Literature DB >> 21543102

Effects of solids retention time on the performance of bioreactors bioaugmented with a 17β-estradiol-utilizing bacterium, Sphingomonas strain KC8.

Hyungkeun Roh1, Kung-Hui Chu.   

Abstract

This study investigated the performance of lab-scale sequencing batch reactors (SBRs) that were inoculated with nitrifying activated sludge and bioaugmented with a Sphingomonas strain KC8 (a 17β-estradiol-degrading bacterium). The bioaugmented SBRs were supplied with synthetic wastewater (average initial total organic carbon (TOC)=175 mgL(-1) and average initial ammonia-N=25 mgL(-1)) and daily dose of 17β-estradiol (1mgL(-1)) and operated under three solid retention times (SRTs) of 5, 10, and 20 d. After three times periods of the operating SRTs, the overall removal of TOC (>87%) and ammonia (>91%) was similar in all the SBRs. Higher 17β-estradiol removals (>99%) were observed for the SBRs. Neither estrogens nor estrogenic activity was detected in the treated water, except some samples from the SBR operating under 5d of SRT. The ratios of known estrogen degraders (Sphingomonas strain KC8 and ammonia-oxidizing bacteria) and amoA gene to the total bacterial population decreased as SRT increased, suggesting the presence of unknown estrogen-degraders in SBRs operating at SRT=10 and 20 d. Real-time-terminal-restriction fragment length polymorphism analysis showed that the evenness of microbial community structures was not affected by the SRT; while, the diversity indices suggest that longer SRTs might lead to more diverse microbial community structure. Overall, the results suggested that bioaugmented bioreactors operating at long SRTs (10 and 20 d) were effective in removing 17β-estradiol to the non-estrogenic treatment endpoint.
Copyright © 2011 Elsevier Ltd. All rights reserved.

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Year:  2011        PMID: 21543102     DOI: 10.1016/j.chemosphere.2011.04.029

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


  2 in total

1.  Bioaugmentation Mitigates the Impact of Estrogen on Coliform-Grazing Protozoa in Slow Sand Filters.

Authors:  Sarah-Jane Haig; Caroline Gauchotte-Lindsay; Gavin Collins; Christopher Quince
Journal:  Environ Sci Technol       Date:  2016-03-03       Impact factor: 9.028

2.  Machine Learning Approach Reveals the Assembly of Activated Sludge Microbiome with Different Carbon Sources during Microcosm Startup.

Authors:  Youngjun Kim; Sangeun Park; Seungdae Oh
Journal:  Microorganisms       Date:  2021-06-25
  2 in total

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