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Assessment of Inter-Individual, Geographic, and Seasonal Variability in Estimated Human Exposure to Fine Particles

Jiao, Wan, Frey, H. Christopher, Cao, Ye
Environmental Science & Technology 2012 v.46 no.22 pp. 12519-12526
particles, health effects assessments, elderly, simulation models, census data, humans, at-risk population, seasonal variation, air, cities, estimated exposure dose, adverse effects
Health effects associated with ambient fine particle (PM₂.₅) exposure are typically estimated based on concentration–response (C–R) functions using area-wide concentration as an exposure surrogate. Persons 65 and older are particularly susceptible to adverse effects from PM₂.₅ exposure. Using a stochastic microenvironmental simulation model, distributions of daily PM₂.₅ exposures were estimated based on ambient concentration, air exchange rate, penetration factor, deposition rate, indoor emission sources, census data, and activity diary data, and compared for selected regions and seasons. Even though the selected subpopulation spends an average of over 20 h per day indoors, the ratio of daily average estimated exposure to ambient concentration (Eₐ/C) is approximately 0.5. The daily average Eₐ/C ratio varies by a factor of 4–5 over a 95% frequency range among individuals, primarily from variability in air exchange rates. The mean Eₐ/C varies by 6–36% among selected NC, TX, and NYC domains, and 15–34% among four seasons, as a result of regional differences in housing stock and seasonal differences in air exchange rates. Variability in Eₐ/C is a key factor that may help explain heterogeneity in C–R functions across cities and seasons. Priorities for improving exposure estimates are discussed.