Journal of Geographical Sciences ›› 2014, Vol. 24 ›› Issue (4): 612-630.doi: 10.1007/s11442-014-1109-z

• Research Articles • Previous Articles     Next Articles

Spatial differences and multi-mechanism of carbon footprint based on GWR model in provincial China

Shaojian WANG1,2(), Chuanglin FANG1,*(), Haitao MA1, Yang WANG3, Jing QIN1,2   

  1. 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
    3. Guangzhou Institute of Geography, Guangzhou 510070, China
  • Received:2013-05-07 Accepted:2013-11-18 Online:2014-04-20 Published:2015-07-09
  • Contact: Chuanglin FANG E-mail:1987wangshaojian@163.com;fangcl@igsnrr.ac.cn
  • About author:

    Author: Wang Shaojian (1986-), PhD Candidate, specialized in land use and resources & urban geography. E-mail: 1987wangshaojian@163.com

  • Supported by:
    National Natural Science Foundation of China, No.41371177.Major Program of National Social Science Foundation of China, No.13&ZD027

Abstract:

Global warming has been one of the major concerns behind the world’s high-speed economic growth. How to implement the coordinated development of the carbon footprint and the economy will be the core issue of the world’s economic and social development, as well as the heated debate of the research at home and abroad in recent years. Based on the energy consumption, integrated with the “Top-Down” life cycle approach and geographically weighted regression (GWR) model, this paper analyzed the spatial differences and multi-mechanism of carbon footprint in provincial China in 2010. Firstly, this study calculated the amount of carbon footprint of each province using “Top-Down” life cycle approach and found that there were significant differences of carbon footprint and per capita carbon footprint in provincial China. The provinces with higher carbon footprint, mainly located in northern China, have large economic scales; the provinces with higher per capita carbon footprint are mainly distributed in central cities such as Beijing, Shanghai and energy-rich regions and heavy chemical bases. Secondly, with the aid of GIS and spatial analysis model (GWR model), this paper had unfolded that the expansion of economic scale is the main driver of the rapid growth of carbon footprint. The growth of population and urbanization also acted as promoting factors for the increase of the carbon footprint. Energy structure had no considerable promoting effect for the increase of the carbon footprint. Improving energy efficiency is the most important factor to inhibit the growing carbon footprint. Thirdly, developing low-carbon economies and low-carbon industries, as well as advocating low-carbon city construction and improving carbon efficiency would be the primary approaches to inhibit the rapid growth of carbon footprint. Moderately controlling the economic scale and population size would also be required to alleviate carbon footprint. Meanwhile, environmental protection and construction of low-carbon cities would evoke extensive attention in the process of urbanization.

Key words: carbon footprint, spatial differences, multi-mechanism, GWR model, China