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International audienceThis paper presents experiments of PM10 data assimilation with the optimal interpolation method. The observations are provided by BDQA (Base de Données sur la Qualité de l'Air), whose monitoring network covers France. Two other databases (EMEP and AirBase) are used to evaluate the improvements in the analyzed state over one month (January, 2001) and for several outputs (PM10, PM2.5 and chemical composition). Then, the method is applied in operational conditions. The results show that the assimilation of PM10 observations significantly improves the one-day forecast for total mass (PM10 and PM2.5). The errors on aerosol chemical composition are not reduced and are sometimes amplified by the assimilation procedure, which shows the need for chemical data. As the observations cover a limited part of the domain (France versus Europe) and as the method used for assimilation is sequential, we focus on the horizontal and temporal impacts of assimilation in the last part of this paper. To conclude, we discuss the perspectives, especially the use of a variational method for assimilation or the investigation of the sensitivity to a few choices (e.g., the error statistics, etc.)

PM&lt;sub&gt;10&lt;/sub&gt; data assimilation over Europe with the optimal interpolation method

PM<sub>10</sub> data assimilation over Europe with the optimal interpolation method