A Deterministic Approach to Evaluate and Implement Monitored Natural Attenuation for Chlorinated Solvents

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1 REMEDIATION Autumn 2007 A Deterministic Approach to Evaluate and Implement Monitored Natural Attenuation for Chlorinated Solvents Michael J. Truex Christian D. Johnson James R. Spencer T. Prabhakar Clement Brian B. Looney A US EPA directive and related technical protocol outline the information needed to determine if monitored natural attenuation (MNA) for chlorinated solvents is a suitable remedy for a site. For some sites, conditions such as complex hydrology or perturbation of the contaminant plume caused by an existing remediation technology (e.g., pump-and-treat) make evaluation of MNA using only field data difficult. In these cases, a deterministic approach using reactive transport modeling can provide a technical basis to estimate how the plume will change and whether it can be expected to stabilize in the future and meet remediation goals. This type of approach was applied at the Petro-Processors Inc. Brooklawn site near Baton Rouge, Louisiana, to evaluate and implement MNA. This site consists of a multicomponent nonaqueous-phase source area creating a dissolved groundwater contamination plume in alluvial material near the Mississippi River. The hydraulic gradient of the groundwater varies seasonally with changes in the river stage. Due to the transient nature of the hydraulic gradient and the impact of a hydraulic containment system operated at the site for six years, direct field measurements could not be used to estimate natural attenuation processes. Reactive transport of contaminants were modeled using the RT3D code to estimate whether MNA has the potential to meet the site-specific remediation goals and the requirements of the US EPA Office of Solid Waste and Emergency Response Directive P. Modeling results were incorporated into the long-term monitoring plan as a basis for evaluating the effectiveness of the MNA remedy. As part of the long-term monitoring plan, monitoring data will be compared to predictive simulation results to evaluate whether the plume is changing over time as predicted and can be expected to stabilize and meet remediation goals. This deterministic approach was used to support acceptance of MNA as a remedy. Oc 2007 Wiley Periodicals, Inc. INTRODUCTION The United States Environmental Protection Agency provides guidance for use of monitored natural attenuation (MNA) in the Office of Solid Waste and Emergency Response (OSWER; US EPA, 1999) directive Use of Monitored Natural Attenuation at Superfund, RCRA Corrective Action, and Underground Storage Tank Sites. This OSWER directive identifies three lines of evidence for evaluating MNA. In summary, these are (1) monitoring data that clearly indicate the plume is shrinking, (2) characterization data that document the biogeochemical conditions necessary to c 2007 Wiley Periodicals, Inc. Published online in Wiley Interscience ( DOI: /rem

2 A Deterministic Approach to Evaluate and Implement Monitored Natural Attenuation for Chlorinated Solvents Mass balance is a simple accounting process that keeps track of loading (or inputs), attenuation, and the releases (or outputs). support known attenuation processes and the ability to achieve remediation goals, and (3) laboratory or field tests that quantify site-specific natural attenuation processes and rates. If site data are insufficient to develop the first and second lines of evidence, then the third line of evidence needs to be developed with a sufficient technical basis to support remediation decisions. The OSWER directive recognizes that natural attenuation processes occur in all soil and groundwater systems and act, to varying degrees, on all contaminants. Thus, a decision to rely on natural attenuation processes as part of a site remediation strategy does not depend on the occurrence of natural attenuation processes, but on their effectiveness in meeting site-specific remediation goals. The concept of a mass balance between the loading and attenuation of contaminants in a groundwater system provides a framework for conceptualizing and documenting the relative stability of a contaminant plume. Mass balance is a simple accounting process that keeps track of loading (or inputs), attenuation, and the releases (or outputs). For a mass balance to be useful in engineering practice, it is necessary to quantify it in practical ways that facilitate overall site remediation and are consistent with regulatory guidance. For plumes that are still expanding or where hydrologic conditions have changed or will change (e.g., starting or terminating pump-and-treat), a deterministic approach may be necessary to evaluate MNA in a timely manner. The traditional empirical approaches used to support MNA are based on retrospective evaluation of field data. Time trends and statistics are used to show that a plume is stable or shrinking and that the biogeochemical and hydrological conditions are in place and sustainable to provide confidence that the attenuation will continue toward remediation goals at an acceptable rate. In cases where this traditional approach is not feasible for example, where an active remediation is ongoing or where a substantive source removal action has been performed an alternative deterministic mass balance model approach is required. In a deterministic approach, each component of the mass balance for a plume, the loading, attenuation, and releases are quantified and coupled to a fate-and-transport calculation. This approach depends on obtaining reasonable estimates for each of the processes that impact contaminant migration. Reactive transport modeling can be used for implementing this type of plume analysis and providing a technical basis for evaluating MNA as a remedy when simpler evaluations based solely on field data are not suitable. The analysis and predictive functions of reactive transport modeling are important within the context of applying a deterministic approach for MNA to (1) help analyze the relative importance of different attenuation and transport processes within a plume, (2) provide timely decision support, for instance, when there are insufficient temporal monitoring data available, (3) evaluate MNA as a remedy to replace existing remedies (e.g., pump-and-treat) that have perturbed the plume such that data to establish whether the plume is stable will not be available for a long time, and (4) help interpret monitoring data for expanding plumes. Key factors in using a model for these purposes include defining appropriate model configuration and calibration processes and establishing methods to use predictive results to guide long-term monitoring efforts. The objective of this work is to present the steps involved in using reactive transport modeling within a deterministic approach to implement MNA at a complex field site. A field dataset collected at a contaminated site in Louisiana was used to develop a framework for employing the reactive transport code RT3D to evaluate and implement MNA under conditions where an empirical approach was not suitable. 24 Remediation DOI: rem c 2007 Wiley Periodicals, Inc.

3 REMEDIATION Autumn 2007 Exhibit 1. Components of the contaminant source material at the Brooklawn study site Component Weight % in NAPL Dissolved-Phase COC a? hexachlorobutadiene 47 nonchlorinated hydrocarbons 32 other chlorinated compounds ,1,2-trichloroethane ,1,2,2-tetrachloroethane 1.5 tetrachloroethene 1.5 1,2-dichloroethane 1.1 trichloroethene ,2-dichloroethene (total) chloroethene (vinyl chloride) Total 100 a Contaminant of Concern. METHODS At the Petro-Processors Inc. Brooklawn site (PPI Brooklawn site), highly variable geology, transient flow conditions, the impact of a hydraulic containment system operated at the site for six years, and a large number of waste components (Exhibit 1) imposed challenges for evaluating MNA and developing the related long-term monitoring plan. The conceptual model of this study site is shown in Exhibit 2. The deterministic evaluation approach for MNA relies on developing a suitable description of the overall mass balance for the plume. This mass balance is essentially a contaminant transport equation that describes a source flux and attenuated transport of the contaminants. A numerical or analytical model can be used to solve the transport equation. For the PPI Brooklawn site, a numerical 3-D multispecies reactive transport code was used in the mass balance analysis. Three-dimensional flow is important at this site because vertical hydraulic head gradients exist between different transmissive hydrogeologic layers and also because the thicknesses of key hydrogeologic units for contaminant transport, such as the alluvial sediments, vary across the site (Exhibit 3). At the PPI Brooklawn site, the groundwater flow is transient where significant groundwater flow variation, including flow reversal, can occur over a yearly cycle due to hydraulic connection with the Mississippi River (Exhibit 4). For this site, it was necessary to use a reactive transport code capable of modeling the multicomponent reaction processes and three-dimensional, transient flow-and-transport conditions to provide a defensible technical basis for site remediation decisions. In this work, reactive transport was simulated using the RT3D numerical code (Clement, 1997; Clement & Johnson, 2002; Clement et al., 1998) with groundwater flow simulations from the MODFLOW-2000 groundwater flow code (Harbaugh, Banta, & McDonald, 2000). The governing equation for three-dimensional, multispecies transport in saturated porous media for constant porosity is shown in Equation 1 (adapted from Zheng & Wang, 1999). This equation describes the combination of all of the source flux and attenuation processes that contribute to the mass balance: dispersion/diffusion, advection, external c 2007 Wiley Periodicals, Inc. Remediation DOI: rem 25

4 A Deterministic Approach to Evaluate and Implement Monitored Natural Attenuation for Chlorinated Solvents Exhibit 2. Conceptual model for the Brooklawn study site sources/sinks, adsorption, and reaction. Equation 1 is presented in a generalized form, and it is necessary to add specific reaction terms to describe processes at the specific site. rate of sources change + adsorption = dispersion advection + /sinks + reaction (1) C k + ρ b Cˆ k = ( ) C k D ij (v ic k ) + q s t θ t x i x j x i θ C s, k + 1 r k θ In Equation 1, C k is the concentration of the kth species (M/L 3 ), t is time (T), D ij is the hydrodynamic dispersion coefficient tensor (L 2 /T), x i is the distance along the respective axis of the coordinate system (L), v i is the linear pore water velocity (L/T), q s is the volumetric flow rate of sources (positive) or sinks (negative) per unit volume of aquifer (L 3 /T), C s,k is the concentration of the kth species in the sources or sinks (M/L 3 ), θ is the porosity of the aquifer (L 3 /L 3 ), ρ b is the dry bulk density of the subsurface sediments (M/L 3 ), Cˆ k is the concentration of the kth species on the solid phase (M/M), and r k represents the reaction terms for transformation of the kth species (M/L 3 /T). 26 Remediation DOI: rem c 2007 Wiley Periodicals, Inc.

5 REMEDIATION Autumn 2007 Exhibit 3. Conceptual geologic cross section for source area of the Brooklawn study site along Transect A-A (Exhibit 2) Exhibit 4. Conceptual hydraulic cross section for the Brooklawn study site along Transect A-A (Exhibit 2) Units are specified generically as M = mass, L = length, and T = time. Note that the linear pore water velocity times the porosity is equal to the specific discharge (Darcy flux). The reaction term r k may be composed of multiple terms to account for the specific reactions occurring. c 2007 Wiley Periodicals, Inc. Remediation DOI: rem 27

6 A Deterministic Approach to Evaluate and Implement Monitored Natural Attenuation for Chlorinated Solvents For a deterministic approach, source flux must be quantified in a way that it can be used within the selected modeling approach. Although empirical data suitable for evaluating MNA may not be available at a site, data or information necessary to describe the source flux, attenuation capacity, and plume behavior in terms of the components of the fate-and-transport equation can be obtained. For a deterministic approach, source flux must be quantified in a way that it can be used within the selected modeling approach. At the Brooklawn site, the source consists of a large amount of dense nonaqueous-phase liquid (DNAPL) beneath the water table. The contaminant flux from the source was estimated based on laboratory data measuring the groundwater concentration of waste components when in equilibrium with the DNAPL source material. Key components of the attenuation capacity for chlorinated solvents are adsorption and reaction. The following sections describe how parameter estimates for adsorption and reaction were obtained for the study site. Furthermore, the methods for formulating the source flux and attenuation capacity within the site model are also discussed. Adsorption Processes For the purpose of modeling contaminant transport, this study used an assumption of linear equilibrium partitioning, K d, to describe contaminant adsorption processes. While the actual adsorption processes may be more complex, linear equilibrium partitioning was selected because specific data to adequately describe other adsorption mechanisms for the contaminants at the site were not available. Valsaraj et al. (1999) determined the partitioning coefficient for 1,4-dichlorobenzene, 1,2-dichloroethane, 1,1,2-trichloroethane, and 1,1,2,2-tetrachloroethane on three types of PPI Brooklawn site sediments and presented a site-specific correlation relating K d to the octanol-water coefficient, K ow, and the fraction of organic carbon of the soil, f oc (Equation 2). The K ow values used in this correlation and the resulting estimates of K d are listed in Exhibit 5, along with the corresponding retardation factors calculated using Equation 3. K d = K 0.56 ow f oc (2) R = 1 + (K d bulk density)/porosity (3) Dechlorination Reaction Processes Geochemical data are necessary to assess what types of reaction processes may occur at a site. Previous studies conducted at the site (e.g., Clement et al., 2002; Pardue & Jackson, 2000) indicated that the geochemical conditions at the site are appropriate to support reductive dechlorination processes throughout and downgradient of the plume. Organic carbon, needed as a precursor substrate to support anaerobic reductive dechlorination, is available as a co-contaminant in the source (Exhibit 1) and also as soil organic matter in the alluvial sediments, where the fraction of organic matter ranges from 0.39 percent (in silty sand) (Kommalapati et al., 2000) to 1.13 percent (in silty clay) (Valsaraj et al., 1999). The presence of elevated chloride concentrations and reductive dechlorination reaction products were also cited as indicators that reductive dechlorination is currently occurring within the Brooklawn alluvial zone (Clement et al., 2002). To further characterize the degradation processes, laboratory microcosm tests were conducted using aliquots of aseptically collected site sediment and groundwater in sealed 28 Remediation DOI: rem c 2007 Wiley Periodicals, Inc.

7 REMEDIATION Autumn 2007 Exhibit 5. Estimated Equilibrium Partitioning and Retardation Coefficients Chemical Species log 10 (K ow ) K d d (L/kg) Re TeCA 2.39 a TCA 2.12 b DCA 1.47 a PCE 2.88 a TCE 2.42 a cis-dce 1.48 c trans-dce 1.48 b VC 0.6 a a From Schwarzenbach et al. (1993). b From US EPA (1979) (values were calculated using a structure-activity correlation). c The value for cis-dce was assumed to be equal to the value for trans-dce. d The K d calculation used an f oc value of 0.39 percent, as measured by Kommalapati et al. (2000) for sandy material in the PPI Brooklawn site alluvial zone. e Retardation factor calculated using a porosity of 0.3 and a dry bulk density of 1.6 kg/l. bottles (Pardue & Jackson, 2000; Truex et al., 2002). Individual bottles were spiked with selected contaminants. Periodically, aqueous and headspace samples were withdrawn to monitor the change in the concentration of the spiked compound and any dechlorination intermediates. Dechlorination occurred for all contaminants based on observations of a decrease in contaminant concentration and production of lesser chlorinated daughter products (e.g., dichloroethene [DCE] and vinyl chloride [VC]) at a significantly greater rate than was observed in sterilized controls. Once formed, intermediate chlorinated compounds were rapidly transformed to ethene in the microcosm tests. The observed dechlorination reactions for chlorinated ethene and chlorinated ethane compounds are shown in Exhibit 6 and are a subset of those reported by Lorah and Olsen (1999) for wetland sediments. Rates of chlorinated ethene and chlorinated ethane dechlorination were determined from microcosm results ( Exhibit 7). A first-order kinetic model was used to describe all the dechlorination pathways shown in Exhibit 6. Previous studies have shown that first-order kinetics are a reasonable and practical alternative for modeling biodegradation mechanisms at field scales (Clement, 2001; Clement et al., 2000, 2004; US EPA, 1998). Reactive Transport Modeling Reactive transport modeling can provide estimates of contaminant fate and migration by applying numerical solution techniques to solve the governing flow, reaction, and transport equations. How well the solution results match observed contaminant migration in the field is, in part, dependent on the configuration of the model (model grid, representation of site geology, selected boundary conditions, etc.) and the input c 2007 Wiley Periodicals, Inc. Remediation DOI: rem 29

8 A Deterministic Approach to Evaluate and Implement Monitored Natural Attenuation for Chlorinated Solvents Exhibit 6. Reaction pathways observed in laboratory microcosm tests using Brooklawn alluvial sediments parameters to the reaction and transport equations. For acceptance of the model as a reasonable estimator of contaminant migration, it is important that the model configuration and input parameter values are established using a sound technical basis. The input parameters for the source flux, adsorption, and reaction component of the model were discussed above. Determining the advection component of the transport equation requires parameters that describe the hydraulic properties of the site, including the distribution of hydraulic conductivity and porosity, and configuring the model to represent the hydraulic setting, including the hydraulic gradients and associated hydraulic boundaries that impact these gradients. Contaminant dispersion must also be described, although typically dispersion can only be estimated as part of a model calibration process. The model must be calibrated to known data to provide a technical basis for using the model in a predictive mode. The study site provides an example of how the model configuration and calibration processes can be structured. For the PPI Brooklawn site, the model was configured as a grid covering an area of 5,975 feet by 7,175 feet with 25 layers of variable thickness as needed to describe the 30 Remediation DOI: rem c 2007 Wiley Periodicals, Inc.

9 REMEDIATION Autumn 2007 Exhibit 7. Summary of reaction parameters and values for laboratory microcosm tests First-Order Reaction Parameter Values from Parameter Values from Rate Parameter Units Brooklawn Microcosm Tests Lorah and Olsen (1999) k PCE 1/day 0.5 ND a k TeCA 1/day k TCE 1/day k TCA 1/day k cdce 1/day k tdce 1/day k 11DCE 1/day 0 ND a k DCA 1/day k VC 1/day k CA 1/day 0 ND a a ND denotes that no data were available. vertical features of the 15 subsurface over a 360-foot depth interval (Exhibit 8). The distribution of hydraulic conductivity was related to the percentage of clay, silt, and sand within each grid cell. Data from 565 boreholes that described the lithology with depth were interpolated to map the distribution of clay, silt, and sand across the modeled area. Intrinsic hydraulic conductivity values for the clay, silt, and sand were assigned based on laboratory permeability data from core samples. Hydraulic conductivity for a grid cell was then calculated as the average of the clay, silt, and sand hydraulic conductivity values weighted by the percentage of each sediment type within the grid cell. The resulting hydraulic conductivity estimates compared favorably to available pump test data. For example, data from a pump test at the site yielded a calculated hydraulic conductivity range of 0.3 to 1.9 feet/day with a mean value of 0.6 feet/day; the estimated hydraulic conductivity value for this area in the model was 0.59 feet/day. Data from another pump test yielded a range of 0.06 to 1.3 feet/day with a mean of 0.5 feet/day; the model value was 0.11 feet/day. Hydraulic head boundary conditions for the flow model were assigned based on the Mississippi River stage and hydraulic head data from upgradient monitoring wells. Because the river stage varies seasonally, a transient boundary condition was established. Groundwater flow is generally perpendicular to the Mississippi River so that two of the model boundaries could be defined as not allowing flow outside the model grid. The flow model was then calibrated to the transient hydraulic head data by making small adjustments to the conductivity values and unknown boundary conditions such as recharge. Calibrated hydraulic heads were within 2 feet of measured hydraulic heads at the 72 monitoring locations. Three key reactive transport parameters related to the natural attenuation capacity are adsorption, reaction, and dispersion. As described above, data were used to establish parameter values for the adsorption and reaction processes. The reactive transport model incorporated a user-defined reaction module within the RT3D code to allow description of the site-specific reaction processes observed in the laboratory microcosm tests. To apply the laboratory-derived dechlorination reaction rates in the field, a scaling factor was c 2007 Wiley Periodicals, Inc. Remediation DOI: rem 31

10 A Deterministic Approach to Evaluate and Implement Monitored Natural Attenuation for Chlorinated Solvents Exhibit 8. Plan view of the modeling grid for the PPI Brooklawn site applied to account for differences between the laboratory conditions under which the rates were determined and the conditions in the field (e.g., sediment disturbance during sample collection, batch test conditions versus porous media flow). An initial value of 0.1 was selected for this scaling factor and then adjusted in the calibration process, although relative reaction rates of the different contaminants were held constant. For dispersion, a reasonable range of dispersivity values was estimated based on the compilation of dispersivity values from multiple field investigations reported in Gelhar et al. (1992). From this information, an initial range of dispersivity values was selected to test in the model calibration process. A systematic approach was used in calibrating the reactive transport model. A matrix of simulations was conducted to examine how variations in reaction and transport parameters impacted the migration of the contaminants. Simulation results were compared to field data collected at wells downgradient from the source area. The best match of simulation results to field data (34 locations) was determined by a combination of (1) the least sum of the difference between simulated and measured concentrations of the eight contaminant species at locations within the plume and (2) comparison of the extent of the simulated plume to observed plume extent based on monitoring locations at or just beyond the plume perimeter where no contamination has been observed. The best fit model configuration was selected as the base case for use in subsequent simulations. Exhibit 9 is a depiction of the simulated VC plume for the best-fit model and the locations used in the calibration comparison. Calibration of the model was conducted using data 32 Remediation DOI: rem c 2007 Wiley Periodicals, Inc.

11 REMEDIATION Autumn 2007 Notes: Wells in the source area are not included. Black dots indicate locations with measured concentrations above the detection limit. Gray dots indicate locations with measured concentrations below the detection limit. Note that monitoring well screen locations are at varying depths. Exhibit 9. Simulated VC plume with the calibrated model and locations for available field data in plan view (a) and isometric view (b) collected prior to the active hydraulic containment activities at the site. These data were collected over a short period of time and did not provide suitable data to directly determine whether the plume had been stable at that time. However, these data provided measured contaminant concentrations at specific locations for comparison to the predicted concentrations from the model. Verification of the model calibration can be conducted using the data collected during continued natural attenuation monitoring, which provides a large set of temporal and spatial data under the natural gradient conditions. This continued process of calibration verification is discussed as part of the configuration of the long-term monitoring plan. c 2007 Wiley Periodicals, Inc. Remediation DOI: rem 33

12 A Deterministic Approach to Evaluate and Implement Monitored Natural Attenuation for Chlorinated Solvents APPLICATION OF THE DETERMINISTIC APPROACH FOR MNA EVALUATION The results of the deterministic evaluation of MNA were found suitable to support selection of MNA as the plume remedy and termination of the hydraulic containment system. Once simulated contaminant migration using the reactive transport model was shown to reasonably match the site history (i.e., model calibration), it was then possible to justify using a deterministic approach for evaluating MNA. In this approach, the reactive transport model predicted future migration of the contaminants, and results were used to evaluate the potential for MNA to meet the remediation goals of the PPI Brooklawn site. Future migration was estimated under the scenario that hydraulic containment around the source area was discontinued. Simulations of future contaminant migration predicted that natural attenuation at the PPI Brooklawn site will stabilize the dissolved contaminant plume such that it does not migrate to the defined downgradient receptors. Specifically, after hydraulic containment ceases, the dissolved contaminant plume will migrate about 1,000 feet downgradient of the source area (Exhibit 10) and then stabilize such that the attenuation mechanisms balance the source flux. An example of how the plume stabilizes over time is depicted in Exhibit 11. The results of the deterministic evaluation of MNA were found suitable to support selection of MNA as the plume remedy and termination of the hydraulic containment system. INTEGRATING THE DETERMINISTIC APPROACH INTO LONG-TERM MONITORING The OSWER directive on MNA (US EPA, 1999) describes US EPA expectations for performance monitoring of the technology. In addition, monitoring plan guidance is described in the Prepare Long-Term Monitoring Plan section of the US EPA MNA Protocol (US EPA, 1998). The predictive modeling results from a deterministic approach to MNA in conjunction with monitoring results can effectively provide a basis for assessing whether the plume is behaving over time as predicted and can be expected to stabilize and meet remediation goals. A long-term monitoring plan (LTMP) incorporating the predictive modeling results was developed and approved for the study site to meet the intent of the monitoring expectations set forth by the US EPA. The LTMP outlines the means to provide the data necessary to confirm that the MNA remedy is meeting the remedial objectives. The remedial objective identified for the groundwater at the PPI Brooklawn site is to maintain the contamination within the boundaries under administrative control of the site such that the contamination does not impact potential downgradient receptors outside of this boundary. Thus, the overall objective of the monitoring plan is to verify that the natural attenuation processes are occurring as expected and the plume stabilizes before reaching receptors or migrating off site. There are two basic components of the LTMP: (1) verification of natural attenuation processes and (2) verification that remedial objectives are being met. Monitoring along transects parallel with the dominant migration pathway was included in the LTMP to verify the natural attenuation processes. Wells at selected locations upgradient of receptors (i.e., sentry wells) were chosen to verify that remedial objectives were met. At the PPI Brooklawn site, model predictions were used to evaluate the fate of the dissolved contaminant plume. These predictions indicate that the plume will expand over 34 Remediation DOI: rem c 2007 Wiley Periodicals, Inc.

13 REMEDIATION Autumn 2007 Note: Wells P and P serve as sentry monitoring wells for the plume. Exhibit 10. Maximum extent (2 µg/l) of VC plume in relation to the site property line and the Mississippi River a period of time due to termination of hydraulic containment and then stabilize. The model results include concentration profiles as a function of time for each contaminant species in the resulting dissolved contaminant plume. Because the source area was hydraulically contained for about six years, after groundwater extraction is terminated, contaminant concentrations are expected to increase downgradient of the source over a period of about ten years before stabilizing. However, the concentrations will increase at a rate that is much lower than would occur if no natural attenuation occurred. Contaminant concentration profiles are expected to follow a specific pattern based on the degradation processes observed in site-specific microcosm tests. If the actual contaminant plume is to become stable, the concentration profiles over time at monitoring locations for each contaminant species should be similar to the profiles predicted by the model. Thus, the c 2007 Wiley Periodicals, Inc. Remediation DOI: rem 35

14 A Deterministic Approach to Evaluate and Implement Monitored Natural Attenuation for Chlorinated Solvents Note: The impact of the seasonal groundwater flow variation is shown by the small oscillations in concentrations at the monitoring location. The overall concentration trend increases for a time at these locations and then remains stable. Exhibit 11. Predicted VC concentrations at points 1 and 2 on Transect A-A (Exhibit 2) Exhibit 12. Simulation concentration profile of PCE along Transect A-A (Exhibit 2) downgradient of the primary source area corresponding to the year 2020 LTMP uses a comparison of predicted concentration profiles to measured concentration profiles to evaluate the performance of the selected MNA remedy. For example, Exhibits 12 and 13 show model-predicted concentration profiles for PCE and VC along a transect (Transect A-A, Exhibit 2) downgradient of the primary source area at the PPI Brooklawn site for the year There are three concentration 36 Remediation DOI: rem c 2007 Wiley Periodicals, Inc.

15 REMEDIATION Autumn 2007 Exhibit 13. Simulation concentration profile of VC along Transect A-A (Exhibit 2) downgradient of the primary source area corresponding to the year 2020 profiles shown in each of the figures. One profile is based on the model prediction using the natural attenuation rates selected from the calibration to site data. Another profile is based on a model prediction using biological natural attenuation rates that are 10 percent of the rates selected from the calibration procedure. The third profile is based on model predictions with biological natural attenuation rates set to zero. As shown in the exhibits, the concentration profile of contaminants downgradient of the source depends significantly on the magnitude of the natural attenuation processes. Thus, comparison of measured and predicted concentrations at monitoring wells located along a transect downgradient of the source is considered to be an acceptable verification of whether attenuation processes are occurring as expected. If natural attenuation processes are occurring at the site as expected, the field data should be most similar to the predicted concentrations based on the calibrated model. If the data are more similar to one of the other profiles, then the site managers will need to re-evaluate the MNA approach and implement a contingency remedy if necessary. CONCLUSIONS Interpretation of site data for evaluating MNA and preparing long-term monitoring plans can be facilitated by a deterministic approach using reactive transport modeling. Simulations do not exactly predict contaminant migration but, with calibration to site data, can provide a framework to assess the natural attenuation processes and estimate their impact on plume migration. The simulation results also provide a basis for implementing a long-term monitoring plan to specifically verify the effectiveness of the natural attenuation processes. Reactive transport models can also provide a rational approach to integrate disparate site data available at an MNA field site and can serve as an acceptable technical basis for US EPA approval of MNA as a remedial action. c 2007 Wiley Periodicals, Inc. Remediation DOI: rem 37

16 A Deterministic Approach to Evaluate and Implement Monitored Natural Attenuation for Chlorinated Solvents ACKNOWLEDGMENTS This work was funded by NPC Services Inc. as part of remedial action planning for the Petro- Processors Inc. Brooklawn site. We also acknowledge the insight provided through the authors participation in the Monitored Natural Attenuation Project sponsored by the U.S. Department of Energy and coordinated by the Savannah River National Laboratory. REFERENCES Clement, T. P. (1997). RT3D A modular computer code for simulating reactive multi-species transport in 3-dimensional groundwater aquifers. PNNL Richland, WA: Pacific Northwest National Laboratory. Clement, T. P. (2001). A generalized analytical method for solving multi-species transport equations coupled with a first-order reaction network. Water Resources Research, 37, Clement, T. P., & Johnson, C. D. (2002). RT3D v2.5 update document. Richland, WA: Pacific Northwest National Laboratory. Retrieved April 27, 2007, from down.htm#doc Clement, T. P., Gautam, T. R., Lee, K. K., Truex, M. J., & Davis, G. B. (2004). Modeling coupled NAPL-dissolution and rate-limited sorption reactions in biologically active porous media. Bioremediation Journal, 8(1 2), Clement, T. P., Johnson, C. D., Sun, Y., Klecka, G. M., & Bartlett, C. (2000). Natural attenuation of chlorinated solvent compounds: Model development and field-scale application at the Dover site. Journal of Contaminant Hydrology, 42(2 4), Clement, T. P., Sun, Y., Hooker, B. S., & Petersen, J. N. (1998). Modeling multi-species reactive transport in groundwater aquifers. Groundwater Monitoring & Remediation, 18(2), Clement, T. P., Truex, M. J., & Lee, P. (2002). A case study for demonstrating the application of U.S. EPA s monitored natural attenuation screening protocol at a hazardous waste site. Journal of Contaminant Hydrology, 59(1 2), Gelhar, L. W., Welty, C., & Rehfeldt, K. R. (1992). A critical review of data on field-scale dispersion in aquifers. Water Resources Research, 28, Harbaugh, A. W., Banta, E. R., & McDonald, M. G. (2000). MODELOW-2000, the U.S. Geological Survey Modular Ground-Water Model-User Guide to Modularization Concepts and the Ground-Water Flow Process, U.S. Geological Survey Open-File Report Washington, DC. Kommalapati, R. R., Valsaraj, K. T., & Constant, W. D. (2000). Soil-water partition coefficients, adsorption/desorption hysteresis, desorption kinetics and bioavailability of chlorinated organic compounds at the PPI site. Final report submitted to NPC Services Inc, Baton Rouge, Louisiana. Lorah, M. M., & Olsen, L. D. (1999). Degradation of 1,1,2,2-tetrachloroethane in a freshwater tidal wetland: Field and laboratory evidence. Environmental Science and Technology, 33(2), Pardue, J., & Jackson, A. (2000). Natural attenuation of chlorinated VOCs in the intermediate sand at the Brooklawn site: Array and microcosm data. Baton Rouge, LA: Hazardous Waste Research Center, Louisiana State University. Schwarzenbach, R. P., Gschwend, P. M., & Imboden, D. M. (1993). Environmental organic chemistry. New York: Wiley. 38 Remediation DOI: rem c 2007 Wiley Periodicals, Inc.

17 REMEDIATION Autumn 2007 Spencer, J. R., Johnson, C. D., Truex, M. J., & Clement, T. P. (2002). Modeling biological transformation of chlorinated ethanes and ethenes in support of natural attenuation. Presented at the Third International Conference on Remediation of Chlorinated and Recalcitrant Compounds, Monterey, CA, May Truex, M. J., Skeen, R. S., & Butcher, M. G. (2002). Dechlorination of chlorinated ethane compounds at the Petro-Processors, Inc. Brooklawn Site: Microcosm test results. PNWD Richland, WA: Battelle Pacific Northwest Division. United States Environmental Protection Agency (US EPA). (1979). Water-related environmental fate of 129 priority pollutants (Vol. II). EPA/440/4-79/029B. Washington, DC: Author. United States Environmental Protection Agency (US EPA). (1998). Technical protocol for evaluating natural attenuation of chlorinated solvents in ground water. EPA/600/R-98/128. Washington, DC: US EPA, Office of Research and Development. United States Environmental Protection Agency (US EPA). (1999). Use of monitored natural attenuation at Superfund, RCRA corrective action, and underground storage tank sites. OSWER Directive number P. Washington, DC: US EPA, Office of Solid Waste and Emergency Response. Valsaraj, K. T., Kommalapati, R. R., Robertson, E. D., & Constant, W. D. (1999). Partition constants and adsorption/desorption hysteresis of volatile organic compounds on soil from a Louisiana Superfund site. Environmental Monitoring and Assessment, 58(2), Zheng, C., & Wang, P. P. (1999). MT3D: A modular three-dimensional multispecies transport model Documentation and user s guide. SERDP Vicksburg, MS: United States Army Corps of Engineers, Engineer Research and Development Center. Retrieved April 27, 2007, from Michael J. Truex is an environmental engineer at the Battelle Pacific Northwest Division specializing in remediation research and field applications primarily related to monitored natural attenuation and bioremediation of chlorinated solvents. His experience includes technology development, technology assessments, applications of numerical fate-and-transport modeling, and feasibility and treatability assessments at U.S. Department of Energy (US DOE), U.S. Department of Defense (DOD), and private remediation sites. Christian D. Johnson has been involved with environmental restoration and remediation technology research and development at Battelle since He has designed and implemented in situ bioremediation systems for treatment of chlorinated solvents at the US DOE, DOD, and private industry sites. Johnson is a developer of RT3D, a multispecies reactive transport simulation software. He continues to improve the RT3D code and to customize it for application of both active remediation and natural attenuation. James R. Spencer is a graduate of the University of Mississippi (BS, 1981; MS, 1983) and has been involved with the Petro-Processors Inc. Brooklawn site for over 15 years. His work has ranged from environmental site assessments to utilizing reactive transport models for site remediation, allowing him to work on a wide rage of projects throughout the southeastern United States. Spencer is a senior hydrogeologist with EcoScience Resource Group, LLC, and is a registered professional geologist in Mississippi, Tennessee, and Arkansas. T. Prabhakar Clement teaches in the Department of Civil Engineering at Auburn University, Alabama. Professor Clement is the lead author of the widely used reactive transport code RT3D; he is also a coauthor of the US EPA s natural attenuation screening tool BIOCHLOR. His current research interests include development c 2007 Wiley Periodicals, Inc. Remediation DOI: rem 39

18 A Deterministic Approach to Evaluate and Implement Monitored Natural Attenuation for Chlorinated Solvents of laboratory-scale models to visualize groundwater transport processes, modeling of density-coupled flow problems, numerical modeling of metals transport involving surface complexation reactions, derivation of analytical solutions to reactive transport equations, and management of erosion in engineered hydrological systems. Dr. Brian B. Looney is a senior fellow engineer at the US DOE Savannah River National Laboratory (SRNL) in Aiken, South Carolina, and an adjunct professor in the Environmental Engineering Science Department at Clemson University. Dr. Looney coordinates development and deployment of innovative environmental characterization and cleanup methods at the SRNL and serves as a technical advisor supporting the US DOE Environmental Management Program. 40 Remediation DOI: rem c 2007 Wiley Periodicals, Inc.