Historical trend and drivers of China's CO2 emissions from 2000 to 2020

被引:28
作者
Wei, Chong [1 ]
机构
[1] Chinese Acad Sci, Shanghai Adv Res Inst, Shanghai Carbon Data Res Ctr SCDRC, CAS Key Lab Low Carbon Convers Sci & Engn, 99 Haike Rd,Pudong New Area, Shanghai 201210, Peoples R China
基金
中国国家自然科学基金;
关键词
China; CO2; emissions; Fossil fuel; Cement; Driving forces; Carbon peak; Monte Carlo simulation; CARBON EMISSIONS; ENERGY; PEAK; IMPACT; DECOMPOSITION; INTENSITY; INDUSTRY; ACHIEVE; COAL;
D O I
10.1007/s10668-022-02811-8
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
China is the largest CO2 emitter in the world and announced that carbon peak and neutral targets will be achieved before 2030 and 2060, respectively. A retrospective analysis of past CO2 emissions and their drivers is important for the actions of peaking CO2 emissions before 2030 in China. CO2 emissions from energy use (coal, oil, and natural gas) and cement production from 2000 to 2020 were calculated first, and their drivers were decomposed into economic and population growth, energy intensity, and emission coefficient by logarithmic mean Divisa index (LMDI) analysis in this study. China's CO2 emissions increased nearly threefold from 3385 in 2000 to 10,788 million tonnes (Mt) in 2020, with a decline from 2013 to 2016. Coal was the major emission sector contributing more than 70% in most years, while natural gas emissions increased nearly 13 times from 53 to 723 Mt in the two decades, although its contribution only accounted for 6.7% in 2020. Economic growth was the major positive driver, while energy intensity reduction was the major negative driver of the emission increments by year and by the Five Year Plan (FYP). Emission coefficient reduction gradually became important due to its negative effect, especially in the 13th FYP, which offset similar to 30% of the emissions induced by economic growth. The projections of CO2 emissions in 2025, 2030, and 2035 could be 11,596 +/- 582, 11,774 +/- 621, and 11,401 +/- 672 Mt, respectively, suggesting that China's carbon emissions could peak around 2030 with an increment of similar to 1000 Mt on the 2020 levels. Under the sustainable growth of the economy and population, it is possible to reduce the carbon peak value or achieve peak time earlier through the additional reduction of energy intensity and emission coefficient by technological progress and energy alternatives such as non-fossil fuels..
引用
收藏
页码:2225 / 2244
页数:20
相关论文
共 80 条
[1]  
Ambade B., 2022, MINIATURIZED ANALYTI, P71, DOI DOI 10.1002/9783527827213.CH4
[2]   Distribution, risk assessment, and source apportionment of polycyclic aromatic hydrocarbons (PAHs) using positive matrix factorization (PMF) in urban soils of East India [J].
Ambade, Balram ;
Sethi, Shrikanta Shankar ;
Chintalacheruvu, Madhusudana Rao .
ENVIRONMENTAL GEOCHEMISTRY AND HEALTH, 2023, 45 (02) :491-505
[3]   Toxicity and health risk assessment of polycyclic aromatic hydrocarbons in surface water, sediments and groundwater vulnerability in Damodar River Basin [J].
Ambade, Balram ;
Sethi, Shrikanta Shankar ;
Kurwadkar, Sudarshan ;
Kumar, Amit ;
Sankar, Tapan Kumar .
GROUNDWATER FOR SUSTAINABLE DEVELOPMENT, 2021, 13
[4]   Source apportionment and health risks assessment of black carbon Aerosols in an urban atmosphere in East India [J].
Ambade, Balram ;
Sankar, Tapan Kumar .
JOURNAL OF ATMOSPHERIC CHEMISTRY, 2021, 78 (03) :177-191
[5]   COVID-19 lockdowns reduce the Black carbon and polycyclic aromatic hydrocarbons of the Asian atmosphere: source apportionment and health hazard evaluation [J].
Ambade, Balram ;
Sankar, Tapan Kumar ;
Kumar, Amit ;
Gautam, Alok Sagar ;
Gautam, Sneha .
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY, 2021, 23 (08) :12252-12271
[6]   Severe haze in northern China: A synergy of anthropogenic emissions and atmospheric processes [J].
An, Zhisheng ;
Huang, Ru-Jin ;
Zhang, Renyi ;
Tie, Xuexi ;
Li, Guohui ;
Cao, Junji ;
Zhou, Weijian ;
Shi, Zhengguo ;
Han, Yongming ;
Gu, Zhaolin ;
Ji, Yuemeng .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2019, 116 (18) :8657-8666
[7]   Decomposition analysis for policymaking in energy: which is the preferred method? [J].
Ang, BW .
ENERGY POLICY, 2004, 32 (09) :1131-1139
[8]  
Caineng Zou, 2018, Natural Gas Industry B, V5, P380, DOI 10.1016/j.ngib.2018.04.010
[9]   Winter and Summer PM2.5 Chemical Compositions in Fourteen Chinese Cities [J].
Cao, Jun-Ji ;
Shen, Zhen-Xing ;
Chow, Judith C. ;
Watson, John G. ;
Lee, Shun-Cheng ;
Tie, Xue-Xi ;
Ho, Kin-Fai ;
Wang, Ge-Hui ;
Han, Yong-Ming .
JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION, 2012, 62 (10) :1214-1226
[10]   Potential impact of shifting coal to gas and electricity for building sectors in 28 major northern cities of China [J].
Chen, Han ;
Chen, Wenying .
APPLIED ENERGY, 2019, 236 :1049-1061