Multi-objective optimization of life cycle assessment of integrated waste management based on genetic algorithms: A case study of Tehran

Abstract

Abstract The ever increasing population of the cities and wastes produced by them has compelled many researchers and authorities to find a solution to this problem. The environmental and economic problems are among the challenges in municipal solid waste management (MSWM). Integrated solid waste management (ISWM) is a comprehensive method which deals with these problems through different combinations of technologies like anaerobic digestion (AD), composting and landfill. In this study, life cycle assessment (LCA) has been used to optimize the solid waste management of the city of Tehran. The primary objective of this study is finding the most optimal case with minimum carbon dioxide (CO2) production and energy consumption by considering economic data. Two different scenarios have been defined to do the investigations. In the first scenario, the current status of waste management in Tehran has been considered while in the second scenario, the system is upgraded by implementing state-of-the-art technologies like AD and landfill gas recovery. An LCA software, called IWM-2 was used for calculating the environmental load of each scenario and writing life cycle inventory. Both scenarios are once optimized by considering two objectives and once with three objectives, in order to find the optimal amount of waste entering each unit of waste management system being identified. It was concluded that utilizing newer technologies (second scenario) not only has less cost but also their saving of CO2 and the consumed energy is 901 t and 3,389 GJ less than the first scenario.