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. 2022 Jan 22;19(3):1226.
doi: 10.3390/ijerph19031226.

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

Chen Li  1 , Heng Li  2 , Xionghe Qin  3
Affiliations

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

Chen Li et al. Int J Environ Res Public Health. .

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 SO2 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.

Keywords: 286 prefecture-level cities; China; Theil index; carbon emissions; spatial heterogeneity.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Capita carbon emissions in prefecture-level-and-above cities in China in 2015 (t/person).
Figure 2
Figure 2
Total carbon emissions in prefecture-level-and-above cities in China in 2015(104 tonnes).
Figure 3
Figure 3
Carbon emissions per GDP in four major regions of China.
Figure 4
Figure 4
Carbon productivity in four major regions of China.
Figure 5
Figure 5
Correlation analysis between carbon emission variables.
Figure 5
Figure 5
Correlation analysis between carbon emission variables.
See this image and copyright information in PMC

References

    1. Wang S.J., Xie Z.H., Wang Z.H. The spatiotemporal pattern evolution and influencing factors of CO2 emissions at the county level of China. Acta Geographica Sinica. 2021;76:3103–3118.
    1. Fan F., Lian H., Liu X. Can environmental regulation promote urban green innovation Efficiency? An empirical study based on Chinese cities. J. Clean. Prod. 2020;287:125060. doi: 10.1016/j.jclepro.2020.125060. - DOI
    1. Fan F., Zhang X.R. Transformation effect of resource-based cities based on PSM-DID model: An empirical analysis from China. Environ. Impact Assess. Rev. 2021;91:106648. doi: 10.1016/j.eiar.2021.106648. - DOI
    1. Ke H.Q., Dai S.Z. Does innovation efficiency inhibit the ecological footprint? An empirical study of China’s provincial regions. Technol. Anal. Strateg. Manag. 2021;33:1959910. doi: 10.1080/09537325.2021.1959910. - DOI
    1. Wang S., Wang X.L., Lu F. The impact of collaborative innovation on ecological efficiency—empirical research based on China’s regions. Technol. Anal. Strateg. Manag. 2020;32:242–256. doi: 10.1080/09537325.2020.1812564. - DOI

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