A Decision Support Framework for Sustainable Waste Management

Robert Kijak and David Moy

Journal of Industrial Ecology, 2004, vol. 8, issue 3, 33-50

Abstract: This article describes a decision support framework for the evaluation of scenarios for the integrated management of municipal solid waste within a local government area (LGA). The work is initially focused on local government (i.e., municipal councils) in the state of Queensland, Australia; however, it is broadly applicable to LGAs anywhere. The goal is to achieve sustainable waste management practices by balancing global and regional environmental impacts, social impacts at the local community level, and economic impacts. The framework integrates life‐cycle assessment (LCA) with other environmental, social, and economic tools. For this study, social and economic impacts are assumed to be similar across developed countries of the world. LCA was streamlined at both the life‐cycle inventory and life‐cycle impact assessment stages. For this process, spatial resolution is introduced into the LCA process to account for impacts occurring at the local and regional levels. This has been done by considering social impacts on the local community and by use of a regional procedure for LCA data for emissions to the environment that may have impacts at the regional level. The integration follows the structured approach of the pressure‐state‐response (PSR) model suggested by the Organisation for Economic Cooperation and Development (OECD). This PSR model has been extended to encompass nonenvironmental issues and to guide the process of applying multiple tools. The framework primarily focuses on decision analysis and interpretation processes. Multiattribute utility theory (MAUT) is used to assist with the integration of qualitative and quantitative information. MAUT provides a well‐structured approach to information assessment and facilitates objective, transparent decisions. A commercially available decision analysis software package based on MAUT has been used as the platform for the framework developed in this study.

Date: 2004
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