Optical properties of PM2.5 particles: Results from a monitoring campaign in southeastern Italy. (15th April 2019)

• Record Type: Journal Article
• Authors: Romano, Salvatore; Perrone, Maria Rita; Pavese, Giulia; Esposito, Francesco; Calvello, Mariarosaria
• Is Part Of: Atmospheric environment. Volume 203(2019)
• Page Start: 35
• Page End: 47
• Publication Date: 2019-04-15
• Subjects: Intensive optical parameters -- Extensive optical parameters -- PM2.5 particles -- Graphical frameworks -- Particle identification methodology; Air -- Pollution -- Periodicals; Air -- Pollution -- Meteorological aspects -- Periodicals; 551.51
• DOI: 10.1016/j.atmosenv.2019.01.037
• Languages: English
• ISSNs: 1352-2310

Abstract

Abstract: The performance of aerosol classification schemes based on intensive optical parameters and applied to mixed particle populations monitored at the surface has been investigated to test the ability of optical parameters to identify different types of particles/particle mixtures and explore their complex features. The results show that the combination of two intensive optical parameters does not allow for the unique identification of different particle types. The classification scheme based on the Absorption Ångström Exponent (AAE) as a function of the Scattering Ångström Exponent (SAE) and color-coded by the Single Scattering Albedo difference (dSSA) is a good graphical framework to discriminate between different types of particle/particle mixtures. This aerosol classification scheme has been applied to study the optical properties of heterogeneous PM2.5 particles that were monitored at a coastal site of the Central Mediterranean and were significantly affected by both natural and anthropogenic sources also because of long-range transport from surrounding countries. The calculated AAE, SAE, and dSSA hourly means smoothly and continuously vary within their respective range (0.6–3.4, −0.7–3.0, and −0.33–0.52, respectively) because of the different mixing degree of different types of particles. Consequently, the main features of the particle populations depend on the range of the AAE, SAE, and dSSA values. Eight different clusters have been selected within the used graphical framework to identify four key particle populations (dust, marine, OC-dominated, and BC-dominated particles) and four particle mixtures dominated by key aerosol populations. In addition, their main features have been characterized. Particle mixtures consisting of large and low-absorbing particles (LLAP), small and high-absorbing particles (SHAP), dominated by dust, and large organic particles have been characterized. Marine, LLAP, and mixed dust clusters with a SAE value below 1 are responsible for aerosol scattering coefficients (σs ; at 470 nm) below 100 Mm −1 . Conversely, SHAP, BC-dominated, and OC-based mixtures are responsible for the highest σs values and represent dominant particles species. Highlights: Characterization of extensive and intensive optical properties of PM2.5 particles. Aerosol classification schemes based on intensive parameters were tested. Selection of the best intensive optical parameters for particle identification. PM2.5 key and mixed particle populations were classified by 8 different clusters. The key particle types include desert dust, marine, OC- and BC-dominated.