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A biofilm model for assessing perchlorate reduction in a methane-based membrane biofilm reactor.

Authors :
Sun, Jing
Dai, Xiaohu
Peng, Lai
Liu, Yiwen
Wang, Qilin
Ni, Bing-Jie
Source :
Chemical Engineering Journal. Nov2017, Vol. 327, p555-563. 9p.
Publication Year :
2017

Abstract

Perchlorate (ClO 4 − ) is recognized as an important contaminant in surface water and groundwater, which would pose health risks at very low concentrations. A methane-based membrane biofilm reactor (MBfR) has been successfully demonstrated for perchlorate reduction, which provided an alternative solution for perchlorate remediation with low cost. In this work, a multispecies biofilm model was developed to evaluate perchlorate reduction in the methane-based MBfR under different operational conditions. The model was calibrated and validated using the experimental data from the long-term operation of the MBfR at seven distinct stages. The results suggested that the developed model could satisfactorily describe perchlorate reduction and denitrification performances in the MBfR (R 2 > 0.9). The modeling results provided insight into the microbial community distribution in the biofilm, with aerobic methanotrophs and perchlorate reduction bacteria being mainly located at the membrane side (∼60%) and heterotrophic bacteria being situated near the liquid side (∼50%). The model simulations indicated that over 80% of perchlorate removal efficiency could be achieved through controlling the optimal combinations of methane pressure (P CH4 ) and perchlorate loading (L ClO4 ) (e.g., applying a P CH4 of 30 kPa at a L ClO4 of 0.08 g Cl/m 2 /d). In addition, the perchlorate reduction would be inhibited by the presence of nitrate and nitrite in the MBfR, which should be appropriately controlled during the future practical application of the promising process. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13858947
Volume :
327
Database :
Academic Search Index
Journal :
Chemical Engineering Journal
Publication Type :
Academic Journal
Accession number :
124934131
Full Text :
https://doi.org/10.1016/j.cej.2017.06.136