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

Liyang Liu,Hui Liu,Yiming Ma

doi:10.3390/ijerph19042295

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%.

Highlights

With the progress of economic construction and the increase of population density, subways have become one of the most important transportation modes
To deal with the above problem and facilitate the accurate air pollution exposure assessment in underground subway stations, this paper proposes a novel particulate matter exposure assessment method that combines the pedestrian flow analysis (PFA) and the computational fluid dynamics (CFD) method.PM2.5, one of the most harmful air pollutants, is selected as the research object
The CFD model is solved in two steps; the first step is to solve the airflow field without the particulate matter source

Summary

Introduction

With the progress of economic construction and the increase of population density, subways have become one of the most important transportation modes. With the dramatic increase in passenger flow and urban air pollution problems, the air quality and population health problems caused by various pollutants in underground subway stations deserve extensive attention [1,2]. Various types of particulate matter have been identified as one of the major air pollutants in the subways, those with a particle size less than 2.5 μm (PM2.5) can even enter the alveoli through the lower respiratory tract, causing respiratory diseases [4] and have been proven to be an important vector for viruses such as COVID-19 [5]. Research on the fine particulate matter pollution in subway stations is of great importance in the construction of subway stations, pollutant control, and health risk assessment

Methods

Results

Conclusion