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Publications

AutoPollen special issue

The main outcomes of the EUMETNET AutoPollen programme are published in a special issue of the scientific journal Aerobiologia. All publications are made available open access to promote knowledge exchange and help grow the monitoring network. 

Tummon, F., Clot, B. Editorial: AutoPollen special issue. Aerobiologia 40, 1–2 (2024). 

Tummon, F., Adams-Groom, B., Antunes, C.M. et al. The role of automatic pollen and fungal spore monitoring across major end-user domains. Aerobiologia 40, 57–75 (2024). 

Erb, S., Berne, A., Burgdorfer, N. et al. Automatic real-time monitoring of fungal spores: the case of Alternaria spp.Aerobiologia 40, 123–127 (2024). 

Daunys, G., Šukienė, L., Vaitkevičius, L. et al. Comparison of computer vision models in application to pollen classification using light scattering. Aerobiologia 40, 109–121 (2024). 

Adamov, S., Pauling, A. A real-time calibration method for the numerical pollen forecast model COSMO-ART. Aerobiologia 39, 327–344 (2023). 

Triviño, M.M., Maya-Manzano, J.M., Tummon, F. et al. Variability between Hirst-type pollen traps is reduced by resistance-free flow adjustment. Aerobiologia 39, 257–273 (2023). 

Tummon, F., Bruffaerts, N., Celenk, S. et al. Towards standardisation of automatic pollen and fungal spore monitoring: best practises and guidelines. Aerobiologia 40, 39–55 (2024). 

Buters, J., Clot, B., Galán, C. et al. Automatic detection of airborne pollen: an overview. Aerobiologia 40, 13–37 (2024). 

Tummon, F., Adamov, S., Clot, B. et al. A first evaluation of multiple automatic pollen monitors run in parallel. Aerobiologia 40, 93–108 (2024). 

Adamov, S., Lemonis, N., Clot, B. et al. On the measurement uncertainty of Hirst-type volumetric pollen and spore samplers. Aerobiologia 40, 77–91 (2024). 

Clot, B., Gilge, S., Hajkova, L., Magyar, D., Scheifinger, H., Sofiev, M., Bütler, F., and Tummon, F. (2020). The EUMETNET AutoPollen programme: establishing a prototype automatic pollen monitoring network in EuropeAerobiologia, 1–9.

Clot, B., Gilge, S., Hajkova, L. et al. The EUMETNET AutoPollen programme: establishing a prototype automatic pollen monitoring network in Europe. Aerobiologia 40, 3–11 (2024). 

Other AutoPollen publications

M. González-Alonso, J. Oteros, M. Widmann, J.M. Maya-Manzano, C. Skjøth, L. Grewling, D. O’Connor, M. Sofiev, F. Tummon, B. Crouzy, B. Clot, J. Buters, E. Kadantsev, Y. Palamarchuk, M. Martinez-Bracero, F.D. Pope, S. Mills, B. Šikoparija, P. Matavulj, C.B. Schmidt-Weber, P.V. Ørby, Influence of meteorological variables and air pollutants on measurements from automatic pollen sampling devices. Science of The Total Environment  931, (2024)

Tummon, F., Alados Arboledas, L., Bonini, M., Guinot, B., Hicke, M., Jacob, J., Kendrovski, V., McCairns, W., Petermann, E., Peuch, V.-H., Pfaar, O., Siacrd, M., Sikoparija, B., and Clot, B. (2021). The need for Pan-European automatic pollen and fungal spore monitoring: A stakeholder workshop position paperClinical Translational Allergy.

Related scientific publications

Adamov, S., Lemonis, N., Clot, B., Crouzy, B., Gehrig, R., Graber, M.-J-, Sallin, C., and Tummon, F. (2021). On the measurement uncertainty of Hirst-type volumetric pollen and spore samplers. Aerobiologia

Addison-Smith, B., Wraith, D. & Davies, J.M. Standardising pollen monitoring: quantifying confidence intervals for measurements of airborne pollen concentration. Aerobiologia 36, 605–615 (2020)

Beggs, PJ, Clot, B.m Sofiev, M., Johnston, F.,  (2023). Climate change, airborne allergens, and three translational mitigation approaches. eBioMedicine

Chappuis, C., Tummon, F., Clot, B., Konzelmann, T., Calpini, B., and Crouzy, B. (2020). Automatic pollen monitoring: first insights from hourly data. Aerobiologia, 36, 159-170.

Crouzy, B., Stella, M., Konzelmann, T., Calpini, B., and Clot, B. (2016). All-optical automatic pollen identification: Towards an operational system. Atmospheric Environment, 140, 202-212.

Crouzy, B., Lieberherr, G., tummon, F., and Clot, B. (2022). False positives: handling them operationally for automatic pollen monitoring. Aerobiologia, 38, 429-432.

Erb, S., Berne, A., Burgdorfer, N. et al. (2023) Automatic real-time monitoring of fungal spores: the case of Alternaria spp. Aerobiologia 

Fernández-Rodríguez S, et al. (2018). Comparison of fungal spores concentrations measured with wideband integrated bioaerosol sensor and Hirst methodology. Atmospheric Environment

Huffman, J.A., Perring, A.E., Savage, N.J., Clot, B., Crouzy, B., Tummon, F., Shoshanim, O., Damit, B., Schneider, J., Sivaprakasam, V., Zawadowicz, M.A., Crawford, I., Gallagher, M., Topping, D., Doughty, D.C., Hill, S.C., and Pan, Y. (2020). Real-time sensing of bioaerosols: Review and current perspectives. Aerosol Science and Technology, 54, 465-495.

Kawashima, S., Thibaudon, M., Matsuda, S., Fujita, T., Lemonis, N., Clot, B., and Oliver, G. (2017). Automated pollen monitoring system using laser optics for observing seasonal changes in the concentration of total airborne pollen. Aerobiologia, 33, 351–362.

Kawashima S, et al. (2007). An algorithm and a device for counting airborne pollen automatically using laser optics. Atmospheric Environment

Lieberherr, G., Auderset, K., Calpini, B., Clot, B., Crouzy, B., Gysel-Beer, M., Konzelmann, T., Manzano, J., Mihajlovic, A., Moallemi, A., O’Connor, D., Sikoparija, B., Sauvageat, E., Tummon, F., and Vasilatou, K., (2021). Assessment of Real-time Bioaerosol Particle Counters using Reference Chamber Experiments. Atmospheric Measurement Techniques, 14, 7693-7706.

Maya-Manzano, J. M., Tummon, F., Abt, R., Allan, N., et al. (2023). Towards European automatic bioaerosol monitoring: Comparison of 9 automatic pollen observational instruments with classic Hirst-type traps. Science of the Total Environment, 866, 161220.

Oteros, J., García-Mozo, H., Alcázar, P., Belmonte, J., Bermejo, D., Boi, M., Cariñanos, P., Díaz de la Guardia, C., Bernández-González, D., González-Minero, F., Gutiérrez-Bustillo, A.M., Moreno-Grau, S., Pérez-Badía, R., Rodríguez–Rajo, F.J., Ruíz-Valenzuela, L., Suárez-Pérez, J., Trigo, M.M., Domínguez-Vilches, E., and Galán, C. (2015). A new method for determining the sources of airborne particles. Journal of Environmental Management, 155, 212–218.

Oteros, J., Sofiev, M., Smith, M., Damialis, A., Prank, M., Werchan, M., Wachter, R., Weber, A., Kutzora, S., Heinze, S., Herr, C.E.W., Menzel, A., Bergmann, K.C., Traidl-Hoffmann, C., Schmidt-Weber, C.B., and Buters J.T.M.  (2019). Building an automatic Pollen Monitoring Network (ePIN): Selection of optimal stations by clustering pollen zones. Science of the Total Environment, 688, 1263-1274.

Oteros, J., Weber, A., Kutzora, S., Rojo, J., Heinze, S., Herr, C., Gebauer, R., Schmidt-Weber, C.B., Buters, J.T.M. (2020). An operational robotic pollen monitoring network based on automatic image recognition, Environmental Research, 191, 110031.

Šantl-Temkiv, T., Sikoparija, B., Maki, T., Carotenuto, F., Amato, P., Yao, M., Morris, C.E., Schnell, R., Jaenicke, R., Pöhlker, C., DeMott, P.J., Hill, T.C.J., Huffman, A. (2019). Bioaerosol Field Measurements: Challenges and Perspectives in Outdoor Studies. Aerosol Science and Technology, 1-27.

Schaefer, J., Milling, M., Schuller, B.W., Bauer, B., Brunner, J.O.,  Traidl-Hoffmann, C., and Damialis, A. (2021). Towards automatic airborne pollen monitoring: From commercial devices to operational by mitigating class-imbalance in a deep learning approach. Science of The Total Environment, 796, 148932.

Šaulienė, I., Šukienė, L., Daunys, G., Valiulis, G., Vaitkevičius, L., Matavulj, P., Brdar, S., Panic, M., Sikoparija, B., Clot, B., Crouzy, B., and Sofiev, M. (2019). Automatic pollen recognition with the Rapid-E particle counter: the first-level procedure, experience and next steps. Atmospheric Measurement Techniques, 12, 3435-3452.

Sauvageat, E., Zeder, Y., Auderset, K., Calpini, B., Clot, B., Crouzy, B., Kozelmann, T., Lieberherr, G., and Tummon, F. (2020). Real-time pollen monitoring using digital holography. Atmospheric Measurement Techniques, 13, 1539–1550.

Sofiev, M., Vira, J., Kouznetsov, R., Prak, M., Soares, J., and Genikhovich, E. (2015). Construction of the SILAM Eulerian atmospheric dispersion model based on the advection algorithm of Michael Galperin. Geoscientific Model Development, 8, 3497–3522.

Sofiev, M. (2019). On possibilities of assimilation of near-real-time pollen data by atmospheric composition models. Aerobiologia, 35, 523-531.

Sofiev,M., Jeroen Buters, Fiona Tummon, Yalda Fatahi, Olga Sozinova, Beverley Adams-Groom, Karl Christian Bergmann, Åslög Dahl, Regula Gehrig, Stefan Gilge, Andrea Kofol Seliger, Rostislav Kouznetsov, Gian Lieberherr, David O’Connor, Jose Oteros, Julia Palamarchuk, Helena Ribeiro, Barbora Werchan, Matthias Werchan, Bernard Clot (2023), Designing an automatic pollen monitoring network for direct usage of observations to reconstruct the concentration fieldsScience of The Total Environment

Tesendic, D., Boberic Krsticev, D., Matavlulj, P., Brdar, S., Panic, M., Minic, V., and Sikoparija, B. (2020). RealForAll: Real-time System for Automatic Detection of Airborne Pollen. Enterprise Information Systems.

Triviño, M.M., Maya-Manzano, J.M., Tummon, F. Clot, B., et al. Variability between Hirst-type pollen traps is reduced by resistance-free flow adjustment (2023).  Aerobiologia

Tummon, F., Adamov, S., Clot, B., Crouzy, B., Gysel-Beer, M., Kawashima, S., Lieberherr, G., Manzano, J., Markey, E., Moallemi, A., and O’Connor, D. (2021). A first evaluation of multiple automatic pollen monitors run in parallel. Aerobiologia