Mathematical modeling of simultaneous carbon-nitrogen-sulfur removal from industrial wastewater

Xu, Xi-Jun, Chen, Chuan, Wang, Ai-Jie, Ni, Bing-Jie, Guo, Wan-Qian, Yuan, Ye, Huang, Cong, Zhou, Xu, Wu, Dong-Hai, Lee, Duu-Jong and Ren, Nan-Qi (2017) Mathematical modeling of simultaneous carbon-nitrogen-sulfur removal from industrial wastewater. Journal of Hazardous Materials, 321 371-381. doi:10.1016/j.jhazmat.2016.08.074

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Author Xu, Xi-Jun
Chen, Chuan
Wang, Ai-Jie
Ni, Bing-Jie
Guo, Wan-Qian
Yuan, Ye
Huang, Cong
Zhou, Xu
Wu, Dong-Hai
Lee, Duu-Jong
Ren, Nan-Qi
Title Mathematical modeling of simultaneous carbon-nitrogen-sulfur removal from industrial wastewater
Journal name Journal of Hazardous Materials   Check publisher's open access policy
ISSN 1873-3336
0304-3894
Publication date 2017-01-05
Year available 2016
Sub-type Article (original research)
DOI 10.1016/j.jhazmat.2016.08.074
Open Access Status File (Author Post-print)
Volume 321
Start page 371
End page 381
Total pages 11
Place of publication Amsterdam, Netherlands
Publisher Elsevier BV
Language eng
Subject 2305 Environmental Engineering
2304 Environmental Chemistry
2311 Waste Management and Disposal
2310 Pollution
2307 Health, Toxicology and Mutagenesis
Abstract A mathematical model of carbon, nitrogen and sulfur removal (C-N-S) from industrial wastewater was constructed considering the interactions of sulfate-reducing bacteria (SRB), sulfide-oxidizing bacteria (SOB), nitrate-reducing bacteria (NRB), facultative bacteria (FB), and methane producing archaea (MPA). For the kinetic network, the bioconversion of C-N by heterotrophic denitrifiers (NO → NO → N), and that of C-S by SRB (SO → S) and SOB (S → S) was proposed and calibrated based on batch experimental data. The model closely predicted the profiles of nitrate, nitrite, sulfate, sulfide, lactate, acetate, methane and oxygen under both anaerobic and micro-aerobic conditions. The best-fit kinetic parameters had small 95% confidence regions with mean values approximately at the center. The model was further validated using independent data sets generated under different operating conditions. This work was the first successful mathematical modeling of simultaneous C-N-S removal from industrial wastewater and more importantly, the proposed model was proven feasible to simulate other relevant processes, such as sulfate-reducing, sulfide-oxidizing process (SR-SO) and denitrifying sulfide removal (DSR) process. The model developed is expected to enhance our ability to predict the treatment of carbon-nitrogen-sulfur contaminated industrial wastewater.
Formatted abstract
A mathematical model of carbon, nitrogen and sulfur removal (C-N-S) from industrial wastewater was constructed considering the interactions of sulfate-reducing bacteria (SRB), sulfide-oxidizing bacteria (SOB), nitrate-reducing bacteria (NRB), facultative bacteria (FB), and methane producing archaea (MPA). For the kinetic network, the bioconversion of C-N by heterotrophic denitrifiers (NO3− → NO2− → N2), and that of C-S by SRB (SO42 → S2) and SOB (S2− → S0) was proposed and calibrated based on batch experimental data. The model closely predicted the profiles of nitrate, nitrite, sulfate, sulfide, lactate, acetate, methane and oxygen under both anaerobic and micro-aerobic conditions. The best-fit kinetic parameters had small 95% confidence regions with mean values approximately at the center. The model was further validated using independent data sets generated under different operating conditions. This work was the first successful mathematical modeling of simultaneous C-N-S removal from industrial wastewater and more importantly, the proposed model was proven feasible to simulate other relevant processes, such as sulfate-reducing, sulfide-oxidizing process (SR-SO) and denitrifying sulfide removal (DSR) process. The model developed is expected to enhance our ability to predict the treatment of carbon-nitrogen-sulfur contaminated industrial wastewater.
Keyword Carbon
Industrial wastewater treatment
Mathematical modeling
Nitrogen
Sulfur
Q-Index Code C1
Q-Index Status Provisional Code
Grant ID 51308147
51576057
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: HERDC Pre-Audit
Advanced Water Management Centre Publications
 
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