Methane Production Mechanism and Control Strategies for Sewers: A Critical Review

被引:2
作者
Hou, Feng [1 ]
Liu, Shuai [2 ]
Yin, Wan-Xin [3 ]
Gan, Li-Li [1 ]
Pang, Hong-Tao [1 ]
Lv, Jia-Qiang [2 ]
Liu, Ying [1 ]
Wang, Ai-Jie [2 ]
Wang, Hong-Cheng [2 ]
机构
[1] Xinkai Water Environm Investment Co Ltd, Beijing 101100, Peoples R China
[2] Harbin Inst Technol Shenzhen, Sch Civil & Environm Engn, State Key Lab Urban Water Resource & Environm, Shenzhen 518055, Peoples R China
[3] Liaoning Univ, Coll Environm, Shenyang 110036, Peoples R China
基金
国家重点研发计划;
关键词
sewer; methane production and control; sewer management; chemical dosing; model evaluation; FREE NITROUS-ACID; SULFATE-REDUCING BACTERIA; HYDROGEN-SULFIDE EMISSION; WASTE-WATER; DISSOLVED METHANE; LABORATORY ASSESSMENT; METHANOGENIC ACTIVITY; OXYGEN INJECTION; MODEL CONCEPT; INHIBITION;
D O I
10.3390/w16243618
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Methane (CH4) emissions from urban sewer systems represent a significant contributor to greenhouse gases, driven by anaerobic decomposition processes. This review elucidates the mechanisms underlying CH4 production in sewers, which are influenced by environmental factors such as the COD/SO42- ratio, temperature, dissolved oxygen, pH, flow rate, and hydraulic retention time. We critically evaluated the effectiveness of empirical, mechanistic, and machine learning (ML) models in predicting CH4 emissions, highlighting the limitations of each. This review further examines control strategies, including oxygen injection, iron salt dosing, and nitrate application, emphasizing the importance of balancing CH4 reduction with the operational efficiency of wastewater treatment plants (WWTPs). An integrated approach combining mechanistic and data-driven models is advocated to enhance prediction accuracy and optimize CH4 management across urban sewer systems.
引用
收藏
页数:18
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