Recycling (Aug 2024)
Improving the Decision-Making for Sustainable Demolition Waste Management by Combining a Building Information Modelling-Based Life Cycle Sustainability Assessment Framework and Hybrid Multi-Criteria Decision-Aiding Approach
Abstract
Increasing efforts have been devoted to promoting sustainable demolition waste management (DWM) from a life cycle thinking perspective. To this end, facilitating sustainability-oriented decision-making for DWM planning requires a sustainability assessment framework for assessing the trade-offs among multifaceted criteria. This study develops a BIM-based DWM sustainability assessment approach to facilitate the life cycle sustainability assessment (LCSA) and decision-making by integrating LCSA-related properties and hybrid Multi-Criteria Decision-Aiding (MCDA) methods into a BIM environment using Dynamo visual scripting. A dynamic linkage is developed in the streamlined BIM-based LCSA process, where the enriched Industry Foundation Class (IFC) models are coupled with custom LCSA data templates to achieve seamless data exchange between the BIM platform and external LCA tools. Subsequently, hybrid MCDA methods convert the assessment results into DWM scenario ranking. A pilot study verifies the applicability of the BIM-based framework. The results unveil that the sustainability score ascended with the recycling rate. The optimal DWM alternative with the highest recycling rate yields the highest sustainability score at 91.63. Conversely, a DWM alternative reflecting the ‘status quo’ in China’s recycling industry has the lowest score at 8.37, significantly lower than the baseline scenario with a 50% recycling rate. It is worth noting that the ‘growth curve’ of the sustainability score continuously flattens as the target recycling rate escalates. The increment in recycling rate from the “Australian standard” scenario to the optimal scenario is 18.4%, whereas the sustainability score merely increases by 2.3%, implying that the former scenario arrived at an optimum point for maximising the cost-efficiency of DWM under the predefined settings.
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