Driving forces of temporal-spatial differences in CO₂ emissions at the city level for China's transport sector

The paper aims to investigate the influencing factors that drive the temporal and spatial differences of CO₂ emissions for the transportation sector in China. For this purpose, this study adopts a Logistic Mean Division Index (LMDI) model to explore the driving forces of the changes for the transport sector's CO₂ emissions from a temporal perspective during 2000-2017 and identifies the key factors of differences in the transport sector's CO₂ emissions of China's 15 cities in four key years (i.e., 2000, 2005, 2010, and 2017) using a multi-regional spatial decomposition model (M-R). Based on the empirical results, it was found that the main forces for affecting CO₂ emissions of the transport sector are not the same as those from temporal and spatial perspectives. Temporal decomposition results show that the income effect is the dominant factor inducing the increase of CO₂ emissions in the transport sector, while the transportation intensity effect is the main factor for curbing the CO₂ emissions. Spatial decomposition results demonstrate that income effect, energy intensity effect, transportation intensity effect, and transportation structure effect are important factors which result in enlarging the differences in city-level CO₂ emissions. In addition, the less-developed cities and lower energy efficiency cities have greater potential to reduce CO₂ emissions of the transport sector. Understanding the feature of CO₂ emissions and the influencing factors of cities is critical for formulating city-level mitigation strategies of the transport sector in China. Overall, it is expected that the level of economic development is the main factor leading to the differences in CO₂ emissions from a spatial-temporal perspective.