TY - JOUR
T1 - A Modeling Comparison of Deep Greenhouse Gas Emissions Reduction Scenarios by 2030 in California
AU - Brinkman, Gregory
AU - Yeh, Sonia
AU - Yang, Christopher
AU - Gibbs, Michael
AU - Roland-Holst, David
AU - Greenblatt, Jeffery
AU - Mahone, Amber
AU - Wei, Dan
AU - Cunningham, Joshua
AU - Eggert, Anthony
AU - Haley, Ben
AU - Hart, Elaine
AU - Williams, Jim
N1 - Publisher Copyright:
© 2016 The Authors
PY - 2016/11/1
Y1 - 2016/11/1
N2 - 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. 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. 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.
AB - 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. 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. 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.
KW - Climate policies
KW - Emissions reduction scenarios
KW - GHG abatement
KW - Modeling comparison
KW - Non-energy GHG
UR - http://www.scopus.com/inward/record.url?scp=84994060571&partnerID=8YFLogxK
U2 - 10.1016/j.esr.2016.10.001
DO - 10.1016/j.esr.2016.10.001
M3 - Article
AN - SCOPUS:84994060571
SN - 2211-467X
VL - 13-14
SP - 169
EP - 180
JO - Energy Strategy Reviews
JF - Energy Strategy Reviews
ER -