Spatiotemporal evolution and spatial differentiation of carbon emission intensity in the Chinese transport sector

Accurately identifying the spatiotemporal evolution and spatial differentiation of carbon emission intensity in the transport sector is essential for formulating region-specific carbon reduction policies. From a static perspective, this study applies the Dagum Gini coefficient to examine spatial disparities and their sources of transport carbon emission intensity. From a dynamic perspective, the kernel density estimation method is used to depict its evolutionary trajectory, and the spatial Markov chain model is further introduced to capture locking effects and spillover effects of spatial variation. The empirical results indicate that (1) The carbon emission intensity of the transport sector in China presents an overall declining trend with significant spatial heterogeneity among provinces. Regional disparities have expanded, with the largest gap occurring between the eastern and western regions, where inter-regional differences contribute an average of 47.374% to the total disparity, representing the main source of variation. (2) The carbon emission intensity in the national, eastern, and central regions tends to converge gradually, while the western region shows a pattern of initial convergence followed by renewed divergence. Within each region, several provinces maintain carbon emission intensity levels significantly higher than the average, forming a clear spatial gradient structure. (3) The traditional Markov chain analysis reveals evident hierarchical solidification and club convergence in transport carbon emission intensity. The spatial Markov chain analysis further indicates that the state of neighboring regions exerts a significant influence on local transition probabilities, demonstrating strong spatial spillover and path dependence effects. Hypothesis testing confirms the necessity of incorporating spatial dependence into the analysis. Finally, regionally differentiated carbon reduction strategies are proposed based on the research findings.