International Journal of Environmental Science and Development

Abstract—This paper has applied operation research to solid waste management systems. The objective is to maximize expected net carbon dioxide equivalent (CO2 e) offsets from four disposal processes (landfill, incineration, producing refuse derive fuel (RDF) and composting). Recycling or non-recycling processes is selected before disposal process. An optimization model was proposed for the optimal solution and decision-making selects the best solution for the solid waste management supply chain for Bangkok, Thailand. Maximum capacity of each disposal process must fulfill, and the recycling method will be a control method. The total amount of municipal solid waste is indicated 9,727.84 tons and maximum amount of recycling waste (827.84 tons) is allowed. The net CO2e offsets is highly correlated with the quantity of solid waste. Moreover, the disposal process that producing RDF is the recommended decision for the department of environment of Bangkok because of the maximum number of CO2e offsets. Eight scenarios were applied to find the lower amount of the net CO2e offsets. Increasing sanitary solid waste disposal capacities are the main assumption affected the amount of CO2e emissions and/or offsets. Scenario 8 increases double capacity for all disposal techniques, and the net CO2e offsets are increased from 4,472.89 tons to 8,945.78 tons. Policymakers and plant operators could adopt the proposed optimization model in the selection of high CO2e offsets system. Moreover, the total number of carbon footprint for organization (CFO) could be reduced.

Keywords—solid waste, solid waste management, waste disposal, optimization model and carbon dioxide offset

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Cite: Chalida U-tapao, Nattaporn Nawakitrangsan and Maruesa Chunawa, "An Optimization Model for Solid Waste Collection and Processing: Case Study of Bangkok, Thailand," International Journal of Environmental Science and Development vol. 15, no. 6, pp. 299-303, 2024.

Copyright © 2024 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).