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An Experimental Framework of Particulate Matter Emission Factor Development for Traffic Modeling

Authors :
Sicong Zhu
Yongdi Qiao
Wenjie Peng
Qi Zhao
Zhen Li
Xiaoting Liu
Hao Wang
Guohua Song
Lei Yu
Lei Shi
Qing Lan
Source :
Atmosphere, Vol 14, Iss 4, p 706 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

To estimate traffic facility-oriented particulate matter (PM) emissions, emission factors are both necessary and critical for traffic planners and the community of traffic professionals. This study used locally calibrated laser-scattering sensors to collect PM emission concentrations in a tunnel. Emission factors of both light-duty and heavy-duty vehicles were found to be higher in autumn compared to summer. Based on this study’s data analysis, PM emissions, in terms of mass, have a strong seasonal effect. The study also conducted a PM composition test on normal days and during haze events. Preliminary results suggested that the transformation of gaseous tailpipe emissions to PM is significant within the tunnel during a haze event. This study, therefore, recommends locally calibrated portable devices to monitor mobile-source traffic emissions. The study suggests that emission factor estimation of traffic modeling packages should consider the dynamic PM formation mechanism. The study also presents traffic policy implications regarding PM emission control.

Details

Language :
English
ISSN :
20734433
Volume :
14
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Atmosphere
Publication Type :
Academic Journal
Accession number :
edsdoj.00e691a06a294aa0a19adf13e2e471f5
Document Type :
article
Full Text :
https://doi.org/10.3390/atmos14040706