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Abstract
Global climate change has emerged as one of the most challenging environmental issues and has gained considerable attention worldwide. Greenhouse Gas (GHG) mitigation policies are needed to avoid the increasing risks of climate change on the environment, human health, and the economy. A wide variety of factors have an influence on the level of GHG emissions, and one of the most important factors is the production and consumption of energy. Energy systems have close relationships with a variety of economic and environmental activities. Therefore, to support effective GHG mitigation policy-making, advanced methodologies are needed to understand the entire system and simulate the multi-dimensional impacts and risks in Environmental and Economic systems.
In this dissertation research, a set of models have been developed to facilitate the Environmental and Economic systems identification and simulation for GHG emissions management. The proposed models include: (a) an environmentally-extended input-output model with detailed disaggregation of energy sectors for life-cycle GHG emission intensities analysis, (b) a disaggregated ecologically-extended input-output model for integrated GHG emissions and emission relationships analysis, (c) a factorial ecologically-extended input-output model for urban GHG emissions metabolism system analysis, (d) an environmentally-extended input-output simulation model for production-based and consumption-based industrial GHG mitigation policy analysis, (e) a Saskatchewan-based computable general equilibrium model for economy-wide GHG mitigation policy analysis, and (f) a multi-dimensional hypothetical fuzzy risk simulation model for GHG mitigation analysis in socio-economic systems. The developed models have been applied to the Province of Saskatchewan, Canada to illustrate their applicability and advantages in system identification and simulation, and to provide decision support for GHG mitigation management.
The major contributions of this research are the development of innovative models and a comprehensive approach for investigating complexities in Environmental and Economic systems to reveal the future risks of different GHG mitigation policies and trade-offs across multiple dimensions. The in-depth case study of the Province of Saskatchewan, Canada provides scientific support for the most desirable GHG mitigation policy development.
