Understanding temporal and spatial changes of O or NO concentrations combining multivariate data analysis methods and air quality transport models.

The application of the multivariate curve resolution method to the analysis of temporal and spatial data variability of hourly measured O and NO concentrations at nineteen air quality monitoring stations across Catalonia, Spain, during 2015 is shown. Data analyzed included ground-based experimental measurements and predicted concentrations by the CALIOPE air quality modelling system at three horizontal resolutions (Europe at 12 × 12 km, Iberian Peninsula at 4 × 4 km and Catalonia at 1 × 1 km). Results obtained in the analysis of these different data sets allowed a better understanding of O and NO concentration changes as a sum of a small number of different contributions related to daily sunlight radiation, seasonal dynamics, traffic emission patterns, and local station environments (urban, suburban and rural). The evaluation of O and NO concentrations predicted by the CALIOPE system revealed some differences among data sets at different spatial resolutions. NO predictions, showed in general a better performance than O predictions for the three model resolutions, specially at urban stations. Our results confirmed that the application of the trilinearity constraint during the multivariate curve resolution factor analysis decomposition of the analyzed data sets is a useful tool to facilitate the understanding of the resolved variability sources.