Nonlinear impacts of urban built environment on freight emissions

被引:0
|
作者
Peng, Tao [1 ,2 ]
Gan, Mi [1 ,2 ]
Yao, Zhu [1 ,2 ]
Yang, Xiaoyuan [1 ,2 ]
Liu, Xiaobo [1 ,2 ]
机构
[1] Southwest Jiaotong Univ, Sch Transportat & Logist, Chengdu, Peoples R China
[2] Southwest Jiaotong Univ, Natl Engn Lab Integrated Transportat Big Data Appl, Chengdu, Peoples R China
基金
中国国家自然科学基金;
关键词
Road transport; Built environment; Pollutant estimation; Nonlinear relationship; GREENHOUSE-GAS EMISSIONS; CO2; EMISSIONS; VEHICLE EMISSION; TIME-SERIES; INVENTORY; CARBON; MODEL; TRANSPORTATION; URBANIZATION; CONSUMPTION;
D O I
10.1016/j.trd.2024.104358
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Truck activities are the primary source of NOx and PM2.5 emissions in urban environments. This study harnesses a vast truck GPS dataset from Chengdu, employing the International Vehicle Emissions (IVE) model to estimate freight-related emissions and utilizing Gradient Boosting Regression Trees (GBRT) for an in-depth analysis of the impact of urban built environment factors-such as land use, traffic design, and density-on these emissions. It reveals significant correlations, highlighting that main road density, built-up area, industrial land ratio, and electricity consumption play pivotal roles in affecting freight pollution. Specifically, regions with main road density ranging from 5890 to 9560 m/km2 exhibit a marked increase in emissions. These insights provide robust support for the formulation of urban planning and traffic management strategies aimed at mitigating freight-related pollution, emphasizing the critical need to consider the urban built environment in policy-making processes.
引用
收藏
页数:19
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