Journal
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
Volume 15, Issue 11, Pages -Publisher
MDPI
DOI: 10.3390/ijerph15112467
Keywords
fossil fuel; carbon emission; Logarithmic Mean Divisia Index (LMDI) method
Funding
- National Key Research and Development Program of China [2016YFC1402000]
- Major Program of the National Social Science Foundation of China [14ZDB151]
- State Key Program of the National Social Science Foundation of China [16AZD018]
- Youth Program of the National Social Science Foundation of China [18CJY018]
- National Special Science Foundation for Postdoctoral Scientists of China [2018T110708]
- National Science Foundation for Postdoctoral Scientists of China [2017M610446]
- Social Science Foundation of Shandong Province [17DJJJ03, 17DJJJ07]
- Qingdao City, China [QDSKL1701010]
- Science Foundation for Postdoctoral Scientists of Qingdao City, China [24]
- National Natural Science Foundation of China [41701593, 71371098, 71571157]
- National Special Research Fund for Non-Profit Marine Sector [201305034, 201405029]
- Ministry of Education Philosophy and Social Sciences Development Report Breeding Project [13JBGP005]
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China is confronting great pressure to reduce carbon emissions. This study focuses on the driving factors of carbon emissions in China using the Logarithmic Mean Divisia Index (LMDI) method. Seven economic factors, including gross domestic product (GDP), investment intensity, research and development (R&D) intensity, energy intensity, research and development (R&D) efficiency, energy structure and province structure are selected and the decomposition model of influencing factors of carbon emissions in China is constructed from a sectoral perspective. The influence of various economic factors on carbon emissions is analyzed quantitatively. Results show that the R&D intensity and energy intensity are the main factors inhibiting the growth of carbon emissions. GDP and investment intensity are the major factors promoting the growth of carbon emissions. The contribution of R&D efficiency to carbon emissions is decreasing. The impacts of energy structure and province structure on carbon emissions are ambiguous through time. Finally, some policy suggestions for strengthening the management of carbon emissions and carbon emission reduction are proposed.
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