What can we expect from data assimilation for air quality forecast? 1: Quantification with academic test cases

International audienceData assimilation is successfully used for meteorology since many years and is now more and more used for atmospheric composition issues (air quality analysis and forecast). The data assimilation of pollutants remains difficult and its deployment is currently in progress. It is thus difficult to have a quantitative knowledge of what we can expect as maximum of benefit. In this study, we propose a simple framework to make this quantification. In this first part, the gain of data assimilation is quantified using academic but realistic test cases over an urbanized polluted area and during a summertime period favourable to ozone formation. Different data assimilation configurations are tested, corresponding to different amount of data available for assimilation. For ozone (O 3) and nitrogen dioxide (NO 2), it is shown that the benefit due to data assimilation lasts from a few hours to a maximum possible of 60 and 21 hours, respectively. Maps of the number of hours are presented, spatializing the benefit of data assimilation