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 NO₂ 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 NO₂ sites for 2001 and validated by comparing predicted with observed NO₂ 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 (R², RMSE and fractional bias) obtained. Validation gave R² = 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.