70 A roadmap to an automated bioaerosol monitoring network in the UK—from old-school to AI

Abstract Bioaerosols, including pollen, fungal spores, bacteria, and viruses, can significantly impact human health, agriculture, and ecosystems. In the UK, hayfever affects 26% of adults and 10% to 15% of children, with fungal allergies estimated at 3% to 6%. These conditions contribute to asthma, lost productivity, and rising healthcare costs, all exacerbated by climate change and extreme weather events. Despite this, UK bioaerosol monitoring remains limited, relying on manual Hirst-type samplers with low temporal resolution and delayed reporting. This reduces the usefulness of data for symptom management and limits integration with weather models that could improve forecasting. The number of active pollen monitoring sites is declining, and there is only one dedicated fungal spore monitoring site. Recent advances in real-time technologies, such as the Swisens Poleno Jupiter, offer a transformative opportunity. These instruments use digital holography, fluorescence spectroscopy, and machine learning to classify airborne particles in real time. While widely adopted across Europe, UK deployment is recent, with only four instruments currently operational. Our initial evaluations reveal that European-trained models perform inconsistently on UK-specific pollen types, highlighting the need for locally generated datasets and a tailored UK classification model. This presentation outlines a roadmap toward a UK-wide automated bioaerosol monitoring network. Key steps include instrument validation, UK-specific model development, strategic site placement, robust data infrastructure, and stakeholder engagement. The vision extends beyond pollen though to include fungal spores, bacteria, and potentially microplastics, many of which fluoresce and are detectable using similar technologies.