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Synoptic meteorology can have a significant influence on UK air quality. Cyclonic (an-ticyclonic) conditions lead to the dispersion (accumulation) of air pollutants away from (over) source regions. Meteorology also modifies atmospheric chemistry processes such as photolysis and wet deposition. Previous studies have shown a relationship between observed satellite tropospheric column NO2 and synoptic meteorology in different seasons. Here, we test whether the UK Met Office Air Quality in the Unified Model (AQUM) can reproduce these observations and then use the model to determine the controlling factors. We show that AQUM successfully captures the observed relationships, when sampled under the Lamb Weather Types, an objective classification of midday UK circulation patterns. By using a range of idealised NOx-like tracers with different e-folding lifetimes, we show that under different synoptic regimes the NO2 lifetime in AQUM is approximately 6 h in summer and 12 h in winter. The longer lifetime can explain why synoptic spatial column NO2 variations are more significant in winter compared to summer, due to less NO2 photochemical loss. We also show that cyclonic conditions have more seasonality in column NO2 than anticyclonic conditions as they result in more extreme spatial departures from the wintertime seasonal average. Within a season (summer or winter) under different synoptic regimes, a large proportion of the spatial pattern in the UK column NO2 field can be explained by the idealised model tracers, showing that transport is an important factor in governing the variability of UK air quality on seasonal synoptic timescales. [ABSTRACT FROM AUTHOR]

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 timeaveraged 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. [ABSTRACT FROM AUTHOR]

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 30-90%, 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 NO 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 NO2O5 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 datasets 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. [ABSTRACT FROM AUTHOR]

Groupings of Lamb weather types ( LWTs) are used to assess the influence of synoptic meteorology on UK tropospheric column NO2. Composite satellite maps using daily 2005-2011 data show significant NO2 anomalies for each group. Hence, despite large day-to-day variability and significant uncertainty in individual retrievals, the satellite data can be used to determine national-scale column NO2 variations under different meteorological conditions. Under cyclonic conditions, NO2 is reduced, while anticyclonic conditions aid its accumulation, especially during winter, consistent with trapping of surface emissions and slower photochemical processing. This composite dataset can be used to test seasonal simulations of air quality models. [ABSTRACT FROM AUTHOR]

Groupings of Lamb weather types ( LWTs) are used to assess the influence of synoptic meteorology on UK tropospheric column NO2. Composite satellite maps using daily 2005-2011 data show significant NO2 anomalies for each group. Hence, despite large day-to-day variability and significant uncertainty in individual retrievals, the satellite data can be used to determine national-scale column NO2 variations under different meteorological conditions. Under cyclonic conditions, NO2 is reduced, while anticyclonic conditions aid its accumulation, especially during winter, consistent with trapping of surface emissions and slower photochemical processing. This composite dataset can be used to test seasonal simulations of air quality models. [ABSTRACT FROM AUTHOR]