This paper presents the assimilation of satellite NO2 observations into a chemistry-transport model (CTM). The NO2 columns from Ozone Monitoring Instrument (OMI) aboard NASA Aura satellite are used during November-December 2005. These satellite observations are assimilated in an air quality model from Polyphemus, in order to better forecast NO2 in Europe. The optimal-interpolation method is applied to produce analyzed columns, and these analyzed columns are mapped to model concentrations assuming that the model vertical profile is perfect. Good consistency is seen in the comparisons of model simulations, satellite data and ground observations before assimilation. The model results with and without assimilation are then compared with ground observations for evaluating the assimilation effects. It is found that the assimilation can improve the NO2 forecasts by reducing their discrepancies against ground observations, indicating a better NO2 forecast obtained with OMI observations. Such improvements are seen in a cold season rather than in a warm one probably due to the longer lifetime of NOx and the initial condition changes having more impacts in winter. This also suggests that the assimilation of the short-lived species like NO2 is a complicate problem.