Inequality characteristics and influencing factors of CO 2 emissions per capita in Jiangsu Province, China.

Autor: Li J; School of Public Administration, Nanjing University of Finance & Economics, Nanjing, 210023, Jiangsu, China. lijianbao888@126.com.; Government Management Research Centre, Nanjing University of Finance & Economics, Nanjing, 210023, Jiangsu, China. lijianbao888@126.com., Huang X; School of Geography and Oceanography Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China., Chuai X; School of Geography and Oceanography Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China.; Frontiers Science Center for Critical Earth Material Cycling, Nanjing University, Nanjing, 210046, Jiangsu, China., Yang H; Department of Geography and Environmental Science, University of Reading, Reading, RG6 6AB, UK., Chen H; School of Public Administration, Nanjing University of Finance & Economics, Nanjing, 210023, Jiangsu, China., Li Y; School of Public Administration, Nanjing University of Finance & Economics, Nanjing, 210023, Jiangsu, China., Wu C; School of Economics, Zhejiang Gongshang University, Hangzhou, 310000, Zhejiang, China.
Jazyk: angličtina
Zdroj: Environmental science and pollution research international [Environ Sci Pollut Res Int] 2024 Apr; Vol. 31 (19), pp. 28564-28577. Date of Electronic Publication: 2024 Apr 01.
DOI: 10.1007/s11356-024-32815-y
Abstrakt: Analyzing the inequality characteristics and influencing factors of CO 2 emissions per capita (CEPC) is conducive to balancing regional development and CO 2 emissions reduction. This study applied the Gini coefficient and Theil index to investigate the CEPC inequalities during 2005-2017 at the county level in Jiangsu Province, China. Considering the spatial spillover and interaction effects, the factors influencing CEPC were analyzed by a hierarchical spatial autoregressive model. The results showed that the inequalities in CEPC first increased and then decreased at the inter-regional, and inter-county levels. The spatial pattern of CEPC was stable, and there was a significantly positive spatial autocorrelation of CEPC at the county level. The High-High type counties were mainly located in Sunan (southern Jiangsu). The spatial interaction effects of the CEPC between the prefecture and county levels indicated that governments at the prefecture level should integrate their county governments to reduce the CEPC. Moreover, carbon intensity, GDP per capita, land urbanization, and industrial structure play an important role in reducing CEPC. Our findings provide a scientific basis for formulating reasonable and effective carbon emission reduction policies.
(© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)
Databáze: MEDLINE
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