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Background: Adverse health effects of air pollution have been reported in previous studies with varying methodological approaches to the exposure assessment. Measuring individual air pollution exposure for large-scale epidemiological studies is infeasible, calling for refined modeling tools. We evaluated the performance of the Geographical Information System–based air pollution and human exposure modeling system (AirGIS). Methods: Modeled concentrations were evaluated against measured concentrations of particulate matter (PM) less than 10 and 2.5 &mgr;m in aerodynamic diameter (PM10/PM2.5) from two fixed-site monitoring stations (background and street) and from two measurement campaigns in Copenhagen, Denmark. Modeled concentrations of black carbon (BC) were evaluated against measured PM2.5 absorbance and PM10 absorbance. Results: Mean concentrations measured in the four series were in the range of 10.4–15.3 &mgr;g/m3 for PM2.5 and 17.8–25.1 &mgr;g/m3 for PM10. The model underestimated by 7%–13% in comparison to the fixed-site monitoring stations. Correlation coefficients of 0.82 and 0.73 were observed for monthly and daily averages of measured and modeled PM2.5 at the background site and, correspondingly, 0.85 and 0.74 at the street site. The spatial variation, as evaluated from the two measurement campaigns, was also well reproduced. Correlation coefficients of 0.77 and 0.79 were observed for BC and PM2.5 absorbance and 0.76 for PM10 absorbance. Conclusion: The AirGIS framework showed an overall high degree of accuracy and will be applicable to future epidemiological studies on health effects of PM and BC.

Evaluation of the Danish AirGIS air pollution modeling system against measured concentrations of PM2.5, PM10, and black carbon