Why Rapid and Deep Decarbonization isn’t Simple: Linking Bottom-up Socio-technical Decision-making Insights with Top-down Macroeconomic Analyses

Energy-economy-emissions modeling has commonly projected that the rapid and significant reductions in greenhouse gas emissions (GHGs) required to avoid the most significant consequences of climate change are, in theory, attainable with emissions policies and existing technologies. However, the assumptions of rates of change embodied in the technological deployments and retirements of these projections may not be consistent with existing socio-technical bottlenecks. This paper proposes to evaluate the top-down projections of a Computable General Equilibrium (CGE) model—one of a number of energy-economy-emissions modeling approaches commonly used for assessing the impacts of decarbonization—with a bottom-up framework representing the aggregated effect of project planning and approval processes. The Socio-technical Decision-making Model (SDM) will be used to construct an upper-bound achievability limit for project developments, given timelines and constraints for regulatory approval, capital investment cycles, public acceptance, and other socio-technical considerations. Results from this framework can be used to develop energy and climate change policy targets more cognizant of the sensitivity of predictions to highly uncertain social, economic, and technical outcomes and adaptations. Illustrative scenarios of nuclear power generation in China are presented to extend and improve our current understanding of CGE model predictions of technical feasibility, as well as the manner in which alternative parameterization for socioeconomic and political impediments can modify simulated pathways. A key finding is that the deployment of nuclear power technologies as a low-carbon generation resource in China may be able to be accelerated above recent economic projections due to support from political, regulatory, industrial, and social drivers.