Abstract/Summary

As a result of an increase in the global population, about 2.01 billion metric tons of municipal solid waste is produced worldwide of which about 33% remains unmanaged. The literature review did not reveal any in-depth study to manage municipal solid waste (MSW) in a novel way such as a decentralized waste-to-composting approach using Life Cycle Sustainability Assessment (LCSA). Therefore, the main objective of this study was to use the comprehensive LCSA paradigm, for assessing the environmental, social, and economic impacts of MSW management using a decentralized facility. Each of the three LCSA components was assessed in Dhaka, Bangladesh. The Environmental Life Cycle Assessment (ELCA), Social Life Cycle Assessment (SLCA), and Life Cycle Costing (LCC) approaches were used. The study assessed and contrasted three alternative waste management procedures with a proposed waste-to-compost facility using a Photovoltaic (PV) solar panel-based automated waste-to-compost machine, including windrow composting at a decentralized site and two landfilling methods; sanitary and unsanitary. Open-LCA software was used to conduct ELCA for the four scenarios: windrow composting (S1), automated solar-powered composting machine (S2), and the current sanitary (S3) and unsanitary (S4) landfilling practices. The ELCAs were conducted for each environmental burden of ELCA analysis. One ton of municipal solid waste was used as a functional unit. Compared to S3 (~2.12 million tons of CO2-eq) and S4 emissions, the total annual GWP100 from S1 (1.14 million tons CO2-eq) and S2 (411 kg CO2-eq) was significantly lower. S2 showed the lowest level of emissions for all categories when compared to the other three scenarios. There was a strong likelihood that utilizing an unsanitary landfill would affect the environment much more than it already has. In the SLCA study the result reveals that for an indicator score ranging from 0 (best performance) to 1 (bad performance), the workers obtained an average score of 0.5 for fair wages in the working conditions subcategory, compared to an average score of 0.3 for informal workers. In the final analysis, the social security subcategory received an average score of 0.9 from both workers which is significantly less than anticipated. When analyzing LCC, the estimated total cost of the decentralized windrow composting facility project was 2,944,404 USD. This figure is significantly more reasonable when compared to the expenses of landfilling and traditional composting methods: a $1,894,243 initial expenditure and an annual operating cost of 53,578 USD. The decentralized facility with an automated solar based waste to compost machine was the most economical option since it had significantly fewer environmental costs than the other choices. Sanitary landfill had the highest total cost (37,885,978 USD) and the proposed model of PV solar panel-based automated machine had the lowest total cost (139,252 USD). Finally, the goal of LCSA, which included ELCA, SLCA, and LCC, was to ascertain which waste management strategies were the most sustainable considering social, environmental, and economic considerations as well as if these strategies differed from one another. LCSA scores for the four distinct waste management scenarios were based on a 1 to 5 ranking scale. With a photovoltaic-powered composting system, the decentralized waste-to-compost facility achieved the highest LCSA score of 4.3. With 2.8, the windrow composting facility placed second, while the sanitary and unsanitary landfills were least desirable, with scores of 1.97 and 1.5, respectively. The significance of the study is that it provides novel insights on decision-making around waste management scenarios/options using LCSA analysis, as well as applying a novel, more structured framework (including the Analytic Hierarchy Process) to select between waste management options. In conclusion, the LCSA method provides a framework to consider and measure the larger life cycle impacts of systems throughout a range of criteria of sustainability. LCSA can act as a decision support tool by providing an overview of the sustainability performance of potential waste management processes. For optimal benefit, decision-makers need to consider the numerous trade-offs that this type of study uncovers as well as the varying goals of relevant stakeholders.