Modeling the Network of Municipal Solid Waste Separation Factors using Fuzzy Cognitive Mapping: A Case Study in Tehran

Abstract

Municipal solid waste management is a major challenge, especially in metropolises. This research focuses on a non-technical issue in municipal solid waste management named municipal solid waste separation at the source and seeks to find the best policy in terms of model results. Source separation for recycling has been recognized as a way to achieve sustainable municipal solid waste (MSW) management. The research questions are what factors affect municipal solid waste separation at the source, what are the relationships between them, and which is the best policy to increase municipal solid waste separation at the source. In this research delphi analysis and fuzzy cognitive mapping are used. After identifying 29 factors affecting the waste separation at the source and adjusting them to 9 factors according to the experts' opinions, due to direct causal relationships between the factors and their analysis with the fuzzy cognitive mapping, the factors network affecting the generation of waste were designed. By delphi analysis and expert gathering, three policies were applied to increase waste separation at the source. After analyzing each of the policies, the percentage of change in waste separation was calculated using fuzzy cognitive mapping and the most favorable policy, respectively, was the second policy (Emphasis on culturing), the first policy (Emphasis on encouragement and fines) and, ultimately, The third policy (Emphasis on physical infrastructure) was identified.