Decomposition Analysis in Electricity Sector Output from Carbon Emissions in China

被引:9
|
作者
Jiang, Xue-Ting [1 ,2 ,3 ]
Su, Min [4 ]
Li, Rongrong [4 ]
机构
[1] Chinese Acad Sci, Xinjiang Inst Ecol & Geog, State Key Lab Desert & Oasis Ecol, Urumqi 830011, Peoples R China
[2] Chinese Acad Sci, CAS Res Ctr Ecol & Environm Cent Asia, Urumqi 830011, Peoples R China
[3] Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
[4] China Univ Petr East China, Sch Econ & Management, 66 West Changjiang Rd, Qingdao 266580, Peoples R China
关键词
CO2; emissions; electricity sector; decoupling; comparative stability analysis; China; MEAN DIVISIA INDEX; CO2; EMISSIONS; ECONOMIC-GROWTH; DECOUPLING ANALYSIS; DRIVING FORCES; LMDI APPROACH; ENERGY USE; CONSUMPTION; DRIVERS; INDIA;
D O I
10.3390/su10093251
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Carbon emissions from China's electricity sector account for about one-seventh of the global carbon dioxide emissions, or half of China's carbon dioxide emissions. A better understanding of the relationship between CO2 emissions and electric output would help develop and adjust carbon emission mitigation strategies for China's electricity sector. Thus, we applied the electricity elasticity of carbon emissions to a decoupling index that we combined with advanced multilevel Logarithmic Mean Divisia Index tools in order to test the carbon emission response to the electric output and the main drivers. Then, we proposed a comparative decoupling stability analysis method. The results show that the electric output effect played the most significant role in increasing CO2 emissions from China's electric sector. Also, relative decoupling was the main state during the study period (1991-2012). Moreover, the electricity elasticity of CO2 emissions had a better performance regarding stability in the analysis of China's electricity output.
引用
收藏
页数:18
相关论文
共 50 条
  • [31] Decomposition analysis of energy-related carbon emissions from the transportation sector in Beijing
    Fan, Fengyan
    Lei, Yalin
    TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, 2016, 42 : 135 - 145
  • [32] Decoupling and Decomposition Analysis of Carbon Emissions from Industry: A Case Study from China
    Wang, Qiang
    Li, Rongrong
    Jiang, Rui
    SUSTAINABILITY, 2016, 8 (10)
  • [33] Decomposition analysis of carbon dioxide emissions in China's regional thermal electricity generation, 2000-2020
    Yan, Qingyou
    Zhang, Qian
    Zou, Xin
    ENERGY, 2016, 112 : 788 - 794
  • [34] CO2 emissions from industrial sector in Fujian Province, China: A decomposition analysis
    Liu, Zheng
    Zheng, Guanling
    Ye, Zhinan
    Gao, Panfeng
    2018 INTERNATIONAL CONFERENCE ON AIR POLLUTION AND ENVIRONMENTAL ENGINEERING (APEE 2018), 2018, 208
  • [35] Optimal Carbon Taxes for Emissions Targets in the Electricity Sector
    Olsen, Daniel J.
    Dvorkin, Yury
    Fernandez-Blanco, Ricardo
    Ortega-Vazquez, Miguel A.
    IEEE TRANSACTIONS ON POWER SYSTEMS, 2018, 33 (06) : 5892 - 5901
  • [36] Assessing drivers of CO2 emissions in China's electricity sector: A metafrontier production-theoretical decomposition analysis
    Wang, H.
    Zhou, P.
    Xie, Bai-Chen
    Zhang, N.
    EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2019, 275 (03) : 1096 - 1107
  • [37] Decomposition of electricity demand in China's industrial sector
    Steenhof, PA
    ENERGY ECONOMICS, 2006, 28 (03) : 370 - 384
  • [38] The Impact of Technological Progress in the Energy Sector on Carbon Emissions: An Empirical Analysis from China
    Jin, Lei
    Duan, Keran
    Shi, Chunming
    Ju, Xianwei
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2017, 14 (12)
  • [39] Carbon dioxide emissions from Russia's electricity sector: future scenarios
    Steenhof, PA
    Hill, MR
    CLIMATE POLICY, 2006, 5 (05) : 531 - 548
  • [40] Regional differences and driving factors analysis of carbon emissions from power sector in China
    Wang, Xiu
    Fan, Fengyan
    Liu, Chonghao
    Han, Yawen
    Liu, Qunyi
    Wang, Anjian
    ECOLOGICAL INDICATORS, 2022, 142