Date of Award

12-2022

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Environmental Engineering and Earth Science

Committee Chair/Advisor

David L. Freedman

Committee Member

Kevin T. Finneran

Committee Member

Lawrence C. Murdoch

Committee Member

Ronald W. Falta

Committee Member

Rong Yu

Abstract

Trichloroethene (TCE) is one of the most commonly found hazardous compounds at Superfund sites, especially in groundwater. Its volatility and toxicity pose a threat to drinking water safety and human health. In the past decades, research on the fate of TCE in the environment has shifted to contamination of low-permeability formations, for example fractured bedrock aquifers. TCE back-diffusion from low permeability zones and management of persistent TCE groundwater plumes caused by this long-term source zone pose major challenges for remediation.

Monitored natural attenuation (MNA) is a cost-effective remediation strategy that has gradually gained acceptance by regulators. Compared to extensive active remediation of persistent TCE plumes, MNA is more attractive for its cost-effectiveness. However, acceptance of MNA as a remediation strategy depends on adequate documentation of in situ TCE degradation at meaningful rates. Collecting lines of evidence in support of TCE natural degradation is an essential component of MNA.

In this study, two lines of evidence were collected for three Department of Defense sites overlain with fractured bedrock that are experiencing TCE back-diffusion. The first type of evidence involved monitoring groundwater for dissolved gas products associated with abiotic degradation (i.e., acetylene, ethene, and ethane) using a novel passive vapor diffusion (PVD) sampler. The other line of evidence was based on the use of intact rock core microcosms to estimate TCE degradation rate constants. This is the first study to employ the use of 14C-labeled TCE in intact rock core microcosms. Estimating the TCE degradation rate constants was accomplished with numerical modeling.

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