接驳地铁站的共享单车碳减排效益评估

Assessing the carbon emission reduction benefits of bikeshare as a feeder mode for metro stations

为促进城市交通绿色低碳化发展,以接驳地铁站的共享单车为研究对象,量化共享单车在接驳地铁站时替代其他交通方式所降低的碳排放量,构建共享单车碳减排量时空矩阵,根据非负矩阵分解(Non-negative Matrix Factorization,NMF)识别共享单车碳减排情景,从多情景层面分析共享单车碳减排效益及其时空分布特征。结果显示:在全天层面,共享单车单次接驳的碳减排量为62.75 g;在多情景层面,共享单车碳减排效益存在时空差异;在时间上,各情景中碳减排量在不同时段达到峰值,早晚高峰期间的碳减排量占全天碳减排总量的45.26%;在空间上,各情景中均有明显的碳减排量高密度区域和次高密度区域,且不同情景之间这些区域的空间分布存在差异。研究成果可为城市交通减碳政策的制定提供参考。

In order to advance the growth of green and low-carbon urban transportation,we assessed the carbon emission reduction benefits of bikeshare as a feeder mode for metro stations by analyzing five workdays'worth of bikeshare order data and metro station data in Shenzhen.First,spatiotemporal constraints were used to analyze bikeshare behavior in connection to metro stations.Secondly,we quantified the carbon emissions reduced by substituting other transportation modes during the bikeshare-to-metro station connection process,based on the feeder distance and carbon reduction factor of the bikeshare.Thirdly,we constructed the spatiotemporal matrix of carbon emission reductions from bikeshare and identified carbon emission reduction scenarios using Non-negative Matrix Factorization(NMF).Finally,we analyzed the carbon emission reduction benefits of bikeshare,along with its spatial and temporal characteristics under each scenario,through time-series and kernel density analysis.The findings reveal that at the all-day level,a single feeder trip of bikeshare results in a carbon emission reduction of 62.75 g.At the multi-scenario level,the NMF algorithm identified five bikeshare carbon emission reduction scenarios,showcasing distinct spatial and temporal distribution differences in the carbon emission reduction benefits of bikeshare among these scenarios.In terms of time,carbon emission reductions within each scenario peak at various times throughout the day.Notably,the carbon emission reductions during the morning and evening peaks contribute to 45.26%of the total carbon emission reductions for the entire day.In terms of spatial analysis,distinct high-density and sub-high-density areas of carbon emission reductions are evident in each scenario,with variations in the spatial distribution of these areas between scenarios.These findings offer valuable insights into the carbon emission reduction benefits of bikeshare as a feeder mode for metro stations and serve as a reference for cities aiming to decarbonize urban transportation.