Temporal and Spatial Distributions of Ozone in Atlanta: Regulatory and Epidemiologic Implications

Abstract

Relationships between ambient levels of selected air pollutants and pediatric asthma exacerbation in Atlanta were studied retrospectively. As a part of this study, temporal and spatial distributions of ambient ozone concentrations in the 20-county Atlanta metropolitan area during the summers of 1993, 1994, and 1995 were assessed. A universal kriging procedure was used for spatial interpolation of aerometric monitoring station data. In this paper, the temporal and spatial distributions of ozone are described, and regulatory and epidemiologic implications are discussed. For the study period, the Atlanta ozone nonattainment area based on the 1-h, exceedance-based standard of 0.12 ppm is estimated to expand-from 56% of the Atlanta MSA by area and 71% by population to 88% by area and 96% by population-under the new 8-h, concentration-based standard of 0.08 ppm. Regarding asthma exacerbation, a 4% increase in pediatric asthma rate per 20-ppb increase in ambient ozone concentration was observed (p-value = 0.001), with ambient ozone level representing a general indicator of air quality due to its correlations with other pollutants. The use of spatial ozone estimates in the epidemiologic analysis demonstrates the need for control of demographic covariates in spatiotemporal assessments of associations of ambient air pollutant concentrations with health outcome.

Applying land use regression model to estimate spatial variation of PM2.5 in Beijing, China

“…A previous study ) conducted in six downtown districts in autumn, 2012 produced a similar result (102.5 μg/m 3 ) to our model, but the kriging method might decrease spatial variation in PM 2.5 exposures (Lee et al 2014;Mulholland et al 1998). Spatiotemporal LUR models are supposed to generate results with fine resolution and high variations for both short-and long-term outdoor exposures (Dons et al 2014), which are aimed at promoting epidemiological and risk assessment studies in Beijing.…”

Residence location as a measure of environmental exposure: a review of air pollution epidemiology studies

“…Similarly diverse applications have been seen in studies of water pollution ( e.g., Baker et al, 1978;Lebowitz et al, 1992;Rao et al, 1995 ) and hazardous waste (e.g., Lagakos et al, 1986;Lampi et al, 1992;Gamble and Lewis, 1996;Molholland et al, 1998 ). Exposure indicators using residence location are easy and inexpensive to construct, and increased use is anticipated given advances in geographic information systems (GIS ) and databases that simplify identification of potentially polluted areas (Clark et al, 1982;Budnick et al, 1984;Geschwind et al, 1992;Dayal et al, 1995 ).…”

A Tool for Public PM<sub>2.5</sub>-Concentration Advisory Based on Mobile Measurements

“…This cross-validation suggested that all tested interpola-tion methods performed reasonably well and the kriging method provided the least biases. Application of the universal kriging procedure for spatial interpolation of ozone data from ten monitoring stations to all zip-code areas in Atlanta, Georgia showed that over 1993 to 1995, the ozone distribution highly correlated with the wind fields [3]. This study also suggested that the Atlanta ozone-nonattainment area would expand from 56% under the 1 h ozone-standard to 88% under the 8 h ozone-standard of the Atlanta metropolitan statistical area.…”