Estimation of Particulate Matter Contributions from Desert Outbreaks in Mediterranean Countries (2015–2018) Using the Time Series Clustering Method

• Main Authors: Álvaro Gómez-Losada, José C. M. Pires
• Format: Article
• Language: English
• Published: MDPI AG 2021-12-01
• Series: Atmosphere
• Subjects: African dust; air pollution; hidden Markov models; particulate matter; PM_2.5/PM₁₀ ratio; principal component analysis
• Online Access: https://www.mdpi.com/2073-4433/12/1/5

North African dust intrusions can contribute to exceedances of the European PM₁₀ and PM_2.5 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 PM_2.5 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 µg·m⁻³ (Bosnia and Herzegovina), 8.8 ± 7.5 µg·m⁻³ (Spain), 7.0 ± 6.2 µg·m⁻³ (France), 8.1 ± 5.9 µg·m⁻³ (Croatia), 7.5 ± 5.5 µg·m⁻³ (Italy), 8.1 ± 7.0 µg·m⁻³ (Portugal), and 17.0 ± 9.8 µg·m⁻³ (Turkey). For PM_2.5, estimated contributions were 4.1 ± 3.5 µg·m⁻³ (Spain), 6.0 ± 4.8 µg·m⁻³ (France), 9.1 ± 6.4 µg·m⁻³ (Croatia), 5.2 ± 3.8 µg·m⁻³ (Italy), 6.0 ± 4.4 µg·m⁻³ (Portugal), and 9.0 ± 5.6 µg·m⁻³ (Turkey). The observed PM_2.5/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 PM_2.5 pollution profiles.