| Theoretical research shows that the transportation sector is one of the important sources of greenhouse gas production.According to statistics,the carbon emissions generated by the transportation sector account for more than 25% of the total social carbon emissions.With the growing scale of China’s transportation industry,the energy consumption and greenhouse gas emissions generated by the transportation industry are increasing year by year.How to effectively reduce the impact of transportation carbon emissions on the environment has become a key issue in the construction of ecological civilization.In order to achieve China’s low-carbon emission reduction goals,the state has issued a series of low-carbon emission reduction policies.However,existing theoretical researches use actual monitoring data to measure transportation carbon emissions and the related research on transportation carbon emission network structure features is relatively scarce There is still insufficient support for transportation low-carbon emission reduction policies.To this end,this paper proposes a method for calculating the carbon emissions of the transportation industry using actual detection data and further understanding its spatial differentiation characteristics,identifying key nodes in the transportation carbon emission network,with a view to formulating transportation low-carbon emission reduction areas Differentiation strategies provide theoretical support.First,the thesis defines related concepts of carbon emissions and transportation carbon emissions,and further systematically combs the three theories of low-carbon transportation theory,social network analysis theory,and spatial interaction theory,and comprehensively analyzes the path planning theory The Floyd algorithm provides a theoretical basis for the research on the spatial differentiation characteristics of transportation carbon emissions and the characteristics of network structure.Secondly,to address the shortcomings of the “top-down” and “bottom-up” methods proposed by the IPCC,which rely heavily on statistical data,the highway toll data actually monitored by Yunnan Province in August 2017 were used to “bottom-up” Improvement of transportation carbon emission calculation method.The system builds a microscopic transportation carbon emission calculation model based on highway toll data.Taking Yunnan Province as an example,the carbon emissions of passenger and freight transportation in Yunnan Province are calculated from the spatial scale of the city and county.The research results show that the total carbon emissions of passenger transportation in Yunnan Province are generally higher than the total carbon emissions of freight transportation.(1)At the urban spatial scale,regions with high total carbon emissions from passenger and freight transportation are mainly concentrated in the urban agglomerations in central Yunnan,and the carbon emissions from passenger transportation and carbon emissions from freight transportation are spatially synchronized.(2)The local autocorrelation of passenger and freight transportation carbon emissions at the municipal spatial scale exhibits a “high-high” clustering characteristic with Kunming at the core,and the passenger and freight transportation carbon emissions at the county spatial scale both present Kunming As the center,the “central clustering,peripheral random” clustering feature.Then,based on the calculated traffic carbon emissions at the spatial scale of the city and county,the Global Moran’s I index and the LISA aggregation map are used to compare the passenger transport and the spatial The spatial differentiation characteristics of freight transport carbon emissions are analyzed.Research indicates:(1)The global autocorrelation characteristics of transportation carbon emissions have a scale effect.The carbon emissions of passenger and freight transportation at the spatial scale of the city are randomly distributed in space,and do not have the spatial autocorrelation characteristics,but the carbon emissions of passenger and freight transportation at the spatial scale of the county There is a significant spatial autocorrelation characteristic in space,and the positive correlation of county passenger transportation carbon emissions is stronger than that of freight transportation carbon emissions.(2)From the perspective of local spatial autocorrelation,the carbon emissions of passenger and freight transportation at the spatial scale of the city are spatially exhibiting a “high-high” agglomeration feature with Kunming as the core,and cities in the central Yunnan urban agglomeration adjacent to Kunming The difference in carbon emissions from transportation between Kunming and Kunming is relatively small;the carbon emissions from passenger and freight transportation at the spatial scale of the county are spatially clustered with Kunming as the center and “central agglomeration,random perimeter”.Furthermore,based on the theory of social network analysis,the construction method of transportation carbon emission connection network is proposed,and the carbon emission network of passenger and freight transportation at the spatial scale of the municipal and county regions in Yunnan Province is constructed.In this aspect,the overall structural characteristics of the transportation carbon emission network are analyzed,and then the node importance of the transportation carbon emission network is analyzed from two aspects: line connection strength and point connection strength.Research indicates:(1)At the level of the transport carbon emission network structure,the central Yunnan urban agglomeration occupies a central position in the transportation carbon emission network at the municipal spatial scale,and the counties under the jurisdiction of Kunming City occupy the core position in the transportation carbon emission network at the county spatial scale.The transportation carbon emission network under the scale is the largest in urban sub-cluster in western Yunnan,but Kunming City and its counties and districts play an important role in the transportation carbon emission connection of agglomeration sub-group,which is a large-scale agglomeration sub-group Bridge of communication between nodes.(2)In terms of the connection intensity of the transportation carbon emission network,Kunming-Qujing City,Kunming City-Dali Prefecture are the main communication channels in the transportation carbon emission network at the city spatial scale;Dali City-Xishan District,Xishan District-Xiangyun County are the county space The main link in the transportation carbon emission network under the scale.The nodes in the transportation carbon emission network at the municipal spatial scale are mainly internal transportation carbon emissions and inflow and outflow carbon emissions.the nodes at the county spatial scale are mainly inflow and outflow carbon emissions.Finally,combined with the spatial differentiation characteristics and network structure characteristics of transportation carbon emissions in Yunnan Province,the countermeasures and suggestions for low carbon emission reduction in transportation in Yunnan Province are proposed. |
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