LIU Yongping, ZHANG Lijun, SU Jin. Air quality monitoring and correlation analysis in public areas of three subway stations in Shanghai[J]. Shanghai Journal of Preventive Medicine, 2022, 34(10): 1007-1013. DOI: 10.19428/j.cnki.sjpm.2022.22089
Citation: LIU Yongping, ZHANG Lijun, SU Jin. Air quality monitoring and correlation analysis in public areas of three subway stations in Shanghai[J]. Shanghai Journal of Preventive Medicine, 2022, 34(10): 1007-1013. DOI: 10.19428/j.cnki.sjpm.2022.22089

Air quality monitoring and correlation analysis in public areas of three subway stations in Shanghai

  • Objective To understand the correlation between air quality and pollutants in three underground subway stations in Shanghai and their influencing factors, in order to provide a reference for improving the ambient air quality of rail transit and enhancing control measures.
    Methods Air quality was monitored in summer, autumn, and winter of 2021 at the halls, platforms, carriages and fresh air wells of three underground stations of Shanghai metro line 9, with indicators including temperature, relative humidity, wind speed, CO2, PM1, PM2.5, PM10, total airborne bacteria, total airborne fungi, and passenger flow. Correlation analysis and multiple regression analysis were used to explore the association between pollutant indicators and environmental indicators.
    Results The relative humidity of air at three stations did not meet the national health standards (GB 37488‒2019), with an exceedance rate of 66.7%; the PM10 detection index at individual stations in autumn and winter did not meet the national health standards (GB 37488‒2019), with an exceedance rate of 20.6%, while the rest of the indexes basically met the requirements of the standards. Spatially, the CO2 and wind speed in the carriage were higher than in other areas of the station; the concentration of particulate matter in the fresh air well and the total number of airborne fungi were higher than in other areas. Seasonally, the concentration of particulate matter was higher in winter than in summer and autumn, while the microbial indexes were higher in summer than in autumn and winter. The correlation and regression analysis showed that the passenger flow was significantly and positively correlated with the CO2 concentration; the temperature and humidity were significantly and negatively correlated with the particulate matter concentration and positively correlated with the microbial index. The correlation and multiple regression analysis showed that the subway station health indicators were significantly affected by the ambient temperature, humidity, seasonal and monitoring regional factors, while the influence of sampling time had no significant effect on the differences in the health indicators.
    Conclusion The air quality of the three stations in this survey generally meets the requirements of health standards. The changes of air pollutants in subway stations show obvious spatial and temporal characteristics. The passenger flow and temperature and humidity, as well as sample sites are important factors affecting the concentration of particulate matter and the level of air microorganisms, which need to be considered when formulating the corresponding protection strategies.
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