Application of mathematical modeling and electrochemical iron dosing strategies to improve the treatment performance of the electro-Fenton process

Application of mathematical modeling and electrochemical iron dosing strategies to improve the... Electro-Fenton technology is an environmentally sustainable advanced oxidation process (AOP) that has shown huge promise and has been extensively studied for the degradation of recalcitrant organics in water. Existing studies on the application of electro-Fenton process for wastewater treatment, however, have not systematically presented approaches to regulate the concentration of dissolved iron in Fenton systems and excess iron usually results in unwanted scavenging reactions, reduced pollutant degradation efficiencies, high sludge production and increased material/operating costs. In this study, an electrochemical iron dosing model was developed for electro-Fenton applications. The generated model resulted in residuals not exceeding 0.10 mM Fe2+ and was able to successfully predict total iron concentration with fluctuations not exceeding 0.15 mM Fe2+. Single-dose and continuous dosing methods were also compared in terms of methylene blue dye degradation, hydrogen peroxide (H2O2) consumption, and chemical oxygen demand (COD) and total organic carbon (TOC) reduction. Single dosing method resulted to pollutant degradation rate that is nine (9) times faster than the rate obtained for continuous dosing of iron during the first 30 min of the reaction. In contrast, continuous dosing outperformed single-dosing mode after 60 min of reaction time in terms of H2O2 consumption and both TOC and COD removal. Furthermore, continuous dosing mode produced less phenolic intermediates compared to single-dosing mode. The modeling and optimization of the dosing process can lead to the significant lowering of iron species in the treated effluent and more importantly reduce the overall cost of the treatment operation. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Cleaner Production Elsevier

Application of mathematical modeling and electrochemical iron dosing strategies to improve the treatment performance of the electro-Fenton process

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Publisher
Elsevier
Copyright
Copyright © 2018 Elsevier Ltd
ISSN
0959-6526
D.O.I.
10.1016/j.jclepro.2018.01.147
Publisher site
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Abstract

Electro-Fenton technology is an environmentally sustainable advanced oxidation process (AOP) that has shown huge promise and has been extensively studied for the degradation of recalcitrant organics in water. Existing studies on the application of electro-Fenton process for wastewater treatment, however, have not systematically presented approaches to regulate the concentration of dissolved iron in Fenton systems and excess iron usually results in unwanted scavenging reactions, reduced pollutant degradation efficiencies, high sludge production and increased material/operating costs. In this study, an electrochemical iron dosing model was developed for electro-Fenton applications. The generated model resulted in residuals not exceeding 0.10 mM Fe2+ and was able to successfully predict total iron concentration with fluctuations not exceeding 0.15 mM Fe2+. Single-dose and continuous dosing methods were also compared in terms of methylene blue dye degradation, hydrogen peroxide (H2O2) consumption, and chemical oxygen demand (COD) and total organic carbon (TOC) reduction. Single dosing method resulted to pollutant degradation rate that is nine (9) times faster than the rate obtained for continuous dosing of iron during the first 30 min of the reaction. In contrast, continuous dosing outperformed single-dosing mode after 60 min of reaction time in terms of H2O2 consumption and both TOC and COD removal. Furthermore, continuous dosing mode produced less phenolic intermediates compared to single-dosing mode. The modeling and optimization of the dosing process can lead to the significant lowering of iron species in the treated effluent and more importantly reduce the overall cost of the treatment operation.

Journal

Journal of Cleaner ProductionElsevier

Published: Apr 20, 2018

References

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