Carbon emission efficiency and spatio-temporal dynamic evolution of the cities in Beijing-Tianjin-Hebei Region, China

• Published in: Environment, development and sustainability Vol. 24; no. 6; pp. 7640 - 7664
• Main Authors: Xue, Li-Ming, Zheng, Zhi-Xue, Meng, Shuo, Li, Mingjun, Li, Huaqing, Chen, Ji-Ming
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.06.2022; Springer Nature B.V
• Subjects: Agglomeration; Carbon; China; Cities; Earth and Environmental Science; Ecology; Economic Geology; Economic Growth; Efficiency; Emissions; Environment; Environmental Economics; Environmental Management; Evolution; Quantiles; regression analysis; Regression coefficients; Regression models; Spatial analysis; Spatial distribution; Sustainable Development; Values; Beijing China; China; Hebei China; Spatial quantile regression; Super-efficiency EBM model; Carbon emission efficiency; Beijing-Tianjin-Hebei cooperation; Spatio-temporal effect
• ISSN: 1387-585X; 1573-2975
• DOI: 10.1007/s10668-021-01751-z

Improving carbon emission efficiency (CEE) would promote the development of the green and low-carbon economy in the Beijing-Tianjin-Hebei (BTH) region, China. This paper uses the EBM model of unexpected output to measure the city-level CEE of the BTH region from 2007 to 2016. The spatial distribution characteristics and evolution law of CEE are analyzed with respect to overall and local aspects, and the spatial quantile regression model is used to verify the influencing factors of CEE. The main findings are as follows: (1) The carbon emission in the BTH region is considered to be of medium efficiency, and there are eight cities within the region at middle- and high-efficiency levels. The overall efficiency values show a downward trend. Beijing, Cangzhou, Baoding have high-CEE values, whereas Handan, Tangshan, and Zhangjiakou have low-CEE values. (2) The CEE values for BTH show significant spatial agglomeration characteristics at both the global and local levels. The “H–H” agglomeration areas are primarily distributed in the central region, and the “L-L” agglomeration areas are chiefly distributed in the southern and northern regions. The spatial pattern change is generally stable. (3) The selected factors, URB, PGDP, DS, ISG, FDI, and TEL, have different regression coefficients on CEE at different quantiles.