Reactive transport modeling to interpret patterns of biomarkers and assess chlorinated ethene biodegradation in aquifers

The biomarkers linked to the biodegradation of chlorinated ethenes (CEs), such as RDase functional gene DNA, mRNA, and enzymes, are increasingly being monitored in contaminant plumes to monitor reductive dechlorination (RD). They are currently used to assess the biodegradation potential and possibly infer RD rates. However, aquifers are hydrodynamically and biogeochemically heterogeneous environments, and local conditions may affect the efficiency of organohalide-respiring bacteria in biodegrading CEs. Identifying the possible causes shaping the observed spatiotemporal patterns still remains a challenge. Chemicals and biomarkers have extensively been monitored in a 1500-m long, 70-m deep CE plume at the Grindsted contaminated site (Denmark) for more than a decade. To assist the interpretation of the monitored patterns, we implemented new enzyme-based kinetics linking the reductive dechlorination of cis-1,2-dichloroethene (cis-DCE) to vinyl chloride (VC) and ethene and the vcrA and bvcA gene expression in Dehalococcoides. We integrated these kinetics in a 1D reactive transport model simulating the Grindsted plume. It was possible to test hypotheses proposed to interpret the uneven distribution of biomarkers causing the non-homogeneous degradation along the plume: (1) variable flow rate and (2) heterogeneous distribution of electron donor sources (i.e., sedimentary organic carbon; SOC) within the plume. The modeling results suggest that Dehalococcoides are more active in terms of RDase gene expression and growth in SOC-rich portions of the aquifer. In those areas, the dechlorination of both CEs is more intense. Under high flow rate conditions, the biodegradation efficiency decreases because of the shorter residence time. This modeling approach provides more thorough mechanistic interpretations of observed spatiotemporal chemical/biomarker patterns in CE plumes and more reliable RD rate estimates, to support the planning of future monitoring and remediation strategies.