Articles | Volume 19, issue 14
https://doi.org/10.5194/amt-19-4779-2026
https://doi.org/10.5194/amt-19-4779-2026
Research article
 | 
24 Jul 2026
Research article |  | 24 Jul 2026

Real-time pollen dynamics and automated detection: novel insights from Wrocław (Poland) 2024–2025

Szymon Tomczyk, Małgorzata Werner, Małgorzata Malkiewicz, and Karol Bubel

Cited articles

Adamov, S., Lemonis, N., Clot, B., Crouzy, B., Gehrig, R., Graber, M. J., Sallin, C., and Tummon, F.: On the measurement uncertainty of Hirst-type volumetric pollen and spore samplers, Aerobiologia, 40, 77–91, https://doi.org/10.1007/s10453-021-09724-5, 2024. 
Adams-Groom, B., Selby, K., Derrett, S., Frisk, C. A., Pashley, C. H., Satchwell, J., King, D., McKenzie, G., and Neilson, R.: Pollen season trends as markers of climate change impact: Betula, Quercus and Poaceae, Sci. Total Environ., 831, 154882, https://doi.org/10.1016/j.scitotenv.2022.154882, 2022. 
Anderegg, W. R. L., Abatzoglou, J. T., Anderegg, L. D. L., Bielory, L., Kinney, P. L., and Ziska, L.: Anthropogenic climate change is worsening North American pollen seasons, P. Natl. Acad. Sci. USA, 118, e2013284118, https://doi.org/10.1073/pnas.2013284118, 2021. 
Andújar-Maqueda, J., Ortiz-Amezcua, P., Cariñanos, P., Abril-Gago, J., De Linares, C., de Arruda Moreira, G., Bravo-Aranda, J. A., Granados-Muñoz, M. J., Alados-Arboledas, L., and Guerrero-Rascado, J. L.: The role of atmospheric boundary layer wind and turbulence on surface pollen levels, Agr. Forest Meteorol., 371, 110584, https://doi.org/10.1016/j.agrformet.2025.110584, 2025. 
Beggs, P. J., Clot, B., Sofiev, M., and Johnston, F. H.: Climate change, airborne allergens, and three translational mitigation approaches, eBioMedicine, 93, 104478, https://doi.org/10.1016/j.ebiom.2023.104478, 2023. 
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Short summary
Our study examines how real-time pollen monitoring can be enhanced by retraining artificial intelligence models with locally collected data. Using the advanced Swisens Poleno Jupiter device in Wrocław, Poland, we recorded hourly pollen concentration changes and their relationship with meteorological conditions. Locally adapted models provide more accurate, timely information, reveal taxon-specific diurnal pollen variability, and improve allergy risk assessment.
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