New operational perspective to identify aerosol in real-time with a pioneering algorithm (CONIOPOL) based on single wavelength polarization lidar (CL61)

Abstract. Air quality monitoring and climate studies require continuous, vertically resolved observations to characterize aerosols and their impact on radiation, cloud microphysics, and atmospheric composition. In this study, we present CONIOPOL (CONIOlogy + POLarization), an automated depolarization-based classification algorithm developed with the polarized Automatic Lidar Ceilometer (ALC), CL61 (Vaisala Oyi, FIN) installed at Uccle, Belgium. The algorithm combines linear depolarization ratio (LDR), attenuated backscatter, and cloud-base height retrievals to distinguish between aerosols, clouds, and precipitation, and to further classify aerosol subtypes.

One full year (February 2024–January 2025) of observations was analyzed to retrieve and evaluate the seasonal and vertical distributions of major aerosol categories, with results compared against Copernicus Atmosphere Monitoring Service (CAMS) model forecast outputs. The CONIOPOL algorithm successfully identified different types of aerosol – including dust, smoke, hygroscopic, and mixed aerosols – demonstrating strong temporal and vertical coherence with CAMS simulations. In particular, dust and smoke plumes detected above 1000 m showed a good agreement with it.

Despite its spectral limitations, the single-wavelength lidar provides continuous, high-resolution, and climatologically consistent aerosol classification, offering valuable insights into the seasonal evolution of aerosol types over mid-latitude Europe. These findings underscore the potential of depolarization-capable ALCs for long-term aerosol and air quality climatology, bridging temporal gaps between satellite, in situ, and multi-wavelength lidar observations.