Surrogate-Assisted Fine Particulate Matter Exposure Assessment in an Underground Subway Station

Liyang Liu, Hui Liu and Yiming Ma
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Liyang Liu: School of Architecture and Urban Planning, Huazhong University of Science and Technology, Wuhan 430074, China
Hui Liu: School of Architecture and Urban Planning, Huazhong University of Science and Technology, Wuhan 430074, China
Yiming Ma: State Key Laboratory of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China

IJERPH, 2022, vol. 19, issue 4, 1-25

Abstract: With the increase in subway travelers, the air quality of underground enclosed spaces at subway stations has attracted much more attention. The study of pollutants exposure assessment, especially fine particulate matter, is important in both pollutant control and metro station design. In this paper, combining pedestrian flow analysis (PFA) and computational fluid dynamics (CFD) simulations, a novel surrogate-assisted particulate matter exposure assessment method is proposed, in which PFA is used to analyze the spatial-temporal movement characteristics of pedestrians to simultaneously consider the location and value of the pedestrian particulate generation source and their exposure streamline to particulate matter; the CFD model is used to analyze the airflow field and particulate matter concentration field in detail. To comprehensively consider the differences in the spatial concentration distribution of particulate matter caused by the time-varying characteristics of the airflow organization state in subway stations, surrogate models reflecting the nonlinear relationship between simulated and measured data are trained to perform accurate pedestrian exposure calculations. The actual measurement data proves the validity of the simulation and calculation methods, and the difference between the calculated and experimental values of the exposure is only about 5%.

Keywords: computational fluid dynamics; particulate matter exposure; pedestrian flow analysis; surrogate model (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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