TY - JOUR
T1 - Driving forces of national and regional carbon intensity changes in China
T2 - Temporal and spatial multiplicative structural decomposition analysis
AU - Cao, Ye
AU - Zhao, Yuhuan
AU - Wang, Hongxia
AU - Li, Hao
AU - Wang, Song
AU - Liu, Ya
AU - Shi, Qiaoling
AU - Zhang, Yongfeng
N1 - Publisher Copyright:
© 2018 Elsevier Ltd
PY - 2019/3/10
Y1 - 2019/3/10
N2 - With the increasing pressure on reducing CO 2 emissions, China promised to reduce carbon intensity by 60–65% by 2030 from 2005 levels. This study aims at identifying the driving forces of national and regional carbon intensity changes in China at multiple levels by a newly extended multiplicative structural decomposition analysis. Attribution analysis is further adopted to identify sectors with large intensity-reduction potential. National and regional carbon intensity changes during 2007–2012 are decomposed into three determinants: intensity (or efficiency) effect, input structure effect and final demand effect. Temporal decomposition results suggest that 29.0% decline of national carbon intensity is mainly due to intensity effect, while input structure and final demand effect drive the increment of national carbon intensity. Eight regions are divided into two groups: carbon intensity in Northwest, South Coast and Northeast increased due to input structure and final demand effect; carbon intensity in other regions decreased due to intensity effect and final demand effect. Investment and export are the dominant final demand categories to carbon intensity decline in most regions. Spatial decomposition results reveal the huge contribution discrepancy of driving forces among 30 provinces, and 30 provinces are accordingly classified into four groups. For most regions, simultaneously optimizing input structure and final demand are preferred in sectors with large intensity-reduction potential like Mining, Manufacture, Metals and metal productions and Production and supply of electricity, gas and water. Targeted intensity-reduction strategies at multiple levels are suggested.
AB - With the increasing pressure on reducing CO 2 emissions, China promised to reduce carbon intensity by 60–65% by 2030 from 2005 levels. This study aims at identifying the driving forces of national and regional carbon intensity changes in China at multiple levels by a newly extended multiplicative structural decomposition analysis. Attribution analysis is further adopted to identify sectors with large intensity-reduction potential. National and regional carbon intensity changes during 2007–2012 are decomposed into three determinants: intensity (or efficiency) effect, input structure effect and final demand effect. Temporal decomposition results suggest that 29.0% decline of national carbon intensity is mainly due to intensity effect, while input structure and final demand effect drive the increment of national carbon intensity. Eight regions are divided into two groups: carbon intensity in Northwest, South Coast and Northeast increased due to input structure and final demand effect; carbon intensity in other regions decreased due to intensity effect and final demand effect. Investment and export are the dominant final demand categories to carbon intensity decline in most regions. Spatial decomposition results reveal the huge contribution discrepancy of driving forces among 30 provinces, and 30 provinces are accordingly classified into four groups. For most regions, simultaneously optimizing input structure and final demand are preferred in sectors with large intensity-reduction potential like Mining, Manufacture, Metals and metal productions and Production and supply of electricity, gas and water. Targeted intensity-reduction strategies at multiple levels are suggested.
KW - Attribution analysis
KW - Carbon intensity
KW - China
KW - Driving forces
KW - Multiplicative structural decomposition analysis
UR - http://www.scopus.com/inward/record.url?scp=85060018161&partnerID=8YFLogxK
U2 - 10.1016/j.jclepro.2018.12.155
DO - 10.1016/j.jclepro.2018.12.155
M3 - Article
AN - SCOPUS:85060018161
SN - 0959-6526
VL - 213
SP - 1380
EP - 1410
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
ER -