4.7 Article

Kinetic assessment of simultaneous removal of arsenite, chlorate and nitrate under autotrophic and mixotrophic conditions

期刊

SCIENCE OF THE TOTAL ENVIRONMENT
卷 628-629, 期 -, 页码 85-93

出版社

ELSEVIER
DOI: 10.1016/j.scitotenv.2018.02.034

关键词

Kinetic model; Autotrophic; Heterotrophic; Mixotrophic; HRT; COD

资金

  1. Recruitment Program of Global Experts
  2. Natural Science Foundation of China [51578391, 51608374]
  3. Foundation Research Program of Central University, China [22120170121]

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In this work, a kinetic model was proposed to evaluate the simultaneous removal of arsenite (As (III)), chlorate (ClO3-) and nitrate (NO3-) in a granule-based mixotrophic As (III) oxidizing bioreactor for the first time. The autotrophic kinetics related to growth-linked As (III) oxidation and ClO3- reduction by As (III) oxidizing bacteria (AsOB) were calibrated and validated based on experimental data from batch test and long-term reactor operation under autotrophic conditions. The heterotrophic kinetics related to nongrowth linked As (III) oxidation and ClO3- reduction by heterotrophic bacteria (HB) were evaluated based on the batch experimental data under heterotrophic conditions. The existing kinetics related to As (III) oxidation with NO3- as the electron acceptor together with heterotrophic denitrification were incorporated into the model framework to assess the bioreactor performance in treatment of the three co-occurring contaminants. The results revealed that under autotrophic conditions As (III) was completely oxidized by AsOB (over 99%), while ClO3- and NO3- were poorly removed. Under mixotrophic conditions, the simultaneous removal of the three contaminants was achieved with As (III) oxidized mostly by AsOB and ClO3- and NO3- removed mostly by HB. Both hydraulic retention time (HRT) and influent organic matter (COD) concentration significantly affected the removal efficiency. Above 90% of As (III), ClO3- and NO3- were removed in the mixotrophic bioreactor under optimal operational conditions of HRT and influent COD. (C) 2018 Elsevier B.V. All rights reserved.

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