Performance of the Aerosol Species Separation Algorithm (ASSA) Using Data from a Raman-Depolarization Lidar System at Thessaloniki, Greece

The aerosol species separation algorithm (ASSA) is a method designed to retrieve vertical concentration profiles of individual aerosol species by combining measurements from lidar systems and spectrophotometers. The ASSA operates as a forward model, simulating as the first step the attenuated backscatter and volume depolarization ratios at various wavelengths initially measured by lidar systems. Subsequently, it extends these simulations to reproduce radiance spectra obtained from co-located spectrophotometers by integrating a radiative transfer model. Currently, the ASSA relies on a lookup table (LUT) of intensive aerosol properties that correspond to mixtures generated from up to eight pure aerosol species as these are defined in the OPAC database. In this study we are focusing on the first step and investigating the performance of the algorithm when solely fitting nighttime data from the Thessaloniki lidar system are used. The algorithm identifies the ensemble of mixture/mass concentration combinations that best fit the elastic and Raman 4 primary species attenuated backscatter and depolarization ratio profiles.