Literature DB >> 33373195

Potential Role of Fiscal Decentralization on Interprovincial Differences in CO2 Emissions in China.

Shulei Cheng1, Wei Fan2, Fanxin Meng3, Jiandong Chen1, Sai Liang4, Malin Song5, Gengyuan Liu3, Marco Casazza6.   

Abstract

Spatial differences in CO2 emissions must be taken into account in CO2 mitigation. In this work, a spatial within-between logarithmic mean Divisia index decomposition model was developed by using cluster analysis to evaluate the potential role of fiscal decentralization in driving interprovincial differences in CO2 emissions in China. The results revealed that the direct impact of fiscal decentralization emerged as a major emission driver after 2009. The differences of provincial CO2 emissions from the national average can be mainly attributed to emission differences between the distinct provincial clusters. The direct and indirect impacts of fiscal decentralization contributed to the shaping of differences in CO2 emission between provinces and their provincial cluster average, and between provincial cluster average and the national average. Reducing the differences in CO2 emission between distinct provincial clusters should be considered a breakthrough for the Chinese government. The provinces with CO2 emissions below the national average and above the average emissions of its provincial cluster still have the potential for further mitigation. Optimizing the expenditure authority of the central and provincial governments and improving the energy efficiency of the provincial fiscal expenditure are the two effective ways to further promote CO2 mitigation.

Entities:  

Year:  2020        PMID: 33373195     DOI: 10.1021/acs.est.0c04026

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  1 in total

1.  City- and county-level spatio-temporal energy consumption and efficiency datasets for China from 1997 to 2017.

Authors:  Jiandong Chen; Jialu Liu; Jie Qi; Ming Gao; Shulei Cheng; Ke Li; Chong Xu
Journal:  Sci Data       Date:  2022-03-24       Impact factor: 6.444

  1 in total

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