Optical characterization of pure pollen types using a multi-wavelength Raman polarization lidar

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Abstract

We present a novel algorithm for characterizing the optical properties of pure pollen particles, based on the depolarization ratio values obtained in lidar measurements. The algorithm was first tested and validated through a simulator and then applied to the lidar observations during a 4- month pollen campaign from May to August 2016 at the European Aerosol Research Lidar Network (EARLINET) station in Kuopio (62°44′ N, 27°33′ E), in Eastern Finland. With a Burkard sampler, 20 types of pollen were observed and identified from concurrent measurements, with birch (Betula), pine (Pinus), spruce (Picea), and nettle (Urtica) pollen being the most abundant, contributing more than 90 % of the total pollen load, regarding number concentrations. Mean values of lidar-derived optical properties in the pollen layer were retrieved for four intense pollination periods (IPPs). Lidar ratios at both 355 and 532 nm ranged from 55 to 70 sr for all pollen types, without significant wavelength dependence. An enhanced depolarization ratio was found when there were pollen grains in the atmosphere, and an even higher depolarization ratio (with mean values of 0.25 or 0.14) was observed with the presence of the more non-spherical spruce or pine pollen. Under the assumption that the backscatterrelated Ångström exponent between 355 and 532 nm should be zero for pure pollen, the depolarization ratio of pure pollen particles at 532 nm was assessed, resulting in 0:24±0:01 and 0:36 ± 0:01 for birch and pine pollen, respectively. Pollen optical properties at 1064 and 355 nm were also estimated. The backscatter-related Ångström exponent between 532 and 1064 nm was assessed to be ∼ 0:8 (∼ 0:5) for pure birch (pine) pollen; thus the longer wavelength would be a better choice to trace pollen in the air. Pollen depolarization ratios of 0.17 and 0.30 at 355 nm were found for birch and pine pollen, respectively. The depolarization values show a wavelength dependence for pollen. This can be the key parameter for pollen detection and characterization.

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Shang, X., Giannakaki, E., Bohlmann, S., Filioglou, M., Saarto, A., Ruuskanen, A., … Komppula, M. (2020). Optical characterization of pure pollen types using a multi-wavelength Raman polarization lidar. Atmospheric Chemistry and Physics, 20(23), 15323–15339. https://doi.org/10.5194/acp-20-15323-2020

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