 3-D space. Add capabilities to analyze the effects of dynamic structural and hydraulic properties that may result from deformation. (This will require the addition of algorithms for static and dynamic localized grid refinement.) Calibrate and validate the model using data from Pacific Northwest National Laboratory’s (PNNL) Field Lysimeter Test Facility (FLTF), the prototype Hanford Barrier, and other selected experimental capillary barriers in the western U.S. Perform a sensitivity analysis to determine the influence of key parameters and model discretization on model predictions, and identify the key model parameters. Provide a barrier design tool as well as technical guidance and documentation to support the preconstruction performance evaluation of candidate barriers.

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New code to modify STOMP was completed at the end of fiscal year 2003. The code was calibrated in January and February 2004 and scheduled to be ready for application by October 2005.

5.6 DRIVERS FOR IMPLEMENTATION OF NEW APPROACHES A major issue in verification monitoring technology development is identifying what motivates stakeholders, end users, and regulators to move from state of the practice to state of the art. Such drivers are often a reduction in risk and a reduction in cost. In the realm of subsurface verification, the drivers for change are cost and development of methods that enable the desired end states for remediation sites. Only recently has the USDOE begun to design verification systems that meet or exceed the regulatory requirements for barriers. Most communities still use old state-of-practice barrier verification systems. This chapter discusses subsurface verification and monitoring for several types of barriers: landfill covers, PRBs, and walls and floors. The discussion here begins with landfill covers, which to date are the most common containment barrier in use. But first, the drivers for implementation of new approaches must be explored.

5.6.1 COSTS For the 30 years or more life span of some sites that use covers or other barriers, long-term monitoring costs can be larger than the initial barrier implementation costs. The system approach described in Section 5.4.1 allows several opportunities to affect life-cycle costs of remediation. This first of these opportunities is optimization. Optimization, with its imbedded use of predictive tools, permits (1) the selection of the parameters to measure, (2) the selection of the sensitivities of sensors, (3) the location and timing of monitoring, and (4) the selection of appropriate action criteria. With optimization, the appropriate actions for a given site can be made, and, therefore, a cookiecutter approach need not be followed. The other major cost opportunity in applying state-of-the-art approaches is in situ physical and chemical analysis. In the mid-1990s, the USDOE was spending more than $200 million on chemical analysis to support its environmental management and remediation activities. As an example, the USDOE Savannah River site (Aiken, South Carolina) requires 40,000 groundwater samples a year at $100 to $1,000 per sample for off-site analysis (i.e., a total of $4 million to $40 million per year) (Ho and Lohrstorfer, 2001).

5.6.2 ENABLING DESIRED END STATES Environmental remediation has begun to move toward different end states such as brownfield rather than greenfield use (reapplication of the remediated lands for industrial use), wildlife preserves, or other forms of public/private lands. INEEL led an inter-agency effort to develop the Long-Term Stewardship Science

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and Technology Roadmap (2001) that suggests that remediated sites will be transferred to locations that are minimally staffed with remediation personnel or nonmanned. These sites will be required to be remotely monitor waste movement by relying on in situ sensors.

5.7 COVERS This section discusses some potential deployments of the barrier verification methods mentioned in Section 5.3 that are applicable to covers. This list of deployment methods is not meant to be exhaustive, but represents some of the possible configurations to move from state of the practice to state of the art. The data quality objectives (DQO) of the monitoring systems would need to be clearly identified, and the methods applied would provide a means of monitoring a landfill after closure in lieu of certain groundwater monitoring. In addition to this discussion, two USDOE case histories are portrayed: one in New Mexico and another in Ohio.

5.7.1 MOVING FROM STATE OF THE PRACTICE TO STATE OF THE ART 5.7.1.1 Methods A review of other hazardous waste facilities by Everett and Fogwell (2003) shows that where barrier monitoring is applied below the liner system, the primary method uses basin lysimeters of variable sizes. Basin lysimeters generally have proven regulatory acceptance, reduced cost, ease of installation, and the ability to collect quantifiable results. A typical design would be a basin lysimeter made up of 100-mil high-density polyethylene (HDPE) installed under the bottom sump. The lysimeter can extend 1.52 m beyond the perimeter of the bottom sump and can be designed with an access pipe that allows the removal of any liquid collected. Due to the lateral flow patterns normally generated near capillary barriers and those that exist at the interface between contrasting soil textures, such a basin lysimeter could be expected to detect most leaks in the bottom liner of a landfill. Time-proven technologies like neutron moderation can be considered below the barrier liner systems of cells. As new technologies are developed and old technologies improved, consideration should be given to deploying or improving these new options. Particular reference could be made to emerging volumeintegrating technologies like high-resolution resistivity and cross-borehole ERT. This strategy of being prepared to employ future technologies as they develop could be facilitated by installing access tubing (probably perforated) beneath the bottom liners of new construction, providing a relatively inexpensive method of accommodating new technologies as they become available. Of the new technologies, those giving volumetric information seem to be the most promising. The main advantage of such a tubing network would be that ERT methods could be used to provide a spatial distribution of any detected leakage.

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Even with today’s technologies, horizontally emplaced perforated access tubes could be used for measuring parameters such as soil moisture movement, gamma detection, soil pore water sampling, and soil gas. The perforated tool access tubes should span the entire length of a cell buried in a 1.22- to 1.83-m deep trenches along the bottom of each cell and located in areas of potential liner failure. The multi-purpose, perforated access tubes could use the following types of barrier-monitoring technologies in measuring the above-mentioned parameters: a neutron probe, a sodium iodide gamma detector, and absorbent pads for evaluating soil pore water quality. The value of this monitoring approach is that it represents a cost-effective graded method that would allow spatial monitoring below the landfill in order to locate liner failure positions. Soil moisture alone could be used as a cost-effective sentinel parameter, which could be supported with other parameters if required. Perforated casing below the landfill might permit the collection of soil gas samples and could be used as part of a leakage or performance check of both the barrier liner and the caps. 5.7.1.2 Verification Measurement Systems Vertically emplaced perforated access tubes (open-holed at bottom) can be installed (for measuring soil moisture movement, gamma detection, and for collecting soil pore water samples). The access tubes can extend from the surface, through the barrier closure cover and the waste, but not through the bottom liner. These access tubes can be used for detecting vertical moisture changes throughout the waste, function as an access port for various other types of geophysical tools (e.g., neutron and gamma logging tools), provide access for absorbent pads, and permit access for direct soil sampling through the open hole at the bottom. It is imperative that a good seal be completed around the perimeter of the access tubes to prevent preferential flow between the access tubes and soil material. The following are other sensors that can be used with such a vertical tube system: • •

•

TDR probe monitoring stations for each vertical access casing can be installed for measuring volumetric soil moisture. Heat dissipation probe monitoring stations (co-located with the TDR probes) can be installed on each of the vertical access casings to measure matrix potential, which is the driving force for unsaturated moisture movement. Suction lysimeters in a vertical profile can be installed to collect soil pore water samples for chemical and radiological analysis.

5.7.1.3 Barrier Cap Monitoring At closure, instruments should be installed in the final barrier cover to measure its effectiveness of the cover in restricting moisture movement. There are many potential designs. Some involve instrumentation of just the cap and some schemes involve vertical neutron access tubes installed in the cover and through the waste

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to the bottom of the trench. Therefore, meaningful, post-closure, verification barrier-monitoring data should not be relied upon until a baseline has been established and moisture equilibration has stabilized. Once stabilization has been achieved in the post-closure monitoring system, it is anticipated that much of the groundwater monitoring specific to a facility could be eliminated or reduced in scope. Settlement is an important long-term risk associated with the barrier performance of both the liner and the cap. A system of determining settlement by using either survey stakes, topographic remote sensing, fiber-optic cables, GPR for settlement plates, or visual inspection should be considered. A time-consistent topographic survey of the cap should be generated to identify such items as settlement depressions, erosion features, and vegetative features that may develop over time. This survey can also serve to give early warning to possible (but not certain) future water leaks. The indication of subsidence can trigger monitoring in more localized areas.

5.7.2 CASE HISTORY: MIXED WASTE LANDFILL The mixed waste landfill in Albuquerque, New Mexico, was established in 1959 as a disposal area for low level radioactive and mixed waste generated by research facilities of Sandia National Laboratory. The landfill accepted low level radioactive and mixed waste from March 1959 through December 1988. Approximately 30,480 cubic meters of low level radioactive and mixed waste containing approximately 6300 curies of activity were disposed of in the landfill. For the landfill cover design, Sandia National Laboratory and the state elected to use RCRA Subtitle C facilities regulations as guidance. The goal of the USEPA-recommended design of final covers for RCRA Subtitle C facilities was to minimize the formation of leachate by minimizing the contact of water with waste, minimize further maintenance, and protect human health and the environment considering future use of the site. The USEPA accepts alternative cover designs that consider site-specific conditions, such as climate and the nature of the waste, that meet the intent of the regulations. An alternative cover design consisting of a thick layer of native soil was developed as the closure path for the mixed waste landfill. The design relies on soil thickness and evapo-transpiration to provide long-term performance and stability and is inexpensive to build and maintain because of the availability of suitable soils in the area. The cover meets the intent of RCRA Subtitle C regulations because of the following: • • • • •

Water migration is minimized through the cover. A monolithic soil layer minimizes maintenance. Erosion control measures minimize cover erosion. A “soft” design accommodates subsidence. Permeability of the cover is less than or equal to that of natural subsoils present.

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The proposed mixed waste landfill alternative cover incorporates a redundant infiltration monitoring system that includes both baseline neutron probe access holes and advanced distributed fiber optics. The cover infiltration monitoring system is coupled with a shallow vadose zone monitoring system deployed directly beneath the landfill. The shallow vadose zone monitoring system consists of three neutron probe access holes drilled at 45° to a depth of 43.28 m below ground surface. The close-coupled cover and shallow vadose zone monitoring system, in essence, functions as an early warning system, providing early detection of a potential threat to groundwater, and allows corrective action to be initiated before significant contaminant migration occurs. This redundant monitoring approach was designed to protect groundwater resources and was implemented because of its simplicity, low cost, and long-term viability. The close-coupled monitoring system is monitored closely. The frequency and duration of post-closure monitoring was established in consultation with the state and formally documented in the mixed waste landfill long-term care plan. The cover and vadose zone monitoring system provides infiltration and performance information and early detection of potential contaminant migration from the landfill, as well as establishing background and trend analysis information. The close-coupled cover and shallow vadose zone monitoring system is a simple yet robust system designed to meet the intent of long-term RCRA and USDOE performance requirements: reducing labor-intensive, long-term groundwater monitoring and allowing substantial cost savings. 5.7.2.1 Cover Infiltration Monitoring The landfill alternative cover will contain six vertical neutron probe access holes, two in each of the original disposal areas. Each access hole will extend through the cover and an additional 2 ft into original landfill soils. Aluminum casings will be installed after cover construction is complete by hand auguring 6.25-cmdiameter boreholes through the cover and driving the aluminum casing to proper depth. Each casing will be fitted with a perforated, tapered drive-tip. A 0.3 m by 0.3 m concrete pad will be placed at the collar of each casing to prevent preferential flow down the annulus. The cover will also contain a distributed fiber optics infiltration monitoring system that will be deployed in two lifts. The lowermost deployment will be on the prepared sub-grade surface. The uppermost deployment will be 0.45 m above the prepared sub-grade surface between the third and fourth native soil lifts. The uppermost fiber-optic grid will be transposed 90° from the lower grid to maximize spatial resolution and increase monitoring efficiency. 5.7.2.2 Neutron Moisture Monitoring The neutron moisture probe is increasingly being applied to address characterization and infiltration issues at environmental sites undergoing long-term care. Neutron moisture monitoring has become the industry standard for soil moisture measurement, and its operation and data interpretation is well established. The

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principal advantages of this technique are repeatability, precision, and long-term viability. Nothing is permanently installed downhole, which allows for periodic calibration of the neutron probe. Practical considerations and knowledge of vadose zone hydrologic processes guide the number and location of neutron probe access holes. 5.7.2.3 Fiber Optics Distributed Temperature Moisture Monitoring The distributed fiber-optic infiltration monitoring system proposed for the cover is based on the observation that a change in soil-water content causes a corresponding change in soil thermal conductivity. When constant power is dissipated from a line heat source (in this implementation, an electrically conducting wire bundled with the optic fiber), the temperature increase near the heat source depends on the thermal conductivity of the surrounding medium. As soil-water content increases so does its thermal conductivity. The temperature increase as measured by the fiber optic will be reduced because of the conduction of the thermal energy away from the heat source. Measurement accuracy is ±1°C with a resolution of approximately 1 m over the entire length of the cable. The optical fiber and line heat sources are bundled in a hermetically sealed stainless-steel cable that is 0.6 cm in diameter. An important advantage of fiber-optic sensors is their ability to provide passive sensing of a wide variety of physical parameters. This not only means that the sensor operates without the need for electrical power, but the overall system (including the input-output fibers that serve as the telemetry links) is also electrically passive, and, thus, the entire system exhibits low intrinsic susceptibility to the effects of electro-magnetic interference. Experience to date in environmental monitoring indicates that electrically based sensors are extremely susceptible to electrical storms, particularly in the semi-arid and arid west and southwest. Therefore, issues of electrical passivity are of paramount importance when a sensor is required for long-term monitoring and performance in an electrically noisy environment. 5.7.2.4 Shallow Vadose Zone Moisture Monitoring Three angled, 11.4-cm outside diameter, 0.5-cm inside diameter access holes will be installed in the shallow vadose zone directly beneath the mixed waste landfill: two to the west and one to the east of the cover. The vadose zone access holes will be spaced at equal increments: the east access hole bisecting the two west access holes. The access holes will be installed under separate contract using resonant sonic drilling. Resonant sonic is the preferred drilling technique because it literally fluidizes and displaces the surrounding soil as the drill string advances, creating a very tight fit between the drill string and the formation. No cuttings are generated, and no fluids are used to advance the drill string. Background values for the soil volumetric moisture content will be measured during installation

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of the neutron probe access holes. Each access hole will be collared approximately 3 m outside of the toe of the cover side slopes. Each access hole will be drilled 60 m at 45˚ to a true vertical depth of 42 m. As each access hole is completed at 60 m, the 11.4-cm sonic drill string will be left in place down-hole and unscrewed at the surface leaving about 0.6 m of stickup. Each sonic drill string will remain open to the vadose zone. A protective cover constructed of steel pipe will extend 0.6 m below grade and 0.9 m above grade. Each protective cover will be fitted with locking caps and secured with locks.

5.7.3 CASE HISTORY: FERNALD ON-SITE DISPOSAL FACILITY The Fernald Environmental Management Project (FEMP), located 29 miles northwest of Cincinnati, Ohio, is constructing an aboveground on-site disposal facility (OSDF) that is used to isolate low level radioactive waste generated by plant remediation activities. The disposal facility design allows for the construction of nine cells filled with a total of 1.9 million m3 of low-level radioactive soil and construction debris from cleanup activities at the site. The disposal cells are designed to remain stable for 1000 years to the extent reasonable and, in any case, no less than 200 years. Each of the OSDF cells has a bottom liner system, including a leachate collection system that is approximately 1.52 m thick. It is composed of multiple layers of clay and gravel (Figure 5.7) and a geosynthetic liner that is designed to protect the underlying Great Miami Aquifer. The cap of each cell is a multicomponent cover approximately 2.68 m thick with components to limit water Erosion mat 0.15 m

Top soil

0.53 m

Vegetative soil layer

0.15 m

Granular filter

Biointrusion barrier

0.91 m 2.65 m 0.30 m

Cover drainage layer

0.61 m

Compacted clay cap

Protective layer 0.30 m 0.30 m

0.30 m 1.81 m

Vegetation (typ)

Leachate collection system (LCS) drainage layer

Geotextile cushion Geomembrane cap (60-ml) Geosynthetic clay cap Geotextile filter Geotextile cushion Primary geomembrane liner (80-ml) Primary Geosynthetic clay liner

Leak detection system (LDS) drainage layer

0.91 m

Compacted clay liner

Subgrade

FIGURE 5.7 Multiple-layer system.

Geotextile cushion Secondary geomembrane liner (80-ml) Secondary Geosynthetic clay liner

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infiltration (geomembrane) and biointrusion (cobblestones) (Kumthekar et al., 2002). As of September 2003, Cell 1 was filled and capped with the monitoring system in place; Cell 2 was filled with capping planned for 2003; and Cells 3, 4, and 5 were partially filled. The objective was to create a monitoring system that generates data on the physical conditions of the cell cover. This objective was selected because engineering experience with final covers incorporating composite barriers indicates that physical stability is the most important factor affecting long-term performance. The following five critical monitoring parameters were established based on the functional requirements and design criteria of the OSDF: 1. Pore water pressure in the drainage layer — Buildup of water pressure in the drainage layer must be kept below a critical value to maintain physical stability. 2. Total and differential settlement — Settlement must be kept at a minimum so as not to impact barrier performance, hydraulic gradients, and the free flow of moisture throughout the drainage layer. Distortions must be limited to less than 10%. 3. Soil-water content and soil-water potential — These elements are critical to the health of the root zone within the vegetative layer, which protects all other layers and must remain in place for other layers to retain effectiveness. 4. Soil temperature above barrier layer — To function properly, the barrier system must not freeze. 5. Overall condition of cover — This parameter includes institutional controls such as maintenance of signage within the buffer area, as well as ecological controls such as the monitoring of biotic intrusion throughout the cover system. Erosion must be prevented through the maintenance of a healthy vegetative layer, which in turn ensures that the biointrusion layer remains functional. A monitoring system was designed to monitor these critical parameters as well as the following four criteria to maintain the OSDF for at least 200 years (Table 5.3): (1) long-term performance, (2) availability for deployment in near term (within 12 months), (3) remote access and control, and (4) capability to integrate into a data management system. It was also essential to develop a system that was easily accessible for equipment maintenance and technology updates as new cells are built and filled. The monitoring system for Cell 1 was installed to address these criteria. Sensors were installed in a series of nests at the most appropriate area to monitor barrier stability. There are 10 soil-water status nests that measure soil-water content and potential, seven pressure transducer risers that monitor pore water pressure in the drainage layer, seven settlement plates and rods, and eight sets of GPR that monitor total and differential settlement (Figure 5.8). There are three water status nests on each of the west, east, and northern slopes of Cell 1 and one at

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TABLE 5.3 Critical Parameters and Selected Monitoring Technologies in the OSDF Final Cover System Component

Parameter Monitored

Drainage layer

Pore water pressure in drainage layer Settlement (total and differential)

Submersible pressure transducers

Soil water content, soil water potential Soil temperature above barrier layer Overall condition of cover

Dielectric water content sensors, thermal dissipation potential sensors Thermocouples

Surface and internal cover grades, barrier layer (distortion) Status of root zone Barrier layer (freezing) Cover system and buffer area

Monitoring Technology

Topographic survey using settlement plates and rods, GPR targets

Routine topographic survey Web cam Visual and/or remote sensing

Source: Kumthekar, U. et al. (2002). Spectrum 2002: International Conference on Nuclear and Hazardous Waste Management.

Pressure Transducer GPR plate

Soil water status nest Settlement plate

Cover perimeter

C

N

Cabling Fiber optic

615 620

630 640

Cell 1

645 650 Southern extent of final cover system construction

605 610 615 620 625 630 635 640 645 650 655 660 665

670

670

665

660 655 650 645 640 635 630 625 620 610

FIGURE 5.8 Layout of instrument nest on the final cover for Cell 1.

the top of the cell to observe conditions at the highest point and the shallowest slope. Each soil-water status nest has four content reflectometers and four soilwater potential probes equally spaced in the vegetative layer (Figure 5.8) (Kumthekar et al., 2002). Seven pressure transducer risers were installed along

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areas of Cell 1 where the slopes are the longest and pore water pressures are the highest: one on top of the cell and two each down the northwest slope, north slope, and northeast slope. Along each slope, one of two transducers was placed near a drainage layer where high pore pressure could be expected if the layer became obstructed. Transducers were placed at the top and middle of the slope to monitor the distribution of pressure along the slopes. Each transducer allows unimpeded flow of water through the riser and is constructed with schedule PVC pipe to prevent damage and aid in the longevity of the riser. Geotextile is used along the riser pipe to prevent plugging of the pipe, movement of barrier materials between layers, and material from entering the well. The geotextile also serves as a cushion to prevent any damage to the geomembrane below it. The settlement plates and rods were installed alongside of the pressure transducer risers. Plates were installed on the surface of the drainage layer with the rods extending to the ground surface. The GPR plates were installed on the west and east slopes and two each along the northwest, north, and northeast slopes. A subterranean vault was installed at the top of the cell to house both the data logger and multi-plexers. Within the sealed vault, humidity sensors monitor the atmosphere for changes that could damage the equipment. To allow for easy access and equipment repair with minimal manpower, the vault can be raised without difficulty above ground. The data logger is connected to a radio transmitter via a fiber-optic cable, allowing data to be uploaded to a management system. It is expected that modification to this design will be made to subsequent cells based on lessons learned from the installation and subsequent monitoring of this system.

5.7.4 VERIFICATION NEEDS Verification needs for covers were established at the workshop through the PRB work group and the subsurface verification subgroup and were as follows: (1) water balance (e.g., storage, percolation, soil moisture, flux, flow rates), (2) gases and vapor transport (e.g., methane, oxygen, radon), (3) physical state (e.g., stiffness, cracks), and (4) long-term monitoring trends (i.e., space and time). Wilson et al. (1995) identified additional needs for covers (Table 5.4). The dominant verification need that appears is the verification of the water balance within the cover system. Both the vadose zone science and technology roadmap and the long-term stewardship science and technology roadmap strongly suggest that the components of subsurface verification be incorporated within the remediation design from the onset (INEEL, 2001; USDOE, 2002). This is a full system design. Full system designs interactively incorporate prediction with optimization, sensor placement, and approaches to trend analysis. The case history described in Section 5.4.1 provides an example of moving from the state of the practice to the state of the art with end user and regulatory acceptance. In this example, the monitoring approach was incorporated in the construction design of the cover. The monitoring approach is a combination of

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TABLE 5.4 Data Needs for In Situ Containment and Stabilization of DOE Sites Data Needs

Required Parametersa

I. Process model/understanding II. Boundary conditions III. Design A. Waste characteristics B. Performance standards IV. Regulatory/interagency agreement standards A. Performance standards B. Time period V. Uncertainties/sensitivity of process model parameters A. Understanding of how data can be applied to different scales B. Spatial and temporal heterogeneity 1. Geology 2. Flow/transport system 3. Waste 4. Engineered design VI. Environmental changes A. Climatic B. Pedogenetic C. Human generated including human intrusion D. Analog studies

I. Boundary conditions A. Performance standards (e.g., regulatory, multiparty agreement or design) 1. Soil 2. Water 3. Period of performance (e.g., 30, 100, 1000, 10000 years) II. Material properties A. Bulk density B. Particle density III. Hydrogeologic parameters A. Effective porosity B. Mass water content C. Volumetric water content D. Infiltration capacity E. Saturated hydraulic conductivity F. Soil-water characteristic curves G. Conductivity/pressure head relationship IV. Parameters related to climate A. Rainfall B. Evapo-transpiration C. Temperature V. Chemical parameters of waste, engineered, and natural systems A. Solubilities B. Cation exchange capacity C. Partition coefficients D. Diffusion coefficients E. Biodegradation rates F. Chemical degradation rates G. Radioactive decay rates H. Organic matter content

a

Modified from Wilson, L.G. et al. (1995). Handbook of Vadose Zone Characterization and Monitoring, Lewis, Boca Raton.

tradition neutron probes and new applications of distributed fiber-optic sensors. Both approaches are aimed at measuring the water balance within the cover. 5.7.4.1 Optimization and Trend Analysis Site closures involving residual contamination and engineered remediation systems such as covers require monitoring relevant pathways to protect human health

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and the environment and to ensure that remediation systems are operating properly. Uncertainties in conceptual models, key parameters controlling important fluxes, and forcing functions require a statistically-based monitoring network characterized by the zone of influence (support) of the sensors/sampling device, the spacing between sensors, and the extent of the domain/site that needs to be monitored. Initial applications will use tools for each pathway, air, surface, and subsurface, because models and approaches that consider coupled systems are currently limited. However, as research proceeds, a coordinated monitoring approach can be built. Tools that optimize monitoring systems will lead to a 50% cost reduction and decrease uncertainty by a factor of five over systems based on judgment or regular grid systems. An optimized monitoring system will allow risks and the uncertainty associated with risks to be assessed more accurately at all remediation sites. Over the life of a remediation project, monitoring costs can be substantial and can even exceed the costs of the remediation system. The capability to reduce monitoring while retaining the critical information for either the site or the engineered barrier will lead to enhanced efficiency. 5.7.4.2 Sensors and Other Hardware Water balance is the critical verification need for covers. The technical baseline for subsurface sensors utilized for this need was described by Scanlon et al. (1997). Further information regarding the sensor types that can be used is provided in Tables 5.5–5.8.

TABLE 5.5 Toolbox: Water Balance Approach Unconfined groundwater balance

Moisture profile for specific yield

Description

Application

Remarks

A water budget requires quantification of all aspects of hydrologic systems that add or remove water from the component of interest. The water balance equation can be solved for any individual component The initial level of shallow well is measured and the moisture content is determined in intervals of 0.1 m in the capillary fringe above the water table

Advantage: Useful at early stage of site characterization Disadvantage: Field measurements are time consuming

Prediction of response of near surface groundwater levels to other parameters of the hydrologic cycle

Advantage: Useful for sites that want to avoid pump test that bring contaminants to surface Disadvantage: Shallow aquifers

Measure specific yield

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TABLE 5.6 Toolbox: Baseline In Situ Chemical Sensors Sensor

Description

Application

Remarks

Dissolved oxygen, Eh and pH probes Ion-selective electrodes

Various probes are available that measure dissolved oxygen, Eh, and pH in borehole fluids

Advantage: Undisturbed real-time measurements

Detect a contaminant plume

Electrodes are designed to detect the presence of specific ions using a reference electrode

Detect the presence of specific ions

Fiber-optic chemical sensors (FOCs)

A variety of chemical sensors using fiber-optic technology are in development stages; FOCS are made of a reagent phase which is physically confined or chemically immobilized at the end of the optical fiber; the reagent phase contains a chemical or immunochemical indicator that changes its optical properties, usually absorbance or fluorescence, when it interacts with the analyte; the fiber-optic cable is attached to a spectrophotometer or fluorimeter which contains a light source and a detector; an excitation signal from the light source is transmitted down the cable to the FOCS and the sensor fluoresces and provides a constant intensity light source that is transmitted back up the cable and detected as a return signal

Advantage: Real time monitoring of contaminants Disadvantage: Calibration Advantage: Selective real-time measurement, eliminate chain of custody Disadvantage: Equipment not readily available

Detect presence of specific organic compounds in water and vapor phase Solid fibers: BTEX, DCE, TCE, carbon tetrachloride, chloroform, JP-5, gasoline Porous fibers: Humidity, pH, ammonia, ethylene, CO, hydrazine, and BTX

5.8 PRBS Since the 1995 International Containment Technology Workshop sponsored by DuPont, the USEPA, and the USDOE, the interest in PRB technology has greatly increased, along with the number of sites where this technology is the selected remediation method (USEPA, 2002). The use of PRBs to remediate halogenated hydrocarbons (Gillham and O’Hanneisin, 1994) and metals (Morrison et al., 2002)

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TABLE 5.7 Toolbox: In Situ Chemical Sensor Examples (DOE/CMST) Technology Microcantilever sensors

Electrochemical sensors

Description Microcantilevers are micro electro-mechanical devices (MEMS); hence, they are small, simple, rugged, and inexpensive; in this application the micro-machined cantilevers have an absorbent coating that changes the bending, frequency, Q-factor, and amplitude response of the cantilever as the targeted species is absorbed or desorbed. Such devices consist of a transduction element covered with a biological or chemical recognition layer; the analytical information is derived from the electrical signal that results from the interaction of the target analyte and the recognition layer.

Chemiresistors

Similar to above

Chemical fiberoptic sensor

Resonance-enhanced multi-photon ionization

Application Physical Chemical Radiological In air or in solution Oak Ridge National Laboratory

Real-time reliable chemical composition on the environment surrounding the sensors Organics Nitrates Metals Pesticides Radioactive materials New Mexico State University (J. Wang) Sandia National Laboratories (Ho and Lohrstorfer) Volatile organic hydrocarbons Lawrence Livermore National Laboratory (F.P. Milanvich)

has been demonstrated. Approximately 60% of the PRB applications to date are treating halogenated hydrocarbons and 20% are treating metals (USEPA, 2002). The background and description of PRBs are discussed in more depth in the book that resulted from the 1995 International Containment Technology Workshop (Rumer and Mitchell, 1995). The USEPA defines a PRB as “an emplacement of reactive materials in the subsurface designed to intercept a contaminant plume, provide a preferential flow path through the reactive media, and transform the contaminant(s) into environmentally acceptable forms (Figure 5.9) to attain remediation concentration goals at points of compliance (USEPA, 1997).” The major implemented designs of PRBs are funnel and gate, continuous trench, and reactor vessels. New designs include deeper injection of reactive propants into fractures that are either natural or induced or into porous formations (Marcus and Bond, 1999).

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TABLE 5.8 Toolbox: Groundwater Monitoring Groundwater Tracers Unconfined groundwater balance

Moisture profile for specific yield

Description

Application

Remarks

A water budget requires quantification of all aspects of hydrologic systems that add or remove water from the component of interest. The water balance equation can be solved for any individual component The initial level of shallow well is measured and the moisture content is determined in intervals of 0.1 m in the capillary fringe above the water table

Advantage: Useful at early stage of site characterization Disadvantage: Field measurements are time consuming

Predict response of near-surface groundwater levels to other parameters of the hydrologic cycle

Advantage: Useful for sites that want to avoid pump tests that bring contaminants to surface Disadvantage: Shallow aquifers

Measure specific yield

Waste

Water table Plume

Treated water

Groundwater flow PRB

FIGURE 5.9 Typical configuration of a PRB showing the source zone, plume of contamination, treatment zone, and plume of treated groundwater. (Reprinted with permission from Powell and Associates.)

Various reactive materials such as zero-valent iron, copper wool, limestone, carbon, and phosphate are used in PRBs. Zero-valent iron and mixtures of iron with other materials such as sand, gravel, or wood chips accounts for 75% of the applications of PRBs globally (USEPA, 2002).

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With the increased applications of PRBs since the mid-1990s, the database of case histories has been established and is constantly expanded. These databases are also increasingly available to the public. An example is the Internet site (http://www.rtdf.org/public/permbarr/prbsumms/default.cfm) maintained by the private–public partnership called the Remediation Technology Development Forum (RTDF). From these case histories, the following basic goals are defined for subsurface verification [United States Corps of Engineers (USACE), 1997]. • • •

•

Assurance that the contaminant plume is being adequately captured and treated Assurance that the barrier meets design goals (e.g., permeability, residence time, reactivity) Estimation of the longevity of the barrier performance (e.g., reaction completeness, hydrologic flow maintained, availability of reactive materials) Assurance that the PRB does not have downgradient adverse effects on groundwater quality

5.8.1 REGULATORY FRAMEWORK The current state of the practice for subsurface verification is described as guidelines by the USACE (1997) and USEPA (1997), and as case studies (Puls et al., 1999a). Such guidance and case histories stress the importance of initially characterizing the contaminant transport system and the groundwater chemistry as the critical framework for verification monitoring. The USACE, for example, states that the design of a PRB and its verification relies on the initial characterization of the groundwater flow system, organic composition of the groundwater, and the inorganic composition of the groundwater (USACE, 1997). The USEPA (1997) suggested similar guidelines with the goals to detect: • • • • •

Loss of reactivity Decrease in permeability Decrease in reaction zone residence time Short-circuiting of the reactive zone Funnel wall leakage

In USEPA guidance, the following compliance monitoring parameters exist: • • •

Contaminant(s) of interest Potential contaminant daughter (degradation) products General water quality parameters (including hydrologic parameters, both baseline and over time; precipitates on iron surfaces; Eh; dissolved oxygen; and ferrous iron)

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USEPA guidance relies on monitoring wells to determine whether regulatory goals are being achieved, contaminant breakthrough occurs, and contaminant flow around the barrier occurs. According to guidance, monitoring well locations should be installed in the following locations: • • • • • •

Upgradient of the barrier Within the reactive zone of the barrier Immediately downgradient of the reactive zone discharge At each end of the of the barrier Below the barrier Above the reactive zone (if possible)

Similar to the USEPA, the USACE (1997) monitoring and verification strategy guidance uses groundwater analysis from monitoring wells. Specifically, the USACE guidance has the following goals: • •

Verify plume capture by the PRB through groundwater analysis from monitoring wells and tracer tests (e.g., sodium bromide). Verify longevity of the PRB through geochemical monitoring of a sample obtained from monitoring wells and through sample analysis from a sample cored from holes into the reactive material of the barrier. • Enable baseline technologies by analyzing volatile organic compounds (VOCs) in the laboratory using GC/MS. • Perform metals, anions, and total organic carbon laboratory analysis. • Obtain water level, pH, Eh, temperature, and dissolved oxygen measurements using in-hole probes. • Measure specific conductance, turbidity, and salinity with field instruments.

5.8.2 MOVING FROM STATE OF THE ART

OF THE

PRACTICE

TO

STATE

The state of the practice for PRBs is in the infant stage. Some field applications have been very successful but an understanding of the chemical behavior of the PRBs remains in development. Excellent progress has been made in developing an understanding of barrier materials. 5.8.2.1 Flow Characterization and Monitoring Tracer technology is the preferred method for flow characterization and monitoring. Borehole flow meters are in disfavor because different types give contradictory results. Without clarification of the reasons for the discrepancies, the end users do not feel that the use of the borehole flow meters can be justified. Tracer technologies for application to PRBs can be selected from Table 5.9.

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TABLE 5.9 Toolbox: Tracers Groundwater Tracers

Description

Application

Ions

Soluble salts are dissolved in water and injected into a well and monitoring wells downgradient are sampled; concentrations of ions are analyzed in the laboratory

Common ions include CaCl2, NaCl, LiCl, NH4Cl

Dyes

Dye is poured on to the ground surface, down a drain, or injected into a well; suspected points of discharge are monitored and visually sampled

Dyes are inexpensive and simple to use; fluorescent or not fluorescent

Gases

Stable isotopes

Radioactive isotopes

Gas tracers can be grouped into three major groups: inert natural, anthropogenic gas, gas isotopes; similar to ions in porous media; gas is injected into the space between the packers in one hole and air pumped out of the area between the packer in the other hole Groundwater samples are collected and analyzed for isotopic composition; the average isotope composition including deuterium and 18O in precipitation reaches the groundwater through infiltration changes with elevation Radioactive isotopes were used in 1950s as tracers in groundwater (Tritium, carbon-14, and radon-222); health concerns have stopped its utilization

Adsorption of dye on subsurface material can be a problem Noble gas-nonreactive, nontoxic, and low natural concentrations Difficult to maintain constant recharge rate, time required to develop equilibrium and loss to atmosphere

Remarks Measure groundwater flow paths and velocity, monitoring sanitary landfill leachate migration, and dilution by receiving waters Identify zones of preferential flow in the vadose zone, speed and direction of flow in karst, and movement, velocity and source of contaminants Detect fracture connectivity in the unsaturated zone

Differentiate between natural and contaminant sources where nitrates, sulfates, and methane present Disadvantage: Lab analysis required, not suitable for injection

Differentiate contaminant derived and naturally occurring chemical constituents in groundwater

Advantage: Normal groundwater sampling, analysis of tritium and radon-222 are simple Disadvantage: Health risk exists

Estimate groundwater age, infiltration and discharging groundwater to surface water

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TABLE 5.9 (continued) Toolbox: Tracers Groundwater Tracers

Description

Application

Water temperature

A pulse of hot water is injected into a well and temperature in one or more observation wells downgradient are measured

Advantage: Simple, inexpensive Disadvantage: Less accurate

Particulates

Selected microbes, typically baker’s yeast or nonpathogenic bacteria, are injected in a well and monitored downgradient at different intervals; a few kilograms of spores can also be utilized; movement of the tracers are monitored downstream

Advantage: Microbes can be used in porous media, high injection concentration, spores pose no health concern Disadvantage: Health concerns with use of viruses, detection

Remarks Measures groundwater travel time between two wells, detects of temperature anomalies associated with radioactive waste or microbial degradation of contaminants Trace velocity, direction flow

5.8.2.2 Verification of Geochemical Gradients and Zones Columns and field conditions, unlike well-mixed batch systems, result in the development of steep chemical gradients within the iron-bearing zone, at the interfaces between the iron bearing zone and the surrounding material, and downgradient where the plume of treated water interacts with the native aquifer material (Tratnyek et al., 2003). Although some early work recognized that these gradients could be significant (Fryar and Schwartz, 1994; Johnson and Tratnyek, 1994; Tratnyek et al., 1995), further characterization of these geochemical gradients is needed at the field scale before their effects on contaminant fate can be accurately assessed. Recently, considerable progress on this topic has occurred through integrated monitoring and modeling studies associated with several field sites, including Moffett Field in Mountain View, California (Gupta et al., 1998; Sass et al., 1998; Yabusaki et al., 2001), the U.S. Coast Guard Support Center in Elizabeth City, North Carolina (Puls et al., 1999b; Blowes and Mayer, 1999; Blowes et al., 1999a,b), and the Y-12 uranium processing plant in Oak Ridge, Tennessee (Gu et al., 2002; Liang et al., 2000).

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Barrier Systems for Environmental Contaminant Containment & Treatment Oxygen

Varies

Carbonate

Varies 0

Nitrate

Varies

0

Sulfate

Varies

Low Low High

Hydrogen

0

pH

Varies

Fe(I)

Low

Contaminated groundwater

8–11 7 Low Treated groundwater

FIGURE 5.10 Schematic of a cross section of an iron PRB showing the major gradients in groundwater geochemistry, zones of precipitation, and expected regions of microbiological influence.

Some of the major geochemical gradients that have been observed associated with iron PRBs are summarized in Figure 5.10 and involve the following: • • • • • •

Dissolved oxygen, which is completely removed within a few millimeters of where groundwater enters the iron bearing zone Dissolved hydrogen, which rises over the width of the iron-bearing zone to near saturation pH and dissolved Fe (II), both of which usually rise rapidly inside the wall and then decline gradually in the downgradient region Dissolved carbon dioxide, which precipitates near the upgradient interface as iron carbonates Nitrite anion (NO3–), which is abiotically reduced to ammonia Sulfate anion (SO42–), which is reduced by anaerobic bacteria to sulfide, much of which then precipitates as iron sulfides (Tratnyek et al., 2003)

Note that lateral diffusion is slow into the plume of treated groundwater, so reoxygenation by this mechanism is expected to be minimal and the anaerobic plume may eventually extend a considerable distance downgradient of the iron PRB. As a consequence of the gradients in groundwater geochemistry described above, zones of authigenic precipitates develop along the flow path of iron PRBs

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329

and columns designed to simulate these conditions (Tratnyek et al., 2003). A considerable amount of research has been conducted on the iron oxides and carbonates that accumulate near the upgradient interface because these solids can cement grains and decrease porosity, thereby preventing contaminated groundwater from flowing through the treatment zone. The effect of these precipitates on overall rates of contaminant reduction is not entirely clear, however, because most field data suggest that contaminant reduction occurs mainly near the upgradient interface, where precipitation of oxide and carbonates might contribute to passive iron surfaces and therefore slower overall rates of corrosion. The zone of precipitation that develops on the native aquifer material beyond the downgradient interface has received comparatively little attention to date (Tratnyek et al., 2003). It is known, however, that most of the dissolved iron that is released by the treatment zone precipitates on the downgradient aquifer material, resulting in the accumulation of Fe(II)-containing oxyhydroxides (and favoring a decrease in pH). These changes minimize undesirable changes in groundwater geochemistry that might be caused by an iron PRB. In addition, the accumulation of highly reactive forms of Fe(II) creates a zone that may result in further contaminant degradation by abiotic and biologically mediated pathways.

5.8.3 CASE HISTORY: SUBSURFACE MONITORING Puls et al. (1999b) describe a specific monitoring program for a former U.S. Coast Guard Support Center in Elizabeth City, North Carolina. At this site, seven rounds of performance monitoring were completed between 1996 and 1998 for a PRB that remediates both chromate and chlorinated solvents. The monitoring and verification approach was described as follows: • •

• •

10 2-cm diameter compliance wells 15 multi-level samplers for TCE, cis-dichloroethylene, vinyl chloride, ethane, acetylene, major anions, metals, Cr(VI), Fe(III), total sulfides, dissolved hydrogen, Eh, and pH, dissolved oxygen, specific conductance, alkalinity, and turbidity Electrical conductance profile with Geoprobe™ to verify emplacement of continuous wall Coring into the barrier to evaluate rate of corrosion and precipitate buildup (vertical and angled 15-cm core into the barrier)

5.8.4 VERIFICATION NEEDS Verification needs for PRBs were established (Table 5.10) and augmented by published monitoring system guidance (USACE, 1997) and in published journal articles. Several high-order verification needs have emerged, all of which focus on the fact that variations in parameters such as flow and biomass are the necessary components to monitor — not merely inflow and outflow.

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TABLE 5.10 Subsurface Verification Needs as Defined at the Baltimore Workshop, July 2002 A. Is the barrier emplaced as designed? B. Does PRB capture plume? a. Capture of flow system — does all flow channel through PRB? b. General consensus — point sensors for flow don’t work. Is there a better way to measure system flow? c. Placement of barrier into impermeable barrier/layer is critical d. Creation of preferential flow during construction C. Effectiveness of the barrier a. Chemical i. Performance assessment: measure daughter products to show system is working; install monitoring well in barrier and horizontal boring across barrier to measure gradients ii. Capacity: defined by modeling iii. Emplacement during construction of barrier, e.g., ERT electrodes can be used for IP measurements iv. Is material in PRB working; how long can it work? v. Sensors that measure chemistry in situ vi. Geochemical indicators that barrier is performing chemically, pH, Eh b. Hydrologic i. Creation of preferential flow during construction ii. Preferential flow into small part of barrier — is treatment adequate? iii. How does flow change through time, clogging, channeling, etc. iv. Conductivity, porosity, precipitation of metals in barrier c. Bio-barriers i. New performance parameters needed ii. New technology to monitor needed

5.8.4.1 Spatial and Temporal Flow Monitoring Considerations Generally, the monitoring data from existing PRB applications show that the installed PRBs are treating the contaminants that flow into the treatment zone. However, the most common observation that compromises the overall PRB treatment system is not capturing the contaminant flow due to overflow, underflow, and side flow. For example, according to the RTDF’s web site, one fifth of the plume is migrating around the barrier and escaping the PRB capture zone at the Copenhagen, Denmark, Freight Yard. Gupta and Fox (1999) noted that the most overlooked factors affecting PRB performance are (1) aquifer heterogeneity (i.e., preferential flow and natural barriers, localized high-flow zones in bounding aquitards for PRB placement, and localized aquifer interconnection), and (2) variations in both the flow velocity and directions of contaminant transport system. For example, at the Borden site (Canadian Forces Base), the shape of the plume and changing flow direction made subsurface verification so difficult that the contaminant concentrations were above the predicted levels and remained

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above the maximum contaminant level (MCL) (USACE, 1997). As a result of such spatial and temporal variability, Eykholt et al. (1999) concluded that the basic deterministic design approach for PRBs was nonconservative for heterogeneous aquifers. 5.8.4.2 Geochemical and Hydrological Process Monitoring Considerations Roh et al. (2000) noted that geochemical and hydrological processes are of high concern in PRBs because these processes have high impact on the reactivity and permeability of the treatment system. For example, Morrison et al. (2002) wrote that the formation of a gas phase and the precipitation of a secondary mineral phase resulted in the loss of hydraulic conductivity of one treatment cell at the Bodo Canyon site in Colorado. The USACE has identified that the monitoring of organic and inorganic composition of the groundwater upgradient of the PRB is important in assessing the potential for loss of hydraulic conductivity (USACE, 1997). Also, construction of the barrier can lead to heterogeneities within the reactive material such as layers with different porosity, which can lead to transverse hydrologic conductivity. Construction also can result in water backflow into the barrier from bounding surface units and in irregular surface topography that can produce heterogeneities in the surface infiltration. 5.8.4.3 Acoustic Wave Devices At present, acoustic wave devices (Figure 5.11) have the highest potential to provide the lowest detection limits for real-time measurements at low cost and

Carbon tetrachloride plume

Monitoring well

Sensor monitoring/ data collection equipment

Acoustic wave traveling across surface of device

Output transducer (detects acoustic wave)

Input transducer (creates acoustic wave) Coating sensitive to carbon tetrachloride

Paws sensor Electronic monitoring equipment

FIGURE 5.11 Acoustic wave sensor (In Situ Remote Sensors and Networks, 1999d).

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Barrier Systems for Environmental Contaminant Containment & Treatment

in portable configuration. Typically an acoustic wave sensor involves the application of a chemically sensitive film onto the surface of the oscillating resonator crystal. Interactions of the film with the analyte induce a change in the mass and viscoelastic properties of the film. This change is measured as the shift of the resonance frequency of the oscillating crystal and is related to the concentration of the analyte. For detection of analytes differing in nature, the coating/analyte interactions can include hydrogen bonding, hydrophobic, π-stacking, acid–base, electrostatic, and size/shape recognition. Selective analyte detection to verify PRBs can be achieved by coating several sensors with different films and analyzing the response pattern in such a sensor array by means of different pattern recognition techniques. In the last decade, federal agency research and development programs have focused on field analytics and sensor technologies that can be applied to hazardous waste site characterization, remediation, and monitoring activities. For example, the USDOE’s Environmental Management Science Program web site currently lists more than 70 research and development projects that address data collection or sample analysis issues. Techniques as diverse as antibody methods, in situ microsensors, spectroelectrochemical sensors, spectrometric DNA diagnostics, dielectrics and nuclear magnetic resonance partitioning tracers, electromagnetic imaging, seismic technologies, acoustic probes, conductive luminescent polymers, cavity ringdown spectroscopy, gamma-ray imaging, optical array sensors, noble gas detectors, and BioCOM sensors are mentioned. Likewise, the U.S. Department of Defense (USDOD) Strategic Environmental Research and Development Program has funded more than 20 research and development activities on its sites focused on characterization and monitoring technologies. Researchers with the U.S. Navy Space and Warfare Systems Command (SPAWAR) have focused specifically on technologies applicable to the more specialized needs of sediment covers (Table 5.11) that are applicable to other barriers as well.

5.9 WALLS AND FLOORS The basic functionality of a floor or wall is to prevent migration of contaminants by providing a physical barrier to their transport. If the physical barrier is compromised either locally or globally by a hole, breach, or flaw, then the ability of that barrier to successfully contain the contaminants can be diminished beyond acceptable levels. It is difficult to obtain stakeholder acceptance of barrier technologies if the integrity and performance capabilities of the installed barrier cannot be proven and the long-term stability cannot be monitored. The requirements for monitoring walls and floors are divided between the vadose zone and the saturated zone, with each equally critical because failures often occur at the junction of the walls and floors regardless of location. Integration of the sensors into the barrier during the design of the system is now practical. Some of the sensor monitoring requirements are as follows:

and PCB (ex E A E A E A E A E A E A E A E A E A E A F A A B

situ analysis) B C B B C A C C B A A A B B B B B B A B B A A A A A A A B A A B A C B A

A A A B A A B C C B A B

Analytea VOC, SVOC, TPH 1, 3 E 1-–3 E 1 E 1-–6, 11 E 1,3 E 1,3 E 1-–6 E 1-–6 E 1-–6 E 1-–6 E 1-–4, 6 E 1, 3, 5 B

Soil/Sediment

Photoionization detector Flame-ionization detector Explosimeter Gas chromatography (GC) plus detector Catalytic surface oxidation Detector tubes Mass spectrometry (MS) GC/MS GC/ion trap MS Ion trap MS Ion mobility spectrometer Ultraviolet (UV) fluorescence

Water

A A

Gas/Air

VOC, SVOC, TPH and PCB (in situ analysis) 11 E A B B A B 5, 11 B A NA B B B

Selectivity

Solid/porous fiber-optic Laser-induced fluorescence

Technique

Detection Limits

Performance

Application

C C C A C C A A A A A B

A B

III III III III III III II III II II II II

I III

A A A B A A C C C C B B

A A

A A A A A A B A A A A A

A A

C C C A B C A A A A B B

B B

A A A A A A A A A A A A

A A

C C C A A C B B B A B A

B B

Turnaround Time per Sample Quantitative Data Capability Technology Status Relative Cost per Analysis Screen/ Identity Characterize/ Quantity Cleanup Performance Long-Term Monitoring

Media Susceptibility to Interference

Table 5.11 Summary of Sensor and Field Analytical Techniques (National Research Council, 2003)

Subsurface Barrier Verification 333

Synchronous luminescence/fluorescence UV-Visible spectrophotometry Infrared spectroscopy Fourier transform infrared (FTIR) spectroscopy Scattering/absorption LIDAR Raman spectroscopy/surface enhanced Raman scattering (SERS) Near IR reflectance/transmittance spectroscopy Immunoassay colorimetric kits Amperometric and galvanic cell sensor Semiconductor sensors Piezoelectric sensors Field bioassessment Toxicity test Room-temperature phosphorimetry

Technique

A A E F F A A B

1, 3 1-–6, 11 1, 3 1, 3 1, 3 1-–6 1-–6 4, 5, 6, 12 (PCBs)

Analytea

E E E E E E

Soil/Sediment

1-–4 1, 3, 5 1-–4 1, 3, 11 1, 3 1-–5, 11

Water NA A NA A E A A A

A A E E E A

Gas/Air NA NA A A A A A B

B B A A A E

Selectivity C B A B A C C A

B C B A C C C B B B C C C C

B C C B C C C B A A A NA NA A

A A B A C A

Detection Limits

Performance

Application

A A A A A C B B

B A A A A A

B B B B B C B B

B B B B B B

I II II I I II II I

I I II II I II

B A A A A C A B

B B B B B B

A A A A A A A A

A A A A A A

B B B B B A A B

B B B B B B

A A A A A C C A

A A A A A A

A B A A A B A A

A A A A A A

Turnaround Time per Sample Quantitative Data Capability Technology Status Relative Cost per Analysis Screen/ Identity Characterize/ Quantity Cleanup Performance Long-Term Monitoring

Media Susceptibility to Interference

TABLE 5.11 (continued) Summary of Sensor and Field Analytical Techniques (National Research Council, 2003)

334 Barrier Systems for Environmental Contaminant Containment & Treatment

7 7 7 7, 7, 7, 7 7, 7 7, 7, 7

10 10 10 10 10 10 10 10

Atomic absorption (AA) spectroscopy Inductively coupled plasma-atomic emission spectroscopy (ICP-AES) X-ray fluorescence Chemical colorimetric kits Titrimetry kits Immunoassay colorimetric kits Anodic stripping voltametry Fluorescence spectrophotometry Amperometric and galvanic cell sensor Field bioassessment Toxicity tests Ion chromatography

Gas chromatography (GC) plus detector Mass spectrometry GC/MS Ion mobility spectrometer Field bioassessment Toxicity tests Chemical colorimetric kits Immunoassay colorimetric kits

9 9

12 (Hg)

9 9 12 (Hg)

2, 4, 5, 11 11 11 2

Chemical colorimetric kits Free product sensors Ground penetration radar Thin-layer chromatography

A A A A A E A A A A

F NA NA NA NA A NA A A NA

A A A B A A A C C B

Explosives (ex situ analysis) E E B A E E B B E L A A E E A A A A A C A A A C E A NA B E A NA B

A B B A E E E A A E

A C A C C C B B

A B B B B B B C C B

A A

Metals (ex situ analysis) E E A A E E A A

NA NA NA NA

B A C B

A A C A

B C C B

B NA B E

B B B A NA NA B B

B B B A A A B NA NA A

A A

B C C A

B A B B C A A A

A B B A A A A C B A

C B

A A C B

A A A A C B B B

A B B B A A B C B A

A A

B C B A

II II II I II II III III

III II III II II II II II II I

I I

II III I II

C C C C C A A A

A A A A B B A C A B

C C

A A B C

B B B A A A A A

A A A A B A A A A A

C C

A A B A

B B B C A A B B

B B B B A A B A A A

A A

B A A A

B B B C C A B B

A A A A A A A C C A

C C

A A B A

B B B C B A A A

B A A A B A A B A A

B B

A A B A

Subsurface Barrier Verification 335

Relative cost per analysis

Technology status

B B

B B

B E B

Hours Data is quantitative with additional effort

Medium Midrange: 10–100 ppm (soil); 0.5–10 ppm (water)

Adequate Requires selection of extraction procedure Measures the contaminant indirectly

Commercially available and routinely used field technology Commercially available technology with moderate field experience Commercially available technology with limited field experience Least expensive B Mid-range expensive

Better Not applicable Measures the specific contaminant directly Low Low: 100–1000 ppb (soil); 1–50 ppb (water) Not applicable Minutes Produces Quantitative Data

C

C C

C C

C

C

Most expensive

More than a day Does not produce Quantitative data

Measures a part of the compound High High: 500+ ppm (soil); 100+ ppm (water)

Serviceable

Analytes: 1, nonhalogenated volatile organics; 2, nonhalogenated semivolatile organics; 3, halogenated volatile organics; 4, halogenated semivolatile organics; 5, polynuclear aromatic hydrocarbons (PAHs); 6, pesticides/herbicides; 7, metals; 8, radionuclides; 9, other inorganics (asbestos, cyanide, fluorine); 10, explosives; 11, total petroleum hydrocarbons; 12, specific analyte (named in matrix).

a

NA A A

Turnaround time per sample Quantitative data capability III II I A

A A

Susceptibility to interference Detection limits

Selectivity

A NA A

Media and/or applicable to

Legend

TABLE 5.11 (continued) Summary of Sensor and Field Analytical Techniques (National Research Council, 2003)

336 Barrier Systems for Environmental Contaminant Containment & Treatment

Subsurface Barrier Verification

• • • • • • • • • • •

337

Flux through walls Continuity and uniformity (thickness, depth, wall/floor connection) Total flow of contaminant Joints (contaminants, moisture, pH, flow, temperature, conductivity) Slurry wall drawdown Sheet pile grout (pH, temperature, flow, conductivity, moisture) Upstream vs. downstream verification System for leachate collection Sensors for vadose and saturated zones Changes in subsurface over time Subsidence of walls and floors

The fact that barriers and/or waste from materials are so vastly different than the surrounding soils yields high signal to noise ratios for geophysical techniques. As a whole, geophysical methods are good for determining gross field changes and estimating boundaries. Most contaminant transport pathways (e.g., holes, cracks, thins) are missed by geophysics and may be better searched for by other techniques such as gaseous tracers. Although tracers are best suited for determining pathways, it is difficult if not impossible to determine variables such as wall thickness to fractions of a foot, special placement of the entire barrier (determining an as-built blueprint), density, or soil moisture using tracers. It is follows that a suite of verification/monitoring technologies will be required to meet stakeholders’ needs.

5.9.1 MOVING FROM STATE OF THE ART

OF THE

PRACTICE

TO

STATE

Clearly, technologies are required that can verify the integrity and performance of newly installed walls and floors and that can be used to monitor the integrity and performance of those barriers for the expected service life of the containment system. Preferably, those technologies will be predictive in nature so as to forecast/detect early or impending failure (as defined by contaminant release beyond the containment boundary). 5.9.1.1 Neutron Well Logging Currently, neutron well logging has become an important tool for estimating porosity and moisture content of a formation. Neutron logging is used to measure the hydrogen index, Ih, which is defined as the equivalent volume fraction of fresh water containing the equivalent amount of hydrogen. Neutrons generally interact with atomic nuclei and therefore interactions are less frequent and neutron ranges are longer than other nuclear radiation. The most common neutron interaction is elastic scattering. Classical mechanics show that the neutron is moderated more efficiently by nuclei with a mass similar to the neutron, such as hydrogen and other low mass elements. There are two types of neutron sources, chemical and

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Barrier Systems for Environmental Contaminant Containment & Treatment

accelerator. Both sources produce fast neutrons, and the logging type is usually distinguished by the detector type, either thermal or epithermal. Chemical sources produce neutrons with an energy of about 4 millivolt equivalents (MeV). Accelerators produce neutrons with an energy of about 14 MeV. Chemical sources have the advantage of being cheap and reliable, while accelerators have the advantage of being able to turn off the neutron source. There are two common methods of measuring water content using neutron diffusion: the neutron log and the moisture gauge. An extended comparison of the two methods can be found in Hearst and Carlson (1994). Moisture gauges are sensitive to thermal neutrons and have an affected radius of 10 to 20 cm. Neutron logs measure thermal or epithermal neutrons depending on sonde configuration and have a measurement radius of 20 to 30 cm. Thermal neutron methods are used in fluid-filled boreholes and are of little value in air-filled boreholes. Epithermal methods are preferred for air-filled boreholes and can also be used in fluid- or foam-filled boreholes. Neutron methods depend on many different parameters such as porosity, matrix, pore fluid, salinity, temperature, pressure, standoff, and borehole geometry. A complete mathematical solution incorporating all of these parameters is not feasible; therefore, numerical approximations are used and are field calibrated. Such approximations do not allow exact pictures of the subsurface but yield statistical equivalents that are averages over the affected range. Neutron logging can be very useful in following soil moisture within the contained area. Longterm calibration standards are recommended for barrier applications. 5.9.1.2 Perfluorocarbon Tracer (PFT) Monitoring/Verification Brookhaven National Laboratory has developed rapid and sensitive analytical methods for a host of PFTs. These tracers were originally used in atmospheric and oceanographic studies and have since been applied to a great variety of problems, including detecting leaks in buried natural gas pipelines and locating radon ingress pathways in residential basements. Leaks/flaws are located by injecting a series of tracers on one side of a barrier wall and then monitoring for those tracers on the other side (Figure 5.12). The injection and monitoring of the tracers is accomplished using conventional low cost monitoring methods, such as existing vadose zone monitoring wells or multilevel monitoring ports placed using CPT techniques. The amount, type of tracer (speciation), and arrival times can all be used to characterize the size and location of a fault. It is easy to see that the larger the opening in a barrier the greater the amount of tracer that is transported across the barrier. Locating the breach requires more sophistication in the tracer and/or analysis methodology. Multiple tracer types can be injected at different points along the barrier in both vertical and horizontal directions. Investigation of the spectra of tracers coming through a breach gives information on the location relative to the various tracer injection points. Arrival times of the different tracers can also be measured to obtain a more detailed

Subsurface Barrier Verification

Injection well

339

Extraction well fitted with multiple sampling ports

Perfluorocarbon tracers

Subsurface barrier wall

FIGURE 5.12 Schematic of PFT technology with multiple tracers.

analysis. Having multiple tracers also allows for confirmation of holes and differentiation between holes and spill over. PFT technology consists of the tracers themselves, injection techniques, samplers, and analyzers. PFTs have the following advantages over conventional tracers: •

• •

•

•

Negligible (a few parts per quadrillion) background concentrations of PFTs exist in the environment. Consequently, only small quantities are needed. PFTs are nontoxic, nonreactive, nonflammable, environmentally safe (contains no chlorine), and commercially available. PFT technology is the most sensitive of all nonradioactive tracer technologies and concentrations in the range of parts per quadrillion (1 in 1015) are routinely measured. The PFTs technology is a multi-tracer technology permitting up to six PFTs to be simultaneously deployed, sampled, and analyzed with the same instrumentation, resulting in a lower cost and flexibility in experimental design and data interpretation. All six PFTs can be analyzed in 15 minutes on a laboratory-based GC. Several real-time, portable instruments are available that allow rapid (less than five minutes) analysis of tracers with slightly reduced sensitivity (parts per trillion).

Understanding mass transport through defects in barriers is central to evaluating barrier continuity. The migration of tracers is analyzed using computer codes that predict the transport of the gas tracer through a porous soil and barrier

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Barrier Systems for Environmental Contaminant Containment & Treatment

with defects. Existing computer codes can be adapted as necessary for the problem. PFT technology allows locating and sizing of breaches at depth and has been shown to have a resolution of fractions of an inch. The technology has regulatory acceptance and is used commercially for nonwaste management practices (e.g., detecting leaks in underground power cables). This technology has been used in a variety of soils and is applicable to other USDOE sites as well as commercial waste sites. PFT technology is expected to and has been shown to operate under a variety of conditions. The technology is unaffected by waste type, temperature (within the confines of expected environmental temperatures at waste sites), or pH/Eh. Tracer transport is affected by geologic or physical differences such as soil type, layering, degree of fracturing, or void volume, but all of these are expected variations and are easily accounted for through normalization, modeling, or experimental measurement. The fundamental principal behind the technology operation and, hence, success remains unchanged. Two parameters that can adversely affect PFT measurements are soil moisture and barometric pressure. As soil moisture content increases, the air-filled porosity of the soil decreases and changes the transport rate of the tracers. For subsurface barriers, this change has not been an issue. For the range of soil moisture encountered in deeper soils (greater than 3 m), no significant changes occur in soil moisture over the duration of a test and, therefore, transport rates are unaffected and this parameter can be ignored. For surface barriers, soil moisture issues are a greater concern. Cover systems can be at saturated conditions in the upper layers after a severe rainfall event. This would clog the pore structure and drastically reduce tracer transport. For lesser degrees of saturation, the effect would be a reduction in transport. The relationship of tracer transport rates vs. soil moisture content needs to be determined. Once the relationship is known, it can be accounted for or minimized (e.g., by not testing immediately after a severe precipitation event). Barometric pressure is only important to cover system measurements and only through barometric pumping. Rapid changes in atmospheric pressure can cause pumping of the soil gases to the surface. This phenomenon is limited (in terms of affecting PFTs) to the first 0.9 to 1.35 m of soil and therefore does not affect subsurface barrier measurements. Even with a shallow surface layer (approximately 0.03 m), barometric pumping has not precluded the technology from successful deployment. In this case, the dilution of the tracer due to nearsurface effects was about one order of magnitude and was well within the range of the technology’s sensitivity. A cost estimate and life-cycle assessment need to be developed. The technology developers have spoken with several commercial interests, including an instrument manufacturer to produce and sell or rent PFT instrumentation, a technology vendor to provide complete packages, and service vendors to provide PFT technology to sites on a service contract. While initial interest is high and the instrument vendor is ready to provide units, no formal cost estimate has been performed.

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5.9.2 CASE HISTORY: COLLOIDAL SILICA DEMONSTRATION During the summer of 1997, a subsurface barrier was installed at Brookhaven National Laboratory in Upton, New York. The barrier consisted of a colloidal silica grout that was placed using permeation grouting. Upon gelling, the grout forms an impermeable barrier that can be used to contain subsurface contaminants. The barrier was installed at a clean site. The site was chosen because of the geology (porous sand matrix) and the stated possible need for containment barriers in future remediation efforts. Colloidal silica was injected into the subsurface in an attempt to provide an impermeable barrier for waste isolation. The internal dimensions of the barrier formed an approximately 6 m square with the barrier walls nominally 1.3 m thick. The west wall of the barrier was injected at a 45° angle to the ground surface, and the east wall was installed vertically. This resulted in the north and south walls (installed vertically) having a triangular shape. Injection rods were pushed into the ground, and grout was injected to form a bulb. The rod was withdrawn slightly, and another bulb was injected to overlap the first. This process was continued until a column of grout was injected. A second column was injected next to and overlapping the first. In this manner, a barrier was formed that consisted of a series of overlapping columns. The integrity of the barrier was strongly dependent on the location of the injection rods to provide proper placement and overlap of the grouted sections. The performance of the barrier was dependent on initial integrity, grout performance (e.g., proper gelling, initial permeability reduction), and long-term stability of the grout (e.g., desiccation, seepage away from the injection zone). After installation, the integrity/performance of the barrier was investigated using a suite of nondestructive subsurface investigation techniques, including geophysics, a gaseous PFT technology, and a sulfur hexafluoride (SF6) gas tracer. Ultimately, the barrier was unearthed and the actual dimensions/location of the barrier were ascertained and compared to the results obtained using the investigation tools. The results clearly demonstrated that the geophysical investigative techniques for determining the integrity/performance of a subsurface barrier were technically lagging the installation techniques and materials development. One particular flaw in the installed barrier serves as a prime example of the challenge that subsurface structures can present. A leak or flaw in the barrier occurred due to a misaligned column. When the injection rod was pushed into the subsurface, it wandered off course. The rod bowed in a banana-shaped fashion. The result was similar to a plank floor with one plank pried upward. At a point along the column, the lift was high enough to create a large opening that would allow contaminant migration to occur. Figure 5.13 presents two photographs of the excavated colloidal silica barrier, shown from the north and south views. In the left photograph, the misaligned column is clearly visible. The misalignment was enough to allow contaminants to escape but was not observed by geophysics. The colloidal silica grout contains approximately 85% water and, as such, presents an enormous signal (and clutter) for virtually any geophysical technique. The

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Barrier Systems for Environmental Contaminant Containment & Treatment

FIGURE 5.13 Excavation of the colloidal silica barrier showing a major flaw in the slant wall.

result was that the electroresistivity method used detected the rough shape of the barrier, but could not differentiate anomalies that occurred on fractions of a meter scale. In this case, the opening created by the lifted column was 0.3 to 0.6 m high and 1 to 2 m in length. Both the SF6 and PFT technology deployments were designed as rudimentary leak tests, but also allowed some analysis to refine flaw location information. The primary objective was to test the barrier integrity by injecting tracers inside the barrier and measuring their concentration outside the barrier as a function of time. The PFT technology was successful in identifying two locations with weak barrier integrity. This tracer technology deployed three different gaseous tracers in three different zones within the barrier confines. The east vertical wall showed leakage centered at a depth of 4.5 m below grade approximately 3.6 m into the panel. In addition, the multi-tracer technology was able to show that tracer leaked over the top of the barrier, thereby reaching the outside monitoring points without having to go through a flaw in the barrier. The actual leak was detected by the tracer oc-PDCH, and the spillover was detected with the tracer PMCH. The west (slant) wall also showed evidence of a large leak that was approximately 3.6 m into the panel at a depth of 5.1 m below grade. This leak was first detected with the tracer PMCH. Leakage also occurred over the top of the panel as evidenced by the tracer oc-PDCH. This leak was easily confirmed upon excavation of the barrier and coincided with the misaligned column. The PFT

Subsurface Barrier Verification

343

technology was also used to estimate the gaseous diffusion coefficient for the grouted panels. The SF6 tracer was able to locate the two major leaks, but also detected other possible leaks. The possible leaks were, in fact, measurements of tracer spillover at the top of the barrier. The tracer technologies appear to be the best suited for leak detection, as they can trace even small (i.e., fractions of an inch) faults in a barrier. Although the tracers reveal pathway information, they cannot identify items such as the exact location of a barrier wall, its thickness, or density. While identifying if potential contaminant migration paths exist is generally considered the most important factor for subsurface barriers, spatial location of the barrier is important if precise repairs are needed. In addition, information on subsurface anomalies that might affect installation (e.g., large rocks, unexpected waste forms), repairs, monitoring, and long-term stability are also important.

5.9.3 CASE HISTORY: BARRIER MONITORING AT THE ENVIRONMENTAL RESTORATION DISPOSAL FACILITY (ERDF) The USDOE ERDF located in Hanford, Washington, is a double-lined waste disposal facility that complies with the USEPA’s Minimum Technology Requirements for hazardous waste landfills (Figure 5.14). The design of the disposal cells

Environmental restoration disposal facility

FIGURE 5.14 ERDF showing Cells 1 and 2 partially full.

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(including new Cells 5 and 6) call for the following: a primary (upper) liner with a 60-mil textured HDPE sheet, and a secondary (lower) liner with a 60-mil textured HDPE sheet in direct contact with a 0.91-m-thick layer of soil–bentonite admixture in the bottom of each cell. Although there is a 100-mil HDPE sheet attached to the sump carrier pipe, it has no containment function (Bechtel Hanford, 1995a,b). The side slopes of the landfill have grades of 3H:1V, while the floors slope toward the sump at grades of 1.5% to 3%. Thus, any leachate should drain toward the sumps. Under normal conditions, the liner systems outside of the sumps should not experience any standing leachate (pressure head). Within the sumps, submersible pumps remove leachate so that the head pressure on the floor of the sump, except for transient storm conditions, should be less than 0.30 m. The low-permeability soil used as the lower component of the secondary liner consists of silty fine sand mixed with approximately 12% bentonite by weight. This material was carefully moisture conditioned, placed in lifts, and compacted in the field. To establish compaction requirements, a sealed double-ring infiltrometer (SDRI) test was performed prior to construction of the liner in the landfill itself. The SDRI verification test is a large-scale simulation of the actual liner and is intended to identify any flaws in construction techniques. SDRI results indicated a soil layer permeability of about 1 × 10–8 cm/s. The top and bottom leachate collection systems were sampled, and the volumes from each recorded. In general, the volume ratio was 100:1 between the upper and lower leachate collection system, and well within the allowable leakage through the primary liner of 175 gallons per day per acre. In general, neutron probes and pressure vacuum lysimeters were the barrier verification monitoring tools of choice. Everett and Fogwell (2003) conducted a study evaluating barrier verification monitoring for Cells 5 and 6 and subsequent cells at the site. Each cell in Figure 5.14 is 21.33 m deep and 152.4 m on a side. The cells are arranged in pairs such that they look like one large cell 152.4 m by 304.8 m. The National Academy of Engineering held discussions on the subject of barrier monitoring through caps and liners, and the consensus was that any monitoring system that penetrated through the bottom liner would be unacceptable. Discussions related to monitoring systems that breach the surface cap were found to be troubling, although the concern related to breaching the cap diminished as the size of the access holes was reduced. Neutron access holes in the cap present some problems due to potential preferential flow between the soil and the casing tubing. Horizontally installed TDR wave-guides and dissipation probes, however, do not present these problems. Monitoring below the liners did not appear to be a problem. Another possible consideration for monitoring systems is redundancy (i.e., a system that does not rely on only one type of barrier-monitoring system). The following are some possible benefits that redundancy provides: • •

A backup system in the event of instrument failure A mechanism to crosscheck instrument accuracies

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• • •

•

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More confidence in the data A method for identifying false positives It can assist in applying the graded approach utilizing an automated monitoring systems first, and then, if necessary, using a manual system that can include analytical costs Extension of the life expectancy of the entire monitoring system by providing backup systems in the event of instrument failure, particularly for the nonretrievable elements of the monitoring system

5.9.3.1 Study Conclusions The above study indicates that barrier verification monitoring has been used at several commercial landfill sites in the western part of the United States, where arid conditions guarantee the existence of a relatively deep vadose zone. These applications of barrier monitoring are generally kept simple and reasonably inexpensive. They have generally been employed to give an early warning of leakage and, thus, have resulted in a reduction in required groundwater monitoring. Barrier monitoring is used specifically in two general areas of a landfill, beneath the bottom layer of the landfill and in the final cap. These correspond to the use of monitoring at two distinct stages of the landfill’s life cycle. The first is during the operation of the landfill, while it is being filled and before the final cap is installed. The second is during the long-term storage phase, while the final cap is in place. Thus, the most appropriate monitoring for the first operational phase is a system installed below the bottom of the landfill, whereas the most appropriate monitoring for the long-term phase is one that monitors the integrity of the cap. The above analysis provides potential candidate technologies and approaches for use in either operational or closure applications. 5.9.3.2 Study Recommendations Although several reasonable candidates for barrier verification monitoring were evaluated by Everett and Fogwell (2003), some are more applicable at this site than others. For all the ERDF cells, when they are closed, barrier monitoring of the caps is strongly recommended (Everett and Fogwell, 2003). The most costeffective approach to use during the operational phase of the landfill, however, would be to instrument new cells with basin lysimeters below the secondary leachate sumps. Because of the proven regulatory acceptance, reduced cost considerations, ease of installation, and the ability to collect quantifiable results, a basin lysimeter made up of 100 mil HDPE installed under the secondary sump and beneath the lower compacted low-permeability soil layer in each new cell is the first recommendation. This lysimeter would extend 1.52 m beyond the perimeter of the secondary sump, and would be designed with an access pipe that allows the removal of any liquid collected. It is important that the basin lysimeter be placed beneath the lowest point of the low-permeability layer. In addition to the basin lysimeter, Everett and Fogwell (2003) recommended that access tubes be laid down beneath the secondary barrier liner. The access

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tubes should extend the full length of each cell with spacing sufficient to allow future cross-borehole tomography. Because the tubes would be laid down during construction of the new cells, the costs would be minimal. These access tubes will provide access for a variety of instruments and would accommodate new technologies as they are developed. Installation at Cells 5 and 6 or future ERDF cells will provide a relatively controlled setting for evaluating the performance and utility of access tubes at future multi-use facilities (Everett and Fogwell, 2003). During the capped long-term storage period of the landfill, instrumentation should be used for maintaining surveillance of the integrity of the barrier cap. Noninvasive methods can be used, including lysimeters around the edge of the cap, subsidence monitoring of the cap structure, and tomographic methods for the spatial resolution of possible failure points. Invasive methods would entail establishing entry points through the cap into the interior of the landfill. In addition to instrumentation of the cap, sensors could be implanted in the body of the landfill in order to monitor its state. Also, any tomographic methods at the surface could be combined with the underlying access tubes to give tomographic data on the interior of the landfill. Several possible current technologies have been described in this chapter. The approach outlined above is consistent with other accepted programs, with additional emphasis placed on access to below the new cells during the operational phase and cap integrity monitoring of final coverings. Almost all monitoring methods are expected to be become obsolete or to have some aspect fail over time; thus, it is prudent to consider new technologies and new testing protocols as they are developed, and to allow for the possibility of changing out instrumentation components.

5.9.4 VERIFICATION NEEDS The ability to verify barrier integrity is valuable to many government agencies and the commercial sector. Verification needs identified at the Baltimore workshop in July 2002 are similar to those identified for PRBs in Table 5.10. The Office of Environmental Management of the USDOE outlined a series of technical targets in a needs document in 2001. Technical Target #5 addresses advanced sustainable containment systems. The key word here is sustainable, as containment systems cannot be considered sustainable if the long-term monitoring and stewardship concerns cannot be addressed. This is likely the biggest obstacle to closure many USDOE sites will have. There are many waste treatment technologies and cover system designs available for final disposition of waste streams, but very little available technology to address long-term monitoring/stewardship issues. The Technical Target further states “Properly applied and monitored (bold added for emphasis) physical containment and barriers will remain a central activity in DOE environmental management for the foreseeable future. Advancing the science and technology base relatively rapidly is particularly important to closure sites that need to implement and document such systems in the next several years.”

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In order for a wall or floor to protect the environment, it must remain free of significant holes and flaws throughout its service life. Currently, containment system failures are detected by monitoring wells downstream of the waste site. Clearly this approach is inefficient, as the contaminants have already migrated from the disposal area before they are detected. Methods that indicate early barrier failure (prior to contaminant release) or predict impending failure are needed. Early detection of cover failure or pending failure allows repair or replacement to be made before contaminants leave the disposal cell. There are clearly two distinct subsets of barriers: cutoff walls/floors and containment barriers. The verification needs of these subsets are different. The vast majority of cutoff walls are slurry wall installations where the greatest verification need is initial integrity. Finding a weak point along the barrier is essential so that the weak spot can be repaired. It appears that the present hydraulic gradient-based methods of testing cutoff walls is working well; therefore, further development of advanced monitoring/measurement methods is not warranted. For containment barriers, the opposite appears to be true. That is, there are no reliable, commercially available integrity/performance measuring technologies available. Therefore, this discussion focuses on containment barriers. It is important to note that advances in containment barrier verification/monitoring technologies could, in most cases, be readily applied to cutoff walls/floors. 5.9.4.1 Adequacy of the Containment Region The barrier must meet the required containment goals. The most commonly observed failure for installed walls/floors is incomplete grouting (e.g., misalignment of injection/drill rods, local incomplete grout cure, blockage of the grout injection/delivery by subsurface obstructions). All of these lead to a localized area of the barrier that has reduced containment. The imperfection may or may not affect the overall performance of the waste site. For instance, a hole in a containment barrier at the top of a wall will not allow significant contaminant migration because horizontal flow in the vadose zone is expected to be minimal and the spread at the top of the barrier will also be minimal. However, should the same size hole occur at the bottom of the barrier (particularly in V-shaped containment designs), the containment characteristics of the barrier could be compromised. The containment becomes a bathtub with the stopper pulled out, and it can drain quickly. Thus, adequacy of the containment requires knowing the size and location of the flaw, and the effect the flaw will have on the overall site performance. 5.9.4.2 Long-Term Performance of the Containment The containment must continue to meet the site performance requirements for the lifetime of the barrier. As the earlier workshop publications discuss (Rumer and Mitchell, 1995), subsurface barriers are subject to a wide variety of failures or loss of performance. Desiccation, chemical attack, geotechnical changes (e.g., earthquakes, subsidence) and many other pathways can lead to reduced

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barrier performance. When these changes occur, stakeholders must be informed so that corrective actions (if needed) can be implemented. Ideally, barrier performance monitoring would be such that stakeholders could predict impending failure and take action prior to contaminants escaping from the containment confines. The following are important considerations in long-term monitoring and verification: •

•

•

Monitoring should allow prediction of failure, if possible, rather than detection of failure through detection of contaminants in downstream wells. Measured parameters need to feed into risk assessment models so that the effect of changes in performance can be fully understood in terms of protection of and risk to the public and environment. Systems should require as little on-site presence as possible.

The key variable for a containment system is water flux. To a lesser degree, volatile contaminant flux is important. Because volatiles are not expected to be major components of new waste/waste forms and are likely to be dispersed already at historical sites, water flux remains the key variable. (Containment systems are not expected to be installed without some sort of cover system; therefore, the water flux through the site is co-dependent on both the containment barrier and the cover barrier.) While water flux can be a good indicator of changes over time and trends in performance, simply measuring flux is not enough. Predictive capabilities are also needed and indicator variables that can be tied to water flux or that give indirect evidence of possible changes in water flux need to be measured. Parameters of concern include soil moisture content, permeability (gas/water), precipitation, run off, evapo-transpiration, short-term climate abnormalities, unusual animal intrusion, changes in the containment barrier materials (e.g., plasticity of clays, oxidation of geotextiles), porosity of the barrier, and the condition and location of monitoring devices.

5.10

CONCLUSIONS

There are numerous opportunities for sensor development and application in the various types of barriers. Sensors can be manufactured cheaply and reliably once there is a demand for this type of technology. Acceptance by the regulatory community would follow once the benefit and cost-effectiveness of the sensors have been demonstrated. A collaborative effort among United States federal agencies would expedite the development of the sensor technologies and should be undertaken immediately. The National Research Council (NRC) recently urged the development of sensors for fielded systems for emergency use in countering terrorism, urging that such a program should build on relevant sensor research underway at agencies throughout the federal government because much of the technology is transferable to other disciplines (e.g., hazardous wastes, counterterrorism, medical) (NRC, 2002).

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A systematic approach to the selection, implementation, and operation of a barrier-monitoring strategy should be adopted. Because several alternative technologies, monitoring objectives, and barrier configurations exist, a single technology may not be the most effective for all applications. Barriers exposed to environmental and human-induced stresses deteriorate as time progresses from decades to centuries. Structural deterioration of some components of a barrier may not always lead to a total functional failure of the system. A uniform approach needs to be developed for specifying the failure condition of barriers. Monitoring data can be combined with models to forecast future performance levels and/or maintenance requirements. Integrated sensor monitoring technologies are expected to play a large part in barrier performance monitoring and verification in addition to being cost-effective methods for long-term monitoring.

REFERENCES Bechtel Hanford, Inc. (1995a). Design Analysis, Construction of W-296 Environmental Restoration Disposal Facility, BHI-00355, Rev. 00, Vol. 1, U.S. Department of Energy Office of Environmental Restoration and Waste Management, June 1995. Bechtel Hanford, Inc. (1995b). Design Analysis, Construction of W-296 Environmental Restoration Disposal Facility, BHI-00355, Rev. 00, Vol. 2, U.S. Department of Energy Office of Environmental Restoration and Waste Management, June 1995. Betsill, J.D. and Gruebel, R.D. (1995). VAMOS. The Verification and Monitoring Options Study, Current Research Options for In-Situ Monitoring and Verification of Contaminant Remediation and Containment within the Vadose Zone, Sandia National Laboratory, TTP-AL221107, May 1995. Blowes, D.W. and Mayer, K.U. (1999). An in situ Permeable Reactive Barrier for the Treatment of Hexavalent Chromium and Trichloroethylene in Ground Water: Vol. 3, Mulitcomponent Reactive Transport Modeling, EPA/600/R-99/095c, U.S. Environmental Protection Agency, Ada, OK. Blowes, D.W., Gillham, R.W., Ptacek, C.J., Puis, R.W., Bennett, T.A., O’Hannesin, S.F., Hanton-Fong, C.J. and Bain, J.G. (1999a). An in situ Permeable Reactive Barrier for the Treatment of Hexavalent Chromium and Trichloroethylene in Ground Water: Vol. 1, Design and Installation, EPA/600/R-99/095a, U.S. Environmental Protection Agency, Ada, OK. Blowes, D.W., Puis, R.W., Gillham, R.W., Ptacek, C.J., Bennett, T.A., Bain, J.G., HantonFong, C.J. and Paul, C.J. (1999b). An in situ Permeable Reactive Barrier for the Treatment of Hexavalent Chromium and Trichloroethylene in Ground Water: Vol. 2, Performance Monitoring, EPA/600/R-99/095b, U.S. Environmental Protection Agency, Ada, OK. Borns, D.J. (1997). Geomembranes w/Incorporated Fiber Optical Sensors, etc., Proceedings of the International Containment Technology Conference, p. 1022. Everett, L.G. (1980). Groundwater Monitoring, Genium Publishing Corp., Schenectady, New York, 440 pp. Everett, L.G. and Fogwell, T.W. (2003). Study of the Vadose Zone Monitoring at the Hanford Site, DOE/RL-2003-31, Revision 0, Richland Operations Office, Richland, WA, 53 pp.

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Everett, L.G., Schmidt, K.D., Tinlin, R.M. and Todd, K.D. (1976). Monitoring Groundwater Quality: Methods and Costs, U.S. Environmental Protection Agency, Las Vegas. Everett, L.G., Wilson, L.G. and Hoylman, E.W. (1984). Vadose Zone Monitoring for Hazardous Waste Sites, Noyes Publications, 358 pp. Eykholt, G.R., Elder, C.R. and Benson, C.H. (1999). Effects of aquifer heterogeneity and reaction mechanism uncertainty on a reactive barrier. Journal of Hazardous Materials, 68, 73–99. Fryar, A.E. and Schwartz, F.W. (1994). Modeling the removal of metals from groundwater by a reactive barrier: experimental results. Water Resources Research, 30, 3455–3469. Gillham, R.W. and O’Hanneisin, S.F. (1994). Enhanced degradation of halogenated aliphatic by zero-valent iron. Ground Water, 32, 958–967. Gu, B., Watson, D.B., Phillips, D.H. and Liang, L. (2002). Biochemical, mineralogical, and hydrological characteristics of an iron reactive barrier used for treatment of uranium and nitrate. In Naftz, D.L., Morrison, S.J., Davis, J.A. and Fuller, C.C. (Eds.), Groundwater Remediation Using Permeable Reactive Barriers, Academic Press, San Diego, pp. 305–342. Gupta, N. and Fox, T.C. (1999). Hydrogeologic modeling for permeable reactive barriers. Journal of Hazardous Materials, 68, 19–39. Gupta, N., Sass, B.M., Gavaskar, A.R., Sminchak, J.R., Fox, T.C., Snyder, F.A., O’Dwyer, D. and Reeter, C. (1998). Hydraulic evaluation of a permeable barrier using tracer tests, velocity measurements, and modeling. In Wickramanayake, G.B. and Hinchee, R.E. (Eds.), Designing and Applying Treatment Technologies: Proceedings of the First International Conference on Remediation of Chlorinated and Recalcitrant Compounds, Vol. 1(6), Monterey, CA, 18–21 May, Battelle Press, Columbus, OH, pp. 157–162. Hearst, J.R., and Carlson, C.C. (1994). A comparison of the moisture gauge and the neutron log in air-filled holes. Nuclear Geophysics, 8(2), 165–172. Ho, C.K. and Lohrstorfer, C.F. (2001). Field test to demonstrate real-time in situ detection of volatile organic compounds, September 19–25, Sandia National Laboratories, Bechtel Nevada Corporation, Las Vegas, NV. Hubbard, S., Peterson, J.E., Majer, E.L., Zawislanski, P.T., Roberts, J., Williams, K.H. and Wobber, F. (1997). Estimation of permeable pathways and water content using tomographic radar data. The Leading Edge of Exploration, 16(11), 1623–1628. INEEL (2001). A National Roadmap for Vadose Science and Technology. NRC/NAS EM reviews. Johnson, T.L. and Tratnyek, P.G. (1994). A column study of carbon tetrachloride dehalogenation by iron metal. In Pasco, W.A (Ed.), Proceedings of the 33rd Hanford Symposium on Health & the Environment In-Situ Remediation: Scientific Basis for Current and Future Technologies, Vol. 2, Battelle Pacific Northwest Laboratories, Richland, WA, pp. 931–947. Kram, M.L. and Keller, A.A. (2004a). Complex NAPL site characterization using fluorescence part 2: Analysis of soil matrix effects on the excitation/mission matrix. International Journal of Soil and Sediment Contamination, 13, 119–134. Kram, M.L. and Keller, A.A. (2004b). Complex NAPL site characterization using fluorescence part 3: Detection capabilities for specific excitation sources. International Journal of Soil and Sediment Contamination, 13, 135–148. Kram, M.L., Keller, A.A., Rossabi, J. and Everett, L. (2001a). DNAPL Characterization methods and approaches part 1: Performance comparisons. Ground Water Monitoring and Remediation, 21(1), 67–76.

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Kram, M.L., Keller, A.A., Rossabi, J. and Everett, L. (2001b). DNAPL Characterization methods and approaches part 2: Cost comparisons. Ground Water Monitoring and Remediation, 21(1), 46–61. Kram, M.L., Keller, A.A., Massick, S.M. and Laverman, L.E. (2004). Complex NAPL site characterization using fluorescence, part 1: Selection of excitation wavelength based on NAPL composition. International Journal of Soil and Sediment Contamination, 13, 103–118. Kumthekar, U., Chiou, J.D., Prochaska, K. and Benson, C.H. (2002). Development of a long-term monitoring system to monitor cover system conditions. Spectrum 2002: International Conference on Nuclear and Hazardous Waste Management, American Nuclear Society, Reno, Nevada, August 4–8. Liang L., Korte N., Gu B., Puls R. and Reeter, C. (2000). Geochemical and microbial reactions affecting long-term performance of in situ “iron barriers.” Advances in Environmental Research, 4, 293–309. Lockhart, C.W., and Roberds, W.J. (1996). Worth the risk? Civil Engineering, April, 62–64. Looney, B.B. and Falta, R.W. (Eds.) (2000a). Vadose Zone Science and Technology Solutions, Vol. I, Battelle Press, Columbus, OH, 589 pp. Looney, B.B. and Falta, R.W. (Eds.) (2000b). Vadose Zone Science and Technology Solutions, Vol. II, Battelle Press, Columbus, OH, 1540 pp. Marcus, D.L. and Bond, C. (1999). Results of the reactant sand-fracking pilot test and implications for the in situ remediation of chlorinated VOCs and metals in deep and fractured bedrock aquifers. Journal of Hazardous Materials, 68, 125–153. Morrison, S.J., Metzler, D.R. and Carpenter, C.E. (2001). Uranium precipitation in a permeable barrier by progressive irreversible dissolution of zero-valent iron. Environmental Sciences Technology, 35, 385–390. Morrison, S.J., Metzler, D.R. and Dwyer, B.P. (2002). Removal of As, Mn, Se, U, V and Zn from groundwater by zero-valent iron in a passive treatment cell: Reaction progress modeling. Journal of Contaminant Hydrology, 56, 99–116. NRC (2003). Making the nation safer: The role of science and technology in countering terrorism, June 2002. Puls, R.W., Paul, C.J. and Powell, R.M. (1999a). The application of in situ permeable reactive (zero-valent iron) barrier technology for the remediation of chromatecontaminated groundwater: a field test. Applied Geochemistry, 14, 989–1000. Puls, R.W., Blowes, D.W. and Gillham, R.W. (1999b). Long-term performance monitoring for a permeable reactive barrier at the U.S. Coast Guard Support Center, Elizabeth City, North Carolina. Journal of Hazardous Materials, 68, 109–124. Roh, Y., Lee, S.Y. and Elless, M.P. (2000). Characterization of corrosions products in the permeable reactive barriers. Environmental Geology, 40, 184–194. Rumer, R. and Mitchell, J. (1995). Assessment of barrier containment technologies: A comprehensive treatment for environmental remediation applications. International Containment Technology Workshop, Baltimore, MD, August 29–31. Sass, B.M., Gavaskar, A.R., Gupta, N., Yoon, W.-S., Hicks, J.E., O’Dwyer, D. and Reeter, C. (1998). Evaluating the Moffett Field permeable barrier using groundwater monitoring and geochemical modeling. In Wickramanayake, G.B. and Hinchee, R.E. (Eds.), Designing and Applying Treatment Technologies: Proceedings of the First International Conference on Remediation of Chlorinated and Recalcitrant Compounds, Vol. 1(6), Monterey, CA, 18–21 May, Battelle Press, Columbus, OH, pp. 169–175.

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Scanlon, B.R., Tyler, S.W. and Wierenga, P.J. (1997). Hydrologic issues in arid, unsaturated systems and implications for contaminant transport. Reviews in Geophysics, 35, 461–490. Smith, S. and Nagel, D.J. (2003). Nanotechnology-enabled sensors: Possibilities, realities, and applications. Sensors, 20(11). Tratnyek, P.G., Johnson, T.L. and Schattauer, A. (1995). Interfacial phenomena affecting contaminant remediation with zero-valent iron metal. Emerging Technologies in Hazardous Waste Management VII, American Chemical Society, Atlanta, GA, pp. 589–592. Tratnyek, P.G., Scherer, M.M., Johnson, T.J. and Matheson, L.J. (2003). Permeable reactive barriers of iron and other zero-valent metals. In M.A. Tarr (Ed.), Chemical Degradation Methods for Wastes and Pollutants: Environmental and Industrial Applications, Marcel Dekker, New York, pp. 371–421. Udd, E. (1995). Fiber Optic Smart Structures, Wiley, New York. USACE (1997). Design guidance for application of permeable barriers to remediate dissolved chlorinated solvents, Environics Directorate USAF, DG 1110–345-117. USDOE (2002). Long Term Stewardship Science and Technology Roadmap, Office of Long Term Stewardship U.S. Department of Energy, INEEL, 201 pp. USDOE/CMST (2001). Long Term Monitoring Sensor and Analytical Methods Workshop, June 13–15. USEPA (1997). Permeable Reactive Subsurface Barriers for the Interception and Remediation of Chlorinated Hydrocarbon and Chromium (VI) Plumes in Ground Water, EPA 600-F-97-008, National Risk Management Research Laboratory, Ada, OK, July, 4p. USEPA (2002). Field applications on in situ remediation technologies: Permeable reactive barriers, Technology Innovations Office. Wilson, L.G., Everett, L.G. and Cullen, S.J. (Eds.) (1995). Handbook of Vadose Zone Characterization and Monitoring, Lewis, Boca Raton, 730 pp. Yabusaki, S., Cantrell, K., Sass, B. and Steefel, C. (2001). Multicomponent reactive transport in an in situ zero-valent iron cell. Environmental Science and Technology, 35, 1493- 1503.

APPENDIX A Workshop Panels PANEL 1 PREDICTION: MATERIALS STABILITY AND APPLICATION PANEL LEADER Craig H. Benson, University of Wisconsin at Madison

PANEL CO-LEADER Stephen F. Dwyer, Sandia National Laboratories

PANEL GRADUATE FELLOW Sazzad Bin-Shafique, University of Wisconsin at Madison

PANEL MEMBERS David W. Blowes, University of Waterloo David A. Carson, United States Environmental Protection Agency, National Risk Management Research Laboratory Peter W. Deming, Mueser Rutledge Consulting Engineers Jeffrey C. Evans, Bucknell University Glendon W. Gee, Battelle Pacific Northwest National Laboratory Laymon L. Gray, Florida State University Kathleen E. Hain, United States Department of Energy, Idaho Operations Office Stephan A. Jefferis, University of Surrey, United Kingdom Mark R. Matsumoto, University of California at Riverside Stanley J. Morrison, Environmental Sciences Laboratory Scott D. Warner, Geomatrix Consultants, Inc. John A. Wilkens, DuPont

PANEL 2 PREDICTION: BARRIER PERFORMANCE PREDICTION PANEL LEADER Charles D. Shackelford, Colorado State University 353

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PANEL CO-LEADER Jack C. Parker, Oak Ridge National Laboratory

PANEL GRADUATE FELLOW Alyssa Lanier, University of Wisconsin at Madison

PANEL MEMBERS Clifford K. Ho, Sandia National Laboratories Richard C. Landis, DuPont Eric R. Lindgren, Sandia National Laboratories Michael A. Malusis, GeoTrans, Inc. Mario Manassero, Politecnico, Torino, Italy Greg P. Newman, Geo-Slope International Ltd. Robert W. Puls, United States Environmental Protection Agency, National Risk Management Research Laboratory Timothy M. Sivavec, General Electric Brent E. Sleep, University of Toronto Terrence M. Sullivan, Brookhaven National Laboratory

PANEL 3 PREDICTION: DAMAGE AND SYSTEM PERFORMANCE PREDICTION PANEL LEADER Hilary I. Inyang, University of North Carolina at Charlotte

PANEL CO-LEADER Steven J. Piet, Idaho National Engineering and Environmental Laboratory

PANEL GRADUATE FELLOW Paul Wachsmuth, University of North Carolina at Charlotte

PANEL MEMBERS James H. Clark, Vanderbilt University Thomas O. Early, Oak Ridge National Laboratory John B. Gladden, Westinghouse Savannah River Company Priyantha W. Jayawickrama, Texas Tech University W. Barnes Johnson, United States Environmental Protection Agency, Office of Solid Waste and Emergency Response Robert E. Melchers, University of Newcastle, Australia

Workshop Panels

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V. Rajaram, Black and Veatch Corporation W. Jody Waugh, United States Department of Energy, Environmental Sciences Laboratory Thomas F. Zimmie, Rensselaer Polytechnic Institute

PANEL 4 VERIFICATION: AIRBORNE AND SURFACE/GEOPHYSICAL METHODS PANEL LEADER Ernest L. Majer, Lawrence Berkeley National Laboratory

PANEL CO-LEADER David P. Lesmes, Boston College

PANEL GRADUATE FELLOW Marcel Belaval, Boston College

PANEL MEMBERS Randolf J. Cumbest, Westinghouse Savannah River Company William E. Doll, Oak Ridge National Laboratory Edward Kavazanjian, Jr., GeoSyntec Consultants John D. Koutsandreas, Florida State University John W. Lane, United States Geological Survey Lee D. Slater, University of Missouri at Kansas City Anderson L. Ward, Battelle Pacific Northwest National Laboratory Chester J. Weiss, Sandia National Laboratories

PANEL 5 VERIFICATION: SUBSURFACE-BASED METHODS PANEL LEADER David J. Borns, Sandia National Laboratories

PANEL CO-LEADER Carol Eddy-Dilek, Westinghouse Savannah River Company

PANEL GRADUATE FELLOW Matthew C. Spansky, Westinghouse Savannah River Company

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PANEL MEMBERS William R. Berti, DuPont George K. Burke, Hayward Baker, Inc. Bruce Davis, National Aeronautics and Space Administration John H. Heiser, Brookhaven National Laboratory Diana J. Hollis Puglisi, Los Alamos National Laboratory John B. Jones, United States Department of Energy, Nevada Operations Office John D. Koutsandreas, Florida State University William E. Lowry, Science and Engineering Associates, Inc. Horace K. Moo-Young, Jr., Villanova University Michael G. Serrato, Westinghouse Savannah River Company

Index A Absorbent pads, 295 ACAP, see Alternative Cover Assessment Program (ACAP) Acar, Alshawabkeh and, studies, 130 Acar and Haider studies, 122 Acceleration in bedrock, 31 Acoustic wave devices, 331, 331–332, 333–336 Adamson and Parkin studies, 99 Adequacy, containment region, 347 ADRE, see Advection-dispersion reaction equation (ADRE) Advanced Infra-Red Imaging Spectrometer (AVIRIS), 234, 235 Advancement needs, 275–276 Advection-dispersion reaction equation (ADRE), 114, 128, 131 AEMS, 307–308 Aerial photography, 232, 272–273 AES, see Auger electron spectroscopy (AES) AFRL, see Air Force Research Laboratory (AFRL) Airborne geophysical methods, see Geophysical method verification Airborne methods, 228–229, 229–231, 231 Air Force Research Laboratory (AFRL), 93, 96, 98, 105, 107, 109 ALARA (as low as reasonably attainable), 23 ALARP (as low as reasonably practical), 23 Albrecht and Benson studies, 89, 160 Albright and Benson studies, 157, 159–160, 163 Algebraic reconstruction tomography (ART), 221 Alshawabkeh and Acar studies, 130 Alternative Cover Assessment Program (ACAP), 159–160, 163, 165 Alves, Genuchten and, studies, 114, 116 American Society of Testing and Materials (ASTM), 288–289 Anaerobic biodegradation, 98–99 Analytical framework, 8–10, 8–11 Analytical models, walls and floors, 115, 120, 120–123, 123 Anderson, Zhu and, studies, 105 Anderson and Hampton studies, 224

Anderson and Woessner studies, 91 Animal species, intrusive events, 29–30 Annan, Davis and, studies, 211 Anon studies, 111 Apparent conductivity maps, 265, 267–269 Appelo, Parkhurst and, studies, 106–109 Applications, geophysical method verification, 209–216 Aqueous-phase transport, 112–117, 115 Archie studies, 225 ART, see Algebraic reconstruction tomography (ART) Arthur and Markham studies, 28 Arthur studies, 28 Auger electron spectroscopy (AES), 191 AVIRIS, see Advanced Infra-Red Imaging Spectrometer (AVIRIS) Ayorinde, Chamberlain and, studies, 32

B Badu-Tweneboah studies, 153 Badv, Rowe and, studies, 128–129 Badv and Rowe studies, 128 Bai and Inyang studies, 26 Bai studies, 26, 30, 193 Baouchelaghem, Gouvenot and, studies, 124 Barbour and Fredlund studies, 117, 126 Barbour studies, 117, 126 Barrier cap monitoring, 311–312 Barrier layers, hydrologic cycle, 74–75 Barrier verification, see Subsurface barrier verification Basin lysimeter, 295 Battelle studies, 98, 173 Bayesian method, 54, 60 Bayes studies, 54 Bear and Verruijt studies, 91 Bear studies, 112 Bedford and Stern studies, 224 Benchmarking, 87–88 Bench-scale tests, 144, 147 Benner studies, 93, 98 Benoit studies, 32 Benson, Albrecht and, studies, 89, 160

357

358

Barrier Systems for Environmental Contaminant Containment & Treatment

Benson, Albright and, studies, 157, 159–160, 163 Benson, Lee and, studies, 193 Benson, Tachavises and, studies, 193 Benson studies, 32, 143–201 Bernabe studies, 26 Berti studies, 287n Bethke studies, 105, 107–108 Betsill and Gruebel studies, 288 Bilbrey and Shafer studies, 187 Binley, Slater and, studies, 215, 241–243 Biological processes, 24–29, 25, 29 Blackmore and Miller studies, 35 Blowes and Mayer studies, 327 Blowes studies, 143–143n, 168, 188, 191, 327 Bodo Canyon site, Colorado, 331 Bogardi studies, 24 Bohn studies, 129 Bolen studies, 163 Bond, Marcus and, studies, 322 Bongi studies, 236 Booker, Rowe and, studies, 116, 122–123 Borns studies, 287–349 Born studies, 287–349 Bostick studies, 93 Boundary conditions, 115, 115–117 Bowerman and Redente studies, 29 Bowman studies, 93 Brace and Orange studies, 226 Bradley and Chapelle studies, 100 Bray, Merry and, studies, 26 Breckenridge, Piet and, studies, 14 Bresler studies, 117, 126 Britton studies, 131 Brookhaven National Laboratory, 255, 338, 341

C Cadwell studies, 15 Calibration, 88–89 Calvin, Vaughan and, studies, 277 Canadian Forces Base, Borden (Ontario, Canada), 95, 330 Canadian Radarsat, 237 Capillary break layers, 74 Caps, material performance factors basics, 153–155, 154–155 composite barriers, 155–160, 156, 158–159 hydraulic considerations, 165 vegetation and materials relationship, 163, 165–167, 166–167 water balance designs, 153, 160–163, 161–162, 164–165

Caps and covers aerial photography, 272–273 apparent conductivity maps, 265, 267–269 calibration, 88–89 caps, 72–90 case histories, 263–274 code quality assurance, 87–88 current practice, 75, 76–80, 81–85 data needs, 86–87 design verification, 262–263 electromagnetic interference, 263–267, 264–265 electromagnetic radar, 269–271, 270, 272 FEHM, 85 geophysical method verification, 261–274 GPR, 263–267, 264–265 HELP model, 81 heterogeneities, role, 90 HIS imagery, 274 hydrologic cycle, 72, 73 HYDRUS-2D, 83 infiltration, arid sites, 90 layers and features, 74–75 limitations, 86–89 long term effectiveness, 12 material stability and applications, 153–166, 154–155 moisture content, 269–271, 270, 272 monitoring, 262–263 multi-spectral scanners, 273 performance issues, 72–75 PRBs, 72–90 quality control, 87–88 RAECOM, 85 requirements, 262–263 research needs, 86–89 role, 86 site characterization, 262–263 SoilCover, 82–83 thermal scanners, 273–274 time-varying properties and processes, 89–90 TOUGH2, 84–85 unresolved challenges, 89–90 UNSAT-H, 82 VADOSE-W, 84 validation and verification, 88–89 water balance method, 75, 81 Carlson, Hearst and, studies, 338 Carmichael studies, 239 Carson studies, 143n Case histories caps and covers, 263–274 colloidal silica demonstration, 341–343

Index Environmental Restoration Disposal Facility, 343, 343–346 Fernald on-site disposal facility, 315, 315–318, 317 geophysical method verification, 243–246 mixed waste landfill, 312–315 subsurface monitoring, 329 vertical barriers, 254–261 Cement-bentonite (CB) cutoff walls, 193 Centralizers, 173 Cepic and Mavako studies, 42 CERCLA, see Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) Chamberlain and Ayorinde studies, 32 Chamberlain and Gow studies, 24 Chamberlain studies, 287n Chanzy studies, 262 Chapelle, Bradley and, studies, 100 Characterization, geophysical method verification, 210–211, 212, 214–216 Characterization, Monitoring, and Sensors Technology (CMST) program, 301 Charbeneau and Daniel studies, 129 Charbeneau studies, 112 Chemical additives, 146–147 Chemico-osmotic efficiency, 127 Chen studies, 24, 201, 224 Cherry, Pankow and, studies, 112 Chien studies, 71n Chu studies, 278 Clarke studies, 1n Clark studies, 62, 160 Clay soils, membrane behavior, 126–127, 127 Clement studies, 187 CMST, see Characterization, Monitoring, and Sensors Technology (CMST) program Coa and Greenhalgh studies, 223 Code development, geophysical method verification, 276 Code quality assurance, 87–88 Colloidal silica, 341–343, 342 Colorado subalpine forest, 27 Compliance, 22, 37–42, 39–41 Complicating factors anions, 129–131, 131 complexation, 131 complicating factors, 128–132 constant seepage velocity, 128 constant volumetric water content, 128–129 effective porosity, 129 nonlinear sorption, 129–130 organic contaminant biodegradation, 131–132

359 rate-dependent sorption, 130 seepage, 128 temperature effects, 132 volumetric water content, 128–129 Component failure contaminant containment, 53–54 probability, 22–23, 34, 44–47, 45–46 Composite barriers, 155–160, 156, 158–159 Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA), 288 Conca and Wright studies, 128 Containment, long-term performance, 347–348 Containment region adequacy, 347 Contaminant release source term, 37–42, 39–41, 55 Contaminants concentration reduction, 99 organic, biodegradation, 131–132 transport processes, 112–123 Contingency plans, 91 Cook and Kilty studies, 262 Cook and Walker studies, 268 Corey studies, 112 Corser and Cranston studies, 160 Costs, subsurface barrier verification, 309 Coupled solute transport, 117–119, 120, 125–126 Covers, 11, 310–320, see also Caps and covers Cox, Daley and, studies, 222 Cox studies, 104 Crampin studies, 223 Cranston, Corser and, studies, 160 Cross-hole GPR investigations geophysical method verification, 245–246, 247–248 vertical barriers, 255, 257–258, 257–259 Cross-well imaging, 222–224 Cultural preferences, 6 Cumbest studies, 209n Current practices caps, 75, 76–80, 81–85 covers, 310–312 PRBs, 325–329 transitioning, 297–309 walls and floors, 111–112, 337–340 Cutoff walls, material stability and applications basics, 191–193, 192 design configuration, 196–198, 197–198 geosynthetics, 198–199, 200 hydraulic considerations, 193–195, 194–196 material property ranges, 192 permeant interaction effects, 199–201, 201

360

Barrier Systems for Environmental Contaminant Containment & Treatment

in situ hydraulic conductivity, 193–195, 194–196 vertical cutoff walls, 198–199, 200 Cyclical stressing mechanisms, 32, 34, 34–37, 36, 38

D Dailey and Ramirez studies, 213, 226, 260 Daily studies, 241 Daley and Cox studies, 222 Daley studies, 220, 222 Damage and system performance prediction analytical framework, 8–10, 8–11 basics, xiv–xv, 1–7, 2–4, 7 biological processes, 24–29, 25, 29 compliance, 22, 37–42, 39–41 component failure, 22–23, 34, 44–47, 45–46, 53–54 contaminant release sources, 37–42, 39–41 cyclical stressing mechanisms, 32, 34, 34–37, 36, 38 degradation mechanism categories, 24–37 economic criteria, 18 empirical prediction approach, 11–12, 11–12 estimation, long-term failure probabilities, 42–53 event consequences and connectivities, 42 event trees, 42, 44 failures, 42–53 fault trees, 42, 43 indexing analysis, 21, 23–24 intrusive events, 29–30 less empirical (theoretical) modeling approach, 14–15 life cycle approach, 61–62, 62 long-term performance analysis, 7–15 maintenance, 59–61 mixed criteria, 23, 23 modeling, 59–61 monitoring, 59–61 multi-dimensional case, 51–53, 52–53 performance prediction approaches, 11–15 prescriptive design criteria, 19–20 pseudo-economic criteria, 18 qualitative analysis, 21, 21, 23–24 quantification, long-term issues, 24–58 random resistance, 45, 47–48, 48 regulatory criteria, 19, 19 relationship, containment concentrations and risks, 54–58, 55–56, 58

risk assessment, 37–42, 39–41, 54–58, 55–56, 58 risk criteria, 20–22, 21–22 semi-empirical prediction approach, 12–14 simplifications of theory, 48–51 slow physico-chemical processes, 24–29, 25, 29 structure-functional failure relationship, 15–24, 17–18 system failure, 22, 43–44, 53–54 system management, updating, 60–61, 61 theory simplifications, 51 transient events, 30, 31, 32, 33–34 updating, 59–61, 60–61 Damage models, improvement needs, 5–6 Daneshjoo and Hushmand studies, 30 Daniel, Charbeneau and, studies, 129 Daniel, Estornell and, studies, 152 Daniel, Koerner and, studies, 152, 155 Daniels studies, 24, 34 Daniel studies, 143 D' Appolonia studies, 145 Darcy's Law and properties, 82, 119, 186 Dasgupta studies, 18 Dasog studies, 35 Data needs, 86–87, 319 Data streams, 238 Davidson, Schaff and, studies, 35 Davis and Annan studies, 211 Davis studies, 209n Day, Ryan and, studies, 145 DCM, see Dichloromethane (DCM) Decision analysis, 2, 299, 299–300 De Flaun studies, 249 Degradation mechanism categories, 24–37 Dehalococcoides ethenogenes, 100 Deming studies, 143n Dense nonaqueous phase liquid (DNAPL) sites, 305 De Paoli studies, 124 Department of Defense, see U.S. Department of Defense (USDOD) Design configuration, cutoff walls, 196–198, 197–198 Design verification caps and covers, 262–263 geophysical method verification, 239, 241–244, 244–246 vertical barriers, 249–250, 250–253, 252, 254 Desorption curve, 102 DiBenedetto studies, 236 Dichloromethane (DCM), 100, 103–104 Direct push technologies, 305, 306

Index Dissolved organic carbon, 100–101 Dobson studies, 238 DOD, see U.S. Department of Defense (USDOD) DOE, see U.S. Department of Energy (DOE) Doll studies, 209n, 211, 228, 262 Donnegan and Rebertus studies, 27 Dover Air Force Base, 255 Downgradient biodegradation processes, 98–101 Du and Rummel studies, 262, 266 DuPont, 321 DuPont site, East Chicago (Indiana), 171 Durability geosynthetics, 149–153 PRBs, material performance factors, 183, 184–185, 185–187 Dwyer studies, 111, 143–201 Dzombak, Roy and, studies, 57

E East Chicago (Indiana), 171 Economic criteria, structure-functional failure relationship, 18 Eddy-Dilek studies, 287–349 EDXA, see Energy dispersive x-ray analysis (EDXA) Einarsson and Rausand studies, 24 Elachi studies, 233 Elder studies, 173–174, 176, 187 Electrical and electromagnetic methods, 214–215, 224–227 Electrical imaging, case study, 243–244, 244–246 Electrical resistivity tomography (ERT), 260, 260–261, 293–294 Electromagnetic induction (EMI), 262–267, 264–265, 293 Electromagnetic radar, 269–271, 270, 272 Electromagnetic surveys, dates, 264 Electron donor production, 100 Elias studies, 24, 26 Elizabeth City, North Carolina, 97, 108, 329 Ellis studies, 100 EMI, see Electromagnetic induction (EMI) Empirical prediction approach, 11–12, 11–12 Endres studies, 215, 241 End states, 309–310 Energy dispersive x-ray analysis (EDXA), 191 Energy Science and Technology Software Center, 85 Envelope of resistance, 46

361 Environmental Management Science Program, 332 Environmental Restoration Disposal Facility, 343, 343–346 Environmental Systems Management, Analysis, and Reporting (E-SMART) network, 304, 304–305 EPA, see U.S. Environmental Protection Agency (USEPA) ERT, see Electrical resistivity tomography (ERT) E-SMART network, 304, 304–305 Estimation, long-term failure probabilities basics, 42–43 component failure, 22–23, 34, 44–47, 45–46 multi-dimensional case, 51–53, 52–53 quantification, long-term issues, 42–53 random resistance, 45, 47–48, 48 simplification of theory, 48–51, 51 system failure, 22, 43–44 Estornell and Daniel studies, 152 European Resources Satellite (ERS-1.ERS-2), 237 Evaluation materials, 147–149, 152 performance factors, 16 PRBs, material performance factors, 170–172, 171–173 Evans studies, 143n, 193 Evapo-transpiration, 81, 90 Event consequences and connectivities, 42 Event trees, 42, 44 Everett, Lorne G., 288 Everett and Fogwell studies, 300, 310, 344–346 Everett studies, 287–349 Exposures, 7, 56, 58 Eykholt studies, 173, 331

F Failures, quantification, 42–53 Falta, Looney and, studies, 292, 294 Farrell studies, 186 Fault trees, 42, 43 Federal Energy Technology Center, 273 FEHM, see Finite element heat and mass (FEHM) FEMP, see Fernald Environmental Management Project (FEMP) Fennelly and Roberts studies, 100 Fenn studies, 81, 86 Fernald Environmental Management Project (FEMP), 315

362

Barrier Systems for Environmental Contaminant Containment & Treatment

Fernald on-site disposal facility, 315, 315–318, 317 Fernandez and Quigley studies, 24 Ferrell studies, 94 Fiber-optic cable, monitoring, 294 Fiber optics distributed temperature moisture monitoring, 314 Fick's Law, 82 Fiedor studies, 97 Field Lysimeter Test Facility (FLTF), 308 Field performance, see Performance and performance factors Finite element heat and mass (FEHM), 85 Finsterwalder and Spirres studies, 124 First-order second moment (FOSM) method, 50, 52 Fleming and Inyang studies, 24, 147 Floors, 110–127, see also Walls and floors Flow characterization and monitoring, 325, 326–327, 330–331 Flow charts, 2, 40 FLTF, see Field Lysimeter Test Facility (FLTF) Fluor Hanford (Richland, Washington), 308 Fogwell, Everett and, studies, 300, 310, 344–346 Fogwell studies, 287n Foose studies, 120, 123 Forrester studies, 14 FOSM, see First-order second moment (FOSM) method Fouling model, 189 Fourier's Law, 82 Fox, Gupta and, studies, 298–299, 330 Fraser, Rowe and, studies, 57 Fratalocchi studies, 124–125 Fredlund, Barbour and, studies, 117, 126 Fredlund and Xing studies, 87 Freedman and Gossett studies, 100 Freight Yard, Copenhagen (Denmark), 330 Fritz and Marine studies, 117 Fritz studies, 118 Fruchter studies, 93 Fryar and Schwartz studies, 327 Fused sensor systems, 238 Future developments, 276–278

G Gallegos studies, 38 Gasperikova studies, 228 Gavaskar studies, 143, 242 GCL (geosynthetic clay liner), see Geosynthetics

Gee, Meyer and, studies, 20 Gee, Ward and, studies, 160, 263 Gee and Ward studies, 15 Gee studies, 143n, 165 Geller, Majer and, studies, 220 Geller and Myer studies, 220 Geller studies, 220, 249 Geochemical processes modeling, 92–97, 94–96, 104–109 monitoring, 331 Geomembrane vertical walls, installation, 200 Geophysical method verification advancement needs, 275–276 aerial photography, 232, 272–273 airborne methods, 228–229, 229–231, 231 apparent conductivity maps, 265, 267–269 applications, 209–216 basics, xv, 274–278 caps and covers, 261–274 case histories, 243–246, 254–261, 263–274 characterization, 210–211, 212, 214–216 code development, 276 cross-hole GPR investigations, 245–246, 247–248, 255, 257–258, 257–259 cross-well imaging, 222–224 data streams, 238 design verification, 239, 241–244, 244–246, 249–250, 250–253, 252, 254, 262–263 electrical and electromagnetic methods, 214–215, 224–227 electrical imaging, case study, 243–244, 244–246 electromagnetic interference, 263–267, 264–265 electromagnetic radar, 269–271, 270, 272 ERT systems, 260, 260–261 fused sensor systems, 238 future developments, 276–278 geophysics, 210–214, 212–213 GPR, 263–267, 264–265 guided/channel waves, 221 HIS imagery, 274 hyperspectral imaging sensors, 234, 234–235 instrumentation, 276 integration, 275 laser-induced fluorescence, 236–237 LIDAR systems, 235–236 moisture content, 269–271, 270, 272 monitoring, 239, 240, 242–243, 249, 254, 262–263 multi-spectral scanners, 232–233, 273 natural field and magnetic methods, 215–216, 227–228 performance monitoring, 212–214, 213

Index PRBs, 239–246, 240 radar systems, 237–238, 238 ray tomography, 220–221 reflected energy, 221 remote sensing, 216, 231–238 requirements, 239, 249, 262–263 scattered energy, 221 seismic methods, 214, 216–224, 218–219, 259 single well imaging, 222–224 site characterization, 214–216, 239–241, 249, 262–263 specific methods, 216–238 thermal scanners, 233, 273–274 tomography, 220–221 vertical barriers, 246–261 VSP imaging, 222–224 wave tomography, 220–221 Geophysics, 210–214, 212–213 Geosynthetics clay liners, 152, 156–159 degradation, 26 durability, 149–153 vertical cutoff walls, 198–199, 200 Gibbs free energy, 99 Gilbert, Liu and, studies, 24 Gilbert and Tang studies, 24 Gillham, O' Hannesin and, studies, 95 Gillham and O' Hannesin studies, 93, 167, 321 Gillham studies, 98, 186 Giroud studies, 26, 120, 151 Gladden studies, 1n Goals, subsurface barrier verification, 288, 289 Gossett, Freedman and, studies, 100 Goubau studies, 227 Goulas studies, 236 Gouvenot and Bouchelaghem studies, 124 Gow, Chamberlain and, studies, 24 Granular iron PRBs, 184–185 Greaves studies, 265 Greenberg studies, 117 Greenhalgh, Cao and, studies, 223 Grote studies, 211, 213, 227 Ground surface layer, hydrologic cycle, 74 Groundwater chemistry, 95 Groundwater hydraulics, PRBs, 91–92 Gruebel, Betsill and, studies, 288 Guar, 101 Guglielmetti, Koerner and, studies, 199 Guided/channel waves, 221 Gunter studies, 107 Gupta and Fox studies, 298–299, 330 Gupta studies, 327 Gu studies, 97, 99–100, 221, 327

363

H Hagemeister studies, 12 Haider, Acar and, studies, 122 Hampton, Anderson and, studies, 224 Hanford Central Plateau, 308 Hanford (DOE site), Washington barrier monitoring, case history, 343 direct push technologies, 305 electromagnetic surveys, dates, 264 EMI/GPR relationship, 263 installation/verification, 250, 252–253 intrusive events, 29–30 vegetation, 165 water balance designs, 160, 161–162 Harbaugh, McDonald and, studies, 119 Hardware, verification needs, 320, 320–323 Harrison Air Force Base (Indiana), 305 Harris studies, 222 Hartley studies, 24 Hathorn studies, 57 Haxo studies, 152 Hayes adn Marcus studies, 93 Hazard inventory, 6–7 Hazardous materials, 3–4, 146–147 Hearst and Carlson studies, 338 Heiser studies, 287n HELP, see Hydrologic evaluation of landfill performance (HELP) Hendrickx, Sheets and, studies, 211, 263, 267 Hendrickx studies, 211, 262–263, 268 Henyey, Leary and, studies, 211, 223 Heterogeneities, role, 90 HIS imagery, 27, 274, 277 Historical developments, xiii–xiv Ho and Lohrstorfer studies, 309 Hood studies, 6Ho and Webb studies, 84 Horizontal barriers, PRBs, 110–111 Ho studies, 16, 20, 28–29, 71n Hsuan and Koerner studies, 160 Hubbard and Rubin studies, 227 Hubbard studies, 209n, 211, 217, 220, 224, 241, 262, 295 Huisman studies, 262–263, 266 Hushmand, Daneshjoo and, studies, 30 Hydraulic considerations caps, material performance factors, 165 conductivity, 240–241 cutoff walls, material stability and applications, 193–195, 194–196 heterogeneous aquifer model, 190 mineral precipitation effect, 185–186 reactive material performance, 172–178, 174–175, 177, 179–182

364

Barrier Systems for Environmental Contaminant Containment & Treatment

samples summary, 165 time-varying properties and processes, 125 Hydraulic head gradient, 122 Hydrogen, 99–100 Hydrological process monitoring, 331 Hydrologic cycle, 72, 73 Hydrologic evaluation of landfill performance (HELP) calibration, 89 caps, 81 data needs, 86–87 risk criteria, 20 water flow through barriers, modeling, 119 Hydrology, site, 91 HYDRUS-2D, 83, 87 Hyperspectral imaging sensors, 234, 234–235

I Idaho National Engineering and Environmental Laboratory (INEEL) cover verification needs, 318 guided/channel waves, 221 intrusive events, 29–30 less empirical modeling approach, 14 Long-Term Stewardship Science and Map, 309–310 Vadose Zone Science and Technology Roadmap, 292 IFSAR technology, 277–278 Implementation drivers, 309–310 Indexing analysis, 21, 23–24 Infiltration, 90, 313 Input parameters, 123–125 In situ hydraulic conductivity, 193–195, 194–196 Inspection time point, 61 Installation, vertical barriers, 249–250, 250–253, 252, 254 Instrumentation, geophysical method verification, 276 Integration, geophysical method verification, 275 International Containment Technology Workshop, 321 Interstate Technology Regulatory Council (ITRC), 169 Intrusive events, 29–30 Inverse modeling, 108–109 Inyang, Bai and, studies, 26 Inyang, Fleming and, studies, 24, 147 Inyang, Reddi and, studies, 54, 143 Inyang and Tomassoni studies, 12

Inyang studies, 1–62, 143n, 145, 191 Ito studies, 224 ITRC, see Interstate Technology Regulatory Council (ITRC)

J Japanese Earth Resources Satellite (JERS), 237 Jayawickrama and Lytton studies, 26 Jayawickrama studies, 1n Jefferis studies, 125, 143n, 193, 200 Jensen studies, 232 JERS, see Japanese Earth Resources Satellite (JERS) Jessbeger studies, 124 Joesten studies, 241–242, 245 Johnson, Korneev and, studies, 221 Johnson, Tura and, studies, 220–221 Johnson and Tratnyek studies, 327 Johnson studies, 1n Jones studies, 287n

K Kachanoski studies, 262–263 Kachanov studies, 35 Kansas City (DOE facility), Missouri, 173–174, 241, 243 Katzmann studies, 111 Kauschinger studies, 110 Kavazanjian and Matasovic studies, 30 Keijzer studies, 117, 126 Kelch studies, 274 Keller, Kram and, studies, 305 Kemper and Quirk studies, 117 Kemper and Rollins studies, 117, 126–127 Khalil and Moraes studies, 35, 37 Khandelwal, Rabideau and, studies, 111, 114, 116–117, 121–122, 130 Khandelwal studies, 130 Khire studies, 160 Kiefer, Lillesand and, studies, 233–234 Kilty, Cook and, studies, 262 Kirtland Air Force Base (New Mexico), 305 Klimentos and McCann studies, 224 Köber studies, 187 Koerner, Hsuan and, studies, 160 Koerner, Lord and, studies, 26 Koerner and Daniel studies, 152, 155 Koerner and Guglielmetti studies, 199 Korb studies, 277 Korneev and Johnson studies, 221

Index Korte studies, 93 Koutsandreas studies, 209n, 287–349 Kozak studies, 37 Kram and Keller studies, 305 Kram studies, 305 Krohn studies, 211, 221 Kroto, Sir Harold, 307 K-25 site, Oak Ridge National Laboratory, 236, 273 Kumthekar studies, 316–317 Kuster and Tokoz studies, 223

L LaGrega studies, 143 Lake and Rowe studies, 26 Landis studies, 71n Land use analysis, safety targets, 19 Lanier studies, 71n LANL, see Los Alamos National Laboratory (LANL) Laplace transforms, 122–123 Laser-induced fluorescence imaging (LIFI), 236–237 Lasse studies, 173 Layard studies, 18 Layers and features, 74–75 LEA, see Local equilibrium assumption (LEA) Leary and Henyey studies, 211, 223 Lee, Miller and, studies, 32 Lee and Benson studies, 193 Lesmes studies, 209n Less empirical (theoretical) modeling approach, 14–15 Liang studies, 327 LIDAR systems, 233, 235–236, 277 LIF, see Laser-induced fluorescence imaging (LIFI) Life cycle approach, 61–62, 62 Lillesand and Kiefer studies, 233–234 Limitations, modeling caps, 86–89 PRBs, 109–110 walls and floors, 123–127 Lim studies, 128 Lindgren studies, 287n Linear least squares spectral analysis (LLSSA), 35–36 Liners, 11, see also Caps and covers Link studies, 15 Li studies, 188 Liu and Gilbert studies, 24 Liu studies, 221

365 LLSSA, see Linear least squares spectral analysis (LLSSA) Local equilibrium assumption (LEA), 130 Lockhart and Roberds studies, 298–299 Lohrstorfer, Ho and, studies, 309 Long-Term Monitoring Sensor and Analytical Methods Workshop, 301 Long-term performance, see also Performance and performance factors damage and system performance prediction, 7–15 estimation necessity, 2 processes and parameters interaction, 8 quantitative methods, 2, 4–5 subsurface barrier verification, 347–348 Long-term post-closure radiation monitoring systems (LPRMS), 302–303, 302–304 Looney and Falta studies, 292, 294 Lord and Koerner studies, 26 Los Alamos National Laboratory (LANL), 273–274, 295 Low permeability walls, design, 120 Lowry v, 287n LPRMS, see Long-term post-closure radiation monitoring systems (LPRMS) Lytton, Jayawickrama and, studies, 26

M Mackenzie studies, 185 Mackey studies, 274 Maintenance, damage and system performance prediction, 59–61 Majer and Gellar studies, 220 Majer studies, 209–278 Malone studies, 57 Malusis and Shackelford studies, 117–119, 127 Malusis studies, 71n, 117, 127 Manassero and Shackelford studies, 122 Manassero studies, 71n, 124–125, 130 Marcus, Hayes and, studies, 93 Marcus and Bond studies, 322 Marine, Fritz and, studies, 117 Marion studies, 224 Markham, Arthur and, studies, 28 Maryland, 229, 230 Mason studies, 222 Massachusetts Military Reservation, 241 Matasovic, Kavazanjian and, studies, 30 Matasovic studies, 30 Material and performance relationship, 144, 144–145, 146–151, 147 Material stability and applications

366

Barrier Systems for Environmental Contaminant Containment & Treatment

basics, xv, 143–144 caps, 153–166, 154–155 composite barriers, 155–160, 156, 158–159 cutoff walls, 191–201, 192 design configuration, 196–198, 197–198 durability, 149–153, 183, 184–185, 185–187 evaluation, 147–149, 152, 170–172, 171–173 geosynthetics, 149–153, 198–199, 200 hydraulic considerations, 165, 172–178, 174–175, 177, 179–182, 185–186, 193–195, 194–196 material and performance relationship, 144, 144–145, 146–151, 147 mineral precipitation effect, 185–187 performance and material relationship, 144, 144–145, 146–151, 147 permeant interaction effects, 199–201, 201 pilot testing, 170–172, 171–173 porosity, 185–186 PRBs, 167–191, 168–169 reaction tracking, 179, 187–191, 189–191 reactivity, 186–187 selection, 147–149, 152, 168–170 in situ hydraulic conductivity, 193–195, 194–196 structural stability factors, 178, 182, 182–183 vegetation relationship, 163, 165–167, 166–167 vertical cutoff walls, 198–199, 200 water balance designs, 153, 160–163, 161–162, 164–165 Mather, Thornthwaite and, studies, 81, 86 Matsumoto studies, 143n Mavko, Cepic and, studies, 42 Mayer, Blowes and, studies, 327 Mayer studies, 97, 108, 187–188 Maymo-Gatell studies, 99 Mazurek studies, 57 McCann, Klimentos and, studies, 224 McCurdy studies, 57 McDonald adn Harbaugh studies, 119 McIntire studies, 239 McKenzie, Orth and, studies, 93 Measurement accuracy, walls and floors, 123–125 Measures studies, 236 Melchers, Stewart and, studies, 6, 18, 23, 43–45, 47 Melchers studies, 1n, 45, 48, 51, 53–54 Melchior studies, 158, 160 Membrane behavior, clay soils, 126–127, 127 Menezes studies, 143n

Mercer studies, 1n Mergener studies, 187–188, 189 Merry and Bray studies, 26 Methane concentration, 38 Meyer and Gee studies, 20 Meyer and Orr studies, 20 Meyer and Taira studies, 20 Meyer studies, 105 Miller, Blackmore and, studies, 35 Miller and Lee studies, 32 Milne-Home and Schwartz studies, 145 Mineral precipitation effect, 185–187 Minerals, 146–147 Miner studies, 223 Misawa Air Base (Japan), 305 Mitchell, Rumer and, studies, 143, 322, 347 Mitchell studies, 117, 124, 126–127 Mixed criteria, 23, 23 Mixed waste landfill, 312–315 Mochizuki studies, 224 Modeling, fluid transport through barriers anaerobic biodegradation, 98–99 analytical models, 115, 120, 120–123, 123 anions, 129–131, 131 aqueous-phase transport, 112–117, 115 basics, xv, 71 calibration, 88–89 caps, 72–90 clay soils, membrane behavior, 126–127, 127 code quality assurance, 87–88 complexation, 131 complicating factors, 128–132 constant seepage velocity, 128 constant volumetric water content, 128–129 contaminants, 99, 112–123 coupled solute transport, 117–119, 120, 125–126 current practice, 75, 76–80, 81–85, 111–112 data needs, 86–87 dissolved organic carbon, 100–101 downgradient biodegradation processes, 98–101 effective porosity, 129 electron donor production, 100 FEHM, 85 floors, 110–127 geochemical processes and modeling, 92–97, 94–96, 104–109 groundwater hydraulics, 91–92 HELP model, 81 heterogeneities, role, 90 horizontal barriers, 110–111 hydrogen, 99–100

Index hydrologic cycle, 72, 73 HYDRUS-2D, 83 infiltration, arid sites, 90 input parameters, 123–125 inverse modeling, 108–109 layers and features, 74–75 limitations, 86–89, 109–110, 123–127 measurement accuracy, 123–125 membrane behavior, clay soils, 126–127, 127 nonlinear sorption, 129–130 organic contaminant biodegradation, 131–132 performance issues, 72–75 PRBS, 90–110 quality control, 87–88 RAECOM, 85 rate-dependent sorption, 130 reactions, 98, 106–107 reactive transport modeling, 107–108 reduction, contaminant concentration, 99 research needs, 86–89, 109–110, 123–127 role, 86 seepage, 128 SoilCover, 82–83 speciation modeling, 105–106 system dynamics, 101–104, 102–103 temperature effects, 132 time-varying properties and processes, 89–90, 125 TOUGH2, 84–85 transport process, contaminants, 112–123 unresolved challenges, 89–90 UNSAT-H, 82 VADOSE-W, 84 validation and verification, 88–89 vertical barriers, 110 volumetric water content, 128–129 walls, 110–127 water balance method, 75, 81 water flow modeling, 119–120 Modeling limitations caps, 86–89 PRBs, 109–110 walls and floors, 123–127 Models and modeling analytical, 115, 120, 120–123, 123 current practices, 75, 76–80, 81–85, 111–112 damage and system performance prediction, 59–61 fouling model, 189 geochemical models, reaction tracking, 179, 187–191, 189–191

367 inverse modeling, 108–109 subsurface barrier verification, 298, 299 MODFLOW, 119, 188 Moffet Field, see Naval Air Station (NAS) Moffet Field, Mountain View (California) Mohamed studies, 32 Moisture content caps and covers, 269–271, 270, 272 change monitoring methods, 292–294 fiber-optics distributed temperature monitoring, 314 neutron moisture monitoring, 313–315 sampling methods, 294–295 shallow vadose zones, monitoring, 314–315 subsurface barrier verification, 292–295 Monitoring, see also Geophysical method verification; Material stability and applications basics, 2 caps and covers, 262–263, 313 damage and system performance prediction, 59–61 fiber-optics distributed temperature monitoring, 314 geophysical method verification, 239, 240, 242–243, 249 infiltration monitoring, covers, 313 moisture change, 292–294 neutron moisture, 313–314 perfluorocarbon tracers, 338–340, 339 shallow vadose zones, 314–315 verification monitoring, 289, 290–292, 291–296 vertical barriers, 254 Monterey, California, 159–160 Monticello Mill Tailings Repository (Utah), 17–18, 20, 176, 177, 179–182 Moore studies, 20, 287n Moo-Young, Jr., studies, 287n Moo-Young and Zimmie studies, 26 Moo-Young studies, 1n Moraes, Khalil and, studies, 35, 37 Morrison, H.F., studies, 209n Morrison, S.J., studies, 143n Morrison studies, 177, 188, 298, 321, 331 Mountain View, California, 106–107, 109, 185 Moya studies, 236 Muftikian studies, 93 Muller-Kirchenbauer studies, 124 Multi-dimensional case, 51–53, 52–53 Multi-spectral scanners, 232–233, 273 Murray and Quirk studies, 201 Myer, Geller and, studies, 220

368

Barrier Systems for Environmental Contaminant Containment & Treatment

N Naftz studies, 143 Nagel, Smith and, studies, 307 Nanotechnology sensors, 307 NAS, see Naval Air Station (NAS) Moffet Field, Mountain View (California) NASA, 232 NASA Jet Propulsion Laboratory, 234 NASA/Stennis co-sponsored project, 232 Nataf transform, 51 National Aeronautics and Space Administration (NASA), 232 National Department of Energy Vadose Zone Science and Technology Roadmap, 292 National Research Council airborne geophysical methods, 228 aqueous-phase transport, 113 life-cycle decisions, 61 sensor and field analytical techniques, 333–336 sensors for fielded systems, 348 Natural attentuation, 290–291 Natural field and magnetic methods, 215–216, 227–228 Naval Air Station (NAS) Moffet Field, Mountain View (California), 106–107, 109, 185, 234, 327 Nazarali studies, 37 Neutron moisture monitoring, 313–314 Neutron probes, 293 Neutron well logging, 337–338 Newman studies, 71n Nibras, Park and, studies, 131 Nichols studies, 227 Nihei studies, 221 Noonan studies, 236 NRC, see U.S. Nuclear Regulatory Commission (USNRC) Nyhan studies, 28

O Oak Ridge, Tennessee K-25 site, 236, 273 successional sequences, timing, 27 TOUGH2 source code, 85 Y-12 plant, 95, 96, 183, 327 Oak Ridge Airborne Geophysical SystemArrowhead (ORAGS-Arrowhead), 228–229, 229

Oak Ridge Airborne Geophysical SystemHammerhead (ORAGS-Hammerhead), 229 Oak Ridge Airborne Geophysical SystemTransient Electrical Methods (ORAGSTEM), 229–231, 230–231 Oak Ridge National Laboratory (ORNL), 229, 236, 238 Office of Emergency and Remedial Response, 288 Office of Scientific and Technical Information (OSTI), 85 O' Hannesin, Gillham and, studies, 93 O' Hannesin and Gillham, studies, 167, 321 Olhoeft studies, 243 Olsen studies, 117, 126 OPFTIR technology, 278 Optimization, verification needs, 299, 319–320 Orange, Brace and, studies, 226 ORNL, see Oak Ridge National Laboratory (ORNL) Orr, Meyer and, studies, 20 Orth and McKenzie studies, 93 OS3D models, 187 OSTI, see Office of Scientific and Technical Information (OSTI) Othman studies, 152 Oyster (DOE facility), Virginia, 249

P Pacific Northwest National Laboratory, 82, 308 Pankow and Cherry studies, 112 Park and Nibras studies, 131 Parker studies, 71–132 Parkhurst and Appelo studies, 106–109 Parkin, Adamson and, studies, 99 Park studies, 131 Parra studies, 211, 224 Paschle and van der Heijde studies, 105 Peclet number, 121 Pellerin studies, 255, 260 Pelton studies, 243 Penman-Wilson formulation, 82, 84 Percolation, 72, 73, 159–160, 163, 164 Perfluorocarbon tracers, 338–340, 339 Performance and performance factors caps, 72–75 composite barriers, 155–160, 156, 158–159 containment, long-term, 347–348 cutoff walls, 191–201, 192 geophysical method verification, 212–214, 213

Index hydraulic considerations, 165, 172–178, 174–175, 177, 179–182 long-term performance analysis, 7–15 materials and mix composition, 144, 144–145, 146–151, 147 pilot testing, evaluation, 170–172, 171–173 PRBs, 167–194, 168–169 prediction approaches, 11–15 reactive materials, 165, 172–178, 174–175, 177, 179–182 structural stability, 178, 182, 182–183 vegetation and material relationship, 163, 165–167, 166–167 water balance designs, 155, 160–163, 161–162, 164–165 Permeable reactive barriers (PRBs) acoustic wave devices, 331, 331–332 anaerobic biodegradation, 98–99 basics, 90–91, 321–324 caps, 72–90 case histories, 329 contaminants, 99 current practices, 325–329 design verification, 239, 241–242 dissolved organic carbon, 100–101 downgradient biodegradation processes, 98–101 electron donor production, 100 floors, 110–127 flow characterization and monitoring, 325, 326–327, 330–331 geochemical processes and modeling, 92–97, 94–96, 104–109 geochemical process monitoring, 331 geophysical method verification, 239–246, 240 groundwater hydraulics, 91–92 horizontal barriers, 110–111 hydrogen, 99–100 hydrological process monitoring, 331 improvements needed, 325–329 inverse modeling, 108–109 limitations, 109–110 material stability and applications, 167–191, 168–169 monitoring, 239, 240, 242–243 reactions, 98, 106–107 reactive transport modeling, 107–108 reduction, contaminant concentration, 99 regulatory framework, 324–325 requirements, 239 research needs, 109–110 site characterization, 239–241 spatial flow monitoring, 330–331

369 speciation modeling, 105–106 subsurface barrier verification, 321–332 subsurface monitoring, 329 system dynamics, 101–104, 102–103 temporal flow monitoring, 330–331 time-varying properties and processes, 89–90 unresolved challenges, 89–90 verification, 327–332, 328, 330 vertical barriers, 110 walls, 110–127 Permeable reactive barriers (PRBs), material performance factors basics, 167–168, 168–169 durability, 183, 184–185, 185–187 evaluation, 170–172, 171–173 hydraulic considerations, 172–178, 174–175, 177, 179–182, 185–186 mineral precipitation effect, 185–187 pilot testing, 170–172, 171–173 porosity, 185–186 reaction tracking, 179, 187–191, 189–191 reactivity, 186–187 selection, 168–170 structural stability factors, 178, 182, 182–183 vegetation relationship, 165–167, 166–167 Permeant interaction effects, cutoff walls, 199–201, 201 PET, see Potential evapo-transpiration (PET) Peterson studies, 211, 222 Petrov studies, 152 Peyton and Schroeder studies, 81, 86–87 Phillips studies, 95, 97, 183, 188 Piet and Breckenridge studies, 14 Piet studies, 1–62 Pilot testing, 170–172, 171–173 Plummer studies, 109 POC, see Point of compliance (POC) POE, see Point of exposure (POE) Point of compliance (POC), 98, 111–112 Point of exposure (POE), 111–112 Political processes, 6 Polosa studies, 273 Porosity, 185–186, 190 Porter studies, 128 Potential evapo-transpiration (PET), 81 Pratt studies, 191 PRBs, see Permeable reactive barriers (PRBs) Precipitated minerals, 94 Prediction, see Damage and system performance prediction; Modeling, fluid transport through barriers Prediction links, 298, 299

370

Barrier Systems for Environmental Contaminant Containment & Treatment

Prescriptive design criteria, 19–20 Probabilistic risk analysis (PRA), 41–42 Pruess studies, 84 Pseudo-economic criteria, 18 Psychological aspects, 6 Puls studies, 71n, 95, 97, 188, 324, 327, 329 Pyrak-Nolte studies, 223

Q Qualitative analysis, structure-functional failure relationship, 21, 23–24 Quality control, caps, 87–88 Quantification, long-term issues biological processes, 24–29, 25, 29 compliance, 37–42, 39–41 component failure, 34, 44–47, 45–46, 53–54 contaminant release sources, 37–42, 39–41 cyclical stressing mechanisms, 32, 34, 34–37, 36, 38 damage and system performance prediction, 24–58 degradation mechanism categories, 24–37 estimation, long-term failure probabilities, 42–53 event consequences and connectivities, 42 event trees, 42, 44 failures, 42–53 fault trees, 42, 43 intrusive events, 29–30 multi-dimensional case, 51–53, 52–53 random resistance, 45, 47–48, 48 relationship, containment concentrations and risks, 54–58, 55–56, 58 risk assessment, 37–42, 39–41, 54–58, 55–56, 58 simplifications of theory, 48–51 slow physico-chemical processes, 24–29, 25, 29 system failure, 43–44, 53–54 theory simplifications, 51 transient events, 30, 31, 32, 33–34 Quantified risk analysis (QRA), 39, 41 Quigley, Fernandez and, studies, 24 Quirk, Kemper and, studies, 117 Quirk, Murray and, studies, 201

R Rabideau, Rubin and, studies, 121 Rabideau and Khandelwal studies, 111, 114, 116–117, 121–122, 130

Rabideau and Van Benschoten studies, 93 Radar systems, 237–238, 238 Radiation attenuation effectiveness and cover optimization with moisture effects (RAECOM), 85 Radioactive metals, 146–147 Rad studies, 152 RAECOM, see Radiation attenuation effectiveness and cover optimization with moisture effects (RAECOM) Ramirez, Dailey and, studies, 213, 226, 260 Ramirez studies, 255 Random resistance, 45, 47–48, 48 Ranson and Sun studies, 238 Ray tomography, 220–221Rausand, Einarsson and, studies, 24 RCRA, see Resource Conservation and Recovery Act (RCRA) Reactions, 98, 106–107 Reaction tracking, 179, 187–191, 189–191 Reactive test wells (RTWs), 170–172, 172 Reactive transport modeling, 107–108 Reactivity materials, 168–169 PRBs, material performance factors, 186–187 specific gravity, 182 Reddi and Inyang studies, 54, 143 Redente, Bowerman and, studies, 29 Redmond, Shackelford and, studies, 130–131 Reduction, contaminant concentration, 99 Reflected energy, 221 Regulatory criteria, 19, 19 Regulatory framework, 4, 324–325 Relationship, containment concentrations and risks, 54–58, 55–56, 58 Remediation Technologies Development Forum (RTDF), 93, 324 Remote sensing, 216, 231–238 Requirements caps and covers, 262–263 geophysical method verification, 239 vertical barriers, 249 Research needs caps, 86–89 PRBs, 109–110 walls and floors, 123–127 Resistance, random, 45, 47–48, 48 Resource Conservation and Recovery Act (RCRA) design criteria, 19–20 geosynthetics, 152 goals, 288 mixed waste landfill case history, 312–313

Index moisture sampling methods, 294 site characterization, 91 Richards' equation, 82 Rignot studies, 238 Risk contaminant concentrations relationship, 54–58, 55–56, 58 contaminant release source terms, 37–42, 39–41 decision analysis, 2 flow chart, 40 psychological aspects, 6 structure-functional failure relationship, 20–22, 21–22 Roberds, Lockhart and, studies, 298–299 Roberts, Fennelly and, studies, 100 Robertus, Donnegan and, studies, 27 Roesler studies, 156, 159–160, 165 Rogers studies, 85 Roh studies, 95, 183, 298, 331 Role, caps, 86 Rollins, Kemper and, stuides, 117, 126–127 Rosenblatt transform, 51 Rouyn-Noranda (Quebec, Canada), 32 Rowe, Badv and, studies, 128 Rowe, Lake and, studies, 26 Rowe and Badv studies, 128–129 Rowe and Booker studies, 116, 122–123 Rowe and Fraser studies, 57 Rowe and Sargam studies, 160 Rowell studies, 128 Rowe studies, 112, 131–132 Roy and Dzombak studies, 57 RT3D models, 187–188 RTW, see Reactive test wells (RTWs) Rubin, Hubbard and, studies, 227 Rubin and Rabideau studies, 121 Rumer and Mitchell studies, 143, 322, 347 Rummel, Du and, studies, 262, 266 Ryan and Day studies, 145

S Sacramento, California, 165, 166 Safety case concept, 22 Saleem studies, 131 Sanchez studies, 62 Sandia National Laboratory, 312 Sargam, Rowe and, studies, 160 Sass studies, 111, 185, 327 Savannah River site, Aiken (South Carolina), 274, 309 Scanlon studies, 320

371 Scattered energy, 221 Schackelford, Malusis studies, 127 Schackelford and Redmond studies, 130–131 Schaff and Davidson studies, 35 Schoenberg studies, 223 Schroeder, Peyton and, studies, 81, 86–87 Schroeder studies, 119 Schuhmacher studies, 188 Schwartz, Fryar and, studies, 327 Schwartz, Milne-Home and, studies, 145 Seaman studies, 130 Seismic methods geophysical method verification, 214, 216–224, 218–219 vertical barriers, 259 Selection, PRBs, 168–170 Semi-empirical prediction approach, 12–14 Sensors, verification needs, 320, 320–323 Serrato studies, 287n Shackelford, Malusis and, studies, 117–119 Shackelford studies, 24, 71–132 Shackleford, Manassero and, stuides, 122 Shackleford studies, 72–132 Shafer, Bilbrey and, studies, 187 Shakshuki studies, 48 Sheets and Hendrickx studies, 211, 263, 267 Shi studies, 57 Shu studies, 57 Side-looking airborne radar (SLAR), 237 Simplifications of theory, 48–51 SIMS, see Surface ionization mass spectrometry (SIMS) Simultaneous iterative reconstruction tomography (SIRT), 221 Single well imaging, 222–224 SIRT, see Simultaneous iterative reconstruction tomography (SIRT) Site characterization adequacy, 91 caps and covers, 262–263 geophysical method verification, 214–216, 239–241 vertical barriers, 249 Site Characterization and Analysis Penetrometer System (SCAPS), 305 Site hydrology, 91 Siu studies, 38 SLAR, see Side-looking airborne radar (SLAR) Slater and Binley studies, 215, 241–243 Slater studies, 209n Sleep studies, 71–132 Slow physico-chemical processes, 24–29, 25, 29 Smart structures, 300–307 Smith and Nagel studies, 307

372

Barrier Systems for Environmental Contaminant Containment & Treatment

Smith studies, 27, 29 Smyre studies, 238, 273–274 Social aspects, 6 Sodium iodide gamma detector, 295 Software, 76–80 Soil-cement-bentonite (SCB) cutoff walls, 192–193 SoilCover, 82–83 Sorel, Warner and, studies, 173 Sorption characteristics, 146–147 Spanksy studies, 287n Spatial flow monitoring, 330–331 SPAWAR, 332 Speciation modeling, 105–106 Specific methods, geophysical method verification, 216–238 Spirres, Finsterwalder and, studies, 124 SPOT satellite imagery, 273 Staverman studies, 117 Steady-state flux, 122 Steefel and Yabusaki studies, 108 Stella studies, 14 Stern, Bedford and, studies, 224 Stewart and Melchers studies, 6, 18, 23, 43–45, 47 Stewart studies, 223 Stohr studies, 273 STOMP, see Subsurface Transport Over Multiple Phases (STOMP) Storage layers, hydrologic cycle, 75 Stormont studies, 160 Strategic Environmental Research and Development Program, 332 Strength distributions, 36 Stressors, 32, 33–34 Stress-strain behavior, 124 Structural stability factors, 178, 182, 182–183 Structure-functional failure relationship basics, 15–24, 17–18 compliance demonstration, 22 economic criteria, 18 indexing analysis, 21, 23–24 mixed criteria, 23, 23 prescriptive design criteria, 19–20 pseudo-economic criteria, 18 qualitative analysis, 21, 23–24 regulatory criteria, 19, 19 risk criteria, 20–22, 21–22 safety case concept, 22 Subsurface barrier verification acoustic wave devices, 331, 331–332, 333–336 AEMS, 307–308 barrier cap monitoring, 311–312

barrier monitoring case history, 343, 343–346 basics, xv–xvi, 287–288, 348–349 case histories, 312–318, 329, 341–346 colloidal silica, 341–343, 342 containment region adequacy, 347 costs, 309 covers, 310–320 current practice, improvements needed, 297–312, 325–329, 337–340 decision analysis, 299, 299–300 direct push technologies, 305, 306 end states, 309–310 Environmental Restoration Disposal Facility, 343, 343–346 E-SMART network, 304, 304–305 Fernald on-site disposal facility, 315, 315–318, 317 fiber optics distributed temperature moisture monitoring, 314 flow characterization and monitoring, 325, 326–327, 330–331 geochemical process monitoring, 331 goals, 288, 289 hardware, 320, 320–323 hydrological process monitoring, 331 implementation drivers, 309–310 infiltration monitoring, covers, 313 long-term performance, containment, 347–348 LPRMS approach, 302–303, 302–304 methods, 292–296 mixed waste landfill, 312–315 modeling links, 298, 299 moisture, 292–295, 313–315 nanotechnology sensors, 307 neutron moisture monitoring, 313–314 neutron well digging, 337–338 new DOE barrier design code, 308–309 optimization, 299, 319–320 perfluorocarbon tracers, 338–340, 339 PRBs, 321–332 prediction links, 298, 299 regulatory framework, 324–325 sensors, 320, 320–323 smart structures, 300–307 spatial flow monitoring, 330–331 subsurface monitoring, 329 system performance, 298–300 temporal flow monitoring, 330–331 transitioning needed, 297–309 trend analysis, 319–320 uncertainty analysis, 299, 299–300

Index vadose zone monitoring, 295–296, 296, 314–315 verification, 327–329, 328 verification measurement systems, 311 verification monitoring, 289, 290–292, 291–296 verification needs, 318–320, 319, 329–332, 330, 346–348 verification system design, 296–297 walls and floors, 332, 337–348 Subsurface monitoring, 329 Subsurface Transport Over Multiple Phases (STOMP), 308 Suction lysimeter, 294–295 Sullivan studies, 71n Summitville, Colorado, 234, 235 Sun, Ranson and, studies, 238 Superfund Initiative on Long Term Reliability of Containment, 288 Surface geophysical methods, see Geophysical method verification Surface ionization mass spectrometry (SIMS), 191 Suter studies, 29 Systems, see also Damage and system performance prediction dynamics, PRBs, 101–104, 102–103 failure, 22, 43–44, 53–54 management, updating, 60–61, 61 performance, 5–6, 298–300

T Tachavises and Benson studies, 193 Tachavises studies, 193, 196–197 Taira, Meyer and, studies, 20 Tang, Gilbert and, studies, 24 Tausch studies, 110 TCM, see Trichloromethane (TCM) Tedd studies, 125 Telford studies, 225 Temporal flow monitoring, 330–331 Theory simplifications, 51 Thermal scanners, 233, 273–274 Thermocouple psychrometer, 293 Thibodeaux studies, 72 Thornthwaite and Mather studies, 81, 86 Thorstad studies, 157 Time domain reflectometer, 293 Time frames, waste containment performance, 4 Time-varying properties and processes, 89–90, 125 Tinoco studies, 118

373 Tokoz, Kuster and, studies, 223 Tomassoni, Inyang and, studies, 12 Tomography algebraic reconstruction tomography, 221 electrical resistivity tomography, 260, 260–261, 293–294 ray tomography, 220–221 wave tomography, 220–221 Toolbox baseline in situ chemical sensors, 321 groundwater monitoring, 323 in situ chemical sensors examples, 322 tracers, 326–327 water balance, 320 Toomay studies, 237 Topp studies, 266 Toshiba Corporation, 307 Total risk integrated methodology (TRIM), 56, 56 TOUGH2, see Transport of unsaturated groundwater and heat (TOUGH2) Transient events, 30, 31, 32, 33–34 Transitioning, see Current practices Transport of unsaturated groundwater and heat (TOUGH2) caps, 84–85 data needs, 87 source code, 85 Transport process, contaminants, 112–123 Tratnyek, Johnson and, studies, 327 Tratnyek studies, 172, 327–329 Trend analysis, 319–320 Trichloromethane (TCM), 103, 173–175, 186–187, 308 TRIM, see Total risk integrated methodology (TRIM) Tura and Johnson studies, 220–221 Tura studies, 220–221

U Udd studies, 301 Uncertainty analysis, 299, 299–300 United States Corp of Engineers (USACE), 324–325, 331 United States Soil Conservation Society, 87 Unresolved challenges, 89–90 UNSAT-H, 82, 87 Updating, 59–61, 60–61 Uranium Mill Tailings Remedial Action (UMTRA) site, 28 U.S. Department of Defense (USDOD), 332 U.S. Department of Energy (DOE)

374

Barrier Systems for Environmental Contaminant Containment & Treatment

airborne geophysical methods, 228 barrier design code, new, 308–309 design verification systems, 309 geosynthetics, 152 goals, 288 Hanford site cap, 160–163 International Containment Technology Workshop, 321 LIFI project, 236 successional sequences, timing, 27 Y-12 plant, Oak Ridge (Tennessee), 95, 96, 183, 327 U.S. Environmental Protection Agency (USEPA) HELP model, 81 International Containment Technology Workshop, 321 PRBs, 323 regulatory framework, 324–325 risk criteria, 22 total risk integrated methodology, 56, 56 U.S. Navy Space and Warfare Systems Command (SPAWAR), 332 U.S. Nuclear Regulatory Commission (USNRC), 37 USDOE, see U.S. Department of Energy (DOE) USEPA, see U.S. Environmental Protection Agency (USEPA) USNRC, see U.S. Nuclear Regulatory Commission (USNRC)

V V. Rajaram, Black and Veatch Corporation, 1n VADOSE-W, 84, 87 Vadose zone monitoring, 289, 295–296, 296, 314–315 Vadose Zone Science and Technology Roadmap, 292 Validation, caps, 88–89 Van Benschoten, Rabideau and, studies, 93 Van der Heijde, Paschke and, studies, 105 Van Eeckhout studies, 238, 273–274 Van Genuchten, Wierenga and, studies, 129 Van Genuchten and Alves studies, 114, 116 Van Genuchten studies, 87 Vanmarcke studies, 47–48 van't Hoff equation, 118 Vasco studies, 222–223 Vaughan and Calvin studies, 277 Vegetation ecological succession, 26–27 layers, hydrologic cycle, 74

materials relationship, 163, 165–167, 166–167 Verification, see also Geophysical method verification; Subsurface barrier verification caps, 88–89 covers, 318–320, 319 geochemical gradients and zones, 327–329, 328 measurement systems, 311 monitoring, 289, 290–292, 291–296 perfluorocarbon tracers, 338–340, 339 PRBs, 329–332, 330 subsurface, 330 system design, 296–297 vertical barriers, 249–250, 250–253, 252, 254 walls and floors, 330, 346–348 Verruijt, Bear and, studies, 91 Vertical barriers basics, 246–261 case histories, 254–261 cross-hole GPR investigations, 247–248, 255, 257–258, 257–259 design verification, 249–250, 250–253, 252, 254 ERT systems, 260, 260–261 geophysical method verification, 246–261 monitoring, 249, 254 PRBs, 110 requirements, 249 seismic methods, 259 site characterization, 249 Vertical cutoff walls, 198–199, 200 Vertical seismic profiling (VSP), 218, 220, 222–224 Vertical walls, installation, 200 Vincent studies, 238, 272–273 VOCs, see Volatile organic compounds (VOCs) Vogan studies, 95 Volatile organic compounds (VOCs), 129 VSP, see Vertical seismic profiling (VSP)

W Wachsmuth studies, 1n Waite Amulet failings soil cover system, 32 Walker, Cook and, studies, 268 Walls and floors analytical models, 115, 120, 120–123, 123 aqueous-phase transport, 112–117, 115 basics, 110

Index clay soils, membrane behavior, 126–127, 127 contaminants, 112–123 coupled solute transport, 117–119, 120, 125–126 current practice, 111–112 horizontal barriers, 110–111 input parameters, 123–125 limitations, 109–110, 123–127 measurement accuracy, 123–125 membrane behavior, clay soils, 126–127, 127 research needs, 109–110, 123–127 subsurface barrier verification, 332, 337–348 time-varying properties and processes, 125 transport process, contaminants, 112–123 vertical barriers, 110 walls, 110–127 water flow modeling, 119–120 Ward, Gee and, studies, 15 Ward and Gee studies, 160, 263 Ward studies, 209n, 263, 266, 271 Warner and Sorel studies, 173 Warner studies, 143n Water balance caps, 75, 81, 155–156 material stability and applications, 153, 160–163, 161–162, 164–165 sensors, 320 thin cover, 167 Water flow modeling, 119–120 Waugh studies, 29, 62 Wave tomography, 220–221 Webb, Ho and, studies, 84 Weibull relationship, 36 Weiler studies, 265 Weiss studies, 209n Well studies, 238 White studies, 241

375 Wierenga and van Genuchten studies, 129 Wilkens studies, 143n Wilkin studies, 187 Wilson studies, 75, 82, 84, 176, 292, 294, 318 WinUNSAT-H, 82 Woessner, Anderson and, studies, 91 Wolery studies, 106–107 Wolford studies, 13 Wollenhaupt studies, 268 Wright, Conca and, studies, 128

X Xing, Fredlund and, studies, 87 XPS, see X-ray photoelectron spectroscopy (XPS) X-ray diffraction, 191 X-ray photoelectron spectroscopy (XPS), 191

Y Yabusaki, Steefel and, studies, 108 Yabusaki studies, 105, 187–188, 327 Yamamoto studies, 224 Yebusaki studies, 108 Yeung stuides, 117 Yilmaz studies, 266 Y-12 plant, Oak Ridge (Tennessee), 95, 96, 183, 327

Z Zero-valent iron (ZVI), 92–109 Zhu and Anderson studies, 105 Ziegler studies, 124 Ziloli studies, 273 Zimmie, Moo-Young and, studies, 26 Zyvoloski studies, 85

COLOR FIGURE 4.7 Comparison of (a) ORAGS-TEM measurements and (b) an analytic signal map derived from ORAGS-Arrowhead magnetic measurements for a bombing target in South Dakota. TEM represent the first-time gate only, and data were acquired at 3 m nominal flight line spacing and 1.5–2 m altitude. Magnetometer results used the 8-sensor magnetometer system at the same altitude and 12 m flight-line spacing. The response of both systems to an east-trending barbed wire fence is seen across the center of the diagrams. The individual anomalies are associated with M-38 practice bombs, or their fragments. These are sand- or cement-filled devices with a mass of 10–15 kg when intact. Horizontal scale is in meters.

COLOR FIGURE 4.8 HIS (AVIRIS) image cube of Moffett Field, California.

Summitville, Colorado Mining District Fe–Mineral Map U.S. Geological Survey AVIRIS Sept. 3, 1993

Summitville Mine Crospy Mountain N

Alum Creek

Wightman Fork Bitter Creek

Alamosa River

1 KM

Reynolds Tunnel Sludge

K–Jarosite

Na-Jarosite

Hematite

Fe–hydroxide

Goethite

Ferrihydrite

not mapped

COLOR FIGURE 4.9 AVIRIS HIS mapping of Summitville, CO, area.

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COLOR FIGURE 4.29 CMP gathering and velocity analysis at the intersection of transects N1 and E1 in (a) March 2001 and (b) May 2001. Note the changes in the ground wave and reflection character. The vertical white line in each plot shows the optimal antenna separation. (From Clement, W.P. and Ward, A.L., Using ground penetrating radar to measure soil moisture content. Handbook of Agricultural Geophysics, Allred, B.J., Daniels, J.J., and Ehsani, M.R., Eds., CRC Press, Boca Raton, 2003.) (See color version insert for this figure.)