Title : Assessing and prioritizing demolition waste management scenarios using a BIM-based life cycle sustainability assessment (LCSA) and multi-criteria decision aiding method
Increasing efforts have been devoted to developing a framework for benchmarking demolition waste management (DWM) alternatives based on their performances against different sustainability criteria before the commencement of demolition. With the intention of mitigating the adverse impacts associated with the generation and treatment of waste materials, this study develops and validates a BIM-based sustainability assessment and decision-aiding framework for facilitating decision-making during the project planning and tendering process. A common misconception is to assess the sustainability performance merely hinging on the environmental aspect, as opposed to considering the trade-offs among the three pillars of sustainability, comprising environmental, economic, and societal perspectives. DWM scenarios with different target recycling rates can yield substantially different outcomes with which essential sustainability indicators like carbon emissions and project cost are intertwined. However, the construction industry has not yet been equipped with an approach to assess the sustainability performance of various demolition waste management scenarios, which is easily adaptable to the local context. With this in mind, a decision-aiding approach combing Life Cycle Sustainability Assessment (LCSA) and Multi-Criteria Decision Aiding (MCDA) methods with Building Information Modelling (BIM) is developed. The approach evaluates the performance of DWM alternatives according to eight sustainability indicators. Analytic Hierarchy Process (AHP) was adopted to weigh the indicators. The TOPSIS method was employed to rank the DWM scenarios. In this process, BIM acts as a data repository to empower the data exchange and visualization of the assessment results. Moreover, a building demolition project located at the Parkville campus of the University of Melbourne was selected as a case study to demonstrate the applicability of the proposed approach.