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Model assessment of reductive dechlorination as a remediation technology for contaminant sources in fractured clay: Modeling tool Appendix D Assessment of the different processes
D.1 Limiting substrate conditionsLimiting substrate conditions are of importance, as they decrease the degradation rate and slow down the dechlorination process. Substrate limiting conditions are particularly important when the chosen electron donor releases hydrogen slowly, as it is the case for propionate, for example. On the contrary, lactate is known to ferment relatively fast under anaerobic conditions [He et al., 2002]. Taking into account substrate limitation requires that the concentration of electron donor (i.e hydrogen in the case of anaerobic dechlorination) is known (see Section B.1.3). As explained previously, hydrogen is usually not injected directly at the field site, but is produced by fermentation of substrates of diverse types (lactate, propionate, ethanol…). Hence, in order to consider the substrate limiting conditions, the fermentation step must also be implemented in the model. Furthermore, hydrogen is consumed by different bacteria, besides the dechlorinating biomass, which usually includes sulfate/iron reducers, methanogens and acetogens (see Figure B.1). Finally, thermodynamics are also expected to play an important role in the concentration of hydrogen, notably during the fermentation step, and would need to be included in such a model. The implementation of these processes in the model entails an increase in the amount of parameters. As no prior information is usually available on the different bacteria populations present at a site, this also increases the uncertainty of the model. If the thermodynamics are disregarded then the model includes 16 variables (among them 7 bacteria populations) and 50 parameters, on most of which no prior information was available. Since the objective of this study and the further use of the model, it was decided to disregard the limiting substrate conditions in the degradation model. D.2 Competitive inhibition between chlorinated ethenesMost of the recent studies consider competitive inhibition between chlorinated ethenes, as their inclusion considerably improves the model accuracy. Hence it seems important to introduce this phenomenon in the model. Furthermore, the inhibition constants are assessed in several studies, so it is possible to find typical ranges for the kinetic parameters associated with this process. D.3 Haldane inhibitionHaldane inhibition in TCE dechlorination has been reported in few studies and is a relevant process only for high concentrations (around 4000 µM [Yu and Semprini, 2004]). The concentrations from experimental data are very low compared to this value (maximum 50 µM). Hence Haldane inhibition is not relevant to simulate sequential degradation during the microcosm experiments. However the concentration at contaminated sites can reach very high values and Haldane inhibition may become an important process in some cases. But in the absence of compatible microcosm experimental data to calibrate the Haldane constants, this process will be disregarded in this study. D.4 Biomass growth/decayBiomass is reported to grow by several orders of magnitude during TCE dechlorination experiments in several studies. As such a growth influences greatly the degradation rates, this process has to be included in the model. Modeling of biomass growth/decay can be simply implemented with Monod kinetics. Furthermore, the presence of two bacterial groups, as reported in other studies, seems to be an important aspect regarding the experimental data. Hence, one group will be assumed to grow only on TCE degradation, while a second one grows via cis-DCE and VC degradation.
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