Suggested Citation:
Morrison, Geoffrey M., Sonia Yeh, Anthony R. Eggert, Christopher Yang, James Nelson, Jeffery Greenblatt, Raphael Isaac, Mark Z. Jacobson, Josiah Johnston, Daniel M. Kammen, Ana Mileva, Jack Moore, David Roland-Holst, Max Wei, John Weyant, Jim Williams, Ray Williams, Christina Zapata (2014) Long-term Energy Planning In California: Insights and Future Modeling Needs . Institute of Transportation Studies, University of California, Davis, Research Report UCD-ITS-RR-14-08

Jurisdictions throughout the world are contemplating greenhouse gas (GHG) emission mitigation strategies that will enable meeting long-term GHG targets; many jurisdictions are now focusing on the 2020-2050 timeframe. We conduct an inter-model comparison of nine California statewide energy models with GHG mitigation scenarios to 2050 to better understand common insights across models, ranges of intermediate GHG targets (i.e. for 2030), necessary technology deployment rates, and future modeling needs for the state. The models are diverse in their representation of the California economy: across scenarios with deep reductions in GHGs by 2050, annual statewide GHG emissions are 8-46% lower than 1990 levels by 2030 and 59-84% by 2050; the largest cumulative reductions occur in scenarios that favor earlier reductions; non-hydroelectric renewables account for 30%-54% of all electricity generated for the state in 2030 and 59-89% by 2050; the transportation sector is decarbonized using a mix of energy efficiency gains and alternative-fueled vehicles; and bioenergy is directed towards the transportation sector, accounting for a maximum of 40% of transportation energy by 2050. Models suggest that without new policy, emissions from other non-energy sectors and from high-global-warming-potential gases may exceed California’s 2050 GHG goal. Finally, high priority areas of future model development include: implementation of uncertainty analysis, improved representation of economic impacts and logistical feasibility of given scenarios, simultaneous modeling of criteria and GHG emissions, and greater modeling of interactions between two or more specific policies.

Keywords: Renewable energy; global warming; model comparison; greenhouse gas emissions; California, criteria emissions