Abstract

Abstract. 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.

Highlights

  • Local air quality (AQ) can be influenced significantly by regional weather systems through the accumulation and dispersion of atmospheric pollutants over and away from source regions and populated areas

  • We investigate the differences in the air quality–synoptic weather relationships found by Pope et al (2014) by attempting to quantify the dominant processes involved; for example, is atmospheric chemistry or weather more important in governing the links between synoptic meteorology and air quality in different seasons? First, we assess the ability of Air Quality in the Unified Model (AQUM) to simulate UK air quality under different synoptic regimes found in the Ozone Monitoring Instrument (OMI) data

  • As AQUM was run for 2006–2010, the OMI column NO2– Lamb weather type (LWT) analyses performed by Pope et al (2014) are repeated for this time period to assess whether the synoptic weather– AQ relationships are consistent between the 7-year period presented in that study and the 5 years analysed here

Read more

Summary

Introduction

Local air quality (AQ) can be influenced significantly by regional weather systems through the accumulation and dispersion of atmospheric pollutants over and away from source regions and populated areas. Pope et al (2014) used the LWTs and Ozone Monitoring Instrument (OMI) tropospheric column NO2 between 2005 and 2011 (note that in the following we often refer to “tropospheric column NO2” as “column NO2”) They found that anticyclonic and cyclonic conditions lead to the accumulation and transport of air pollutants over and away from source regions, respectively. This is defined as “dynamical” model evaluation, i.e. assessing a model’s ability to simulate changes in air quality stemming from changes in emissions and/or meteorology (Dennis et al, 2010) This follows the work by Pope et al (2015), who used “operational” model evaluation, i.e. statistical analyses aimed at determining the agreement between the model and observations (Dennis et al, 2010), to perform the first evaluation of AQUM against satellite observations. The model setup and application of OMI averaging kernels (AK) is discussed in

Lamb weather types
Satellite data
Model setup
OMI averaging kernels
OMI tropospheric column NO2–LWT relationships
AQUM tropospheric column NO2–LWT relationships
AQUM tropospheric column tracer–LWT relationships
Conclusions
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call