This study presents a comprehensive evaluation of the combination of the regional scale chemistry-transport model DEHM (Danish Eulerian Hemispheric Model) and the Gaussian plume-in-grid model UBMv10 (Urban Background Model). The focus of the study was centred around the following research question: the combination of an Eulerian regional scale approach and a Gaussian high-resolution/local scale approach improves the performance from evaluation with measurements compared to the Eulerian regional scale approach alone. We also investigated the research question that the integrated Eulerian/Gaussian approach has a similar performance as Eulerian models set up with the same high spatial resolution. The DEHM/UBM model has been run for a domain covering Denmark, Finland, Norway and Sweden with a 1 km × 1 km spatial resolution, producing hourly concentration estimates for four decades, 1979–2018. The results were evaluated against rural and urban background measurements in the four countries and the performance of the DEHM/UBM model was compared to the performance of the DEHM model based on a similar evaluation. The comparison showed that the DEHM/UBM model, in general, performs similar to the DEHM model, however, DEHM/UBM captures the interannual variability better in most cases. The DEHM/UBM model results for 2015 were also compared with corresponding high-resolution results from the chemistry-transport models SILAM (System for Integrated modeLling of Atmospheric coMposition) and MATCH (Multi-scale Atmospheric Transport and CHemistry model) for the four Nordic capitals; Copenhagen, Helsinki, Oslo and Stockholm. This model comparison was carried out to evaluate and compare the performance of the relatively simple, yet computationally fast approach of the DEHM/UBM model setup to the more time-consuming approaches of applied regional scale models on very high-resolution. The DEHM/UBM model performed similarly to SILAM and MATCH for most components, however, the 3D models performed better with respect to capturing the differences between rural and urban settings for the four capitals.