Spatial and temporal evolution characteristics and spillover effects of China's regional carbon emissions

• Published in: Journal of environmental management Vol. 325; p. 116423
• Main Authors: Zhou, Kaile, Yang, Jingna, Yang, Ting, Ding, Tao
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01-01-2023
• Subjects: Carbon emission reduction; Carbon emissions; Spatial econometric model; Spatial spillover effect; Spatial econometric model; Carbon emissions; Spatial spillover effect; Carbon emission reduction
• ISSN: 0301-4797; 1095-8630
• DOI: 10.1016/j.jenvman.2022.116423

China's carbon emissions account for approximately a quarter of the world's total greenhouse gas emissions. In 2020, China's fossil fuels accounted for approximately 85% of the primary energy demand, with coal alone accounting for 60%. Considering the severe global warming situation, it is necessary to reveal the spatial and temporal differences and analyze the spillover effects of carbon emissions between regions. In this study, a positive and significant spatial correlation between regional carbon emissions in China was found using an exploratory spatial data analysis. The spatial Durbin model was then utilized to explore the direct and spillover effects of factors that included economic growth, the energy intensity, and the level of technological innovation on regional carbon emissions. Whether a direct effect or a spillover effect, economic growth and improvements in the regional levels of technological innovation had significant inhibitory effects on carbon emissions both in the long term and in the short term. Specifically, an increase of 1% in the level of technological innovation led to a reduction of approximately 0.17% in the region's carbon emissions. However, a growth in the energy intensity will increase carbon emissions. In addition, an increase in the technological input intensity will lead to an increase in carbon emissions in local regions. However, an increase in neighboring regions will restrain carbon emissions in a local region. Based on these findings, it is recommended that the government accelerate regional innovation synergies and increase investment in clean energy technologies.
•A positive spatial correlation between regional carbon emissions in China.•Direct and spillover effects of influence factors are explored.•Regional technology innovation level has inhibitory effect on carbon emissions.•Increase in neighboring regions will restrain carbon emissions in the local region.