Analysis of Factors Influencing Carbon Emissions from Transportation Considering City Classification
In order to analyze the carbon emission pattern of urban transportation,this paper selects six indi-cators based on the expanded STIRPAT model combined with random forest feature screening as influencing fac-tors on carbon emissions from urban transportation:the percentage of new energy vehicle sales,PGDP,the number of public charging posts,the total value of tertiary industry,the number of public bus(electric)operations,and the amount of urban road freight.The carbon emissions from urban transportation of 130 cities are measured by the published carbon emission factors,and the carbon emission ranking of urban transportation is classified ac-cording to the measured carbon emissions using the classification of carbon emissions from urban transportation.The RF-GS classification prediction model was used to forecast the number of carbon emission city classes using the index data of each city from 2017-2022,while the influencing factors were analyzed by adjusting the annual growth rate of the influencing factors of transportation dimension.The results show that:the number of cities in low classes of carbon emissions from urban transportation increases 8.99％when the annual growth rate of the percentage of new energy vehicles increases from 50％to 70％;when the annual growth rate of public charging pile construction decreases from 55％to 40％,the number of cities in low classes of carbon emissions from urban transportation decreases by 14.61％;when the annual growth rate of road freight volume decreases from 5％to 3％,the number of cities in the same classes increases by 3.37％.
carbon emissions from urban transportationSTIRPAT modelclassification predictionrandom forest
国家科技期刊平台
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万方数据
