Air quality modeling at the very local scale within an urban area is performed through a hybrid modeling system (HMS) that combines the CAMx Eulerian model the with AUSTAL2000 Lagrangian model. The enhancements obtained by means of the HMS in the reconstruction of the spatial distribution of fine particles (PM2.5) and elemental carbon (EC) concentration are presented for the case-study of Milan city center in Northern Italy. Modeling results are reported for three receptors (a green area, a residential and shopping area, and a congested crossroad on the inner ring road of the city center) selected in order to represent urban sites characterized by both different features 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 source apportionment analysis, developed not only with respect to the kind of emission sources but also to the geographical location of the sources within the whole Northern Italy computational domain. Results show that the outcome of the Eulerian model at the local scale is only representative of a background level, similar to the Lagrangian model’s outcome for the green area receptor, but fails to reproduce concentration gradients and hot-spots, driven by local sources’ emissions.