Multivariate spatio temporal models for large datasets and joint exposure to airborne multipollutants in Europe

We consider the distribution of population by exposure to multiple airborne pollutants at various spatial and temporal resolutions over Europe. The estimation of this distribution and its uncertainty are obtained via model based high resolution semiparametric estimates of daily average concentrations for seven pollutants in years 2009-2011. In order to exploit the spatial information content and allow the computation of daily multipollutant exposure distribution, uncertainty included, we use a multivariate spatio-temporal model capable to handle non Gaussian large datasets such as multivariate and multiyear daily air quality, land use and meteorological data over Europe.