中国省际物流业碳排放的空间效应及其传导机制

物流业是我国仅次于工业、建筑业的第三大碳排放源，研究省际物流资源要素的空间效应及其传导机制可以为物流业低碳转型发展提供科学依据。运用GeoDa软件分析我国2013—2020年30个省物流业碳排放时空关联性及其局部空间差异波动性，将STIRPAT模型和EKC模型相结合探究我国省际物流业碳排放影响因素对碳排放的空间效应并明晰其传导机制。结果表明，我国物流业碳排放量呈现出“东高西低”的空间分布特征；省际物流业碳排放聚集分布的二元结构明显，呈现“高—高”和“低—低”集聚为主的空间分布特征；我国省际物流业碳排放存在空间溢出性特征，对本地区物流业碳排放产生正向促进作用的影响因素由强至弱依次为物流业的能源消耗量、产业规模、基础设施，毗邻地区对其产生正向影响的因素是物流业基础设施；物流业基础设施在直接效应与间接效应下对碳排放均产生显著的正向影响，物流业的产业规模和能源消耗量仅在直接效应下对碳排放产生正向影响。我国物流业碳排放的空间集聚、区域差异的形成与演变是在省际物流业的产业规模、能源消耗量、基础设施等多种物流业资源要素协同作用下产生的结果，据此提出省际物流业“协同降碳”建议，推动我国物流业的低碳转型。

Spatial effects and transmission mechanism of carbon emissions from interprovincial logistics industry in China

The logistics industry is the third largest carbon emission source after the industry and construction industry in China. Studying the spatial effects and transmission mechanism of resource elements related to inter-provincial logistics can provide a scientific basis for the low-carbon transformation development of the logistics industry. GeoDa software was used to analyze the spatial-temporal correlation and the volatility of local spatial differences in carbon emissions from the logistics industry in 30 provinces from 2013 to 2020. STIRPAT model and EKC model were combined to explore the spatial effects of influencing factors on carbon emissions from the logistics industry in China and clarify the transmission mechanism. The results showed that the carbon emissions of China's logistics industry presented the spatial distribution characteristics of “high in the east and low in the west”. The dual structure of carbon emission concentration distribution in the provincial logistics industry was obvious, showing the spatial distribution characteristics of “high-high” and “low-low” concentration. The carbon emission of China's inter-provincial logistics industry had the characteristics of spatial spillover. The influencing factors that positively promoted the carbon emission of the logistics industry in the region from strong to weak were energy consumption, industrial scale, and infrastructure of the logistics industry, and the factors that havd a positive impact on the carbon emission of the logistics industry in the adjacent areas were infrastructure of the logistics industry; under both direct and indirect effects, logistics infrastructure had a significant positive impact on carbon emissions, while the industrial scale and energy consumption of logistics had a positive impact on carbon emissions only under direct effects. The spatial agglomeration of carbon emissions and the formation and evolution of regional differences in China’s logistics industry were the result of the synergistic effect of various logistics resource factors such as the industrial scale, energy consumption and infrastructure of the inter-provincial logistics industry. Accordingly, the suggestion of “collaborative carbon reduction” is put forward to promote the low-carbon transformation of China's logistics industry.