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A G ROUNDWATER F LOW AND S OLUTE T RANSPORT M ODEL OF S EQUENTIAL B IODEGRADATION OF M ULTIPLE C HLORINATED S OLVENTS IN THE S URFICIAL A QUIFER, P ALM B AY , F LORIDA

A Thesis Presented to The Academic Faculty by Daniel K. Burnell

In Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in Geophysical Sciences

Georgia Institute of Technology June 2002

A GROUNDWATER FLOW AND SOLUTE TRANSPORT MODEL OF SEQUENTIAL BIODEGRADATION OF MULTIPLE CHLORINATED SOLVENTS IN THE SURFICIAL AQUIFER, PALM BAY, FLORIDA

Approved:

Dr. Robert P. Lowell, Chairman

Dr. L. Timothy Long

Dr. Martial Taillefert

Dr. Leonid Germanovich

Dr. James W. Mercer

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ACKNOWLEDGMENTS Many people have provided support and technical assistance for this project. First of all, I would like to first thank my advisor Dr. Robert Lowell for not only his encouraging me to enter the Ph.D. program but also for his advice and patience during my completion of this dissertation. I would also like to thank both Pat Tydor and Rob Sands (Harris Corporation), and Larry Sims for the opportunity to perform this research. I would also like to thank Dr. James Mercer, Dr. Robert Lowell, Dr. L. Timothy Long, Dr. Martial Taillefert, and Dr. Leonid Germanovich for reviewing this dissertation and providing helpful comments. Finally, I would like to thank Dr. Neal Durant for his assistance in helping me to better understand degradation mechanisms. My love and gratitude goes to my wife Allison for her love and support. Additional appreciation is expressed to GeoTrans and L.S. Sims & Associates for the use of their resources in some of the computer simulations and graphics. A special thanks goes to Tracy Wisenburg and Christina Paugh for their time working on the manuscript and graphics. I want to also thank Scott Anderson for his help in organizing the site data into a Geographic Information System (GIS). This work was supported by Harris Corporation through its efforts to improve groundwater quality in Palm Bay, FL.

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TABLE OF CONTENTS Page

ACKNOWLEDGMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii NOMENCLATURE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv SUMMARY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xix CHAPTER I – RESEARCH OBJECTIVE AND BACKGROUND . . . . . . . . . . . . . . . . . 1 I.1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 I.2 DISSERTATION OBJECTIVE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 I.3 ORGANIZATION OF DISSERTATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 I.4 LITERATURE REVIEW OF TCE, DCE, AND VC ANAEROBIC BIODEGRADATION RATE CONSTANTS AND NUMERICAL TRANSPORT MODELING . . . . . . . . . . . . 9 I.4.1 TCE, DCE (CIS ), AND VC ANAEROBIC BIODEGRADATION RATE CONSTANTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 I.4.2 SINGLE AND COUPLED MULTI-SPECIES SOLUTE TRANSPORT SIMULATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 I.4.3 FIELD-SCALE MULTI-SPECIES CONTAMINANT TRANSPORT SIMULATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 I.4.4 MOTIVATION FOR THIS RESEARCH . . . . . . . . . . . . . . . . . . . . . . . . 29 I.5 STUDY AREA AND PREVIOUS WORK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 CHAPTER II – MODEL GOVERNING EQUATIONS AND BENCHMARK PROBLEMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 II.1 MODELING APPROACH AND GOVERNING EQUATIONS . . . . . . . . . . . . . . . . . . 39 II.1.1 CONTINUUM APPROXIMATION . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 II.1.2 GOVERNING EQUATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 II.2 BENCHMARK PROBLEM SIMULATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 II.2.1 CASE 1: THREE-DIMENSIONAL SINGLE SPECIES TRANSPORT FROM A CONTINUOUS RECTANGULAR-PRISMATIC SOURCE RELEASE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 II.2.2 CASE 2: ONE-DIMENSIONAL TRANSPORT OF A THREE MEMBER DECAY CHAIN FROM A CONTINUOUS POINT SOURCE RELEASE . . 58

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TABLE OF CONTENTS (continued) Page CHAPTER III – STUDY AREA HYDROGEOLOGY AND CHEMICAL DISTRIBUTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 III.1 HYDROGEOLOGIC SETTING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 III.2 HYDROSTRATIGRAPHY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 III.3 HYDRAULIC PROPERTIES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 III.4 GROUNDWATER SOURCES AND SINKS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 III.5 GROUNDWATER FLOW DIRECTIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 III.6 CHEMICAL MEASUREMENT, TRANSPORT PROCESSES, AND DISTRIBUTION . . 71 III.6.1 DISSOLVED CHEMICALS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 III.6.1.1 FIELD SAMPLING PROCEDURES . . . . . . . . . . . . . . . . . . 72 III.6.1.2 LABORATORY MEASUREMENT PROCEDURES . . . . . . . . 73 III.6.2 SOURCE RELEASE AREAS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 III.6.3 RELEVANT PHYSICAL AND CHEMICAL TRANSPORT PROCESSES . . 76 III.6.3.1 ADVECTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 III.6.3.2 HYDRODYNAMIC DISPERSION . . . . . . . . . . . . . . . . . . . 77 III.6.3.3 ADSORPTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 III.6.3.4 DEGRADATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 III.6.3.4.1 ABIOTIC DEGRADATION . . . . . . . . . . . . . 81 III.6.3.4.2 BIODEGRADATION . . . . . . . . . . . . . . . . . . 83 III.6.4 OBSERVED CHEMICAL DISTRIBUTION . . . . . . . . . . . . . . . . . . . . . . 92 III.6.4.1 CALIBRATION (1984, 1989, AND 1991) AND VERIFICATION (1992) DATES . . . . . . . . . . . . . . . . . . . 92 III.6.4.2 MODEL PREDICTION DATES (1996 AND 2001) . . . . . 100 III.6.4.3 MASS BALANCE CALCULATIONS . . . . . . . . . . . . . . . . 105 III.6.4.4 EVALUATION OF DEGRADATION MECHANISM . . . . . . 109 III.6.5 QUANTITATIVE ANALYSIS OF BIODEGRADATION RATE . . . . . . . 114 CHAPTER IV – MODEL CONSTRUCTION AND CALIBRATION PROCEDURE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122 IV.1 MATHEMATICAL MODEL AND FINITE DIFFERENCE MODEL CONSTRUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 IV.1.1 METHOD OF SOLUTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 IV.1.2 MODEL DISCRETIZATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 IV.1.3 INITIAL AND BOUNDARY CONDITIONS . . . . . . . . . . . . . . . . . . . . 128 IV.1.3.1 SOURCE MASS RELEASE RATE AND DURATION . . . . . 129 IV.1.3.2 HISTORICAL SOURCE RELEASE TIMING AND WELL PUMPING SCHEDULES . . . . . . . . . . . . . . . . . . . . . . . . 130 v

TABLE OF CONTENTS (continued) Page IV.1.4 FLOW PARAMETER VALUES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 IV.1.5 TRANSPORT AND REACTION PARAMETER VALUES . . . . . . . . . . . 135 IV.2 MODEL CALIBRATION PROCEDURE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138 IV.2.1 FLOW CALIBRATION TARGETS, CALIBRATION CRITERIA , AND INVERSE PARAMETER ESTIMATION PROCEDURE . . . . . . . . . . . . . 138 IV.2.2 TRANSPORT CALIBRATION TARGETS, CALIBRATION CRITERIA , AND PROCEDURE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144 CHAPTER V – GROUNDWATER FLOW AND SOLUTE TRANSPORT MODEL RESULTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148 V.1 GROUNDWATER FLOW CALIBRATION RESULTS AND ANALYSIS . . . . . . . . . . 149 V.1.1 CALIBRATED HYDRAULIC HEADS . . . . . . . . . . . . . . . . . . . . . . . . 150 V.1.2 ANALYSIS OF FLOW CALIBRATION ACCURACY . . . . . . . . . . . . . 152 V.1.2.1 FLOW MODEL SENSITIVITY ANALYSIS . . . . . . . . . . . . 154 V.1.2.2 FLOW MODEL UNCERTAINTY ANALYSIS . . . . . . . . . . . 155 V.1.3 MODEL WATER BALANCE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 V.1.4 GROUNDWATER VELOCITY FIELD ANALYSIS . . . . . . . . . . . . . . . 160 V.2 CALIBRATED RATE CONSTANTS, MODEL RESULTS, AND ANALYSIS . . . . . . 164 V.2.1 SIMULATED HYDRAULIC HEADS AND TCE, DCE, AND VC CONCENTRATIONS DURING CALIBRATION PERIOD (1981 TO 1991) AND 1992 VERIFICATION . . . . . . . . . . . . . . . . . . . . . . . . . 168 V.2.2 SIMULATED HYDRAULIC HEADS AND TCE, DCE, AND VC CONCENTRATIONS DURING PREDICTION PERIOD (1993- 2020) . 176 V.2.3 MODEL CALCULATED CONTAMINANT MASS BALANCE AND ESTIMATED CLEANUP TIME FOR PUMP-AND-TREAT VERSUS NATURAL BIODEGRADATION . . . . . . . . . . . . . . . . . . . . . . . . . . . 181 V.2.4 ANALYSIS OF TRANSPORT MODEL ACCURACY . . . . . . . . . . . . . . 184 V.2.4.1 TRANSPORT AND REACTION PARAMETER FIRST ORDER ERROR SENSITIVITY ANALYSIS . . . . . . . . . . . 186 V.2.4.2 TRANSPORT MODEL UNCERTAINTY ANALYSIS . . . . . . 187 CHAPTER VI – CONCLUSIONS AND RECOMMENDATIONS . . . . . . . . . . . . . . . 192 APPENDIX A – MODEL OUTPUT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 348 APPENDIX B – DESCRIPTION OF GIS ANALYSIS TOOL TINMASS . . . . . . . . . . . . . . . . . 363

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TABLE OF CONTENTS (continued) Page REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 366 VITA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 409

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LIST OF TABLES Page 3-1. 3-2. 3-3. 3-4. 3-5. 3-6. 3-7. 3-8. 3-9. 3-10. 3-11. 3-12. 3-13. 3-14. 4-1. 5-1. 5-2. 5-3. 5-4. 5-5. 5-6. 5-7. 5-8. 5-9.

Historical average 1989 - 1991 pumping rates for GDU/PBU supply wells and recovery wells. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203 Hydrogeologic parameters for study area. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205 Summary of water level data collected in December 1996 and November 2001. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206 Degradation mechanisms for PCE (tetrachloroethene) and 1,1,1-TCA. . . . . . . 211 Summary of estimated source release times and pumping schedules. . . . . . . . . 212 Summary of important processes acting on chlorinated compounds in the subsurface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213 Relative effects of advection, dispersion, sorption, and biodegradation on plume migration from a continuous source. . . . . . . . . . . . . . . . . . . . . . . . . . . . 214 Summary of possible degradation mechanisms in the study area. . . . . . . . . . . . 215 Effect of electron acceptor conditions and redox potential on feasibility of CAH reductive dechlorination. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217 Degradation parameters measured during November 2001 sampling event at study area. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 218 Summary of natural attenuation data collected in November 2001 at the study area. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 Summary of TCE and VC mass removed from each pumping well based on field data collected from 1985 to 2001. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220 Mass balance analyses for TCE and VC for field data collected from 1984 to 2001. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 221 Model Parameter Values for BIOCHLOR model. . . . . . . . . . . . . . . . . . . . . . . . 222 Summary of source release times and pumping schedules in solute transport model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223 Pumping rates for GDU/PBU supply wells and recovery wells for the transport model calibration. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224 Estimated flow model parameter values. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227 Study area values for solute transport model field data. . . . . . . . . . . . . . . . . . . 228 Study area values for solute transport model. . . . . . . . . . . . . . . . . . . . . . . . . . . 229 Observed versus simulated water-levels for the calibrated model. . . . . . . . . . . 230 Flow model calibration statistics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233 Summary of flow model sensitivity analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . 234 Solute transport model calibration criteria and number of calibration targets . . 235 Observed versus simulated TCE, DCE, and VC concentrations for the calibrated model in 1984. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236 viii

LIST OF TABLES (continued) Page 5-10. Observed versus simulated TCE, DCE, and VC concentrations for the calibrated model in 1991. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 240 5-11. Observed versus simulated TCE, DCE, and VC concentrations for the calibrated model in 1996. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 244 5-12. Observed and simulated TCE concentrations for the calibrated model in 2001. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247 5-13. Model calculated total TCE mass released from each source area. . . . . . . . . . . 248 5-14. Summary of cumulative mass balance results for TCE, DCE, and VC in the model in 2001. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249 5-15. Estimated clean-up date for each recovery system based on model simulation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 250 5-16. Summary of transport model calibration statistics during calibration period. . . 251 5-17. Summary of transport model calibration statistics during the prediction period. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 252

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LIST OF FIGURES Page 1-1. 1-2.

Site Location Map. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 254 Location and Average 1989 - 1991 Pumping Rates of GDU/PBU Supply Wells and Harris Recovery Wells. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255 2-1. Definition of Porosity and Representative Elementary Volume. . . . . . . . . . . . . 256 2-2. Comparison of AT123D97 and MT3D results for three-dimensional transport at 30 days and a depth 1.25 m. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 257 2-3. Comparison of AT123D97 and MT3D results for three-dimensional transport at 30 days and a depth 12.5 m. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 258 2-4. Comparison of AT123D97 and MT3D results for three-dimensional transport at 300 days and a depth 1.25 m. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 259 2-5. Comparison of AT123D97 and MT3D results for three-dimensional transport at 300 days and a depth 12.5 m. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 260 2-6. Comparison of analytical solution and MT3D results for one-dimensional parent-daughter chains during transport. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 261 3-1. Generalized Stratigraphic Column. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 262 3-2. Map of Cross Section Transects A-A' and B-B' . . . . . . . . . . . . . . . . . . . . . . . . . 263 3-3. Cross Section A-A' with 1992 and 2001 Composite Plumes Along Approximate Flowpath. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 264 3-4. Cross Section B-B' with 1992 and 2001 Composite Plumes. . . . . . . . . . . . . . . 265 3-5. Observed 1991 Water-Level Contour Map of 4.5 m Depth Zone at Semiconductor Campus. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 266 3-6. Observed Water-Level Contour Map of 12 m Depth Zone Based on Average Water Level Data Collected in 1989, 1990, and 1991. . . . . . . . . . . . . . . . . . . . 267 3-7. Observed Water-Level Contour Map of 25 m Depth Zone Based on 1989, 1990, and 1991 Average. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 268 3-8. Observed Water-Level Contour Map of 4.5 m Depth Zone at Semiconductor Campus Based on Data Collected in 1996. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269 3-9. Observed 1996 Water-Level Contour Map of 12 m Depth Zone Based on Data Collected in 1996. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 270 3-10. Observed 1996 Water-Level Contour Map of 25 m Depth Zone Based on Data Collected in 1996. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271 3-11. Trichloroethene Source Areas in the Solute Transport Model. . . . . . . . . . . . . . 272 3-12. Plots of Longitudinal Dispersivity, Horizontal Transverse Dispersivity, and Vertical Transverse Dispersivity Values Versus Observed Scale. . . . . . . . . . . . 273 x

LIST OF FIGURES (continued) Page 3-13. Observed 1984 Average Trichloroethene, 1,2 Dichloroethene (total), and Vinyl Chloride in the 4.5 m Zone. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 274 3-14. Observed 1984 Average Trichloroethene, 1,1 Dichloroethene, and Vinyl Chloride Concentrations (:g/L) in the 12 m Depth Zone. . . . . . . . . . . . . . . . . . 275 3-15. Observed 1984 Average Trichloroethene, 1,1 Dichloroethene, and Vinyl Chloride Concentrations (:g/L) in the 25 m Depth Zone. . . . . . . . . . . . . . . . . . 276 3-16. Observed 1989 Average Trichloroethene, 1,1 Dichloroethene, and Vinyl Chloride Concentrations (:g/L) in the 4.5 m Depth Zone. . . . . . . . . . . . . . . . . 277 3-17. Observed 1989 Average Trichloroethene, 1,1 Dichloroethene, and Vinyl Chloride Concentrations (:g/L) in the 12 m Depth Zone. . . . . . . . . . . . . . . . . . 278 3-18. Observed 1989 Average Trichloroethene, 1,1 Dichloroethene, and Vinyl Chloride Concentrations (:g/L) in the 25 m Depth Zone. . . . . . . . . . . . . . . . . . 279 3-19. Observed 1991 Average Trichloroethene, 1,1 Dichloroethene, and Vinyl Chloride Concentrations (:g/L) in the 4.5 m Depth Zone. . . . . . . . . . . . . . . . . 280 3-20. Observed 1991 Average Trichloroethene, 1,1 Dichloroethene, and Vinyl Chloride Concentrations (:g/L) in the 12 m Depth Zone. . . . . . . . . . . . . . . . . . 281 3-21. Observed 1991 Average Trichloroethene, 1,1 Dichloroethene, and Vinyl Chloride Concentrations (:g/L) in the 25 m Depth Zone. . . . . . . . . . . . . . . . . . 282 3-22. Observed 1992 Average Trichloroethene, 1,1 Dichloroethene, and Vinyl Chloride Concentrations (:g/L) in the 4.5 m Depth Zone. . . . . . . . . . . . . . . . . 283 3-23. Observed 1992 Average Trichloroethene, 1,1 Dichloroethene, and Vinyl Chloride Concentrations (:g/L) in the 12 m Depth Zone. . . . . . . . . . . . . . . . . . 284 3-24. Observed 1992 Average Trichloroethene, 1,1 Dichloroethene, and Vinyl Chloride Concentrations (:g/L) in the 25 m Depth Zone. . . . . . . . . . . . . . . . . . 285 3-25. Observed 1996 Average Trichloroethene, 1,1 Dichloroethene, and Vinyl Chloride Concentrations (:g/L) in the 4.5 m Depth Zone. . . . . . . . . . . . . . . . . 286 3-26. Observed 1996 Average Trichloroethene, 1,1 Dichloroethene, and Vinyl Chloride Concentrations (:g/L) in the 12 m Depth Zone. . . . . . . . . . . . . . . . . . 287 3-27. Observed 1996 Average Trichloroethene, 1,1 Dichloroethene, and Vinyl Chloride Concentrations (:g/L) in the 25 m Depth Zone. . . . . . . . . . . . . . . . . . 288 3-28. Observed 2001 Average Trichloroethene, 1,1 Dichloroethene, and Vinyl Chloride Concentrations (:g/L) in the 4.5 m Depth Zone. . . . . . . . . . . . . . . . . 289 3-29. Observed 2001 Average Trichloroethene, 1,1 Dichloroethene, and Vinyl Chloride Concentrations (:g/L) in the 12 m Depth Zone. . . . . . . . . . . . . . . . . . 290 3-30. Observed 2001 Average Trichloroethene, 1,1 Dichloroethene, and Vinyl Chloride Concentrations (:g/L) in the 25 m Depth Zone. . . . . . . . . . . . . . . . . . 291 3-31. Measured Alkalinity (mg/L) in the 4.5 m, 12 m, and 25 m Depth Zones in December 2001. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 292 xi

LIST OF FIGURES (continued) Page 3-32. Measured Chloride (mg/L) in the 4.5 m, 12 m, and 25 m Depth Zones in December 2001. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 293 3-33. Measured Fe+2 (mg/L) in the 4.5 m, 12 m, and 25 m Depth Zones in December 2001. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 294 3-34. Measured Methane(mg/L) in the 4.5 m, 12 m, and 25 m Depth Zones in December 2001. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 295 3-35. Measured Total Organic Carbon (TOC) (mg/L) in the 4.5 m, 12 m, and 25 m Depth Zones in December 2001. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 296 3-36. Measured Sulfate (mg/L) in the 4.5 m, 12 m, and 25 m Depth Zones in December 2001. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 297 3-37. Measured Sulfide (mg/L) in the 4.5 m, 12 m, and 25 m Depth Zones in December 2001. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 298 3-38. Measured Ethene (:g/L) in the 4.5 m, 12 m, and 25 m Depth Zones in December 2001. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299 3-39. BIOCHLOR Results and Observed 1984 Trichloroethene, 1,1 Dichloroethene, and Vinyl Chloride Concentrations (:g/L) for Monitor Wells Along the Building 6 Plume Centerline. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 300 4-1. Model Boundary Conditions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 301 4-2. Model Grid and Boundary Conditions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 302 4-3. Transport Model Calibration Process. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 303 5-1. Simulated Regional Steady-State Water Levels in the 4.5 m Depth Zone. . . . . 304 5-2. Simulated Local Steady-State Water Levels in the 4.5 m Depth Zone. . . . . . . . 305 5-3. Simulated Regional Steady-State Water Levels in the 12 m Depth Zone. . . . . 306 5-4. Simulated Local Steady-State Water Levels in the 12 m Depth Zone. . . . . . . . 307 5-5. Simulated Regional Steady-State Water Levels in the 25 m Depth Zone. . . . . 308 5-6. Simulated Local Steady-State Water Levels in the 25 m Depth Zone. . . . . . . . 309 5-7. Plot of Simulated Versus Observed Water Level at Model Target Locations. . 310 5-8. Plot of Residual Versus Observed Water Level at Model Target Locations. . . 311 5-9. Leakance Zonation Between 4.5 m and 12 m Depth Zones. . . . . . . . . . . . . . . . 312 5-10. Leakance Zonation Between 12 m and 25 m Depth Zones. . . . . . . . . . . . . . . . 313 5-11. Calibrated Model Water Budget, Palm Bay, Florida. . . . . . . . . . . . . . . . . . . . . 314 5-12. Groundwater Velocity (m/day) Distribution in the 4.5 m Depth Zone. . . . . . . . 315 5-13. Groundwater Velocity (m/day) Distribution in the 12 m Depth Zone. . . . . . . . 316 5-14. Groundwater Velocity (m/day) Distribution in the Aquitard Located Between 12 m and 25 m Depth Zones. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 317 5-15. Groundwater Velocity (m/day) Distribution in the 25 m Depth Zone. . . . . . . . 318 5-16. Forward Particle Tracking Results and Travel Times (days) in the Surficial Aquifer. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 319 xii

LIST OF FIGURES (continued) Page 5-17. Recovery Well Capture Zone in the 4.5 m Depth Zone of the Surficial Aquifer at Semiconductor Campus. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 320 5-18. Recovery Well Capture Zone in the 12 m Depth Zone of the Surficial Aquifer at Semiconductor Campus. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 321 5-19. Recovery Well Capture Zone in the 25 m Depth Zone of the Surficial Aquifer at Electronics Systems Campus. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 322 5-20. Recovery Well Capture Zone in the 25 m Depth Zone of the Surficial Aquifer at Electronics Systems Campus. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323 5-21. Recovery Well Capture Zone in the 12 m Depth Zone of the Surficial Aquifer at Building 100. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 324 5-22. Simulated Local 1967 Water Levels in the 4.5, 12, and 25 m Depth Zones. . . 325 5-23. Simulated Local 1975 Water Levels in the 4.5, 12, and 25 m Depth Zones. . . 326 5-24. Simulated Local 1982 Water Levels in the 4.5, 12, and 25 m Depth Zones. . . 327 5-25. Simulated 1984 Trichloroethene, 1,2 Dichloroethene (total), and Vinyl Chloride Concentrations (:g/L) in the 4.5 m Depth Zones. . . . . . . . . . . . . . . . 328 5-26. Simulated 1984 Trichloroethene, 1,2 Dichloroethene (total), and Vinyl Chloride Concentrations (:g/L) in the 12 m Depth Zones. . . . . . . . . . . . . . . . . 329 5-27. Simulated 1984 Trichloroethene, 1,2 Dichloroethene (total), and Vinyl Chloride Concentrations (:g/L) in the 25 m Depth Zones. . . . . . . . . . . . . . . . . 330 5-28. Simulated Local 1989 Water Levels in the 4.5, 12, and 25 m Depth Zones. . . 331 5-29. Simulated 1989 Trichloroethene, 1,2 Dichloroethene (total), and Vinyl Chloride Concentrations (:g/L) in the 4.5 m Depth Zones. . . . . . . . . . . . . . . . 332 5-30. Simulated 1989 Trichloroethene, 1,2 Dichloroethene (total), and Vinyl Chloride Concentrations (:g/L) in the 12 m Depth Zones. . . . . . . . . . . . . . . . . 333 5-31. Simulated 1989 Trichloroethene, 1,2 Dichloroethene (total), and Vinyl Chloride Concentrations (:g/L) in the 25 m Depth Zones. . . . . . . . . . . . . . . . . 334 5-32. Simulated 1992 Trichloroethene, 1,2 Dichloroethene (total), and Vinyl Chloride Concentrations (:g/L) in the 4.5 m Depth Zones. . . . . . . . . . . . . . . . 335 5-33. Simulated 1992 Trichloroethene, 1,2 Dichloroethene (total), and Vinyl Chloride Concentrations (:g/L) in the 12 m Depth Zones. . . . . . . . . . . . . . . . . 336 5-34. Simulated 1992 Trichloroethene, 1,2 Dichloroethene (total), and Vinyl Chloride Concentrations (:g/L) in the 25 m Depth Zones. . . . . . . . . . . . . . . . . 337 5-35. Simulated Local 1996 Water Levels in the 4.5, 12, and 25 m Depth Zone. . . . 338 5-36. Simulated 1996 Trichloroethene, 1,2 Dichloroethene (total), and Vinyl Chloride Concentrations (:g/L) in the 4.5 m Depth Zones. . . . . . . . . . . . . . . . 339

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LIST OF FIGURES (continued) Page 5-37. Simulated 1996 Trichloroethene, 1,2 Dichloroethene (total), and Vinyl Chloride Concentrations (:g/L) in the 12 m Depth Zones. . . . . . . . . . . . . . . . . 340 5-38. Simulated 1996 Trichloroethene, 1,2 Dichloroethene (total), and Vinyl Chloride Concentrations (:g/L) in the 25 m Depth Zones. . . . . . . . . . . . . . . . . 341 5-39. Simulated Local 2001 Water Levels in the 4.5, 12, and 25 m Depth Zone. . . . 342 5-40. Simulated 2001 Trichloroethene, 1,2 Dichloroethene (total), and Vinyl Chloride Concentrations (:g/L) in the 4.5 m Depth Zones. . . . . . . . . . . . . . . . 343 5-41. Simulated 2001 Trichloroethene, 1,2 Dichloroethene (total), and Vinyl Chloride Concentrations (:g/L) in the 12 m Depth Zones. . . . . . . . . . . . . . . . . 344 5-42. Simulated 2001 Trichloroethene, 1,2 Dichloroethene (total), and Vinyl Chloride Concentrations (:g/L) in the 25 m Depth Zones. . . . . . . . . . . . . . . . . 345 5-43. Simulated Trichloroethene, 1,2 Dichloroethene (total), and Vinyl Chloride Concentration Versus Time Near Source Well GS-35S. . . . . . . . . . . . . . . . . . . 346 5-44. Simulated and Observed Trichloroethene, 1,2 Dichloroethene (total), and Vinyl Chloride Concentration Versus Time at Downgradient Pumping Well GS-124D. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347

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NOMENCLATURE aH

horizontal transverse dispersivity (L)

aL

longitudinal dispersivity (L)

aV

vertical transverse dispersivity (L)

bls

below land surface

C

concentration of the solute in groundwater (ML-3);

CAH

chlorinated aliphatic hydrocarbon

Cr

concentration of a source of water (ML-3);

D*

molecular diffusion coefficient (L2/T)

DCA

dichloroethane

DCE

1,2 dichloroethene, total of cis and trans isomers

Dij

values of the hydrodynamic dispersion tensor (L2T-1);

DNAPL

dense nonaqueous phase liquid

e

residual

ESS

Electronic Systems Sector

Gb

gigabyte

Ghz

gigahertz

GDU

General Development Utilities

GDU-10

General Development Utilities water supply well #10

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GIS

geographic information system

GS35D

monitoring well no. 35 in the 25 m depth zone

GS35S

monitor well no. 35 in the 12 m depth zone

h

hydraulic head (L)

Kd

soil-water partition coefficient (L3/M)

Kij

hydraulic conductivity tensor (L/T)

km

kilometer (L)

Kn

Knudsen number

Koc

octonal-water partition coefficient (L3/M)

L

characteristic length scale (L)

8i

first-order decay or degradation constant of species i (T-1).

m

meter (L)

:g/L

micrograms per liter (M/L3)

M-1

monitor well no. 1 in the 4.5 m depth zone

Mb

megabyte

MCL

maximum contaminant level

MGD

million gallons per day (L3/T)

MHZ

megahertz

MODFLOW Modular Three-Dimensional Finite-Difference Ground-Water Flow Model MODPATH

Program that computes pathlines from MODFLOW

MSL

mean sea level (L)

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MT3D

Modular Three-Dimensional Transport Model for Simulation of Advection, Dispersion, and Chemical Reactions of Contaminants in Groundwater Systems

n

total porosity (-)

ne

effective porosity (-);

ORP

oxidation-reduction potential (ML2/T3A)

OU

Operable Unit

PBU

Palm Bay Utilities

PCE

tetrachloroethene

REV

representative elementary volume

Ri

retardation factor of species i (-);

RSD

residual standard deviation

RSS

residual sum of the squares

SC

Semiconductor Campus

Ss

specific storage (L-1)

Sy

specific yield (-)

t

time (T)

TCA

Trichloroethane

TCE

Trichloroethene

USEPA

United States Environmental Protection Agency

USGS

United States Geological Survey

v

average linear groundwater velocity (L/T)

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VC

vinyl chloride

VOC

volatile organic compound

W

volumetric flux per unit volume

W+

volumetric flux per unit volume of a source of water (T-1);

W-

volumetric flux per unit volume of a sink of water (T-1); and

xj

coordinate axes (L)

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SUMMARY Over the past 25 years, evidence has accumulated that our groundwater resources, which provide more than 50 percent of the drinking water in the U.S., are being threatened by contamination caused by industrial, commercial, and agricultural activities. More than 300,000 sites are estimated to have groundwater or soil contamination with cleanup times ranging from a few years to thousands of years (National Research Council, 1994). In order to develop new approaches and innovative cleanup technologies for groundwater pollution, interdisciplinary research is being performed to better understand not only key individual physical, chemical, and biological processes but also the combined effects of each process as part of a more complex environmental system. One important area of current research is the development of numerical models of increasing complexity that accurately simulate the primary physical, chemical, and biological processes that affect the fate and transport of dissolved contaminants in shallow, unconfined aquifers. Most of the current quantitative models of subsurface groundwater and geochemical conditions are limited in their accuracy primarily because of complex subsurface heterogeneity and the excessive expense to collect sufficient data to accurately calibrate the models. Because of the slow movement of contaminants in groundwater, data collection must be extensive spatially and occur for a long period of time to observe significant changes in concentration levels. This is particularly the case

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for the slowly degrading chlorinated solvents, including trichloroethene (TCE), which are commonly used at industrial facilities across the U.S. This dissertation provides one of the first comprehensive model calibration and predictive analyses of field-scale sequential TCE-DCE-VC degradation using extensive amounts of three-dimensional data collected over a 20-year period. The primary objective of this research is to analyze the field data and quantitatively examine the effects of advection, hydrodynamic dispersion, sorption, recharge dilution, and determine long-term field-scale anaerobic biodegradation rate constants for dissolved TCE, cis 1,2 dicloroethene (DCE), and vinyl chloride (VC) in the study area. In addition, the relative importance of pump-and-treat and natural biodegradation during remediation is examined. The Harris Palm Bay facility was selected for this analysis because it is has a well characterized, relatively homogenous hydrogeologic setting, and is naturally anaerobic. The multispecies model MT3D99 was calibrated to data from 1981 to 1991 and then was critically examined based on its ability to match an independent set of data from 1992 to 2001. Because of the current interest in natural attenuation and the fact that field-scale biodegradation rates of chlorinated solvents are not well constrained (Suarez and Rifai 1999; Aronson and Howard, 1997; Wiedemeier et al., 1999; USEPA, 1998; Sturman et al., 1995), this dissertation therefore provides more accurate estimates of field-scale biodegradation rates for TCE, DCE (cis), and VC in a naturally occurring anaerobic aquifer.

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Results of the model calibration demonstrated the ability of multispecies reactive transport models to accurately simulate plume-scale spatial and temporal variations of dissolved chlorinated solvents. Using an automated inverse parameter estimation code for MODFLOW, an accurate flow model calibration was achieved with a low mean residual (0.0091 m) and standard deviation (0.31 m) based on the 7.9 m observed range in hydraulic heads for 91 targets in this complex three-dimensional flow field. For the transport model, a manual calibration was performed and met the calibration criteria during both the calibration period (1981 to 1991) and prediction period (1992 to 2001). Within the central core of the plumes where most of the contaminant mass occurs, the simulated concentrations of TCE, DCE, and VC were generally within a factor of three of observed concentrations. This level of accuracy was less than the observed variability of the concentration data and was met over a 20-year period in which levels changed significantly from approximately 10,000 :g/L in 1981 to near nondetect (< 1 :g/L) in 2001. Multispecies models provide better estimates of rate constants for sequential biodegradation than single species models because multispecies models simultaneously simulate the mass balance between each reacting chemical. Using the multispecies model MT3D99, the calibrated first-order field-scale biodegradation rate constants (half lives) for TCE, DCE (cis), and VC were 0.46 yr-1 (550 days), 0.53 yr-1 (480 days), and 0.43 yr-1 (590 days), respectively for the 25 °C groundwater temperatures at the site. Based on available data including values in Wiedemeier et al. (1999) and Aronson and Howard

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(1997), these calibrated first order field-scale biodegradation rate constants are in the upper-range of observed field biodegradation rate constants (half lives) for TCE with observed values ranging from 0.053 yr-1 (4800 days) - 0.90 yr-1 (280 days). The calibrated rate constants (half lives) are in the mid-range of field-scale values for both cis DCE, which ranged respectively from 0.18 yr-1 (1400 days) - 3.3 yr-1 (77 days), and VC, which ranged from 0.12 yr-1 (2100 days) - 2.6 yr-1 (97 days). Results of this study indicate that biodegradation was the dominant removal mechanism for cleanup. For the period from commencement of pumping in 1985 until 2001, the recovery wells removed approximately 2.3 %, 9.4 %, and 24 %, respectively, of the TCE, DCE, and VC mass removed from groundwater in the study area by 2001. Over this same period (19852001), natural biodegradation removed approximately 94%, 88%, and 73%, of the TCE, DCE, and VC mass removed from groundwater in the study area. Additional model simulations indicated that the cleanup standards are reached approximately 30 percent faster with pump-and-treat than with natural biodegradation as the sole remedy at this study area.

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CHAPTER I RESEARCH OBJECTIVE AND BACKGROUND I.1

INTRODUCTION

Over the past 25 years, there has been increasing evidence that groundwater resources, which provide more than 50 percent of the drinking water in the U.S., are being threatened by contamination resulting from industrial, commercial, and agricultural activities. It has been estimated that over 300,000 sites have groundwater or soil contamination (NRC, 1994). Many of these sites are impacted with chlorinated solvents, which are difficult to remediate because chemicals such as trichloroethene (TCE) biodegrade slowly and form more toxic chemicals such as vinyl chloride (VC) in groundwater. Monitored Natural Attenuation (MNA) is now being implemented for many sites impacted by TCE with reductions in contaminant mass expected to occur as a result of natural biodegradation processes. Unfortunately, our understanding of the sustainability of biodegradation of both TCE and its degradation products (1,2 cis dichloroethene [DCE] and VC) is limited, and there is significant uncertainty in the long- term biodegradation rate constants of these compounds (Suarez and Rifai 1999; Aronson and Howard, 1997; Wiedemeier et al., 1999; Sturman et al., 1995). Accurate field-scale values of natural biodegradation rate constants for solvents such as TCE, DCE (cis), and 1

VC are essential in order to predict cleanup times at sites employing not only MNA but also other remedies including pump-and-treat. Aquifer cleanup technologies such as pump-and-treat have been found to be very costly and may be required for long periods of time to reach health-based cleanup standards. Some of the causes for the lack of success of pump-and-treat include: 1) slow rates of contaminant diffusion from low permeability zones; 2) slow rates of degradation and desorption; 3) presence of localized zones of trapped, nonaqueous phase contaminants that slowly dissolve into groundwater; and 4) very low concentration levels of cleanup goals (NRC, 1995). At the few sites where pump-and-treat has been successful, biodegradation may have also played an important role. An accurate assessment of the biodegradation rates of the contaminants would allow one to determine the relative importance mass removal by pump-and-treat versus natural biodegradation. The determination of accurate biodegradation rate constants of slowly degrading chemicals such as TCE, DCE (cis), and VC requires large amounts of chemical data collected over long periods of time in order to examine trends of both parent and daughter products. In addition, isolating the effects of biodegradation in groundwater is complicated by the fact that subsurface contaminants are affected by a number of natural attenuation mechanisms including advection, hydrodynamic dispersion, sorption, recharge dilution, and biodegradation. Recovery wells also remove contaminant mass from the subsurface. In order to examine and quantify the effects of these additional mechanisms, both data analyses (e.g. Wiedemeier et al., 1999) and numerical modeling

2

(e.g. Zheng and Bennett, 1995) can be applied. Data analyses include examining the production of daughter products (DCE and VC), production of chloride, changes in dissolved mass-in-place over time, mass balance analyses, and identifying the terminal electron accepting process (TEAP) of microorganisms. Using the conceptual model formulated from analyses of the data collected in the study area, the field-scale biodegradation rate constants can be determined by calibrating numerical transport models through varying biodegradation rate constant values until the concentration and mass balance of each chemical during sequential TCE-DCE-VC biodegradation are matched over the period of available data. The groundwater contaminant plumes at the Harris Palm Bay, FL facility are an excellent study area to examine and quantify the effects advection, hydrodynamic dispersion, sorption, and sequential TCE-DCE-VC biodegradation. This study area has a large amount of three-dimensional data collected from over 200 monitoring wells for a 20 year period (Post, Buckley, Schuh and Jernigan, Inc., 1983; 1984; Geraghty & Miller, 1987; L.S. Sims & Associates, 1997; 1998; 1999; 2000; 2001; 2002). In aerobic aquifers, biodegradation rates are more difficult to determine because of multiple redox conditions with anaerobic conditions occurring within the cores of plumes and aerobic conditions occurring along the plume edge. At this study area, the surficial aquifer is naturally anaerobic (Post, Buckley, Schuh and Jernigan, Inc., 1983; L.S. Sims & Associates, 2002), which allows one to isolate and focus on the anaerobic biodegradation mechanism of TCE, DCE, and VC over a 20 year period. The plumes are also under hydraulic control

3

by site recovery wells, which prevents unaccounted mass losses from advective and dispersive plume mass flux out of the monitor well network. Because the mass removal rates of TCE, DCE, and VC by the recovery wells are well constrained, the remaining plume mass losses from biodegradation can be determined for a more accurate estimation of biodegradation rates. Given the extensive amount of data collected both spatially and temporally that constrain the numerical model, the Harris facility in Palm Bay, Florida was chosen for the research objective of this dissertation. This research consists of a detailed three-dimensional quantitative analysis of historical and future geochemical conditions at this study area. Although many groundwater and contaminant transport model studies have been performed (see Anderson [1995] for review), very few have been calibrated with extensive amounts of field data for three-dimensional flow and transport of multiple chlorinated compound chain degradation and then later examined carefully in terms of their level of predictive accuracy for a 20-year period of data. In this study, a groundwater flow and reactive transport model was calibrated to trichloroethene (TCE), total (cis and trans) 1,2 dichloroethene (DCE), and vinyl chloride (VC) concentrations from 1981 to 1991. The calibrated model was later critically evaluated in terms of its ability to predict these concentrations for the ten-year period (1992-2001) after the calibration was performed. This quantitative analysis and critical evaluation will: 1) provide useful estimates of the long-term field-scale degradation rates of TCE, DCE (cis), and VC for use in future bioremediation and field-scale studies; 2) elucidate the relative effects of advection,

4

hydrodynamic dispersion, sorption, recharge dilution, and biodegradation on TCE, DCE, and VC concentration levels both spatially and temporally; and 3) provide a better understanding of the predictive capabilities of currently available three-dimensional groundwater flow and solute transport models to simulate multiple dissolved chemical species over time using a high quality data set.

I.2

DISSERTATION OBJECTIVE

The primary objective of this research is to analyze the field data and quantitatively examine the effects of advection, hydrodynamic dispersion, sorption, recharge dilution, and determine long-term field-scale anaerobic biodegradation rate constants for dissolved TCE, DCE (cis), and VC. This research includes numerical groundwater flow and solute transport modeling to simulate TCE, DCE, and VC concentration levels from the Building 6 spill in 1967 until cleanup standards are met. As part of this objective, the key tasks of this research will be to: 1) accurately estimate the bulk hydraulic conductivity of the surficial aquifer using inverse flow calibration and simulate the three-dimensional velocity field; 2) calibrate a solute transport model to observed TCE, DCE, and VC data from 1981 to 1991; 3) determine field-scale anaerobic biodegradation rates for TCE, DCE (cis), and VC; 4) critically examine the predictive capability of the numerical model to match observed data from 1992 to 2001; and 5) examine the effectiveness of mass removal by pump-and-treat versus natural biodegradation during cleanup. Given the better known release timing and the large

5

plumes associated with the Building 6 source area (Figure 1-2), this dissertation will more carefully evaluate the dynamics of the Building 6 plumes. Effects of uncertainties of key model parameters will be examined through sensitivity analyses.

I.3

ORGANIZATION OF DISSERTATION

The dissertation is organized into six chapters and two appendices. A brief description of each chapter and appendix is provided below. The remainder of Chapter I provides a detailed literature review of both biodegradation rate constants for TCE, DCE (cis), and VC and previous field-scale numerical modeling studies of contaminants in groundwater. A more detailed discussion is then provided of this research for comparison with previous work. Chapter I concludes with a description of the study area that was selected in order to performed detailed analyses and achieve the objective of this dissertation. Chapter II provides background information on the governing equations and key assumptions utilized in the application of numerical groundwater flow and solute transport modeling. Two new benchmark simulations are then presented to expand the number of code comparisons to the numerical model MT3D (Zheng and Wang, 1998) and to more carefully examine the capabilities of this numerical model for simulating the problem of interest in this dissertation. The first benchmark simulation examines threedimensional single species transport from a continuous rectangular-prismatic source area by comparing MT3D results with a recently updated version of AT123D (Lester et al, 2002). The second benchmark simulation examines one-dimensional transport of three 6

species from a point source by comparing MT3D results with the recently developed code BIOCHLOR (Aziz et al., 2000). Chapter III provides a detailed description of the hydrogeologic and geochemical setting of the study area. This chapter presents the large amount of data collected in the study area and the detailed analyses of this data in order to formulate a conceptual model of advection, hydrodynamic dispersion, sorption, and biodegradation of TCE, DCE, and VC in groundwater. Chapter III initially describes the hydrogeologic setting and then presents the observed spatial distribution and temporal changes in concentration levels of dissolved TCE, DCE, and VC in groundwater since the initial spill in 1967. The remainder of this chapter presents quantitative analyses of dissolved mass-in-place, amount of mass removed by recovery wells, and biodegradation rates of TCE, DCE (cis), and VC. Chapter IV provides a detailed presentation of the numerical model construction and calibration procedure. A numerical modeling analysis was performed in order to more accurately quantify advection, hydrodynamic dispersion, sorption, and biodegradation mechanisms in the study area. This chapter begins with a presentation of the governing equations for three-dimensional groundwater flow and solute transport of TCE, DCE, and VC in the study area. The model grid and both flow and transport model parameter values are then discussed. Chapter IV concludes with a detailed description of the flow and transport calibration targets and calibration procedure.

7

Chapter V presents the results of this quantitative analysis of advection, hydrodynamic dispersion, sorption, and biodegradation of dissolved TCE, DCE, and VC in groundwater in the study area. The calibrated field-scale biodegradation rate constants for TCE, DCE (cis), and VC are initially presented for the anaerobic conditions at the study area. The calibrated rate constants are compared with previously determined values from both laboratory and field-scale values from the literature review. The results of the flow model calibration are then examined with a detailed discussion of areas of uncertainty. The flow model is then applied to demonstrate that the plume is under hydraulic control of the recovery wells. This capture zone prevents advective and dispersive mass fluxes outside the monitoring network and facilitates analyses of biodegradation rates. Chapter V concludes with a discussion of the accuracy of the numerical groundwater flow and solute transport model in terms of its ability to match the large spatial and temporal changes occurring from 1967 to present. Chapter VI provides the main conclusions of the dissertation. This chapter also provides a discussion of future recommended work in order to improve our understanding of the important geochemical mechanisms and confirm the presence of dechlorinating microorganisms (halorespirers) in the study area. Recommendations are also provided to facilitate the development and application of more comprehensive numerical models in the future.

8

I.4

LITERATURE REVIEW OF TCE, DCE, AND VC ANAEROBIC BIODEGRADATION RATE CONSTANTS AND NUMERICAL TRANSPORT MODELING

Research studies indicate that the primary anaerobic degradation mechanism for TCE occurs through reductive dechlorination (Fennel et al., 1997; Mayo-Gatelle et al., 1997; Gerritse et al., 1999) in which one chloride atom is removed during each step of the following sequential biotransformation reactions: TCE (C2Cl3H) ÿ cis 1,2 DCE (C2Cl2H2) ÿ VC (C2ClH3)ÿ Ethene (Cl2H4). These reductive dechlorination reactions, which can be approximated at concentrations below the low milligram per liter range (Haston and McCarty, 1999) by the following first order rate law: C = Coe-kt where C is the concentration of the chemical at time t, Co represents the initial concentration at t = 0, and k is the transformation rate constant. The transformation rate constant can also be described by a half live (J1/2) through the relationship J1/2 = (ln 2)/k where ln is the natural log. These sequential reactions are mediated by various halorespiring bacteria (Hollinger, 1997) that utilize TCE, DCE, and VC as electron acceptors. With the implementation of MNA at numerous site across the U.S., it is important to determine the sustainability of natural attenuation and particularly long-term biodegradation rates for chlorinated solvents including TCE, DCE (cis), and VC. Therefore, both laboratory and field-scale studies of TCE, DCE (cis), and VC 9

biodegradation rate constants will be reviewed. Scale-dependent phenomena such as hydraulic dispersion and interfacial biofilm mass transfer limitations may cause observed field-scale rate constants to be lower than results from lab studies (Goldstein et al., 1985; Sturman et al., 1995; and others). Field scale biodegradation rates are determined from both data analyses and transport model calibration. Solute transport modeling is also commonly applied to estimate the cleanup time using remedies including pump-and-treat and MNA. However, not many of these models have been rigorously calibrated and examined in terms of their predictive capabilities. In addition, very few detailed multispecies modeling analyses have been performed particularly for TCE, DCE, and the more toxic degradation product VC. Because of the importance of numerical modeling, a comprehensive review is also provided for both single and multi-species field-scale simulations of contaminant in groundwater.

I.4.1

TCE, DCE (CIS), AND VC ANAEROBIC BIODEGRADATION RATE CONSTANTS

TCE Anaerobic Rate Constants Many laboratory studies have been performed to determine anaerobic biodegradation rate constants for TCE. The anaerobic first order biodegradation half lives for TCE from these studies varied significantly from 2 days (Fogel et al. 1986) to 6930 days (Wilson et al., 1990). In an early study, Wilson et al. (1986) collected soil and groundwater samples at a municipal landfill in Oklahoma for a laboratory microcosm study of anaerobic biodegradation of TCE and other chemicals. After an initial lag time

10

for the microbes to acclimate to laboratory induced conditions, the spiked TCE concentrations in the microcosms decreased significantly in comparison to TCE concentrations in the controlled study (field samples autoclaved at 120 degrees Celsius) with the difference being attributed to biodegradation. Based on the TCE concentration data, biodegradation half lives were estimated be 89 days. At the St. Joseph site in Michigan, Haston et al. (1994) performed laboratory column studies and reported TCE half life values ranging from 141 to 210 days for sulfate reducing and methanogenic conditions. At the Picatinny Arsenal in New Jersey, Wilson et al. (1991) reported TCE half lives ranging from 231 to 6930 days under iron and sulfate reducing conditions. Recent laboratory studies have examined TCE biodegradation rates under nutrient and hydrogen enriched conditions and have measured very rapid biodegradation rates on the order of a few days (Haston and McCarty, 1999; Maymo-Gatell, 1999; Maymo-Gatell, 2001; and others). Numerous field studies have also been performed to determine biodegradation rate constants for TCE with half lives ranging from 116 days (Gorder et al. 1996) to 10.5 years (Robb et al., 2000). In an early study, Roberts et al. (1982) examined TCE concentrations in groundwater both during and after a 3 month injection of partially treated water in Palo Alto, California. Their analysis of water quality concentration data versus time at various well locations showed the formation of anaerobic conditions with an apparent TCE half life of approximately 230 days. Wiedemeier (1996) used two chemical tracers (chloride and trimethylbenzene) to eliminate effects of dilution, sorption,

11

and hydrodynamic dispersion on observed TCE data at Plattsburg Air Force Base. The remaining decreases in TCE along the groundwater flow path were attributed to biodegradation. Their study estimated biodegradation half lives of 219 days in the anaerobic zone and negligible biodegradation in the downgradient aerobic zone. At the St. Joseph site in Michigan, the biodegradation half lives were estimated under sulfate/methanogenic conditions and ranged from 113 days (Weaver et al., 1995) to 693 days (Wilson et al., 1995). Schilling et al. (1998) used an analytical transport model calculation (Buscheck and Alcantar, 1995) to estimate the TCE half live at a site in Cedar Rapids, Iowa based on observed concentration data. The results of their calculation indicated a half life of TCE ranging from 305 to 723 days. At the Picatinny Arsenal, Wilson et al. (1991) estimated biodegradation half lives ranging from 53 days to 161 days while Imbrigiotta et al. (1996) estimated a half life of 806 days in a separate study area. Both of these studies were for samples collected in sulfate and iron reducing conditions. More recently, Clement et al. (1999) estimated the anaerobic half live of TCE to be 770 days at Dover AFB Area-6 through calibration of the numerical model RT3D. Barton et al. (2000) calibrated the BIOCHLOR model to observed TCE data at Naval Air Station in Fallon, Nevada. Under the assumption of 2 separate zones of different biodegradation rates, they estimated biodegradation half lives of 346 days in the anaerobic zone of the plume and 1925 days in the downgradient aerobic zone. Robb et al. (2000) examined TCE concentrations versus distance from the source area in a glacial aquifer in New England. Using the analytical transport calculation method of Buscheck and Alcantar

12

(1995), they estimated a biodegradation half life of 10.5 years. Devlin et al. (2002) performed a controlled field tracer test with chemicals including tetrochloroethene (PCE), which degrades more rapidly than its daughter product TCE (Aronson and Howard, 1997). In this field experiment, limited amounts of biodegradation were observed over the 1 year duration of the test indicating a longer test period was required. 1,2 DCE (cis) Anaerobic Rate Constant There have been fewer biodegradation studies of the daughter product DCE (cis) compared to its parent compound TCE. The available data indicate significant variability in DCE (cis) biodegradation half lives with values ranging from 27 days (Ehlke et al., 1991) to 1386 days (Cox et al., 1995). In the laboratory, Ehlke et al. (1991) performed microcosm analyses of 1,2 cis DCE biodegradation from samples collected in the core of TCE, DCE, and VC plumes at the Picatinny arsenal site located in Morris County, New Jersey. After an initial acclimation period of 18 weeks, the spiked DCE concentrations decreased with half lives ranging from 27 to 82 days (field samples autoclaved at 120 degrees C). These two sample locations were in areas exhibiting some of the highest observed contaminant concentrations at the site. The reported half lives for the samples for this site ranged from 27 to 82 days. In a microcosm study of samples collected from creek bed sediments at the Naval Air Station near Jacksonville, FL, Bradley and Chapelle (1997) reported a half life of 116 days for anaerobic mineralization of DCE under methanogenic conditions. Recent laboratory studies have examined DCE biodegradation rates under nutrient and

13

hydrogen enriched conditions and have measured very rapid biodegradation rates with values ranging from a few days to a week (Haston and McCarty, 1999; Maymo-Gatell, 1999; Maymo-Gatell, 2001; and others). Several field studies have also been performed to determine biodegradation rate constants for DCE (cis) with half lives ranging from 77 days (Swanson et al., 1996) to 1386 days (Cox et al., 1995). At the St. Joseph site in Michigan, Weaver et al. (1996) estimated a biodegradation rate for cis 1,2 DCE of 289 days. At the Plattsburg Air Force Base site, Wiedemeier (1996) used the chemical tracers chloride and trimethylbenzene to eliminate effects of dilution, sorption, and hydrodynamic dispersion on observed DCE data. The remaining decreases in DCE along the groundwater flow path were attributed to biodegradation. Their study estimated biodegradation half lives of 329 days in the anaerobic zone and negligible biodegradation in the downgradient aerobic zone. More recently, More recently, Clement et al. (1999) estimated the anaerobic half live of DCE to be 820 days at Dover AFB Area-6 through calibration of the numerical model RT3D. Barton et al. (2000) calibrated the BIOCHLOR model to observed DCE data at Naval Air Station in Fallon, Nevada. Under the assumption of 2 separate zones of different biodegradation rates, they estimated biodegradation rates of 277 days in the anaerobic zone of the plume and 3.8 years in the downgradient aerobic zone. Schilling et al. (1998) used an analytical transport model calculation (Buscheck and Alcantar, 1995) to estimate the DCE half live at a site in Cedar Rapids, Iowa. The results of their calculation indicated a half life of DCE ranging from 264 to 408 days. Lehmicke et al. (2000)

14

examined biodegradation rates of cis DCE at a site in Kent, Washington. Although they were unable to examine mass loss along a flow path because of the complex flow field from pump-and-treat at the site, a biodegadation half life of 1.1 years was estimated based on the log-linear trend over time of DCE at several monitor wells. VC Anaerobic Rate Constants There have been fewer biodegradation studies of the daughter product VC compared to TCE. The available data indicate significant variability in VC anaerobic biodegradation half lives with values ranging from 23 days (Barrio-Lage et al., 1990) to 1824 days (Wiedemeier et al., 1996). There have been only a few laboratory studies of biodegradation rates of VC under anaerobic conditions. Barrio-Lage et al. (1990) performed enhanced laboratory microcosm studies and estimated first order anaerobic rate constants of 23 to 100 days for VC. Bradley and Chapelle (1996) performed laboratory studies and found that VC can be oxidized under anaerobic conditions under iron reducing conditions. The estimated first order biodegradation half lives for their data ranged from 14 to 85 days (Aronson and Howard, 1997). Under nutrient enriched conditions, Maymo-Gatell (2001) observed VC biodegradation half lives on the order of weeks with biodegradation of VC being cometabolic. In other words, VC biodegradation occurred fortuitously as more chlorinated compounds (PCE and TCE) served as the substrates being used as electron acceptors.

15

The available field studies for anaerobic biodegradation of VC report half life ranges of 98 days (Weaver et al., 1996) to 1824 days (Wiedemeier et al., 1996). At Plattsburg Air Force Base, Wiedemeier et al. (1996) used two chemical tracers (chloride and trimethylbenzene) to eliminate effects of dilution, sorption, and hydrodynamic dispersion on observed VC data. The remaining decreases in VC along the groundwater flow path were attributed to biodegradation. Their study estimated a biodegradation a half life of 1.5 years in the anaerobic zone and negligible biodegradation rates in the downgradient aerobic zone. Schilling et al. (1998) used an analytical transport model calculation (Buscheck and Alcantar, 1995) to estimate the VC half live at a site in Cedar Rapids, Iowa. The results of their calculation indicated a half life of VC ranging from 200 to 550 days. At the St. Joseph site in Michigan, the biodegradation half lives were estimated under sulfate/methanogenic conditions to range from 98 days to 1690 days (Weaver et al., 1995). At Dover Air Force Base, Ellis et al. (1996) evaluated the VC mass loss along the groundwater flow path and estimated the biodegradation half life to range from 693 to 806 days. More recently, Clement et al. (1999) estimated the anaerobic half live of VC to be 860 days at Dover AFB Area-6 through calibration of the numerical model RT3D. At a site in Washington, Lehmicke et al. (2000) examined biodegradation rates of VC during pump and treat. Although they were unable to examine mass loss along a flow path because of the complex flow field, they applied two methods to estimate a biodegradation rate constant for VC. In the first method, the rate constant of VC was varied using BIOCHLOR model in order to match observed ratios of

16

ethene to VC. In the second method, the rate was estimated based on the observed loglinear trend for time series data of VC at site monitor wells. Both methods indicated an anaerobic biodegadation half life of 0.55 years for VC. Aronson and Howard (1997) provide a detailed review of laboratory and field studies of anaerobic rate constants for chlorinated organic chemicals. This review focused on naturally occurring conditions in which there was no seeding or enrichment of microbial cultures in the samples. In this review, the range of anaerobic rate constant (half life) values was 0.051 to 0.91 yr-1 (277 days to 4950 days) for TCE and 0.12 to 2.6 yr-1 (96 to 2100 days) for VC based on laboratory and field studies. Recommended rate constants for DCE were not provided in this review. However, a literature review by Wiedemeier et al. (1999) reported values ranging from 0.25 to 2.2 yr-1 (116 to 1019 days) for DCE. Limitations of laboratory and field methodologies The available results from both laboratory and field studies demonstrate that anaerobic biodegradation rate constants of TCE, DCE, and VC vary significantly. Although some variability is expected given the differences in the characteristics of each site including type and number of microbes, temperature, and geochemistry, there is also variability caused by uncertainties in the estimated biodegradation rate constants in each study. This uncertainty may contribute significantly to the observed variability in anaerobic biodegradation rates.

17

Because it is very difficult to reproduce field conditions, the rate constants determined in laboratory studies may not be representation of biodegradation occurring in the field. For example, the pH, temperature, contaminant concentrations, nutrients, electron donors and acceptors, and balance of microbe consortia may be altered during sample collection, transport, and set up for the laboratory study (Wiedemeier et al.,1999; Aronson and Howard, 1997). In addition, disturbances to the conditions occur when the samples are spiked with new contaminant concentration levels. After collection in the field, sediments and groundwater are mixed during laboratory setup which can cause either increases (Davis and Olson, 1990) or decreases (Weiner and Lovely, 1997) in microbial activity of the sample. The observed lag times after adding additional contaminants for biodegradation analyses, which is interpreted as microbial acclimation to changed environmental conditions, demonstrate the effects of sample disturbance. Finally, the biodegradation rate constants in laboratory studies are for local conditions, and therefore a large number of samples may be required to quantify field-scale biodegradation rates. There are also uncertainties in the rate constant values determined from field studies. In particular, it is difficult to isolate effects of biodegradation from the effects of recharge dilution, sorption, hydrodynamic dispersion, and advection in field studies. In well controlled field studies, there are also significant uncertainties in the analysis methodologies for determining biodegradation rate constants. Furthermore, many of the rate constants were determined from snapshots of field data collected over relative short

18

periods of time with relatively small levels changes in chemical concentrations at each well location (e.g. Schilling et al., 1998; Wiedemeier et al., 1996; and others). Short-term studies are less accurate than long-term studies because of the greater sensitivity to both variability in concentration data and measurement error in studies over shorter periods of time. Short-term studies may potentially be affected by changes in microbial activity that are not representative of well acclimated long-term microbial conditions. For slowly degrading chemicals such as TCE, DCE, and VC, long-term measurements should provide a more representative estimate of the effective biodegradation rate. A more detailed discussion of the uncertainties of field studies is provided below. The use of tracers (e.g. chloride and trimethylbenzene) along with contaminants (e.g. Wiedemeier et al., 1996) is a useful method to determine biodegradation rate constants. The use of tracers allows one to eliminate the effects of hydrodynamic dispersion and sorption. The remaining mass loss is then attributed to biodegradation. Controlled field tracer tests are not typically performed for long periods of time (years) which prevents the determination of long-term rate constants. There are also significant uncertainties (30%) in the groundwater velocity values determined from tracer tests in controlled studies (Devin et al., 2002). This uncertainty in groundwater velocity affects rate constants determined from both model calculation and mass flux calculation methods. In addition, conservative tracers are not available in many studies particularly for sites contaminated by chlorinated solvents. For TCE, DCE, and VC, the nonreacting compound chloride cannot be used as a chemical tracer for eliminating effects of

19

dispersion because it is produced during biodegradation of these chemicals. When apparent conservative tracer compounds (e.g. trimethylbenzene) are present, such as at fuel spill sites, they are not always appropriate because they biodegrade under anaerobic conditions (Wiedemeier et al., 1999). Model calculations, which are typically applied for a single snapshot of assumed steady-state plume conditions, may have significant uncertainties in estimated rate constants when this assumption is violated significantly. For example, a variation in the source flux during controlled field experiments can cause significant changes in downgradient concentrations during the test (e.g. Wilson et al., 2000). In addition, the examination of steady-state plume conditions does not examine changes in concentration levels with time at a given monitoring point. More accurate long-term biodegradation rate constants of TCE, DCE, and VC can be determined through field studies of sufficient length so that concentrations decrease significantly at each location over the period of measurement. Mass flux approaches cannot be used at many sites to determine rate constants for TCE, DCE, and VC because these chemicals do not degrade rapidly enough to measure any mass losses through wells along the groundwater flow path. Within larger well networks, the change in dissolved mass of TCE, DCE, and VC can be measured to estimate the mass loss of each chemical in the control volume defined by the well network (e.g. Durant et al, 2001). However, in many cases, some contaminant mass moves out of the well network by advection and hydrodynamic dispersion. Unfortunately,

20

it is difficult to accurately quantify this mass loss and therefore the remaining mass loss from biodegradation cannot be accurately determined. In mass flux based methods, both measurement and spatial variability in concentrations adds significant uncertainty in the calculated mass given the limited number of data points along each cross section of wells. One method to reduce these uncertainties is through the use of pumping wells in which the plume mass flux can be directly measured each pumping well. In addition, the pumping wells exert hydraulic control on the plumes to prevent unaccounted advective and dispersive flux mass loss outside the monitoring network. In summary, anaerobic biodegradation rate constants reported in the literature for TCE, DCE, and VC display wide variabilities. Although some of the variability is attributed to changes in laboratory and field conditions of each measurement, there is also significant uncertainty in the methodologies for determining lab and field-scale rate constant values. In the laboratory, the uncertainties are caused by both difficulties of representing actual field conditions and the lack of measurements from locations throughout the plumes. In field measurements, the uncertainties are caused primarily by unaccounted mass losses by advection and hydrodynamic dispersion outside of the monitoring zone, uncertainties in the groundwater velocity mass flux calculations, and lack of data collected over long periods of time to observe significant changes in TCE, DCE, and VC concentrations. Furthermore, many of the field studies did not quantify the mass balance between parent and daughter products during sequential biodegradation of TCE, DCE, and VC.

21

This research will seek to obtain more accurate rate constants of TCE, DCE, and VC by examining plumes that are hydraulically controlled. A study area will be used that has large amounts of concentration data that change significantly throughout the plume over a 20 year period for more accurate determination of long-term rate constants. Numerical multispecies modeling will be used to quantify each natural attenuation mechanism and carefully examine the mass balance between parent and daughter products during TCE-DCE-VC sequential biodegradation. Given the importance of the numerical modeling in this analysis, a detailed literature review of numerical multispecies model applications is provided below.

I.4.2

SINGLE AND COUPLED MULTI-SPECIES SOLUTE TRANSPORT SIMULATION A large amount of effort has also been performed over the past two decades to

develop general purpose models and documentation for field-scale solute transport models for one chemical species. Some of the more well known of these codes include MOC (Konikow and Bredehoeft, 1987; Konikow et al.,1994; USGS, 1996), RANDOM WALK (Prickett et al., 1981), SUTRA (Voss, 1984), VS2D (Lappala et al., 1987; Hsieh et al., 1999), SWIFT (Reeves, et al., 1986; Ward, 1991), HST3D (Kipp, 1987), FTWORK (Faust et al., 1990), MODFLOWT (Duffield and GeoTrans, 1997), and MT3D (Zheng, 1992; Zheng et al., 2001). MODFLOWT and MT3D use the MODFLOW (McDonald and Harbaugh, 1987; Harbaugh et al., 2000) code and recently developed enhancements

22

(Hill et al., 2001; Mehl et al., 2001; USGS, 2001) to simulate the groundwater velocity field. The recent development of pre- and post processing capabilities for these models and the coupling with geographic information systems for rapid input of data has significantly improved the capabilities to construct and calibrate complex numerical transport models. In particular, the development of MODELCAD (Geraghty & Miller, 1989), Visual MODFLOW (Waterloo Hydrogeologic, 1996; 2001), GMS (DOD, 1997; 2001), and GWVISTAS (Environmental Simulations, 1997; 2001) should be noted based on the popularity of their usage. More recently, GIS capabilities have been linked with models for rapid import of site data as discussed in Rifai et al. (1993). For the ARC/INFO platform, the program MODELGIS (Greenwald et al., 1996) is noted because of its ability to rapidly incorporate information such as stream widths and lengths for model boundary conditions into the flow model MODFLOW. More recently, the transport code CLAM/GIS (Aral and Sani, 1998), which is well integrated with the user friendly ARCVIEWTM (ESRI, 1996) platform, has been developed for rapid incorporation of boundary conditions, infiltration, water level, and hydraulic conductivity data. A large number of field-scale transport simulations of single dissolved species have been performed over the past fifteen years. Reviews of groundwater flow and single species transport simulation applications are provided in Anderson (1995), National Research Council (1990), Abriola (1987), and Naymik (1987).

23

I.4.3

FIELD-SCALE MULTI-SPECIES CONTAMINANT TRANSPORT SIMULATION Over the past five years, there has been significant advances in the development

of specialized computer models for simulating three-dimensional coupled flow and reactive transport of multiple dissolved contaminants in groundwater. De Blanc et al. (1996) modified the multiphase code, UTCHEM, to model multispecies bioreactive transport. Clement (1997) developed the general purpose three-dimensional multispecies reactive transport code RT3D. Zheng and Wang (1998) developed the MT3DMS code with its recent update developed by Zheng et al. (2001) in order to simulate multi-species transport in both porous and dual porosity media. MT3D99 (Zheng, 1998) was developed to include enhanced reaction packages for MT3DMS. The RT3D and MT3D codes use separate flow model codes such as MODFLOW (MacDonald and Harbaugh, 1987; Harbaugh et al., 2000) to provide the velocity field for the simulation. Other recently developed codes for field-scale applications include SEAM3D (Waddill and Widdowson, 1998), BIOREDOX (Carey et al., 1999), and reaction packages for MT3DMS (Prommer, 1998; 1999). It should be noted that other multi-phase models including PORFLOW (Runchal, 1987; Runchal and Sagar, 1992; Runchal, 1994), TOUGH2 (Pruess, 1991; Oldenburg and Pruess, 1993), TRACER3D (Travis, 1984; Travis and Birdsell, 1991), and FRAC3DVS (Therrien and Sudicky, 1996) can also be applied to simulate multiple reacting chemicals in groundwater. A brief review of some of the applications of reactive transport, multi-species models to simulate field-scale

24

transport of petroleum hydrocarbons and chlorinated solvents in groundwater is given below. Petroleum Hydrocarbon Applications Laboratory and field studies of microbes under aerobic conditions have shown that gasoline-derived compounds such as benzene, toluene, ethylbenzene, and xylene (BTEX) undergo biodegradation in groundwater (e.g. Wilson, 1983; Chiang et al., 1989, Swindoll et al., 1988). Some of the earliest applications of numerical multi-species transport models for petroleum hydrocarbons were performed using codes including BIO1D (GeoTrans, 1987; Srinivasan and Mercer, 1988) and BIOPLUME (Rifai et al., 1987; 1988; Rifai et al., 1989), which simulated a single contaminant under aerobic conditions with oxygen as the electron acceptor. However, the importance of multiple electron acceptors and accompanying variable biodegradation rates in each distinct redox zone was well known. In order to better understand these mechanisms, a number of codes including BIOPLUME III (Rifai et al., 1996), BIO3D (Frind et al., 1989), BIOMOC (Essaid and Bekins, 1997), and SEAM3D (Wadill and Widdowson, 2000) were later developed to simulate biodegradation from multiple electron acceptors. Several researchers have applied numerical models to simulate sequential aerobic/anaerobic biodegradation of multiple chemicals by calibrating two-dimensional models to petroleum hydrocarbon data (Essaid et al. 1995; Brauner and Widdowson, 1996; Lu et al., 1999; Waddill and Widdowson, 2000). More recently, Schafer (2001) calibrated a model to simulate important redox processes for prediction of long-term

25

xylene concentrations under a pump-and-treat site remedy at a former refinery in western Germany. Results of this modeling indicated that iron reduction was a key process in controlling plume evolution. Brauner and Widdowson (2001) calibrated the multispecies SEAM3D (sequential electron acceptor) model to match three-dimensional BTEX transport and biodegradation under aerobic, nitrate-reducing, ferrogenic, and methanogenic conditions for a natural attenuation experiment at Columbus Air Force Base. These simulations indicated that aerobic biodegradation accounted for the majority of the hydrocarbon biodegradation (46 % of biodegraded mass), followed by ferrogenesis (28%), nitrate-reduction (21%), and methanogenesis (5%). Chlorinated Solvent Applications With the recent interest in the natural attenuation of dissolved solvents (e.g. USEPA, 1998; Wiedemeier et al., 1999) in groundwater, numerical transport simulations of multiple reacting chlorinated solvents are beginning to be performed. It is known that reductive dechlorination is an important mechanism for TCE-DCE-VC sequential degradation (Semprini et al., 1995; Wiedemier et al., 1999; USEPA, 1999; and others) in groundwater. Reductive dechlorination, which involves sequential degradation of parent products into daughter products, is different than biodegradation of petroleum hydrocarbons which occurs through direct reactions with electron acceptors such as oxygen. As discussed in Suarez and Rifai (1999), Wiedemier et al., (1999), and others, the biodegradation rates of petroleum hydrocarbons are much more rapid than for chlorinated solvents as seen by the fact that chlorinated solvent plumes are larger and

26

more persistent than petroleum hydrocarbon plumes (USEPA, 1999). In addition, the degradation product (VC) is more toxic (USEPA, 1986) than the parent compound (TCE), which demonstrates the importance of not only simulating the fate and transport of TCE but also its daughter products. A review of the literature shows that there has been very few numerical models that have been applied to simulate the transport and sequential degradation of multiple reacting dissolved chlorinated solvents at the fieldscale. A summary of the known case studies is provided below. Carey et al. (1998) applied a coupled biodegradation-redox transport model, BIOREDOX, to simulate redox-dependent biodegradation of dissolved TCE, DCE, and VC in groundwater at the Plattsburgh Air Force Base in New York. The rate constants for these chemicals were assumed using mid-range values from the literature. The predicted results for both a two-dimensional integrated-depth and vertical cross sectional model were shown to produce similar results for the site-specific parameters used in this study. Under the assumption of first-order sequential biodegradation kinetics, Clement et al. (1998) applied RT3D to simulate the hypothetical injection of PCE and its degradation products (TCE, DCE, and VC) in a two-dimensional groundwater flow field. This study demonstrated the utility of using numerical multispecies transport models for examining degradation product concentrations at downgradient receptors such as water supply wells. Holder et al. (1998) modified the BIOPLUME II model to simulate TCE and DCE sequential biodegradation at a site in Phoenix, Arizona. Under the assumption of biodegradation occurring primarily near the source area, the half lives of both TCE and

27

DCE were both set to a value of 69 days in the source area with no biodegradation outside this zone. The model simulation results generally matched the observed high concentrations near the source and lower concentrations at downgradient locations. However, significant differences in observed and simulated values were present at some monitoring points. Widdowson et al. (1998) performed a hypothetical analysis of reductive dechlorination using a modified version of SEAM3D. Results of their model simulations demonstrated trends of TCE, DCE, and VC concentrations similar to trends observed in field data, which indicated the utilility of SEAM3D for evaluating natural attenuation. Clement et al. (1999) simulated PCE, TCE, DCE, and VC concentrations at Dover AFB Area-6 for non-pumping conditions. Through model calibration, the estimated the anaerobic half lives of TCE, DCE, and VC were 770 days, 820 days, and 860 days, respectively. Results of the model simulations indicated good agreement between calculated and field estimated plume mass. Mason et al. (2000) calibrated the reactive transport model RT3D to simulate steady-state TCE, DCE, and VC plume conditions for a continuous source release at the Naval Air Station Lakehurst site in New Jersey. Results of the calibration indicated that the overall shape of the plumes were reasonably well matched. Harvey et al. (2001) presented a study of the potential uncertainties associated with reactive transport models along a PCE to VC degradation pathway. Their study demonstrated the importance of well-planned groundwater monitoring systems to ensure adequate data for reactive transport modeling. It should be noted that none of these modeling studies were calibrated to observed site data where the

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plume mass has changed significantly over time. This lack of calibration to dynamically changing plume conditions likely decreases the accuracy and predictive capability of these models.

I.4.4

MOTIVATION FOR THIS RESEARCH A detailed review of anaerobic rate constants indicates significant uncertainties in

long-term biodegradation rate constant values for TCE, DCE, and VC. Therefore, this research will seek to provide more accurate values of anaerobic biodegradation rate constants through calibration of a numerical multispecies solute transport model. The study area was chosen based on the availability of 20 years of concentration data showing significantly decreases in TCE, DCE, and VC plume size over time. In addition, the study area utilizes recovery wells that keep the plumes under hydraulic control. This eliminates uncertainties associated with advective and dispersive mass fluxes out of the monitoring network and allows determination of more accurate rate constants. In addition, the mass fluxes in the recovery wells are accurately quantified through weekly flow and quarterly groundwater sampling measurements. The application of this numerical multispecies model also allows one to quantify advection, hydrodynamic dispersion, sorption, and biodegradation mechanisms at the site over the 20 year period of data. A detailed review of previous multispecies reactive solute transport models of chlorinated solvents indicates that none of these models have been applied to large

29

amounts of data collected over a long period of time with the model calibrated to significantly changing plume conditions and then later examined in terms of its predictive accuracy. One reason for this is that there are very few sites with extensive threedimensional monitoring networks where data has been collected at sufficient frequency over the long periods of time that are needed to accurately examine the relatively slow sequential degradation of multiple dissolved chlorinated solvents. Another reason for the lack of calibrated multispecies models of chlorinated solvents is that the degradation rates of TCE, DCE (cis), and VC are not well constrained (Gooverts et al., 2001; Suarez and Rifai (1999), Aronson and Howard, 1997; Wiedemeier et al., (1999), USEPA (1998), and others), which leads to uncertainties in transport model simulations. Sturman et al. (1995) report that field degradation rates tend to be a factor of 4 to 10 times greater than in the laboratory. In addition, the complete sequential degradation of TCE, DCE, and VC via reductive dechlorination does not always occur with little or no DCE or VC forming at some sites. Some sites also have complex hydrogeologic settings in which the subsurface is highly heterogeneous with subsurface permeabilities that cannot be sufficiently characterized to accurately simulate the transport of dissolved chemicals. Finally, the calibration and validation of a single species transport model to field data is known to be very difficult (e.g. Zheng and Bennett, 1995; Konikow, 1986;1993). For multiple chemicals, this task becomes significantly more complex because one must accurately simulate not only the mass balance between multiple reacting chemicals but also the changes in concentration levels of each chemical over time.

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This dissertation will provide one of the first comprehensive model calibration and predictive analyses of field-scale sequential TCE-DCE-VC degradation using extensive amounts of three-dimensional data collected over a 20-year period on the behavior of elongated plumes both before and during pump-and-treat cleanup at the Harris facility in Palm Bay, FL. The study area is of interest because of its relatively homogeneous beach sand deposits associated with a near shore shallow water environment, naturally occurring anaerobic conditions, and the large amount of data that has been collected. This reduces the uncertainty associated with site characterization and thus significantly improves the capabilities of solute transport models to simulate subsurface transport. These increased accuracies in simulating contaminant transport also provide a unique opportunity to use the 20-year period of concentration data to fill data gaps in the scientific literature by providing more accurate estimates of field-scale degradation rates during reductive dechlorination of TCE, DCE, and VC as indicated by geochemical data. Given the uncertainties and limitations in laboratory data (Gooverts et al., 2001; Sturman et al., 1995, and others), models constructed at the field-scale are important tools for estimating field-scale degradation rates. After calibrating the model to data from 1981 to 1991, the model will be critically evaluated based on its ability to match an independent set of data from 1992 to 2001 in order to help researchers better understand the current capabilities of multispecies transport models. From a practical perspective, there have been many studies arguing that remediation including pump-and-treat is ineffective for the cleanup of large-scale

31

contaminant plumes because of long cleanup times, presence of nonaqueous phase liquids, slow rates of desorption, and other factors (NRC, 1995; and others). Natural attenuation has now been applied as a remedial component of cleanup for tens of thousands of sites across the U.S. (USEPA, 1997). The success of remediation (pumpand-treat and natural biodegradation) for the large-scale chlorinated plumes at this site, with cleanup standards that are now nearly reached, provides an important counter example to this currently held opinion. In addition, this research provides long-term biodegradation rate constants for TCE, DCE (cis), and VC which improves our understanding of the sustainability of natural biodegradation rates occurring during application of in situ or engineered bioremediation at other sites with large-scale groundwater contamination.

I.5

STUDY AREA AND PREVIOUS WORK

This study focuses on groundwater contamination at the Harris facility in Palm Bay, Florida (Figure 1-1). The facility consists of two principal parts: 1) Electronic Systems Sector ( ESS) Campus and 2) Semiconductor Sector Campus (SC). To the south of the facility is the GDU (General Development Utilities) Wellfield, which currently extracts approximately 4 million gallons per day (MGD) of water for residents from water supply wells located to the south and west of the facility. Impacted groundwater with dissolved chlorinated compounds was discovered in several production wells in the GDU Wellfield in 1981. Since that time, groundwater from the wellfield has been treated

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prior to domestic use. In order to remediate impacted groundwater, groundwater recovery wells have been operating at the study area since 1985. The locations of the GDU water supply wells and industrial facility recovery wells in the study area are presented in Figure 1-2. Many studies have been performed to characterize the hydrogeology and geochemistry of the study area (Post, Buckley, Schuh and Jernigan, Inc., 1983; 1984; Geraghty & Miller, 1987; L.S. Sims & Associates, 1997; 1998; 1999; 2000; 2001; 2002). At least 300 stratigraphic borings have been drilled in the study area to characterize the geologic setting. Geophysical surveys also have been performed to better map stratigraphic horizons. More than 200 monitoring wells are present at the study area. Hydraulic head data and groundwater samples have been collected quarterly each year from many of these wells and chemically analyzed since the early 1980s. Pumping rates of both the recovery wells and municipal wells are well known, which significantly improves the accuracy of calibrated parameter values. This large amount of local data was used to construct and obtain a detailed groundwater flow and solute transport model calibration at the study area. Early groundwater analyses in the study area began in the late 1950s and continued into the early 1980s with pumping tests and the installation of water supply wells at the Port Malabar development (Geraghty & Miller, 1982). Beginning in the early 1980s, more detailed studies were performed to examine groundwater contamination in the study area (CH2MHill, 1983; Geraghty & Miller,1987,1989,1990;

33

ESE, 1987; L. S. Sims & Associates, 1999, 2000; 2001). Although there have been no previous quantitative studies of dissolved contaminant transport in the study area, numerical models of groundwater flow have been constructed by PBS&J (1984), Geraghty & Miller (1987), and ESE (1987). These earlier models were used to first match observed water level data and then to evaluate various scenarios of existing and proposed aquifer development. More recently, Burnell et al. (1993) calibrated a threedimensional model of groundwater flow and solute transport at the Harris facility. A brief description of each of these modeling studies is given below. PBS&J (1984) constructed a local, two-dimensional groundwater flow model to examine the response of eight proposed Harris pumping wells located to the north of the Semiconductor Campus retention pond (Figure 1-1). These wells were proposed to provide high quality water which meets the requirements of industrial operations at Harris. PLASM, the Prickett-Lonnquist Aquifer Simulation Model (Prickett and Lonnquist, 1971) was used to simulate two-dimensional groundwater flow in the lower unit of the surficial aquifer. Maximum pumping rates were assumed in both the proposed wells and the GDU/PBU wells in order to provide a worst-case scenario of the zone of influence of the proposed wells. The results of this modeling effort showed that the proposed Harris wells would have no effect on other users in the area. Geraghty & Miller (1987) constructed a local, three-dimensional groundwater flow model to evaluate the effectiveness of the Harris groundwater recovery well system which began operating in 1985. MODFLOW, the United States Geological Survey

34

(USGS) Modular Three-Dimensional Finite Difference Groundwater Flow Model (McDonald and Harbaugh, 1984) was used to simulate groundwater flow at the Harris site. This groundwater flow model was calibrated to March 24, 1987 observed water level data by matching model calculated and observed potentiometric surface maps. The model results showed that the Harris recovery wells were capturing the main part of the volatile organic compound (VOC) plume in the 25 m zone at the site. The modeling results also showed that the VOC plume in the 12 m zone would be captured after installation of the proposed recovery wells. ESE (1987) constructed a regional, three-dimensional groundwater flow model to evaluate whether additional municipal pumping wells located to the south and west of the Harris site would affect the zone of capture of the Harris recovery wells. This regional model included several local flow system discharge points including the municipal well field and Turkey Creek. The groundwater flow code MODFLOW was used to simulate future aquifer responses to the proposed stresses. The groundwater flow model was calibrated to August 1-14, 1987 water level data at the site. The model results indicated that the proposed GDU/PBU wellfield expansion would have no effect on the Harris recovery well system. Burnell et al. (1993) constructed a regional, three-dimensional numerical groundwater flow and solute transport model with finer grid spacing at the Harris facility. The flow model was calibrated using inverse methods to average water levels from 1989 to 1991 at 91 monitoring wells in the study area. Recovery wells have been in operation

35

since 1985 at the Harris facility in order to remove contaminants from groundwater. The use of known pumping rates in the recovery wells provided increased confidence in the calibrated groundwater velocity field. Results of this model indicated a good match to observed groundwater flow directions and field data. The transport model in Burnell et al. (1993) was calibrated to match average VC concentration data in 1984, 1989, and 1991 for over 100 wells sampled in each year. VC was chosen because its widespread distribution, elevated concentrations, and its low cleanup goal of 1 :g/L. Decreases in VC from degradation were not represented in this study under the assumption that the rate of accumulation from its parent compounds was equal to its rate of degradation. Because VC will eventually degrade faster than it accumulates as a result of the decreasing contribution from its parent compounds (TCE and DCE) as their concentrations decrease over time, this assumption provided estimates of worst-case higher future concentration levels and cleanup times for the plumes as required by USEPA. Although VC concentrations were matched from 1981 to 1992, the model did provide conservatively higher VC concentrations in its future predictions as the parent compounds (TCE and DCE) diminished. An examination of later data collected in 1996 and 2001 indicates that VC concentrations by this model were overestimated for these dates. The match to data from 1981 to 1992 suggests that the assumption of similar accumulation rates and degradation rates was reasonable for this period. However, the over- predictions of future simulated VC concentrations was caused by the fact that most of the parent compounds had already degraded and therefore

36

the rate of VC degradation exceeded its rate of accumulation at these later times. Results of this previous modeling effort also provided worst-case estimates that cleanup standards at the Harris site would be reached by 2029.

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CHAPTER II MODEL GOVERNING EQUATIONS AND BENCHMARK PROBLEMS This chapter begins with a brief discussion of the continuum approximation and representative elementary volume concepts used in groundwater flow and transport modeling. The modeling approach and the governing equations for the MODFLOW and MT3D numerical codes used in this study are then presented. Although this chapter discusses important physical and chemical processes that are represented in the mathematical model, a more detailed discussion of these processes and their effect on the fate and transport of TCE, DCE, and VC in the study area will be provided in Chapter III. This chapter also provides a brief description of the numerical solution techniques of the MODFLOW and MT3D codes that are utilized in this study. Because of the importance of understanding the capabilities and limitations of groundwater models, this chapter concludes with two new benchmark problems for MT3D99. The benchmark problems were chosen to compare results of MT3D to an updated version of AT123D (USEPA, 2001; Lester et al., 2002) and the recently developed multispecies code BIOCHLOR (Aziz et al., 2000), which incorporates recent three-dimensional analytical solutions for multiple species reactive transport in groundwater (Sun and Clement, 1999. Sun et al.,

38

1999a; Sun et al., 1999b). These benchmark problems were designed to examine capabilities of MT3D99 that will be applied to the study area in this dissertation.

II.1

MODELING APPROACH AND GOVERNING EQUATIONS

II.1.1 CONTINUUM APPROXIMATION Quantitative studies rely on appropriate averaging techniques of microscopic processes for defining macroscopic properties within a valid representative elementary volume (REV) range in order to represent each physical property by a fictitious continuum. Given the relatively homogeneous nature of the unconsolidated deposits at the site, the appropriate size of the REV for this study area is small (

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