Abstract

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.

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