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Structural decomposition of heavy-duty diesel truck emission contribution based on trajectory mining

文献类型：期刊论文

作者Cheng, Shifen1,2; Zhao, Yibo1,2; Zhang, Beibei1,2; Peng, Peng1,2; Lu, Feng1,2
刊名JOURNAL OF CLEANER PRODUCTION
出版日期2022-12-20
卷号380页码:12
关键词Heavy-duty diesel trucks Traffic emissions High -resolution emission inventory Emission contribution Trajectory mining
ISSN号0959-6526
DOI10.1016/j.jclepro.2022.135172
通讯作者Lu, Feng(luf@lreis.ac.cn)
英文摘要Nonlocal heavy-duty diesel trucks (HDDTs) transported across regions cause serious pollution in local atmo-spheric environments. However, previous studies misestimate the number of nonlocal HDDTs in the region and cannot identify the origin of the HDDTs on unmonitored road segments, resulting in unclear spatiotemporal distribution patterns of the emission contributions. This study therefore inferred the origins of HDDTs using trajectory data mining and obtained an accurate decomposition of the emission contribution from nonlocal HDDTs, from the single-vehicle-based HDDT emission inventory. A case study is conducted in Beijing. The results showed that the emission contribution of HDDTs from other regions to Beijing has a significant aggregation pattern and power function relationship with distance. The majority of nonlocal HDDTs in Beijing originate from Hebei and Tianjin and have the largest interaction intensity with Beijing, contributing 43% of the traffic counts and 37.05% of the emission intensity of HDDTs in Beijing. Temporally, the emission contribution of HDDTs from different regions has daily periodicity and is affected by major festivals. Nonlocal HDDTs dominate night-time emissions, which contributed 69.94% of total emissions at 1:00 a.m. The spatial heterogeneity of the emission contribution structure is mainly attributable to the traffic volume, highway freight ton-kilometers, and tertiary industry proportion. These findings extend the scientific understanding of the emission contributions of HDDTs and provide an important scientific basis for future strategies related to the control and management of emissions from HDDTs.
WOS关键词VEHICLE EMISSION ; TRAFFIC EMISSIONS ; AIR-POLLUTION ; INVENTORY ; TRANSPORTATION ; IMPACT ; PROVINCE ; LEVEL ; CHINA ; CITY
资助项目National Natural Science Foundation of China[42101423] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA23010202] ; China Postdoctoral Science Foundation[2020M680655] ; China Postdoctoral Science Foundation[2021T140656]
WOS研究方向Science & Technology - Other Topics ; Engineering ; Environmental Sciences & Ecology
语种英语
WOS记录号WOS:000915602500001
出版者ELSEVIER SCI LTD
资助机构National Natural Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences ; China Postdoctoral Science Foundation
源URL[http://ir.igsnrr.ac.cn/handle/311030/189684]  
专题中国科学院地理科学与资源研究所
通讯作者Lu, Feng
作者单位1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
推荐引用方式
GB/T 7714		 Cheng, Shifen,Zhao, Yibo,Zhang, Beibei,et al. Structural decomposition of heavy-duty diesel truck emission contribution based on trajectory mining[J]. JOURNAL OF CLEANER PRODUCTION,2022,380:12.
APA Cheng, Shifen,Zhao, Yibo,Zhang, Beibei,Peng, Peng,&Lu, Feng.(2022).Structural decomposition of heavy-duty diesel truck emission contribution based on trajectory mining.JOURNAL OF CLEANER PRODUCTION,380,12.
MLA Cheng, Shifen,et al."Structural decomposition of heavy-duty diesel truck emission contribution based on trajectory mining".JOURNAL OF CLEANER PRODUCTION 380(2022):12.

入库方式： OAI收割

来源：地理科学与资源研究所

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