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{"id":52179967,"title":"Development of ambient air quality population-weighted metrics for use in time-series health studies","translated_title":"","metadata":{"grobid_abstract":"A robust methodology is developed to compute population-weighted daily measures of ambient air pollution for use in time-series studies of acute health effects. Ambient data, including criteria pollutants and four fine particulate matter components, from monitors located in the twentycounty metropolitan Atlanta area over the 1999 through 2004 time period were normalized, spatially resolved using inverse distance-square weighting to census tracts, denormalized using descriptive spatial models, and population-weighted. Error associated with applying this procedure with fewer than the maximum number of observations was also calculated. In addition to providing more representative measures of ambient air pollution for the health study population than provided by a central monitor alone and dampening effects of measurement error and local source impacts, results are used to evaluate spatial variability and to identify air pollutants whose ambient concentrations are poorly characterized. The decrease in correlation of daily monitor observations with daily population-weighted average values with increasing distance of the monitor from the urban center is much greater for primary pollutants than for secondary pollutants. Of the criteria pollutant gases, sulfur dioxide observations were least representative due to the failure of ambient networks to capture the spatial variability of this pollutant whose concentrations are dominated by point source impacts. Daily fluctuations in PM 10 mass were less well characterized than PM 2.5 mass due to a smaller number of PM 10 monitors with daily observations. 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The decrease in correlation of daily monitor observations with daily population-weighted average values with increasing distance of the monitor from the urban center is much greater for primary pollutants than for secondary pollutants. Of the criteria pollutant gases, sulfur dioxide observations were least representative due to the failure of ambient networks to capture the spatial variability of this pollutant whose concentrations are dominated by point source impacts. Daily fluctuations in PM 10 mass were less well characterized than PM 2.5 mass due to a smaller number of PM 10 monitors with daily observations. 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