Mobile wireless sensor networks (MWSN) are widely used for monitoring physical phenomena such as air pollution where the aim is usually to generate accurate pollution maps in real time. The generation of pollution maps can be performed using either sensor measurements or physical models which simulate the phenomenon of pollution dispersion. The combination of these two information sources, known as data assimilation, makes it possible to better monitor air pollution by correcting the simulations of physical models while relying on sensor measurements. The quality of data assimilation mainly depends on the number of measurements and their locations. A careful deployment of nodes is therefore necessary in order to get better pollution maps. In this ongoing work, we tackle the placement problem of pollution sensors and design a mixed integer programming model allowing to maximize the assimilation quality while ensuring the connectivity of the network. We perform some simulations on a dataset of the Lyon city, France in order to show the eeectiveness of our model regarding the quality of pollution coverage.