Characterizing the Indoor-Outdoor Relationship of Fine Particulate Matter in Non-Heating Season for Urban Residences in Beijing

PLOS ONE, Dec 2019

Objective Ambient fine particulate matter (PM2.5) pollution is currently a major public health concern in Chinese urban areas. However, PM2.5 exposure primarily occurs indoors. Given such, we conducted this study to characterize the indoor-outdoor relationship of PM2.5 mass concentrations for urban residences in Beijing. Methods In this study, 24-h real-time indoor and ambient PM2.5 mass concentrations were concurrently collected for 41 urban residences in the non-heating season. The diurnal variation of pollutant concentrations was characterized. Pearson correlation analysis was used to examine the correlation between indoor and ambient PM2.5 mass concentrations. Regression analysis with ordinary least square was employed to characterize the influences of a variety of factors on PM2.5 mass concentration. Results Hourly ambient PM2.5 mass concentrations were 3–280 μg/m3 with a median of 58 μg/m3, and hourly indoor counterpart were 4–193 μg/m3 with a median of 34 μg/m3. The median indoor/ambient ratio of PM2.5 mass concentration was 0.62. The diurnal variation of residential indoor and ambient PM2.5 mass concentrations tracked with each other well. Strong correlation was found between indoor and ambient PM2.5 mass concentrations on the community basis (coefficients: r≥0.90, p<0.0001), and the ambient data explained ≥84% variance of the indoor data. Regression analysis suggested that the variables, such as traffic conditions, indoor smoking activities, indoor cleaning activities, indoor plants and number of occupants, had significant influences on the indoor PM2.5 mass concentrations. Conclusions PM2.5 of ambient origin made dominant contribution to residential indoor PM2.5 exposure in the non-heating season under the high ambient fine particle pollution condition. Nonetheless, the large inter-residence variability of infiltration factor of ambient PM2.5 raised the concern of exposure misclassification when using ambient PM2.5 mass concentrations as exposure surrogates. PM2.5 of indoor origin still had minor influence on indoor PM2.5 mass concentrations, particularly at 11:00–13:00 and 22:00–0:00. The predictive models suggested that particles from traffic emission, secondary aerosols, particles from indoor smoking, resuspended particles due to indoor cleaning and particles related to indoor plants contributed to indoor PM2.5 mass concentrations in this study. Real-time ventilation measurements and improvement of questionnaire design to involve more variables subject to built environment were recommended to enhance the performance of the predictive models.

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Characterizing the Indoor-Outdoor Relationship of Fine Particulate Matter in Non-Heating Season for Urban Residences in Beijing

September Characterizing the Indoor-Outdoor Relationship of Fine Particulate Matter in Non-Heating Season for Urban Residences in Beijing Lihui Huang 0 1 2 Zhongnan Pu 0 1 2 Mu Li 0 1 2 Jan Sundell 0 1 2 0 Funding: This study is supported by the Natural Science Foundation of China (41172212, 41230314) and the Chinese Postdoctoral Science Foundation , 2014M550739 1 Editor: Maosheng Yao, Peking University , CHINA 2 1 Key Laboratory of Subsurface Hydrology and Ecological Effects in Arid Region, Ministry of Education, School of Environmental Science and Engineering, Chang'an University , Xi'an, 710054, China , 2 Institute of Built Environment, Department of Building Science, Tsinghua University , Beijing, 100084 , China Ambient fine particulate matter (PM2.5) pollution is currently a major public health concern in Chinese urban areas. However, PM2.5 exposure primarily occurs indoors. Given such, we conducted this study to characterize the indoor-outdoor relationship of PM2.5 mass concentrations for urban residences in Beijing. - In this study, 24-h real-time indoor and ambient PM2.5 mass concentrations were concurrently collected for 41 urban residences in the non-heating season. The diurnal variation of pollutant concentrations was characterized. Pearson correlation analysis was used to examine the correlation between indoor and ambient PM2.5 mass concentrations. Regression analysis with ordinary least square was employed to characterize the influences of a variety of factors on PM2.5 mass concentration. Hourly ambient PM2.5 mass concentrations were 3–280 μg/m3 with a median of 58 μg/m3, and hourly indoor counterpart were 4–193 μg/m3 with a median of 34 μg/m3. The median indoor/ambient ratio of PM2.5 mass concentration was 0.62. The diurnal variation of residential indoor and ambient PM2.5 mass concentrations tracked with each other well. Strong correlation was found between indoor and ambient PM2.5 mass concentrations on the community basis (coefficients: r 0.90, p<0.0001), and the ambient data explained 84% variance of the indoor data. Regression analysis suggested that the variables, such as traffic conditions, indoor smoking activities, indoor cleaning activities, indoor plants and number of occupants, had significant influences on the indoor PM2.5 mass concentrations. PM2.5 of ambient origin made dominant contribution to residential indoor PM2.5 exposure in the non-heating season under the high ambient fine particle pollution condition. Nonetheless, the large inter-residence variability of infiltration factor of ambient PM2.5 raised the concern of exposure misclassification when using ambient PM2.5 mass concentrations as exposure surrogates. PM2.5 of indoor origin still had minor influence on indoor PM2.5 mass concentrations, particularly at 11:00–13:00 and 22:00–0:00. The predictive models suggested that particles from traffic emission, secondary aerosols, particles from indoor smoking, resuspended particles due to indoor cleaning and particles related to indoor plants contributed to indoor PM2.5 mass concentrations in this study. Real-time ventilation measurements and improvement of questionnaire design to involve more variables subject to built environment were recommended to enhance the performance of the predictive models. The rapid urbanization and industrialization result in the recent nationwide ambient fine particle pollution (haze episodes) in Chinese urban areas. Fine particulate matter (PM2.5) is a complicated mixture of solid and liquid particles that vary in number, size, shape, surface area, chemical composition, solubility and origin [1, 2]. Exposure to toxic components in ambient PM2.5 is associated with a wide spectrum of adverse respiratory and cardiovascular health effects[3–12], and even with low birth weight and increased risk of preterm birth [13, 14]. Therefore, fine particle pollution in ambient air is currently a major public health concern in China, and is driving increasing research interest [12, 15–17]. Chinese urban residents spend nearly 90% of lifetime indoors, and of that, 70% is in residential indoor microenvironments[18]. As a result, exposure to airborne PM2.5 primarily occurs indoors. Ambient PM2.5 penetrate indoors through the ventilation system, the building envelope and cracks [19–21]. The outdoor-indoor transit of ambient particles can alter PM chemical and physical properties such as mass concentrations, size-distribution and composition [20, 22–24]. For example, the fraction of ambient PM2.5 that can penetrate indoors and remain suspended (defined as infiltration factor, Finf) largely vary from 35% to 95% in the literature[19, 25–32]. Particles in the accumulation mode have higher Finf values than particles of other size bins [24, 26]. On the other hand, particles generated by indoor sources may also significantly contribute to indoor PM2.5. The primary indoor PM2.5 sources include environmental tobacco smoke (ETS), home cleaning and heat/combustion activit (...truncated)


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Lihui Huang, Zhongnan Pu, Mu Li, Jan Sundell. Characterizing the Indoor-Outdoor Relationship of Fine Particulate Matter in Non-Heating Season for Urban Residences in Beijing, PLOS ONE, 2015, 9, DOI: 10.1371/journal.pone.0138559