Characteristics And Optimization Of Carbon Emissions Distribution For Residents’ Travel Within Rail Station Areas Under Public Transit Guidance

Urban residents’ carbon emissions from travel are significant,and the rational organization of rail transit station area space can effectively guide residents to use public transportation,thereby increasing the proportion of low-carbon travel among residents and reducing their carbon emissions.Currently,there is limited research on residents’ carbon emissions from travel within rail transit station areas.This study focuses on the station area spaces of 26 stations along Beijing Subway Line 6,which cover diverse urban functions and are highly representative.The aim is to explore the relationship between residents’ carbon emissions from travel within the station areas and functional elements,with the ultimate goal of further reducing residents’ carbon emissions from travel within these areas.Based on literature research,path planning API simulation of walking scenarios,and the definition of the rail transit station area as the area reachable on foot within 15 minutes from the station,this study selected density,functional mix,distance,and accessibility as the four functional elements within the station area.We surveyed travel data from residents in the station area of the 26 stations and calculated the carbon emissions from travel for each station.Cluster analysis combined with the elbow rule was used to divide the stations into three categories: low,medium,and high carbon emission stations,and the urban spatial distribution characteristics and functional element features of the three categories of stations were analyzed.Through a comprehensive use of correlation analysis,regression analysis,Euclidean distance method,and cluster analysis,this study explored the correlation and trends between residents’ carbon emissions from travel and functional elements within the station area,and determined the station area spaces suitable for low-carbon travel.The findings of this study are as follows:(1)Stations with low carbon emissions are mainly concentrated in the city’s core area,with high population and function density and high walking accessibility.The average walking distance between stations and different functions has small differences,while stations with high carbon emissions are located in the city’s outskirts,with low population and function density,low walking accessibility,and large differences in average walking distance between stations and different functions.(2)There is a significant negative correlation between residents’ carbon emissions from travel and the density of technology and cultural services functions within the station area.The inflection point is reached when the density is 28 per square kilometer,and the carbon emissions are the lowest.There is no significant correlation with the functional mix within the station area.There is a significant negative correlation between residents’ carbon emissions from travel and the average distance between the station and the road and transportation service functions within the station area.The inflection point is reached when the average distance is 710 meters,and the carbon emissions are the lowest.There is a significant negative correlation between residents’ carbon emissions from travel and the accessibility of living and leisure functions within 10 and 15 minutes of walking distance from the station.The inflection points are reached when the accessibility is 122 and 257,respectively,and the carbon emissions are the lowest.The station areas of Chaoyangmen,Dongsi,and Chegongzhuang were identified as low-carbon travel station areas.This study can help to reduce the carbon emissions from resident travel within the rail transit station area and provide new ideas for rail transit station area planning and urban low-carbon development.