.
UNITED STATES ENVIRONMENTAL PROTECTION AGENCY WASHINGTON D.C. 20460

OFFICE OF THE ADMINISTRATOR SCIENCE ADVISORY BOARD
February 1 7 , 2012

E PA

- SAB

- 12

- 005

T he Honorable Lisa P. Jackson Administrator U.S. Environmental Protection Age ncy 1200 Pennsylvania Avenue, N.W. Washington, DC 20460

Subject: Advisory on EPA’s Draft T echnical Report entitled Considerations Related to Post

Closure Monitoring of Uranium In

- Situ Leach/In

- Situ Recove ry (ISL/ISR) Sites

Dear Administrator Jackson :

The EPA is considering the need to update the environmental protection standards for uranium mining because current regulations, promulgated in response to the Uranium Mill T ailings Radiation Control Act of 1978, do not address the relatively recent proce ss of in

- sit u leaching (ISL) of uranium from underground ore bodies. In the ISL process, an extraction fluid is pumped underground through a set of injection wells to solubilize uranium , is retrieved at a central extraction well, and is then processed to

r emove the uranium and recycle the fluid back in to the ground for further uranium extraction. Because the ISL process affect s groundwater quality, t he EPA’s Office of Radiation and Indoor Air requested advice from the Science Advisory Board (SAB) on issues related to design and implementation of groundwater monitoring at ISL mining sites.

The EPA prepared a draft technical report, Considerations Related to Post

- Closure Monitoring of Uranium In

- Situ Leach/In

- Situ Recovery (ISL/ISR) Sites (dated June 2011)

, that describes a proposed general approach to monitoring at ISL sites and provides case studies and key issues associated with post

- closure monitoring. T he a gency requested SAB recommendations on the technical aspects of designing and implementing the grou ndwater monitoring networks at ISL uranium mines, including wells within the production area to compare post

- and pre

- operational groundwater quality, and wells

ou t side the mine production area to detect the presence or absence of excursion s of the leach at e solution from the production zone

.

T he SAB mak e s recommendations concerning monitoring to characteriz e baseline groundwater quality prior to the start of mining operations

, monitoring to detect any leachate excursion s during mining

, and monitoring to de termine when groundwater quality has stabilized after mining operations have been completed . The SAB also reviews the advantages and disadvantages of alternative statistical techniques to determine whether post

- operational groundwater quality has returned to near pre

- mining conditions and whether mine operation can be predicted not to adversely impact groundwater quality after site closure acceptance..
The EPA draft technical report presents an excellent preliminary framework of considerations applicable to groundwater monitoring at ISL uranium mines. It emphasizes the relevance of Groundwater Monitoring Requirements for Treatment, Storage, and Disposal Facilities (TS D F’s) in 40 CFR Part 264, Subpart F, in response to the Resource Conservation and Recovery Act (RCRA). The draft report also gives examples of ISL groundwater monitoring data and of statistical techniques for comparing post

and pre

- operati onal monitoring data. However, a lthough all pertinent topics are touched upon in the draft report , few top ics contain sufficient detail to guide setting and implementing these standards.

The SAB recommends that the EPA expand greatly this draft technical report so that it is protective and realistic in guiding the monitoring program and evaluating its resu lts. To be a guide for decisions that are based on knowledge of both the general behavior of groundwater constituents and the conditions at the mine under consideration, the draft technical report should include detailed discussion of the following critica l activities by the EPA :

**•** Survey the extensive monitoring data available for ISL uranium mine s to identify data sets suitable for building an evidence base th at could inform EPA’s regulations

.

**•** C ompil e and systematically analyze these data sets to define the geology and hydrology of the site and support modeling of the interactions between pertinent groundwater constituents and associated geologic media

.

**•** Apply environmental models to provide realistic predict ions of the rates at which groundwater constitu tents approach stable conditions following the cessation of mining operations, for a range of realistic bounding conditions

.

**•** D escribe systematic approaches for determining the optimal number, location, and sampling frequency of monitoring wells.

**•** S pecify criteria for selecting groundwater analytes of primary and secondary importance for monitoring by emphasizing the linkages between analytes and monitoring objectives

.

**•** Consider some alternative approaches to the described statistical treatment of difference s between pre

- and post

- mining groundwater quality, and recognize that other factors may have more influence than statistical uncertainty on the reliability of these differences.

The SAB recommends that the EPA organiz e the draft technical report by appl ying the EPA’s Data Quality Objectives process . Further, it advises the EPA to optimiz e the quality and timeliness of the draft technical report by inviting cooperation by the other regulators and participation by the scientific community in addressing the activities identified in the enclosed report

. The SAB appreciates the opportunity to provide advice on the draft technical report and engage in th oughtful dialogue on this topic, and looks forward to your response.

Sincerely,

/Signed/ /Signed/

Dr. Deborah L. S wackhamer Dr. Bernd Kahn Chair Chair, Radiation Advisory Committee Science Advisory Board S cience Advisory Board

Enclosure.

i NOTICE

This report has been writte n as part of the activities of the EPA Science Advisory Board (SAB), a public advisory group providing extramural scientific information and advice to the Administrator and other officials of the En vironmental Protection Agency. The SAB is structured to pr ovide balanced, expert assessment of scientific matters related to problems facing the a gency. This report has not been reviewed for approval by the a gency and, hence, the contents of this report do not necessarily represent the views and policies of the E nvironmental Protection Agency, nor of other agencies in the Executive Branch of the Federal government, nor does mention of trade names of commercial products constitute a recommendation for use. Reports and advisories of the SAB are posted on the EPA web site at http://www.epa.gov/sab

..

ii U.S. Environmental Protection Agency Science Advisory Board Radiation Advisory Committee (RAC) Augmented for Uranium In

- Situ ISL/ISR Advisory

CHAIR

Dr. Bernd Kahn , Professor Emeritu s, Nuclear and Radiological Engineering Program, and Associate Director, Environmental Radiation Center, GTRI, Georgia Institute of Technology, Atlanta, GA

MEMBERS
Dr. Susan M. Bailey, Associate Professor, Colorado State University, Department of Environ mental and Radiological Health Sciences, Fort Collins, CO

Dr. Thomas B. Borak , Professor, Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO

Dr. Shih

- Yew Chen , Senior Environmental Systems Engineer , Environmental Science Division, Argonne National Laboratory, Argonne, IL

Dr. Faith G. Davis , Senior Associate Dean and Director of Graduate Studies, Professor of Epidemiology, Division of Epidemiology and Biostatistics, School of Public Health, Univers ity of Illinois at Chicago, IL

Dr. R. William Field, Professor, Department of Occupational and Environmental Health, College of Public Health, University of Iowa, Iowa City, I A

Dr. Jonathan M. Links , Professor and Deputy Chair, Department of Environment al Health Sciences, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD

Dr. William F. Morgan, Director of Radiation Biology and Biophysics, Biological Sciences Division, Fundamental & Computational Sciences Directorate, Pacific No rthwest National Laboratory, Richland, WA

Mr. Bruce A. Napier, Staff Scientist, Radiological Science & Engineering Group, Pacific Northwest National Laboratory, Richland, WA

Dr. Dale L. Preston , Principal Scientist, Hirosoft International, Eureka, CA

Dr. Daniel O. Stram , Professor, Department of Preventive Medicine, Division of Biostatistics and Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA

CONSULTANTS

Dr. Thomas Borch

, Associate Professor, Enviro nmental Chemistry & Biochemistry, Department of Soil & Crop Sciences, Joint Position in Department of Chemistry, Colorado State University, Fort Collins, CO.

iii Dr. Douglas B. Chambers , Vice President and Director of Risk & Radioacti vity, Senes Consultants, Ltd., Ontario, Canada

Dr. June T. Fabryka Martin , Earth Observations Systems Group

, Los Alamos National Laboratory, Los Alamos, NM

Dr. Thomas E. Johnson , Assistant Professor, Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO

Dr. Brian A. Powell , Assistant Professor, Department of Environmental Engineering & Earth Sciences, L. G. Rich Environmental Laboratory, Clems on University, Anderson, SC

SCIENCE ADVISORY BOARD STAFF
Dr. K. Jack Kooyoomjian , Designated Federal Officer, Science Advisory Board, U.S. Environmental Protection Agency , Washington, DC.

iv 

### U.S. Environmental Protection Agency Science Advisory Board

CHAIR

Dr. Deborah L. Swackhamer , Professor and Charles M. Denny, Jr., Chair in Scienc e, Technology and Public Policy, Hubert H. Humphrey School of Public Affairs and Co

- Director of the Water Resources Center, University of Minnesota, St. Paul, MN

SAB MEMBERS
Dr. George Alexeeff , Acting Director, Office of Environmental Health Hazard Asses sment, California Environmental Protection Agency, Oakland, CA

Dr. David T. Allen , Professor, Department of Chemical Engineering, University of Texas, Austin, TX

Dr. Pedro Alvarez , Department Chair and George R. Brown Professor of Engineering, Department of Civil & Environmental Engineering, Rice University, Houston, TX

Dr. Joseph Arvai , Svare Chair in Applied Decision Research, Institute for Sustainable Energy, Environment, & Economy, Haskayne School of Business, University of Calgary, Calgary, Alberta, Canada

Dr. Claudia Benitez

- Nelson , Full Professor and Director of the Marine Science Program, Department of Earth and Ocean Sciences, University of South Carolina, Columbia, SC

Dr. Timothy J. Buckley , Professor and Chair, Division of Environmental Healt h Sciences, College of Public Health, The Ohio State University, Columbus, OH

Dr. Patricia Buffler , Professor of Epidemiology and Dean Emerita, Department of Epidemiology, School of Public Health, University of California, Berkeley, CA

Dr. Ingrid Burke

, Director, Haub School and Ruckelshaus Institute of Environment and Natural Resources, University of Wyoming, Laramie, WY

Dr. Thomas Burke , Professor, Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Johns Hopkin s University, Baltimore, MD

Dr. Terry Daniel , Professor of Psychology and Natural Resources, Department of Psychology, School of Natural Resources, University of Arizona, Tucson, AZ

Dr. George Daston , Victor Mills Society Research Fellow, Product Safety and Regulatory Affairs, Procter & Gamble, Cincinnati, OH

Dr. Costel Denson , Managing Member, Costech Technologies, LLC, Newark, DE.

v Dr. Otto C. Doering III , Professor, Department of Agricultural Economics, Purdue University, W. Lafayette, IN

Dr. Michael Dourson , President, Toxicology Excellence for Risk Assessment, Cincinnati, OH

Dr. David A. Dzombak , Walter J. Blenko, Sr. Professor of Environmental Engineering, Department of Civil and Environmental Engineering, College of Engineering, Carnegie Mellon U niversity, Pittsburgh, PA

Dr. T. Taylor Eighmy , Vice President for Research, Office of the Vice President for Research, Texas Tech University, Lubbock, TX

Dr. Elaine Faustman , Professor and Director, Institute for Risk Analysis and Risk Communication, Sc hool of Public Health, University of Washington, Seattle, WA

Dr. John P. Giesy , Professor and Canada Research Chair, Veterinary Biomedical Sciences and Toxicology Centre, University of Saskatchewan, Saskatoon, Saskatchewan, Canada

Dr. Jeffrey K. Griffith s , Professor, Department of Public Health and Community Medicine, School of Medicine, Tufts University, Boston, MA

Dr. James K. Hammitt , Professor, Center for Risk Analysis, Harvard University, Boston, MA

Dr. Barbara L. Harper , Risk Assessor and Environm ental

- Public Health Toxicologist, and Division Leader, Hanford Projects, and Program Manager, Environmental Health, Department of Science and Engineering, Confederated Tribes of the Umatilla Indian Reservation (CTUIR), West Richland, WA

Dr. Kimberly L. Jo nes , Professor and Chair, Department of Civil Engineering, Howard University, Washington, DC

Dr. Bernd Kahn , Professor Emeritus and Associate Director, Environmental Radiation Center, Georgia Institute of Technology, Atlanta, GA

Dr. Agnes Kane , Professor and Chair, Department of Pathology and Laboratory Medicine, Brown University, Providence, RI

Dr. Madhu Khanna , Professor, Department of Agricultural and Consumer Economics, University of Illinois at Urbana

- Champaign, Urbana, IL

Dr. Nancy K. Kim , Senior Executive, Health Research, Inc., Troy, NY

Dr. Cecil Lue

- Hing , President, Cecil Lue

- Hing & Assoc. Inc., Burr Ridge, IL

Dr. Floyd Malveaux , Executive Director, Merck Childhood Asthma Network, Inc., Washington, DC.

vi Dr. Judith L. Meyer , Professor Emeritus, Odum School of Ecology, University of Georgia, Lopez Island, WA

Dr. James R. Mihelcic , Professor, Civil and Environmental Engineering, University of South Florida, Tampa, FL

Dr. Christine Moe , Eugene J. Gangarosa Professor, Hubert Department of Global H ealth, Rollins School of Public Health, Emory University, Atlanta, GA

Dr. Horace Moo

- Young , Dean and Professor, College of Engineering, Computer Science, and Technology, California State University, Los Angeles, CA

Dr. Eileen Murphy , Director of Research and Grants , Ernest Mario School of Pharmacy, Rutgers University, Piscataway, NJ

Dr. James Opaluch , Professor and Chair, Department of Environmental and Natural Resource Economics, College of the Environment and Life Sciences, University of Rhode Island, Kingston, RI

Dr. Duncan Patten , Research Professor, Hydroecology Research Program , Department of Land Resources and Environmental Sciences, Montana State University, Bozeman, MT

Dr. Stephen Polasky , Fesler

- Lampert Professor of Ecological/Environmental E conomics, Department of Applied Economics, University of Minnesota, St. Paul, MN

Dr. C. Arden Pope, III , Professor, Department of Economics, Brigham Young University , Provo, UT

Dr. Stephen M. Roberts , Professor, Department of Physiological Sciences, Dir ector, Center for Environmental and Human Toxicology, University of Florida, Gainesville, FL

Dr. Amanda Rodewald , Professor of Wildlife Ecology, School of Environment and Natural Resources, The Ohio State University, Columbus, OH

Dr. Jonathan M. Samet , P rofessor and Flora L. Thornton Chair, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA

Dr. James Sanders , Director and Professor, Skidaway Institute of Oceanography, Savannah, GA

Dr. Jerald Sc hnoor , Allen S. Henry Chair Professor, Department of Civil and Environmental Engineering, Co

- Director, Center for Global and Regional Environmental Research, University of Iowa, Iowa City, IA

Dr. Gina Solomon , Senior Scientist, Health and Environment Prog ram, Natural Resources Defense Council, San Francisco, CA

Dr. Daniel O. Stram , Professor, Department of Preventive Medicine, Division of Biostatistics, University of Southern California, Los Angeles, CA.

vii Dr. Peter Thorne , Professor and Head, Occupational and Environmental Health, College of Public Health, University of Iowa, Iowa City, IA

Dr. Paige Tolbert , Professor and Chair, Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA

Dr. John Vena , Professor and Department Head, Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA

Dr. Robert Watts , Professor of Mechanical Engineering Emeritus, Tulane University, Annapolis, MD

Dr. R. Thomas Zoeller , Professor, Department of Biology, University of Massachusetts, Amherst, MA

SCIENCE ADVISORY BOARD STAFF

Dr. Angela Nugent , Designated Federal Officer, Science Advisory Board, U.S. Environmental Protection Agency, Washington, DC.

viii TABLE OF CONTENTS

Acronyms, Symbols and Abbreviations

................................ ................................ ................................ .. x

1. EXECUTIVE SUMMARY

................................ ................................ ................................ .................. 1

2. INTRODUCTION

................................ ................................ ................................ ................................ 6

2.1. B ACKGROUND ON I N

- S ITU L EACHING M INING

................................ ................................ ............ 6 2.2. T HE SAB R EVIEW P ROCESS

................................ ................................ ................................ ......... 7

3. DESIGNING AND IMPLEMENTING A MONITORING NETWORK

................................ ....... 8

3.1. I NTRODUCTION

................................ ................................ ................................ ............................ 8 3.2. E VIDENCE

- B ASED D ECISION

- M AKING

................................ ................................ ......................... 8 3.3. G UIDING P RINCIPLES AND A SSUMPTIONS FOR R EGULATORY M ONITORING

................................ . 9 3.4. I NDICATORS OF I NTEREST

................................ ................................ ................................ ............ 9 3.5. C ONSTITUENT I NTERACTIONS AND E NVIRONMENTAL T RANSFORMATIONS

................................ . 9 3.6. S PATIAL AND T EMPORAL S AMPLING D ENSITIES

................................ ................................ ........ 10 3.7. H YDRO

- GEOCHEMICAL M ODELING

................................ ................................ ............................ 11 3.8. E STABLISHING B ASELINE G ROUNDWATER C HEMISTRY

................................ ............................. 14 3.9. P OST

- C LOSURE M ONITORING

................................ ................................ ................................ .... 14 3.10. A NALOGOUS S YSTEMS

................................ ................................ ................................ ............... 15 3.11. S TANDARDIZED T ERMINOLOGY

................................ ................................ ................................ . 15

4

. PRE

- OPERATIONAL MONITORING

................................ ................................ .......................... 17

4.1. B ACKGROUND I NFORMATION C ONSIDERED BY THE SAB

................................ .......................... 17 4.2. D EFINING D ATA Q UALITY O BJECTIVES FOR B ASELINE C HARACTERIZATION

............................ 17 4.3. B ASELINE C HARACTERIZATION P ARAMETERS

................................ ................................ ........... 18 4.4. D RILLING AND W ELL C ONSTRUCTION P RACTICES

................................ ................................ ..... 20 4.5. C HALLENGES FOR B ACKGROUND C HARACTERIZATION

................................ ............................. 20 4.6. F REQUENCY AND D URATION OF M ONITORING TO D ETERMINE B ACKGROUND

.......................... 22 4.7. S TANDARDIZED D ATA C OLLECTION

................................ ................................ .......................... 23

5. POST

- OPERATIONAL MONITORING AND RESTORATION

................................ ............... 24

5.1. I NTRODUCTION AND O VERVIEW

................................ ................................ ................................ 24 5.2. D EFINING R ESTORATION G OALS

................................ ................................ ................................ 24 5.3. E VALUATION OF E XISTING D ATASETS

................................ ................................ ....................... 24 5.4. C RITERIA FOR C OLLECTION AND A NALYSIS OF M ONITORING D ATA

................................ .......... 26 5.5. D URATION OF P OST

- M INING /R ESTORATION M ONITORING

................................ ........................ 27 5.6. G ROUPING C ONSTITUENTS FOR M ONITORING A CTIVITIES

................................ ......................... 28 5.7. H AZARD Q UOTIENT OR OTHER R ISK

- W EIGHTING S CHEME FOR D ETERMINING R ELEVANT A NALYTES

................................ ................................ ................................ ............................. 28

6. STATISTICS, DATA REQUIREMENTS AND USE

................................ ................................ .... 29

6.1. D ESIGN OF W ELL P LACEMENT AND S AMPLING P ROGRAM

................................ ......................... 29 6.2. S TATISTICAL A NALYSIS D ISCUSSION

................................ ................................ ......................... 30

7. ADDITIONAL ISSUES BEYOND THE CHARGE

................................ ................................ ....... 3 5

7.1. M ONITORIN G OF O THER ISL I MPACTS

................................ ................................ ....................... 35.

ix 7.2. P OTENTIAL I MPACTS ON G ROUNDWATER U SABILITY

................................ ................................ 35 7.3. E STABLISHING D ATA Q UALITY O BJECTIVES

................................ ................................ .............. 36 7.4. I NTEGRATION WITH O THER EPA R EGULATORY P ROGRAMS A PPLICABLE TO G ROUNDWATER Q UALITY

................................ ................................ ................................ ..... 36 7.5. T APPING E XISTING R ESOURCES FOR E NVIRONME NTAL M ODELING

................................ ........... 37 7.6. W ORKING R ELATIONSHIP WITH THE N UCLEAR R EGULATORY C OMMISSION

.............................. 38 7.7. P ROMOTING P REDICTABILITY AND R EDUCING U NCERTAINTY IN U RANIUM M INING S TANDARDS

................................ ................................ ................................ ........................... 38

REFERENCES

................................ ................................ ................................ ................................ ........ 39

APPENDIX A. EPA CHARGE TO THE SAB

................................ ................................ .................. A

- 1

APPENDIX B. WATER QUALITY PARAMETERS FOR GROUNDWATER MONITORING AT ISL URANIUM MINING SITES

................................ ................................ B

- 1.

x 

### A cronyms, Symbols and Abbreviations

ACLs Alternate Concentration Limits Ca 2 UO 2 - (CO 3 ) 3 Calciu m u ranyl c arbonate t ernary c omplex CFR U.S. Code of Federal Regulations COC Contaminant of Concern CREM Council for Regulatory Environmental Modeling CrunchFlow Software package for multicomponent reactive flow and transport **∆** Delta (differences) for a g iven criterion or allowed value; or a null value **δ** Del; measured difference DQO Data Quality Objective Eh Oxidation/reduction potential compared to that of hydrogen EPA Environmental Protection Agency (U.S. EPA) EXAFS E xtended X

- ray abs orption fine struct ure HA Health Advisories ISL In

- Situ Leach ISR In

- Situ Recovery MCL Maximum Concentration Level MCLG Maximum Concentration Level Goals MIN3P General purpose f low and reactive transport code for variably saturated media MKB Models Knowledge Base MNA Monitor ed natural attenuation NACEPT National Advisory Council for Environmental Policy and Technology NAS National Academy of Sciences ND North Dakota NM New Mexico NRC Nuclear Regulatory Commission (U.S. NRC) ORIA Office of Radiation and Indoor Air (U.S. EPA/O RIA) ORNL Oak Ridge National Laboratory ORP Oxygen / reduction p otential
p Probability v alues ( p 1 , p 2 , ....p n ) pH Negative Log Concentration of Hydrogen Ions PHREEQC U

. S

. G eological S urvey c omputer c ode for speciation, batch

reaction, one

- dimensional transpor t and inverse geochemical calculations PAA Production Authorization Area RCRA Resource Conservation and Recovery Act RSL Regional Screening L evels SAB Science Advisory Board (U.S. EPA/SAB) SDWA Safe Drinking Water Act SMCL Secondary Maximum Concentration L evel TAC Texas Administrative Code TCEQ Texas Commission on Environmental Quality TSDF Treatment, Storage and Disposal Facilities TX Texas.

xi UIC Underground Injection Control UMTRCA Uranium Mill Tailings Radiation Control Act of 1978 USGS U.S. Geological S urvey XPS X

- ray absorption spectroscopy XRD X

- ray fluorescence analysis.

1 

### 1. EXECUTIVE SUMMARY

The EPA is currently reviewing its regulations that establish environmental protection standards for uranium and thorium mill tailings ( 40 CFR Part 192 ) to determin e if revisions are necessary in light of current mining practices. The standards are promulgated by EPA under the Uranium Mill Tailings Radiation Control Act of 1978 (UMTRCA)

. T he Nuclear Regulatory Commission (NRC), or the NRC Agreement State in which the mine is located, issues and oversees the mine operating licenses. The original UMTRCA regulations

, written in 1983 and revised in 1995

, focused on surface and underground mining of uranium, which at that time were the prevalent type s of uranium extraction

. Currently, in situ leaching (ISL) is a common method of uranium extraction. ISL operations involve injection of uranium extraction fluids into subsurface ore bodies. Hence, the EPA is considering establishing standards applicable to groundwater monitorin g systems at and around ISL facilities.

The EPA’s Office of Radiation and Indoor Air (ORIA) has prepared a draft technical report, Considerations Related to Post

- Closure Monitoring of Uranium In

- Situ Leach/In

- Situ Recovery (ISL/ISR) Sites, dated June 2011. The draft technical report provides background information concerning the objectives, design, and implementation of groundwater monitoring systems for ISL/ISR operations. Monitoring wells positioned outside the production area are used to detect excu rsions of leach solution from the production area during the operational phase. Monitoring wells within the production area are used pre

- operationally to establish baseline conditions and post

- operationally to determine when physical and chemical condition s in groundwater have been restored and stabilized. Part 1 of the EPA draft technical report presents the overall approach , including the regulatory context for EPA’s standards under UMTRCA ; Part 2 provides detail s on specific issues associated with the ap proach , including monitoring at existing ISL facilities, establishing post

- operation al steady state, performing statistical analys e s to compare pre

- and post

- operation al conditions, and describing encountered post

- closure performance issues.

The EPA requ ested that the Science Advisory Board (SAB) provide feedback on the draft technical report and respond to four charge questions. The first charge question requests comments on the technical aspects of designing and implementing the groundwater monitoring n etworks described in the report, and identi fication of any omitted or mis

- characterized technical considerations. The remaining questions relate to characterization of baseline groundwater quality in pre

- operational monitoring and the monitoring duration n eeded; approaches for monitoring post

- operation al phases and determining when groundwater quality has stabilized adequately based on post

- operational monitoring data; and statistical techniques and data requirements to compare post

- to pre

- operational (bas eline) monitoring for determining whether groundwater quality has met the applicable regulatory standards

.

The SAB f inds the draft technical report to be an excellent framework of considerations applicable to groundwater monitoring at ISL uranium mines. A pplication of statistics and the Resource Conservation and Recovery Act (RCRA) regulations to groundwater monitoring is discussed in detail. Other important aspects are mentioned, e.g., planning, well location, sampling frequency, selection of analytes fo r monitoring , and modeling, but are not discussed in sufficient detail.

The SAB recommends that the EPA greatly expand its discussion of specified topics in the draft technical report to provide a more substantive foundation for developing and evaluating EPA standards related to ISL uranium mining . The draft technical report should be a guide for effectively and realistically protecting the environment and human health by combining general information on the.

2 behavior of groundwater constituents with specif ic information on their concentrations and concentration changes at the mine.

Two critical interrelated aspects of the draft technical report that would benefit from enhancement concern the availability of environmental data and application of models. To build an evidence base adequate for inform ing EPA’s regulations

, the SAB recommends that the EPA survey the extensive data collected at ISL uranium mining sites by monitoring, regulatory, and research groups, and that it compile systematically those data t hat are of suitable scope and quality to support modeling interactions between pertinent groundwater constituents and associated geologic media . A closely

- related topic is the application by the EPA of environmental models to predict the groundwater’s appr oach to stable conditions following the end of mining operations . Examples of applying such models for a range of realistic bounding conditions would be a useful addition to the draft technical report . Another modeling topic is that the EPA apply statistic al model s to support decisions concerning the optimal number, location, and sampling frequency of monitoring wells.

Another topic is identifying criteria for selecting analytes of primary and secondary importance for monitor i ng and listing their required detection limits and data precision. The examples of groundwater monitoring data sets presented in attachments to the draft technical report will be far more instructive when accompanied by a gency comments concerning their virtues, shortcomings, and appli cability beyond the specific mine to the broad category of monitoring ISL uranium mines. In an integrated program of monitoring and modeling with built

- in feedback, monitoring results are used to validate the model, while model output is used to assure app ropriate monitoring system design.

Regarding the discussion in the draft technical report of statistical approaches for evaluating the reliability of difference between post

- and pre

- mining measurements of groundwater constituent concentrations, the EPA s hould address two additional aspects. For certain purposes, parametric models and Bayesian methodology can be useful alternatives to the presented non

- parametric statistical treatment. More broadly, a well

- designed sampling program and reliable measurement s can be far more important than the statistical uncertainty in assuring reliable results.

The EPA is encouraged to address its technical objectives systematically by applying the EPA’s Data Quality Objectives (DQO) approach

, and to address them efficient ly by including participants from other regulatory agencies and the research community. In the near term, the EPA can develop a set of guiding principles and assumptions to specify its concept of an appropriate groundwater monitoring system, within the lim itations of the information currently available to the A gency. Over the long term, e.g., a 3

- to 5

- year period, a reasonable target would be to have in place a systematic data base and validated models with defined precision and limitations that can be use d as a basis for ISL uranium mine standards and decisions concerning post

- mining stability of groundwater quality.

T he SAB offers the following specific recommendations which are discussed in the report in more detail

..

3 Designing and Implementing a Monito ring Network ( Charge Question 1 ) :

**•** Develop a long

- term ( e.g., 3

- 5 year) program of data analysis and model development for defining the geology and hydrology of the site as a basis for setting evidence

- based standards ( s ee s ection 3.2);

**•** In the near

- term, ar ticulate a set of guiding principles and assumptions for standards setting ( see

s ection 3. 3 ) ;

**•** Identify indicators, both chemical and radioactive, for establishing conditions pre

- and post

operationally ( see s ection s 3. 4

, 4.3);

**•** Specify criteria by which to distinguish between primary and secondary indicators on basis of risk, return to pre

- operati onal or other predetermined conditions, and information concerning other constituents ( see s ection 3.4);

**•** Discuss in detail the many factors that affect interaction s and transformations during and after operation ( see s ection 3.5);

**•** Obtain and analyze g eological and mineralogical data to support decisions based on groundwater monitoring ( see s ection s 3. 5 , 5 .5 );

**•** Before adequate modeling has been developed, specify a s ufficiently dense spatial and temporal monitoring system to assure collecting sufficient data for pre

- and post

- mining comparison ( see

s ection 3. 6 );

**•** Consider applying available groundwater models relevant to ISL uranium mines ( see s ection s 3. 7 , 7.5 );

**•** Supp ort research for providing both empirical values and model coefficients for understanding the approach to stability after ISL uranium mining ( see s ection 3. 7 );

**•** Develop individual modules if needed to reduce the complexity of groundwater models ( see

s ection 3. 7 ) ;

**•** Devote at least as much effort to defin ing baseline groundwater conditions as to post

- operational trend monitoring see s ection s 3. 8 , 5.6 ); and

**•** Prepare a glossary of uniform definitions for use by pertinent regulatory agencies and mine operators ( see s ection 3. 1 1 ).
Establishing Baseline Conditions ( Charge Question 2 ) :

**•** Define monitoring objectives of baseline characterization within the framework of the Data Quality Objective ( DQO ) approach ( see s ection s 4.2 , 7.3 );

**•** Identify groundwater constituents and parameters pertinent for monitoring , not limited to those with regulatory limits but also including non

- hazardous constituents that can affect the behavior of , or serve as surrogates for, con s tituents of interest ( see s ection 4.3);.

4 **•** Consider challenging an d fluctuating ambient circumstances in baseline characterization ( see

s ection s 4.5 , 3. 4 );

**•** Build in flexibility to modif y the design and implementation of monitoring program s as new information becomes available ( see s ection 4.6); and

**•** Apply consistent samp le collection techniques, record keeping, and data compilation ( see s ection 4. 7 )

.
Post

- Mining and Restoration Monitoring ( Charge Question 3 ) :

**•** Carefully qualify the meaning of “return to pre

- operational groundwater quality” ( see s ection s 5.2, 3. 1 1 );

**•** Develop a set of guiding principles for crafting standards ( see s ection s 5.2 , 3. 3 );

**•** Combine the extensive existing data sets with knowledge of constituent interactions in the rock /water system to model post

- mining approach to stability ( see s ection s 5.3 , 3.2 );

**•** Ma tch sampling frequency and duration to information needs for model confirmation ( see

s ection 5. 5 );

**•** Collect sufficien t pre

- operational groundwater monitoring data to support reliable post

operational decision making ( see s ection s 5. 6
, 3. 8 ) ;

**•** Discus s implica tions of data presented in tables in the A ttachment s to the draft technical report ( see s ection 5. 7 ); and

**•** Apply a risk

- weighting system in determining acceptability of groundwater quality at ISL uranium mines ( see s ection s 5. 7

, 3.4 ).
Statistical Techniqu es ( Charge Question 4 ) :

**•** Present a survey of methods to determine sufficient well number and density ( see s ection s 6.1

, 3. 6 ); and

**•** Select statistical evaluation approach in terms of strengths and weaknesses to suit questions to be answered ( see s ection 6.2).

Addi tional Advice Beyond the Charge

The SAB also commented on several topics b eyond the charge to support preparation of the enhanced draft technical report . These topics concerned:

**•** Monitoring media other than groundwater for potential contaminants ( see s ection 7.1) ;

**•** Considering plans for groundwater use that may be impacted by ISL uranium mining ( see s ection 7.2) ;

**•** Elaborating on recommendations for applying the DQO framework to establishing technical approaches to standard setting ( see s ection 7.3);.

5 **•** Addin g other considerations for integrating EPA requirements with existing EPA regulatory
programs ( see s ection 7.4);

**•** Tapping available resources for the recommended modeling ( see s ection 7.5);

**•** Encouraging the working relation of EPA staff with NRC or state age ncy staff ( see s ection 7.6) ; and

**•** T he importance of this regulatory review and update ( see s ection 7.7)

..

6 

### 2. INTRODUCTION

2.1. Background on I n - Situ Leaching Mining Uranium mining by in

- situ leaching ( ISL ) was developed during the past 50 years (U.S. Bureau of Mi nes, 1981; Charbeneau 1984; U.S. EPA 2008) and the first commercial ISL mine was licensed in 1975. Currently, ISL mining is preferred to surface and underground mining for a suitably contiguous ore body located in a porous aquifer between effective confini ng layers . Although uranium mining in the United States has been quiescent during the past decade, potential mine operators have expressed renewed interest in uranium mining by ISL. Following the July 18

- 19, 2011 public face

- to

- face meeting,

a meeting part icipant provided a list of 32 former or currently active ISL mines as well as an additional 16 sites for which ISL license applications ha d been submitted (John Cash, personal communication, September 7, 2011)

. These estimates appear largely consistent wit h publicly available information about uranium recovery licenses and license applications under the purview of the NRC ( http://www.nrc.gov/materials/uranium

- recovery/license

- ap ps.html ) and Agreement States, primarily Texas

, in which licenses are issued by the Texas Commission on Environmental Quality (TCEQ) ( http://www12.tceq.state.tx.us/crpub/ ).

In the ISL mining process, a uranium

- solubilizing extraction fluid (i.e., lixiviant ) is delivered to the subsurface ore body through a set of injection wells and is withdrawn at a central recovery well. A n ISL mine consists of m any such units. The recovered lixiviant is c ontact ed at a surface facility with ion

exchange or solvent extraction media to extract the dissolved uranium, restored to its initial extraction strength, and returned through the injection wells for further uranium dissolution and extraction. The mining process is terminated after a period of time (that may exceed 10 years) when the operator deems th at product ion no longer is profitable. The lixiviant then is replaced by groundwater (possibly augmented by suitable reagents) that initially is cycled through the injec tion and recovery wells (“pump and treat”) to restore the site groundwater to its pre

- operational quality.Water from early restoration cycles that contain s residual lixiviant is most often treated with reverse osmosis and returned to the wellfield (John Ca sh, written communication, December 20, 2011) . Brine generated from the reverse osmosis treatment is typically sent to an evaporation pond or pumped in to a disposal well.

According to a simplified concept, the uranium

- solubilizing reagent s in the lixivia nt function by oxidizing uranium (IV) to uranium (VI) and forming soluble complex es with the resulting uranium ion; reagents such as oxygen plus carbon dioxide gases are used because they are effective and have less of an impact on the aquifer than do other harsher chemicals

. Other reagents such as hydrogen peroxide, ammonia, bicarbonates

, and acids will also leach uranium. Restoring groundwater quality after mining by flushing the aquifer with water

, with water plus reagents intended to restore water quality , or by natural attenuation (without human intervention) are alternatives that have been considered . If additional restoration efforts are needed, reagents may be added to reduce uranium to its original insoluble uranium (IV) form, and to make insoluble any other ions, such as arsenic and molybdenum, that were dissolved or released by the lixiviant. In practice, the ongoing processes in the ground during mining and restoration are considerably more complex, as must be the efforts to return the system to its original form.
Regulation of radiological and non

- radiological hazards associated with uranium and thorium ore processing involves multiple federal agencies. Under the Uranium Mill Tailings Radiation Control Act of 1978 (UMTRCA)

, t he EPA has the responsi bility to establish health and environmental protection standards in 40 CFR Part 192. The NRC in 10 CFR Part 40

— or an agency in its Agreement State

— controls mine operation under UMTRCA at active ( Title II ) sites by license conditions and guidance.

7 (U.S. NRC 2003). The U.S. Department of Energy ( DOE ) is responsible for control of inactive (Title I ) mining and milling sites.

Before ISL mining operations can begin

, the aquifer in which ISL mining is proposed to take place must be designated an “ exempted aquife r ” by the EPA, meaning the aquifer is exempt from the requirements for protection of groundwater as an underground source of drinking water under the Safe Drinking Water Act (SDWA) (see Section 7.2)

. Secondly, the ISL mine operator must obtain permits for lixiviant injection wells from the EPA’s Underground Injection Control (UIC) program developed pursuant to the SDWA (in some cases, the authority to issue UIC permits has been delegated to states) (EPA 2011a). The mine operator must monitor groundwater bef ore starting mining operation s, in order to establish the groundwater quality baseline within and around the mine units , and must continue to monitor groundwater during and after operation al phases in order to detect pollutant excursion beyond the mine uni ts

. Post

- operation al groundwater quality then must be monitored on site until it becomes acceptable or reaches steady state. This finding signals that no further monitoring is needed to detect constituent instability within the mining area. The EPA, in sup port of revising 40 CFR Part 192, intends to establish standards for determining t he duration of monitoring for those substances of which steady

- state attainment and/or return to pre

- operational quality is required.

2.2. The SAB Review Process The EPA requeste d technical advice in the form of an Advisory Review from the SAB to support revision of 40 CFR Part 192 regarding issues relevant to groundwater monitoring for both stable and radioactive substances at ISL uranium mining sites. The charge from the EPA (Ap pendix A) focus es on achieving reliable analyte results

-- both radiological and non

- radiological

-- in groundwater monitoring before, durin g, and after ISL mining. In particular, the charge asks for advice on i mportant aspects that contribute to confidenc e in data reliability : (1) monitoring network design ; (2) effective baseline monitoring ; (3) restoration

- phase monitoring to define trends in groundwater constituents and ultimate arrival at stability ; and (4) use of appropriate statistical techniques and data processing for reliable conclusions. As background for the SAB, the agency developed a draft technical report
, Considerations related to post

- closure monitoring of uranium in

- situ leach/in

- situ recovery (ISL/ISR) sites (dated June 2011), to describe t he proposed overall approach and specific monitoring issues. The draft technical report addresses groundwater monitoring for both stable and radioactive substances. It is concerned principally with designing a monitoring program and comparing post

- and pre

- operational monitoring data. It specifies 5 successive phases of groundwater monitoring: baseline (pre

- operational), mining (operational), restoration (immediate post

- operational), steady state attainment (post

- treatment) and long

- term stability assuranc e (post

- closure). For the crucial action of comparing post

- and pre

operational data, the report discusses applicable statistical techniques for indicating that the two data sets are or are not identical. Some data sets submitted by ISL mine operators to t he licensing agency are attached to the EPA’s draft technical report as examples. To respond to the EPA charge, the SAB ’s Radiation Advisory Committee (RAC)

— augmented with additional experts in the areas of environmental statistics, geochemistry (including soil chemistry), geology, geostatistics, hydrogeology, environmental monitoring, and radiation health science

— held public meetings on July 12, July 18

- 19, September 6, and October 5, 2011 to receive technical briefings from the agency, hear public comment s, and deliberate on the charge questions. Public commenters, including a hydrogeologist from the NRC, identified useful sources of information related to groundwater monitoring at ISL uranium mines. The augmented RAC’s draft advisory report was
pr ovided t o the chartered SAB in November for review and disposition in a December 21, 2011 public meeting..

8 

### 3. DESIGNING AND IMPLEMENTING A MONITORING NETWORK

Charge Question 1: Comment on t he technical areas described in the report and their relative importance for designing and implementing a monitoring ne t work. Identify any tech nical considerations that have been omitted or mis

- characterized

.
3.1. Introduction For purposes of this report, the SAB treats the concept of a “monitoring network” as:

**•** a spatially

- distribut ed network of monitoring wells ;

**•** a time

- dependent series of measurements via those wells ;

**•** a set of constituent indicators that are quantified ;

**•** additional geophysical and geochemical measures made or assumed ; and

**•** underlying conceptual and/or kinetic models t hat :

o provide the technical basis for network design and implementation, and

o make use of the data collected from wells in the network

.

T he SAB makes two general recommendations

– one long

- term ( Section 3.2) , and one for the near term ( Section 3.3)

– as w ell as several specific recommendations ( Section s 3.4 to 3.1 1 )

.
3.2. Evidenc e - Base d Decision

- Making

The SAB recommends that t he scientific/technical approach to designing and implementing a monitoring network for ISL uranium mining sites be evidence

- based, or a t least evidence

- informed. The discussion with EPA staff, NRC staff , and members of the public associated with ISL uranium mining operations during the face

- to

- face meeting suggested that considerable monitoring data pertinent to designing and implementing groundwater monitoring network s are available but that only a limited fraction of this information was incorporated in to the draft technical report. E mpirical site

- specific approaches form the bas i s of discussions in the draft technical report and were em phasized during the presentations

. D ata would need to be collected

, organized , and analyzed in a comprehensive and standardized way (e.g., via standard ized reporting protocols) in order to build the evidence base to inform the regulatory approach , as sketc hed in a flow chart in Figure 1 (at the end of Section 3)

. Accordingly, the SAB r ecommend s for the long term that EPA initiate and maintain a formal process to build this evidence base in , say, 3 to 5 years. Most importantly, the information should cont ribute to defining the geology and hydrology of the site. Ideally, t he data to be collected should include (1) the constituents used for baseline characterization, (2) constituent concentrations observed immediately upon completion of mining but prior to r estoration, and (3) concentration trends observed as the groundwater approaches acceptable and sustainable conditions following restoration

. D ata from monitoring wells, including information on excursions during operation and subsequent recovery, should be gathered to provide examples of the groundwater situation.

The extensive data reported to be available are not in one place or in one format , nor of equal quality

. M ining companies have accumulated baseline data to support the mining license applicatio ns and to justify the proposed moni toring network design to the regulator

. These data can be used for validation in hydro

- geochemical modeling efforts to aid in determin ing system behavior during baseline, operational, and post

- operational stages. Even for hydro

- geo chemi cal systems that differ widely, physic al and chemical principles that apply universally will allow application of such modeling. Ready accessibility of the available information to the public will facilitate analysis and modeling by the scie ntific/technical.

9 community and enhance public trust . As seen for other data sets (e.g., RadNet following the recent nuclear power plant accidents in Japan), the scientific community is eager to perform some of the work that the EPA would otherwise be expec ted to do. Hence, results will be available sooner because of the distributed, parallel effort.

3.3. Guiding Principles and Assumptions for Regulatory Monitoring

T he SAB recommends for the near term

, until the needed large evidence base is a ccumulated and syste matized

, that the EPA articulate a se t of guiding principles and assumptions on which to base regulat ions

. The proposed standards can be based on these assumptions during the next several years, and super s eded if evidence of their unsuitability bec omes ava ilable. For example, assumption of seasonality in groundwater quality will require seasonal measurements for more than one year (as discussed in Section 6.2.4)

. If the reviewed data , for example, show that no seasonality is observed , or that the concept of seasonality should be replaced by groundwater quality response to monthly rainfall or major rain events, the sampling frequency specification would be changed.

3.4. Indicators of I nterest
The SAB recommends that the EPA identify , in addition to pertine nt groundwater constituents, se t s of indicators to assist in establish ing baseline conditions and post

- closure monitor ing conditions , with direct linkage between the baselin e and post

- closure indicators. I ndicators can include: (1) specific radio nuclides

, by mass concentration or radioactivity, as appropriate ; (2) gross radioactivity , by alpha

particle , beta

- particle , and gamma

- ray activity ; (3) water quality (e.g., total dissolved solids) ; and (4) geophysical and geochemical variables . The latter can indic ate groundwater status

, serve as surrogates of status or prognostic indicators, or influence consti tuent values (e.g., pH, flow). W here appropriate, the physico

- chemical form (e.g., speciation

, oxidation state, solubility) of the constituents should be det ermined. Section 4.3 expands upon this recommendation from the perspective of background characterization data.

Because th is list of indicator s could be extensive

, the SAB recommends that the EPA specify criteria by which to distinguish between pri mary an d secondary indicators. Such categorization can be helpful in risk

- weight ing the indicators for use in regulatory decision

- making (see Section 5. 7 )

. N ot all indicators will behave the same way post

- closure comp ared with baseline conditions. R isk from a giv en groundwater constituent is itself dependent on both its intrinsic toxicity and its concentration

, s o that what constitutes a primary versus secondary indicator may depend on the locality

. Calculating average baseline value s on a sitewide basis may be i nappropriate for some constituents if, for example, the ISL uranium mine is located within a roll

- front deposit

, where concentrations of some constituents show sharp trends over short distances reflecting the onset of reducing conditions that precipitate u ranium minerals

. Hence, baseline measurements should include those made outside the proposed production zone

, e.g., hydraulically upgradient, downgradient or tangential to the direction of groundwater flow through the uranium deposit ( also see Section 4. 2 )

.
3.5. Constituent Interactions and Environmental Transformations

The SAB recommends that the EPA draft technical report discuss how the composition of groundwater and minerals in the production zone may be modified by :

**•** m ass balance issues of the lixiviant/e xtraction fluid , particularly the fate of excess lixiviant injected in to production area s ;

**•** changes in m icrobial communities and activity ;.

10 **•** e nvironmental transformations associated with lixiviant flow and composition ; and

**•** i mpact s of external changes caused, for example, by nearby acti vities or groundwater
movement

. These effects arise from interactions among constituents, environmental transformations, and other processes acting on the constituents and aquifers that produce (potentially linked) changes in in dicators over time in mining and restoration processes that should be anticipated and documented. Some of this information for a site can be derived from experience at other sites , but other information will require

on

- site monitoring data and possibly spe cific studies.

The SAB recommends that geological monitoring information also be obtained from samples of formation material collected pre

- and post

- mining to characterize mineralization because the ability to solubilize or oxidize constituents will depen d on the geochemistry of the solid phase (e.g., Stewart et al. 2000)

. S ome surface spectroscopies (e.g., X

- ray absorption spectroscopy [ XPS ]

, extended X

- ray absorption fine structure [EXAFS]) and mineralogical analyses (e.g., X

- ray fluorescence analysis [ X RD ] ) can be helpful to characterize the preexisting minerals and their surfaces within the secondary pore system. Also collected should be information relevant to modeling the aquifer for understanding groundwater flow and predicting future concentrations of constituents both on

- and off

- site. The information collected can be utilized to evaluate the potential for mobilizing constituents off

- site that may impact human health.

3.6. Spatial and T emporal S ampling Densities Ultimately, the purpose of monitoring is to determine the concentration distribution (in space and time) of constituents or indicators of interest at baseline, during mine operation, post

- closure, and post

restoration

. T he space and time patterns of the indicators, the sampling scheme, and the r egulatory requirements must match

. That is, monitoring should reflect the expectations implied by the regulations, which themselves should reflect the underlying anticipated geo

- physico

- chemical behavior of the constituents.

A cr ucial aspect of monitoring is the detailed spatial and temporal s ampling scheme. Sampling is often performed in a regular pattern (i.e., on a grid in space an d at equal intervals in time). The optimum spacing required in space and time (i.e., that spacing which accurately reflects t he underlying distribution)

– or conversely, the sampling density

– is ultimately determined by the distributions of the constituents of interest. A fundamental approach to determining sampling is by the Nyquist sampling theorem (Oppenheim and Schafer 2010 ) , which states that sampling must occur at twice the highest frequency (spatial or temporal) present in the signal. In this case, the “signal” is the spatial and temporal distribution of the constituents of interest. If constituent concentration changes s lowly across space or time, then fewer samples, spaced f urther apart, are appropriate. I f the concentration changes more rapidly in space or time, then sampling density mu st correspondingly increase

.

While the Nyquist sampling theorem will indicate the sampling needed to portray accurately the space and time distribution of any constituent, it can result in collecting more data than necessary if the regulat ions do not require fully mapping the space and time distribution of constituents of interest. Ac cordingly, the Nyquist sampling theorem should be viewed as giving the upper bound on sampling density, not the required scheme per se

. The above considerations lead to a paradox: to determine the optimum sampling scheme, the space and time distributions of the constituents have to be known in advance

. In practice, the SAB recommends that a combination of existing data and modeling be used to obtain some information about the general.

11 behavior of c onstituents in space and time. That is, models c an be develo ped that incorporate the anticipated variation across mine sites ; model development w ill be aided by existing data from a variety of active and closed mine sites at hydro

- geochemically similar locations

. The models c an be validated initially with those exi st ing data. M odels can then be used to predict the range of constituent behaviors likely to be observed at subsequent mine sites as a basis for setting sampling requirements

. For example, sampling in time c an reflect the anticipated time

- varying time cons tants of the anti cipated temporal kinetics. Because much of the rapid change in post

- closure conditions occurs immediately post

- closure, more freque nt sampling should occur during that initial period

. This is consistent with, for example, an assumption of first

- order rather than zero

- order kinetics.

T he SAB recommends that the EPA provide additional discussion in its draft technical report on the following important monitoring issues :

**•** Spatial or temporal hotspots ( and distinguishing from random outliers) ;

**•** Behavior of i ndividual wells vs

. the average behavior of the pooled well s ;

**•** Seasonality or other periodicity ;

**•** T rends related to environmental factors (e.g., groundwater flow, rainfall ) ;

**•** Measurement accuracy and precision ; and

**•** Long

- time events that can a ffect baseline or post

- closure monitoring, such as extreme weather cycles.

3.7. Hydro

- g eochemical M odeling

3.7.1. Role of Hydro

- geochemical Modeling During the face

- to

- face meeting and teleconference s , much time was spent discussing the need or desire to have a modeli ng component that can predict the chemical and physical (and possibly biological) processes occurring during ISL uranium mining and the post

- mining restoration phase

. C oncern was expressed that models capable of capturing the complex kinetic and thermodyna mic behavior, particularly immediately following the end of active mining, are mentioned but not presented in detail in the draft technical report. Th is issue is particularly significant given the need

, ultimately, to rely on natural attenuation processes to restore groundwater to an acceptable and sustainable quality within a reasonable time frame.

The SAB recommends that the EPA expand its draft technical report to :

**•** elaborate on the potential roles of modeling to inform decision

- making during each of the different phases of ISL mining ;

**•** identify best practices for establishing a baseline mineralogical and hydrogeologic model of an intended ISL site ;

**•** summarize current capabilities and gaps in the use of models to predict the effectiveness of natural atten uation at site s spanning a range of operational conditions (such as type and amount of lixiviant injected) and restoration practices (such as sweep volumes) ; and

**•** discuss how an ISL uranium mine operator could design a site

- specific monitoring strategy to

c onfirm that natural attenuation processes are at least as effective as predicted

..

12 3.7.2. Characteristics of a Baseline Site Model
A s recognized by the draft technical report , ISL operations represent a massive redox/geochemical transient perturbation of a spatia lly complex reduced porous ore body that imposes dramatic changes on a mostly equilibrium

- governed geochemical condition. How the initial condition is described is essential to understanding the eventual rebound. The SAB recommends that the EPA’s draft tec hnical report discuss best practices for establishing a baseline mineralogical and hydrogeologic model of an intended ISL site. The better the baseline model, the better all subseque nt leaching/recovery/monitoring efforts will be

. Ideally, a baseline model include s a three

- dimensional understanding of the geologic formation, aquifer/aquitard mapping, hydraulic gradients, pump test response at various scales, geotechnical fracture mapping at various scales, and transmissivity.

R eactive transport in the form ation can be described on many different scales, but much of the modeling focus needs to be on understanding of the primary and secondary fracture surfaces and their existing weathered mineralogies in the unperturbed formation. Most sandstones hosting uran ium deposit s can have complex porosities; they can be loosely cemented with significant inter

- granular (primary) porosity or tightly cemented with secondary fracture (or microfracture) porosity with relatively high surface area to volume ratios. The draft technical report can benefit from a section that emphasizes and discusses these issues in detail.

3.7.3. Existing Models and Modeling Gaps
T he best hope to inform decision making about ISL design, operations, restoration, closure and monitoring will come from th e application of reactive transport models that are rich in thermodynamic databases for redox couples, reactive surfaces, sulfur/iron/carbonate minerals, surface sorption/precipitation reactions, and kinetic modules. This is di scussed in the draft technica l report but deserves more attention

. The SAB recommends that the EPA ’s draft techni c al report discuss the applicability of available models that have been developed and used to address similar situations . Such models have been used by the EPA, by industri es other than ISL uranium mines, and in different applications (see Section s 3.10 and 7. 5 )

. For example, numerous geochemical modeling software packages are readily available with the capability for modeling equilibrium fluid speciation, and redox, sorptio n, and precipitation reactions for specific hydro

- geochemical conditions. E xamples of these models include PHREEQC (Parkhurst and Appelo 1999), T he Geochemist ’s Workbench ® (Bethke and Yeakel 2009) and Crunch Flow ( Steefel 2009)

. N ew developments in this fie ld and their incorporation by the A gency will be of benefit. The reactive

- transport code MIN3P is one such example, with common he ritages to other models, but with particular applicability to pyrite

- dominated heterogeneous and porous systems (e.g., Mayer e t al. 2002 )

.
The SAB recognizes limitations in existing models, such as the inability of most models to capture chemical reaction kinetics. At the relatively low groundwater flow

- rate s for many ISL uranium mines

, local equilibrium can be assumed with respe ct to aqueous complexation and sorption reactions , thereby allowing use of thermochemical modeling databases for those reactions. T he kinetics of mineral dissolution, precipitation and transformation remain unknown for many systems , but should be considere d to the extent possible.

K nowledge gained from modeling the geochemical evolution of a site is valuable and worth the effort to the extent that the considerations listed above can be addressed

. At a minimum, the EPA can consider adapting these existing models for application to the ISL technology to gain technical insight into the performance of ISL operations and their associated monitoring network s

. T he feasibility of modeling can be evaluated by compar ing predicted results with monitoring data

, which appear to be abundant. The.

13 modeling efforts will complement the monitoring data to support assessment of the impacts of site operations on groundwater quality , and will provide lessons learned for future licensing of similar operation s

.

The SAB recommen ds that r esearch be undertaken to obtain empirical values of time

- frames and (spatial and temporal) rate constants/reaction rates to validate kinetic models. Th ese model s should include components (both causal and mediating), interconnections, and sensiti vity (e.g., by perturbation analysis ) and consider the following areas (at a minimum level):

**•** Geochemical modeling with chemical reaction kinetic equations and equilibrium thermodynamic equations , as appropriate ;

**•** Evaluation of an appropriate kinetic model (e.g., first order for both spatial and temporal kinetics) ;

**•** Incorporat ing natural attenuation processes such as sorption and the formation of secondary mineral s , and the effects of redox conditions and microbial activities on these processes ( Ford et al. 2 008, Li et al. 2011, U.S. EPA 2010) ;

**•** Need for a conceptual (physical) model ; and

**•** Interplay between data collection and modeling ( see Figure 1)

.
3.7.4. Benefits of a Validated Model
As noted above, the draft technical report should describe in detail the needed e ffort s, recognizing that the regulator can provide licensing conditions and guidance for operating a specific mine

. The SAB views modeling as a tool to assist in the design of remediation and monitoring strategies. For example, a reliable model may help id entify the areas at risk and in need of monitoring at baseline and after restoration attempts, and in interpret ing monitoring results. M odeling can assist in developing a good monitoring design, but can not make up for poor design. Modeling also can help to inform and formulate the sampling requirements to be included in the regulation , such as consideration of seasonal effects

. A validated model might also provide a sufficient technical basis for reducing the level of characterization needed for a particul ar site.

T he primary comparison between baseline (pre

- operational) and post

- operation al conditions is the concentration of various analytes in the groundwater and other water quality parameters. The SAB acknowledges that practical considerations must be t aken in t o account w hen performing baseline determinations and evaluating post

- closure performance of a site. For example, a complete mineralogical characterization of the site during baseline and post

- closure periods provide s complete evidence of long

- term site stability

, but this level of characterization is impractical from physical and economic viewpoint s . Therefore, a reliable validated model that can predict the evolution of the groundwater chemistry based on the behavior of the entire system (aqueous and solid phase components) w ill be helpful . If a single integrated model cannot be developed to serve this purpose, an alternative approach is to develop and test a set of process

- scale models or modules that can be used collectively to achieve the same o bjective.

The SAB recommends that, based on these considerations, the EPA develop or apply a geochemical model (or a series of individual modules) that can reproduce observed data from an existing ISL mine

. The intent of this modeling effort will be for the EPA to have a model that can be validated by field measurements and then use d to predict the likelihood that a site will achieve its restoration objectives within a given time frame. An important unknown is how long post

- restoration monitoring must occ ur before the site is released for other uses

. A reliable model would be capable of making this prediction.

14 and, if valid kinetic data are incorporated, show that the groundwater quality at a site will or will not attain steady

- state conditions comparable t o that of the baseline.

This information will give the EPA the ability to set a fixed time or guiding principles for post

restoration monitoring a t vari ous sites. The current common practice of setting a default six

- month or

one

- year monitoring period

, subject to exten sion if post

- closure monitoring goals have not been met ( U.S. EPA 2011a, page 2)

, is not based on scientific knowledge supporting the adequacy of such a requirement

. A reliable model also will give the EPA a technically defen si ble method fo r establishing guiding principles for the number of wells for groundwater characterization and monitoring required at a site and the frequency with which the wells must be sampled.

The power of the modeling efforts described above will be in the knowledg e g ained to craft the regulation. Due to the high degree of variability the modeling programs may have, it seems technically burdensome to require a complete hydro

- geochemical model of every site and it is unclear at this early stage how the parameters of the modeling efforts would be regulated ( e.g., the choice of modeling code). That site

- specific considerations must be applied is well understood due to the heterogeneity across ISL uranium mines . For this reason, model development has to rely heavily on f ield information gathered from the sites

. The modeling effort is close ly relat ed to the effort for ascertaining ground truth; the better the information , the more accurate the model prediction. The wealth of site data should be incorporated into the model ing effort. Conversely, any limitation identified in modeling should become a topic for future research. T he real intent is to understand fully the physical/chemical processes occurring within a site. To accomplish that, modeling can be used effectively in combination with site characterization and environmental surveillance. With such level of understanding, the EPA will be capable of producing a consistent set of guiding principles that are technically defensi ble.

3.8. Establishing B aseline Groundwater Chemis try
The SAB recommends that a t least as much effort should be devoted to establishing baseline conditions as is put into post

- closure monitoring. Critical considerations include:

**•** Spatial and temporal patterns (e.g., seasonality, annuality) ;

**•** Effects of cha nges in groundwater volume per se on baseline conditions ;

**•** K ey geochemical constituents that control the mobility of hazardous constituents ;

**•** Data needed to estimate the extent to which natural attenuation processes can be expected to restore groundwater to an acc eptable and sustainable quality after restoration;

**•** Other data needed to develop and validate hydro

- geochemical models to inform decisions on characterization, restoration, closure, and monitoring; and

**•** Drilling and sampling techniques to ensure coll ection of reliable and representative data.
This topic is discussed in detail in Section 4.

3.9. Post

- C losure M onitoring

T he issues inherent in establishing baseline conditions also pertain to post

- closure monitoring. While the restoration process is intended t o return the aquifer to its pre

- mi n ing or other predetermined state, both mining and restoration are dynamic processes that themselves introduce spatia l and temporal instabilities. Considerations include:.

15 **•** Spatial and temporal extent of perturbations to the aquifer ;

**•** Comparability (e.g., same monitoring wells) to baseline ;

**•** Modeling trend of return to stability ; and

**•** Indicators and their concentrations used as acceptability criteria

. This topic is discussed in detail in Section 5.

3.10. Analogous Systems

S ampling, mo nitoring, analyte selection, and modeling issues have also been considered for a nalogous systems in which massive transient redox/geochemical perturbations occur: landfill leachate plumes, acid mine drainage plumes, and subsurface reactive barriers. For t h ese analogues

, progress has been made in identifying issues around spatially complex and porous geology, time/scale/rebound, equilibrium versus kinetic reactions, redox couples that best indicate the dominant redox system, issues around groundwater samplin g under reduced conditions, and model application. The draft technical report would benefit by addressing more fully the applicability of these analogues to monitoring groundwater in the vicinity of ISL uranium mining sites

.
3.11. Standardized Terminology

The SA B recommends that the EPA pursue cross

- agency adoption of standardized definitions for key terms such as excursion

, contamination , and “return to pre

- operational groundwater quality

. ” For example, the term “ e xcursion ” has been defined in different regulati ons and guidance documents related to ISL monitoring as:

**•** transport of contaminants beyond the exempted portion of the aquifer (U.S. EPA 2011 a , S ection 2.3) ;

**•** an elevated reading within the min ing field (that indicates the potential for contamination) (U.S. NRC 2011); and

**•** the movement of mining solutions, as determined by analysis for control parameters, into a designated monitor well ( Texas Administrative Code , TAC Rule §§331.2)

.

The SAB similarly found various definitions of t he term “ contamination ” in re gulatory requirements, guidance, and site operating licenses. The NRC applies this term to the detection of contaminants or elevated constituents at a well beyond the boundaries of the min ing field (see also Section 5.2 )

..

16 Figure 1. Flowchart representing the coupling of data and modeling analyses to generate an evidence

informed regulatory approach and methodology. ( a The term s “p arameter s and sampling paradigms” refer to a consistent approach or methodology fo r deter mining the monitoring requirements at a given site, while recognizing that the requirements themselves are site

- specific.) Validate

Build Collect and collate data on the spatial/temporal patterns of main constituent behaviors and other parameters pre

- , during, and post

- mining.

Extract information from the data to gener ate predictors of:

**•** Trends (kinetic and thermodynamic )

,

**•** Primary vs. secondary constituents and linkages , and

**•** Hydrologic, geologic, and lithologic parameters

.

Build and validate kinetic models

.

Build conceptual model with predictive and explanatory power

.

Identify measurement parameters of importance (primary and secondary)

.

Determine data sampling paradigms based on the spatial and temporal patterns of main constituent behav ior s pre

- , during, and post

- mining.

Build these parameters and sampling paradigms into the regulatory approach or methodology. a

Generat e operational guidance on the execution of the approach. Feedback.

17 

### 4. PRE

- OPERATIONAL MONITORING

Charge Question 2 : Comment on t he proposed approaches for characterizing baseline groundwater chemical conditions in the pre

- mining phase and proposed approaches for determining the duration of such monitoring to establish baseline conditions.

4.1. Background Information Considered by the SAB

In responding to the EPA discussion of establishing baseline conditio ns in S ection 4.2 of its draft technical report ( U.S. EPA 2011a)

, the SAB considered geologic settings of current and potential ISL operations and the inter

- relationships among geologic, hydrologic and water

- quality conditions. The following observations a bout characterization during the pre

- mining phase are based upon EPA and NRC presentations ( e.g., Striz 2011 ) and regulatory guidance documents (e.g., U.S. NRC 2003 ) , selected permit applications for proposed ISL operations, and license conditions establis hed by the NRC ( or by one of its Agreement States ) for ISL uranium mining operati ons

.

4.2. Defining Data Quality Objectives for Baseline Characteriza t ion

Th e SAB recommends that the proposed approach to groundwater monitoring for pre

- mining chemical and radiol ogical characterization be defined in the context of the DQOs for baseline characterization

. For example, the most basic DQO may be to establish zone

- specific statistical distribution s of baseline concentrations for key hazardous constituents that may be r eleased to groundwater during mining or restoration operations. Regulations require these distributions to be based on independent and representative water samples collected from zones in which baseline wells are located by a statistically valid sampling d esi gn:

**•** Mine

- area monitor wells complet ed within the proposed production zone ;

**•** Mine

- area nonproduction wells that comprise the monitor well ring to monitor for excursions ; and

**•** Mine

- area non

- production monitor we l ls completed in any freshwater aquifers that overlie or underlie the production zone.

Additional DQOs such as the following also may be appropriate :

**•** Demonstrat e correlations among key geochemical constituents that may support optimization of the characterization approach (e.g

. , identifying and monit oring surrogates , such as conductance, for key constituents );

**•** Identif y key geochemical constituents that control the mobility of hazardous constituents during the recovery phase (e.g., red o x couples that define the Eh

- pH field );

**•** Understand the hydrologic a nd geologic controls responsible for producing localized mineralization of uranium and other hazardous trace metals in the ore deposit;

**•** Identify optimal physic o

- chemical indicators for excursions, considering both reliability and
cost

- effectiveness of anal ytical methods;.

18 **•** Establish spatial variability of key geochemical constituents as the basis for determining the extent to which the mean or upper concentration limit of baseline concentrations is a function of well location, e.g., hydraulically upgradient, downgradient or tangential to the mine deposit, or in the near

- field versus the far

- field of structural controls and potential pathways;

**•** Assess the presence or absence of temporal variations in groundwater chemistry;

**•** Obtain data needed for geochemical mode ling of water/rock interactions to predict re

equilibration trends and rates during the recovery phase (e.g., Bain et al. 2001) ; and

**•** Identify the critical or most vulnerable pathways ( e.g., Striz 2011) . Generally, vertical excursions into overlying or unde rlying aquifers are of greater concern than are horizontal excursions. Thus, for ISL operations in confined aquifers, the primary consideration should be no likelihood of breaching the confining beds conditions

. 1

The key point for consideration is that e ach DQO may require a different approach to the design and implementation of a baseline characterization program, as illustrated in the following Section in which baseline characterization parameter s are mapped to relevant DQOs.

4.3. Baseline Characterization P arameters
The EPA is encouraged to emphasize the importance of evaluating and presenting water

- quality data within the context of their geochemical interrelationships, not so lely as independent variables. The SAB recommends that baseline c hemical conditio ns be defined broadly to encompass transport flow paths and conceptual model s of mineralogic controls not only for hazardous constituents (e.g., trace metals) but also for associated parameters. Iron serves as a prime example of the potential complexity of geochemical interrelationships in an aquifer

. Iron

- bearing minerals buffer the redox chemistry of the groundwater

, and i ron (oxy) hydroxides not only constitute one of the most important sorbents for trace metals but also are one of the most important sou rces because of the ir potential to release these sequestered constituents into the groundwater when reducing conditions are restored.

Based on this broad perspective, the SAB recommends that analyte s be included in baseline characterization to meet the f ollowing objectives:

**•** Establish baseline conditions for key hazardous constituents with the potential to be released to the groundwater during mining or recovery operations;

**•** Characterize baseline conditions of chemical and secular equilibrium as one measu re of mineralogic stability (e.g., mineral saturation indices) . This is an alternative approach to defining concentration ranges as the sole measure of ba seline chemistry ;

**•** Collect data needed to define the Eh

- pH fields for the mine production area as well as for the adjacent aquifers ;

1 Failure of unlined (#S3) ponds at the Oak Ridge National Laborat ory ( ORNL ) provides one example of the consequences of failing to recognize the vulnerability of a confining layer serving as a barrier for contaminant transport (Kim et al. 2009; Wu et al. 2006). The p ond s were unlined because they were situated above a c lay layer (saprolite). A f atal flaw in this design was that the clay was fractured and allowed releases of constituents into the subsurface..

19 **•** Collect baseline data needed to assess the likely effectiveness of natural attenuation processes to achieve site

- specific rem e diation objectives within a reasonable timeframe , and to identify indicators that can be used later (post

- mining) to monitor attenuation progress ;

**•** Include aluminum in the background characterization suite because of its utility for normalizing metal concentrations and fingerprinting trace

- metal sources (Myers and Thorbjornsen 2004; Thorbjornsen and Myer s 2008), which may include formation solids/colloids, contamination, or residual annular

- fill bentonite in the vicinity of the well

screen ; and

**•** Apply effective statistical methods and develop effective graphical techniques to delineate geochemical fingerp rints, such as Piper and Stiff diagrams (Stri z 2011) and plots presented in the EPA technical support document, “Fingerprint Analysis of Contaminant Data” ( Power 2004).

Tables B

- 1 and B

- 2 in Appendix B of this report are intended to illustrate how the abo ve criteria might provide a basis for developing site

- specific lists of analytes and groundwater quality parameters to be monitored during baseline, mining , remediation, and closure operations. N ot all parameters listed in these tables would be applicable to a specific site; not all applicable parameters would need to be measured at a site; nor would all parameters selected for measurement at a given site need to be sampled with the same frequency. A lthough an exhaustive set of data might be desirable to al low evaluation of all parameters, a more practical approach is to limit data collection to a set of high

- priority primary parameters determined for a site

, augmented

, if necessary, by a second set of lower

- priority parameters

. Because this is a site

- specif ic consideration, no attempt has been made to prioritize the parameters listed in Tables B

- 1 and B

- 2

. The inclusion of redox speciation of the analytes of interest in Table B

- 2 differentiates this list from a typical RCRA analyte list in which only concen trations of the analytes are to be measured. If properly sampled and measured, the redox speciation data will provide invaluable information regarding the state of the aquifer. This will be important for determining the baseline conditions as well as for d emonstrating that the aquifer has been restored after mining is complete. For example (see Section 5.3)

, the sulfide/sulfate ratio will help to understand and explain aqueous concentrations of radium ; and the distribution of uranium between its tetravalent and hexavalent states, uranium (IV) and uranium (VI)

, respectively, has a direct relationship to the measured aqueous concentrations of uranium due to the low solubili ty of uranium (IV) relative to uranium (VI). Although m easuring analyte redox speciation has practical limitations , notably in preserving the redox state of a field sample, under most subsurface

c onditions simple pH and redox potential measurements are possible.
Couplin g these field measurements with the hydro

- geochemical modeling discussed abo ve c an be useful for predicting analyte redox speciation. Whenever possible

, the redox potential and oxidation state of the analytes of interest should be considered based upon the availability of data collected from the analyte list s (Table s B

- 1 and B

- 2 )

. The stability lines for site

- specific redox couples of interest (e.g., iron(II)/ (III), sulfide/sulfate, molybdenum(II)/(IV), manganese(II)/ ( I V)/ (V II ), and uranium(IV)/(VI) ) should be plotted and analyzed with the relationships described by Borch et al

. ( 2 010 ) and Lindsay ( 1979 )

.

C larification or guidance is needed concerning whether baseline concentrations should be determined for filtered and/ or unfiltered samples, particularly in the case of trace metals. Although f iltered groundwater concentrations are more appropriate for modeling geochemical speciation

, mineral/water interactions , and mineral saturation indices , unfiltered concentrations also have r elevance for.

20 characterization. For example, comparison of filtered and unfiltered concentrations may est ablish the extent to which samples collected from the well may be biased by formation solids, annular

- fill material, or metal corrosion products. I n addition, some regulatory standards for trace metal s apply to total concentrations (e.g., arsenic, mercury, selenium).

4.4. Drilling and Well Construction Practices Little discussion is provided in the draft technical report about potential effects over the life cycle of drilling, well construction and development activities on the capability of the monitoring well to provide
water

- quality samples that will be adequately representative of baseline conditions

. Regulatory requirements and guidance generally f ocus on the mechanical and physical integrity of the well and annular seals to prevent undesirable vertica l migration of groundwater from one strata to another. The EPA is encouraged to consider how drilling, construction and development activities may affect or bias concentrations of water

- quality parameters of interest, and to identify protocols that might b e used to detect or minimize such biases . Three examples are :

**•** Physical changes to formation minerals induced by drilling may increase concentrations of colloids and suspended solids in the vicinity of the screened interval , causing an upward bias in conce ntrations of trace metals in filtered and unfiltered samples. U se of bentonite drilling muds or improper placement of bentonite annular

- fill and seals also may have the potential to bias the concentrations of strongly

- sorbing metals

. These effects may be m inimized by proper development of the screened interval while monitoring trends in turbidity.

**•** I ntroduction of oxidizing fluids into the reducing ore zone during drilling, well construction or development may chemically alter formation minerals in the vici nity of the screened interval , leading to elevated concentrations of , for example, uranium, other trace metals, radioactive uranium daughter products, and sulfate ( Abitz and Darling 2010 ). C hanges to baseline redox conditions m ay be detected in the field b y monitoring trends in redox indicators during well development or during purging of the screened interval prior to sample collection.

**•** Oxidizing conditions might also affect groundwater at a monitoring well as a result of new exploration boreholes drilled nearby

. C ollecting representative groundwater samples within the proposed production zone thus requires that baseline water quality be established early in the exploration phase ( Abitz and Darling 2010 )

. For these reasons, the EPA should consider expandi ng its draft technical report to include guidance on best practices (a) for conducting and documenting drilling, well completion, and development activit i es at wells used to establish baseline conditions, and (b) for evaluating the capability of the well t o provide reli able and representative groundwater samples

.

4.5. Challenges for Background Characterization

The EPA draft technical report properly emphasizes that the design and implementation of a baseline characterization program will be driven by site

- speci fic factors. Some additional discussion and guidance may be needed to emphasize that the location of the baseline wells must be based on a statistical ly valid sampling design developed following the DQO process.

A random selection of wells from a systemat ic grid is one example of a statistically valid appro ach for locating baseline wells. However, even a statistically valid distribution of sampling wells does not.

21 eliminate complications for establishing baseline conditions in the context of site

- specific f actors such as those described below.

**•** Intersecting or adjoining d eposits near mine leases. Mining companies often submit applications to expand the area of ISL operations or to establish satellite ISL wellfields. Consequently, environmental impacts of oper ations may overlap but not be coincident in time

, and complicat e defining ba seline groundwater chemistr y for a proposed mine . Such overlap a lso may caus e ambiguity about which min ing operation is the source of any future excursions

.

**•** Groundwater c ontaminat ion in adjacent abandoned mine shafts and tunnels could complicate the definition of baseline chemistry and specification of restoration target concentrations

. I f operations at an ISL mine that intersect s these mine workings subsequently chemically alter t he groundwater in the workings

, then a n argument could be made that less restoration effort should be required than for t he native sandstone leached in other areas

.

**•** Dewatering effects of old mine workings in or near a proposed ISL operation may subject the formation to oxidizing conditions that may extend for some distance around the old mine working s (i.e., into areas that were not mined by the underground operation). Such dewatering may have diminished or eliminated reducing conditions in the aquifer, and uranium may move a longer distance than would normally be predicted before it encounters reducing conditions in the aquifer

.

**•** Improper selection of sampling horizons creates an invalid bias in the water

- quality parameters , e.g., by collecting samples from ore horizons relative to samples collected from the entire thickness of the formation

.

**•** Limited knowledge about site mineralogy , particularly related to trace metals, may undermine the reliability of geochemical modeling to predict the types and rates of w ater/rock interactions controlling groundwater chemistry and hence post

- mining rehabilitation. Uranium distributions are generally determined from downhole gamma logs; chemical assays are not always performed, and presumably performed rarely on cuttings fr om barren holes.

**•** Changes occurring in the groundwater environment during mine operation but for reasons unrelated to the mine itself c ould have the potential to invalidate the use of pre

- operational monitoring data as a comparison for post

- operational mo nitoring data. One approach to mitigate t his possibility is to utilize data from those monitoring wells that ring the mining unit

, and that clearly are not impacted by the lixiviant

, to provide ba seline monitoring data throughout the mining operation al pha se

.
The SAB recommends that the EPA discuss in its draft technical report how the above situations can be addressed in the context of establishing DQOs (see Section 4 .2 ) , sampling protocols (see Section 4 .3 )

, and well drilling and construction practices ( see Section 4 .4). C orollary topics for consideration in the draft technical report are to (1) summarize the various types of mineralogical characterizations desirable for baseline characterization (see also Section 3.5) ; (2) ensure that the approach propos ed for baseline characterization is sufficiently flexible to accommodate other character i s t ics encountered at future mines ; and (3) include models and coefficients for monitoring networks w h ere available..

22 4.6. Frequency and Duration of Monitoring to Determine Background

The SAB recommends adopting a phased approach to ba seline characterization that takes into account the following:

**•** N eed for additional background locations c an be informed by the level of uncertainty in the range and spatial variability of cons t ituents in the groundwater ;

**•** N eed for additional data from a particular well (or the need to resample a well) c an be informed by the consistency of the data with concentrations predicted from geochemical modeling of the site ; and

**•** N eed to continue samplin g an individual well c an be based on testing for trends in the data indicating the extent to which the we ll has recovered from drilling and construction activities.

T he adequacy of development and re

- equilibration time of baseline wells should be confirm e d prior to sampling. The EPA is encouraged to consider how best to test for steady

- state geochemical conditions at baseline wells, and to evaluate whether samples represent water

- quality data from these wells. The baseline data ultimately will provide the t echnical basis for establishing action levels for exceedances observed during the post

- restoration monitoring phase. As such, it is critical that the data represent the natural variability of each analyte, unbiased by variability resulting from residual ef fects of drilling, construction and development. Under some conditions, r esidual impacts from drilling can dominate the concentrations of some groundwater constituents (particularly trace metals) in the vicinity of the well screen for months (if not years)

.

The EPA is encouraged to include in its draft technical report guidance on best practices for groundwater sampling . In doing so, the agency can reference the extensive work it has already performed in this area (e.g., Puls and Barcelona 1989, Yesk i s a nd Zavala 2002)

, giving emphasis to the following aspects :

**•** D ocument the volume of water purged before sample collection and field parameter data measured during purging ( e.g ., pH, Eh, conductivity , turbidity ) to provide a basis for assessing whether the g roundwater sample is representative of predrilling conditions

.

**•** Collect additional water

- quality samples during purging that may provide additional insights on well performance issues. For this purpose, a time

- series suite could be defined that involves co llecting water

- quality samples in increments of one to two casing volumes during purging to be analyzed for major ions, trace metals and nonmetals, and total organic carbon. These data would then be evaluated for trends that might indicate residual drillin g or construction products, mixing of groundwaters from different hydrologic zones, or disequilibrium with formation mineralogy.

**•** Other approaches for evaluating representativeness are to plot redox

- couple data on phase diagrams and to use geochemical model ing to determine the extent to which measured water

quality parameters are in equilibrium or disequilibrium with mineral phases known to be present in the formation.
A single sample from each well is insufficient to determine whether water

- quality paramete rs are stable and representative of the groundwater at the sample location. Background chemistry should be based on a statistical analysis of groundwater chemistry data from a sufficiently large set of wells sampled over a.

23 period of time. The RCRA requirem ents (40 CFR 264 Subpart F) for the frequency of sampling are appropriate and applicable for this purpose :
§§192.32(g)(1). A sequence of at least four samples, taken at an interval that assures, to the greatest extent technically feasible, that an indepen dent sample is obtained, by reference to the uppermost aquifer's effective porosity, hydraulic conductivity, and hydraulic gradient, and the fate and transport characteristics of the potential contaminants

. Examples of calculations for determining the len gth of time ( or distance, in the case of neighboring wells) required to ensure samples will be independent , and examples of how to test for independence, would be useful additions to the draft technical report

.

4.7. Standardized Data Collection

The SAB recommen ds that the EPA adopt a standardized format for compiling groundwater monitoring data from ISL uranium mine s in order to develop a database that can be made publically available. This step will provide the EPA and stakeholders with a more complete and accu rate picture of activities in response to regulations in this field

..

24 

### 5. POST

- OPERATIONAL MONITORING AND RESTORATION

Charge Question 3 : Comment on t he approaches considered for monitoring in the post

mining/restoration phase and the approaches considered for determining when groundwater chemistry has reached a “stable” level.

5.1. Introduction and Overview The draft technical report points to two primary objectives for post operation and restoration monitoring. The first is to provide comments on how the moni toring program during the post

- mining and restoration phase s should be organized and carried out ; the second is to discuss approaches for determining when the groundwater chemistry has reached a “stable” state. C onsiderable reliance is placed on the method for determining baseline conditions that is addressed in the response to C harge Q uestion 2 (see Section 4)

.
5.2. Defining Restoration Goals

The SAB recommends that the EPA provide careful qualification about its meaning of “ return to pre

operational groundwat er quality. ” Restoration activities may not fully or precisely restore the aquifer to
pre

- operational quality; consequently some quantitative measure of how close is close enough will have to be de veloped to support a decision. Examples of alternative appr oaches to defining remedial goals include returning the aquifer to pre

- operational conditions based on statistical comparison with pre

established criteria versus the use of a risk

- informed basis. A glossary of definitions should be included in the draft t echnical report for terms that may have somewhat different definitions within the scientific community and hence can be open to interpretation

. These words include: colloid, steady state, irreversible (in the context of a chemical reaction), stability/stab le, baseline, and heterogeneity.

The SAB recommends that the EPA develop a set of guiding principles that will be used to craft restoration standards

. The draft technical report suggests that many considerations are highly site

specific. However, t he E PA can provide generic guidance with provisions to be adapted to site

- specific conditions (i.e.

, geology, groundwater flow, groundwater chemistry). One critically important aspect for which little discussion is provided in the draft technical report concer ns guidance on adopti ng alternative concentration limits (ACLs) as restoration goals. Such ACLs are particularly important for post

operation al monitoring of ISL facilities because adoption of ACLs appears to be the no rm, rather than the exception. In a se nse, ACLs serve as de facto regulatory standards that vary from site to site (see also Section 7.7) . Thus, in considering standards that apply to ISL uranium mines

, the EPA can provide guidance on ACLs (U.S. EPA 1987)

. For effective generic guidance

, av ailable data must be analyzed

. M any of the specific recommendations below are intended for developing a consistent set of physical and chemical parameters to be monitored, a uniform database of available data, and public dissemination of the data . The latt er will give the academic and research community the opportunity to evaluate the data and apply them to hydro

geochemical modeling as a means for predicting post

- closure behavior through universally applicable princ iples of chemistry and physics. Modeling will provide an opportunity to combine knowledge of physical/chemical processes with what is known about a site. In this way, monitoring data can test the model and suggest the likely effectiveness of alternative remediation scheme s

.
5.3. Evaluation of Existin g Datasets

T he SAB recommends that the EPA continue to seek out and collate data sets of sufficient scope and quality to provide information relevant for setting the standards under consideration

. Such data sets are.

25 available from existing and former s ites during the baseline evaluation, operation, and restoration stages For example, the U

. S

. G eological S urve y (USGS) compiled this type of information from public records to examine the effectiveness of groundwater restoration at legacy ISL mines in Texas (Hall 2009)

. Because geochemical, biological and physical conditions are highly variable among ISL uranium min es , a corollary activity is to use the existing data to identify fundamental transferable concepts among the sites. Some examples to illustrate th is point are:

**•** Correlations among various chemical and physical parameters may provide general descriptions of the systems :

o The valence state of uranium and arsenic should correlate with the ir total measured aqueous concentration s

. For uranium, this relat ionship is due to the increase d solubility of the hexavalent state

, uranium (VI), relative to the tetravalent state

, uranium (IV) (Borch et al. 2010)

. T he measured redox potential ( when little or no dissolved oxygen is present) should be related to the valen ce state of uranium and arsenic. R igorous analysis of the redox kinetics and speciation of the system may be needed because m any geochemical redox reactions do not achieve an equilibrium
state

. C omplexation with dissolved ions may provide thermochemical gr adients that favor an oxidized state of a metal or metal l oid despite the presence of reducing conditions 2

o D ue to the relative ly low solubility of radium sulfate, RaSO 4 (s olid ), aqueous concentrations of radium

- 226 ( 226 Ra) and radium

- 228 ( 228 Ra) should be i nversely related to the sulfate concentration ; and ;

o Iron (oxy ) hydroxides and clay minerals are generally expected to be the dominant sorbents of uranium and radium in the ore deposits

. Consequently, a queous uranium and radium concentrations should be inve rsely related to the amount of iron (oxy ) hydroxide and clay minerals in the subsurface (Catalano and Brown 2005; Moyes et al. 2000)

.

**•** O ne key indicator for post

- mining/restoration is the ratio of carbonates to sulfides in the mined unit. If there is insu fficient neutralization potential remaining in the unit, it is likely to continue to oxidize from remnant lixiviant and cause mobilization of U(VI) and other contaminants.

**•** The existing datasets can be u sed to demonstrate use of hydro

- geochemical modeling f or predicting behavior of the system during operation, restoration, and post

- restoration

. N umerous modeling programs currently are available at varying degrees of sophistication (see Sections 3. 7 and 7. 5 ) . These models can incorporat e chemical speciation m odels with hydrologic flow models to predict spatial and temporal concentrations of analytes in aqueous and solid phases. A feasibility study employing the modeling program PHREEQC was commissioned by the NRC ( U.S. NRC 2007 ; also see Parkhurst and Appelo 1 999) . The study

2 An example of this phenomenon has been clearly demonstrated by Wan et al. (2005) during a uranium bioreduction study. After amending uranium

- contaminated sediments with lactate, uranium reduction was seen up to 80 days but after >100 days uranium was reoxidized despite the fact that a microbial population capable of reducing uranium was maintained. It was found t hat the oxidation was due to the formation of thermodynamically favorable aqueous uranyl carbonate ternary complexes such as Ca 2 UO 2 - (CO 3 ) 3 . Oxidation of uranium(IV) to uranium(VI) is highly undesirable because of the enhanced environmental mobility of ur anium(VI) relative to uranium(IV)..

26 examined three techniques for estimating the volume of water that must be passed through the aquifer system to achieve restoration standards. A m odel that consider s hydrology, contaminant transport, and geochemical reactions provide d a qual itative estimate of the geochemical conditions and estimate d the behavior of the system during post

- restoration monitoring

. Because in

- situ mining is a major perturbation of the system, a quantitative model in support of site measurements can provide confi dence that the restoration goal of site stability after closure ha s been met. The U.S. NRC (2007) emphasized that development of a justifiable conceptual model that captures the major chemical and physical phenomena at each site is required. This approach will allo w for site

- specific flexibility

.

**•** Information on solubility, aqueous speciation, and sorption affinity may be found to guide extrapolation to aqueous concentrations near equilibrium. P rediction of temporal trends by hydro

- geochemical modeling is d ifficult due to the lack of kinetic data for some relevant systems. The very act of in situ mining take s a system far from an equilibrium state during normal operation. T he thermodynamics and kinetics during the early phase of restoration are likely to be important. In most cases, aqueous complexation reactions and sorption reactions
may reach at least a local equilibrium. Therefore, the major focus should be on incorporating kinetics of mineral precipitation and dissolution into the modeling efforts. An ex ample is provided in A ttachment B of the d raft t echnical r eport when discussing transitions from ferric ( oxy ) hydroxides to soluble ferrous iron to ferrous sulfide minerals

.

**•** The EPA has case studies from sites that have completed restoration ( U.S.EPA 20 1 1a, Attachments B and C ). These may be pertinent to discussions in t he draft technical report on the use of confidence levels for determining if restoration goals have been achieved.

**•** A uniform database can be prepared from the collected site data that we re used to characteriz e baseline, operation, restoration, and post

- restoration conditions

. This database

can be made publically available so that the academic/research community can evaluate the data and help to develop conceptual and quantitative models w hich can be used to further refine the regulations and monitoring activities for in

- situ mining.
The SAB recommends that the EPA discuss the implications of the data on restoration activities at mines included in attachments to the draft technical report. Listing measured analytes and water quality parameters without pertinent discussion is of limited utility. For example, would it matter if the calcium concentration is above the baseline concentration but uranium and radium concentrations are all at or bel ow baseline?

5.4. Criteria for Collection and Analysis of Monitoring Data Development of a set of guiding principles discussed above ( Section 5.2) for use in forming standards will be an improvement on the current practices primarily guided by site

- specific me trics

, which allow for a high degree of variability. A set of general principles that consider s variable site conditions within a broadly consistent approach can ensure that consistent standards are applied for all sites. Several relevant principles are :

**•** T he data gathered during restoration will be valuable for determin ing if the restoration activities are effective. A feedback loop should be implemented that requires a change in restoration activities if the data indicate that the goals will not be met. Th is can be a simple projection of groundwater chemistry based on the extrapolation procedures outlined in the.

27 d raft t echnical r eport or a more complex c oupled hydro

- geochemical model of the system that considers relevant reaction kinetics ;

**•** Pertinent data i ncorporated into the consistent, publically available

, database discussed above will encourage interrogation of the data to refine future monitoring during in

- situ mining activities ;

**•** S everal approaches are available to analyze the large sets of data gene rated from site s with multiple wells at multiple times. While a site

- averaging technique is a simple approach, the key to understanding outliers and spatial variability is to look at the data for individual wells. Therefore, unless specifically guided by a statistical test, chemical parameters should not be reported or evaluated as a site

- wide average value. ( S ee Section 6 .2 )

.

5.5. Duration of Post

- M ining/Restoration Monitoring

M i ning by ISL alters the subsurface physical (e.g., aquifer porosity and permeability ) and chemical environment. When mining ends and no further anthropogenic actions influence the groundwater

, then the groundwater and the minerals with which it is in contact begin to shift toward a new geochemical steady state. P ropos ing method s of return ing to baseline hydrologica l and chemical conditions during restoration activities impl ies that the system will return to steady state conditions comparable to pre

operational baseline conditions

. However, although groundwate r conditions may be sufficient to satisfy license requirements

, the SAB is not aware of available data indicat ing that mineralogical and hydrological conditions can be fully restored. Examination of post

- mining /restoration data from former ISL uranium mining units would be useful to det ermine the extent to which r etu r n to baseline conditions has indeed been achieved. The examples in the draft technical report appear to focus primarily on analyte concentrations.

In addition to water quality data, m ineralogical data can be used to evaluat e the long

- term stability of the system. Because c omplete mineralogical characterization is unrealistic or economically infeasible

, alternative approaches are needed. D ata from existing facilities can be used to propose a technically reliable time frame fo r post

- closure monitoring. Th is is a case in which hydro

- geochemical modeling can be a valuable tool for predicting how long a system will take to return to baseline conditions. Combining a validated model with the data from a relatively limited number of sites that have proceeded completely through the restoration and closure process will provide an estimate of technically reliable time frames for post

- operational and post

- restoration phase monitoring

.

The SAB recommends the following actions regarding s ampling frequency and duration:

**•** Increased frequency of groundwater monitoring during the initial restoration phase . The system is expected to return rapidly from its status far from equilibrium during mining to nearer its natural state as the lixiviant is flushed out. Measuring t his rapid change with sufficient frequency (e.g., weekly or biweekly ) will provide valuable data regarding the trajectory of aquifer parameters and analyte concentrations for validating and v erifying hydro

- g e o chemical mode l s;

**•** Statis tical testing to verify that baseline conditions, once reached, are maintained (see Section 6 .2 ) ; and.

28 **•** Application of hydro

- geochemical models to data sets from ISL uranium mines that have been restored to indicate magnitude of duration needed to attain res toration, as defined by consistent criteria.

5.6. Grouping C onstituents for M onitoring A ctivities

T o verify that baseline conditions have been achieved by site restoration activities, the SAB recommends that the list of analytes and groundwater parameters to be monitored before, during, and after operation be established pre

- operationally

. T he analyte list s provided in Appendix B include the analytes and groundwater parameters that the SAB considers potentially relevant for baseline determination and evalua ti on of post

- closure stability.

5.7. Hazard Quotient or other Risk

- W eighting S cheme for Determining Relevant Analyte s
The SAB recommends that the EPA consider developing a risk

- weighting scheme to apply to the analytes being monitored during baseline and restorat ion activities. Such weighting can show the relative risk from a given analyte that is out of compliance. This will prevent the scenario that a site must continue restoration activities even though it has met the goals defined by risk analysis. This scheme can be combined with the recommended primary and secondary list discussed above where the analytes on the primary list must meet the restoration goals while the secondary list contains analytes of little risk that provide information on the extent of rest oration.

One approach to consider is the hazard quotient, which is the ratio of the measured analyte concentration to the analyte concentration at which no adverse effect is expected (Fjeld et al. 2007). According to this approach , constituent concentra tions in groundwater are acceptable with regard to health risk provided the sum of their hazard quotients is <1. Accordingly, a site at which an analyte has not met a restoration goal but does not present a n unacceptable health risk c an use a hazard quotie nt approach to demonstrate that there is little potential for adverse health effects. In the example above considering calcium, uranium, and radium, if the calcium concentration had not attained baseline levels during restoration but the overall groundwate r composition had a hazard quotient less than one, then the site could be released despite the fact that the restoration goal for calcium ha d not been attained

.
An alternative risk

- weighting scheme can factor in the economic and associated environmental

co nsequences associated with water quality that relate to chemical or physical constituents that do not directly impact public health, but would still require adding materials and energy (direct ly and indirect ly ) to remove the constituents prior to use (see also Section 7.2)

. Examples include excessive levels of boron that may limit its use for irrigation, or elevated concentrations of calcium that may cause excessive scaling in pipelines or equipment..

29 

### 6. STATISTICS, DATA REQUIREMENTS AND USE

Charge Question 4: Comment on statistical techniques that would be applicable for use with ISL/ISR mining applications (particularly for the areas in Charge Questions 2 and 3), as well as the subsequent data requirements for their use.

6.1. Design of W ell P lacement and S amp ling P rogram
Ma ny issues concerning the design and execution of monitoring plans for pre

- and post

mining/restoration are difficult to address in full in a brief technical report

. Each site is unique geologically

, and effects of ISL uranium mining on hyd rodynamics and water chemistry are c omplex. The draft technical report presents a reasonable general approach to statistical analysis of data from a monitoring program . H owever , the statistical analysis can only be as reliable as the overall design of the study, which must ensure that the monitoring wells will be representative of the aquifers at risk of contamination.

The problem of designing a monitoring system with adequate site locations and densities is not directly discussed in the draft technical report, although other EPA reports may cover this issue in other contexts. The monitoring system must be designed to provide adequate coverage for all aquifers deemed to be affected by ISL uranium mining according to the hydrological survey and hydro

- geoc hemical modeling. The term”adequate coverage” implies both selecting locations with most affected groundwater (e.g., potential hotspots) and overall assessment of pre

- and post

- mining/restoration aquifer conditions. Any “cherry

- picking” of affected locatio ns for underestimating long

- term changes due to ISL mining and recovery operations must be avoided.

The SAB recommends that the draft technical report give a summary of methods to determine the number

, density , and location of monitoring wells. A ba sic approach c an specify monitoring an initial number of wells that w ill be adequate under a presumed standard physical model for groundwater pollutant concentrations (based on prior standard practice). A fter an initial ( perhaps one year) interval, heterog eneity (and periodic ity

, see below) can be evaluated ; if the coefficient of variation (comparing different wells) of key potential constituents is unexpectedly high, additional wells can be added to the system prior to the start of the ISL operations

, in t ime to collect several months of baseline data for those wells before operations begin.

The draft technical report gives a sample size formula ( U.S. EPA 2011 a , page 52) that is relevant for testing whether a single analyte differs in the post

- mining ver sus pre

- mining period for a single well ; this is highly relevant for predicted “hotspot” regions that would be most affected by ISR activities

. Th e formula should be supplemented with a discussion of finding sample size needed for characterizing whether th e average value of an an aly te of interest over an entire aquifer is comparable in the post

mining period compared to the pre

- mining period. Here

, both the number of we lls and the number of samples per well are relevant, and the among

- well variance in an a ly te value determin es the number of wells required. Care must be taken in deciding over how large an aquifer or spatial area to average, because including wells in aquifer regions unaffected by IS L activities w ill attenuate the apparent e ffects of IS L mining

. O nce the region of interest is defined, standard sample size considerations (similar to the formula given i n U.S. EPA 2011 a , page 52, but with the variance term now involving a sum of within

and among

- well variability) c an be applied to this problem..

30 6.2. S tatistical A nalysis D iscussion The statistical analyses discussed in the draft technical report assume that monitoring wells provide
measurements during both pre

- and post

- mining/restoration, and describe a set of statistical analyses to determine the foll owing:

**•** w hether measurements of a single given pollutant concentration in the pre

- and post

mining/restoration periods for a single well are temporally stable (e.g.

, not subject to trend s in either period) ;

**•** w hether the data from a given well (if temporally stable in both periods) provide statistical evidence that differences in pollutant level (post

- mining/restoration versus pre

- mining period s ) are not greater than a given allowed value

, **∆** ;

**•** w hether group ed wells are heterogeneous either in their temporal tre nds or in their post

mining/restoration versus pre

- mining differences in concentration levels ; and

**•** w hether, in longer follow

- up, trends are evident in individual wells or overall in a group of wells

.
The draft technical report mainly discusses non

- param etric statistical methods to test for trends, p ost

– mining/restoration versus p re

- mining differences and heterogeneity , including the following:

**•** the Mann

- Kendall test to test for unexpected trends (U.S. EPA 2011 a , S ection s 8.3.2, 8.3.3, 8.5, and Attachment D, Section s D.2 and D.3)

,

**•** the Wilcoxon test for comparing baseline and post

- restoration samples for statistical differences for a single well (U.S. EPA 2011 a , S ection s 8.4.1.1 , 8.5, and Attachment D, Section D.5)

, and

**•** a test for heterogeneity among the p ooled set of wells b ased on the Wilcoxon test for trend (U.S. EPA 2011 a , S ections 8.4.1.2, 8.5, and Appendix D, Section D.4)

.
A lso given is a n approximation to the sample size needed to test for pre

- post differences so that power and T ype I 3

The SAB identifies, however, a larger issue missing from the statistical advice given in the draft technical report; specifically, stronger guidance on the overall design of the monitoring program that error of the statistical analysis are controlled (U.S. EPA 2011 a , Appendix E, Table E

- 4)

.
The methods that are described in the d raft technical report are reasonable as far as they go, with caveats discussed in Section 6.2.1. The charge question asks for guidance on which tests and statistical techniques should be used. The SAB agrees with the draft technical report that it is appropriate to utilize the Mann

- Kenda l l test for trend to determine for a given contaminant of interest or other analyte whether the post

- recov ery data are stable at a single well location. The use of the Wilcoxon test for post minus pre differences (i.e. whether the post

- recovery contaminant level is equivalent to that prior to the beginning of operations) is also appropriate when data for a sin gle analyte at a single location are considered. These methods are robust to outliers and errors and do not require detailed knowledge of distributions of contaminants.

3 In statistics, a Type I error may be compared with a false positive. It is an error of the first kind and is the wrong decisi on that is made when a test rejects the null hypothesis..

31 will provide the data for statistical analysis. By “ design, ” the SAB is referring to the number, location, and density of wells and the timi ng of measurements both before operations and after recovery. These design factors are much less fully discussed in the draft technical report than are the analyses of data from a single location.
Clearly, the locations to be monitored must adequately rep resent the aquifers at risk of contamination. In addition, the required density of monitoring locations depends on the spatial variability of the analytes to be monitored: greater variability requires higher monitoring density. The period of monitoring at each location depends on the temporal variability of the contaminants of interest at each location (see also Section 3.6). These factors will not be the same at each ISL uranium mine so that it is not possible to suggest a "one size fits all" design solut ion. The EPA needs to define a flexible approach to designing monitoring systems for the aquifers of interest that (1) is informed by hydrological and geochemical analysis of the aquifers and (2) can adapt to unexpected spatial and temporal variability by increasing either the density of monitoring locations or the period of time each location is to be sampl ed.

The SAB recommends that the draft technical report consider the complications that arise in practice when applying this relatively simple and straig htforward approach to data f rom ISL uranium mining . A few of these complications are discussed in the following subsections.

6.2.1. Strengths and Weaknesses of Non

- Parametric Approach The general non

- parametric approach taken has weaknesses as well as strengths. While robustness to outliers, non

- detects, and data blunders such as mis

- recording values is greater with the non

- parametric procedures

, something is lost in terms of modeling flexibility. For example

, a linear model framework can more readily incorporate correlations between measurements by specifying models for both the means and the v ariances of the measurements. Also

, repeated measurements (same well, same time) can be properly handled whether or not they are available consistently (taken at each time period) or only sporadically.

As noted above in Section 6.2, n on

- parametric tests are generally appropriate for testing relatively simple hypotheses

, such as the Wilcoxon test to determine whether constituent concentrations in specific wells post

- recove ry are comparable to those for baseline conditions

, and the Mann

- Kendal l te st for trends in constituent concentrations at specific wells during the post

- recovery phase . However, comparisons involving many wells may become more difficult using non

- parametri c methods than using more flexible parametric models. For example, constructing an estimate of aquifer

- wide levels of a given contaminant (an average over many wells) and deciding whether such estimates differ in the recovery period compared to the pre per iod when different numbers of measurements are taken at each monitoring site in each period and where there is variability of contaminants among sites seems more difficult to do using non

- parametric techniques than with parametric methods

, specifically

, mi xed effects variance component models. M ixed linear models can allow nesting of repeated measurements of the same well at the same time, while estimating slopes and intercepts for the response to restoration efforts of individual wells, and allow a test fo r homogeneity time trends . The presence of extreme outliers or of highly non

- normal data distributions require s caution in interpreting the findings of the analysis

, and the data should be examined for such outliers.
For example, t he proposed test for hete rogeneity (across well s ) based on using the z

- scores 4

4 In statistics, z

- scores are stan dard scores, normal scores, or standardized variables. The z

- score allows comparison of observations from different normal distributions

. from the Wilcoxon test assum es that all z

- scores are constructed to be equally informative about the overall post

- pre differences. This would not be the case if some wells have more measurements than do other wells..

32 Wells with larger z scores may simply have more observations available (and hence more power) to detect the post

- pre level changes

. If all wells have the same number of pre and post measurements then the proposed method of testing for het erogeneity should be appropriate

. The linear model framework, when it applies, provides a more general test for heterogeneity not dependent upon having the same number of observations per well.

6.2.2. Implications of Heterogeneity The draft technical report does not propose what actions might be taken if heterogeneous results are found for the post

- pre differences for different wells

. What actions are likely to be triggered if there is evidence of a single well (or of several wells) in which post

- pre differen ce criteria have not been met?

6.2.3. Gro upin g of W ells
The draft technical report pays little attention to deciding how wells should be grouped to test for either overall patterns or heterogeneity

, and whether all wells in a grouping should be treated the same in such
tests. For example

, it makes little sense to analyz e distant wells or wells that are up gradient in the same way as the wells most proximal to the aquifers or injection locations of interest

. I ncluding unaffected wells in the analysis tends both to attenuate the overall estimate of post

- pre mining differences a nd to reduce the ability to detect heterogeneity. If heterogeneity is detected

, it would be reasonable to specify additional analyses that relate the levels to factors such as distance from in jection points and groundwater gradients. Again

, this can be done more readily in the framework of linear models than with nonparametric tests.

6.2.4. Periodic Patter ns and T rends Seasonality , or whatever underlying factor it represents, complicates the propos ed analyses. S ufficient data must be collected to estimate seasonal trends and account adequately for seasonality in the statistical analysis. This require s at least two years of data (a minimum of one year during the pre

operational phase plus one year durin g the post

- operation al phase ) under the assumption that the mining/restoration process disturbs only the overall level of contamination but not the seasonal pattern. Seasonal patterns in concentration levels that are dominated by very short

- term but intens e events (e.g.

, heavy rainfall events that recharge aquifers with oxygenated water over just a few days in the summer months) require both more measurements per year and more years of data to determine the response of the post

- mining /restoration water syst em to these events.

T he draft technical report should be clear about whether seasonality or extreme short

- term events are expected to pla y a role in contaminant levels. Adopting the principle that monitoring locations for at least a full year prior to ope rations as well as after recovery , with consistent timing of observations within these years, has the effect of automatically "subtracting out" any consistent seasonal components when post

- operational recovery periods are compared to the initial conditions . If seasonal patterns are either predicted (by hydrological models) or observed to be highly variable from year to year (perhaps because of the influence of extreme weather events)

, then a single year of pre

- operational information may not be adequate. A design in which pre

- operational data are collected for a minimum of two years would be preferable for estimating year

- to

- year vari ability in the seasonal pattern although this design may be “overkill” if, for example, the aquifer s are deep en ough to be imp ervious to short

- term seasonal variability.
At some locations, the effects of longer term events on groundwater flow and quality may also be relevant if a mine may be operating for a decade or more. These effects may be instigated by large

- scale.

33 changes in land use (such as logging) , land cover (e.g., resulting from disease or infestation such as the pinebark beetle)

, and climate.

A carefully designed monitoring plan in which each well has equivalently timed measurements (quarterly or monthly measurements taken at the same periods in each quarter or month ) will largely eliminate the need for seasonal adjustment because the seasonality terms can be “subtracted out” when statistical tests of post

- pre differences are performed. Again, if sporadic but intense events dominate seasonal diff erences, more years of data and/ or more measurements per year are required to capture differences (post

- mining versus pre

- mining) in response to these events.

6.2.5. Role of Modeling in Assessment Modeling of groundwater and geochem ical dynamics plays a crucial role in assess ing which aquifers are at risk, the dimensions of the affected areas, the constituents most affected by the long

- term effects of IS L mining and re storation, and the time required for restoration

. M odeling of aqui fer conditions and chemical dynamics is crucial in designing an appropriate assessment of pre

- mining groundwater constituents, including spatial and temporal extent of monitoring. In addition, modeling can define constituents that should be monitored close ly because of the risk attributed to them directly, and because of their role in the underlying chemistry that may be affected by IS L mining and restoration. Modeling also plays an important role in interpret ing restoration monitoring results, especially w he n monitoring shows that certain analytes are not returned to baseline or predefined concentrations

. This can be seen in several of the examples given in Attachments B and C to the draft technical report.

Overall, modeling assist s in design ing monitorin g and interpret ing its results, but cannot make up for poor monitoring design. A certain margin of safety for each s patial, temporal, and chemical dimension of a monitoring program for the pre

- mining and post

- mining/restoration periods needs to be adopted so that the long

- term effects of IS L mining and recovery on all chemical constituents of groundwater relevant to public health will be well characterized even in situations when models are incomplete or assumptions are not met.

6.2.6. Multiple Comparisons
The h ypothesis

- testing framework described in the draft technical report gives a rather different context for discussions of multiple comparisons than is typical, and the discussion of multiple comparisons seems a bit off focus from the hypothesis testing frame work. In the draft technical report

, the null hypothesis is that the post

– pre mining differences for a given potential pollutant are at or above a given criteri on , **∆** . In usual multiple comparisons analysis

, one is concerned with making the experiment

- wid e T ype I error of concluding that ANY of the post

– pre differences, **δ** , are different than the null value **∆**

, when they are all in fact truly at the null value. In such analysis

, one is interested in controlling the probability that the minimum value of a s et of p

- values { p 1 , p 2 , ..., p n } is less than some fixed value alpha (each p k corresponds to the overall p

- value for some potential pollutant).

Here

, things are a bit different; because the site will not be regarded as suitable for release unless all poten tial pollutants are significantly below each **∆** criteria (which may be different for each pollutant)

, an “experiment

- wi d e” error would only occur if all { p 1 , p 2 , ..., p n } were below alpha . I t is this probability that should be controlled under the null hypoth esis. However

, the null hypothesis of interest now is not the global null hypothesis (i.e.

, that all post

– pre differences, **δ** , are at or above **∆** , in which case we could allow a very relaxed p

- value)

. R ather

, the composite null hypothesis is that at least one of the **δ** are equal or above **∆**

. In particular

, for the null hypothesis that exactly one of the **δ** is equal to **∆**.

34 and all other **δ** are so far from **∆** that the power to reject **δ** = **∆** is close to 1

, then testing each hypothesis at the nominal level alpha does ind eed control the experiment

- wise false positive rate at this same alpha level.

For all other possible null hypotheses (more than one **δ** equal to **∆** )

, the nominal level provides a conservative test. I n this setting

, control of the experiment

- wi d e T ype I err or rate is accomplished by simply ignoring the fact that more than one comparison has been made while testing each hypothesis in
turn.

In this arrangement, the concern with multiple comparisons is not loss of control of a global T ype I error rate, but ra ther, loss of control of power. Because the site is released only if all null hypotheses are rejected, then the sample size needs to be set so that a reasonable probability exists that all null hypotheses can be rejected, assuming that they are all false. T he site operators’ interest lies in perform ing

a careful power analysis to provide enough measurements to decrease considerably the nominal T ype II 5

6.2.7. Bayesian Approaches error fo r each test, while keeping the T ype I error rate at a traditional (e.g.

, 5 or 10 percent) value in each analysis.

Another option which the EPA might consider is the use of Bayesian methodology to determine the efficacy of post

- operational restoration. For example, pre

- operational monitoring data may lend themselves to the formation o f robust, realistic and informative prior distributions of groundwater constituents. An analysis using these data to estimate parameters of the prior distributions is similar to an Empirical Bayes method and can be viewed as an approximation to the complet e hierarchical Bayesian analysis (Ma rtz 2000; Gelman et al. 2009). If this methodology were to be adopted, then a decision

- making process that uses Bayesian posterior densities to determine whether or not groundwater restoration has been completed would ne ed to be developed.

5 In statistics, a Type II error may be compared with a false negative. It is an error of the second kind and is the w rong decision that is made when a test fails to reject a false null hypothesis..

35 

### 7. ADDITIONAL ISSUES BEYOND THE CHARGE

7.1. Monitoring of Other ISL Impacts The following situations may only indirectly affect post

- closure groundwater monitoring, but can impact efforts to protect public health and the environment. For this reason, the EPA may wish to summarize briefly in the draft technical report these potential events and identify the applicable EPA and NRC regulations and guidance on the design and implementation of focused monitoring programs to prevent adverse envi ronmental impacts.

**•** Release of l iquid, solid, and airborne contaminants during routine operation from surface structures, pipelines, evaporation ponds, waste disposal wells, well drilling, and sample collection;

**•** Vadose

- zone modeling to evaluate the potent ial for surface and near

- surface contaminant releases to impact groun dwater in the uppermost aquifer;

**•** E ffect of accidents, incidents, and natural disasters on distributing lixiviant

- borne contaminants or disturbing po st

- closure groundwater contents; and

**•** Co ntribution by nearby mining, abandoned mines, and waste sites to the constituents of post

closure groundwater.

7.2. Potential Impacts on Groundwater Usability The consequences of a lterations of the ore body aquifer chemistry are expected to be minor if the aqui fer is confined (but see footnote to Section 4.2 for an example of confinement fail ure )

, is not a potential drinking water source, and will be restored to pre

- operational baseline quality. The EPA needs to assure that environmental protection standards fo r uranium mining adequately consider potential impacts on the
current and planned use of aquifers by local populations for domestic water use, livestock watering and agricultural uses. Uranium mining by ISL could permanently and significantly alter such us e patterns. More importantly, given the prospect of worsening local and regional water shortages due to increasing demands and large

- scale climate changes, society arguably places a much higher value on available
water resources today than was the case in 1978 when the UMTRCA regulations were first promulgated.
One aspect about post

- mining restoration frequently brought to the SAB’s attention is that ISL mining occurs in an exempt ed aquifer

. Given this situation, several members of the public stated that t h e exempted aquifer does not need protection because the ground water is too contaminated to ever serve as a source of drinking water

. According to this perspective, only the non

- ex empted aquifer needs protection and groundwater restoration should be consid ered successful when it returns the water quality to a level that will not degrade the water quality beyond the exempted aquifer (Jo hn Cash, written communication ).

A n EPA presentation on the application process for a Underground Injection Control (UIC) pe rmit listed specific criteria that must be met for any portion of an aquifer to be de signated as an exempted aquifer under 40 CFR 146.4 ( http://water.epa.gov/learn/ training/dwatraining/upload/dwaUIC

- uicpermit.pdf ) :

**•** The aquifer does not currently serve as a source of drinking water; and

**•** It cannot now and will not in the future serve as a source of drinking water; or.

36 **•** The total dissolved solids (TDS) content of the gro und water is more than 3,000 mg/l and less than 10,000 mg/l, and the aquifer is not reasonably expected to supply a public water supply.
The second criterion listed above for an exempted aquifer requires that EPA determine that the aquifer cannot now and w ill not in the future serve as a drinking water source. The decision may be based on any of the following four specific si tuations regarding the aquifer { 40 CFR 146.4(b)(1)

- (4) } :

**•** It produces mineral, hydrocarbon or geothermal energy, or the Class II or III UIC well permit applicant can demonstrate it contains minerals or hydrocarbons in quantity and location that are expected to be commercially producible;

**•** It is situated at a depth or location that makes the recovery of the ground water for drinking water
p urposes economically or technologically impractical;

**•** It is so contaminated that rendering the water fit for human consumption would be economically or technologically impractical; or

**•** It is located over a Class III well mining area subject to subsidence or catastrophic collapse.
According to a representative of the mining industry ( John C ash, personal communication), most ISL mining applications for an exempted aquifer are based on the criterion that the aquifer cannot and will not in the future serve as a d rinking

- water source due to its mineral

- production potential. Thus, t here does not appear to be evidence sub stantiating the assumption that all exempted aquifers in which ISL operations exist or are proposed necessarily have TDS contents exceeding 3000 mg/ L

, nor that the groundwater is too contaminated to serve as a source of drinking water now or in the future. In fact, o ne might postulate that the basis for an aquifer exemption under the mineral

- potential criterion is no longer valid once the uranium mine rals have been removed by ISL mining operations.
This potential inconsistency in the UIC and UMTRCA regulations , which may be administrative rather than technical in nature, warrant s clarification in the EPA’s draft technical report.

7.3. Establishing D ata Qual ity Objectives

The SAB recommends in Section s 4.2 and 4.5 that the EPA define explicitly the DQO framework in the draft technical report

. The adequacy and technical accuracy of information in the EPA’s draft technical report

— specifically, information relat ed to the four charge questions for this advisory activity

— can best be assured if the a gency implements the DQO process for this project to define its objectives and its options for meeting those objectives. The absence of succinct definitions of these cri tical details complicated the SAB’s ability to identify the information and actions needed by the a gency to review the adequacy of existing regulatory standards in 40 CFR Part 192. For example, the compliance points for the standards are not consistently clear, the extent to which the existing standards are being met cannot be assessed, and the alternative technical approaches for meeting objectives are not explicit. This presents difficulties to relate DQOs to potential options being considered within the existing draft technical report

.

7.4. Integration with Other EPA Regulatory Programs Applicable to Groundwater Quality

The EPA may wish to address explicitly in the draft technical report how the a gency will integrate the ISL uranium mining standards with the long

- established and well

- documented requirements and guidance for other EPA regulatory programs that are also applicable to groundwater quality and that.

37 address many of the same groundwater monitoring challenges

. The discussion in the draft technical report concerning the applicability of RCRA is a good example.

7.5. Tapping Existing Resources for Environmental Modeling Modeling is complementary to monitoring in attaining a full understanding of groundwater quality at ISL uranium min es and the EPA can dra w upon existing modeling efforts for this task. For example, ORIA has undertaken cooperative multiagency modeling efforts to support regulatory programs

, including enviro n mental pathway models for groundwater modeling to inform remedia tion at sites contami nated with radioactive material a nd hazardous waste ( U.S. EPA 1993a, 1993b, 1993c).

Another source of information is t he SAB ’s review of the EPA’s 2003 draft guidance on the development, evaluation, and application of regulatory environmental models and Models Knowledge Base (MKB) (U.S. EPA 2003), prepared by the EPA Council for Regulatory Environmental Modeling (CREM). In the SAB review

, the panel emphasized a number of ways in which the Draft Guidance and MKB can be improved (U

. S

. EPA SAB 2006)

. T he fol lowing points from that review may be relevant to technical guidance supporting the regulatory program for uranium ISL sites:

**•** Care in articulating the audience to which the Draft Guidance is directed;

**•** The need to develop and apply models within the context of a specific problem ;

**•** Caution in the way that information on modeling uncertainty is evaluated and communicated, and the need for Draft Guidance to fully discuss uncertainty and sensitivity analysis methods ;

**•** Consistency in conforming the terminology used in the Draft Guidance to previous uses and meanings of these terms in other environmental modeling activities; and

**•** The need to gather, and in many cases to develop, additional information to be included in the modeling database, including the framework, e valuation, and limitations of individual models; and to implement a mechanism that allows the community of model users to submit feedback on their experiences and suggestions for model improvement.

The EPA (U.S. EPA/ORD Office of the Science Advisor) and the U.S. Dep artmen t of Transportation

w ere co

- sponsors of a National Academ y of Sciences (NAS) study ( NAS 2007) on the use of models to inform the regul atory decision

- making process. T he report prepared by the NAS Committee on Models in the Regulatory Deci sion Process recommended that evaluation of a regulatory model should continue throughout the life of a model, including throughout regulatory applications and revisions of the model. The NAS committee observed that the one

- time peer review of a model that is typically seen in the published literature is insufficient for many models used in the environmental regulatory process, and that more time, effort, and variety of expertise is required to conduct and respond to peer review at different stages of the l ife cycle, especially for complex models. The NAS committee emphasized the need to communicate clearly all of the uncertainties . It also noted that a wide range of possibilities is available for performing model uncertainty analysis and that, in some cases , presenting results from a small number of model scenarios will provide an adequate uncertainty analysis. In many instances, however, probabilistic methods will be necessary to characterize properly at least some of the uncertainties. The NAS Committee re port touched on communicating uncertainty, the interdependence of models and measurements, principles for model development, the selection and application of.

38 models, the issue of proprietary models, model management in the rule

- making context, improving

mo del accessibility, and related topics.

The EPA CREM published its guidance (U.S. EPA 2009 a ) following the reviews of modeling evaluations by the SAB, the NAS and the National Advisory Council for Environmental Policy and Technology ( NACEPT ) (U. S. EPA NAC EPT 2008). Th e CREM guidance provides an overview of the best practices for ensuring and evaluating the quality of environmental models.

7.6. Working Relationship with the Nuclear Regulatory Commission During its face

- to

- face meeting, the SAB observed what app eared to be insufficient communication between EPA and NRC staff concerning the accessibility of groundwater monitor ing data and its regulatory implications for ISL uranium mining. As a result, the EPA draft technical report needs more operational details and delineat i on of present

- day guidelines for monitoring

. The EPA is encouraged to conduct a cooperative dialog and to consider the establishment of a working group

— perhaps similar to the MARSSIM Working Group

— to coordinate its review of the uranium mining standards.

7.7. Promoting Predictabil it y and Reducing Uncertainty in Uranium Mining Standards

A s noted in the EPA’s draft technical report , protocols for establishing baseline groundwater quality (as well as for monitoring groundwater before, during, and afte r mining) are established in the facility license issued by the NRC or applicable Agreement State (U.S. EPA 2011 a , p. 26). Regarding this practice, the SAB agrees with the statement made ten years ago by the NRC’s Center for Nuclear Waste Regulatory Analys es (U.S. NRC

. 2001, p. 1

- 1):
Widespread use of license conditions is not an optimum regulatory framework. Since these license conditions are subject to rejection or modification through legal challenge, they add substantial uncertainty and economic and ope rational risk to ISL operations. Ensuring consistency of requirements for all licensees is also difficult with widespread use of license conditions.

In sum mary , t he SAB considers that the critical review and update of the EPA ISL uranium mine standards ar e necessary and timely . The EPA can implement this task following the key principles in Executive Order 13563, Improv i ng Regulation and Regulatory Review (signed January 18, 2011; Federal Register, Vol 76, No. 14, pp 3821

- 3823)

. Although UMTRCA regulations are not mentioned explicitly in EPA’s “ Final Plan for Periodic Retrospective R eviews of Existing Regulations” (U.S. EPA 2011c) developed in response to Executive Order 13563 , many of the processes and evaluation criteria presented in the EPA’s plan are re levant for addressing the issues and suggestions in the SAB’s advisory report..

39 

### REF ERENCES

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A

- 1 

### APPENDIX A

. EPA CHARGE TO THE SAB

June 2, 2011

MEMORANDUM

SUBJECT: Advisory Review of the Draft Technical Report: Considerations Related to Post

- Closure Monitoring of Uranium In

- Situ Leach/In

- Situ Recovery (ISL/ISR) Si tes

FROM: Michael P. Flynn, Director / S / Office of Radiation and Indoor Air

TO: Vanessa Vu, Director Science Advisory Board

This is to request that the Science Advisory Board’s augmented Radiation Advisory Committee (RAC) conduct an advisory r eview of the attached draft Technical Report: Considerations Related to Post

- Closure Monitoring of Uranium In

- Situ Leach /In

- Situ Recovery (ISL/ISR) Sites (Technical Report).

Background

In accordance with the Uranium Mill Tailings Radiation Control Act (UMTRCA) s ection 206, the Environmental Protection Agency (EPA) is authorized to develop standards for the protection of public health, safety, and the environment from radiological and non

- radiological hazards associated with residual radioactive material s. Regulatory standards implementing UMTRCA (40 CFR Part 192 Health and Environmental Protection Standards for Uranium and Thorium Mill Tailings) were originally issued in 1983, and last revised in 1995. EPA is currently conducting a review of its regula tions for uranium and thorium milling to determine if the existing standards in 40 CFR Part 192 should be updated.

While the existing regulatory standards apply to both conventional mills and unconventional ore processing methods, they were not written i n anticipation of new technologies such as heap leaching and in

- situ leach/in

- situ recovery (ISL/ISR). With ISL/ISR operations expected to be the most common type of new uranium extraction facility in the U.S., and the potential for these facilities to aff ect groundwater, EPA has prepared the attached draft Technical Report, which addresses considerations involved in establishing groundwater monitoring systems around uranium ISL/ISR operations. There are several objectives for monitoring an ISL/ISR uraniu m extraction operation, specifically:

1) to establish baseline (pre

- mining) groundwater chemical compositions; 2) to detect excursions of the injected and mobilized components beyond the well field; and 3) to determine when the post

- mining/restoration phase ground water chemistry has “stabilized,” i.e.
, reached concentration levels that are expected to remain constant over time.

EPA is considering including groundwater monitoring requirements as a component of the regulatory standards included in any revision of 40 CFR Part 192. The draft Technical Report is intended to support the technical considerations about monitoring requirements ( e.g. , sampling protocols, timeframes, statistical tools and techniques) that may be included in revisions to 40 CFR Part 192..

A

- 2 Sp ecific Request

At this time, EPA is seeking advice from the RAC on the technical considerations relevant to establishing monitoring plans to achieve the objectives described above. The Technical Report focuses on these considerations for designing and implementing a monitoring network. After receiving the advisory review, EPA plans to revise the Technical Report and use the information as a basis for updating 40 CFR Part 192 to explicitly address ISL/ISR extraction processes.

Specifically, EPA reque sts that the RAC provide comments on the following:

1) The technical areas described in the report and their relative importance for designing and implementing a monitoring network. Identify any technical considerations that have been omitted or mischaracter ized. 2) The proposed approaches for characterizing baseline groundwater chemical conditions in the pre

mining phase and proposed approaches for determining the duration of such monitoring to establish baseline conditions. 3) The approaches considered for monito ring in the post

- mining/restoration phase and the approaches considered for determining when groundwater chemistry has reached a “stable” level. 4) Suitable statistical techniques that would be applicable for use with ISL/ISR mining applications (particularly for the areas in Items 2 and 3 above), as well as the subsequent data requirements for their use.

If you have any questions about this request, please contact Mary E. Clark of my staff at (202) 343

- 9348.

Attachment

cc: Carl Mazza, OAR.

B

- 1 

### A PPENDIX B. W ATER QUALITY PARAMETERS FOR GROUNDWATER MONITORING AT ISL URANIUM MINING SITES

Table B

- 1. P rimary and secondary water

- quality parameters (see discussion in Section 4.3)

Parameter a,b Primary Relevance for Baseline Determination and Post

- Operational Monit oring c Mentioned in NRC guidance and/or baseline data reported by operator or applicant Mentioned in Regulations or EPA

Screening Level GuidanceNRC 2003CrownpointLicense(NM)ProductionAuthorizationAreas (PAAs) (TX)Dewey-Burdock(ND)ApplicableEPAand NRCregulationsdOther EPAgroundwaterstandards orscreening levelse

Major Ions

Bicarbonate Excursion indicator, geochemical modeling, source fingerprint ● ● ● ●
─ ─

Calcium Source fingerprint, geochemical modeling ● ● ● ●
─ ─ Carbonate Geochemical modeling ● ● ● ●
─ ─ Chloride Excursion indicator, geochemical modeling, source fingerprint ● ● ● ●
─ SMC L

Fluoride Source fingerprint, geochemical modeling ● ● ● ●
─ SMCL, RSL Magnesium Source fingerprint, geochemical modeling ● ● ● ●
─ ─ Nitrate Redox indicator, source fingerprint ● ● ● ●
─ MCL

Potassium Source fingerprint, geochemical modeling ● ● ● ●
─ ─ Silica Well performance indicator, geochemical

m odeling ─ ─ ● ●
─ ─

Sodium Source fingerprint, geochemical modeling ● ● ● ●
─ ─ Sulfate Excursion indicator, geochemical modeling, source fingerprint ● ● ● ●
─ SMCL

Trace Nonmetal Constituents

Ammonia Redox indicator, geochemical modeling ● ●
─ ●
─ RSL , HA Phosphate Geochemical modeling

─ ─ ─ ─ ─ ─ Sulfide Redox indicator

, geochemical modeling

─ ─ ─ ─ ─ ─ General W ater C hemistry Alkalinity Excursion indicator, geochemical modeling, source fingerprint ● ● ● ●
─ ─

T otal D issolved S olids Excursion ind icator, well performance indicator ● ● ● ●
─ SMCL

T otal Organic Carbon Well performance indicator

─ ─ ─ ─ ─ ─

T otal S uspended S olids Well performance indicator

─ ─ ─ ─ ─ ─.

B

- 2 Parameter a,b Primary Relevance for Baseline Determination and Post

- Operational Monit oring c Mentioned in NRC guidance and/or baseline data reported by operator or applicant Mentioned in Regulations or EPA

Screening Level GuidanceNRC 2003CrownpointLicense(NM)ProductionAuthorizationAreas (PAAs) (TX)Dewey-Burdock(ND)ApplicableEPAand NRCregulationsdOther EPAgroundwaterstandards orscreening levelse

Field P arameters

D issolved O xygen Redox indicator, well performance indicator

─ ─ ─ ─ ─ ─

O xidation R eduction P otential Redox indicator, well performance indicator

─ ─ ─ ●
─ ─

pH Excursion indicator, geochemical modeling, source fingerprint ●
─ ● ●
─ SMCL

C onduct ivity Excursion indicator, well performance indicator ● ● ● ●
─ ─

Tem perature Well performance indicator

─ ─ ─ ─ ─ ─ Turbidity Well performance indicator

─ ─ ─ ─ ─ ─ Water level Excursion indicator, well performance indicator ─ ─ ─ ─ ●
─

Trace Metals
Aluminum Well performance indicator, geochemical modeling , source fing erprint for trace metals ●
─ ─ ●
─ SMCL, RSL Antimony

─ ─ ─ ─ ● ● MCLG, RSL

Arsenic Mobilized COC, redox indicator ● ● ● ● ● MCL

Barium Mobilized COC, geochemical modeling, source fingerprint ● ●
─ ● ● MCL

Beryllium

─ ─ ─ ─ ● ● MCL

Boron Source finger print ● ●
─ ● HA, RSL

Cadmium

─ ● ● ● ● ● MCL

Chromium Mobilized COC, redox indicator, geochemical modeling ● ●
─ ● ● MCL

Cobalt

─ ─ ─ ─ ─ ─ RSL Copper Mobilized COC, geochemical modeling ● ●
─ ●
─ MCLG, SMCL

Iron Well performance indicator, redox in dicator, geochemical modeling ● ● ● ●
─ SMCL, RSL

Lead Mobilized COC, geochemical modeling ● ● ● ● ● MCL Manganese Well performance indicator, redox indicator, geochemical modeling ● ● ● ●
─ HA, SMCL,

RSL Mercury Mobi l ized COC ● ● ● ● ● MCL.

B

- 3 Parameter a,b Primary Relevance for Baseline Determination and Post

- Operational Monit oring c Mentioned in NRC guidance and/or baseline data reported by operator or applicant Mentioned in Regulations or EPA

Screening Level GuidanceNRC 2003CrownpointLicense(NM)ProductionAuthorizationAreas (PAAs) (TX)Dewey-Burdock(ND)ApplicableEPAand NRCregulationsdOther EPAgroundwaterstandards orscreening levelse

Molybdenum Mobilized COC, excursion indicator, redox indicator, geochemical modeling ● ● ● ● ● HA, RSL

Nickel Mobilized COC ● ●
─ ● ● HA, RSL

Selenium Mobilized COC, excursion indicator, redox indicator, geochemical modeling ● ● ● ● ● MCL

Silver

─ ● ●
─ ● ● HA, SM CL,

RSL

Strontium Geochemical modeling, source fingerprint

─ ─ ─ ●
─ HA

Thallium

─ ─ ─ ─ ● ● MCL

Thorium Mobilized COC ●
─ ─ ● ●
─ Uranium Mobilized COC, excursion indicator, redox indicator, geochemical modeling ● ● ● ● ● MCL

Vanadium Mobilized COC, excursion indicator, redox indicator, geochemical modeling ● ●
─ ● ● RSL

Zinc Mobilized COC, geochemical modeling ● ●
─ ●
─ HA, SMCL,

RSL Radiological parameters Gross alpha Excursion indicator, mobilized COC ● ●
─ ● ● MCL

Gross beta +
gross gamma Exc ursion indicator, mobilized COC ● ●
─ ●
─ MCL

Radium

- 226 Excursion indicator, mobilized COC ●
─ ● ●
─ MCL

Radium

- 228 Excursion indicator, mobilized COC ● ●
─ ─ ● MCL

Radon Mobilized COC

─ ─ ─ ●
─ MCL

Additional site

- specific parameters
Constituents in injected solutions, e.g., lixiviants, antiscalants, pH adjustment, chemicals used during groundwater restoration ●
─ ─ ─ ─ ●

Constituents likely to be present in spills or leaks, e.g., acids, bases, salts, oxidants, reductants, pregnant lixiviant f ─ ─ ─ ─ ─ ─

a This list was compiled based on examination of parameters listed in EPA’s draft technical report (U.S. EPA 2011 a , S ection 4.2 and A ttachment A ), 40 CFR Part 192, EPA’s Drinking Water Standards and Health Advisories (U.S. EPA 2011b ), and Table 2 .7.3

- 1 in U.S. NRC 2003.

b Parameters may be added to, or removed from

, this list based on site

- specific considerations.

c “ Sourc e fingerprint” indicates the parameter is commonly used to distinguish among different types of groundwater

, such as the fie ld in which the sample is plotted on a trilinear (Piper) diagram. “Geochemical modeling” indicates this parameter is commonly used to model the rates and interdependencies of water

- chemistry reactions in geologic media, principally.

B

- 4 redox reactions, mineral

- dissolution/precipitation reactions, sorption and ion

- exchange reactions. “Mobilized COC” indicates the parameter is a contaminant of concern (COC) that may be released into the groundwater as a direct or indirect result of mining or restoration activites

. d Applicable EPA and NRC regulations include 10 CFR Part 40, 40 CFR Part 192, and 40 CFR Part 264.

e Other relevant EPA groundwater standards and screening levels include maximum concentrations levels (MCLs), secondary MCLs (SMCLs), MCL goals (MCLG) a nd hea l th advisories (HA) for drinking water (U.S. EPA. 2011 b ), and EPA r egional s creening l evels (RSLs) for t apwater (U.S. EPA Regions 3, 6, and 9. 2011)

. f “ P regnant lixiviant” refers to the uranium

- bearing leachate solution that is recovered from the p roduction wells..

B

- 5 Table B

- 2. Other Water

- Quality Characterization Parameters (see discussion in Section 4.3)

Parameter Comments

Redox C ouples Ammonia (aq ueous )/nitrate

─ Arsenic (III)/(V)

─ Chromium (III)/(VI)

─ Iron (II)/(III)

─ Sulfide/sulfate ratio In addition to providing information about in

- situ redox conditions, t he sulfide/sulfate ratio will also help to understand and explain aqueous concentrations of radiu m. Manganese (II)/(IV)/(VII)

─ Selenium (

- II )/( 0 )/( IV )/( VI) Data reported for selenium (IV) and selenium (VI) for Dewey

- Burdock site (U.S. EPA 2011 a , Table A

- 1). Measurement of selenium oxidation states would be helpful from an analysis standpoint but du e to analytical limitations may not be necessary. Also, there are certainly practical limitations in sampling frequency. Uranium (IV)/(VI)

─ Stable Isotop e Ratios
Carbon

- 13/Carbon

- 12 Potential tracer of sources, groundwater mixing, kinetic rates of
geoc hemical processes, microbial activity Hydrogen and oxygen isotopes Potential tracer of sources, groundwater mixing

Sulfur

- 34/Sulfur

- 32 Potential tracer of sources, groundwater mixing, kinetic rates of geochemical processes, microbial activity

Uranium

- decay series

Lead

- 210 Data reported for Dewey

- Burdock site (U.S. EPA 2011 a , Table A

- 1)

. Mentioned in NRC 2003 but discounted

Polonium

- 210 Data reported for Dewey

- Burdock site (U.S. EPA 2011 a , Table A

- 1).

Radon

- 222 Data reported for Dewey

- Burdock site (U .S. EPA 2011 a , Table A

- 1).

Thorium

- 230 Data reported for Dewey

- Burdock site (U.S. EPA 2011 a , Table A

- 1).

Radium

- 226

─ Radium

- 228

─ Uranium

- 234/Uranium

- 238 Ac t ivity ratio is an indicator of uranium release and transport processes, attenuation

. Other C haracterization Parameters
Carbonate/sulfide ratio This ratio is a key indicator for the effectiveness of groundwater restoration in the mined unit during the post

- mining phase . If there is insufficient neutralization potential remaining in the unit, it i s likely to continue to oxidize from remnant lixiviant and cause mobilization of U(VI) and other contaminants

. Microbial community composition and activity Redox control ; indicator of potential for microbial processes to contribute significantly to monito red natural attenuation ( MNA ) for long

- term groundwater restoration (e.g., see Ford et al. 2008, Li et al. 2011, U.S. EPA 2010 )

. Colloid concentration and composition Transport mechanism