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Spatial Heterogeneity of Factors Influencing CO 2 Emissions in China’s High-Energy-Intensive Industries

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  • Shijie Yang

    (School of Environment Science and Spatial Informatics, Chinese University of Mining and Technology, Xuzhou 221116, China
    School of Geography and Environment, Shandong Normal University, Jinan 250358, China)

  • Yunjia Wang

    (School of Environment Science and Spatial Informatics, Chinese University of Mining and Technology, Xuzhou 221116, China)

  • Rongqing Han

    (School of Geography and Environment, Shandong Normal University, Jinan 250358, China)

  • Yong Chang

    (School of Geography and Environment, Shandong Normal University, Jinan 250358, China)

  • Xihua Sun

    (School of Geography and Environment, Shandong Normal University, Jinan 250358, China)

Abstract

In recent years, China has overtaken the United States as the world’s largest carbon dioxide (CO 2 ) emitter. CO 2 emissions from high-energy-intensive industries account for more than three-quarters of the total industrial carbon dioxide emissions. Therefore, it is important to enhance our understanding of the main factors affecting carbon dioxide emissions in high-energy-intensive industries. In this paper, we firstly explore the main factors affecting CO 2 emissions in high-energy-intensive industries, including industrial structure, per capita gross domestic product (GDP), population, technological progress and foreign direct investment. To achieve this, we rely on exploratory regression combined with the threshold criteria. Secondly, a geographically weighted regression model is employed to explore local-spatial heterogeneity, capturing the spatial variations of the regression parameters across the Chinese provinces. The results show that the growth of per capita GDP and population increases CO 2 emissions; by contrast, the growth of the services sector’s share in China’s gross domestic product could cause a decrease in CO 2 emissions. Effects of technological progress on CO 2 emissions in high-energy-intensive industries are negative in 2007 and 2013, whereas the coefficient is positive in 2018. Throughout the study period, regression coefficients of foreign direct investment are positive. This paper provides valuable insights into the relationship between driving factors and CO 2 emissions, and also gives provides empirical support for local governments to mitigate CO 2 emissions.

Suggested Citation

  • Shijie Yang & Yunjia Wang & Rongqing Han & Yong Chang & Xihua Sun, 2021. "Spatial Heterogeneity of Factors Influencing CO 2 Emissions in China’s High-Energy-Intensive Industries," Sustainability, MDPI, vol. 13(15), pages 1-24, July.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:15:p:8304-:d:601196
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    as
    1. Lin, Boqiang & Wang, Xiaolei, 2015. "Carbon emissions from energy intensive industry in China: Evidence from the iron & steel industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 746-754.
    2. Wu, Rui & Geng, Yong & Cui, Xiaowei & Gao, Ziyan & Liu, Zhiqing, 2019. "Reasons for recent stagnancy of carbon emissions in China's industrial sectors," Energy, Elsevier, vol. 172(C), pages 457-466.
    3. Griffin, Paul W. & Hammond, Geoffrey P. & Norman, Jonathan B., 2018. "Industrial energy use and carbon emissions reduction in the chemicals sector: A UK perspective," Applied Energy, Elsevier, vol. 227(C), pages 587-602.
    4. Wang, Yongpei & Li, Jun, 2019. "Spatial spillover effect of non-fossil fuel power generation on carbon dioxide emissions across China's provinces," Renewable Energy, Elsevier, vol. 136(C), pages 317-330.
    5. Wang, Shaojian & Shi, Chenyi & Fang, Chuanglin & Feng, Kuishuang, 2019. "Examining the spatial variations of determinants of energy-related CO2 emissions in China at the city level using Geographically Weighted Regression Model," Applied Energy, Elsevier, vol. 235(C), pages 95-105.
    6. Yue-Jun Zhang & Zhao Liu & Huan Zhang & Tai-De Tan, 2014. "The impact of economic growth, industrial structure and urbanization on carbon emission intensity in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 73(2), pages 579-595, September.
    7. Franco, Sainu & Mandla, Venkata Ravibabu & Ram Mohan Rao, K., 2017. "Urbanization, energy consumption and emissions in the Indian context A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 898-907.
    8. Stephen Matthews & Tse-Chuan Yang, 2012. "Mapping the results of local statistics," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 26(6), pages 151-166.
    9. Liddle, Brantley, 2015. "What Are the Carbon Emissions Elasticities for Income and Population? Bridging STIRPAT and EKC via robust heterogeneous panel estimates," MPRA Paper 61304, University Library of Munich, Germany.
    10. Zhang, Yu & Zhang, Sufang, 2018. "The impacts of GDP, trade structure, exchange rate and FDI inflows on China's carbon emissions," Energy Policy, Elsevier, vol. 120(C), pages 347-353.
    11. Liddle, Brantley & Sadorsky, Perry, 2017. "How much does increasing non-fossil fuels in electricity generation reduce carbon dioxide emissions?," Applied Energy, Elsevier, vol. 197(C), pages 212-221.
    12. Xu, Shi-Chun & He, Zheng-Xia & Long, Ru-Yin, 2014. "Factors that influence carbon emissions due to energy consumption in China: Decomposition analysis using LMDI," Applied Energy, Elsevier, vol. 127(C), pages 182-193.
    13. Wang, Changjian & Wang, Fei & Zhang, Xinlin & Yang, Yu & Su, Yongxian & Ye, Yuyao & Zhang, Hongou, 2017. "Examining the driving factors of energy related carbon emissions using the extended STIRPAT model based on IPAT identity in Xinjiang," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 51-61.
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