Trilinearity and component interaction constraints in the multivariate curve resolution investigation of NO and O3 pollution in Barcelona

Abstract

Multiway and multiset data analysis extensions of the multivariate curve resolution alternating least squares (MCR-ALS) method are proposed for the investigation of the temporal distribution of the pollution by nitric oxide (NO) and ozone (O(3)) in one sampling station in the urban centre of Barcelona (Catalonia, Spain), during the years 2000-2006. Different specific studies were performed considering the annual and pluriannual contamination by these two contaminants, individually or in combination using different data matrix augmentation strategies and multiway and multiset data analysis models. Daily, hourly and annual profiles were estimated describing different patterns and summarising the main contamination processes. The daily and night trends found were mainly attributed to traffic and photochemical processes favoured by light radiation. Moreover, winter-summer seasonal trends were also clearly detected and their changes over different years assessed. The extension MCR-ALS method to multiset data analysis using different constraints like non-negativity, trilinearity and interaction among components is confirmed to be a powerful method to improve the interpretability of the different contamination patterns in atmospheric contamination studies.