Artikel ; Online: Laboratory Evaluation of the (355, 532) nm Particle Depolarization Ratio of Pure Pollen at 180.0° Lidar Backscattering Angle
Remote Sensing, Vol 14, Iss 3767, p
2022 Band 3767
Abstract: While pollen is expected to impact public human health and the Earth’s climate more and more in the coming decades, lidar remote sensing of pollen has become an important developing research field. To differentiate among the pollen taxa, a polarization ... ...
| Abstract | While pollen is expected to impact public human health and the Earth’s climate more and more in the coming decades, lidar remote sensing of pollen has become an important developing research field. To differentiate among the pollen taxa, a polarization lidar is an interesting tool since pollen exhibit non-spherical complex shapes. A key attribute is thus the lidar particle depolarization ratio ( PDR ) of pollen, which is however difficult to quantify as pollen are large and complex-shaped particles, far beyond the reach of light scattering numerical simulations. In this paper, a laboratory π-polarimeter is used to accurately evaluate the PDR of pure pollen, for the first time at the lidar exact backscattering angle of 180.0°. We hence reveal the lidar PDR of pure ragweed, ash, birch, pine, cypress and spruce pollens at 355 and 532 nm lidar wavelengths, as presented at the ELC 2021 conference. A striking result is the spectral dependence of the lidar PDR , highlighting the importance of dual-wavelength (or more) polarization lidars to identify pollen taxa. These spectral and polarimetric fingerprints of pure pollen, as they are accurate, can be used by the lidar community to invert multi-wavelength lidar polarization measurements involving pollen. |
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| Schlagwörter | lidar particle depolarization ratio ; pure pollen ; polarization lidar ; laboratory ; Science ; Q |
| Thema/Rubrik (Code) | 333 |
| Sprache | Englisch |
| Erscheinungsdatum | 2022-08-01T00:00:00Z |
| Verlag | MDPI AG |
| Dokumenttyp | Artikel ; Online |
| Datenquelle | BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl) |
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