Vertical distribution, optical characterization and automated classification of airborne pollen from in-situ measurements

Abstract. Bioaerosols, such as pollen grains, play an important role in air quality, human health and atmospheric processes. However, their vertical distribution within the boundary layer remains insufficiently researched. In this study, we investigate the vertical profiles of pollen concentrations between 4 and 272 m a.g.l. at the Vehmasmäki station in Eastern Finland. In–situ measurements with optical pollen sensors at 4 m, 115 m, and 272 m were conducted simultaneously with ground-based observations from a Hirst-type volumetric air sampler and a Cloud Droplet Analyzer. Multiple campaigns were conducted during pollen seasons between 2021–2024, focusing on the dominant pollen types, i.e., birch and pine pollen. Optical pollen sensors agreed with Cloud Droplet Analyzer measurements during intensive pollen periods (R² ≥ 0.91). Polarization scatter plots for birch and pine pollen revealed distinct optical signatures, during predefined intensive pollen periods between 2021–2023, consistent with laboratory results. Furthermore, we assess how background fine-mode aerosol influences these signatures. During a major birch pollen episode in May 2024, pollen concentrations decreased with height. These vertical profiles were compared with predictions from the System for Integrated modeLling of Atmospheric coMposition (SILAM), which reproduced the vertical distribution from the observations, but systematically overestimated pollen concentrations at all heights. Moreover, a machine–learning classification approach combining optical pollen sensor measurements and meteorological variables demonstrated the possibility of identification of dominant pollen types. Our results demonstrate the feasibility of optical pollen sensors for continuous, real–time monitoring of dominant pollen taxa in boreal regions, from measurements in Vehmasmäki.