Spatial-Temporal Patterns and Driving Factors of Logistics Carbon Emissions: Case Study of Yangtze River Delta in China

Abstract

With the growing dependence of human beings on the logistics industry, the trend of logistics carbon emissions (LCEs) growth has become much more serious. To investigate the spatial-temporal pattern of LCEs as well as their driving factors, city-scale LCEs were calculated by combining them with nighttime light remote sensing data. In addition, a spatial panel data model was applied in the case of China’s Yangtze River Delta. The results showed that the overall LCEs performed as a rising trend during 2010–2019. The LCEs of the eastern cities and provincial capitals were significantly higher than those of other cities with obvious spatial agglomerations. For driving factors, the gross domestic product, population size, and proportion of tertiary industry all had significant positive influences on the LCEs. Overall, this study is of great practical significance to accurately obtain information on the spatial-temporal dynamics of LCEs at the city-level scale, so as to facilitate the differentiated implementation of carbon reduction measures.