transportation carbon intensity, spatial correlation, spatial econometric analysis, complex network theory, social network analysis, Technology

It is of great significance to understand the variations and spatial correlation of carbon intensity in transportation industry for achieving the goals of energy conservation, emission reduction and "dual carbon". With the help of spatial econometric analysis and complex network theory, this paper quantifies the transportation carbon intensity of provinces in China from 2009 to 2021, analyzes its spatial and temporal characteristics by gini coefficient and kernel density estimation, and studies the structural evolution of spatial correlation networks for every provinces′ transportation carbon intensity by using improved gravity model and network characteristic indices. The results show that: 1)The carbon intensity of transportation in China is decreasing year by year, and the rate of decrease is fluctuating. 2)The unevenness of carbon intensity in transportation among various provinces is gradually decreasing, while the differences in carbon intensity within each region are distinct, with the greatest disparities occurring among the provinces in North China. 3) The spatial correlation of carbon intensity shows a complex network structure, and the center of the network gradually changes from Tianjin to Shanghai. 4) The eastern coastal regions are close to the center of this network, featuring complex relationships and abundant information resources. The results of this study can provide some references for competent departments, offering theoretical guidance for assessing the emission reduction intensity of various provinces and cities and for formulating targeted collaborative emission reduction plans.