Shuo Yang , Leyu Zhou , Chang Liu , Shan Sun , Liang Guo , Xiaoli Sun
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引用次数: 0
摘要
虽然已有研究探讨了建筑环境(BE)和交通领域的干预措施,以减少出行碳排放(TCE),但规划者仍难以确定最有效的干预单位、识别关键变量并确定其最佳值。本研究采用极端梯度提升(XGBoost)模型创建了一个多尺度比较框架,从而弥补了这一不足。研究发现,建筑环境与旅行相关碳排放之间的关系因建筑环境测量单位的分区和规模而异。不同地理单元对旅行相关碳排放的解释力也不同,其中居民 15 分钟步行距离缓冲区对旅行相关碳排放的解释力最强。大多数变量与 TCE 呈非线性关系,而且 BE 属性与 TCE 之间关联的精确阈值已被量化。基于这些研究结果,我们为减少TCE的BE干预措施提供了精确而细致的见解。
Examining multiscale built environment interventions to mitigate travel-related carbon emissions
While established studies have explored interventions in the built environment (BE) and transportation sector to mitigate travel carbon emissions (TCE), planners still struggle to determine the most effective units of intervention, identify key variables, and determine their optimal values. This study addresses the gap by employing the extreme gradient boosting (XGBoost) model to create a multi-scale comparative framework. This study revealed that the relationship between the built environment and travel-related carbon emissions varies depending on the zoning and scale of the BE measurement unit. The explanatory power of TCE varies across different geographic units, with the 15-min walk distance buffer of residents being the most effective in explaining TCE. Most variables were nonlinearly associated with TCE, and the precise threshold of the association between BE attributes and TCE was quantified. Based on these findings, we provide precise and nuanced insights into BE interventions to reduce TCE.
期刊介绍:
A major resurgence has occurred in transport geography in the wake of political and policy changes, huge transport infrastructure projects and responses to urban traffic congestion. The Journal of Transport Geography provides a central focus for developments in this rapidly expanding sub-discipline.