Journal of Geographical Sciences ›› 2014, Vol. 24 ›› Issue (4): 631-650.doi: 10.1007/s11442-014-1110-6

• Research Articles • Previous Articles     Next Articles

Spatiotemporal dynamics of carbon intensity from energy consumption in China

Yeqing CHENG1(), Zheye WANG1,2, Xinyue YE3, Yehua Dennis WEI4   

  1. 1. Northeast Institute of Geography and Agroecology, CAS, Changchun 130102, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
    3. Department of Geography, Kent State University, Kent, Ohio 44242, USA
    4. Department of Geography, University of Utah, Salt Lake City, UT 84112-9155, USA
  • Received:2013-10-27 Accepted:2013-12-05 Online:2014-04-20 Published:2015-07-09
  • About author:

    Author: Cheng Yeqing (1976-), PhD and Associate Professor, specialized in economic geography and rural development. E-mail: yqcheng@iga.ac.cn

  • Supported by:
    Key Research Program of the Chinese Academy of Sciences, No.KZZD-EW-06-03.No.KSZD-EW-Z-021-03.Key Project of Chinese Ministry of Education, No.13JJD790008.National Natural Science Foundation of China, No.41329001.No.41071108

Abstract:

The sustainable development has been seriously challenged by global climate change due to carbon emissions. As a developing country, China promised to reduce 40%-45% below the level of the year 2005 on its carbon intensity by 2020. The realization of this target depends on not only the substantive transition of society and economy at the national scale, but also the action and share of energy saving and emissions reduction at the provincial scale. Based on the method provided by the IPCC, this paper examines the spatiotemporal dynamics and dominating factors of China’s carbon intensity from energy consumption in 1997-2010. The aim is to provide scientific basis for policy making on energy conservation and carbon emission reduction in China. The results are shown as follows. Firstly, China’s carbon emissions increased from 4.16 Gt to 11.29 Gt from 1997 to 2010, with an annual growth rate of 7.15%, which was much lower than that of GDP (11.72%). Secondly, the trend of Moran’s I indicated that China’s carbon intensity has a growing spatial agglomeration at the provincial scale. The provinces with either high or low values appeared to be path-dependent or space-locked to some extent. Third, according to spatial panel econometric model, energy intensity, energy structure, industrial structure and urbanization rate were the dominating factors shaping the spatiotemporal patterns of China’s carbon intensity from energy consumption. Therefore, in order to realize the targets of energy conservation and emission reduction, China should improve the efficiency of energy utilization, optimize energy and industrial structure, choose the low-carbon urbanization approach and implement regional cooperation strategy of energy conservation and emissions reduction.

Key words: carbon intensity, spatiotemporal dynamics, spatial autocorrelation, spatial panel model, China