Utility-specific projections of electricity sector greenhouse gas emissions: a committed emissions model-based case study of California through 2050

被引:18
作者
Grubert, Emily [1 ]
Stokes-Draut, Jennifer [2 ,3 ]
Horvath, Arpad [3 ]
Eisenstein, William [4 ]
机构
[1] Georgia Inst Technol, Sch Civil & Environm Engn, 790 Atlantic Dr, Atlanta, GA 30332 USA
[2] Lawrence Berkeley Natl Lab, Energy Anal & Environm Impacts Div, 1 Cyclotron Rd, Berkeley, CA 94720 USA
[3] Univ Calif Berkeley, Dept Civil & Environm Engn, 760 Davis Hall, Berkeley, CA 94720 USA
[4] Univ Calif Berkeley, Ctr Resource Efficient Communities, 390 Wurster Hall 1839, Berkeley, CA 94720 USA
关键词
electricity; committed emissions; decarbonization; climate change; utilities; macro energy systems; LIFE-CYCLE ASSESSMENT; CARBON EMISSIONS; CO2; EMISSIONS; VARIABILITY; INTENSITY; SYSTEM;
D O I
10.1088/1748-9326/abb7ad
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The environmental profile of electricity is changing rapidly, motivating a need for provider- and time-specific estimates for accurate environmental assessment. This work shows that defensible, provider- and time-specific emissions projections can be derived from two major factors: committed emissions from existing power plants and policy restrictions on future system characteristics. This letter introduces a bottom-up, power plant-based model that projects utility-specific annual average greenhouse gas (GHG) intensity of electricity in the U.S. state of California for 2018-2050, believed to be the first openly available GHG emissions model with utility-specific projections. California is a useful case study for testing in part because of its strict regulatory GHG targets and the complexity of its electricity system, including limited asset ownership by utilities and substantial reliance on imported electricity. This plant-based approach to emissions projections bounds uncertainty in a way that less infrastructurally grounded approaches cannot. For example, emissions from unspecified sources of power can be estimated based on available plants. Based on historical power plant lifetimes, existing policy, and default model assumptions, the CO(2)intensity of Californian electricity is projected to drop from 175 kg CO2/MWh (sales + losses, 2020) to 95 kg CO2/MWh by 2030, operationally decarbonizing by 2047. Upstream methane leakage increases GHG intensity of natural gas-fired power plants by about 30%, assuming a 100 year time horizon and national average estimates for leakage (which likely underestimate leakage for California). Although drivers like market conditions also affect future outcomes, California's current policy targets do not appear to require early retirement for utility generation assets, though up to about two gigawatts of extant in-state merchant capacity might be affected. Under current policy, new generating assets must either comply with the 100% clean electricity standard by 2045 or stop selling in California before the end of their expected useful life.
引用
收藏
页数:11
相关论文
共 39 条
[1]   Assessment of methane emissions from the US oil and gas supply chain [J].
Alvarez, Ramon A. ;
Zavala-Araiza, Daniel ;
Lyon, David R. ;
Allen, David T. ;
Barkley, Zachary R. ;
Brandt, Adam R. ;
Davis, Kenneth J. ;
Herndon, Scott C. ;
Jacob, Daniel J. ;
Karion, Anna ;
Kort, Eric A. ;
Lamb, Brian K. ;
Lauvaux, Thomas ;
Maasakkers, Joannes D. ;
Marchese, Anthony J. ;
Omara, Mark ;
Pacala, Stephen W. ;
Peischl, Jeff ;
Robinson, Allen L. ;
Shepson, Paul B. ;
Sweeney, Colm ;
Townsend-Small, Amy ;
Wofsy, Steven C. ;
Hamburg, Steven P. .
SCIENCE, 2018, 361 (6398) :186-188
[2]   Carbon emission intensity in electricity production: A global analysis [J].
Ang, B. W. ;
Su, Bin .
ENERGY POLICY, 2016, 94 :56-63
[3]  
[Anonymous], Emissions generation resource integrated database (eGRID)
[4]  
[Anonymous], 2018, Renewables Portfolio Standard: Program Overview
[5]  
[Anonymous], **NON-TRADITIONAL**
[6]  
Blumstein C., 2002, Journal of Industry, Competition and Trade, V2, P9, DOI [10. 1023/A:1020822720063, DOI 10.1023/A:1020822720063, 10.1023/A:1020822720063]
[7]  
BREEZE Software, 2017, CALEEMOD APPENDIX DE
[8]  
Burns D, 2020, WORLD ENV WAT RES C
[9]  
California Energy Commission, 2018, 01AFC19C CAL EN COMM
[10]  
California Energy Commission, 2019, POW CONT LAB PCL