Spatiotemporal variations & driving mechanisms of tourism transport carbon emissions in coastal China

This paper employs a bottom-up methodology to estimate tourism-related transportation carbon emissions in China's coastal regions from 2006 to 2023, analyzing their spatiotemporal evolution characteristics across multiple scales. It further extends the LMDI model from both intra- and inter-sectoral perspectives and constructs an M-R spatial decomposition model to comparatively analyze factor-driven contributions and the drivers of spatial disparities. Key findings show: (1) the centroid of emissions in coastal areas has shifted southeastward, with greater changes in the south; (2) Per capita wealth effect (Δ Cl) is the main driver of emission growth, while transportation intensity is the key restraining factor; (3) eight provinces, including Guangdong and Shandong, exceed the average emission level, with Jiangsu showing the largest deviation.