Integrating Enzyme-Based Kinetics in Reactive Transport Models to Simulate Spatiotemporal Dynamics of Biomarkers during Chlorinated Ethene Degradation

Biomarkers such as functional gene mRNA (transcripts) and proteins (enzymes) provide direct proof of metabolic regulation during the reductive dechlorination (RD) of chlorinated ethenes (CEs). Yet, current models to simulate their spatiotemporal variability are not flexible enough to mimic the homologous behavior of <i>RDase</i> functional genes. To this end, we developed new enzyme-based kinetics to model the concentrations of CEs together with the transcript and enzyme levels during RD. First, the model was calibrated to existing microcosm data on RD of cis-DCE. The model mirrored the <i>tceA</i> and <i>vcrA</i> gene expression and the production of their enzymes in <i>Dehalococcoides</i> spp. Considering <i>tceA</i> and <i>vcrA</i> as homologous instead of nonhomologous improved fitting of the mRNA time series. Second, CEs and biomarker patterns were explored as a proof of concept under groundwater flow conditions, considering degraders occurring in immobile and mobile states. Under both microcosm and flow conditions, biomarker-rate relationships were nonlinear hysteretic because <i>tceA</i> and <i>vcrA</i> acted as homologous genes. The mobile biomarkers additionally undergo advective-dispersive transport, which increases the nonlinearity and makes the observed patterns even more challenging to interpret. The model offers a thorough mechanistic description of RD while also allowing simulation of spatiotemporal dynamic patterns of various key biomarkers in aquifers.