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A platform for research: civil engineering, architecture and urbanism
Exposure assessment and modeling of particulate matter for asthmatic children using personal nephelometers
AbstractIt has been shown that acute exposures to particulate matter (PM) may exacerbate asthma in children. However, most epidemiological studies have relied on time-integrated PM measurements taken at a centrally located stationary monitoring sites. In this article, we characterized children's short-term personal exposures to PM2.5 (PM with aerodynamic diameters <2.5μm) and separated them into ambient and nonambient components. The personal DataRAM without a size-selective inlet was used to estimate real-time PM2.5 concentrations on 20 asthmatic children, inside and outside of their residences, and at a central site. The personal and indoor pDRs were operated passively, while the home outdoor and central site instruments were operated actively. The subjects received 29.2% of their exposures at school, even though they only spent 16.4% of their time there. More precise personal clouds were estimated for the home-indoor and home-outdoor microenvironments where PM concentrations were measured. The personal cloud increased with increasing activity levels and was higher during outdoor activities than during indoor activities. We built models to predict personal PM exposures based on either microenvironmental or central-site PM2.5 measurements, and evaluated the modeled exposures against the actual personal measurements. A multiple regression model with central site PM concentration as the main predictor had a better prediction power () than a three-microenvironmental model (). We further constructed a source-specific exposure model utilizing the time-space-activity information and the particle infiltration efficiencies (mean=0.72±0.15) calculated from a recursive mass balance model. It was estimated that the mean hourly personal exposures resulting from ambient, indoor-generated, and personal activity PM2.5 were 11.1, 5.5, and 10.0μg/m3, respectively, when the modeling error was minimized. The high PM2.5 exposure to personal activities reported in our study is likely due to children's more active lifestyle as compared with older adult subjects in previous studies.
Exposure assessment and modeling of particulate matter for asthmatic children using personal nephelometers
AbstractIt has been shown that acute exposures to particulate matter (PM) may exacerbate asthma in children. However, most epidemiological studies have relied on time-integrated PM measurements taken at a centrally located stationary monitoring sites. In this article, we characterized children's short-term personal exposures to PM2.5 (PM with aerodynamic diameters <2.5μm) and separated them into ambient and nonambient components. The personal DataRAM without a size-selective inlet was used to estimate real-time PM2.5 concentrations on 20 asthmatic children, inside and outside of their residences, and at a central site. The personal and indoor pDRs were operated passively, while the home outdoor and central site instruments were operated actively. The subjects received 29.2% of their exposures at school, even though they only spent 16.4% of their time there. More precise personal clouds were estimated for the home-indoor and home-outdoor microenvironments where PM concentrations were measured. The personal cloud increased with increasing activity levels and was higher during outdoor activities than during indoor activities. We built models to predict personal PM exposures based on either microenvironmental or central-site PM2.5 measurements, and evaluated the modeled exposures against the actual personal measurements. A multiple regression model with central site PM concentration as the main predictor had a better prediction power () than a three-microenvironmental model (). We further constructed a source-specific exposure model utilizing the time-space-activity information and the particle infiltration efficiencies (mean=0.72±0.15) calculated from a recursive mass balance model. It was estimated that the mean hourly personal exposures resulting from ambient, indoor-generated, and personal activity PM2.5 were 11.1, 5.5, and 10.0μg/m3, respectively, when the modeling error was minimized. The high PM2.5 exposure to personal activities reported in our study is likely due to children's more active lifestyle as compared with older adult subjects in previous studies.
Exposure assessment and modeling of particulate matter for asthmatic children using personal nephelometers
Wu, Chang-Fu (author) / Delfino, Ralph J. (author) / Floro, Joshua N. (author) / Quintana, Penelope J.E. (author) / Samimi, Behzad S. (author) / Kleinman, Michael T. (author) / Allen, Ryan W. (author) / Sally Liu, L.-J. (author)
Atmospheric Environment ; 39 ; 3457-3469
2005-01-26
13 pages
Article (Journal)
Electronic Resource
English