Towards control strategies of particulate matter concentration in subway platforms: A case study in Beijing

Abstract

The particulate matter (PM) concentration in subway platforms greatly affects people’s health. Previous control strategies fail to consider comprehensive factors, or exhibit deficient in quantitative suggestions. In this paper, we propose a comprehensive framework for exploring control strategies of the PM concentration in subway platforms using the field observation data of 12 subway stations of Beijing. The framework consists of factor analysis stage, simulation stage, and prediction stage. The first stage extracts five important factors (concentration of outdoor PM, passenger flow, train departure frequency, operation years and platform type) related to the PM concentration in platforms, and ranks the importance of those factors. The second stage reveals two vertical distribution laws and a horizontal distribution law of the PM concentration in platforms. The third stage predicts the PM2.5 concentration in platforms based on the mass balance model. Finally, we suggest seven pieces of control strategies including regularly clean tunnels, platforms and ventilation systems; release negative ionic air; and add air cleaners in specific locations. In particular, we suggest a quantitative strategy on the wind speed of air supply outlet which can reduce the PM2.5 concentration in platforms 15.4%–62.3% under different air quality. The results of our study can provide a scientific basis for control of the particulate pollution in platforms, and effectively improve the subway environment.