Abstract
The growth of global population and economy continually increases the waste volumes and consequently creates challenges to handle and dispose solid wastes. It becomes more challenging in mixed rural-urban areas (i.e., areas of mixed land use for rural and urban purposes) where both agricultural waste (e.g., manure) and municipal solid waste are generated. The efficiency and confidence of decisions in current management practices significantly rely on the accurate information and subjective judgments, which are usually compromised by uncertainties. This study proposed a resource-oriented solid waste management system for mixed rural-urban areas. The system is featured by a novel Monte Carlo simulation-based fuzzy programming approach. The developed system was tested by a real-world case with consideration of various resource-oriented treatment technologies and the associated uncertainties. The modeling results indicated that the community-based bio-coal and household-based CH4facilities were necessary and would become predominant in the waste management system. The 95% confidence intervals of waste loadings to the CH4and bio-coal facilities were 387, 450 and 178, 215 tonne/day (mixed flow), respectively. In general, the developed system has high capability in supporting solid waste management for mixed rural-urban areas in a cost-efficient and sustainable manner under uncertainty.
Highlights
Solid waste is causing significant environmental problems in urban and suburban areas and leading to numerous adverse health and environmental impacts around the world [1]
The modeling results indicate that all MSWS from both urban and rural areas as well as the cattle manure initially flow to two facilities: the community-based bio-coal and the householdbased CH4 facilities, and the residues from these two facilities flow to the landfill for final disposal (Figure 4)
This study developed a resource-oriented solid waste management system for a mixed rural-urban area
Summary
Solid waste is causing significant environmental problems in urban and suburban areas and leading to numerous adverse health and environmental impacts around the world [1]. Due to the rising waste generation rates and the lack of available space in landfills, urban communities and even some rural areas are facing some critical challenges in developing effective solid waste management systems and partly due to the existence of various uncertainties in the system [3, 4] These uncertainties may arise from a variety of possible sectors including waste generation rates, disposal capacity, treatment costs, and their interactions, as well as other general uncertainty sources such as incomplete information, measurement and sampling errors, subjective judgement, assumptions and approximation, and dynamics of environmental conditions [5,6,7,8]. Possibilistic and probabilistic uncertainties are usually treated separately [2, 20, 21, 27, 28]
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