A multiobjective optimization framework for sustainable design of municipal solid waste processing pathways to energy and materials

• Published in: International journal of energy research Vol. 44; no. 2; pp. 771 - 783
• Main Authors: Rizwan, Muhammad, Saif, Yousef, Almansoori, Ali, Elkamel, Ali
• Format: Journal Article
• Language: English
• Published: Bognor Regis John Wiley & Sons, Inc 01.02.2020
• Subjects: Design optimization; Ecological footprint; Economic analysis; Economic benefits; Economics; Emissions control; Energy management; environmental analysis; Environmental aspects; Environmental impact; Environmental management; Environmental objective; Frameworks; Greenhouse effect; Greenhouse gases; multiobjective optimization; Multiple objective analysis; Municipal solid waste; Municipal waste management; Nonlinear programming; Optimization; Solid waste management; Superstructures; Sustainability; Sustainability management; Sustainable design; sustainable management; Sustainable waste management; Urban areas; Waste disposal; Waste management; Waste management industry; Waste treatment
• ISSN: 0363-907X; 1099-114X
• DOI: 10.1002/er.4884

Summary A large quantity of municipal solid waste (MSW) is generated worldwide, and its effective management is a major problem in urban areas or particularly the areas where waste is dumped. Numerous technological alternatives are available for waste treatment, each with different costs and environmental footprints. For sustainable waste management, both economic and environmental aspects should be considered. Therefore, this study addresses the systematic design of processing routes for the sustainable management and utilization of MSW under economic and environmental criteria. To address this, a generic superstructure‐based multiobjective optimization framework is developed. MSW superstructure composes of the potential processing routes for the waste management where MSW can be utilized for energy generation and other valuable waste‐based products. On the basis of superstructure, we develop a multiobjective mixed‐integer nonlinear programming (MINLP) model that simultaneously maximizes the net profit and minimizes the greenhouse gas (GHG) emissions. The developed optimization model is coded and solved in GAMS to determine the optimal most promising routes for the sustainable processing of MSW. A case of the Emirate of Abu Dhabi is employed to test the applicability of the developed framework. The optimization results emphasize that pathway 2 shows a decent trade‐off between economic and environmental objectives, whereas the two most environmentally sustainable processing pathways have the potential to reduce GHG emissions by 58% and 80%, compared with business as usual (BAU) scenario, and also possess potential economic benefits. The insights gained from this analysis guide the municipality planners to devise a promising and sustainable waste management strategy. A generic multiobjective optimization framework is developed by integrating techno‐economic analysis with life cycle assessment (LCA), for the sustainable design of MSW processing pathways to energy and useful products. The developed optimization model identifies the optimal or promising processing routes for the sustainable management and utilization of MSW under both economic and environmental criteria. The multiobjective optimization framework is generic in formulation and, therefore, can be implemented to any municipality subject to availability of the required data.