The impact of weather and atmospheric circulation on O3 and PM10 levels at a rural mid-latitude site
- ISSN: 1680-7375
- DOI: 10.5194/acp-9-2695-2009
In spite of the strict EU regulations, concentra- tions of surface ozone and PM10 often exceed the pollution standards for the Netherlands and Europe. Their concentra- tions are controlled by (precursor) emissions, social and eco- nomic developments and a complex combination of meteo- rological actors. This study tackles the latter, and provides insight in the meteorological processes that play a role in O3 and PM10 levels in rural mid-latitudes sites in the Nether- lands. The relations between meteorological actors and air quality are studied on a local scale based on observations from four rural sites and are determined by a comprehensive correlation analysis and a multiple regression (MLR) analy- sis in 2 modes, with and without air quality variables as pre- dictors. Furthermore, the objective Lamb Weather Type ap- proach is used to assess the influence of the large-scale circu- lation on air quality. Keeping in mind its future use in down- scaling future climate scenarios for air quality purposes, spe- cial emphasis is given to an appropriate selection of the re- gressor variables readily available from operational meteoro- logical forecasts or AOGCMs (Atmosphere-Ocean coupled General Circulation Models). The regression models per- form satisfactory, especially forO3, with an R2 of 57.0% and 25.0% for PM10. Including previous day air quality informa- tion increases significantly the models performance by 15% (O3) and 18% (PM10). The Lamb weather types show a sea- sonal distinct pattern for high (low) episodes of average O3 and PM10 concentrations, and these are clear related with the meteorology-air quality correlation analysis. Although using a circulation type approach can provide important additional physical relations forward, our analysis reveals the circula- tion method is limited in terms of short-term air quality fore- cast for both O3 and PM10 (R2 between 0.12 and 23%). In summary, it is concluded that the use of a regression model is more promising for short-term downscaling from climate scenarios than the use of a weather type classification ap- proach.