Detection and characterization of airborne pollen using lidars in Finland

Pollen has various effects on human health and the environment. Studies show that lidar (light detection and ranging) can detect the presence of pollen in the atmosphere, and it is possible to track airborne pollen using the depolarization ratio in the absence of other depolarizing non-spherical particles (e.g. dust).Since 2016, several pollen campaigns were performed at Vehmasmki (6244'N, 2733'E, 190 m above sea level) site, a rural forest area located ~18 km from the Kuopio cite centre, in Eastern Finland. The clean air in Finland favours the pollen study. This station is operated by the Finnish Meteorological Institute, and is permanently equipped with a multi-wavelength Raman polarization lidar PollyXT, a Halo Photonics StreamLine Pro Doppler lidar, a Vaisala CL61 ceilometer, and multiple in situ instruments. All three lidars are equipped with polarization channels and enable the investigation of the optical properties at the wavelengths of 355, 532, 910 and 1565 nm. In addition, a Hirst-type Burkard pollen sampler was placed 4 meters above ground level near the lidars, which enabled the microscopic identification of pollen types and the number concentration.During the pollination events, enhanced linear particle depolarization ratios (PDRs) were detected by lidars, suggesting the presence of non-spherical particles. A positive (negative) correlation was found between the pollen concentration (contribution of other aerosols) and PDRs. Depolarization ratios of pollen layers were measured at four wavelengths, allowing investigating its wavelength dependence. This could enable the distinction of pollen from other depolarizing aerosols. Results also highlight the suitability of the PDR at longer wavelengths for pollen detection. We have developed two pollen algorithms for characterizing the optical properties of pure pollen particles, based on PollyXT measurements. They were applied to evaluate the pollen depolarization ratio which is an essential parameter needed to separate pollen backscatter from the background aerosol backscatter. The algorithm was also applied for the aerosol classification, and identified different pollen types.