| Environmental problems caused by climate warming are increasing,and the environmental problems are mainly caused by the sharp rise of carbon emissions.The Double Carbon Project was proposed to better respond to carbon emission reduction actions.Various industries in China have also acted in response to the national call to find,plan and develop suitable emission reduction programs.The logistics industry is an important part of the tertiary industry,driving the rise of the national economy.The development of green logistics is crucial for China to achieve carbon emission reduction and develop a low-carbon economy.Based on this,this paper takes 30 provinces in China(excluding Tibet and Hong Kong,Macao and Taiwan)as the research object,and uses the theory of sustainable development as the theoretical guide to explore the characteristics of spatial and temporal changes in the carbon emission efficiency of China’s logistics industry and its influencing factors.Firstly,based on the energy consumption data of each region in 30 provinces,the carbon emission and intensity of the logistics industry in each province from 2005 to2020 were measured using the carbon emission coefficient method.Secondly,the carbon emission efficiency of logistics industry is measured based on the three-stage DEA model to provide data support for exploring the spatial distribution characteristics and influencing factors of carbon emission efficiency in each province.Finally,the spatio-temporal geographically weighted regression model is used to systematically analyze the factors influencing the carbon emission efficiency of the logistics industry in each region.Comprehensive research process,the results show that:(1)The total carbon emission of China’s logistics industry shows a stepwise increase,with a total increase of 415,492,000 t.During the study period,the carbon emission intensity of the logistics industry generally shows a decreasing trend in the time scale;in the spatial scale,the carbon emission intensity of the logistics industry in the western region is significantly higher than that in other regions.(2)In the whole study area,the carbon emission efficiency values of logistics industry in Shanghai,Hebei,Fujian and Anhui are 1,0.999,0.998 and 0.996,respectively,and the efficiency of all four provinces is at the frontier level.This means that these regions have higher carbon emission efficiency in the logistics industry compared to other provinces and show lower carbon emission levels.(3)For the carbon emission efficiency of the logistics industry between 2005 and2020,the standard deviation of the ellipse along the X-axis and the standard deviation along the Y-axis in 2020 are 1001287.852 km and 1155370.620 km respectively,showing a trend of "circularization" in the spatial distribution.This indicates that the carbon emissions from the logistics industry in different regions are not as high as they should be.This indicates that the difference of carbon emission efficiency of logistics industry in different regions gradually decreases and shows more balanced distribution characteristics.(4)There is spatial and temporal heterogeneity in the effects of GDP per capita,industrial structure,labor input,energy structure and science and technology innovation capacity on the carbon emission efficiency of logistics industry in different time and regions.Specifically,the effect of GDP per capita on carbon emission efficiency of logistics industry is most significant in Northwest and Northeast China,while the negative inhibitory effect of industrial structure on carbon emission efficiency of logistics industry is mainly concentrated in Northeast China.In addition,the positive contribution of labor input to the carbon emission efficiency of logistics industry is mainly reflected in the eastern coastal regions,while the factors of energy structure and scientific and technological innovation ability show positive effects on the carbon emission efficiency of logistics industry in most regions.Finally,the full text is summarized to provide theoretical support for finding a sustainable development path for the logistics industry and to propose targeted carbon emission reduction countermeasures. |
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