Abstract
Background: Scientific evidence indicates that chronic exposure to air pollution causes harm to health. A key issue to study the health impact of air pollution is to have reliable exposure assessment. Aims: To describe and to compare the methodology used to assign levels of residential outdoor exposure to nitrogen dioxide (NO2) in children from the INMA-Valencia cohort, Spain. Methods: Outdoor concentrations of NO2 were measured in the study area. Passive samplers were placed at 97 selected sitesduring periods of 7 days in three campaigns in 2009. A Geographic Information System (GIS) was established based on land use, road traffic (traffic intensity and distances), altitude, and population density. Diverse approaches combining land use regression (LUR) models and universal kriging were used to predict air pollution levels in the study area by using the mean of the campaigns. The assayed models took into account the following methods: a) kriging vs LUR (kriging only, LUR, and a combination of LUR plus kriging) and b) frequentist vs bayesian approaches. The different methodologies were evaluated by cross validation (leave-one-out method), by the root mean square errors (RMSE) and by the R-squared of the regression between measured and estimated concentrations Results: The mean NO2 measured value was 35.97, 24.64, and 19.60 µg/m3 in February, April, and July campaigns, respectively .The models presented a high goodness of fit (R2 around 0.8 and RMSE 20%) and the results were similar in all methods (LUR vs Kriging and frequentist vs bayesian methods) Conclusion/Discussion: Results show the usefulness offered by GIS for spatial pattern identification of outdoor air pollution levels in our study area. Following these findings we derive that estimations of air pollution levels using GIS can be a good proxy of actual measurements of outdoor air pollution levels. Exposure aassessment to air pollution during early age will allow analyzing its effects on health
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