Exploration of processes governing microbial reductive dechlorination in a heterogeneous aquifer flow cell

Although microbial reductive dechlorination (MRD) has proven to be an effective approach for in situ treatment of chlorinated ethenes, field implementation of this technology is complicated by many factors, including subsurface heterogeneity, electron donor availability, and distribution of microbial populations. This work presents a coupled experimental and mathematical modeling study designed to explore the influence of heterogeneity on MRD and to assess the suitability of microcosm-derived rate parameters for modeling complex heterogeneous systems. A Monod-based model is applied to simulate a bioremediation experiment conducted in a laboratory-scale aquifer cell packed with aquifer material from the Commerce Street Superfund site in Williston, VT. Results reveal that (uncalibrated) model application of microcosm-derived dechlorination and microbial growth rates for transformation of trichloroethene (TCE), cis-1,2-dichloroethene (cis-DCE), and vinyl chloride (VC) reproduced observed aquifer cell concentration levels and trends. Mean relative errors between predicted and measured effluent concentrations were quantified as 6.7%, 27.0%, 41.5%, 32.0% and 21.6% over time for TCE, cis-DCE, VC, ethene and total volatile fatty acids (fermentable electron donor substrate and carbon source), respectively. The time-averaged extent of MRD (i.e., ethene formation) was well-predicted (4% underprediction), with modeled MRD exhibiting increased deviation from measured values under electron donor limiting conditions (maximum discrepancy of 14%). In contrast, simulations employing a homogeneous (uniform flow) domain resulted in underprediction of MRD extent by an average of 13%, with a maximum discrepancy of 45%. Model sensitivity analysis suggested that trace amounts of natural dissolved organic carbon served as an important fermentable substrate, providing up to 69% of the reducing equivalents consumed for MRD under donor-limiting conditions. Aquifer cell port concentration data and model simulations revealed that ethene formation varied spatially within the domain and was associated with regions of longer residence times. These results demonstrate the strong influence of subsurface heterogeneity on the accuracy of MRD predictions, and highlight the importance of subsurface characterization and the incorporation of flow field uncertainty in model applications for successful design and assessment of in situ bioremediation.