Open Access Paper
13 September 2024 Aerosol classification in Cyprus using active and passive remote sensing techniques
A. Savva, A. Nisantzi, A. Ansmann, D. Hadjimitsis, R. E. Mamouri
Author Affiliations +
Proceedings Volume 13212, Tenth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2024); 1321217 (2024) https://doi.org/10.1117/12.3037304
Event: Tenth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2024), 2024, Paphos, Cyprus
Abstract
Limassol region in Cyprus, located in the Eastern Mediterranean, represents a major crossroads for various air masses, making the place a hub for mixing particles from both local and remote aerosol sources. The unique atmospheric conditions of the area offer an ideal place to study the vertical atmospheric structure. This study utilizes active and passive remote sensing techniques, such as the sun-photometer AERONET CUT-TEPAK station (Aerosol Robotic Network) and the Polly XT Raman LIDAR depolarization system available in Limassol (34.7°N, 33°E). An extended analysis of long-term ground-based measurements using AERONET Level 2.0 solar products is presented. The study focuses on the classification method proposed by Toledano et al. (2007) for different aerosol types. Aerosol optical depth at 440 nm (AOD) and Ångström Exponent at 440-870 nm (AE) are examined for 14 years (2010 - 2023). The results show a strong contribution of dust particles in spring months and continental particles in summer periods. Marine particles were found to be extremely dominant according to the classification. Subsequently, to examine the presence of dust particles in the marine’s classification, the study incorporates the particle depolarization ratio (PDR) from the LIDAR vertical profiles at 532 nm using the Klett method. Thus, a new aerosol scheme has been developed concluding in four aerosol categories (dominating conditions of marine aerosol (M), mineral dust (D), anthropogenic haze/ biomass burning (H+S), mixed aerosol).
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
A. Savva, A. Nisantzi, A. Ansmann, D. Hadjimitsis, and R. E. Mamouri "Aerosol classification in Cyprus using active and passive remote sensing techniques", Proc. SPIE 13212, Tenth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2024), 1321217 (13 September 2024); https://doi.org/10.1117/12.3037304
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KEYWORDS
Aerosols

Atmospheric particles

Depolarization

LIDAR

Optical properties

Active remote sensing

Passive remote sensing

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