ENVIRONMENTAL POLICY ANALYSIS
REMEDIATION
A Risk-Based Approach to Soil Remediation Modeling ANDY DAVIS, SUSAN KAMP, GEORGE F E N N E M O R E , RICHARD S C H M I D T , MICHAEL KEATING Geomega Boulder, CO 80303
KARL H O E N K E , JEFF WYATT Chevron Chemical Company San Ramon, CA 94583
A new cost-efficient approach to modeling cleanup of contaminated sites is described. The technique involves linkage of accepted computer models to form a risk-based remediation (RBR) package that analyzes site remediation via iterative fate and transport modeling. Significant savings are realized through use of this strategy compared with current practices that are not cost-efficient and are tantamount to overremediation. Application of this RBR strategy to a soil cleanup task at a Superfund site in the southeastern United States resulted in a reduction of the soil volume requiring remediation from 17,600 m3 to 5350 m3 while meeting riskbased groundwater criteria at downgradient exposure points. The RBR approach also focuses attention on the questionable cost-benefit value associated with marginal increments in risk reduction.
Most proposed or completed soil cleanup actions at more than 500 U.S. Superfund sites are based on human health risk assessments (i). Cleanup goals for contaminated sites incorporate future land use and exposure assumptions after averaging temporal and spatial risks across the site. Typically, policy involves a strategy that removes all material exceeding a numerical value based on risk assessment results. This deterministic approach, by definition, results in over-remediation of the site because all soil exceeding the action level is replaced with clean fill containing chemical concentrations well below the mandated cleanup level. Recalculating risks at this point reveals an average site risk far below the mandated goal. Recognition of this issue (2) has led to development of alternative statistical approaches that attempt to correct for over-remediation of sites (3, 4). However, these cleanup strategies often seek to resolve the problem through an averaging concept, either sitewide or based on a residential unit area— for example, 0.2 hectare (ha) (5)—rather than on a cause-and-response, risk-based approach between source and receptor. Moreover, previous efforts to reduce remedial volumes have focused on surface soilrelated risk but not on subsurface soils. A riskbased approach accounting for both spatial variability in contaminant concentrations and the migration of constituents through the vadose and saturated zones to downgradient (groundwater) exposure points has not yet been applied to subsurface soils. We describe development and use of a risk-based remediation (RBR) package, a modular computer program (based on widely accepted codes), which meets the human health protection intent of site remediations and accounts for heterogeneity in chemical distribution and site-specific vadose and saturated zone characteristics. Ancillary material, including computational analyses, risk calculations, model input data, and citation to the full documentation, is supplied as supporting information to this article. The program output links contaminant removal and risk reduction causally (6), resulting in a decreased volume of material requiring treatment relative to conventional approaches. Our approach has important policy implications because it focuses attention on the questionable cost-benefit value associated with marginal increments in risk reduction. Site-specific modeling The RBR program was used to determine the excavation volume and to verify attainment of remedial goals at the 0.7-ha Marzone Superfund site in Tifton, Ga. The former pesticide-formulating facility, built in 1950, is depicted in Figure 1. The remedial investigation (RI)/feasibility study, based on an initial
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0013-936X/97/0931-520A$14.00/0 © 1997 American Chemical Society
19 samples (7), identified atrazine, oc-BHC, DDT, DDE, DDD, dieldrin, endosulfan II, heptachlor epoxide, methyl parathion, and toxaphene as chemicals of concern (COCs). These data were used in a site risk assessment establishing numerical cleanup goals for surface soils [0-0.3-meter (m) depth], based on potential dermal and ingestion exposure pathways, and for subsurface soils (0.3 m to groundwater), based on ingestion of groundwater at a hypothetical domestic drinking water supply well. The surface of the Marzone site is flat with littie vegetation. The unsaturated zone consists mainly of tightly packed clay with low permeability [10~7 centimeters per second (cm/s)], high bulk density [1.8 grams (g)/cm3], and low porosity (0.27) compared with typical clays (8). U.S. Climatologic Data Center records collected in Tifton from 1951 to 1980 indicate that the area receives an annual average rainfall of 118 cm, with a depth to groundwater varying between 1.2 m and 2.5 m. The subsurface lithology consists of interdigitating finegrained sediments (Figure 2) composed of clays, sandy clays, and occasional silty clays and clayey sands. The northern edge of the Marzone site is situated on a groundwater divide so that all groundwater flowing across the site to a potential exposure point south of the site boundary originates from recharge of infiltrating
FIGURE 1
Marzone Superfund Site, Georgia Site map showing layout of former pesticide-formulating facility. The inset indicates correspondence between computer modules that were used and the fate and transport of compounds in soil and groundwater.
precipitation at the site (Figure 2). The average hydraulic conductivity based on a pumping test at the site was 1.1 x 10"3 cm/s (9). The record of decision (ROD) specified treatment of excavated soils by low-temperature thermal desorption, followed by replacement of the remediated soils in the excavation. Because of the ubiquitous distribution of surface COCs and location and neighborhood sensitivity, all surface soils with COCs exceeding action levels were treated. Additional post-RI sampling at 106 site locations provided sufficient data to allow subsurface soil remedial objectives to be met through a risk-based approach. The criterion for subsurface soil cleanup was protection of groundwater at a set of assumed receptor points located at specified distances downgradient for each COC. Subsurface soil cleanup was
attained when predicted groundwater concentrations met maximum contaminant levels (MCLs) or risk-based levels at all hypothetical receptor wells, located 25 m downgradient of the site boundary for atrazine and 10 m downgradient of the site boundary for all other subsurface COCs (Figure 2).
Computational methodology The RBR model package accommodates modules simulating the fate and transport of compounds in soil and groundwater (Figure 1, inset). The KTB3D kriging module within GSLIB {10) was used to incorporate three-dimensional vadose zone chemical distribution, and the output interfaced with the vadose zone model SWMS-2-D to simulate transport of contaminants through the unsaturated zone to the groundwater table. The solute transport model MT3D {11), coupled with a velocity field from a calibrated VOL.31, NO. 11, 1997/ENVIRONMENTAL SCIENCE & TECHNOLOGY/NEWS* 5 2 1 A
tions for each surface and subsurface constituent. The exact form of the spatial reSurface lithology and groundwater flow lationships depended on the Site map showing groundwater flow path and location of hypothetical exposure points. The subsurface lithology shown in the cross section (inset) consists of interdigitating fine-grained sediments composed of site-specific distribution of clays, sandy clays, and occasional silty-clays and clayey-sands. the constituents being modeled (13). Subsequently, the 3-D kriging routine KTB3D (10) was used to estimate chemical concentrations for each surface and subsurface soil remedial unit (RU) (7.6 m on a side and 0.7 m deep, consistent with compatible excavation equipment). An underlying assumption of kriging is that the average value of the data is spatially invariant. To account for chemical attenuation with depth, a linear, vertical drift term—the magnitude of which was computed by GSLIB based on the chemical-specific sampling results and the method of Myers (14)—was incorporated into the krige. Failure to include this drift term resulted in underestimation of surface chemical concentrations and overestimation of subsurface concentrations. The kriged soil chemical distribution was used to assign concentrations to individual RUs. All surface (0-0.3 m) RUs with analyte concentrations exceeding action levels were identified for removal and treatment. Subsurface soil RUs at incremental 0.6-m intervals (i.e., 0.30.9, 0.9-1.5, and 1.5-2.1 m) were identified for remediation differently, because potential human health risks at the site were defined on the basis of subsurface transport to the hypothetical reMODFLOW (12) groundwater flow model, simuceptor points. The extent of chemical transport from lated migration of chemicals through the aquifer to subsurface soil to receptor points depends on the downgradient compliance points. The temporally depth distribution in the vadose zone, the soil and varying groundwater concentration predicted at each COC properties, and the distance from the expocompliance point was then compared with the corsure point (Figure 3). responding MCLs or risk-based action levels. The RBR SWMS_2D, a well-documented and benchmodel was run iteratively for all COCs to test the efmarked U.S. Department of Agriculture computer fect of additional soil removal and treatment until code (15), was used to simulate vadose zone transthe compliance point criteria were met. Soil report. It simultaneously solves the unsaturated flow moval was modeled according to a heirarchy of COC (Richard's) equation and the contaminant transconcentrations (from highest to lowest) and spatial port (convective dispersion) equation using the filocation, considering the amount of overburden renite element method. The unsaturated zone at the quired for removal and whether contamination was Marzone site was spatially discretized into 7.6 m x contiguous to other soil designated for removal. 7.6 m columns corresponding to the site RUs (Figure 3), with variable vertical depth because the Variograms were developed to represent the groundwater table was generally shallower at the spatial relationship between existing data locaFIGURE 2
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north end of the site. Individual columns were vertically discretized into 20 uniform segments. As shown schematically in Figure 3, the RBR code selects RUs for removal hierarchically, based on the relative contribution in each grid cell, by assessing the concentration of each compound. A steady-state solution for infiltrating water was obtained using a constant flux boundary condition and initial analyte concentrations determined for each segment from the krige. A time-dependent flux of solute migrating from the base of each column into the saturated zone was predicted that constituted the temporally varying water table boundary condition input to MT3D. First-order chemical degradation and linear partitioning between soil and water were assumed (6). The mass balance error for water and solutes in the unsaturated zone model was
