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Sustainable Plastic Waste Management Using a System Dynamics Approach
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This study used system dynamics modeling to analyze municipal solid plastic waste management, simulating how different policy interventions affect waste generation, recycling, and environmental leakage over time. Understanding the dynamics of plastic waste systems helps identify the most effective points for intervention to reduce microplastic pollution.
The exponential population growth coupled with rapid industrialization and urbanization triggered enormous generation of municipal solid plastic waste (MSPW). The massive generation of MSPW, coupled with the poor management, have caused significant negative impacts on the environment. Recently, a variety of MSPW management measures, such as source separation and plastic reduction, have been developed worldwide to guide MSPW management systems towards sustainability. Hence, developing a sustainable MSPW management system, through the application of advanced waste measures, is important for future sustainable development. However, sustainable MSPW management systems have not been well addressed in the literature. Therefore, this study aims to develop a generic system dynamics (SD) model to study the sustainable MSPW management. This is achieved through forecasting the effects of sustainable measures, namely source separation policy, recycling process, and incineration with energy recovery technology on MSPW management and amount of GHG reduction. The proposed model is implemented on a case study of MSPW management system in Dubai to assess its applicability and effectiveness. Vensim software is used to stimulate and analyze the model through testing five different scenarios. The simulation results indicated that scenarios HSLRWI and LSHRLI perform best in terms of the amount of plastic waste recycled, scenario LSWRHI leads to the highest amount of GHG reduction, and scenario LSHRLI gives the highest amount of incinerated plastic waste with energy recovery and least amount of plastic waste landfilled. Therefore, the proposed model helps decision makers in choosing the scenario that works best according to their strategies and goals.
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