| Summary: | Municipal solid waste treatment options are not necessarily pragmatic if their long-term benefits don’t mutually satisfy all related stakeholders such as industry, municipality, etc. Stakeholders are inclined to select an option with the maximized benefits and minimized lifecycle costs. A decision support framework is needed to identify and evaluate available waste treatment options under diverse multiple criteria and conflicting preferences of multiple stakeholders. This study developed a decision support framework that guides stakeholders to reach an agreement on the most sustainable and pragmatic waste treatment option. The framework compares lifecycle sustainability impacts of different waste treatment options and uses Analytical Hierarchy Process to determine a weighting scheme, which has an ability to combine diverse impacts based on stakeholders’ preferences. It also employs Game Theory to model stakeholders’ dialogues and behaviors in the group decision-making. The outcome of the framework is to recommend fair shares of costs and benefits to assist stakeholders in reaching a mutually agreeable solution.
The application of the developed framework is demonstrated through a case study of waste treatment in Metro Vancouver (British Columbia, Canada), where the industry and the municipality are proposing the production of Refuse Derived Fuel (RDF). Results show that both industry and the municipality may benefit from RDF and waste-to-energy options, respectively; however as a compromised solution, the industry should pay a tipping fee to access the required amount of solid waste from the Metro Vancouver to substitute the use of fossil fuels with RDF.
Uncertainty is unavoidable due to the inherent complexity in the methods and input data, and should be acknowledged to enhance the reliability in decision-making process. Most common uncertainties encountered in such environmental management problems are in cost and benefit estimates, and stakeholders’ ability in verbalizing their preferences, and their knowledge about each other’s priorities. The decision support framework used sensitivity analysis, Fuzzy Set Theory, and Bayesian Games to study the uncertainty impacts on the decision-making process. === Graduate Studies, College of (Okanagan) === Graduate
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