European models incorporating satellite and chemical transport modelling with local variables in LUR

Introduction. To quantify effects on health outcomes over background air pollution levels, it is necessary to undertake large epidemiological studies and/or pool data from multiple cohorts. Air pollution exposure estimates over large geographic areas at sufficient spatial resolution are thus needed. Satellite-derived (SAT) and chemical transport model (CTM) estimates of PM2.5 and NO2 are increasingly used in combination with Land Use Regression (LUR) models to accomplish this. We aimed to compare the contribution of SAT and CTM data to the performance of LUR PM2.5 and NO2 models for Europe. Methods. Four sets of models, all including local traffic and land use variables, were compared (LUR without SAT or CTM, with SAT only, with CTM only, and with both SAT and CTM). LUR models were developed using two monitoring data sets: PM2.5 and NO2 ground level measurements from the European Study of Cohorts for Air Pollution Effects (ESCAPE) and from the European AIRBASE network. Results. LUR PM2.5 models including ...