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Light-scattering by Irregularly Shaped Particles including Black Carbon: Application to Elastic Backscatter Lidar
Light-scattering provides rich information on a large range of particles such as aerosols, blood cells, and colloidal suspensions. Among light-scattering techniques, elastic backscatter lidar allows sensing and characterizing of atmospheric constituents remotely. The development of an original elastic backscatter lidar technique, name PSR-EBL for Picosecond Short-Range Elastic Backscatter Lidar will be presented. The purpose of this technique is to measure backscattering radiative properties of aerosols based on the time-of-flight principle using short picosecond laser pulses with a bi-static configuration. One of the major advantages of the PSR-EBL technique is its ability to measure aerosol backscatter from a few meters away in order to determine, after calibration and inversion, their microphysical properties. This lidar technique has today all the necessary capabilities to remotely characterize, without sampling and without contact, aerosols close to their emission sources, whether natural (biomass fires) or anthropogenic (engines). An instrument based on this technique, named Colibri, was introduced to measure the spatio-temporal propagation and properties of aerosol plumes such as black carbon emissions from kerosene. However, the retrieval of accurate lidar products require a comprehensive knowledge of backscattering and extinction by particles, usually non-spherical. Different light-scattering models and experiments will be exposed to estimate the different the lidar-relevant parameters (i.e. backscattering, extinction, lidar ratio) for different aerosols (including soot, volcanic ashes). The use of these methods has allowed us to better understand the impact of several microphysical parameters of particles on the lidar-relevant parameters. For balck carbon, the use of the Rayleigh Debye Gans for Fractal Aggregates (RDG-FA) model is proposed for the first time to model in a simple manner the backscattering cross-sections and lidar ratio of soot particles, accounting for their fractal morphology. This approximate model has several advantages for remote-sensing, as it requires lower computational resources and may be easily integrated in lidar inversion. This approximate model has been successfully applied for estimating the number and mass concentration of kerosene black carbon emissions from lidar measurements.
Bio: Dr. Romain Ceolato is a Research Scientist at ONERA – The French Aerospace Laboratory– managed by the French Ministry of Defense. He received his MS degree in Fundamental Physics in 2010 and his Ph.D. degree in Optical Science in 2013 from the Institut Supérieur de l'Aéronautique et de l'Espace (SUPAERO). In 2012, he was a Visiting Scholar at Mississippi State University. Currently, he is a member of the Optronics Department at ONERA. Dr. Ceolato’s research interests cover different areas of light-scattering by particulate media and rough surfaces, in particular laser-based diagnostic methods, including elastic backscatter lidar for short-range applications.