JOURNAL OF NATURAL RESOURCES ›› 2016, Vol. 31 ›› Issue (8): 1364-1377.doi: 10.11849/zrzyxb.20150905

• Resource Economy • Previous Articles     Next Articles

Analyze on the Spatial-temporal Pattern and Influence Factors of China’s per Capita Household Carbon Emissions

LIU Li-na1, QU Jian-sheng1, 2, HUANG Yu-sheng1, WANG Li1, ZENG Jing-jing1, 2, BIAN Yue1   

  1. 1. Key Laboratory of Western China’s Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China;
    2. Information Center for Global Change Studies, Lanzhou Information Center, CAS, Lanzhou 730000, China
  • Received:2015-08-20 Revised:2016-01-29 Online:2016-08-20 Published:2016-08-20
  • Supported by:

    National Key Basic Research Program, No.2016YFA0602800; National Natural Science Foundation of China, No.41371537


This paper calculates per capita household carbon emissions (HCEs) based on IPCC’s reference approach and Input-output analysis (IOA) of different categories of carbon emissions in China from 1997 to 2012. Its driving factors are also analyzed with the Spatial Error Model (SEM) and the Spatial Lag Model (SLM). The main purpose of this work is to emphasize the characteristics of household carbon emissions based on temporal scale and spatial scale. The results show that: 1) Based on different carbon sources, HCEs can be divided into direct and indirect emissions; based on different human needs, HCEs can be classified as basic and development emissions; based on different consumers’ behaviors, HCEs can be divided into transportation, housing, food, goods and service emissions. 2) At the time scale, both direct and indirect per capita HCEs, basic and development per capita HCEs, and each item of per capita HCEs based on behaviors exhibit the increasing tendency. 3) From the spatial perspective, there is a common pattern in spatial distributions of per capita HCEs. The cluster effect of per capita HCEs is stable. 4) From the space point of view, the per capita HCEs in China shows a decreasing tendency from east to west in 2012. 5) Based on the spatial analysis model, the proportion of basic HCEs per capita in the whole is the main driving factor. Meanwhile, per capita income and per capita GDP are also affecting per capita HCEs. On the basis of analyzing the spatial-temporal patterns and driving factors of per capita household carbon emissions, we provide scientific evidences and put forward effective suggestions for carbon emissions reduction measures and policies.

Key words: China, household carbon emissions, Moran’, s I, spatial analysis model

CLC Number: 

  • X24