A model for simultaneous evaluation of NO₂, O₃ and PM₁₀ pollution in urban and rural areas: handling incomplete data sets with multivariate curve resolution analysis

Abstract. A powerful methodology, based on multivariate curve resolution alternating least squares (MCR-ALS) with quadrilinearity constraints, is proposed to handle complex and incomplete four-way atmospheric data sets, providing concise and easy interpretable results. Changes in air quality by nitrogen dioxide (NO₂), ozone (O₃) and particular matter (PM₁₀) in eight sampling stations located in Barcelona metropolitan area and other parts of Catalonia during the COVID-19 lockdown (2020) with respect to previous years (2018 and 2019) are investigated using such methodology. MCR-ALS simultaneous analysis of the 3 contaminants among the 8 stations and for the 3 years allows the evaluation of potential correlations among the pollutants even when having missing data blocks. NO₂ and PM₁₀ show correlated profiles due to similar pollution sources (traffic and industry), evidencing a decrease in 2019 and 2020 due to traffic restriction policies and COVID-19 lockdown, especially noticeable in the most transited urban areas (i.e., Vall d’Hebron, Granollers and Gràcia). Ozone evidences an opposed inter-annual trend, showing higher amounts in 2019 and 2020 respect to 2018 due to the decreased titration effect, more significant in rural areas (Begur) and in the control site (Obserbatori Fabra).