Title: Spatio-temporal pattern evolution and spatial convergence of greenhouse gas emission efficiency in China's cities: analyses based on exploratory spatial data analysis and spatial econometric models

Authors: Kaifeng Wang; Dalei Wu; Junyu Li

Addresses: Institute for Environment and Development, Guangdong Academy of Social Sciences, Guangzhou, China ' Department of Postgraduates, Guangdong Academy of Social Sciences, Guangzhou, China ' Institute of Guangdong, Hong Kong and Macao Development Studies, Sun Yat-sen University, Guangzhou, China

Abstract: This paper integrates greenhouse gas (GHG) emissions into the emission efficiency (GEE) index using data envelopment analysis (DEA) and dynamically explores GEE's spatial heterogeneity, correlation, and convergence, offering evidence and insights for optimising China's spatial pattern of GHG emission reduction. Findings indicate that GEE in the 285 sample cities grew by 18% on average during 2004-2018. East-west spatial heterogeneity and positive spatial autocorrelation of GEE progress are evident, and high-high clustering areas of the GEE index gradually shift eastward. GEE displays significant conditional β-convergence, emphasising the need for tailored emission reduction strategies, considering economic and social differences among cities.

Keywords: greenhouse gases; GHGs; efficiency; spatial heterogeneity; spatial dependence; convergence.

DOI: 10.1504/IJGW.2024.139901

International Journal of Global Warming, 2024 Vol.33 No.4, pp.380 - 403

Received: 28 Jun 2023
Accepted: 31 Dec 2023
Published online: 09 Jul 2024 *

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