Abstract
Abstract. In spite of the strict EU regulations, concentrations of surface ozone and PM10 often exceed the pollution standards for the Netherlands and Europe. Their concentrations are controlled by (precursor) emissions, social and economic developments and a complex combination of meteorological 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 Netherlands. 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) analysis in 2 modes, with and without air quality variables as predictors. Furthermore, the objective Lamb Weather Type approach is used to assess the influence of the large-scale circulation on air quality. Keeping in mind its future use in downscaling future climate scenarios for air quality purposes, special emphasis is given to an appropriate selection of the regressor variables readily available from operational meteorological forecasts or AOGCMs (Atmosphere-Ocean coupled General Circulation Models). The regression models perform satisfactory, especially for O3, with an (R2 of 57.0% and 25.0% for PM10. Including previous day air quality information increases significantly the models performance by 15% (O3) and 18% (PM10). The Lamb weather types show a seasonal 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 circulation method is limited in terms of short-term air quality forecast 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 approach.
Highlights
Ground-level ozone (O3) and particulate air pollution (PM10) have been identified as two of the most important air pollutants for Europe in general (Jol and Kielland, 1997; Brunekreef and Holgate, 2002) and over the Benelux region in particular (Tulet et al, 2000)
Prior to the selection of the weather and air quality variables for the regression analysis, their mutual relations are investigated as a function of time
We have taken into account autocorrelation effects when computing the Pearson correlation values
Summary
Ground-level ozone (O3) and particulate air pollution (PM10) have been identified as two of the most important air pollutants for Europe in general (Jol and Kielland, 1997; Brunekreef and Holgate, 2002) and over the Benelux region in particular (Tulet et al, 2000). Since their adverse health effects have been observed for decades, the supervising European institutions have produced appropriate legislation and several emission reduction measures have been taken to reduce ambient air pollution (European Community, 1999; WHO, 2000, 2005).
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