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Finding optimal processing pathway for the conversion of MSW into energy and valuable products in Pakistan
Author(s):
1. Hira Amin: Department of Chemical Engineering, Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad, Pakistan
Abstract:
As a developing country, Pakistan is constantly confronted with several roadblocks on its way to advancement. Municipal solid waste (MSW) management is one of those arduous challenges. This research project investigates the most sustainable approach to convert municipal solid waste into energy out of the several methods available for conversion. This study proposed the most optimal pathway by developing a systematic methodology by considering all the possible technological conversion alternatives for municipal solid waste. This methodology leads to superstructure-based optimization of MSW processing pathways. Thermochemical, biochemical, physicochemical, recycling, and landfill-based electricity generation are all potential technological alternatives for producing valuable products from MSW that are incorporated in the superstructure. A mixed integer nonlinear programming (MINLP) model is constructed based on the proposed superstructure to discover the optimal MSW processing paths considering two alternative MSW handling scenarios. The optimal approach for synthesizing valuable products from MSW under the economic objective function is provided by the solution to the optimization problem. The established methodology is applied to 15 cities of Pakistan as a case study to determine the best processing pathway for managing and processing Municipal solid waste into energy and valuable products. Optimization demonstrates that combined recycling and composting of MSW is the most economically beneficial route for processing MSW.
Page(s): 0-0
DOI: DOI not available
Published: Journal: Sixth International Conference on Sustainability in Process Industries (SPI) 19-20 Octover 2022 (Book of Abstracts), Volume: 0, Issue: 0, Year: 2022
Keywords:
Municipal solid waste , superstructure , mixed integer nonlinear programming , Waste to Energy
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