气候变化领域集成服务门户(CCPortal): Optimizing the Chinese Electricity Mix for CO2 Emission Reduction: An Input-Output Linear Programming Model with Endogenous Capital

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DOI	10.1021/acs.est.9b05199
	Optimizing the Chinese Electricity Mix for CO2 Emission Reduction: An Input-Output Linear Programming Model with Endogenous Capital
	Kang J.; Ng T.S.; Su B.; Yuan R.
发表日期	2020
ISSN	0013936X
起始页码	697
结束页码	706
卷号	54 期号:2
英文摘要	This study develops an input-output linear programming (IO-LP) model to identify a cost-effective strategy to reduce the economy-wide carbon dioxide (CO2) emissions in China from 2020 to 2050 through a shift in the electricity generation mix. In particular, the fixed capital formation of electricity technologies (FCFE) is endogenized so that the capital-related CO2 emissions of various generation technologies can be captured in the model. The modeling results show that low-carbon electricity, e.g., hydro, nuclear, wind, and solar, is associated with lower operation-related CO2 emissions but higher capital-related CO2 emissions compared to coal-fired electricity. A scenario analysis further reveals that a shift in the electricity generation mix could reduce the accumulated economy-wide CO2 emissions in China by 20% compared to the business-as-usual (BAU) level and could help peak China's CO2 emissions by 2030. The emission reduction is mainly due to a drop in operation-related CO2 emissions of electricity, contributing to a decrease in accumulated economy-wide emissions by 21.4%. The infrastructure expansion of electricity, on the other hand, causes a rise in the accumulated emissions by 1.4%. The proposed model serves as an effective tool to identify the optimal technology choice in the electricity system with the consideration of both direct and indirect CO2 emissions in the economy. American Chemical Society.
scopus关键词	Carbon dioxide; Cost effectiveness; Emission control; Linear programming; Carbon dioxide emissions; CO2 emission reduction; Cost effective strategies; Economy-wide emissions; Electricity generation; Generation technologies; Linear programming models; Low-carbon electricities; Electric power generation; carbon dioxide; coal; capital formation; carbon dioxide; carbon emission; cost-benefit analysis; electricity generation; environmental economics; input-output analysis; linear programing; optimization; Article; carbon footprint; China; cost effectiveness analysis; economic aspect; electric power plant; electricity; energy yield; environmental policy; pollution control; system analysis; electricity; system analysis; China; Carbon Dioxide; China; Coal; Electricity; Power Plants; Programming, Linear
来源期刊	Environmental Science and Technology
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/176994
作者单位	Department of Industrial and Systems Engineering and Management, National University of Singapore, Singapore, 117575, Singapore; Energy Studies Institute, National University of Singapore, Singapore, 119620, Singapore; Institute of Environmental Sciences, CML, Leiden University, Einsteinweg 2, Leiden, 2333 CC, Netherlands; College of Business Management and Economics, Chongqing University, Shazheng Street 174, Chongqing, 400044, China
推荐引用方式 GB/T 7714	Kang J.,Ng T.S.,Su B.,et al. Optimizing the Chinese Electricity Mix for CO2 Emission Reduction: An Input-Output Linear Programming Model with Endogenous Capital[J],2020,54(2).
APA	Kang J.,Ng T.S.,Su B.,&Yuan R..(2020).Optimizing the Chinese Electricity Mix for CO2 Emission Reduction: An Input-Output Linear Programming Model with Endogenous Capital.Environmental Science and Technology,54(2).
MLA	Kang J.,et al."Optimizing the Chinese Electricity Mix for CO2 Emission Reduction: An Input-Output Linear Programming Model with Endogenous Capital".Environmental Science and Technology 54.2(2020).