ALBERT

Description: Peroxyacetyl nitrate (PAN) is an important chemical species in the troposphere as it aids the long-range transport of NOx and subsequent formation of O3 in relatively clean remote regions. Over the past few decades observations from aircraft campaigns and surface sites have been used to better understand the regional distribution of PAN. However, recent measurements made by satellites allow for a global assessment of PAN in the upper troposphere – lower stratosphere (UTLS). In this study, we investigate global PAN distributions from two independent retrieval methodologies, based on measurements from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument, on board ENVISAT from the Institute of Meteorology and Climate Research (IMK), Karlsruhe Institute of Technology and the Department of Physics and Astronomy, University of Leicester (UoL). Retrieving PAN from MIPAS is challenging due to the weak signal in the measurements and contamination from other species. Therefore, we compare the two MIPAS datasets with observations from the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS), insitu aircraft data and the TOMCAT 3-D chemical transport model. MIPAS shows peak UTLS PAN concentrations over the biomass burning regions (e.g. ranging from 150 to 〉 200 pptv at 150 hPa) and during the summertime Asian monsoon as enhanced convection aids the vertical transport of PAN from the lower atmosphere. At 150 hPa, we find significant differences between the two MIPAS datasets in the tropics, where IMK PAN concentrations are larger by 50–100 pptv. Comparisons between MIPAS and ACE-FTS show better agreement with the UoL MIPAS PAN concentrations at 200 hPa, but with mixed results above this altitude. TOMCAT generally captures the magnitude and structure of climatological aircraft PAN profiles within the observational variability allowing it to be used to investigate the MIPAS PAN differences. TOMCAT-MIPAS comparisons show that the model is both positively (UoL) and negatively (IMK) biased against the satellite products. These results show that satellite PAN observations are able to detect realistic spatial variations in PAN in the UTLS, but further work is needed to resolve differences in existing retrievals to allow quantitative use of the products.

Description: Synoptic meteorology can have a significant influence on UK air quality. Cyclonic (anticyclonic) 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.

Description: 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 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 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.

Description: Synoptic meteorology can have a significant influence on UK air quality. Cyclonic conditions lead to the dispersion of air pollutants away from source regions, while anticyclonic conditions lead to their accumulation 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 explore the relative importance of various 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 idealized 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 tropospheric 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 tropospheric 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 tropospheric column NO2 field can be explained by the idealized model tracers, showing that transport is an important factor in governing the variability of UK air quality on seasonal synoptic timescales.

Description: 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.