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Can I read Sulphur-based autotrophic denitrification of wastewater obtained following graphite production: Long-term performance, microbial communities involved, and functional gene analysis on EtoBox?

Sulphur-based autotrophic denitrification of wastewater obtained following graphite production: Long-term performance, microbial communities involved, and functional gene analysis by Xiaochen Xu; Rao Zhang; Hongbin Jiang; Fenglin Yang is a Engineering article available to read on EtoBox.

What is Sulphur-based autotrophic denitrification of wastewater obtained following graphite production: Long-term performance, microbial communities involved, and functional gene analysis about?

Sulphur-based autotrophic denitrification is an energy-efficient NO-N removal process; it does not require carbon and may potentially replace traditional denitrification processes. This process was used to treat graphite production-derived wastewater and achieved almost complete removal of NO-N (concentration in effluent: 5.2 mg/L; concentration in influent: 606 mg/L) at a salinity of 15 g/L with a 30 h hydraulic retention time. A unique microbial community was established, in which the abundance of Thiobacillus increased with the increase of the NO-N concentration and salinity. Metagenomic analysis revealed that the denitrification metabolic pathway in the bioreactor was active. It also revealed the increased activation of nhaH, a gene encoding Na/H antiporters; proA, proB, and proC, genes encoding proline; and Trk and Kdp systems during the treatment of graphite production-derived wastewater to maintain cell function, providing valuable information about utilizing the sulphur-based autotrophic denitrification process to treat graphite production-derived wastewater.

Who reads Sulphur-based autotrophic denitrification of wastewater obtained following graphite production: Long-term performance, microbial communities involved, and functional gene analysis?

It is typically read by researchers, students, and practitioners in Engineering.

Author
Xiaochen Xu; Rao Zhang; Hongbin Jiang; Fenglin Yang
Publisher
Elsevier Science; Elsevier ; Elsevier BV (ISSN 0960-8524)
Published
2020
Language
EN
Field
Engineering (Physical Sciences)

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