TY - JOUR
T1 - Decomposition analysis of energy-related CO2 emission in the industrial sector of China
T2 - Evidence from the LMDI approach
AU - Fatima, Tehreem
AU - Xia, Enjun
AU - Cao, Zhe
AU - Khan, Danish
AU - Fan, Jing Li
N1 - Publisher Copyright:
© 2019, Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2019/7/1
Y1 - 2019/7/1
N2 - Energy consumption and increasing CO2 emissions in China are mainly indorsed to the industrial sector. The objective of this study was to explore the main factors driving CO2 emissions in China’s industry throughout 1991–2016. Based on the log-mean Divisia index (LMDI) method, this study decomposes the change of industry-related CO2 emissions into energy structure effect, income effect, energy intensity effect, carbon emission, and labor effect. The core results indicate that CO2 emissions in China’s industry experienced a significant increase from 738.5 to 7271.8 Mt during 1991–2013, while it decreased to 6844.0 Mt in 2016. The income effect and labor effect are the top two emitters, which accounted for increases of 351.8 Mt and 57.8 Mt in CO2 emissions respectively. Additionally, the energy structure effect also played a role in increasing CO2 emissions. Energy intensity and carbon emission effects are the most important factors in reducing CO2 emissions. The policy suggestions about the different period-wise analyses in terms of economic growth, energy structure, and energy intensity are provided.
AB - Energy consumption and increasing CO2 emissions in China are mainly indorsed to the industrial sector. The objective of this study was to explore the main factors driving CO2 emissions in China’s industry throughout 1991–2016. Based on the log-mean Divisia index (LMDI) method, this study decomposes the change of industry-related CO2 emissions into energy structure effect, income effect, energy intensity effect, carbon emission, and labor effect. The core results indicate that CO2 emissions in China’s industry experienced a significant increase from 738.5 to 7271.8 Mt during 1991–2013, while it decreased to 6844.0 Mt in 2016. The income effect and labor effect are the top two emitters, which accounted for increases of 351.8 Mt and 57.8 Mt in CO2 emissions respectively. Additionally, the energy structure effect also played a role in increasing CO2 emissions. Energy intensity and carbon emission effects are the most important factors in reducing CO2 emissions. The policy suggestions about the different period-wise analyses in terms of economic growth, energy structure, and energy intensity are provided.
KW - CO emissions
KW - China’s industry
KW - Decomposition Analysis
KW - LMDI
UR - http://www.scopus.com/inward/record.url?scp=85069150038&partnerID=8YFLogxK
U2 - 10.1007/s11356-019-05468-5
DO - 10.1007/s11356-019-05468-5
M3 - Article
C2 - 31134541
AN - SCOPUS:85069150038
SN - 0944-1344
VL - 26
SP - 21736
EP - 21749
JO - Environmental Science and Pollution Research
JF - Environmental Science and Pollution Research
IS - 21
ER -