A modeling comparison of deep greenhouse gas emissions reduction scenarios by 2030 in California
[1];
- Univ. of California, Davis, CA (United States). Inst. of Transportation Studies; Chalmers Univ. of Technology, Gothenburg (Sweden). Dept. of Energy and Environment
- Univ. of California, Davis, CA (United States). Inst. of Transportation Studies
- California Air Resources Board, Sacramento, CA (United States)
- Univ. of California, Berkeley, CA (United States). Dept. of Agricultural and Resource Economics
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Energy Analysis and Environmental Impacts Division and Joint Center for Artificial Photosynthesis
- Energy and Environmental Economics (E3), San Francisco, CA (United States)
- Univ. of Southern California, Los Angeles, CA (United States). Sol Price School of Public Policy
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- ClimateWorks Foundation, San Francisco, CA (United States)
California aims to reduce greenhouse gas (GHG) emissions to 40% below 1990 levels by 2030. We compare six energy models that have played various roles in informing the state policymakers in setting climate policy goals and targets. These models adopt a range of modeling structures, including stock-turnover back-casting models, a least-cost optimization model, macroeconomic/macro-econometric models, and an electricity dispatch model. Results from these models provide useful insights in terms of the transformations in the energy system required, including efficiency improvements in cars, trucks, and buildings, electrification of end-uses, low- or zero-carbon electricity and fuels, aggressive adoptions of zero-emission vehicles (ZEVs), demand reduction, and large reductions of non-energy GHG emissions. Some of these studies also suggest that the direct economic costs can be fairly modest or even generate net savings, while the indirect macroeconomic benefits are large, as shifts in employment and capital investments could have higher economic returns than conventional energy expenditures. These models, however, often assume perfect markets, perfect competition, and zero transaction costs. They also do not provide specific policy guidance on how these transformative changes can be achieved. Greater emphasis on modeling uncertainty, consumer behaviors, heterogeneity of impacts, and spatial modeling would further enhance policymakers' ability to design more effective and targeted policies. Here, this paper presents an example of how policymakers, energy system modelers and stakeholders interact and work together to develop and evaluate long-term state climate policy targets. Lastly, even though this paper focuses on California, the process of dialogue and interactions, modeling results, and lessons learned can be generally adopted across different regions and scales.
- Research Organization:
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE)
- Grant/Contract Number:
- AC36-08GO28308
- OSTI ID:
- 1333279
- Report Number(s):
- NREL/JA-6A20-67459
- Journal Information:
- Energy Strategy Reviews, Vol. 13-14, Issue C; ISSN 2211-467X
- Publisher:
- ElsevierCopyright Statement
- Country of Publication:
- United States
- Language:
- English
Web of Science
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