Literature DB >> 16255035

Nitrate promotes biological oxidation of sulfide in wastewaters: experiment at plant-scale.

Juan García de Lomas1, Alfonso Corzo, Juan M Gonzalez, Jose A Andrades, Emilio Iglesias, María José Montero.   

Abstract

Biogenic production of sulfide in wastewater treatment plants involves odors, toxicity and corrosion problems. The production of sulfide is a consequence of bacterial activity, mainly sulfate-reducing bacteria (SRB). To prevent this production, the efficiency of nitrate addition to wastewater was tested at plant-scale by dosing concentrated calcium nitrate (Nutriox) in the works inlet. Nutriox dosing resulted in a sharp decrease of sulfide, both in the air and in the bulk water, reaching maximum decreases of 98.7% and 94.7%, respectively. Quantitative molecular microbiology techniques indicated that the involved mechanism is the development of the nitrate-reducing, sulfide-oxidizing bacterium Thiomicrospira denitrificans instead of the direct inhibition of the SRB community. Denitrification rate in primary sedimentation tanks was enhanced by nitrate, being this almost completely consumed. No significant increase of inorganic nitrogen was found in the discharged effluent, thus reducing potential environmental hazards to receiving waters. This study demonstrates the effectiveness of nitrate addition in controlling sulfide generation at plant-scale, provides the mechanism and supports the environmental adequacy of this strategy.

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Year:  2006        PMID: 16255035     DOI: 10.1002/bit.20768

Source DB:  PubMed          Journal:  Biotechnol Bioeng        ISSN: 0006-3592            Impact factor:   4.530


  9 in total

1.  Microbial community fingerprinting by differential display-denaturing gradient gel electrophoresis.

Authors:  M C Portillo; D Villahermosa; A Corzo; J M Gonzalez
Journal:  Appl Environ Microbiol       Date:  2010-11-12       Impact factor: 4.792

2.  Prediction and quantifying parameter importance in simultaneous anaerobic sulfide and nitrate removal process using artificial neural network.

Authors:  Jing Cai; Ping Zheng; Mahmood Qaisar; Tao Luo
Journal:  Environ Sci Pollut Res Int       Date:  2014-12-20       Impact factor: 4.223

3.  Genus-specific and phase-dependent effects of nitrate on a sulfate-reducing bacterial community as revealed by dsrB-based DGGE analyses of wastewater reactors.

Authors:  Kouhei Mizuno; Yui Morishita; Akiko Ando; Naofumi Tsuchiya; Mai Hirata; Kenji Tanaka
Journal:  World J Microbiol Biotechnol       Date:  2011-08-17       Impact factor: 3.312

4.  Kinetic limitations during the simultaneous removal of p-cresol and sulfide in a denitrifying process.

Authors:  Francisco J Cervantes; Edna R Meza-Escalante; Anne-Claire Texier; Jorge Gómez
Journal:  J Ind Microbiol Biotechnol       Date:  2009-08-12       Impact factor: 3.346

5.  Characterization of a newly isolated strain Pseudomonas sp. C27 for sulfide oxidation: Reaction kinetics and stoichiometry.

Authors:  Xi-Jun Xu; Chuan Chen; Hong-Liang Guo; Ai-Jie Wang; Nan-Qi Ren; Duu-Jong Lee
Journal:  Sci Rep       Date:  2016-02-11       Impact factor: 4.379

6.  Kinetics of Indigenous Nitrate Reducing Sulfide Oxidizing Activity in Microaerophilic Wastewater Biofilms.

Authors:  Desirée Villahermosa; Alfonso Corzo; Emilio Garcia-Robledo; Juan M González; Sokratis Papaspyrou
Journal:  PLoS One       Date:  2016-02-12       Impact factor: 3.240

7.  Effects of electron acceptors on sulphate reduction activity in activated sludge processes.

Authors:  Francisco Rubio-Rincón; Carlos Lopez-Vazquez; Laurens Welles; Tessa van den Brand; Ben Abbas; Mark van Loosdrecht; Damir Brdjanovic
Journal:  Appl Microbiol Biotechnol       Date:  2017-05-25       Impact factor: 4.813

8.  Autohydrogenotrophic Denitrification Using the Membrane Biofilm Reactor for Removing Nitrate from High Sulfate Concentration of Water.

Authors:  Yanhao Zhang; Haohan Zhang; Zhibin Zhang; Yuchen Wang; Taha Marhaba; Jixiang Li; Cuizhen Sun; Wen Zhang
Journal:  Archaea       Date:  2018-08-05       Impact factor: 3.273

9.  Machine Learning Predicts Biogeochemistry from Microbial Community Structure in a Complex Model System.

Authors:  Avishek Dutta; Thomas Goldman; Jeffrey Keating; Ellen Burke; Nicole Williamson; Reinhard Dirmeier; Jeff S Bowman
Journal:  Microbiol Spectr       Date:  2022-02-09
  9 in total

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