[Spatiotemporal Characteristics and Driving Factors of Transportation Carbon Emissions in the Yellow River Basin]

As the "dual carbon" goals steadily advance， investigating the characteristics and driving factors of transportation carbon emissions in the Yellow River Basin is of great significance for promoting low-carbon transition and high-quality development. Based on transportation carbon emission data of 64 prefecture-level cities （states and leagues） in the basin from 2010 to 2022， we comprehensively applied spatial autocorrelation analysis， standard deviational ellipse， optimal parameter geographical detector （OPGD）， and geographically and temporally weighted regression （GTWR） to explore the spatio-temporal patterns and driving mechanisms of transportation carbon emissions. The findings reveal that： ① Transportation carbon emissions in the Yellow River Basin showed an increasing trend， with a spatial pattern of "high in the east， low in the west." The centroid of the standard deviational ellipse consistently remained in Changzhi City while shifting southeastward. ② OPGD identified freight volume， population size， urbanization level， and openness level as the primary driving factors， with interactions primarily exhibiting nonlinear enhancement and bifactorial enhancement. ③ GTWR results showed that freight volume， population size， and urbanization had significant positive driving effects on transportation carbon emissions in most cities， while the openness level demonstrated a negative inhibitory effect. Accordingly， we propose establishing a cross-regional carbon trading mechanism， optimizing urban spatial layouts， and advancing intelligent transportation systems， which could provide a scientific basis for reducing transport carbon emissions in the Yellow River Basin.