The Department of Defense is currently responsible for the cleanup of groundwater contaminated with chlorinated solvents at thousands of sites nationwide. Much recent research has focused on technology development for both source and plume remediation (e.g., thermal methods, chemical oxidation, surfactant/cosolvent flooding, soil vapor extraction, air sparging, pump-and-treat, enhanced in situ biodegradation). Process and parameter uncertainty and the expensive cost of source and plume remediation efforts, however, have limited the ability to make effective decisions about DNAPL site remediation alternatives. For many sites, a robust, cost-effective remediation design requires some combination of source and plume remediation while considering the uncertainties that arise from hydrological and biogeochemical properties, from the site history and conditions, and from the effects of remediation.

The objective of this project was to develop a new probabilistic remediation modeling program, Probabilistic Remediation Evaluation Model for Chlorinated Solvents (PREMChlor), for simultaneously evaluating the effectiveness of source and plume remediation considering the uncertainties in all major parameters, thereby supporting the remediation selection process.

The Department of Defense is currently responsible for the cleanup of groundwater contaminated with chlorinated solvents at thousands of sites nationwide. Much recent research has focused on technology development for both source and plume remediation (e.g., thermal methods, chemical oxidation, surfactant/cosolvent flooding, soil vapor extraction, air sparging, pump-and-treat, enhanced in situ biodegradation). Process and parameter uncertainty and the expensive cost of source and plume remediation efforts, however, have limited the ability to make effective decisions about DNAPL site remediation alternatives. For many sites, a robust, cost-effective remediation design requires some combination of source and plume remediation while considering the uncertainties that arise from hydrological and biogeochemical properties, from the site history and conditions, and from the effects of remediation.

Model demonstration examples are used to illustrate the different probabilities of meeting a remediation goal for different combinations of source and plume remediation scenarios considering uncertainties in input parameters. PREMChlor was applied to a trichloroethene (TCE) plume in a shallow aquifer at a manufacturing plant in Kinston, North Carolina. The calibrated model, using a deterministic approach, closely matched the pre-remediation site condition. Probabilistic simulations predicted the effects of remediation and captured most uncertainties in the key parameters based on estimated PDFs. The PREMChlor model has also been used to conduct sensitivity analyses by assessing the influence or relative importance of each input parameter on plume behavior, in terms of contaminant mass concentration, for three different plume types. Results showed that the degree of influence of different input parameters on the contaminant mass concentration varies widely for different plume types.

PREMChlor gives users a single platform where cost, source treatment, plume management, monitored natural attenuation, and risk assessment can all be evaluated together and where uncertainty can be incorporated into the site decision-making process. It was developed using an earlier version of GoldSim, so it must be run with GoldSim Player version 9.60. This program is available free of charge from the GoldSim website. Other PREMChlor files are available from the principal investigators.