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Urban biowaste integrated management based on synergy mechanism and multi-objective optimization: A case study in
Fan Fei1, Zongguo Wen2, Sang Ri3
1College of Public Administration, Huazhong University of Science and Technology, Wuhan 430074, China; State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing 10084, China.
Abstract:
Urban biowaste is the organic fraction of municipal solid waste (MSW) and is a predominant waste type in low- and middle-income countries. Urban biowaste is the main cause of pollution and produces odor and leachate, and it could also serve as a source of energy and nutrient elements. Therefore, urban biowaste management should actuate minimal pollution, maximized resource utilization, and economic feasibility, which makes it a multi-objective problem. With increasing requirements for the classified management of MSW, the complexity of urban biowaste management is increasing, and it is necessary to consider the synergy mechanism between different wastes and technologies from a systematic perspective. We constructed urban biowaste management integrated model (UBMIM) to support urban biowaste management system design and policy formation. Firstly, a dynamic quantitative simulation of the numerical matching and influence conduction was conducted based on technology system synergy mechanism. Secondly, a multi-objective evaluation of the technology system was conducted based on material flow analysis, life cycle assessment, and project economic benefit assessment. On this basis, a multi-objective optimization algorithm was used for technology selection under high-dimensional objectives, and the long-term risks were identified and policy recommendations were made based on an uncertainty analysis algorithm. As a case study for the application research of the model, Suzhou, China, was selected, and integrated technology solutions and policy suggestions were provided for 2020 and 2025. The optimized solution can improve the system's efficiency of energy-saving and emission reduction by 14.5%-400.9% while reducing operating costs and new investments.
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