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Driving factors of carbon emissions in China: A joint decomposition approach based on meta-frontier.

Authors :
Liu, Bingquan
Shi, Junxue
Wang, Hui
Su, Xuelin
Zhou, Peng
Source :
Applied Energy. Dec2019, Vol. 256, pN.PAG-N.PAG. 1p.
Publication Year :
2019

Abstract

• A joint decomposition model based on meta-frontier was proposed. • The effect of scale efficiency was captured based on variable return to scale model. • The catch up effect of carbon emission and energy usage technology was captured. Production-theoretical decomposition analysis (PDA) is widely used to explore the factors related to changes in carbon emissions. However, traditional PDA mainly focuses on scenarios of decision making units (DMUs) with constant returns to scale, and neglects technology heterogeneity among DMUs. Therefore, this paper proposes a joint approach combined PDA and index decomposition analysis (IDA) based on the variable returns to scale (VRS) and the meta-frontier model, and further decomposed the change of carbon emissions into 9 driving factors. Based on above, we investigated the effects of the nine factors on the change of carbon emissions at national, regional and provincial levels in China during the period of 2007–2016. The results indicated that the increase of carbon emissions in China have slowed down since 2012, but the overall situation is not optimistic, especially in the western region. Economic activity played a dominant role in increasing carbon emissions for each region. Carbon emission efficiency and potential carbon factor were also the two important factors related to increase carbon emissions. Conversely, energy intensity, the catch-up effect of pure technical efficiency and scale efficiency on carbon emissions played a positive role in decreasing CO 2 emissions, especially for the eastern region. However, the driving factors related to energy usage, such as the catch-up effect of energy usage scale efficiency and the pure energy usage technical efficiency had trifling and unstable effects on the change of carbon emissions. Based on the above analysis, we propose suggestions to reduce carbon emissions. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03062619
Volume :
256
Database :
Academic Search Index
Journal :
Applied Energy
Publication Type :
Academic Journal
Accession number :
139218330
Full Text :
https://doi.org/10.1016/j.apenergy.2019.113986