Spatiotemporal differentiation of carbon emission efficiency and influencing factors: From the perspective of 136 countries

Yaping Xiao; Dalai Ma; Fengtai Zhang; Na Zhao; Ling Wang; Zuman Guo; Jiawei Zhang; Bitan An; Yuedong Xiao

doi:10.1016/j.scitotenv.2023.163032

Spatiotemporal differentiation of carbon emission efficiency and influencing factors: From the perspective of 136 countries

Sci Total Environ. 2023 Jun 25:879:163032. doi: 10.1016/j.scitotenv.2023.163032. Epub 2023 Mar 23.

Authors

Yaping Xiao¹, Dalai Ma², Fengtai Zhang¹, Na Zhao¹, Ling Wang³, Zuman Guo¹, Jiawei Zhang¹, Bitan An¹, Yuedong Xiao¹

Affiliations

¹ School of Management, Chongqing University of Technology, Chongqing 400054, China.
² School of Management, Chongqing University of Technology, Chongqing 400054, China. Electronic address: madalai@cqut.edu.cn.
³ College of Economic and Trade, University of Electronic Science and Technology of China, Zhongshan Institute, Zhongshan 528499, China.

PMID: 36965718
DOI: 10.1016/j.scitotenv.2023.163032

Abstract

The severity of the global climate issue is rising, primarily as a result of excessive carbon dioxide emissions. Climate change is a global problem. How to reduce carbon dioxide emissions while promoting social and economic development is a problem that all countries need to face. This study examines global carbon emission efficiency in order to make recommendations for comprehensively improving global low-carbon development level. We extend the research scale of carbon emission efficiency from countries, regions, economic belts and sectors to the world, which can show the differences of countries and has theoretical guiding significance for global low-carbon development. This study calculates the carbon emission efficiency for 136 countries from 2000 to 2019 using the Super-EBM model. The discussion that follows examines the temporal and spatial characteristics of carbon emissions efficiency in 136 countries from the perspective of countries, developed and developing countries, and regions. Finally, the Tobit model is used to comprehensively analyze the factors that affect carbon emission efficiency. The results show that: (1) There are great differences in carbon emission efficiency among countries and regions. Only a few countries reach the production frontier, mainly in Europe, which are Switzerland, Luxembourg, Iraq, Norway, Denmark and the United Kingdom. The carbon emission efficiency of most countries is not ideal, being mainly concentrated in Asia and Africa, and has not achieved significant improvement over time. Asia has the lowest carbon emission efficiency. Mongolia, Ukraine, Iran, Angola, Belarus and Uzbekistan are the key governance areas for global energy conservation and carbon emissions reduction. (2) Developed countries have the much higher average carbon emission efficiency than developing countries. Combined with the industrial development stages of developed and developing countries, this is in line with the environmental Kuznets curve (EKC) hypothesis. The average carbon emission efficiency gap between developing and developed countries shows a trend of "first narrowing and then widening", which demonstrates that developing countries' reliance on energy input to boost their economies will improve carbon emission efficiency, but only temporarily. (3) Urbanization level, foreign trade and proportion of renewable energy effectively improve the carbon emission efficiency, while industrial structure and proportion of electricity users have an inhibitory effect on the carbon emission efficiency. Global low-carbon development should be hastened by strengthening international cooperation, optimizing industrial structure, promoting urbanization and foreign trade, and adjusting the energy structure.

Keywords: Carbon emission efficiency; Influencing factors; Spatiotemporal differentiation; Super-EBM model.