中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
A high-resolution emissions inventory and its spatiotemporal pattern variations for heavy-duty diesel trucks in Beijing, China

文献类型:期刊论文

作者Cheng, Shifen3,4; Lu, Feng1,2,3,4; Peng, Peng3,4
刊名JOURNAL OF CLEANER PRODUCTION
出版日期2020-03-20
卷号250页码:14
关键词Heavy-duty diesel trucks Traffic emissions Vehicle emissions inventory Spatiotemporal patterns
ISSN号0959-6526
DOI10.1016/j.jclepro.2019.119445
通讯作者Lu, Feng(luf@lreis.ac.cn)
英文摘要Heavy-duty diesel trucks (HDDTs) cause serious pollution, and a high spatiotemporal resolution emissions inventory is a valuable assessment tool for use in quantitatively understanding the emissions mechanisms of HDDTs and scientifically developing associated emissions reduction measures. This study aims to comprehensively utilize multi-source spatiotemporal data on transportation-including fine-scale trajectories of HDDTs, road traffic conditions, and attribute data for road networks and HDDTs-supplemented by relatively mature vehicle pollution emissions models to establish a high spatiotemporal resolution emissions inventory for HDDTs in Beijing using a bottom-up approach. Spatial statistical techniques, including spatial autocorrelation, high/low clustering, and outlier analysis, are also used to explore the spatiotemporal distribution pattern of pollution emissions in the city. The results showed the following: (1) spatially, nitrogen oxide (NOx) and particulate matter (PM) emission hotspots spread from the Beijing sixth-ring roads to the fourth-ring roads from daytime to nighttime. The road segments with high emissions intensities have pronounced spatial agglomeration effects at night, but these are scattered during daytime. (2) Temporally, total HDDT NOx emissions are consistent with the traffic volume trends and are lower during major festivals. The highest NOx emissions occur at intercity highways, and this reflects the severe impact that intercity freight traffic has on air quality. The dominant HDDT NOx emissions are from vehicles belonging to the China 4 emissions standard. (3) NOx and PM emissions have a significant spatial autocorrelation and exhibit high-value clustering as a whole. (4) At different time intervals, the distribution of High-High/Low-Low clustering and outliers of NOx and PM in the road network is consistent with the spatial distribution of the pollutant emission intensity. The High-Low outlier is mainly distributed within the fourth-ring roads, and the number gradually reduces between night and day. The Low-High outlier is affected by the heterogeneous distribution of HDDTs and exhibits discontinuous distribution characteristics. Our results effectively evaluate Beijing's emissions control measures for HDDTs and provide a scientific decision-making basis for developing targeted emission reduction strategies for HDDTs. (C) 2019 Elsevier Ltd. All rights reserved.
WOS关键词VEHICLE EMISSIONS ; AIR-POLLUTION ; TRAFFIC DATA ; POLLUTANTS ; MODEL ; SCALE
资助项目Strategic Priority Research Program of the Chinese Academy of Sciences[XDA23010202] ; Regional Key Project under Science and Technology Service Network Initiative of Chinese Academy of Sciences[KFJ-STS-QYZD-xxx]
WOS研究方向Science & Technology - Other Topics ; Engineering ; Environmental Sciences & Ecology
语种英语
WOS记录号WOS:000508829800005
出版者ELSEVIER SCI LTD
资助机构Strategic Priority Research Program of the Chinese Academy of Sciences ; Regional Key Project under Science and Technology Service Network Initiative of Chinese Academy of Sciences
源URL[http://ir.igsnrr.ac.cn/handle/311030/131557]  
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.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China
2.Fuzhou Univ, Acad Digital China, Fuzhou, Fujian, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
推荐引用方式
GB/T 7714
Cheng, Shifen,Lu, Feng,Peng, Peng. A high-resolution emissions inventory and its spatiotemporal pattern variations for heavy-duty diesel trucks in Beijing, China[J]. JOURNAL OF CLEANER PRODUCTION,2020,250:14.
APA Cheng, Shifen,Lu, Feng,&Peng, Peng.(2020).A high-resolution emissions inventory and its spatiotemporal pattern variations for heavy-duty diesel trucks in Beijing, China.JOURNAL OF CLEANER PRODUCTION,250,14.
MLA Cheng, Shifen,et al."A high-resolution emissions inventory and its spatiotemporal pattern variations for heavy-duty diesel trucks in Beijing, China".JOURNAL OF CLEANER PRODUCTION 250(2020):14.

入库方式: OAI收割

来源:地理科学与资源研究所

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