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Spatial Heterogeneity of Carbon Emissions and Its Influencing Factors in China: Evidence from 286 Prefecture-Level Cities

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  • Chen Li

    (School of Management, Shanghai University of Engineering Science, Shanghai 201620, China)

  • Heng Li

    (School of Economic and Management, Huainan Normal University, Huainan 232038, China)

  • Xionghe Qin

    (School of Urban and Regional Science, East China Normal University, Shanghai 200062, China)

Abstract

In the face of the severe challenge of global warming, promoting low-carbon emission reductions is an important measure to cope with global climate change and achieve a green cycle of sustainable development. The purpose of this study was to reveal the spatial heterogeneity of carbon emissions and the influencing factors in 286 prefecture-level-and-above cities in China, and to provide an empirical basis for the formulation of low-carbon emission reduction policies in China. This study used a combination of comparative analysis, regional difference analysis, correlation analysis, principal component analysis, and stepwise regression analysis to analyze the spatial differences in carbon emissions and their influencing factors in 286 prefecture-level-and-above cities in China, and draws the following main conclusions: (1) From 2005 to 2015, regional differences in six sectors, including household carbon emissions, widened in the 286 prefecture-level-and-above cities in China, while regional differences in 14 sectors, including rural household carbon emissions, narrowed. (2) There were significant intra-group differences in urban household carbon emissions, and the contributions to intra-group differences in carbon emissions differed across the six sectors in the northeast, east, central, and west regions. (3) Although the total and average carbon emissions of each sector increased from 2005 to 2015, China’s carbon emission intensity was decreasing, and carbon productivity is increasing. (4) Carbon emissions per capita (CCE) were positively correlated with GRP per capita, industrial SO 2 emissions per capita, and the proportion of employees in the secondary sector, and negatively correlated with population density and the proportion of employees in the tertiary sector. (5) Resident savings and consumption factors, pollution emission factors, and economic structure factors had a facilitating effect on CCE, while population density factors and economic growth factors have a weakening effect on CCE.

Suggested Citation

  • Chen Li & Heng Li & Xionghe Qin, 2022. "Spatial Heterogeneity of Carbon Emissions and Its Influencing Factors in China: Evidence from 286 Prefecture-Level Cities," IJERPH, MDPI, vol. 19(3), pages 1-29, January.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:3:p:1226-:d:730944
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    as
    1. Fei Fan & Dailin Cao & Ning Ma, 2020. "Is Improvement of Innovation Efficiency Conducive to Haze Governance? Empirical Evidence from 283 Chinese Cities," IJERPH, MDPI, vol. 17(17), pages 1-20, August.
    2. Fei Fan & Shangze Dai & Keke Zhang & Haiqian Ke, 2021. "Innovation agglomeration and urban hierarchy: evidence from Chinese cities," Applied Economics, Taylor & Francis Journals, vol. 53(54), pages 6300-6318, November.
    3. Padilla, Emilio & Serrano, Alfredo, 2006. "Inequality in CO2 emissions across countries and its relationship with income inequality: A distributive approach," Energy Policy, Elsevier, vol. 34(14), pages 1762-1772, September.
    4. Fei Fan & Huan Lian & Song Wang, 2020. "Can regional collaborative innovation improve innovation efficiency? An empirical study of Chinese cities," Growth and Change, Wiley Blackwell, vol. 51(1), pages 440-463, March.
    5. Shuai Liu & Fei Fan & Jianqing Zhang, 2019. "Are Small Cities More Environmentally Friendly? An Empirical Study from China," IJERPH, MDPI, vol. 16(5), pages 1-16, February.
    6. Haichao Yu & Yan Liu & Chengliang Liu & Fei Fan, 2018. "Spatiotemporal Variation and Inequality in China’s Economic Resilience across Cities and Urban Agglomerations," Sustainability, MDPI, vol. 10(12), pages 1-19, December.
    7. Haiqian Ke & Wenyi Yang & Xiaoyang Liu & Fei Fan, 2020. "Does Innovation Efficiency Suppress the Ecological Footprint? Empirical Evidence from 280 Chinese Cities," IJERPH, MDPI, vol. 17(18), pages 1-23, September.
    8. Schipper, Lee & Murtishaw, Scott & Khrushch, Marta & Ting, Michael & Karbuz, Sohbet & Unander, Fridtjof, 2001. "Carbon emissions from manufacturing energy use in 13 IEA countries: long-term trends through 1995," Energy Policy, Elsevier, vol. 29(9), pages 667-688, July.
    9. Chang, Yih F & Lin, Sue J, 1998. "Structural decomposition of industrial CO2 emission in Taiwan: an input-output approach," Energy Policy, Elsevier, vol. 26(1), pages 5-12, January.
    10. Cai, Bofeng & Zhang, Lixiao, 2014. "Urban CO2 emissions in China: Spatial boundary and performance comparison," Energy Policy, Elsevier, vol. 66(C), pages 557-567.
    11. Song Wang & Jiexin Wang & Chenqi Wei & Xueli Wang & Fei Fan, 2021. "Collaborative innovation efficiency: From within cities to between cities—Empirical analysis based on innovative cities in China," Growth and Change, Wiley Blackwell, vol. 52(3), pages 1330-1360, September.
    12. Jing Xie & Qi Sun & Shaohong Wang & Xiaoping Li & Fei Fan, 2020. "Does Environmental Regulation Affect Export Quality? Theory and Evidence from China," IJERPH, MDPI, vol. 17(21), pages 1-23, November.
    13. Wang, Shaojian & Fang, Chuanglin & Wang, Yang, 2016. "Spatiotemporal variations of energy-related CO2 emissions in China and its influencing factors: An empirical analysis based on provincial panel data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 505-515.
    14. Jian-qing Zhang & Tingting Chen & Fei Fan & Song Wang, 2018. "Empirical research on time-varying characteristics and efficiency of the Chinese economy and monetary policy: evidence from the MI-TVP-VAR model," Applied Economics, Taylor & Francis Journals, vol. 50(33), pages 3596-3613, July.
    15. Zhengwen Wang & Yunxiao Zong & Yuwan Dan & Shi-Jie Jiang, 2021. "Country risk and international trade: evidence from the China-B&R countries," Applied Economics Letters, Taylor & Francis Journals, vol. 28(20), pages 1784-1788, November.
    16. Poumanyvong, Phetkeo & Kaneko, Shinji, 2010. "Does urbanization lead to less energy use and lower CO2 emissions? A cross-country analysis," Ecological Economics, Elsevier, vol. 70(2), pages 434-444, December.
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