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Frontiers in Energy

ISSN 2095-1701

ISSN 2095-1698(Online)

CN 11-6017/TK

邮发代号 80-972

2019 Impact Factor: 2.657

Frontiers of Energy and Power Engineering in China  0, Vol. Issue (): 214-220   https://doi.org/10.1007/s11708-010-0133-7
  RESEARCH ARTICLE 本期目录
Correlation between carbon emissions and energy structure –Reliability analysis of low carbon target
Correlation between carbon emissions and energy structure –Reliability analysis of low carbon target
Ben HUA()
Research Center of Natural Gas, South China University of Technology, Guangzhou 510640, China
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Abstract

The influence of energy intensity ? on carbon intensity κ depends upon the fraction of energy mixes with high carbon emissions in the total energy mixes γ. The correlation of γ with a variety of primary energy mix fractions and technology advances such as CCS and CCHP is analyzed and deduced. Taking the long-term carbon reduction target in 2050 settled upon by the Copenhagen Agreement and the mid-term target suggested by the “450 Scenes Program” of the International Energy Agency (IEA) as constraints, the new pattern of the energy transition of the world in 2020, 2030, and 2050 are estimated and figured out. The peak value of energy consumption will lag behind the peak value of carbon emissions; the world energy structure shifting point will be in 2020–2025. Estimates show that China’s mid-2020 and long-term targets of energy-saving and emission reduction announced by the Chinese government might be achieved.

Key wordscorrelation    carbon emissions    energy consumption    high carbon emissions energy mix    target of emission reduction    reliability
收稿日期: 2010-03-24      出版日期: 2011-06-05
Corresponding Author(s): HUA Ben,Email:cehuaben@scut.edu.cn   
 引用本文:   
. Correlation between carbon emissions and energy structure –Reliability analysis of low carbon target[J]. Frontiers of Energy and Power Engineering in China, 0, (): 214-220.
Ben HUA. Correlation between carbon emissions and energy structure –Reliability analysis of low carbon target. Front Energ Power Eng Chin, 0, (): 214-220.
 链接本文:  
https://academic.hep.com.cn/fie/CN/10.1007/s11708-010-0133-7
https://academic.hep.com.cn/fie/CN/Y0/V/I/214
Fig.1  
NationGDP/1016USDEnergy consumption/(Mtce·a-1)?/(kgce·USD-1)κ/(kgCO2·USD-1)ω/(tCO2· tce-1)
US13201833240.3370.551.63
UK234503240.2230.361.61
France223073750.260.261.00
Germany290674690.2580.421.63
Japan434017430.2350.361.53
Russia986910070.5670.881.55
China2668123990.3260.722.21
India90636050.1510.302.00
Republic of Korea88803230.4520.691.53
Tab.1  
Nation
USUKFranceRussiaChinaIndiaRepublic of KoreaJapan
O40.436.535.519.121.129.947.045.2
C24.617.25.116.469.655.024.422.9
G24.437.415.553.62.78.513.414.6
0.33G8.0512.35.117.70.92.84.44.9
γ73.166.045.753.291.687.775.873
Tab.2  
Fig.2  
2005202020302030 EIA2050
C/%27.828292430
βC00.10.300.8
O/%36.325193410
G/%23.624202412
a0.40.40.60.60.6
βG0.330.330.30.30.3
B/%023.035
βB000.100.2
γ0.640.6060.480.660.233
Tab.3  
2005202020302030 EIA2050
CO2 emissions/(GtCO2·a-1)27.030.726.042.910.8
Population/1096.77.78.38.39.0
Per capita/(tCO2·p-1·a-1)4.04.03.15.21.2
Energy carbon intensity ω1.541.451.151.150.48
Coal CCS ratio βC00.1[4]0.4[4]00.8
High-carbon energy ratio γ0.640.580.420.660.2
Energy consumption/(Gtce·a-1)15.1821.225.025.322.5
Per capita/(tce·p-1·a-1)2.32.83.03.12.14
Tab.4  
Fig.3  
2005202020302050
CO2 emissions/teCO251745418
Population/10813.11414.715
Per capita emission/(teCO2 ·p-1·a-1)3.95.33.71.2
Energy carbon intensity ω2.31.71.20.55
High-carbon energy ratio γ0.930.710.50.23
CCS ratio β00.10.40.8
Energy consumption/(Gtce·a-1)22.2414533
Per capita emission/(tce·p-1·a-1)1.72.933.12.2
Tab.5  
Fig.4  
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