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Environmental Science and Pollution Research

, Volume 24, Issue 6, pp 5757–5772 | Cite as

Analysis of the impact path on factors of China’s energy-related CO2 emissions: a path analysis with latent variables

  • Wenhui Chen
  • Yalin Lei
Research Article

Abstract

Identifying the impact path on factors of CO2 emissions is crucial for the government to take effective measures to reduce carbon emissions. The most existing research focuses on the total influence of factors on CO2 emissions without differentiating between the direct and indirect influence. Moreover, scholars have addressed the relationships among energy consumption, economic growth, and CO2 emissions rather than estimating all the causal relationships simultaneously. To fill this research gaps and explore overall driving factors’ influence mechanism on CO2 emissions, this paper utilizes a path analysis model with latent variables (PA-LV) to estimate the direct and indirect effect of factors on China’s energy-related carbon emissions and to investigate the causal relationships among variables. Three key findings emanate from the analysis: (1) The change in the economic growth pattern inhibits the growth rate of CO2 emissions by reducing the energy intensity; (2) adjustment of industrial structure contributes to energy conservation and CO2 emission reduction by raising the proportion of the tertiary industry; and (3) the growth of CO2 emissions impacts energy consumption and energy intensity negatively, which results in a negative impact indirectly on itself. To further control CO2 emissions, the Chinese government should (1) adjust the industrial structure and actively develop its tertiary industry to improve energy efficiency and develop low-carbon economy, (2) optimize population shifts to avoid excessive population growth and reduce energy consumption, and (3) promote urbanization steadily to avoid high energy consumption and low energy efficiency.

Keywords

Energy-related carbon emissions Path analysis with latent variables model Direct and indirect influence Causality relationships Influencing mechanism Policy implications 

Notes

Acknowledgments

The authors acknowledge and express appreciation for the following support of this research: Chinese Academy of Land and Resource Economics No. 12120113093200, the Development Research Center of China Geological Survey Bureau under Grant No. 12120114056601, and the Fundamental Research Funds for the Central Universities under Grant No. 53200859632.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.School of Humanities and Economic ManagementChina University of GeosciencesBeijingPeople’s Republic of China
  2. 2.Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Land and ResourcesBeijingChina

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