Spatial Variability of PM2.5 in Urban Areas in the United States
Epidemiologic time-series studies typically use either daily 24-hour PM concentrations averaged across several monitors in a city or data obtained at a ?central monitoring site' to relate to human health effects. If 24-hour average concentrations differ substantially across an urban area, exposure misclassification could be an important consideration when a limited number of ambient PM monitors are used to represent population-average ambient exposures. Using the U.S. Environmental Protection Agency's Aerometric Information Retrieval System (AIRS) database for 1999 and 2000, the spatial variability of PM2.5 concentrations in twenty seven urban areas across the United States was characterized. The 90th percentile value (P90) of the concentration differences and the coefficient of divergence (COD) of monitoring site pairs were used to quantify the degree of uniformity of PM2.5 concentrations in the urban areas characterized. Pearson correlations of PM2.5 daily average concentrations were used to indicate spatial uniformity in temporal changes (i.e., concentrations at both sites increasing or decreasing together). We observed that the PM2.5 concentrations varied to differing degrees in the urban areas examined. Patterns of variability within several urban areas in the southeastern United States indicated high correlations between site pairs and spatial uniformity in concentration fields. Considerable spatial variation was found in the other regions, especially in western cities. Even within urban areas in which all site pairs were highly correlated, a variable degree of heterogeneity in PM2.5 concentrations was found. Thus, even though concentrations at pairs of sites were highly correlated, their concentrations were not necessarily the same. Our findings indicate that the potential for exposure misclassification errors in time-series epidemiologic studies exists. Exposure misclassification errors resulting from the neglect of spatial variability may contribute to uncertainties in the relative risk estimates resulting from epidemiologic investigations. In future epidemiologic studies, it is important that the spatial variation in ambient PM2.5 concentrations within a study area be taken into consideration so as to reduce some sources of exposure misclassification.
Epidemiologic time-series studies typically use either daily 24-hour PM concentrations averaged across several monitors in a city or data obtained at a ?central monitoring site' to relate to human health effects. If 24-hour average concentrations differ significantly across an urban area, exposure misclassification could be an important consideration when an average of all the ambient PM monitors is used as a surrogate for personal exposure. Based on the results of our study, the use of correlation coefficients alone may not be sufficient to determine whether or not PM2.5 concentrations are uniform within urban areas. Investigators should examine the spatial variability of ambient air quality within a study area prior to initiating studies relating concentrations of PM and other pollutants to human health outcomes in epidemiologic studies, and should include the characterization of spatial variability used in their calculations in publications