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Evaluating the capability of regional-scale air quality models to capture thevertical distribution of pollutants

pubblicazioni - Articolo

Evaluating the capability of regional-scale air quality models to capture thevertical distribution of pollutants

L’articolo discute i risultati di un confronto modellistico relativo alla ricostruzione di profili verticali di variabili meteorologiche e di qualità dell’aria. L’esercizio condotto rappresenta un elemento di sostanziale novità nel campo della modellistica numerica di qualità dell’aria e costituisce quindi un significativo contributo al rafforzamento della competenza di RSE nel campo della modellistica di chimica e trasporto, le cui applicazioni riguardano svariate attività di Ricerca di Sistema.

The evaluation of regional air quality models is a challenging task, not only for the intrinsic complexity of the topic but also in view of the difficulties in finding sufficiently abundant, harmonized and time/spacewell- distributed measurement data. This study, conducted in the framework of AQMEII (Air Quality ModelEvaluation International Initiative), evaluates 4D model predictions obtained from 15 modelling groups and relating to the air quality of the full year of 2006 over the North American and European continents. The modelled variables are ozone, CO, wind speed and direction, temperature, and relative humidity. Modelevaluation is supported by the high quality in-flight measurements collected by instrumented commercial aircraft in the context of the MOZAIC programme. The models are evaluated at five selected domains positioned around major airports, four in North America (Portland, Philadelphia, Atlanta, Dallas) and one inEurope (Frankfurt). Due to the extraordinary scale of the exercise (number of models and variables, spatial and temporal extent), this study is primarily aimed at illustrating the potential for using MOZAIC data for regional-scale evaluation and the capabilities of models to simulate concentration and meteorological fieldsin the vertical rather than just at the ground. We apply various approaches, metrics, and methods to analyze this complex dataset. Results of the investigation indicate that, while the observed meteorological fields aremodelled with some success, modelling CO in and above the boundary layer remains a challenge and modelling ozone also has room for significant improvement. We note, however, that the high sensitivity of models to height, season, location, and metric makes the results rather difficult to interpret and to generalize.With this work, though, we set the stage for future process-oriented and in-depth diagnostic analyses.

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