Evaluation of a regional air quality model using satellite column NO$_2$: treatment of observation errors and model boundary conditions and emissions

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 NOx 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 NOx–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.