Abstract
This paper presents the results of using a data assimilation technique known as Optimal Interpolation (OI) for improving the PM10 estimates of the air quality model AURORA. Ground-based measurements provided by IRCEL (the Belgian Interregional Environment Agency) have been used in the data assimilation process. AURORA has been set up to cover a domain consisting of Belgium, Luxemburg, and small parts of France, Germany and the Netherlands with a grid resolution of 5×5 km2. In this study, the characterization of the error covariances between the grid-cells has been done by using the Hollingsworth-Lönnberg method. The simulation results show that the optimal interpolation technique manages to significantly reduce the error of the PM10 estimates, which indirectly leads to an improvement of the PM2.5 field.
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