Mechanistic and quantitative profiling of electro-Fenton process for wastewater treatment. (15th May 2023)

• Record Type: Journal Article
• Authors: Wang, Anliu; Jiang, Ying; Yan, Yiqi; Bu, Lingjun; Wei, Zongsu; Spinney, Richard; Dionysiou, Dionysios D.; Xiao, Ruiyang
• Is Part Of: Water research. Volume 235(2023)
• Publication Date: 2023-05-15
• Subjects: Advanced oxidation processes -- Electro-Fenton -- Micropollutant -- Profiling -- Degradation kinetics; Water -- Pollution -- Research -- Periodicals; 363.7394
• DOI: 10.1016/j.watres.2023.119838
• Languages: English
• ISSNs: 0043-1354

Abstract

Highlight: Quantitative profiling of electron-Fenton treatment process was performed. Contribution of each subprocess in electro-Fenton process was compared and profiled. Radical oxidation accounts for the majority of the removal. Our methodology could boost exploration of subprocesses in other Fenton-like systems. Abstract: Electro-Fenton (EF) process represents an energy-efficient and scalable advanced oxidation technology (AOT) for micropollutants removal in wastewaters. However, mechanistic profiling and quantitation of contribution of each subprocess ( i.e., adsorption at electrode, coagulation, radical oxidation, electrode oxidation/reduction, and H2 O2 oxidation) to the overall degradation are substantially unclear, resulting in difficulty in tunability and optimization for different treatment scenarios. In this study, we investigated degradation kinetics of a target micropollutant in an EF system. The contribution of all possible subprocesses was elucidated by comparing the observed degradation rate in the EF system with the sum of the kinetics in each subprocess. The results indicated that the overall degradation can be attributed to the synergistic action of the above-mentioned subprocesses. The radical oxidation accounts for 87% elimination, followed by electrode reoxidation/reduction of 7.7%. These results not only advance the fundamental understanding of synergistic effect in EF system, but also open new possibilities to optimize these techniques for better scalability. In addition, the methodology in this study could potentially boost the in-depth exploration of subprocess contribution in other Fenton-like systems. Graphical abstract: Image, graphical abstract