[Analysis of the Temporal and Spatial Evolution of Carbon Emissions in the Provincial Logistic Industry in China from the Perspective of Shared Responsibility].

To reduce enterprise costs and achieve China's 2060 carbon neutrality goal at an early stage, this study analyzes in depth the spatial and temporal evolution of carbon emissions from the logistics industry in China's provinces and its influencing factors from the perspective of shared responsibility and on the basis of a multiregional input-output model. Using Moran's I index and local spatial autocorrelation model, we conducted a correlation analysis of logistics industry carbon emissions from 2012 to 2017. Additionally, based on the geographically weighted regression （GWR） model, we conducted an in-depth analysis of the spatiotemporal evolution and influencing factors of carbon emissions from the logistics industry across various provinces in China. The research results indicate that transportation carbon emissions exhibited significant spatial clustering characteristics. From 2012 to 2017, there were significant differences in the logistics industry carbon emissions among China's provinces, with a marked polarization. Provinces with higher economic levels had a lower proportion of carbon emissions associated with outbound trade and internal logistic industry demand. The R2 of the GWR model ranged from 0.625 715 to 0.765 095, whereas the R2 of the OLS model ranged from 0.476 970 to 0.716 380. Additionally, the AICc values of the GWR model were consistently lower than those of the OLS model, indicating that the GWR model provided a significantly better fit and could better explain the spatiotemporal heterogeneity between various influencing factors and logistics industry carbon emissions. The heterogeneity results of the influencing factors showed that logistic energy intensity, freight turnover, and logistic industry per capita GDP were significantly positively correlated with logistic industry carbon emissions. Therefore, the spatiotemporal heterogeneity of influencing factors on carbon emissions should be completely considered and differentiated emission reduction policies for different provinces should be formulated.