Surfactant enhanced aquifer remediation: application of mathematical models in the design and evaluation of a pilot-scale test

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1 Groundwater Quality: Matured and Enhanced Restoration of Groundwater Pollution (Proceedings ofthe Groundwater Quality 2001 Conference held al Sheffield, UK. June 2001). IAHS Publ. no Surfactant enhanced aquifer remediation: application of mathematical models in the design and evaluation of a pilot-scale test LINDA M. ABRIOLA, CHAD D. DRUMMOND, LAWRENCE D. LEMKE, KLAUS M. RATHFELDER Environmental and Water Resources Engineering, The University of Michigan, 1351 Beat, Ann Arbor, Michigan, USA abriola@engitt.umicli.edu KURT D. PENNELL School of Civil and Environmental Engineering, Georgia Institute of Technology, 790 Atlantic Drive, Atlanta, Georgia, USA ERIK PETROVSKIS & GARY DANIELS GeoTrans Inc., 710 Avis Drive, Ann Arbor, Michigan, Abstract This paper provides an overview of the application of flow and transport simulators to the design and performance evaluation of a surfactant enhanced remediation pilot demonstration in Oscoda, Michigan, USA. For model simulations, input parameters were estimated from batch and column experiments conducted with aquifer materials and fluids collected from the site. Geostatistical methods were used, in conjunction with available grain size data from core samples, to generate representative hydraulic conductivity distributions for the unconfmed glacial outwash formation. The final remedial design incorporated a gallery of water injection wells, installed behind the surfactant injection points, to control surfactant delivery and maximize solubilized plume capture. Model predictions of test performance are compared with actual aqueous concentration measurements within the treated source zone. Discrepancies between predicted and measured concentrations are identified and discussed. Extraction well breakthrough data are also evaluated to explore the effectiveness of DNAPL removal and surfactant recovery. Key words DNAPL; field site; geostatistics; surfactant enhanced aquifer remediation USA INTRODUCTION AND SITE DESCRIPTION The prevalence of dense non-aqueous phase liquids (DNAPLs) at hazardous waste sites across the United States is well documented (Mercer & Cohen, 1990). Residual and pooled DNAPL, if not removed or sequestered, can contaminate millions of litres of groundwater over time scales of decades and even centuries. Societal costs associated with DNAPL contamination include diminished potable water supplies, increased health risks to exposed populations, and economic devaluation of contaminated land. It is now widely recognized that conventional pump-and-treat methods are inefficient for DNAPL recovery, due to their inability to mobilize entrapped solvents and the generally low solubility of these organic liquids. The ineffectiveness of existing remedial technologies for treatment has created the need for alternative remediation approaches. One such technology, surfactant enhanced

2 304 Linda M. Abriola et al. aquifer remediation (SEAR), is designed to overcome DNAPL solubility and/or mobility limitations through micellar solubilization and/or interfacial tension reduction. Numerous laboratory column and sand tank studies have demonstrated surfactant effectiveness for the recovery of organic liquid residuals from aquifer materials (e.g. Pennell et al., 1996; Taylor et al., 2001). However, SEAR field demonstrations have exhibited results that are somewhat more mixed, with mass recovery ranging from little or none to 75-99% (Taylor, 1999). In field applications of SEAR, DNAPL source removal can be adversely influenced by such factors as formation textural variations, fluid density contrasts, surfactant sorption losses, solution viscosity changes, and irregular contaminant distributions. The use of numerical models to evaluate the potential effect of these factors can provide valuable insight into the performance and optimization of SEAR applications in the field. This paper describes the use of mathematical models in the design and performance evaluation of a SEAR pilot-scale test conducted to solubilize tetrachloroethylene (PCE) at the Bachman Road site in Oscoda, Michigan, USA. The selected test zone underlies an operating business that adjoins an occupied residence (Fig. 1). A narrow PCE plume emanates from the suspected source area beneath the former dry cleaning building and discharges into Lake Huron approximately 220 m downgradient. Although low concentrations of PCE degradation by-products have been observed downgradient of the source zone, natural attenuation has been insufficient to control plume spread at this site. The contaminated unconfmed aquifer is composed of relatively homogeneous glacial outwash sands confined below by a thick clay layer. Aquifer thickness in the suspected source zone is 4.9 m. Collected core samples revealed the existence of a coarse sand and gravel layer at a depth of 3.7-^1.9 m and a sand/silt/clay transition zone at the base of the aquifer. Soil and groundwater samples beneath the building confirmed the presence of residual PCE within the course layer near the top of the saturated zone, and detected consistently high PCE concentrations at the base of the aquifer. The actual distribution and volume of entrapped PCE, however, was unknown. Suspected source zone Former dry cleaning facility '0 Advective contaminant flow J Lake Huron Fig. 1 Bachman Road SEAR pilot-scale test location. The simulated contaminant advective flow to Lake Huron from suspected source zone is shown. PILOT-SCALE TEST DESIGN SIMULATIONS The primary design parameters for the test were: well locations, injected surfactant concentration, monitoring well sampling frequency, and pumping schedule. These

3 Surfactant enhanced aquifer remediation: application of models 305 parameters were varied to maximize delivery of surfactant to the source zone, minimize injected surfactant volume, and prevent surfactant losses outside the test area. Three primary modelling tasks were undertaken to design the pilot-scale test configuration. First, geostatistical modelling of the aquifer hydraulic conductivity field was performed to generate parametric input for flow and transport models. Next, the system pumping well configuration was designed and optimized using industry standard three-dimensional flow and transport software. Two-dimensional multiphase infiltration and solubilization simulators were then used to explore the potential initial PCE distribution and surfactant performance in the field. Geostatistical heterogeneity modelling Sediment beneath the Bachman Road site consists predominantly of fine to medium grained sand. Grain size distributions were measured for 167 core samples collected at 0.15 to 0.61 m intervals along eight vertical and angled cores. After grain size distribution renormalization excluding the fraction coarser than 850 (xm, the mean grain size was used to estimate hydraulic conductivity from the Carman-Kozeny relationship. Estimated hydraulic conductivity values ranged from 5 to 46 m day 1 (Drummond et al, 2000). Three-dimensional realizations of conductivity values, conditioned to the original 167 estimates, were generated at one-foot (30 cm) grid increments across the study area using a sequential Gaussian simulation algorithm (Deutsch & Journel, 1998). These realizations were employed in three-dimensional flow and transport simulations. For two-dimensional infiltration and solubilization simulations, a 6.7 x 4.9 m XZ profile (vertical east-west) was extracted from the three-dimensional conductivity fields. Three-dimensional flow and transport modelling Three-dimensional numerical simulation software was used to design and optimize the surfactant delivery/extraction system (Fig. 2). VMODFLOW v2.8.2 was used to predict natural and engineered flow fields, MT3DMS to forecast surfactant transport, and MODPATH to predict advective surfactant sweep using particle tracking. Pertinent transport model parameters include longitudinal (0.3 m), transverse (0.15 m), and vertical dispersivity (0.05 m). Simulation results and site constraints dictated that the final pilot-scale test design consist of a single extraction well ( min" 1 ), a row of three water injection wells (3.8 1 min" 1 each) to establish a flow field through the source zone, and a gallery of three surfactant injection wells (1.9 1 min" 1 each) positioned between the water supply and extraction wells. The selected pumping schedule involved start-up of the extraction well, followed shortly by all injection wells. Injection of a 6% surfactant solution over the entire aquifer thickness was initiated three weeks later for five days. Operation of well SI was then discontinued and injection of surfactant continued for an additional five days in wells S2 and S3, screened over the top and bottom 1.2 m of saturated depth. Simulations predicted that this targeted injection scheme would efficiently deliver surfactant to suspected highly contaminated regions and reduce overall

4 306 Linda M. Abiïola et al. ML2 (40 ; 5 ft. o W3 NJIL5 (65 ) Shed ML3 (52 ) m Ex Well Speedy 197 Printing Surfactant injection well (S 1, S2, S3) o Water injection well (Wl, W2, W3j /SI, m Multilevel well monitoring point (with vertical depth below grourwf ML-5E Treatment Zone Fig. 2 Bachman Road SEAR pilot-scale test site plan. SEAR treatment zone is shaded. surfactant cost. Water injection and extraction were then maintained for an additional month to ensure surfactant and plume capture. Simulations using this final design predicted a sweep of the entire treatment zone and over 95% recovery of injected surfactant. Transport simulations were also used to develop a systematic sampling schedule of the extraction and multilevel wells. Extensive sampling was necessary to capture the peak surfactant concentration at the monitoring and extraction wells for future data analysis. Use of transport simulations permitted optimization of the sampling frequency, while minimizing sampling and analysis costs. Approximately 4500 samples (not including duplicates) were analysed for dissolved constituents, including PCE and Tween 80, at the University of Michigan analytical laboratory. Two-dimensional infiltration and solubilization modelling Two-dimensional infiltration and solubilization modelling were performed to evaluate the solubilization potential of Tween 80 at the Bachman Road site (Drummond et al., 2000). The two-dimensional cross sectional domain traced a flow path between the centre surfactant injection well (S2) and the extraction well (see Fig. 2). Infiltration simulations to predict the initial PCE distribution were conducted using the model VALOR (Abriola et al., 1992). Figure 3 portrays one example PCE infiltration simulation. Predicted saturations ranged up to 10% on top of the transition zone, indicating source PCE would likely be present just above the clay layer. Larger saturations were also predicted in the upper part of the saturated zone within the high conductivity middepth stratification. Simulated infiltration results matched concentration trends evident at the field site.

5 Surfactant enhanced aquifer remediation: application of models 307 ~i PCE saturation r distance (m) Fig. 3 Representative predicted PCE pre-test distribution. For plotting purposes, the maximum saturation shown is 3%. Satufations resulting from infiltration simulations were then input to the solubilization simulator MISER (Abriola et al., 1997) to evaluate the robustness of the pilot-scale test design and to test the efficacy of the scheme in the presence of representative aquifer heterogeneity. MISER had been previously validated with data from surfactant flushing experiments conducted in laboratory sand tank systems (Rathfelder et al., 2001). Simulation results indicated that Tween 80 should be effective in removing source PCE at the site. Simulated surfactant recovery along the cross section was about 97% after 20 days, with the remaining surfactant primarily contained in low permeability regions or adsorbed on the solid phase. MODEL POST-AUDIT Good agreement was found between simulated and field-measured surfactant concentrations. Figure 4(a) is a plot of measured and predicted Tween 80 breakthrough curves at the observation point ML-4E (see Fig. 2). ML-4E is the lowermost sample point of multilevel well 4 at a depth of 6.8 m below the ground surface. Figure 4(b) presents measured and simulated breakthrough curves for well ML-5E at a depth of 6.5 m. The sweep of ML-5E with surfactant was judged critical in that, prior to test commencement, measured aqueous PCE concentrations were greater than 100 ppm and samples exhibited a strong solvent odour and sheen. Together, these characteristics are strongly indicative of free-phase PCE present near ML-5E. Comparison of measured and predicted Tween 80 breakthrough curves reveals steeper fronts and less tailing for measured curves with slightly greater maximum concentrations. Possible reasons for these discrepancies include over-estimation of longitudinal dispersivity, excessive numerical dispersion, and a lower degree of aquifer heterogeneity. Interpretation of breakthrough concentration discrepancies are complicated by the unsteady three-dimensional flow field, variable targeted surfactant injection, and uncertainty in aquifer parameters and their distribution.

6 308 Linda M. Abriola et al Measured jtl Breakthrough Measured Breakthrough Simulated Breakthrough Simulated Breakthrough Time from start of Tween injection (days) Fig. 4 Simulated and measured Tween 80 breakthrough curves for (a) ML-4E, and (b) ML-5E. Concentrations in ppm. SEAR FIELD PERFORMANCE Field data illustrate the effectiveness of the Tween 80 flush to enhance the solubility of PCE at the Bachman Road field site. Figure 5 presents PCE and Tween 80 concentrations measured at the extraction well. As expected, the concentration of PCE rises with the arrival of Tween 80. A second increase of PCE concentration due to the targeted injection scheme is also evident. PCE concentrations at the extraction well prior to water injection varied from to ppm. The PCE concentration tailing at the end of the test may indicate that soluble PCE originating outside the treatment zone was arriving at the extraction well. This would be possible because the zone of influence of the extraction well is significantly larger than the targeted treatment zone. Another possible explanation is that solubilized PCE was still present in the treatment zone at the end of the test. Overall, approximately 95% of the injected surfactant was recovered and the ability of Tween 80 to greatly increase the solubility of PCE and enhance source removal at the Time from start of Tween injection (d) Fig. 5 Measured PCE and Tween 80 concentrations at extraction well.

7 Surfactant enhanced aquifer remediation: application of models 309 Bachman field site was demonstrated. Extraction well data indicate that over 19 1 of PCE were extracted during the test. The application of computer models in pilot-scale test design was invaluable to the execution of an efficient and effective SEAR demonstration. On-going work includes further evaluation of field data and calibration of models to reproduce that data. Quarterly multilevel well sampling within the source zone is also being performed to quantify PCE concentration rebound. Further characterization and simulation work are underway to explore the potential for full-scale SEAR implementation. Acknowledgements Funding for this research was provided by the Michigan Department of Environmental Quality, under Contract no. Y80GT1, and the US Environmental Protection Agency, Great Lakes and Mid-Atlantic Center for Hazardous Substance Research (GLMAC-HSRC), under Grant no. R The content of this publication does not necessarily represent the views of either agency and has not been subject to agency review. The following individuals provided assistance in data collection and data analysis: Michael Gebhard, Ernie Hahn, Peter Brink, C. Andrew Ramsburg, Tom Yavaraski, Jodi Ryder and Hsin-Lan Hsu. REFERENCES Abriola, L. M., Rathfelder, K. M., Yadav, S. & Maiza, M. (1992) VALOR: a PC code for simulating subsurface immiscible contaminant transport. Electric Power Research Institute TR-I010I8. Palo Alto, California, USA. Abriola, L. M., Lang, J. & Rathfelder, K. M. (1997) Documentation for: Michigan Soil-Vapor Extraction Remediation (MISER) Model A computer program to model bioventing of organic chemicals in unsaturated geological material. US Environmental Protection Agency, EPA/600/R-97/099. Deutsch, C. V. & Journel, A. G. (1998) GSLIB Geostatistical Software Library and User's Guide: Applied Geostatislics Series. Oxford University Press, New York, USA. Drummond, C. D., Lemke, L. D., Rathfelder, K. M., Hahn, E. J. & Abriola, L. M. (2000) Simulation of surfactantenhanced PCE recovery at a pilot test field site. In: Treating Dense Nonacpteous-Phase Liquids (DNAPLs): Remediation of Chlorinated and Recalcitrant Compounds (ed. by G. B Wickramanayake, A. R. Gavaskar & N. Gupta), Battelle Press, Columbus, USA. Mercer,.1. W. & Cohen, R. M. (1990) A review of immiscible fluids in the subsurface: properties, models, characterization, and remediation. J. Contain. Hydrol. 6(2), Pennell, K. D., Abriola, L. M. &. Loverde, L. E. (1996) The use of surfactants to remediate NAPL-contaminated aquifers. In: Non-Aqueous Phase Liquids (NAPLs) in the Subsurface Environment: Assessment and Remediation (ed. by L. N. Reddi), ASCE, New York, USA. Rathfelder, K. M Abriola, L. M, Taylor, T. P. & Pennell, K. D. (2001) Surfactant enhanced recovery of tetrachloroethylene from a porous medium containing low permeability lenses. 2. Numerical simulation. J. Contant. Hydrol. 48(3-4), Taylor, T. P. (1999) Characterization and surfactant enhanced remediation of organic contaminants in saturated porous media. PhD Dissertation, Georgia Institute of Technology, Georgia, USA. Taylor, T. P., Pennell, K. D., Abriola, L. M. & Dane, J. H. (2001) Surfactant enhanced recovery of tetrachoroethylene from a porous medium containing low permeability lenses. 1. Experimental studies../. Contain. Hydrol. 48(3-4),