We compare tropospheric column NO₂ between the UK Met Office operational Air Quality in the Unified Model (AQUM) and satellite observations from the Ozone Monitoring Instrument (OMI) for 2006. Column NO₂ retrievals from satellite instruments are prone to large uncertainty from random, systematic and smoothing errors. We present an algorithm to reduce the random error of time-averaged observations, once smoothing errors have been removed with application of satellite averaging kernels to the model data. This reduces the total error in seasonal mean columns by 10–70%, which allows critical evaluation of the model. The standard AQUM configuration evaluated here uses chemical lateral boundary conditions (LBCs) from the GEMS (Global and regional Earth-system Monitoring using Satellite and in situ data) reanalysis. In summer the standard AQUM overestimates column NO₂ in northern England and Scotland, but underestimates it over continental Europe. In winter, the model overestimates column NO₂ across the domain. We show that missing heterogeneous hydrolysis of N₂O₅ in AQUM is a significant sink of column NO₂ and that the introduction of this process corrects some of the winter biases. The sensitivity of AQUM summer column NO₂ to different chemical LBCs and NO_x emissions data sets are investigated. Using Monitoring Atmospheric Composition and Climate (MACC) LBCs increases AQUM O₃ concentrations compared with the default GEMS LBCs. This enhances the NO_x–O₃ coupling leading to increased AQUM column NO₂ in both summer and winter degrading the comparisons with OMI. Sensitivity experiments suggest that the cause of the remaining northern England and Scotland summer column NO₂ overestimation is the representation of point source (power station) emissions in the model.