Bio-electro-Fenton systems in wastewater treatment: Research progress and prospects

被引:1
作者
Zhang, Peijian [1 ,2 ,3 ]
Zhang, Sheng [3 ]
Xu, Min [1 ,2 ]
Jiang, Shiqi [1 ,2 ]
Ou, Xiyan [1 ,2 ]
Wang, Chenjie [1 ,2 ,3 ]
Yu, Yin [1 ,2 ]
Wu, Changyong [1 ,2 ]
机构
[1] Chinese Res Inst Environm Sci, State Key Lab Environm Criteria & Risk Assessment, Beijing, Peoples R China
[2] Chinese Res Inst Environm Sci, Res Ctr Environm Pollut Control Engn Technol, Beijing, Peoples R China
[3] Hebei Univ Engn, Sch Energy & Environm Engn, Handan, Peoples R China
关键词
Bio-electro-Fenton; System configuration; Optimizing process control; Recalcitrant organics removal; Wastewater treatment; MICROBIAL FUEL-CELLS; HYDROGEN-PEROXIDE; ORGANIC POLLUTANTS; BIOELECTRO-FENTON; BIOFUEL CELLS; GRAPHITE FELT; COD REMOVAL; DEGRADATION; CATHODE; ANODE;
D O I
10.1016/j.jelechem.2025.118959
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Fenton process is a highly promising technology for wastewater treatment, but its operational potential is limited by pH sensitivity and excessive sludge production. The bio-electro-Fenton (BEF) system combines the costeffectiveness of biotechnology with the sludge reduction effects of electro-Fenton, offering greater economic benefits and treatment potential compared to other enhanced Fenton processes. However, challenges persist in terms of stringent pH control, low electricity production efficiency, and limited reaction efficiency when applied at a large scale. Therefore, this paper introduces the BEF mechanism, examines key factors influencing its efficiency in terms of biological and catalytic performance, and highlights recent innovations in electrode materials, catalysts, and reactor design. The discussion focuses on the challenges and limitations faced by the BEF system in catalysts and reactor configurations for large-scale industrial applications. Strategies are proposed to overcome key technical constraints and enhance the cost-effectiveness of the process. It is recommended to integrate BEF with biological methods, develop highly efficient catalysts, and leverage modeling technologies such as Matlab/ Simulink and artificial neural networks to accelerate the full-scale application of BEF technology.
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页数:15
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