Spatial patterns of conditions leading to peak O3 concentrations revealed by clustering analysis of modeled data

摘要: Air quality models are currently the best available tool to estimate ozone (O3) concentrations in Metropolitan Area of Buenos Aires (MABA). While DAUMOD-GRS has been satisfactorily evaluated against observations urban area, a Monte Carlo (MC) analysis showed that it is region around MABA, where lack impedes model testing, concentrates not only greatest estimated O3 peak levels but also largest uncertainty. In this work, we apply clustering these MC outcomes order study spatial patterns conditions leading hourly concentrations. Results show families distribute, as emissions, radially city. A cluster exhibiting an morning dominates low-emission areas, behavior can be explained both from theory and few monitoring campaigns carried out Its distinct dynamics compared with typical diurnal profile occurring area suggests need new measurements surroundings MABA which could contribute improve our understanding formation drivers region. The results illustrate potential applying on large ensembles modeled data better understand variability solutions.