Air quality has become a key factor when assessing human welfare over the years, since its cleanliness is vital to ensure the health and development of any living being. However, it is being progressively compromised by population growth and environmentally harmful human activities, such as industrialization, increased energy use and transportation. Big and crowded cities like Barcelona are particularly susceptible to these kind of effects and are therefore more likely to experience dangerous reductions of air quality. For this reason, this paper aims to model the air quality in Barcelona by building regression models that enable the estimation of the relationship between two air pollutants (NO2 and PM10), whose point measurements are interpolated throughout the city of Barcelona using GIS techniques, and a series of explanatory variables related to the climate (precipitation, temperature and wind), territory (proximity to coast, industry and mountains, building density and greenspace) and traffic volume. The results provided by these models are intended to bring an improvement in urban planning, since they allow the detection of areas requiring priority actions to control air pollution.