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

Author:

Zhu Sicong123,Qiao Yongdi1,Peng Wenjie1,Zhao Qi4,Li Zhen5,Liu Xiaoting67,Wang Hao7ORCID,Song Guohua1,Yu Lei8,Shi Lei9,Lan Qing2310

Affiliation:

1. Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, Beijing Jiaotong University, Haidian District, Beijing 100044, China

2. Hebei Higher Institute of Transportation Infrastructure Research, Development Center for Digital and Intelligent Technology Application, Cangzhou 061001, China

3. Cangzhou Intelligent Transportation Technology Innovation Center, Cangzhou 061001, China

4. The Department of Traffic Information and Control Engineering, North China University of Technology, No. 5, Jinyuanzhuang Road, Shijingshan District, Beijing 100144, China

5. College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China

6. Department of Ophthalmology, The First Affiliated Hospital, Jinan University, Guangzhou 510632, China

7. Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China

8. School of Transportation and Logistics Engineering, Shandong Jiaotong University, No. 5001 Haitang Road, Changqing District, Jinan 250357, China

9. Hebei Expressway Group Limited, No. 136, Yellow River Avenue, Gaoxin District, Shijiazhung 050031, China

10. College of Transportation Engineering, Hebei University of Water Resources and Electric Engineering, No. 1 Chongqing Road, Cangzhou 061001, China

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.

Funder

Xuchang regional government and institution

Hebei Education Department

Hebei Provincial Transport Department

Hebei Province Talent Project

Transportation Bureau of Hejian City

Fundamental research funds for the central universities of Beijing Jiaotong University

University-Industry Collaborative Education Program

Publisher

MDPI AG

Subject

Atmospheric Science,Environmental Science (miscellaneous)

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