Aerosol typing results from AERONET data classification and NATALI retrieval

This study examines the results of two different methods for aerosol typing applied to active and passive remote sensing measurements, performed at a site in Magurele/Bucharest, Romania. In particular, we analyze the aerosol types reported as derived from AERONET (AErosol RObotic NETwork) measurements and NATALI (Neural Network Aerosol Typing Algorithm Based on Lidar Data) results as they are integrated within the DIVA platform. Each method has its own strengths and limitations but the study is focused on finding a better characterization of the aerosol types by using all available optical properties of aerosols measured at a particular site.