Land use regression (LUR) models have become a popular tool to capture small-scale variations in air pollution exposures in epidemiological analyses, and have been developed with a variety of approaches with no clear indication of the most efficient and appropriate one. We evaluated the performance of the LUR model for NO2 developed for the European Study of Cohorts for Air Pollution Effects (ESCAPE) for Catalunya, Spain, compared to two other LUR models derived locally and independently for two cohort studies (INMA-Sabadell and REGICOR-Girona) in different sub-areas of the ESCAPE domain. We made use of sampling campaigns from the three studies as independent sets of measurements by which to evaluate each model. We compared changes in R2 and measures of bias when applying each model to its own dataset vs. the independent datasets from the other studies. The three studies differed principally in their scale of analysis (from urban area only for INMA-Sabadell to large province covering urban and rural areas for ESCAPE-Catalunya and REGICOR-Girona) and sampling protocol (e.g. site selection).