Recently, air pollution monitoring emerges as a main service of smart cities because of the increasing industrialization and the massive urbanization. Wireless sensor networks (WSN) are a suitable technology for this purpose thanks to their substantial benefits including low cost and autonomy. Minimizing the deployment cost is one of the major challenges in WSN design, therefore sensors positions have to be carefully determined. In this paper, we propose two integer linear programming formulations based on real pollutants dispersion modeling to deal with the minimum cost WSN deployment for air pollution monitoring. We illustrate the concept by applying our models on real world data, namely the Nottingham City street lights. We compare the two models in terms of execution time and show that the second flow-based formulation is much better. We finally conduct extensive simulations to study the impact of some parameters and derive some guidelines for efficient WSN deployment for air pollution monitoring.