Extinction-related Angström exponent characterization of submicrometric volume fraction in atmospheric aerosol particles
Identificadores
URI: http://hdl.handle.net/10481/56240Metadatos
Afficher la notice complèteAuteur
Quirantes, A.; Guerrero Rascado, Juan Luis; Pérez Ramírez, Daniel; Foyo Moreno, Inmaculada; Ortiz-Amezcua, Pablo; Benavent Oltra, José Antonio; Lyamani, H.; Titos Vela, Gloria; Bravo Aranda, Juan Antonio; Cazorla, A.; Valenzuela, A.; Casquero Vera, Juan Andrés; Bedoya-Velásquez, Andrés Esteban; Alados Arboledas, Lucas; Olmo Reyes, Francisco JoséEditorial
Elsevier
Materia
Lidar Aerosol Graphical method Submicrometric fraction
Date
2019Patrocinador
Andalusia Regional Government through project P12-RNM-2409; Spanish Ministry of Sciences, Innovation and Universities (CGL2016-81092 and CGL2017 -90884 - REDT)Résumé
The AEAOD– ΔAEAOD grid proposed by Gobbi et al. (2007) is a graphical method used to visually represent the spectral characterization of aerosol optical depth (AOD), i.e. Angström exponent (AE) and its curvature, in order to infer the fine mode contribution (η) to the total AOD and the size of the fine mode aerosol particles. Perrone et al. (2014) applied this method for the wavelengths widely used in lidar measurements. However, in neither case does the method allow for a direct relationship between η and the fine mode fraction contribution to the total aerosol population. Some discussions are made regarding the effect of shape and composition to the classical AE-ΔAE plot. The potential use of particle backscatter measurements, widely used in aerosol characterization methods together with extinction measurements, is also discussed in the AE-ΔAE grid context. A modification is proposed that yields the submicron contribution to the total volume concentration by using particle extinction data, and a comparison to experimental measurements is made. Our results indicate that the use of a modified AE-ΔAE grid plot to directly obtain submicrometric and micrometric mode fraction to the total aerosol population is feasible if a volume-based bimodal particle size distribution is used instead of a number-based one.