Exploring the nonlinear and asymmetric influences of built environment on CO2 emission of ride-hailing trips
Exploring the nonlinear and asymmetric influences of built environment on CO2 emission of ride-hailing trips
复制标题
探索建筑环境对网约车出行二氧化碳排放的非线性和不对称影响
DOI：
10.1016/j.eiar.2021.106691
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发表时间：
2021-10-09
影响因子：
7.9
通讯作者：
Du, Huibin
中科院分区：
文献类型：
--
作者：
Gao, Jiong;Ma, Shoufeng;Du, Huibin
在许多城市出现的叫车服务被认为是减少对汽车的依赖和降低二氧化碳排放的一种方法。尽管有许多关于建筑环境对出行行为影响的研究，但网约车对碳排放的影响在很大程度上被忽视了。利用梯度提升决策树方法对成都市中国的数据进行处理，从分类水平上考察了建成环境对网约车出行碳排放的非线性影响。同时，这种影响的不对称性在几个时空语境中分别从起源地和目的地进行了探讨。结果表明，在建成区环境变量中，人口密度是预测碳排放的最关键因素，但存在门槛效应。如果考虑到不对称效应，始发站和终点站到地铁站的距离可能会对排放产生相反的影响。在早高峰时段，土地利用多样性与CO2排放呈“U”型关系，而在晚高峰时段则不同。道路密度对CO2排放的影响没有呈现出一致的趋势，但在起点和终点表现出不对称性。这些发现为网约车管理和可持续城市发展的政策制定提供了有用的投入。
Emerging in many cities, ride-hailing is recognized as an approach to reduce car dependence and to lower CO2 emissions. Despite a number of studies on the impact of the built environment on travel behavior, the impacts of ride-hailing on carbon emissions is largely overlooked. Using gradient boosting decision trees (GBDT) method to deal with the data from Chengdu, China, this study examines the nonlinear influence of built environment on carbon emissions of ride-hailing trips at a disaggregated level. Meanwhile, the asymmetry of this influence is explored at origin and destination in several spatiotemporal contexts. The results show that, among the built environment variables, population density is the most crucial factor in predicting carbon emission, however there is a threshold effect. The distance to the subway station at origin and destination may have an opposite effect on emissions when asymmetric effects are taken into consideration. There is a 'U' type relationship between land use diversity and CO2 emission at the morning peak hour while pattern is different at evening peak. The impact of road density on CO2 emission does not show a consistent trend however display the asymmetry at origin and destination. These findings provide useful inputs to policymaking for ride-hailing management and sustainable urban development.