Driving factors of carbon dioxide emissions in China: an empirical study using 2006--2010 provincial data

Yu LIU, Zhan-Ming CHEN, Hongwei XIAO, Wei YANG, Danhe LIU, Bin CHEN

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Front. Earth Sci. ›› 2017, Vol. 11 ›› Issue (1) : 156-161. DOI: 10.1007/s11707-016-0557-4
RESEARCH ARTICLE
RESEARCH ARTICLE

Driving factors of carbon dioxide emissions in China: an empirical study using 2006--2010 provincial data

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Abstract

The rapid urbanization of China has increased pressure on its environmental and ecological well being. In this study, the temporal and spatial profiles of China’s carbon dioxide emissions are analyzed by taking heterogeneities into account based on an integration of the extended stochastic impacts using a geographically and temporally weighted regression model on population, affluence, and technology. Population size, urbanization rate, GDP per capita, energy intensity, industrial structure, energy consumption pattern, energy prices, and economy openness are identified as the key driving factors of regional carbon dioxide emissions and examined through the empirical data for 30 provinces during 2006–2010. The results show the driving factors and their spillover effects have distinct spatial and temporal heterogeneities. Most of the estimated time and space coefficients are consistent with expectation. According to the results of this study, the heterogeneous spatial and temporal effects should be taken into account when designing policies to achieve the goals of carbon dioxide emissions reduction in different regions.

Keywords

carbon dioxide emission / heterogeneity / space spillover

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Yu LIU, Zhan-Ming CHEN, Hongwei XIAO, Wei YANG, Danhe LIU, Bin CHEN. Driving factors of carbon dioxide emissions in China: an empirical study using 2006--2010 provincial data. Front. Earth Sci., 2017, 11(1): 156‒161 https://doi.org/10.1007/s11707-016-0557-4

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Acknowledgments

We thank two anonymous reviewers for their helpful comments on the earlier version of this paper and Dr. Leo Lester for proof reading. Valuable discussion and suggestions from Professor Tasawar Hayat and Professor Ahmed Alsaedi are highly appreciated. This study has been supported by the National Natural Science Foundation of China (Grant Nos. 71473242, 71403285, and 71403017), the National Basic Research Program of China (No. 2012CB955700), and the Strategic Priority Research Program of the Chinese Academy of Sciences (No. XDA05140300).Supplementary materialƒis available in the online version of this article at http://dx.doi.org/10.1007/s11707-016-0557-4 and is accessible for authorized users.

Supplementary material

ƒis available in the online version of this article at http://dx.doi.org/10.1007/s11707-016-0557-4 and is accessible for authorized users.

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2016 Higher Education Press and Springer-Verlag Berlin Heidelberg
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