Título Estimation of Particulate Matter Contributions from Desert Outbreaks in Mediterranean Countries (2015-2018) Using the Time Series Clustering Method
Autores GÓMEZ LOSADA, ALVARO, Pires, Jose C. M.
Publicación externa Si
Medio Atmosphere
Alcance Article
Naturaleza Científica
Cuartil JCR 3
Cuartil SJR 2
Impacto JCR 3.11
Impacto SJR 0.692
Fecha de publicacion 01/01/2021
ISI 000609738600001
DOI 10.3390/atmos12010005
Abstract North African dust intrusions can contribute to exceedances of the European PM10 and PM2.5 limit values and World Health Organisation standards, diminishing air quality, and increased mortality and morbidity at higher concentrations. In this study, the contribution of North African dust in Mediterranean countries was estimated using the time series clustering method. This method combines the non-parametric approach of Hidden Markov Models for studying time series, and the definition of different air pollution profiles (regimes of concentration). Using this approach, PM10 and PM2.5 time series obtained at background monitoring stations from seven countries were analysed from 2015 to 2018. The average characteristic contributions to PM10 were estimated as 11.6 +/- 10.3 mu g.m(-3) (Bosnia and Herzegovina), 8.8 +/- 7.5 mu g.m(-3) (Spain), 7.0 +/- 6.2 mu g.m(-3) (France), 8.1 +/- 5.9 mu g.m(-3) (Croatia), 7.5 +/- 5.5 mu g.m(-3) (Italy), 8.1 +/- 7.0 mu g.m(-3) (Portugal), and 17.0 +/- 9.8 mu g.m(-3) (Turkey). For PM2.5, estimated contributions were 4.1 +/- 3.5 mu g.m(-3) (Spain), 6.0 +/- 4.8 mu g.m(-3) (France), 9.1 +/- 6.4 mu g.m(-3) (Croatia), 5.2 +/- 3.8 mu g.m(-3) (Italy), 6.0 +/- 4.4 mu g.m(-3) (Portugal), and 9.0 +/- 5.6 mu g.m(-3) (Turkey). The observed PM2.5/PM10 ratios were between 0.36 and 0.69, and their seasonal variation was characterised, presenting higher values in colder months. Principal component analysis enabled the association of background sites based on their estimated PM10 and PM2.5 pollution profiles.
Palabras clave African dust; air pollution; hidden Markov models; particulate matter; PM2.5/PM10 ratio; principal component analysis
Miembros de la Universidad Loyola

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