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How does ridesplitting reduce emissions from ridesourcing? A spatiotemporal analysis in Chengdu, China

机译:如何互动地减少浪田的排放? 中国成都的时空分析

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摘要

Ridespitting, which enables riders with similar routes to share a ridesourcing trip, is a promising transportation technology to reduce traffic congestions and air pollutions. This study aims to explore how ridesplitting reduces emissions from ridesourcing based on GPS trajectory data from Didi Chuxing in Chengdu, China. First, this study quantifies the emission factors of both regular ridesourcing and ridesplitting trips to evaluate the emission reductions per ride-km from ridesplitting. The results show that the average emission reduction rates of CO2, CO, NOx, and HC are 28.7%, 32.5%, 27.7%, and 31.2%, respectively. Then, a spatiotemporal analysis of the emission reductions indicates that ridesplitting generally reduces more emissions around the expressways and during peak hours. Finally, a spatial error model is adopted to analyze the effects of travelrelated and built environment variables on emission reductions from ridesplitting. The trajectory overlapping rate of shared rides turns out to be the most important determinant for expanding the environmental benefits of ridesplitting.
机译:RideStites,它使具有类似路线的乘客来分享郊游之旅,是一种有前途的运输技术,可减少交通拥堵和空气污染。本研究旨在探讨如何根据中国成都迪ch的GPS轨迹数据减少跨阳离子的排放。首先,本研究量化了普通郊游和跨竞争行程的排放因子,以评估从互补的每千克的排放减排。结果表明,CO2,CO,NOx和HC的平均排放率分别为28.7%,32.5%,27.7%和31.2%。然后,对减排的时空分析表明,额外视频通常会减少高速公路周围的更多排放和高峰时段。最后,采用空间误差模型来分析旅行和建筑环境变量对互补的排放减排的影响。共享游乐设施的轨迹重叠率先成为扩大互补的环境效益的最重要的决定因素。

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