PMSS and gral inter-comparison: Strengths and weaknesses of the two models in reproducing Urban NOx levels in a real case application

Air dispersion models are useful tools for quantifying pollutant concentrations in urban environment however many issues related to the dispersion estimation within urban canopy still persist. Most of them concern the emissions estimation, the flow field reconstruction between obstacles (buildings, bridges, tunnels, etc.) and the pollutant dispersion driven by the estimated flow field. This study presents results of a model inter-comparison conducted in a real case study, focusing on a 6 km x 6 km square domain covering the city of Modena (Italy), between two Lagrangian dispersion models set-up with the aim of estimating the NOx concentrations produced by traffic flow within the urban area of the city. Comparisons are made between the Graz Lagrangian Model (a.k.a. GRAL) and the Parallel Micro SWIFT and SPRAY (a.k.a. PMSS) modelling suite, in terms of dispersion concentrations and computing cost. The horizontal resolution for both the models is set to 4 meters and the traffic emissions estimation is based on a bottom-up approach: the PTV VISUM traffic model is used to estimate traffic flows on the Modena urban road network and the EMEP/EEA cold and hot emission factors are employed to estimate related emissions. All the other urban emission sources were considered to contribute to the regional background concentrations and estimated with the WRF-Chem model, which estimates also initial and boundary meteorological conditions (multi-scale approach). The general objective of the inter-comparison is to use equivalent input data for both the models keeping the emissions and the meteorological initial and boundary/condition consistent so that any discrepancies in output would be the results of differences in the micro-scale dispersion models. Since different turbulence parametrisation and dispersion scheme are implemented in the two models, the goal of this study is to identify the strengths and the weaknesses of both the models in reproducing urban NOx concentrations, in a real case application, at urban traffic and urban background sites.