Proceedings of the 11 th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes Page 281 MODEL BASED YEARLY AIR QUALITY EVALUATION ON A VERY COMPLEX TERRAIN ALPINE REGION (VALLE D’AOSTA) Camillo Silibello 1 , Sandro Finardi 1 , Tommaso Pittini 1 , Tiziana Magri 2 , Giordano Pession 2 1 ARIANET S.r.l., via Gilino 9, 20128 Milano, Italy 2 ARPA Valle d’Aosta, Loc. Grande Charrière 44, 11020 Saint-Christophe, Italy INTRODUCTION European legislation contemplates the combined use of monitoring data, emission inventories and modelling techniques to assess and manage air quality. Aosta valley is one of the deepest and longest valley of the Alps: the strong terrain complexity of the regional territory has induced the Regional Environmental Protection Agency (ARPA-VdA) to employ 3D dispersion models to study air pollution within this valley. The promising results obtained using Lagrangian particle models (Pession et al., 2005) have suggested to test the capability of the Atmospheric Modelling System (AMS) Aria RegionalTM, based on the 3D Flexible Air quality Regional Model (FARM), to reproduce observed concentration levels in such complex situation. The AMS has been applied to a first reference year (1999) in a nested way (see Figure 1) starting from national- scale fields (meteorology and pollutants concentra-tions) coming from the national MINNI project (Zanini et al., 2004; Silibello et. al, 2005). The AMS includes four subsystems to: reconstruct flows and turbulence parameters; apportion data from emission inventories to grid cells, perform air quality simulations over the selected domain and compute the air quality indicators required by the EC directives (Figure 2). Emission data coming from the regional inventory have been integrated with data from national and foreign neighbours regions, while meteorological fields have been derived integrating background national scale field, estimated by RAMS model (Cotton et al., 2003), with local surface based observations by means of MINERVE processor (Aria Technologies, 2001). The regional scale meteorological fields together with land cover information (e.g. roughness length) and chemical species Fig. 1; Nesting from MINNI fields to Valle d’Aosta region. AIR QUALITY ASSESSMENT Chemical- transport sub-system Emission sub-system Meteo sub-system Minerve MINNI/RAMS meteo fields Land-use and topography meteo reference year INEMAR, other inventories Space, time, species tables Emission Manager Emission reference scenario Conc fields MINNI conc. fields FARM SurfPro B.C. Bounder Postprocessing sub-system Dep. vel. diffusivities AIR QUALITY ASSESSMENT Chemical- transport sub-system Emission sub-system Meteo sub-system Minerve MINNI/RAMS meteo fields Land-use and topography meteo reference year INEMAR, other inventories Space, time, species tables Emission Manager Emission reference scenario Conc fields MINNI conc. fields FARM SurfPro B.C. Bounder Postprocessing sub-system Dep. vel. diffusivities Fig. 2; AMS used to perform air quality evaluation over Valle d’Aosta region from MINNI project.