Accurately quantifying bioaerosol and understanding their impacts is of importance to an increasingly diverse range of research communities as they pose scientific questions relating to their influence on climate via cloud-aerosol interactions; the effects of allergenic species on public health and air quality and how this may be impacted by changes introduced by net zero policy; and the efficacy of early warning capabilities for national security and defense. In addition to their effects on human health and climate, pollen and fungal spores negatively affect agriculture and forestry, contributing to reduced crop yields and forest health. Climate change exacerbates these issues, as rising temperatures and increased CO2 emissions alter plant life cycles and fungal emissions.
Given these increasing concerns, there has been a paradigm shift in bioaerosol monitoring techniques. Traditional manual measurements are being progressively replaced by automated in situ measurements, advanced omics techniques and remote sensing technologies. These advanced approaches do not only provide more accurate information about bioaerosols but also enhance model predictions and forecasts. However, the detection and classification of bioaerosol remains a significant technical challenge, where real-time methods capable of high temporal resolution are often limited by their discriminative capabilities, and offline methods which provide rich taxonomic information suffer from poor time resolution and difficulties in producing atmospheric concentrations.
The aim of this session is to bring together expertise from a wide range of disciplines broadly studying bioaerosols. We welcome presentations covering topics on real-time detection methods and machine learning data processing techniques, validation, laboratory studies, indoor and outdoor ambient observations, the application and development of models, forecasting and nowcasting, exposure assessment and associated health impacts.
Orals: Tue, 5 May, 16:15–18:00 | Room 1.61/62
Bioaerosols interact with society and environment in a multi-faceted way. Information about biological aerosols in the atmosphere is at high demand for medical practitioners and allergy sufferers, climate change researchers, agriculture and forestry industries, air quality forecasters, a variety of information added-value businesses, and many other stakeholders. However, the monitoring practices established over 70 years ago and barely changed since then are country-specific, with varying data availability and usage policy. These roadblocks slow down cross-disciplinary research and development of measures to understand and, upon necessity, control societal and environmental impacts of bioaerosols.
A series of technological breakthroughs during last 10 years introduced a variety of automatic particle counters capable of bioaerosol monitoring in real time. They paved the way to the volunteering consolidation of European aerobiologists to establish the EUMETNET AutoPollen Programme (www.autopollen.net), laid down the foundation for the bioaerosol monitoring infrastructure with the EU Horizon SYLVA project (A SYstem for reaL-time obserVation of Aeroallergens, https://sylva.bioaerosol.eu), initiated developments of European standards and guidelines for the automatic bioaerosol measurements with the EURAMET project BioAirMet, and started the European standardization effort with CEN WG 39.
The new technologies allow to observe bioaerosol concentration in real time, analyze vertical concentration profiles via remote-sensing, perform metagenomic analysis of bioaerosols with the 3rd generation DNA sequencing technique, and combine these observations with atmospheric composition models. Newly established regional networks have been connected to regional atmospheric composition models, which assimilate the real-time regional data to improve the forecasts. It changes the existing paradigm of bioaerosol observations as the new monitoring networks involve large-scale data handling infrastructure, which also includes numerical models as an interface between the different technologies and a bridge to users of information.
The new observations heavily rely on sophisticated technologies, such as high-resolution image analysis, holography, multi-band scatterometry and fluorescence spectrometry, lidar-based remote sensing, and nanotechnology for DNA sequencing. A particle recognition task, the key challenge for the new devices, is solved via machine learning approaches. Technological complexity of the new instruments and large amounts of raw data they produce have been recognized, and a European-scale solution has been proposed by AutoPollen/SYLVA. AutoPollen is being converted into a EUMETNET operational programme with the SYLVA infrastructure as its technological backbone. The programme, with support of Copernicus Atmosphere Monitoring Service (https://atmosphere.copernicus.eu), ACTRIS aerosol monitoring network, and other stakeholders, will become operational from 2027. The central processing system will be hosted by Finnish Meteorological Institute with support of MeteoSwiss, Technical University of Munich, and all SYLVA partners. The pre-operational work of AutoPollen/SYLVA started already in 2025, owing to the efforts of the SYLVA consortium, its sister projects and collaborators. The programme is open for all European (and from outside Europe) groups performing automatic bioaerosol monitoring. AutoPollen offers technological and organizational support, community-developed bioaerosol monitoring solutions, and a motivated team of experts advancing the relevant research and applications.
How to cite: Sofiev, M. and the SYLVA project consortium: Towards operational processing centre of the European AutoPollen network for automatic bioaerosol monitoring, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14687, https://doi.org/10.5194/egusphere-egu26-14687, 2026.
Operational pollen forecast models are potentially powerful tools for patients with allergic rhinitis symptoms caused by airborne pollen. Such a warning system can inform people in a timely manner so preventive measures and adapted medication doses can be taken. In Belgium a birch pollen forecast framework has been established based on the pollen emission and transport model SILAM (System for Integrated modeLling of Atmospheric composition) using a bottom-up approach. This implies, however, that spatially distributed birch pollen emission sources should be assessed before the start of the pollen release season.
We hypothesize that pre-seasonal meteorological-based proxies can be used in combination with the observed Seasonal Pollen Integral (SPIn) for updating the birch pollen emission source map into SILAM prior to the start of the birch pollen season.
Here we analyze the correlations between these pre-seasonal proxies and SPIn observations of birch pollen at the aerobiological surveillance network of Belgium for the period 1987 to 2019. Based on the correlations, temporal scaling factors are derived for updating the main birch pollen emission source map for Belgium (with 2018 as reference year). We evaluate the updated SILAM runs driven by ECMWF ERA5 meteorology by comparing multi-seasonal (2013-2019) modelled levels with daily observed pollen data from the surveillance network.
Preliminary analysis indicates that implementing updated pollen emission source maps in SILAM runs increase the model performance indicator R² (correlation coefficient) by 24% for daily airborne birch pollen levels, and by 90% for the SPIn values at all measurement sites of the network. However, by identifying and adjusting the impact of the weather effect on the observed SPIn values during the pollen season, the correlations with the pre-seasonal meteorological-based proxies as well as the SILAM model performance increase drastically. The R² between modelled and observed SPIn increases from 0.37 without any scaling to 0.71 including scaling and to 0.83 including weather adjusted scaling.
This shows the high potential for improving the modelling and forecasting of the birch pollen levels if pre-seasonal environmental data are included to assess the state of the spatial distributed birch pollen emission sources prior to the start of the pollen release season.
How to cite: Verstraeten, W. W., Bruffaerts, N., Kouznetsov, R., Sofiev, M., and Delcloo, A. W.: Mind the weather signal in the Seasonal birch Pollen Integral, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7886, https://doi.org/10.5194/egusphere-egu26-7886, 2026.
Pollen grains are recognized drivers of respiratory diseases, yet their fragments pose an even greater public health risk. However, the persistence, variability, and sources of these fragments remain largely unknown, hindering effective risk mitigation. Here we integrate real-time bioaerosol observations, DNA sequencing, a new data-driven framework, and atmospheric transport modelling to provide the first evidence of sustained cross-boundary transport of pollen fragments from the Asian continent to Japan. Pollen fragments dominated local exposures, exceeding intact grains by over sixfold, with continental sources contributing more than 30% from February to April and surpassing 70% in February. Such unaccounted-for episodes persisted for months, revealing a hidden health burden that current pollen alert systems fail to capture. This blind spot undermines Japan’s pollen risk mitigation strategies and highlights parallel gaps in international policy frameworks. Ignoring pollen fragments leads to systematic underestimation of health burdens, underscoring the urgent need for next-generation monitoring and coordinated cross-boundary policies to address this overlooked dimension of atmospheric bioaerosols.
How to cite: Zhang, H., Maki, T., Song, C., Crawford, I., Gallagher, M., Laszlo, M., Marczylo, E., Zheng, Z., and Topping, D.: Pollen fragments amplify cross-boundary impacts on air quality, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10690, https://doi.org/10.5194/egusphere-egu26-10690, 2026.
Fungal spores are abundant bioaerosols with major impacts on respiratory health and crop protection, yet routine monitoring remains limited because reference methods are labour-intensive and typically only output results after substantial reporting lag. Met Éireann is establishing Ireland’s first national fungal spore monitoring network using co-located Hirst-type volumetric samplers and Swisens Poleno automatic bioaerosol sensors. This work describes the network design rationale, deployment progress to date, and a roadmap from pilot measurements to operational products.
By May 2026, six Poleno instruments (four Jupiter and two Mars) will be operational across an urban–rural transect in Ireland: Dublin, Cork, and Limerick cities (urban exposure and public-health relevance), Mullingar, Oak Park/Carlow and Claremorris/Mayo (rural, agricultural landscapes). Each Poleno is paired with a co-located Hirst sampler to provide a continuous reference dataset for validation and continuity with established aerobiological records. The same instruments, staff workflows, and training approaches are also used for pollen monitoring, enabling year-round multi-taxa surveillance and shared operational learning.
A core objective is to develop a reproducible training and validation pipeline for fungal spore classification from Poleno holographic imagery (and, for Jupiter, fluorescence-assisted measurements). We present an end-to-end workflow for generating labelled datasets: sourcing priority fungi, harvesting spores, controlled aerosolisation into a laboratory-based Poleno device, curation of particle image libraries, and iterative machine-learning model training before deployment to field units. Initial target taxa are selected to be those most readily identifiable to human analysts, allowing rapid iteration on training protocols before moving to all spore types. Once the workflow is robust, species selection will be expanded using a balanced prioritisation framework that weights both human health relevance and agricultural impact equally.
Preliminary outputs from the first operational year emphasise implementation and comparability. We summarise the siting and maintenance challenges encountered during deployment, including placing instruments in populated areas while avoiding local exhaust influences (e.g., rooftop fume hoods), coastal artefacts affecting Hirst tapes (salt deposition and particle overload during high-wind conditions), and biological interference in manual samplers (insects attracted to the adhesive/tape materials). We also outline harmonised quality assurance steps for co-located datasets, including the role of confidence thresholds, and the handling of non-biological interferents.
We will show first-year case studies for the first trained taxa (e.g., Alternaria), comparing daily Hirst counts with high-resolution Poleno output and describing how we calibrate and align the two methods.
Over the next 2–3 years our objectives are to: (1) build 12–24 month co-located Hirst reference datasets at each station; (2) expand the fungal spore training library to cover the most common and impactful taxa in Ireland; (3) produce annual spore calendars, trends, and meteorological drivers; and (4) eventually deliver near-real-time concentration products suitable for online dissemination.
How to cite: Hourihane Clancy, J. and Markey, E.: Rolling out Ireland’s real-time fungal spore monitoring network: co-located Hirst–Poleno observations, training workflows, and a pathway to operational forecasting, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5688, https://doi.org/10.5194/egusphere-egu26-5688, 2026.
Large aerosol particles within the coarse mode affect the environment, climate, and human health in ways that strongly depend on particle type. Although this size range is dominated by mineral dust and sea spray aerosol (SSA), less abundant biological particles can exert disproportionate effects, such as triggering ice formation at comparatively warm temperatures. Accurate, type-resolved characterization of coarse-mode aerosols is therefore critical for understanding their environmental and climatic roles. Here, we present a new laboratory-based reference dataset for common coarse-mode aerosol sources, including pollen, dust, bacteria, and microplastics, based on laboratory measurements of single-particle ultraviolet light-induced fluorescence (UV-LIF) spectroscopy and particle morphology. Comparison with existing datasets reveals source-specific fluorescence signatures, but also demonstrates substantial overlap between biological and non-biological particles, which can lead to misclassification when fluorescence information is used alone.
Building on this dataset, we introduce a new machine-learning classification framework that combines fluorescence and morphological features. The algorithm is trained using laboratory data and evaluated with field observations from Zeppelin Observatory, Svalbard. To improve discrimination of combustion-related particles and to better separate dust from SSA, we apply domain adaptation using in situ measurements. The updated classifier successfully reproduces the previously reported annual bioaerosol cycle, yields higher bioaerosol concentrations than a fluorescence-only method, and maintains similar correlations with established biological and combustion tracers. Our open-source code enables more robust quantification of bioaerosols across a range of environments, allows reassessment of prior observations, and can be further improved as new particle characterization data become available.
How to cite: Jönsson, A., Fu, J., Pereira Freitas, G., Crawford, I., Dagsson-Waldhauserová, P., Krejci, R., Tobo, Y., Yttri, K. E., and Zieger, P.: Tracing biological, human, and inorganic sources of coarse aerosols via single-particle fluorescence and optical morphology, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6675, https://doi.org/10.5194/egusphere-egu26-6675, 2026.
Bioaerosols are ubiquitous and can affect both air quality and public health. While natural sources are well-studied, anthropogenic sources, particularly emissions from sewer vents (SV) connected to indoor sanitation pipelines, remain insufficiently characterized. Such vents may episodically release fecal-associated microorganisms into ambient air during toilet flushing, yet their emission characteristics and exposure risks are not well quantified. Here we assess SV as a potential urban bioaerosol source and quantify inhalation exposure risks across four representative buildings: university dormitory, nursing home, residential community, and inpatient building. We monitored real-time particle emissions and simultaneously collected culturable bacteria and fungi at each SV and in the corresponding pedestrian zones (PZ) using two Andersen six-stage impactors. Chronic non-carcinogenic inhalation hazard quotients (HQs) were calculated based on estimated exposures. Results showed that culturable bacterial concentrations were higher at SV than PZ (ranging from 1.80 to 9.21 times) except the inpatient building, while fungal concentrations were opposite. Size-resolved measurements indicated that SV bacteria were dominated in particles >2.1 μm, while PZ bacteria had a larger coarse fraction, with 38% at >7 μm. Fungal aerosols at both locations were mainly at 1.1–4.7 μm range. Consistent with these patterns, bacterial HQs were higher at SV (0.15 males; 0.13 females) than at PZ (0.04 for both sexes). Fungal HQs exceeded bacterial HQs at both locations (SV: 0.20 males, 0.18 females; PZ: 0.21 males, 0.18 females), yet all HQs remained below commonly used reference thresholds. Ongoing work will apply high-throughput sequencing and SourceTracker to resolve microbial community composition and apportion SV contributions to PZ bioaerosols, informing targeted mitigation (e.g., filtration and UV sterilization) and supporting integration of sewer infrastructure into urban bioaerosol monitoring frameworks.
Keywords: bioaerosols; sewer vent; particle size distribution; culturable microorganisms; health risk assessment
How to cite: Deng, Y., Liu, J., and Fang, T.: A Potential Bioaerosol Source from Sewer Vent and its Health Risk Assessment, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6911, https://doi.org/10.5194/egusphere-egu26-6911, 2026.
Introduction
Respiratory aerosols are a major vector for the transmission of respiratory diseases such as COVID-19. Phonation and speech are known sources of respirable aerosol in humans. Previous studies have shown that intensified vocal activities can produce aerosol concentrations exceeding those from conversational speech by more than a factor of 10, and those from quiet breathing by up to a factor of 30.1,2 The number and mass concentrations of aerosols emitted during breathing, speaking, and singing, as well as their dependence on vocal loudness, are now relatively well characterised.3,4 However, a clear gap remains in time-resolved and single-particle measurements of respiratory aerosol composition, and in the application of instruments widely used in atmospheric bioaerosol research5,6 to clinical and voice-related settings. Addressing this gap is critical for improving our mechanistic understanding of respiratory aerosol generation and for informing safer clinical practice.
Method
The WIBS-NEO was deployed in a zero-background clinical setting, allowing aerosols to be directly attributed to specific vocalisations. 14 healthy participants performed a range of speech and voice activities, including humming (/m:/), sustained phonation (/a:/), fricatives (/ʒ/ pulses), projection (“Hey!”), and tongue trills, with breathing and speaking as reference measurements. The WIBS-NEO measured aerosol size (optical diameter, µm), shape (asymmetry factor, AF), number concentration (cm⁻³), and fluorescence intensity, while an Aerodynamic Particle Sizer (APS; TSI) was deployed concurrently to validate size distributions and concentrations.
Results
Several key findings emerge from this study. Figure 1 shows box-and-whisker plot of the total particle and fluorescent particle number concentrations measured by the WIBS-NEO across the different activities. Based on the mean values (rather than max/min), aerosol emissions increase in the following order: breathing (~0.1 particles/cm3), speaking, fricatives, projection, phonation, humming, and tongue trills (~0.5 particles/cm3), spanning about five orders of magnitudes across activities. Total particle number concentrations measured by the WIBS-NEO are comparable in magnitude to those obtained using the APS.
Fluorescent particles contribute approximately half of the total particle number concentration for most activities, indicating that 50% of emitted aerosols exhibit detectable fluorescence (60% for fricatives). This suggests that a substantial fraction of respiratory aerosols carry proteinaceous and other fluorescent compounds derived from human respiratory fluid.
Single-particle fluorescence analysis further shows that, among fluorescent particles, type A particles dominate (>90%), followed by type AB particles (~8%). This distribution indicates that respiratory aerosol fluorescence is primarily associated with fluorophores in the tryptophan- and albumin-dominated regions, with additional contributions from flavins (e.g., riboflavin). These findings are consistent with complementary bulk fluorescence spectroscopic measurements of human respiratory fluid samples.
Conclusion
This study demonstrates the suitability of the WIBS-NEO for characterising respiratory aerosols generated during human vocal activities in a clinical environment. Voice-related tasks produce elevated aerosol emissions relative to quiet breathing, with a substantial fraction exhibiting protein-associated fluorescence consistent with respiratory fluid. These fluorescent aerosols may serve as carriers of airborne pathogens and as potential markers for their detection. The WIBS-NEO’s ability to deliver time-resolved, single-particle fluorescence measurements supports its use for identifying higher-risk vocal tasks and informing evidence-based mitigation strategies in clinical practice.
How to cite: Tian, J., Szczepanska, A., Harrison, J., Archer, J., Bzdek, B., Reid, J., Crawford, I., Moss, M., Topping, D., Saccente-Kennedy, B., Epstein, R., Costello, D., Calder, J., and Shah, P.: Characterising respiratory aerosol emissions from speech and therapy activities using Wideband Integrated Bioaerosol Sensor (WIBS-NEO), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18758, https://doi.org/10.5194/egusphere-egu26-18758, 2026.
The transmission of pathogenic bioaerosols poses a substantial risk not only to human health but also to animal welfare and agricultural productivity, where the spread of infections can lead to significant economic and public health system burdens. This underscores the importance of developing reliable aerosol sampling techniques that can capture airborne particles.
Electrostatic precipitation (ESP) is a promising method for aerosol collection1. However, its dependence on corona discharge to charge particles generates ozone byproducts. The presence of ozone can compromise the integrity of bioaerosols2. This is problematic in applications where preserving the viability of the collected bioaerosols is essential, such as those requiring cultivation. Therefore, to address this limitation whilst keeping the advantages of ESP-based techniques, ozone-free (i.e. corona discharge-free) electrostatic actuation was investigated as a potential alternative.
Indium tin oxide (ITO)-coated microscope slides (Diamond Coatings) were electrically connected to four different electrical conditions: negative, positive, grounded, and floating (no connection) in an 8 m3 aerosol test chamber. Voltages between -10kV to +10kV were applied. 1 µm diameter fluorescent polystyrene microspheres (PSL) were used as model aerosolised particles. Four optical particle counters (OPC-N3, Alphasense) were positioned in the vicinity of the slides to continuously monitor aerosol concentration. For each experiment, aerosols were nebulised for 15 minutes, followed by a 10-minute sampling period during which voltages were applied. Afterwards, the chamber was cleaned using an extraction system equipped with HEPA filter, and then the samples were retrieved for imaging using an EVOSM700 fluorescence microscope. Particle counts were obtained using Celeste 6 analysis software and normalised against the chamber concentration. To direct the particle flow towards the slide, aiming to enhance the collection efficiency, a fan-assisted collection device was constructed to direct airflow onto the slide (Fig 1a). Fan speed and spatial placement were varied to optimise collection efficiency.
Ozone-free electrostatic collection of PSL particles was successfully demonstrated, with both positive and negative biases collecting up to 17.0 and 8.5 times more PSL particles than the grounded and floating slides, respectively. A correlation was observed between applied voltage and collection performance, as higher voltages generated stronger electric fields, thereby enhancing the electrostatic force and particle capture. The simple fan-driven collection device achieved an initial collection efficiency of 31.5%. Investigation into fan speed and spatial positioning revealed that lower fan speeds and a closer fan-to-collection-medium distance performed better, with the highest collection efficiency at 59.1% at 10.9 L/min air flow rate (lower speed setting) (Fig 1b).
These findings demonstrate that ozone-free electrostatic collection is an effective alternative approach to the ESP-based method for aerosol collection, with the potential of maintaining bioaerosol viability, which will be tested in the near future to confirm. Overall, the results establish a foundation for advancing electrically actuated aerosol collection devices and highlight promising future applications in public health surveillance, environmental bioaerosol monitoring, and agricultural biosecurity.
This work was supported by Research England-funded Biodetection Technologies Hub and the Engineering and Physical Sciences Research Council [grant number EP/X017591/1].
References: [1] Foat et al. (2016), [2] Ouyang et al. (2023).
How to cite: Chung, E., Heidari-Koochi, M., Weerasiri, L., Johnston, I., Munro, I., and Coudron, L.: Ozone-free electrostatic collection of aerosolised microspheres, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17844, https://doi.org/10.5194/egusphere-egu26-17844, 2026.
Aerosol hygroscopicity play a fundamental role on cloud activation, radiative transfer, and particle–light interactions, yet its impact on fluorescence properties remains poorly understood. During the CleanCloud Helmos OrograPhic site experimeNt (CHOPIN) campaign at Mount Helmos, Greece (38.0°N, 22.2°E; 1700–2314 m a.s.l.), aerosol hygroscopicity and fluorescence were investigated across two periods: autumn (Oct–Nov 2024) and spring (Apr–May 2025). The high altitude and strategic location of the site allow the observation of a wide variety of aerosol types, including Saharan dust, biomass burning smoke, urban pollution, and biogenic particles.
A multi-wavelength elastic-Raman–fluorescence lidar (ATLAS-NEF) operating at 355, 387, 407 and 470 nm, provided vertically resolved aerosol optical properties (extinction, backscatter, lidar ratios) and water vapor mixing ratios, as well as fluorescence backscatter profiles.
Hygroscopic growth factors were derived from Raman-based backscatter following Hänel-type parameterizations, supported by measurements (pressure, temperature, and relative humidity) from radiosondes, a tethered helikite, and Unmanned Aerial Vehicles (UAVs). Fluorescence quenching was quantified as a function of relative humidity and compared to the optical growth exponent γ, while the Wideband Integrated Bioaerosol Sensor (WIBS) and Multiparameter Bioaerosol Sensor (MBS) provided information on bioaerosol concentrations and types.
Aerosol backscatter generally increased with relative humidity, while fluorescence decreased, indicating humidity-dependent quenching. Biogenic particles showed strong fluorescence but limited hygroscopic growth, whereas dust and urban aerosols were moderately hygroscopic with reduced fluorescence. Synergies with MBS and WIBS highlighted temporal variability in bioaerosol concentrations, linking lidar fluorescence changes to particle composition and aging. These results demonstrate that this synergistic approach provides a robust framework to assess humidity-driven changes in optical and microphysical properties, with implications for cloud formation and radiative forcing.
How to cite: Gidarakou, M., Papayannis, A., Foskinis, R., Zografou, O., Schmale, J., Gini, M. I., Zieger, P., Jönsson, A., Papetta, A., Marenco, F., Fetfatzis, P., Granakis, K., Eleftheriadis, K., and Nenes, A.: Coupling aerosol hygroscopicity and fluorescence using lidar and in situ observations during the 2024–2025 CHOPIN campaign, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18730, https://doi.org/10.5194/egusphere-egu26-18730, 2026.
Airborne biological materials (bioaerosols) disperse across ecosystems as they are transported through the atmosphere. This dispersal makes their detailed taxonomical composition characterization essential for understanding their ecological roles and potential impacts on public health. Although metagenomic approaches improved their characterization, complementary tools are needed to better understand their properties. One such tool is flow cytometry (FCM), an established method for analyzing microorganisms, but rarely applied to atmospheric bioaerosol studies (Negron et al., 2020, Liang et al., 2022, Abboud et al., 2026). This study aims to characterize and quantify bioaerosols using FCM to understand population variation at the Helmos Hellenic Atmospheric Aerosol & Climate Change Station (HAC2; Peloponnese, Greece, 2’314m asl, 42°N 05′, 34°E 14′). The sampling area is a typical free-tropospheric background site, with minimal influence from surface-polluted layers. It lies at the intersection of different air masses e.g., continental, Saharan and long-range biomass burning.
Sample collection (n = 55) was performed using a Coriolis µ high-volume wet cyclone over a period of 7 weeks in autumn (6 October to 28 November 2024) as part of the CleanCloud Helmos OrograPhic sIte experimeNt campaign (CHOPIN; http://go.epfl.ch/chopin-campaign). Combining nucleic acids for FCM staining with a self-organising map-based clustering algorithm (FlowSOM, Bioconductor - FlowSOM) after acquisition allowed us to identify populations characterized by low and high nucleic acid content (LNA and HNA, respectively) (Abboud et al., 2026). The analysis included meteorological parameters and atmospheric pollutants, providing a comprehensive overview of these populations. Meanwhile, Oxford Nanopore Technologies (ONT) sequencing was employed to achieve in-depth taxonomic resolution.
The results show that the average number of bioaerosols collected in the planetary boundary layer (PBL, n = 39) was 1.5 ± 3.3 × 10⁵ m⁻³, compared to 8.7 ± 7.9 × 10³ m⁻³ in the free tropospheric layer (FTL, n = 13)., a decrease of two orders of magnitude between the layers. The LNA population dominated the bioaerosol fraction in both layers, accounting for 79% and 85% of the detected bioaerosols in the PBL and FTL, respectively, while intact cells represented 92% and 100%, respectively. In both layers, LNA population was smaller than the HNA, with mean diameters of 2.4 ± 0.9 µm and 4.4 ± 3.4 µm in the PBL, and 2.5 ± 1.3 µm and 4.3 ± 2.6 µm in the FTL, respectively. The different populations were taxonomically identified using ONT sequencing.
This work was supported by the Swiss National Science Foundation project LIPIC-Air (project number 215416) and the CleanCloud project, funded by the European Commission's Horizon Europe call for proposals, "Improved knowledge of cloud-aerosol interactions" (HORIZON-CL5-2023-D1-01-04).
References
Abboud E., Rossi P., Crouzy B., Nenes A.,Violaki K., (2026). Characterization of the Atmospheric Microbiome in a Semi-Rural Area of Central Europe Using Flow Cytometry. Under review in ISME Communication.
Liang L et al. (2022). The characterization and quantification of viable and dead airborne biological particles using flow cytometry and double fluorescent staining. J Aerosol Sci, 165.
Negron, A., Deleon-Rodriguez, N., Waters, S. M., Ziemba, L. D., Anderson, B., Bergin, M., Konstantinidis, K. T., & Nenes, A. (2020) Atmospheric Chemistry and Physics, 20(3), 1817–1838
How to cite: Abboud, E., Molina, C., Gkretsi, S., Rossi, P., Foskinis, R., Fetfatzis, P., Granakis, K., Eleftheriadis, K., Nenes, A., and Violaki, K.: Characterization of the Atmospheric Microbiome at a high-altitude station in the eastern Mediterranean using Flow Cytometry during the fall season, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13320, https://doi.org/10.5194/egusphere-egu26-13320, 2026.
Winter haze across the Indo-Gangetic Plain (IGP) forms a dense, persistent atmospheric layer capable of transporting airborne bacteria over long distances, influencing human health, agricultural productivity, and climate dynamics. Present study investigates transports of bacterial communities through winter haze movement over IGP, analysing 20 airborne samples collected simultaneously in the winter of 2022-2023 from four urban cities along west-to-east traveling path from Delhi (28.49° N, 77.18° E) to Varanasi (25.26° N, 82.99° E) to Muzaffarpur (26.12° N, 85.39° E) and finally reaching to Ranchi (23.41° N, 85.44° E). Highest bacterial loading has been observed in Delhi, where the loading of bacterial ASV and genus reaches 71705 ± 4143 and 590 ± 70, respectively, representing a significantly higher loading (30%) of bacteria compared to the easternmost city of Ranchi. Venn diagram analysis confirmed widespread long-range transport, as demonstrated by a substantial overlap, where 500 bacterial genera were shared among all four geographically distinct sampling locations, accounting for approximately 50% of the total bacterial community that travelled along with winter haze movement. The health implications are underscored by the high prevalence of pathogenic ASVs, predominantly associated with respiratory and skin microbiomes, which ranged from 3,000 to over 5,000 ASVs per sample across the IGP, with Delhi and Muzaffarpur showing the highest concentration. Current result establishes that winter haze acts as an efficient vector for the high-load, long-distance transport of diverse bacterial communities, including potentially harmful human pathogens, across the most densely populated region in India.
How to cite: Pramanick, A., Saikh, S. R., Mushtaque, M. A., and Das, S. K.: Winter-haze mediated dispersal of urban airborne bacteria across the Indo-Gangetic Plain of India, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-514, https://doi.org/10.5194/egusphere-egu26-514, 2026.
Airborne bacteria are a critical yet highly dynamic component of atmospheric ecosystems, shaped by the interplay between local sources and long-range transport. Over a three-year monitoring period in Busan, South Korea, we quantified airborne bacterial populations using quantitative PCR and high-throughput sequencing. Bacterial concentrations fluctuated substantially (2.8–5.8 log10 copy·m-3), with pronounced peaks in spring and minima during summer. These fluctuations mirrored the temporal trends of both local PM10 and desert-derived PM10 transported from arid regions thousands of kilometers away. Time-series analyses further revealed robust, synchronized annual cycles for bacterial abundance, desert PM10, and local PM10 (P<0.05), with parametric modeling capturing a four-week lag between desert dust emissions and subsequent local microbial peaks. Structural equation modeling provided quantitative confirmation that both local generation and regional dispersal significantly influenced airborne bacterial dynamics (P<0.05), with regional dispersal predominating during peak spring dust storm periods. Together, our findings underscore the major role of transcontinental dust transport in shaping atmospheric bacterial communities, often surpassing local contributions.
How to cite: Jeong, S.-Y. and Kim, T. G.: Seasonality of airborne bacterial population in South Korea, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2898, https://doi.org/10.5194/egusphere-egu26-2898, 2026.
Bioaerosols are ubiquitous airborne microorganisms comprised of bacteria, fungi, pollen, virus and their constituents. Fungi have been associated with negative health effects ranging in severity from allergic reactions to asthma and serious infection, where susceptible individuals are at greater risk of life-threatening health outcomes resulting from exposure. While airborne fungi are abundant, they are poorly characterized due to the low temporal resolution of traditional offline sampling methods, limiting our understanding of key emission drivers in critical micro-environments and their impacts on air quality.
There is a critical need to better characterize background fungal aerosol concentrations to build baselines to explore exposure assessment. Here we investigate the utility of emerging real-time detection methods in conjunction with offline sampling during a two-week pilot study to characterize the outdoor concentrations of key aeroallergenic fungi at high time resolution.
A Multiparameter Bioaerosol Spectrometer (MBS) was deployed at UKHSA Chilton alongside a Burkard sampler during summer 2022, capturing the extreme European-wide heatwave which occurred 9-15th of August; The MBS is a biofluorescence spectrometer that classifies and quantifies bioaerosols on a single particle basis via their autofluorescent signatures, allowing for fungal aerosol concentrations to be derived at 5-minute time resolution; Next Generation Sequencing (NGS) was performed on daily integrated Burkard samples to provide broader fungal compositional context. Meteorological data was also recorded.
Clear diurnal behaviour in Cladosporium- and Penicillium-like aerosol was observed with the MBS, with maximums occurring in the late afternoon and early morning respectively. These characteristic diurnal emission features would not be evident from sample integrations typical of offline sampling.
Splitting the MBS real-time data into pre-heatwave and heatwave periods revealed that during heatwave conditions the environment was too hot and dry for the typical day time sporulation and emission of Cladosporium to occur, where the emission was delayed until the early morning when temperatures dropped and subsequently critical humidity levels had recovered; The typical early morning release of Penicillium was largely unaffected by the heatwave, however, daytime concentrations dropped to zero during the hottest and driest periods.
Analysis of the daily NGS data showed that the abundance of key species such as Alternaria and Cladosporium were enhanced during the heatwave, while Aureobasidium and Epicoccum are suppressed by heatwave conditions in our observations.
We demonstrate the utility of a complimentary real-time and offline NGS dual approach to gain deeper insights into fungal spore emissions. This allowed us for the first time to investigate the impacts of heatwave conditions on the emissions of key aeroallergenic species, providing insight into how diurnal emissions may be impacted by a warming climate. We also suggest that this approach shows promise for routine fungi monitoring to assess impacts on public health.
How to cite: Crawford, I., Douglas, P., and Marczylo, E.: Assessing heatwave impacts on fungal spore emissions with real-time detection and next generation sequencing technologies, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9988, https://doi.org/10.5194/egusphere-egu26-9988, 2026.
Atmospheric biological particles, including pollen and other plant-derived materials, constitute a substantial fraction of coarse particulate matter, particularly during flowering seasons. Olive trees represent one of the most widespread crops in southern Europe, and olive oil is a major economic resource for the region. Approximately 95% of global olive cultivation is concentrated in the Mediterranean basin (Sofiev et al., 2017). Pollen production from an area with complete olive coverage can reach up to 10¹⁰ pollen grains m⁻² season⁻¹, with an average grain diameter of 20.1 ± 4.0 μm. Olive pollen is considered among the most allergenic tree pollens in Europe, inducing respiratory symptoms such as rhinitis and asthma in humans (Liccardi et al., 1996), while also acting as a significant atmospheric source of organic matter and nutrients to terrestrial and aquatic ecosystems (Rösel et al., 2012; Violaki et al., 2021).
In this study, a series of chamber experiments was conducted to investigate the response of olive pollen to atmospheric stressors, with a particular focus on NOx pollution. Olive pollen (Olea europaea L.) was collected between 5 and 7 May 2024 from Puglia, southern Italy (https://www.bonapol.com/). Prior to chamber exposure, comprehensive lipidomic, biological, and chemical characterizations were performed, including analyses of metals, major ions, and carbon content.
A robust analytical workflow for pollen lipidomics was developed and applied before and after chamber aging. Using LC-Q-TOF/MS with ESI in both positive and negative ionization modes, approximately 480 lipid species spanning 41 lipid classes were identified. Phosphatidylcholines (PC) were the dominant class (66%), followed by diacylglyceryl carboxyhydroxymethylcholine (DGCC, 19%), and ether monogalactosyldiacylglycerols (MGDG, 8%). A significant decrease in major membrane lipids (PC, PG, SM, DGDG, and MGDG) was observed after aging, indicating lipid degradation processes. In contrast, oxidized lipid species, including oxidized triacylglycerols (OxTG), oxidized phosphatidylcholines (OxPC), and ether-linked lipids, showed a pronounced increase, highlighting oxidative transformations induced by atmospheric aging. Overall, these results highlight the sensitivity of lipids in pollen grains to atmospheric aging and emphasize the importance of considering oxidative processing when assessing the chemical evolution of primary biological aerosol particles.
References
Liccardi et al., Int Arch Allergy Immunol. Nov;111(3):210-7, 1996.
Rösel, et al., Aquatic Sciences, 74, 87–99, 2012.
Sofiev, et al., Atmos. Chem. Phys., 17, 12341–12360, 2017.
Violaki, et al., npj Clim Atmos Sci 4, 63, 2021.
How to cite: Violaki, K., Molina, C., Abboud, E., Kaltsounoudis, C., Panagiotopoulos, C., and Nenes, A.: Impact of Atmospheric Aging on the Lipidomic Profile of Olive Pollen (Olea europaea L.), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10985, https://doi.org/10.5194/egusphere-egu26-10985, 2026.
Biological ice nucleating particles (bio-INPs), as a subset of the broader class of biological aerosol particles, are known to be the most efficient INPs at temperatures above -15°C, and several laboratory studies have identified and characterized specific biological ice nucleators (e.g., Hartmann et al., 2025; Wieland et al., 2025). However, in field studies, a clear correlation or even attribution of INPs to specific biological aerosol particles or bioaerosol in general often remains elusive. While several factors contribute to this, one aspect is the lack of measurement techniques that can comprehensively characterize the bioaerosol. In recent years, significant progress has been made in this regard. By combining laser-induced fluorescence (LIF) techniques (fluorescent aerosol particles have typically been used as a proxy for the bioaerosol) with imaging techniques (e.g. holography), we now have instruments capable of identifying and quantifying, for example, pollen and spores of different taxa in situ and in real time. This opens up new possibilities to study the relationship between bioaerosol and INP in the field.
During the 2024 pollen season, we deployed a SwisensPoleno Jupiter (hereafter Poleno) at the ACTRIS-station Melpitz, a rural background station about 40km northeast of Leipzig (Germany). The Poleno is one of the aforementioned instruments that combines UV-induced fluorescence spectroscopy with digital holography (Sauvageat et al. 2020), allowing not only the measurement of bioaerosol concentrations, but also the identification of various taxa (mainly pollen and fungal spores) through an AI-driven classification algorithm. In parallel, a Hirst-type pollen trap was operated and its samples were evaluated by manual pollen and spore counting. These measurements of the pollen trap samples will be used as a reference for the Poleno measurements, as there are few comparative studies in the literature using this relatively new state-of-the-art instrument. In parallel to these measurements, aerosol particles were collected on polycarbonate filters for subsequent off-line INP analysis using droplet freezing array techniques. The INP samples were also heat-treated to determine the fraction of heat-labile, proteinaceous INPs, which is typically used as a lower limit for the amount of bio-INP in a sample.
First results from the comparison of daily mean Pollen concentrations derived with the Poleno (default classification) and the manually evaluated Hirst trap samples show overall good agreement. However, the level of agreement varies depending on the species.
Preliminary results of the INP analysis show generally high INP concentrations (up to 10-2 #/L at -7.5°C) with indications towards a seasonality, with more ice active samples being more frequent in spring/summer. Correlations of INP concentration (and type) with different bioaerosols (pollen and spores) will be investigated. Additionally, we plan to evaluate the efficacy of short-chained saccharides as an easy-to-measure proxy for pollen concentrations.
Hartmann, S., et al. (2025) Env. Sci. & Tech.
Sauvageat, E., et al. (2020) Atmos. Meas. Tech., 13, 1539–1550
Wieland, F., et al. (2025) Biogeosciences, 22, 103–115
How to cite: Hartmann, M., Bastl, M., Poulain, L., Voigtländer, J., Wex, H., and Hartmann, S.: Co-located real-time bioaerosol monitoring and measurements of Ice Nucleating Particles (INP) at the rural background station Melpitz, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12046, https://doi.org/10.5194/egusphere-egu26-12046, 2026.
Bioaerosols are an important component of atmospheric particulate matter and include a wide range of biological materials such as bacteria, fungal spores, pollen, and biological fragments, originating from sources including vegetation, soil, water surfaces, and human activities. They play a key role in air quality, climate processes, and ecosystem functioning. While bioaerosol sources and properties are expected to differ markedly between polluted urban regions and remote background environments, direct comparative observational evidence remains limited.
In this study, we present a comparative characterization of bioaerosols under contrasting atmospheric conditions in eastern China and the Tibetan Plateau (TP), using real-time measurements from a Wideband Integrated Bioaerosol Sensor (WIBS). Field observations were conducted at an urban site in the Yangtze River Delta (YRD), strongly influenced by anthropogenic emissions, and at a high-altitude background site on the TP, representing a minimally disturbed environment. Particle-resolved fluorescence signals, optical size, and number concentrations were analyzed to examine regional differences in bioaerosol abundance and properties. In addition, unsupervised clustering methods were applied to classify bioaerosol particles based on their optical and fluorescence characteristics.
Clear contrasts in bioaerosol behavior were observed between the two regions. The YRD site exhibited substantially higher bioaerosol concentrations and pronounced diurnal variability, closely associated with pollution periods and urban atmospheric dynamics. In contrast, bioaerosols observed on the TP were characterized by lower concentrations and distinct size distributions, reflecting cleaner background conditions. Clustering results further indicate differences in dominant bioaerosol types: bioaerosols in the YRD were largely associated with anthropogenic-influenced biological particles, whereas the TP showed fluorescence types more closely linked to natural sources such as vegetation and long-range atmospheric transport.
Overall, this study demonstrates how environmental context strongly influences bioaerosol abundance, composition, and temporal behavior. By combining real-time fluorescence measurements with data-driven classification, this work provides a coherent framework for comparing bioaerosols across contrasting atmospheric environments and contributes to a broader understanding of bioaerosol variability within the Earth system.
How to cite: Zhu, B., Zhao, P., Morse, A. P., and Jiajun, X.: Comparative Characterization of Atmospheric Bioaerosols in the Yangtze River Delta and the Tibetan Plateau, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16549, https://doi.org/10.5194/egusphere-egu26-16549, 2026.
Automatic pollen monitoring has become increasingly important for aerobiology, public health, and climate-related
studies. Across Europe, manual Hirst-type traps are progressively complemented or fully replaced by automatic
instruments that acquire particle-resolved measurements and apply machine-learning–based classification instead of
manual light-microscopic identification. This transition enables real-time pollen information but introduces new
challenges related to data quality, model interpretability, and computational efficiency.
SwisensPoleno instruments are airflow cytometers that measure individual airborne particles in-flight. Each particle is
characterized by an array of sensors, including two orthogonal digital holography images, from which morphological
features are derived. Previous modelling approaches for pollen classification have largely relied on deep learning
architectures leveraging the full images. While these methods can achieve high accuracy, they are computationally
expensive to train and evaluate, are prone to overfit for the particular regions where training data was generated and
exhibit a black-box nature that complicates error analysis and systematic performance improvements. Persistent offseason false positives have thus remained difficult to diagnose and mitigate.
Here, we present a fast-feedback classification pipeline that combines manual prefiltering of datasets, automatic
filtering of holography-derived features and a random forest classifier (Figure 1). Prior to model training, datasets are
manually screened and particles are automatically filtered based on deviations from empirically derived feature
distributions. This effectively cleans the training datasets and removes non-representative or artefactual samples. The
resulting training-ready datasets are then used to train random forest models, providing both competitive classification
performance and full interpretability at the feature level.
This novel approach leads to significant performance gains compared to previous methods and successfully addresses
long-standing off-season false-positive issues (Figure 2). Thanks to the reduced specificity when using random forest
based models in comparison to deep-learning based models, the classification performance has proven to be robust
comparing 6 different locations in Southern Europe over multiple years. The proposed methodology offers a transparent,
computationally
How to cite: Schwendimann, A., Koch, K., Zeder, Y., Niederberger, E., and Erb, S.: Interpretable pollen classification using empirical feature filtering and random forest models on holographic airflow cytometry data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-23287, https://doi.org/10.5194/egusphere-egu26-23287, 2026.
The allergenic pollen forecast has become a standard part of the daily air quality production chain of the regional CAMS (Copernicus Atmosphere Monitoring Service) models. The first operational European pollen forecasts started in 2013 based on the developments within MACC (Monitoring Atmospheric Composition and Climate, the predecessor of CAMS) and were released during its Interim Implementation phase (MACC-II). The four-day birch predictions were computed by seven regional models (CHIMERE, EMEP, EURAD-IM, LOTOS-EUROS, MATCH, MOCAGE, SILAM) and aggregated into a multi-model ENSEMBLE. The establishment of European pollen forecasts and their evaluation were supported by cooperation with the European Aeroallergen Network (EAN), which serves as the main provider of pollen observations in Europe. Over the years, the CAMS model cluster was expanded with four new independent models DEHM, GEMAQ, MINNI, MONARCH and the list of pollen forecasts was gradually extended with olive, alder, grass, ragweed, and mugwort species. Currently, the CAMS European pollen forecast is delivered by eleven state-of-the-art chemical transport models and their ENSEMBLE for six pollen species. Only recently has the systematic evaluation of CAMS pollen predictions developed into regular reports published at the end of the season.
Present work will demonstrate the progress in the model’s performance across 11 CAMS regional models and their ENSEMBLE, based on the evaluation of daily timeseries from first-day hourly model forecasts. The forecast accuracy will be assessed in terms of the model mean bias, temporal correlation coefficient, root mean square error, and shifts in the pollen season start and end of the aerobiological season.
The analysis shows that there is no ultimate ”best” model. Depending on the type of pollen and the evaluation score, the different models appear to be good. In 2024 the ENSEMBLE scores were among the best, sometimes outperforming all individual models. The median ENSEMBLE was, in most cases, capable of disregarding the outliers, still providing good forecasts. Exception was the alder forecast, where the majority of models were very low, and the resulting underestimation penetrated through the median, leading to a strongly low-biased ENSEMBLE. Practically all models showed some deviations from the main ENSEMBLE for individual pollen species.
How to cite: Palamarchuk, Y., Sofiev, M., Kouznetsov, R., and Gauss, M.: Advances in pollen forecast quality across CAMS regional models, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19276, https://doi.org/10.5194/egusphere-egu26-19276, 2026.
We present concurrent measurements of atmospheric bioaerosols at the Sonnblick Observatory obtained with a SwisensPoleno Jupiter and a WIBS-5 from DROPLET ENVEA Group between August and November 2024. The observatory is located directly at the top of Mount “Hoher Sonnblick” (3106 m a.s.l.) and serves as an ACTRIS national facility for in-situ aerosol observations and as European Center for Cloud ambient INTercomparison (ECCINT). Because of its high altitude, the station is often immersed in clouds, making it suitable for studying aerosol–cloud interactions. Bioaerosols are known to act as ice-nucleating particles at relatively high temperatures, but their occurrence in the atmosphere is still poorly understood. Therefore, assessing the presence of bioaerosols at this high alpine site is of particular interest.
During the late summer 2024 ECCINT intercomparison campaign, the WIBS-5 was operated alongside the permanently installed SwisensPoleno Jupiter. Both instruments detect fluorescence signals of single particles, but exhibit differences in excitation sources and detection wavebands. Also, the SwisensPoleno Jupiter uses a particle concentrator to enhance the sampling of larger particles (≥10 µm) and additionally provides holographic images. In contrast, without a concentrator, the WIBS-5 primarily samples smaller particles down to 500 nm.
In this presentation, we first present data from both instruments independently and examine observed bioaerosol patterns in relation to other aerosol properties and meteorological conditions. For the WIBS-5, we apply the common classification scheme dividing particles into A, B, C classes and their combinations, while for the SwisensPoleno Jupiter we use a deterministic classification roughly separating particles into pollen-, spore-, plant-debris-, dust-like, and other fluorescent types.
In the second step, we compare data from the two instruments to illustrate how differences in size sensitivity and detection approach relate to observed bioaerosol patterns. We also discuss how the instruments can be used complementarily to provide a broader view of bioaerosol presence in the atmosphere.
How to cite: Burkart, J., Könemann, T., Danner, A., Schauer, G., Maier, C., Bachleitner, T., Baumgardner, D., D. Hughes, D., and Ludewig, E.: Concurrent SwisensPoleno Jupiter and WIBS-5 Measurements of Atmospheric Bioaerosols at the Sonnblick Observatory, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19329, https://doi.org/10.5194/egusphere-egu26-19329, 2026.
Real-time air-flow cytometry has been rapidly expanding as a method for monitoring airborne biological particles, providing continuous measurements with high temporal resolution. This is particularly relevant for pollen monitoring, where accurate and timely information is needed for health-related applications. In this study, we present results from measurements performed with the Swisens Poleno air-flow cytometer, an automated instrument combining light-scattering, holographic imagery, fluorescence excitation, and polarization measurements to detect and classify airborne bioaerosols.
For data analysis, a deep-learning pollen-recognition classifier was used to target the most common pollen taxa in Europe. The classifier was trained on pollen samples provided to the device under laboratory conditions and achieved an average classification accuracy above 90%, with most errors occurring between morphologically similar taxa. Performance in real atmospheric measurements was expectedly lower. To evaluate and correct this, classifier-processed Poleno measurements were compared with co-located measurements from manual Hirst-type traps across Europe. A transposed confusion-matrix correction was applied to account for systematic misclassifications, improving agreement with reference data. The resulting performance was further evaluated for Poleno measurements available through the EU Horizon SYLVA project.
These results demonstrate that combining real-time cytometry with machine-learning and correction techniques provides a reliable and effective approach for automated pollen monitoring, supporting the broader advancement of bioaerosol observation and health-related applications.
How to cite: Kadantsev, E., Kouznetsov, R., and Sofiev, M.: Real-time pollen monitoring across Europe with the Swisens Poleno by a deep-learning classifier: laboratory and field validation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19423, https://doi.org/10.5194/egusphere-egu26-19423, 2026.
Atmospheric pollen concentrations exhibit strong temporal variability driven by plant
phenology and affected by meteorological conditions, yet the strength and consistency of
pollen-meteorology relations depend on region and pollen taxon. In this study, we examine
the relationships between daily airborne pollen concentrations and meteorological
parameters across three regions in Greece, i.e. Athens, Thessaloniki and Finokalia (Crete)
using multiple meteorological datasets and correlation metrics. Pollen observations were
obtained from aerobiological monitoring stations, while meteorological information was
derived from ERA5 reanalysis and nearby meteorological stations. Additionally, for Athens
and Thessaloniki, the Climpact dataset with meteorological parameters was used.
Correlation analyses were performed for selected pollen taxa, grouped pollen categories and
total pollen concentrations using Pearson, Spearman, and Kendall correlation coefficients.
Lagged correlations were also examined for delayed influences on pollen variability, and
analyses were conducted with both including and excluding zero-pollen days.
The results indicate marked regional and taxon-specific variability in pollen–meteorology
relationships. Temperature and relative humidity exhibit the strongest associations with
pollen concentrations, with correlation values ρ reaching -0,75 and 0,57 respectively. Non-
parametric Spearman correlation coefficient provides more stable relationships compared to
Pearson correlation, particularly for taxa with highly skewed distributions. Across data
sources (ERA5, station observations, and climpact datasets), correlation estimates are
generally comparable, suggesting that the pollen–meteorology relationships are robust to
the choice of meteorological dataset.
Overall, the results demonstrate that airborne pollen concentrations are systematically
related to meteorological conditions, with the strength and structure of correlations
depending primarily on region, pollen taxon, and the statistical approach applied.
How to cite: Roditis, G., Giannakaki, E., Pyrri, I., and Koutsoupi, I.: Linking airborne pollen concentrations and meteorological conditions in Greece, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21646, https://doi.org/10.5194/egusphere-egu26-21646, 2026.
The Amaranthaceae family comprises approximately 173 genera and more than 2100 species, many of which are important from an ornamental, agronomic and clinical point of view due to the high prevalence of allergic sensitisation associated with their pollen. It has been suggested that species in this family could maintain or even increase their presence under changing climate scenarios, given their high tolerance to poor soils and prolonged arid conditions.
This study analyses aerobiological and phenological variables of Amaranthaceae pollen in three cities in south-eastern Spain (Cartagena, Murcia and Lorca; Region of Murcia) during the period 2010–2021. Data from the Aerobiological Network of the Region of Murcia (REAREMUR) were used, obtained using Hirst-type volumetric traps (VPPS 2000) and analysed following standardised methodologies (EN 16868:2019).
The results show two main pollen release seasons (MPS 1 and MPS 2), defined using the Nilsson and Persson (1981) method: a first peak in spring (April-June) and a second peak in summer (July-September). During MPS 1, the highest concentrations were recorded in Lorca, followed by Murcia and Cartagena, while in MPS 2 this pattern was reversed, with peaks in Cartagena. However, since 2017, a pronounced and sustained decline in concentrations during MPS 2 has been observed in Cartagena, a behaviour also described in other coastal cities in south-eastern Spain, such as Alicante and Almería.
Trend analysis using linear regression showed a significant increase in Seasonal Pollen Integral (SPIn) in Cartagena during MPS 1. In MPS 2, a significant advance in the start of the season, a delay in the end, and an increase in its duration were detected, along with a significant decrease in both the peak day concentration and the SPIn. In Lorca, MPS 1 showed an earlier start and longer duration, while in MPS 2, a prolongation of the period was also observed, associated with a delay in the end date. No statistically significant trends were identified in Murcia. These trends were re-evaluated using the non-parametric Mann-Kendall test and the Theil-Sen slope estimate, which confirmed these results, except in the case of the increase in SPIn in MPS 1 in Cartagena, which did not reach statistical significance. During MPS 1 in Lorca, no significant trends were found with this test either, although the results were replicated in MPS 2.
Overall, the results point to a phenological change in Amaranthaceae pollen in south-eastern Spain, with a significant decrease in the amount of pollen in the bioaerosol in MPS 2, raising concerns about a possible impact on plant biodiversity that should be addressed.
The result of this work is part of grant PID2024-157581OB-I00, funded by MICIU/AEI/10.13039/501100011033 and by the FSE+.
How to cite: Moreno, J. M., Aznar Martínez, F., Negral Alvarez, L., and Moreno Grau, S.: Phenological changes in Amaranthaceae pollen in south-eastern Spain (Mediterranean region), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19416, https://doi.org/10.5194/egusphere-egu26-19416, 2026.
Primary biological aerosols such as pollen, fungal spores, bacteria and plants debris have traditionally been associated with the coarse particle mode. In contrast, small organic particles in the submicron range have largely been attributed to secondary formation processes, as few primary biogenic sources were known [1-3]. Due to their hygroscopic properties, bioaerosols may act as cloud condensation nuclei (CCN) and ice nuclei (IN), potentially influencing cloud formation and precipitation [4]. In the Amazon rainforest, coarse particles are typically present at lower number concentrations, whereas fine organic particles are more abundant and thus are known to contribute significantly to cloud microphysics under certain conditions [1,5].
In this study, we investigate a previously overlooked primary biogenic source of organic aerosol droplets linked to spore release by many fungi and lichens, with measurements conducted at the Amazon Tall Tower Observatory (ATTO) site in Brazil [6]. Many lichenized and non-lichenized Ascomycota release spores actively, building pressure in their reproductive cells through osmolyte-driven water influx until the spores are suddenly expelled.
We combined controlled laboratory experiments with ambient field measurements to characterize particles emitted during this process. Particle size distributions were measured in isolated chamber experiments using two complementary particle sizers covering a broad size range, providing information on both particle size and emission strength. Field experiments gave insights into emission patterns and triggers under natural tropical forest conditions. Droplets were additionally collected by impaction for further microscopic and chemical analyses. The chemical composition was determined using scanning transmission X-ray microscopy with near-edge X-ray absorption and fine structure (STXM-NEXAFS) spectroscopy, as well as high performance liquid chromatography (HPLC) with electrospray ionisation ultra-high resolution orbitrap mass spectrometry (ESI-UHR-Orbitrap-MS).
This integrated approach allows us to assess the size, chemical composition, and emission strength of fungal aerosol emissions. The findings provide new insights into the contribution of sub- and supermicron fungal emissions to organic aerosol populations and their potential implications for atmospheric processes.
[1] Pöschl, U., et al. (2010). Rainforest aerosols as biogenic nuclei of clouds and precipitation in the Amazon. Science, 329, 1513–1516. https://doi.org/10.1126/science.1191056
[2] Barbosa, C. G. G., et al. (2022). Amazon rainforest aerosols: Characterization and implications for climate. npj Climate and Atmospheric Science, 5, 73. https://doi.org/10.1038/s41612-022-00294-y
[3] Graham, B., et al. (2003). Source attribution and seasonality of Amazon aerosol: Implications for cloud formation. Journal of Geophysical Research: Atmospheres, 108. https://doi.org/10.1029/2003JD004049
[4] Pöhlker, M. L., et al. (2023). Global organic and inorganic aerosol hygroscopicity and its effect on radiative forcing. Nature Communications, 14(1), 6139. https://doi.org/10.1038/s41467-023-41695-8
[5] Moran-Zuloaga, D., et al. (2018). Long-term study on coarse mode aerosols in the Amazon rainforest with frequent intrusion of Saharan dust plumes. Atmospheric Chemistry and Physics, 18(13), 10055–10088. https://doi.org/10.5194/acp-18-10055-2018
[6] Andreae, M. O., et al. (2015). The Amazon Tall Tower Observatory (ATTO): Overview of pilot measurements on ecosystem ecology, meteorology, trace gases, and aerosols. Atmospheric Chemistry and Physics, 15(18), 10723–10776. https://doi.org/10.5194/acp-15-10723-2015
How to cite: Geis, D., Brill, S., Hildmann, S., Artaxo, P., Chilinski, M., Elbert, W., Englert, J., Godoi, R., Hoffmann, T., Leitner, J., Rauch, T., Sebben, B., Thines, E., Weber, B., Weber, J., Weigand, M., Meller, B. B., Pöschl, U., and Pöhlker, C.: Fungal liquid jets as a source of sub- and supermicron particles, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19530, https://doi.org/10.5194/egusphere-egu26-19530, 2026.
Organic and biological aerosols represent an important fraction of atmospheric particles, with identified impacts on atmopsheric physics and cloud processes (e.g., ice nucleation, chemical reactivity) and air quality. The RACLET measurement campaign (Reactive gases, Aerosols and CLouds, Exploring organic matter Transformations) was led in April 2024 at Puy de Dôme Mountain’s observatory (1465 m asl, central France), in the frame of the European research network ACTRIS (Aerosols, Clouds and Trace Gases Research Infrastructure), and supported by the ATMO-ACCESS program. Thanks to its altitude above the surrounding landscape and its geographical localization, this observation site offers unique possibilities of observing a range of atmospheric conditions (free troposphere, boundary layer, clouds) and air masses of different origins and composition (continental, marine, anthropogenic and saharan).
A range of real-time instruments were combined for several weeks in order to characterize aerosols at high temporal resolution through their morphological, optical, chemical and physical properties (SMPS, ACSM, OPC…), including the specific monitoring of bioaerosol particles using fluorescence-based intruments (DMT WIBS neo, Swisens Poleno Jupiter). The data were associated with meteorological variables, remote sensing measurements (LIDAR) and backward air mass trajectory analyses (CAT ECMWF ERA5). The main goal was to evaluate the benefits of combining multiple measurements techniques in the characterization of ambient organic aerosols, their interactions with reactive gases and cloud processes, and in the study of the transport and transformations processes of aerosols in dry or wet conditions. During the timeframe of the campaign, several consecutive periods with distinct patterns of aerosol properties could be identified, including distant desert dust intrusions from the Sahara region, elevated concentrations of coarse biological material, and plumes of anthropogenic influence. Detailed description of the different situations will be presented, and the benefits and limits of such multi-instrumented approach in the characterization of aerosols will be discussed. Particular attention has also been paid to the behaviour of fluorescence measurements throughout these events, and on their potential ability to discriminate between biological and non-biological particles.
How to cite: Larouère, M., Amato, P., Baray, J.-L., Dupuy, R., Canzi, A., Deguillaume, L., Borbon, A., Pichon, J.-M., Ribeiro, M., and Freney, E.: Multi-instrument characterization of distinct sequential aerosol patterns at Puy de Dôme Mountain observatory, France: outcomes from the RACLET field campaign, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12331, https://doi.org/10.5194/egusphere-egu26-12331, 2026.
