Reinvestigating the Spatiotemporal Differences and Driving Factors of Urban Carbon Emission in China

• Published in: Frontiers in Environmental Science
• Main Authors: Ke-Liang Wang, Ru-Yu Xu, Fu-Qin Zhang, Yun-He Cheng
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2022-04-01
• Subjects: urban carbon emissions; spatiotemporal differences; driving factors; geographical detector model; interaction
• Online Access: https://www.frontiersin.org/articles/10.3389/fenvs.2022.880527/full

This study analyzed the spatiotemporal differences and driving factors of carbon emission in China’s prefecture-level cities for the period 2003–2019. In doing so, we investigated the spatiotemporal differences of carbon emission using spatial correlation analysis, standard deviation ellipse, and Dagum Gini coefficient and identified the main drivers using the geographical detector model. The results demonstrated that 1) on the whole, carbon emission between 2003 and 2019 was still high, with an average of 100.97 Mt. Temporally, carbon emission in national China increased by 12% and the western region enjoyed the fastest growth rate (15.50%), followed by the central (14.20%) and eastern region (12.17%), while the northeastern region was the slowest (11.10%). Spatially, the carbon emission was characterized by a spatial distribution of “higher in the east and lower in the midwest,” spreading along the “northeast–southwest” direction. 2) The carbon emission portrayed a strong positive spatial correlation with an imbalance polarization trend of “east-hot and west-cold”. 3) The overall differences of carbon emission appeared in a slow downward trend during the study period, and the interregional difference was the largest contributor. 4) Transportation infrastructure, economic development level, informatization level, population density, and trade openness were the dominant determinants affecting carbon emission, while the impacts significantly varied by region. In addition, interactions between any two factors exerted greater influence on carbon emission than any one alone. The findings from this study provide novel insights into the spatiotemporal differences of carbon emission in urban China, revealing the potential driving factors, and thus differentiated and targeted policies should be formulated to curb climate change.