Assessing Transport Carbon-Emission Inequality for Sustainable Regional Development: Spatiotemporal Evolution, Network Characteristics, and Driving-Factor Evidence Across Chinese Provinces

Achieving sustainable transport requires not only reducing aggregate emissions but also avoiding the concentration of emission burdens and transition costs in less-developed regions. Transport carbon-emission inequality therefore captures a distributional dimension of environmental and social sustainability. Using city-level transport emissions and population data for 31 mainland Chinese provincial-level regions from 2005 to 2024, this study develops an integrated framework for measuring and monitoring this inequality. Population-weighted within-province Gini coefficients and Theil T indices are combined with a modified-gravity interprovincial network, annual network analysis, CONCOR and core–periphery analysis, two-way fixed effects, and leakage-safe machine learning. The mean provincial Gini declined from 0.311 in 2005 to 0.287 in 2024, but inequality remained higher in the northwest and southwest and lower along the eastern coast. Full-network weight increased from 61.275 to 3336.040, retained directed edges increased from 174 to 217, and reciprocity rose from 0.471 to 0.571, indicating stronger interprovincial embeddedness and a greater need for coordinated governance. Population density was negatively associated with inequality across several specifications, although wild-cluster bootstrap inference did not confirm uniform significance. Under zero province-pair overlap, LightGBM achieved R2 = 0.241 with distance and 0.121 without distance; residual machine learning added no stable predictive information beyond the gravity benchmark. These findings contribute to sustainability research by quantifying the distributional fairness of transport decarbonization, providing a reproducible monitoring tool for identifying regional sustainability risks, and supporting differentiated mitigation responsibilities, sustainable transport infrastructure, and cross-provincial coordination.