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Modeling Dehalococcoides sp. Augmented Bioremediation in a Single Fracture System
Author(s) -
Torlapati Jagadish,
Clement T. Prabhakar,
Schaefer Charles E.,
Lee KangKun
Publication year - 2012
Publication title -
groundwater monitoring and remediation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.677
H-Index - 47
eISSN - 1745-6592
pISSN - 1069-3629
DOI - 10.1111/j.1745-6592.2011.01392.x
Subject(s) - bioremediation , environmental remediation , bioaugmentation , aquifer , dehalococcoides , yield (engineering) , sensitivity (control systems) , reductive dechlorination , groundwater , biodegradation , environmental science , soil science , bacterial growth , chlorinated solvents , benchmark (surveying) , biological system , contamination , biochemical engineering , environmental chemistry , chemistry , materials science , geotechnical engineering , geology , ecology , engineering , electronic engineering , biology , bacteria , paleontology , polymer , vinyl chloride , metallurgy , organic chemistry , copolymer , geodesy
A numerical reactive transport model was developed to simulate the bioremediation processes in a perchloroethene (PCE) contaminated single fracture system augmented with Dehalococcoides sp. (DHC). The model describes multispecies bioreactive transport processes that include bacterial growth and detachment dynamics, biodegradation of chlorinated species, competitive inhibition of various reactive species, and the loss of daughter products because of back‐partitioning effects. Two sets of experimental data, available in the study by Schaefer et al. (2010b), were used to calibrate and test the model. The model was able to simulate both datasets. The simulation results indicated that the yield coefficient and the DHC maximum utilization rate coefficient were the two important process parameters. A detailed sensitivity study was completed to quantify the sensitivity of the model to variations in these two parameter values. The results show that an increase in yield coefficient increases bacterial growth and thus expedites the dechlorination process, whereas an increase in maximum utilization rate coefficient greatly increased dechlorination rates. The proposed model provides a mathematical framework for simulating remediation systems that employ DHC bioaugmentation for restoring chlorinated‐solvent contaminated groundwater aquifers.