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https://doi.org/10.5194/egusphere-2026-2699
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/egusphere-2026-2699
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
29 May 2026
| 29 May 2026
Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Bioaerosols outcompete dust as dominant immersion-mode-INPs in central Europe and redefine INP parameterizations
Abstract. Knowledge gaps in the source and parameterization of ice-nucleating particles (INPs) remain a major uncertainty in quantifying the properties and climate impacts of mixed-phase clouds (MPCs). Bioaerosols are increasingly recognized as important INPs for MPCs, yet it is unclear whether their contribution is critical through modelling studies. We investigate this using field observations at a semi-rural site in the central Europe, combining INP and aerosol measurements, remote sensing, and air-mass source analysis. We synergically use the results of in-situ and offline measurements to identify INPs originated from different sources, including biological aerosols, dust, and biomass burning aerosols, and to quantify their abundance and relative contributions to total INPs. More than 85% of immersion-mode INPs (>−24°C) are heat-labile and significantly correlated with fluorescent biological aerosols particles and pollen, while heat-resistant INPs (<~10%) are likely mineral dust, while biomass burning is an insignificant source. The proposed bioaerosol-ware INP parameterization reproduces observations across multi-regional datasets, showing that neglecting bioaerosol-INPs results in an average ~50% (~32%) bias in predictions of immersion-mode INPs active warmer than −15°C (−24°C), with frequent deviations of up to an order of magnitude from observations.
How to cite. Gao, K., Foskinis, R., Gidarakou, M., Violaki, K., Li, G., Brem, B. T., Erb, S., Clot, B., Graber, M.-J., Sikoparjja, B., Matavulj, P., Licina, D., Zhang, C., Crouzy, B., Papayannis, A., Kanji, Z. A., and Nenes, A.: Bioaerosols outcompete dust as dominant immersion-mode-INPs in central Europe and redefine INP parameterizations, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2026-2699, 2026.
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Laboratory of Atmospheric Processes and Their Impacts, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
present address: Department of Environmental Systems Science, Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Romanos Foskinis
Laboratory of Atmospheric Processes and Their Impacts, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
Environmental Remote Sensing Laboratory, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
Marilena Gidarakou
Laser Remote Sensing Unit, Physics Department, National Technical University of Athens, Zografou, Greece
Kalliopi Violaki
Laboratory of Atmospheric Processes and Their Impacts, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
Guangyu Li
Department of Environmental Systems Science, Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
present address: Laboratory for Microwave Spatial Intelligence and Cloud Platform, Deqing Academy of Satellite Applications, Deqing, China
Benjamin Tobias Brem
PSI Center for Energy and Environmental Sciences, Villigen PSI, Switzerland
Sophie Erb
Federal Office of Meteorology and Climatology MeteoSwiss, Payerne, Switzerland
Bernard Clot
Federal Office of Meteorology and Climatology MeteoSwiss, Payerne, Switzerland
Marie-José Graber
Federal Office of Meteorology and Climatology MeteoSwiss, Payerne, Switzerland
Branko Sikoparjja
Biosense Institute - Research and Development Institute for Information Technologies in Biosystems, University of Novi Sad, Novi Sad, Serbia
Predrag Matavulj
Institute for Data Science, University of Applied Sciences North – Western Switzerland, Bahnhofstrasse 6, Windisch, Switzerland
Dusan Licina
Human-Oriented Built Environment Lab, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
Cuiqi Zhang
Department of Environmental Systems Science, Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Benoît Crouzy
Federal Office of Meteorology and Climatology MeteoSwiss, Payerne, Switzerland
Alexandros Papayannis
Laboratory of Atmospheric Processes and Their Impacts, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
Laser Remote Sensing Unit, Physics Department, National Technical University of Athens, Zografou, Greece
Zamin A. Kanji
Department of Environmental Systems Science, Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Athanasios Nenes
CORRESPONDING AUTHOR
Laboratory of Atmospheric Processes and Their Impacts, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
Centre for Studies of Air Quality and Climate Change, Institute of Chemical Engineering Sciences, Foundation for Research and Technology Hellas, Patras, Greece
Short summary
This study identified bioaerosols (>85%) as the dominant source for ice nucleating particles in mixed-phase clouds at a semi-rural site in central Europe, using a combination of in-situ, remote sensing and airmass modelling analysis. We developed a bioaerosol-aware ice nucleating particle parameterization that outperformed existing dust-only schemes across multiple field datasets. These findings improve representation of bioaerosol–cloud interactions and reduce uncertainty in climate feedback.
This study identified bioaerosols (>85%) as the dominant source for ice nucleating particles in...
The authors present a field study conducted in Payerne, Switzerland, during which they collected an extensive dataset of ice nucleating particles (INPs), fluorescent particles, pollen grains, other aerosol properties, and remote-sensing measurements. Based on a careful analysis of these data, they conclude that biological aerosol particles are more important immersion-mode INPs than dust across a wide temperature range. They compare established INP parameterizations with newly developed parameterizations that incorporate the the ratio and/or the concentration of fluorescent particles to account for the biological component of INPs. These new parameterizations perform better and reproduce measured INP concentrations from independent datasets very well.
I would like to congratulate the authors on this highly relevant and very well-executed study. I only have two “major” comments, which I am confident can be addressed relatively quickly.
About the HIRST data
In line 175, Hirst_Total is defined as the concentration of 48 pollen types larger than 10 µm.
However, in line 246, you write:
"(...) ABC_WIBS numbers are much larger than Hirst_Total (including pollen, fungi and fungal spores measured by a Hirst) (...)"
Do you mean that Hirst_Total includes fungi and fungal spores here? If so, this contradicts the definition given earlier. If not, what exactly do you mean?
Similarly, in line 357, you write:
"Figure 4 further shows that pollen particles (likely also fungi and fungal spores, see Supplement Figs. S6 to S8) represented by Hirst_Total are significantly correlated (...)"
Again, it is unclear whether fungal spores are included in Hirst_Total. If they are not, on what basis do you conclude that "likely also fungi and fungal spores" are significantly correlated with INPs?
If fungal spores are included, then the phrase "likely also fungi and fungal spores" is confusing. At least one of the authors must have analyzed the Hirst tapes directly and therefore you should absolutely know if and (if you counted them) how much fungal spores (of certain species/genera) were present.
Therefore, please clarify the following points:
In addition, I strongly suggest including a figure showing the relative abundance of the detected pollen taxa (and fungal spores, if available), for example in Supplement Fig. S6. Not all detected pollen taxa are expected to exhibit ice nucleating activity at the same temperatures, or even at all, so this information would be highly valuable.
Interpretation of WIBS data
Line 356: You cite Tang et al. (2022) after stating that A particles are representative of bacteria and fungal spores. However, Tang et al. did not directly measure this. Instead, they refer to chamber studies conducted with the older WIBS-4 instrument, which uses different detector gain settings and is therefore not directly comparable to the instrument used here.
I believe it is important to discuss direct in situ comparison studies (e.g., WIBS versus HIRST measurements or biological tracers), particularly regarding ABC particles, since these show the strongest correlation with INPs and may therefore contribute most substantially to the observed INP population.
Since you deployed both a WIBS and a HIRST instrument, as well as a Rapid-E, such an analysis could potentially be performed using your own dataset. However, I understand from the manuscript that a future publication based on these data is planned where this might be examined in detail. If such an analysis is not planned, I would strongly encourage the authors to include it here, as it would be a missed opportunity. If it is planned for future work, then the present manuscript should at least provide a more comprehensive discussion of the relevant literature.
In that case, the literature suggests that ABC particles, rather than A particles, are generally more representative of fungal spores (e.g., Clancy et al., 2025; Gratzl et al., 2025; Sarangi et al., 2022). This should be discussed in detail, including how it might affect the interpretation of which particle types are acting as INPs in this study. Similarly, it would be useful to discuss which WIBS fluorescence classes are most representative of pollen grains. For example, Clancy et al. (2025) report that BC particles, rather than ABC particles, are most strongly associated with pollen.
I would also suggest adding a brief discussion of what is currently known about the ice nucleating activity of the detected PBAPs, particularly pollen grains and, if relevant, fungal spores.
For example, in line 360, I would expect that most pollen taxa detected by the Rapid-E have previously been tested for ice nucleating activity and that many exhibit at least some degree of activity. How much do the remaining taxa detected only by the Hirst instrument contribute to the overall pollen concentration? Can this difference alone explain the observed difference in correlation coefficients?
Or could the discrepancy instead arise because fungal spores are included in the Hirst measurements?
Minor comments
78: After mentioning Cornwell et al., who identified bioaerosols as the primary source of INPs, you could also cite Gratzl et al. (2025), who specifically identified fungal spores as the dominant source in northern Finland.
99: What type of forest?
Section 2.2
DRINCZS: How many droplets were analyzed per sample? What was the droplet volume? How were atmospheric INP concentrations calculated from the measurements?
Section 2.3.1
142: Please explain what the Forced Trigger mode is, or at least its purpose. This becomes clearer in line 148, but it is not immediately obvious that the threshold is derived from the Forced Trigger measurements.
143: Do you mean any of the three fluorescence channels rather than detectors, since there are only two detectors measuring fluorescence intensity?
144–145: Please briefly explain which particle classes (A, B, AB, etc.) fluoresce in which channels. This may not be obvious to readers unfamiliar with the WIBS instrument.
151–156: This is only a suggestion, but it may be useful to include a table summarizing all concentration metrics derived from the WIBS and the other instruments. A large number of concentration types are introduced throughout the manuscript, and a summary table would improve readability.
262: I suggest adding "that are not detected as ABC particles" after "including large FBAPs" or a similar clarification.
Section 3.2
Why is this particular case study discussed in the main text, whereas the others are included only in the Supplement? Is there a specific reason for highlighting this case?
Figure 3: The rainbow color scale used in panels k and l is outdated. Does the blue stripe near the bottom of the panels (~500 m) indicate that no data were available below that height? The unit "a.u." should also be included directly in the plots.
Section 3.3
335: You write:
"Total_WIBS (i.e., total particles between 0.5 and 30 μm detected by WIBS) generally shows a weak correlation with N_INP (ρ_Pearson and ρ_Spearman < 0.2), reflecting the scarcity of INPs relative to the total abundance of even coarse particles for warm MPCs."
Based on Total_WIBS alone you cannot conclude that this is true for coarse particles, since I guess they are only a minor fraction of Total_WIBS. You should refer to DELTA_coarse here.
350: Why are fungal spores excluded here? Most fungal spores are larger than 2.5 µm.
Figure 5: I do not fully understand the added value of Fig. 5b relative to Fig. 5a. Could the authors clarify this point? Furthermore, how can all INPs active above −12°C be heat-labile in panel c if this is not apparent in panel a? Please elaborate.
397: Change “and” soil dust to “or” soil dust (since just with heating you cannot be sure of either).
410–412: This sentence is very long and could be split into two shorter sentences to improve readability.
464–465: Is there a reference supporting the statements regarding more intense aging and reduced ice-nucleating activity? If not, please reformulate this as a possible explanation rather than a conclusion.
471 (and also line 302): Must heat-labile INPs at low temperatures necessarily be FBAPs (or PBAPs)? Other possibilities should also be considered and discussed.
Table 1 (line 477): WIBS_ratio is not equal to the difference between Fluo_WIBS and Total_WIBS. That quantity would correspond to NonFluo_WIBS.
Supplement
Figure S12: Data appear to be missing for panels b, c, and f.
Case studies in general: If the authors wish to retain all case studies in the Supplement, it would be very helpful to include a brief explanatory paragraph for each one, similar to the descriptions provided in the main text. Otherwise, it is difficult for readers to interpret their significance.
S10: Are Groups 1, 2, and 3 simply different dates, or are they referred to as groups for a specific reason?
Middle of paragraph: "In contrast" instead of "B contrast".
Microscopy images: I personally appreciate that the authors included these images. If possible, I would suggest increasing both their size and image quality.
Figure S6c: Does "Spores" refer to unidentified fungal spores? Were all observed spores marked in the images? This relates again to the question of whether fungal spores were included in the analysis and, if not, why they were excluded. It may also be worth noting that only one dust particle is marked, although several more appear to be present in the images, which is somewhat difficult to assess given the current image quality.
Technical corrections
119: "For" instead of "Fpr".
174: Change "will be replaced" to "were replaced".
256: Add "of" after "(mostly >0.05)".
Figure 6, line 428: "n =" is missing before "16".
References:
Clancy, J. H., Markey, E., Martínez-Bracero, M., Maya-Manzano, J. M., McGillicuddy, E. J., Sewell, G., Sarda-Estève, R., Baisnée, D., Vélez-Pereira, A. M., Davis, G., and O’Connor, D. J.: Comparative Analysis of Real-Time Fluorescence-Based Spectroscopic Instruments: Bioaerosol Detection in the Urban Environment of Dublin City, Ireland, Atmosphere, 16, https://doi.org/10.3390/atmos16030275, 2025.
Gratzl, J., Böhmländer, A., Pätsi, S., Pogner, C.-E., Gorfer, M., Brus, D., Doulgeris, K. M., Wieland, F., Asmi, E., Saarto, A., Möhler, O., Stolzenburg, D., and Grothe, H.: Locally emitted fungal spores serve as high temperature ice nucleating particles in the European sub-Arctic, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-1599, 2025.
Sarangi, B., Baumgardner, D., Bolaños-Rosero, B., and Mayol-Bracero, O. L.: Measurement report: An exploratory study of fluorescence and cloud condensation nuclei activity of urban aerosols in San Juan, Puerto Rico, Atmos. Chem. Phys., 22, 9647–9661, https://doi.org/10.5194/acp-22-9647-2022, 2022.