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.

尽管微生物还原脱氯（MRD）已被证明是一种原位有效的方法在处理氯化乙烯时，该技术的现场实施受到许多因素的影响，其中包括地下异质性，电子供体的可利用性以及微生物种群的分布。这项工作提出了一个耦合的实验和数学建模研究，旨在探索异质性对MRD的影响，并评估微观尺度的速率参数对复杂异质系统建模的适用性。应用基于Monod的模型来模拟在实验室规模的含水层单元中进行的生物修复实验，该含水层单元中装有来自佛蒙特州Williston的Commerce Street Superfund网站的含水层材料。结果表明，（未经校准的）模型应用了微生物衍生的脱氯和微生物生长速率转化三氯乙烯（TCE），顺式-1,2-二氯乙烯（顺式-DCE）和氯乙烯（VC）再现了观察到的含水层细胞浓度水平和趋势。对于TCE，顺式，随着时间的推移，预测和测量的污水浓度之间的平均相对误差被量化为6.7％，27.0％，41.5％，32.0％和21.6％。-DCE，VC，乙烯和总挥发性脂肪酸（可发酵的电子供体底物和碳源）。MRD的时间平均范围（即，乙烯形成）得到了很好的预测（4％的预测不足），而模拟的MRD在电子给体极限条件下显示出与测量值的偏差增加（最大差异为14％）。相比之下，采用均匀（均匀流）域的模拟导致MRD范围的平均预测为低13％，最大差异为45％。模型敏感性分析表明，痕量的天然溶解有机碳可作为重要的可发酵底物，在供体限制性条件下提供了多达69％的MRD还原当量。含水层细胞端口浓度数据和模型模拟表明，乙烯的形成在域内在空间上变化，并且与更长停留时间的区域有关。这些结果证明了地下非均质性对MRD预测准确性的强烈影响，并强调了地下表征的重要性以及在模型应用中纳入流场不确定性对于成功设计和评估MRD的重要性。原位生物修复。