Air quality modeling at a very local scale within an urban area is performed through a hybrid modeling system (HMS) that combines the CAMx Eulerian model with the AUSTAL2000 Lagrangian model. The improvements obtained using the HMS in reconstructing the spatial distribution of fine particle (PM2.5) and elemental carbon (EC) concentrations are presented for the case study in the center of Milan in Northern Italy. Modeling results are reported for three receptors (a green area, a residential and commercial area, and a congested intersection on the inner ring road of the city center) selected to represent urban sites characterized by both different characteristics in terms of the surrounding built environment and by different exposure to local emission sources. The peculiarity of the three receptors is further highlighted by the analysis of the distribution of the sources, developed not only with respect to the type of emission sources but also to the geographical location of the sources within the entire computational domain of Northern Italy. The results show that the result of the local-scale Eulerian model is only representative of a background level, similar to the result of the Lagrangian model for the green area receptor, but fails to reproduce concentration gradients and hot spots, determined by emissions from local sources, which are instead well reproduced by the hybrid model.