A comparison of reanalysis techniques: Applying optimal interpolation and Ensemble Kalman Filtering to improve air quality monitoring at mesoscale

• Offline data assimilation analysis applied to TCAM model
• Comparison of optimal interpolation and Ensemble Kalman Filter performances
• Consistency between background TCAM fields and assimilation technique results

To fulfill the requirements of the 2008/50 Directive, which allows member states and regional authorities to use a combination of measurement and modeling to monitor air pollution concentration, a key approach to be properly developed and tested is the data assimilation one. In this paper, with a focus on regional domains, a comparison between optimal interpolation and Ensemble Kalman Filter is shown, to stress pros and drawbacks of the two techniques. These approaches can be used to implement a more accurate monitoring of the long-term pollution trends on a geographical domain, through an optimal combination of all the available sources of data.The two approaches are formalized and applied for a regional domain located in Northern Italy, where the PM10 level which is often higher than EU standard limits is measured.