Abstract
Core Ideas Soil vapor extraction (SVE) wells are an effective interim remediation technique. Flow and transport modeling assists in evaluation of vapor plume behavior. Plume simulations assuming drum failure and SVE provide a framework for remediation planning. A small borehole subset could be monitored for detection of VOC releases due to drum failure. Soil vapor extraction (SVE) has been used at sites across the Department of Energy complex, including sites where legacy subsurface wastes represent a potential source of groundwater contamination. At Los Alamos National Laboratory (LANL), leakage from waste drums buried at an inactive chemical waste site has created a subsurface vapor plume of volatile organic compounds (VOCs). Soil vapor extraction operation in 2015 and rebound testing through 2017 were successful in reducing the plume's mass and mitigating VOC migration toward the water table. However, the possibility that waste drums could fail and release VOCs could pose a challenge in the future. To explore the impacts of drum failure, as well as the capabilities of SVE remediation, we simulated hypothetical contaminant release scenarios and subsequent SVE remediation. Three‐dimensional subsurface VOC behavior, including advection, diffusion, and plume interactions with topography, were simulated using the porous flow simulator Finite Element Heat and Mass Transfer. Simulations of future site conditions have allowed identification of “sentry” boreholes that can be monitored for early detection in case of drum failure. Sentry boreholes can also be used to set concentration thresholds above which SVE should be initiated. For the LANL site, simulations show that SVE can be started 3 yr following drum failure and remain a viable remediation tool. More broadly, the principles outlined in this work can be used to support remediation planning at other subsurface waste sites. Predictive models of future releases can be analyzed to set concentration threshold values, guide selection of sentry boreholes, and increase operational efficiency.
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