This study aims to explore the influencing factors of the spatial and temporal distribution of carbon emissions from the logistics industry in Northwestern provinces of China, so as to provide a policy basis and theoretical guidance for the logistics industry in these provinces to achieve carbon emission reduction goals.
Based on the calculation of carbon emissions from the logistics industry in Northwestern provinces of China during 2013–2023, this study analyzes their spatial and temporal differentiation characteristics. From the logistics-economy-society dimension, the Logarithmic Mean Divisia Index (LMDI) and Multi-Regional (M-R) decomposition models are used to investigate the influencing factors of carbon emissions.
The results indicate that economic development and logistics industry structure promote logistics carbon emissions, while energy intensity, energy structure, and employment scale restrain them. Temporally, total carbon emissions fluctuated upward from 2013 to 2019, dropped sharply in 2020, rose slightly in 2021, and then declined gradually. Spatially, in 2023, carbon emissions in Xinjiang and Gansu exceeded the regional average due to high energy intensity and unreasonable logistics structure; Xinjiang was also affected by its large employment scale. Carbon emissions in Shaanxi, Qinghai and Ningxia were below the regional average.
This study breaks through the application boundaries of the LMDI and M-R decomposition models and extends them to the regional industry research level; it reveals the specific causes of spatial and temporal differences in carbon emissions from the logistics industry in Northwestern provinces of China.
