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. 2022 May 25;19(11):6427.
doi: 10.3390/ijerph19116427.

Spatial Differences and Influential Factors of Urban Carbon Emissions in China under the Target of Carbon Neutrality

Kai Liu  1   2 , Ziyi Ni  1 , Mei Ren  1   2 , Xiaoqing Zhang  1   2
Affiliations

Spatial Differences and Influential Factors of Urban Carbon Emissions in China under the Target of Carbon Neutrality

Kai Liu et al. Int J Environ Res Public Health. .

Abstract

Cities are areas featuring a concentrated population and economy and are major sources of carbon emissions (CEs). The spatial differences and influential factors of urban carbon emissions (UCEs) need to be examined to reduce CEs and achieve the target of carbon neutrality. This paper selected 264 cities at the prefecture level in China from 2008 to 2018 as research objects. Their UCEs were calculated by the CE coefficient, and the spatial differences in them were analyzed using exploratory spatial data analysis (ESDA). The influential factors of UCEs were studied with Geodetector. The results are as follows: (1) The UCEs were increasing gradually. Cities with the highest CEs over the study period were located in the urban agglomerations of Beijing-Tianjin-Hebei, Yangtze River Delta, Pearl River Delta, middle reaches of the Yangtze River, and Chengdu-Chongqing. (2) The UCEs exhibited certain global and local spatial autocorrelations. (3) The industrial structure was the dominant factor influencing UCEs.

Keywords: Geodetector; carbon neutrality; exploratory spatial data analysis; influential factors; spatial differences; urban carbon emissions.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
The UCEs in China between 2008 and 2018. (a) 2008; (b) 2010; (c) 2012; (d) 2014; (e) 2016; (f) 2018. Note: This figure shows only the results of even years, and the results of odd years can be seen in Supplementary Materials.
Figure 1
Figure 1
The UCEs in China between 2008 and 2018. (a) 2008; (b) 2010; (c) 2012; (d) 2014; (e) 2016; (f) 2018. Note: This figure shows only the results of even years, and the results of odd years can be seen in Supplementary Materials.
Figure 2
Figure 2
The average values of UCEs in China and its four regions between 2008 and 2018.
Figure 3
Figure 3
The local spatial autocorrelation of UCEs in China between 2008 and 2018. (a) 2008; (b) 2010; (c) 2012; (d) 2014; (e) 2016; (f) 2018. Note: This figure shows only the results of even years, and the results of odd years can be seen in Supplementary Materials.
Figure 4
Figure 4
The influential factors of UCEs in China from 2008 to 2018. (a) 2008; (b) 2010; (c) 2012; (d) 2014; (e) 2016; (f) 2018. Note: All the results passed the 1% significance test. This figure shows only the results of even years, and the results of odd years can be seen in Supplementary Materials.
See this image and copyright information in PMC

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