Spatial heterogeneity of PM10 and O3 in São Paulo, Brazil, and implications for human health studies

Abstract

Developing exposure estimates is a challenging aspect of investigating the health effects of air pollution. Pollutant levels recorded at centrally located ambient air quality monitors in a community are commonly used as proxies for population exposures. However, if ample intraurban spatial variation in pollutants exists, city-wide averages of concentrations may introduce exposure misclassification. We assessed spatial heterogeneity of particulate matter with an aerodynamic diameter ≤10 μm (PM 10 ) and ozone (O 3 ) and evaluated implications for epidemiological studies in São Paulo, Brazil, using daily (24-hr) and daytime (12-hr) averages and 1-hr daily maximums of pollutant levels recorded at the regulatory monitoring network. Monitor locations were also analyzed with respect to a socioeconomic status index developed by the municipal government. Hourly PM 10 and O 3 data for the São Paulo Municipality and Metropolitan Region (1999-2006) were used to evaluate heterogeneity by comparing distance between monitors with pollutants' correlations and coefficients of divergence (CODs). Both pollutants showed high correlations across monitoring sites (median = 0.8 for daily averages). CODs across sites averaged 0.20. Distance was a good predictor of CODs for PM 10 (p < 0.01) but not O 3 , whereas distance was a good predictor of correlations for O 3 (p < 0.01) but not PM 10 . High COD values and low temporal correlation indicate a spatially heterogeneous distribution of PM 10 . Ozone levels were highly correlated (r ≥ 0.75), but high CODs suggest that averaging over O 3 levels may obscure important spatial variations. Of municipal districts in the highest of five socioeconomic groups, 40% have ≥1 monitor, whereas districts in the lowest two groups, representing half the population, have no monitors. Results suggest that there is a potential for exposure misclassification based on the available monitoring network and that spatial heterogeneity depends on pollutant metric (e.g., daily average vs. daily 1-hr maximum). A denser monitoring network or alternative exposure methods may be needed for epidemiological research. Findings demonstrate the importance of considering spatial heterogeneity and differential exposure misclassification by subpopulation. Copyright 2011 Air & Waste Management Association.