Cost-benefit analysis of demolition waste management via agent-based modelling: A case study in Shenzhen
•The cost-benefit of demolition waste management in China was analysed.•Selective demolition methods can reduce the generation of waste.•Selective demolition methods can save demolition waste management costs. The economic instrument is an effective approach to encourage demolition contractors to co...
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Veröffentlicht in: | Waste management (Elmsford) 2022-01, Vol.137, p.169-178 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •The cost-benefit of demolition waste management in China was analysed.•Selective demolition methods can reduce the generation of waste.•Selective demolition methods can save demolition waste management costs.
The economic instrument is an effective approach to encourage demolition contractors to conduct low-impact waste management. It is essential for project managers and decision-makers to better understand the cost-benefit of demolition waste (DW) management, to promote development of an effective waste management plan. This study explores the interactive dynamics and adaptive nature between stakeholders, where the cost-benefit of DW management is analysed through the agent-based modelling approach. Shenzhen, a leading city in China in the management of DW, was selected as the study area. It was revealed that if the traditional demolition method is adopted as the primary choice, the net benefit of demolition of buildings in the study case will reach −131.4 billion yuan, i.e. the cost will surpass the revenue. If the selective demolition method is widely used by demolition contractors, simulation results indicate that the net benefit will reach 33.3 billion yuan, an increase of 125.34%, compared to the situation in which the traditional demolition method is widely implemented. Based on the simulation, an optimal management framework for DW management stakeholders was constructed. The research results can provide a decision-making basis for the government and relevant departments to formulate DW management measures. |
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ISSN: | 0956-053X 1879-2456 |
DOI: | 10.1016/j.wasman.2021.10.036 |