Invisible aerosol layers: improved lidar detection capabilities by means of laser-induced aerosol fluorescence

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Abstract. One of the most powerful instruments for studying aerosol particles and their interactions with the environment is atmospheric lidar. In recent years, fluorescence lidar has emerged as a useful tool for identifying aerosol particles due to its link with biological content. Since 2022, this technique has been implemented in Leipzig, Germany. This paper describes the experimental setup and data analysis, with a special emphasis on the characterization of the new fluorescence channel centered at 466 nm. The new capabilities of the fluorescence lidar are examined and corroborated through several case studies. Most of the measurement cases considered are from the spring and summer of 2023, when large amounts of biomass-burning aerosol from the huge forest fires in Canada were transported to Europe. The fluorescence of the observed aerosol layers is characterized. For wildfire smoke, the fluorescence capacity was typically in the range of 2–7 x 10-4, which aligns well with the values reported in the literature, with slightly larger values. The key aspects of this study are the capabilities of the fluorescence lidar technique, which can potentially improve not only the typing but even the detection of aerosol particles. In several measurement cases with an apparently low aerosol load, the fluorescence channel clearly revealed the presence of aerosol layers that were not detectable with the traditional elastic-backscatter channels. This capability is discussed in detail and linked to the fact that fluorescence backscattering is related to aerosol particles only. A second potential of the fluorescence technique is the distinction between non-activated aerosol particles and hydrometeors, given water's inability to exhibit fluorescence. A smoke-cirrus case study suggests an influence of the aerosol layer on cloud formation, as it seems to affect the elastic backscatter coefficient within the cloud passing time. These mentioned applications promise huge advancements towards a more detailed view of the aerosol-cloud interaction problem.

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