Decomposition analysis of energy-related CO2 emission in the industrial sector of China: Evidence from the LMDI approach

Tehreem Fatima, Enjun Xia, Zhe Cao, Danish Khan, Jing Li Fan*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

41 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)21736-21749
Number of pages14
JournalEnvironmental Science and Pollution Research
Volume26
Issue number21
DOIs
Publication statusPublished - 1 Jul 2019

Keywords

  • CO emissions
  • China’s industry
  • Decomposition Analysis
  • LMDI

Fingerprint

Dive into the research topics of 'Decomposition analysis of energy-related CO2 emission in the industrial sector of China: Evidence from the LMDI approach'. Together they form a unique fingerprint.

Cite this