Examining the characteristics of aerosols: a statistical analysis based on a decade of lidar and photometer observations at the Eastern border of ACTRIS

Abstract. A decade-long (2015–2024) analysis of aerosol properties was conducted at RADO-Bucharest station in Romania a key atmospheric observational site at the Eastern border of the Aerosol, Clouds and Trace gases Research Infra-structure (ACTRIS). This study aims to characterize the optical and microphysical properties of aerosols, classify predominant aerosol types, and investigate their seasonal variability and transport pathways based on long-term multiwavelength Raman lidar and sun/sky/lunar photometer measurements. Results indicate a dominance of fine-mode aerosols, with an average Aerosol Optical Depth (AOD) of ~0.2 and Ӓngström Exponent (AE) values between 1.5–2.0, highlighting pollution-driven aerosol regimes. Seasonal variations were observed, with continental aerosols prevailing in winter, dust transport peaking in spring (altitudes of 2–8 km), and biomass-burning aerosols increasing during summer. Marine aerosols were occasionally detected at ~2 km altitude, often mixed with dust. Analysis of 408 aerosol layers using the NATALI (Neural network Aerosol Typing Algorithm based on LIdar data) identified complex aerosol mixtures, with 63 high-resolution cases revealing a predominance of “dust polluted” and “continental smoke” types. Lidar-derived extinction Ӓngström coefficients (median ~0.9 in the low troposphere) and lidar ratios (~48 sr in the low troposphere, ~49 sr in the high troposphere) suggest varying optical properties linked to aerosol composition and absorption characteristics. FLEXPART (FLEXible PARTicle dispersion model) retro-plume simulations provided insights into aerosol source regions and transport patterns showing contributions from local emissions, long-range transported desert dust, and biomass burning events from Europe and North America. These findings emphasize the persistent influence of regional pollution and transported aerosols on air quality and climate. The integration of ground-based remote sensing and advanced retrieval algorithms like NATALI provides a robust framework for aerosol characterization, enhancing climate models and air quality assessments.