Atmos. Chem. Phys. Discuss., 13, 475-526, 2013
www.atmos-chem-phys-discuss.net/13/475/2013/
doi:10.5194/acpd-13-475-2013
© Author(s) 2013. This work is distributed
under the Creative Commons Attribution 3.0 License.
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This discussion paper has been under review for the journal Atmospheric Chemistry and Physics (ACP). Please refer to the corresponding final paper in ACP.
Dynamic evaluation of a multi-year model simulation of particulate matter concentrations over Europe
È. Lecœur and C. Seigneur
CEREA, Joint Laboratory École des Ponts ParisTech/EDF R&D, Université Paris-Est, 77455 Marne-la-Vallée, France

Abstract. A nine-year air quality simulation is conducted from 2000 to 2008 over Europe using the Polyphemus/Polair3D chemical-transport model (CTM) and then evaluated against the measurements of the European Monitoring and Evaluation Programme (EMEP).

The spatial distribution of PM2.5 over Europe shows high concentrations over northern Italy (36 μg m−3) and some areas of eastern Europe, France, and Benelux, and low concentrations over Scandinavia, Spain, and the easternmost part of Europe. PM2.5 composition differs among regions.

The operational evaluation shows satisfactory model performance for ozone (O3). PM2.5, PM10, and sulfate (SO42−) meet the performance goal of Boylan and Russell (2006). Nitrate (NO3) and ammonium (NH4+) are overestimated, although NH4+ meets the performance criteria. The correlation coefficients between simulated and observed data are 63% for O3, 57% for PM10, 59% for PM2.5, 57% for SO42−, 42% for NO3, and 58% for NH4+. The comparison with other recent one-year model simulations shows that all models overestimate nitrate. The performance of PM2.5, sulfate, and ammonium is comparable to that of the other models.

The dynamic evaluation shows that the response of PM2.5 to changes in meteorology differs depending on location and the meteorological variable considered. Wind speed and precipitation show a strong negative day-to-day correlation with PM2.5 and its components (except for sea salt, which shows a positive correlation), that tends towards 0 as the day lag increases. On the other hand, the correlation coefficient is near constant for temperature, for any day lag and PM2.5 species, but it may be positive or negative depending on the species and, for sulfate, depending on the location. The effects of precipitation and wind speed on PM2.5 and its components are better reproduced by the model than the effects of temperature. This is mainly due to the fact that temperature has different effects on the PM2.5 components, unlike precipitation and wind speed which impact most of the PM2.5 components in the same way.

These results suggest that state-of-the-science air quality models reproduce satisfactorily the effect of meteorology on PM2.5 and, therefore, are suitable to investigate the effects of climate change on particulate air quality.


Citation: Lecœur, È. and Seigneur, C.: Dynamic evaluation of a multi-year model simulation of particulate matter concentrations over Europe, Atmos. Chem. Phys. Discuss., 13, 475-526, doi:10.5194/acpd-13-475-2013, 2013.
 
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