Pollen and fungal spores are important for human health in both outdoor and indoor environments. They are linked to several respiratory illnesses which range in severity from minor to deadly. Better detection and forecasting of pollen and fungal spores would allow for interventions to be developed that would reduce their risk to human health. 

The current methodologies available for the detection of pollen and fungal spores are either expensive or time consuming, and often both. This hugely limits their use. For example, the UK Met Office currently only has available 11 regulatory grade sites for pollen monitoring from which their pollen forecast is based upon. This equates to about one regulatory pollen monitoring station per 11 million people in the UK. Similarly, regulatory agencies lack cheap methodologies to detect fungal spores in both outdoor and indoor locations. A cheaper, more agile detection method would much increase the UK's capacity for the detection and forecasting of pollen and fungal spores. 

The AIPS project has combine several rapidly developing technologies. It brings together a distributed internet-of-things (IoT) sensor arrays in combination with regulatory grade equipment and artificial intelligence (AI) techniques. The IoT sensors measure the size distribution of the small particles that are present within the air. The sources and compositions of these particles are many and varied. Atmospheric particles include bioaerosols that are composed of fragments from the biosphere, including pollen and fundal spores. Finding these bioaerosols within the much larger populations of other atmospheric aerosols, is like finding a needle in a haystack. Fortunately for this project, pollen and fungal spores have well defined sizes that are distinct to the background aerosol which makes detection possible. AI approaches will use machine learning algorithms to classify the pollen and fungal spore species of interest and generate approaches to detect them in real time. The results are then compared to regulatory grade equipment to assess the skill of the low-cost approach.  This real time detection will allow for data-driven real-time forecasts of the pollen and spore species of interest.

The presentation will provide an overview of the AIPS project, and discuss the efficacy and applicability of the new AI and IoT tools with respect to bioaerosol detection and forecasting needs.

How to cite: Pope, F., Allison, G., Brown, K., Buckley, A., Crawford, I., Douglass, P., Hansell, A., MacKenzie, R., Marczylo, E., Mills, S., Neil, L., Satchwell, J., Symon, F., Topping, D., and Zhang, H.: Artificial Intelligence for Pollen and Spore Detection, Forecasting and Human Health (AIPS), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7168, https://doi.org/10.5194/egusphere-egu25-7168, 2025.

Biogenic aerosols play a key role in various infectious diseases, like COVID-19 (virus) and Tuberculosis (bacteria). This fact makes detecting and characterizing bioaerosol, especially the pathogenic kind, crucial for human health. Traditional surveillance (via agar plates or PCR) of pathogenic bioaerosol is time and/or labor intensive. As staff in health-related sectors like hospitals is already limited, rapid and automated pathogenic bioaerosol monitoring is of dire need.

In this proof of concept study, we build and test a continuous pathogenic bioaerosol sampler and detector. The set-up consists of three main parts. In a first step (Collection phase), the bioaerosol is sampled via a particle into liquid sampler. This bioaerosol liquid flow is mixed continuously with antibodies for the relevant pathogen species, which are conjugated to magnetic nanobeads. From here the bioaerosol-antibody-bead flow is transported into a column, containing magnetic spheres. There the bioaerosol of interest is captured (Selection phase), stained and then released separately to be analyzed in a flow cytometer (Detection phase).

We are currently working to connect all three successfully tested phases into one continuous, automated, and autonomous instrument for pathogenic bioaerosol monitoring.

How to cite: Karbiener, P., Utinger, B., and Kalberer, M.: Continuous Detection of Pathogenic Bioaerosol Using Antibody Labelled Magnetic Beads and Flow Cytometry, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-372, https://doi.org/10.5194/egusphere-egu25-372, 2025.

Airborne bacteria have a significant role in structural variation of atmospheric microorganisms with limited knowledge about their composition and geographical distribution, which demands high attention to understand their effect on human health and climate change, as their substantial temporal variation depends on local meteorological conditions. Current study presents composition, diversity, and variability of airborne bacterial loading over the Eastern Himalayas in India. A long-term airborne bacterial sampling is carried out within Bose Institute campus, situated at Darjeeling (27.03°N, 88.26°E, 2200m amsl) from January 2022 to September 2023. Samples are collected for eight hours duration, three times a day at 15m above the ground over sampling site. Illumina NextSeq platform is used to analyze V3-V4 regions of 16S rRNA gene in airborne bacterial samples using bacterium-specific primers. Total 88 samples are being investigated and categorized into four groups according to seasons: winter (temperature = 7±3ºC, relative humidity (RH) = 88±7%), pre-monsoon (15±2ºC, 87±10%), monsoon (17±1ºC, 97±3%), and post-monsoon (13±4ºC, 91±8%). About one-fourth (349 bacterial genera) population of airborne bacterial genera are present throughout the year, implying as background of Eastern Himalayan atmosphere. Human pathogens like Aeromonas, hydrophila, Acinetobacter lwoffii, Staphylococcus aureus, and Staphylococcus epidermis, responsible for gastroenteritis, endocarditis, respiratory, skin, and urinary tract infections are dominating in the atmosphere over Eastern Himalayas. Airborne bacterial loading varies significantly during different seasons with maximum concentration during pre-monsoon (Total cell count = 4.6±2.1 cells.m^-3, OTUs = 597±343, Genera = 189±76, Shannon diversity index = 4.1±1.0), followed by post-monsoon (4.2±1.6 cells.m^-3, 492±299, 171±65, 4.1±0.5), monsoon (3.8±1.3 cells.m^-3, 332±171, 122±58, 3.4±1.0), and winter (3.6±1.7 cells.m^-3, 239±87, 105±37, 3.4±0.8). Two distinct groups of beta diversities have been noticed over Eastern Himalayas during pre-monsoon & monsoon and post-monsoon & winter seasons, indicating similar bacterial populations. Eastern Himalayan airborne bacteria exhibit a strong dependency on temperature (r= -0.90, p<0.001) during seasonal changes from winter to pre-monsoon and post-monsoon to winter. Wind (r= 0.80, p<0.01) plays a significant role in the diversity of pre-monsoon season by transporting desert dust from western India, having highly diverse bacteria, and introducing unique pathogenic bacteria responsible for respiratory and skin infections over Eastern Himalayas.

How to cite: Saikh, S. R., Pramanick, A., Mushtaque, M. A., and Das, S. K.: Investigation on meteorological dependency of airborne bacterial communities enriched with pathogens over Eastern Himalayas, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-986, https://doi.org/10.5194/egusphere-egu25-986, 2025.

The chemistry and atmospheric fate of biological aerosols (bioaerosols) have been largely unexplored, despite their significant contribution to atmospheric particulate matter and organic carbon. Although bioaerosols are typically larger than anthropogenic aerosols, up to 100 µm, they can be transported over long distances and thus affect cloud physics (CCN, IN) and play a role in atmospheric chemical reactions. Studies have found that bioaerosols are expected to increase in concentration due to rapid climate change. For example, pollen concentrations are anticipated to increase by 21% and the pollen season length to increase by 21 days. Further, increases in instances and intensities of harmful algal blooms are already being observed. Due to the growing importance of bioaerosols in the atmosphere and climate, the goal of this study was to determine the effects of simulated atmospheric aging on bioaerosol functional groups and polarity. Water extracts of bioaerosols, lodgepole pine pollen and spirulina algae, were aged in a Suntest CPS solar simulator for 24 hours, under simulated solar radiation and in the presence of  H₂O₂ to promote oxidation with OH radicals. Proton Nuclear Magnetic Resonance Spectroscopy(¹H-NMR) and Fourier-Transform Infrared Spectroscopy (FTIR) analyses were performed for fresh and aged bioaerosol extracts. FTIR results show an increase in polarity of both bioaerosols after aging with simulated solar radiation, up to 30.9% in pollen and 27.5% in algae, whereas ¹H-NMR results are more complex, and a clear polarity increase was not observed. To our knowledge, this is the first study to analyze the effects of atmospheric aging on the chemistry of bioaerosols.

How to cite: Bahdanovich, P., Axelrod, K., Khlystov, A., and Samburova, V.: Photochemistry of Atmospheric Bioaerosols, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2600, https://doi.org/10.5194/egusphere-egu25-2600, 2025.

How to cite: Crawford, I., Zhang, H., Topping, D., Bintinazarudin, N., and Gallagher, M.: Assessing indoor fungal spore health impacts with real-time detection technologies, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4339, https://doi.org/10.5194/egusphere-egu25-4339, 2025.

Bioaerosols encompass a diverse range of airborne particles such as viruses, bacteria, fungal spores, pollen, and various fragments related to plants and animals. Bioaerosols through their extensive involvement in surface-atmosphere physic-chemical reactions affect the stability of the biosphere, climate change, and human health. To accurately measure bioaerosols and provide early warning of exposure, a range of real-time bioaerosol detection instruments have been developed that can rapidly identify bioaerosol species through techniques such as fluorescence spectroscopy, holography and light scattering. In this work we deployed a Multiparameter Bioaerosol Spectrometer (MBS), a UVLIF and morphological single particle spectrometer,  as part of a pilot experiment at the Rothamsted North Wyke Farm Platform (NWFP). Analysis of the MBS measurements was used to assess the contributions of biofluorescent aerosol emitted from local farmyards and animal housing compared with the surrounding environment. Preliminary analysis of the data shows that the expected distinct bioaerosol diurnal concentration pattern experienced significant perturbations induced by the nearby animal house emissions. Concentrations in general were higher during morning and nighttime periods and displayed more stable patterns in the afternoon indicative of activities. Bioaerosol sizes ranged from D_p = 0.5 to 5 µm and were dominated by specific fluorescent clusters clearly dependent on the emission source. These data will be examined in more detail using laboratory training data sets to inform AI algorithms to further discriminate bioaerosol classes.

How to cite: Chen, Z., Matthews, E., Crawford, I., West, J., Flynn, M., Topping, D., Gallagher, M., and Coe, H.: A case study based on bioaerosol emissions from farmland and animal houses, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10456, https://doi.org/10.5194/egusphere-egu25-10456, 2025.

Primary biological aerosol particles (PBAPs) significantly affect human health and aerosol-cloud-climate interactions. Fluorescent aerosol particles (FAPs), detected using light/laser-induced fluorescence (LIF) instruments, serve as a crucial proxy for understanding the concentration and size distribution of PBAPs and the factors that influence their variability in the atmosphere. This study systematically evaluates FAPs collected from field measurements worldwide and simulates their concentrations on a global scale using machine learning algorithms, incorporating comprehensive global weather, climate and emissions data. The simulated global concentration reveals spatial variations in size and concentration, with heightened annual mean concentration predominantly observed in the tropics and the Asia region. The post-hoc Shapley Additive Explanation (SHAP) method indicates that the spatio-temporal patterns of FAPs concentrations and size distributions are primarily driven by anthropogenic emissions in urban regions, while weather factors are more closely linked to variations in oceanic and rural areas. Notably, certain non-biological emissions (e.g., dust and black carbon) exhibit strong correlations with FAPs, particularly in densely populated areas and the Arctic region. Overall, this study underscores the significant role of anthropogenic emissions in shaping simulated FAP concentrations on a global scale and provides guidance for future investigations into FAP concentrations in unexplored regions.

How to cite: Miao, Y. and Lee, P. K. H.: Global Modeling of Fluorescent Aerosol Particles with Machine Learning Reveals Potential Regional Anthropogenic Impacts, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16487, https://doi.org/10.5194/egusphere-egu25-16487, 2025.

To study bioaerosols under controlled conditions, aerosol chambers equipped with aerosol generators have been used for a long time. However, the method used for generation can change the constitution and properties of the bioaerosol produced, including the biological integrity of fungal spores, bacteria or airborne viruses. The properties of a bioaerosol in turn influence the results of detection, enumeration and identification methods downstream (Pogner et al., 2024). Recent developments of automatic bioaerosol monitors equipped with AI-based identification algorithms require simple and reliable generation of bioaerosols in the laboratory to collect  data for the machine learning trainings.

Figure 1 View into the SAG chamber through the window at the front, containing a petri dish with a fungal colony.

The Swisens Aerosol Generator (SAG) is an atomizer for efficient and gentle aerosolization of fungal spores, as well as other dry biological materials, for measurement with the SwisensPoleno and other instruments. The SAG principle is based on the design described by Lee et al. (2010), with improvements for better controllability and a higher yield. It consists of a chamber, shown in Figure 2, in which the petri dishes and other materials are placed. Pressured air, generated by a separate air supply unit, is led to a nozzle inside the chamber and directed over the biological materials. The horizontal air stream detaches the fungal spores into the air of the chamber, which can then be taken in by the instrument to measure the content.

Figure 2 Left: Aerosol chamber with HEPA filter at the top for clean air supply. Right: Air supply unit with digital flow meter, flow controls and air filter.

The structure and quantity of aerosolized particles is highly dependent on the fungi species, its growth stage and success, as well as the airflow onto the petri dish. Measurements with Cladosporium cladosporioides (Tested by Pogner et al. (2024) with SAG prototype) created, for example, numerous data of agglomerated spores and mycelium parts besides single spores, whereas Alternaria alternata constantly generated single spores in high numbers. With the SAG the process and the efficiency of fungal spores aerosolization can be improved, making it a new tool besides other fungal spore aerosols generation methods. This opens more opportunities to choose the best means of aerosolization depending on the fungal species and required particles.

References:

Lee, Jun Hyun, Gi Byung Hwang, Jae Hee Jung, Dae Hee Lee, und Byung Uk Lee. 2010. «Generation characteristics of fungal spore and fragment bioaerosols by airflow control over fungal cultures». Journal of Aerosol Science 41 (3): 319–25. https://doi.org/10.1016/j.jaerosci.2009.11.002.

Pogner, Clara-E, Elias Graf, Erny Niederberger, und Markus Gorfer. 2024. «What do spore particles look like - use of real-time measurements and holography imaging to view spore particles from four bioaerosol generators». Aerosol Science and Technology 58 (7): 1–17. https://doi.org/10.1080/02786826.2024.2338544.

How to cite: Graf, E., Gütlin, H., Niederberger, E., Burch, P., and Musa, T.: Testing the generation of fungal spore aerosols with a new atomization setup, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17236, https://doi.org/10.5194/egusphere-egu25-17236, 2025.