Literature DB >> 35240152

Degrading chlorinated aliphatics by reductive dechlorination of groundwater samples from the Santa Susana Field Laboratory.

Nalok Dutta1, Keith Thomsen2, Birgitte K Ahring3.   

Abstract

Microbial reductive dechlorination is one of the chosen methods for remediation of chlorinated compounds in anaerobic environments. In this study we examined the degradation of chlorinated aliphatics in groundwater samples from the Santa Susana Field Laboratory (SSFL) containing a concentration of 0.228 mM trichloroethylene (TCE) and 0.279 mM 1,2 dichloroethylene (DCE). We tested the influence of adding different carbon sources on the dechlorinating activity in batch cultures with and without dechlorinating bacteria. In-situ microcosms were established using SSFL groundwater supplemented with EVO (5%) (vol/vol) SRS emulsion and with or without species of Dehalocococcoides (DCB-1, DCB-2 or DCB-3). Emulsified vegetable oil (EVO) gave the highest dechlorinating activity with DCB-1 added compared to any other substrate addition tested. All three bacterial cultures tested had significant dechlorinating activities while the native populations in the SSFL groundwater samples only showed limited degradation of trichloroethylene into intermediates in the form of DCE, vinyl chloride and ethane. The conversion of chlorinated ethylenes (CEs) was optimal in the bioreactors amended with DCB-1 followed by DCB-2, and DCB-3 all supplemented with EVO. We further analyzed the TCE degradation first order kinetics in batch cultures and found that the culture with DCB-1 supplemented with EVO showed 43.59% and 51.38% increased degradation rate compared to the same condition with cultures of DCB-2 or DCB-3 added. The microcosm studies further showed that with DCB-1 and EVO, reductive dechlorination of TCE in the SSFL converted 90% of the input TCE to ethane with a degradation rate of 0.0039 mM/day. Published by Elsevier Ltd.

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Keywords:  Dehalogenating bacteria; First-order degradation kinetics; Groundwater bioremediation; Microcosms; Reductive dechlorination

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Year:  2022        PMID: 35240152     DOI: 10.1016/j.chemosphere.2022.134115

Source DB:  PubMed          Journal:  Chemosphere        ISSN: 0045-6535            Impact factor:   7.086


  1 in total

1.  Optimization of Dechlorination Experiment Design Using Lightweight Deep Learning Model.

Authors:  Jianghua Peng; Houzhang Tan
Journal:  Comput Intell Neurosci       Date:  2022-06-25
  1 in total

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