A GIS-based moving window approach was developed as a means for generating high resolution air pollution maps over large geographic areas. The approach is demonstrated by modelling annual mean NO(2) pollution for the EU-15 (excluding Sweden) at the 1 km level on the basis of emissions and meteorological data. Models were developed using monitoring data from 714 background NO(2) sites for 2001 and validated by comparing predicted with observed NO(2) concentrations for a reserved set of 228 background sites. First the emission map (NO(x)) was derived by disaggregating national emissions estimates, categorised by source, to a 1 km grid, using proxies including population and road density, traffic statistics and land cover. A set of annuli was then constructed, of varying radii, and these passed over the emissions grid to derive a calibration between measured annual average concentrations at each monitoring site and distance-weighted emissions in the surrounding area, using a focalsum function. The resulting model was then used to predict concentrations at the reserved set of validation sites, and measures of performance (R(2), RMSE and fractional bias) obtained. Validation gave R(2)=0.61, RMSE=6.59 and FB=-0.01, and indicated performance equivalent to universal kriging and better than ordinary kriging and land use regression.