Biological particles significantly impact various aspects of life, including health, the economy, and the environment. Currently, up to 30% of Europe’s population suffers from pollen allergies and asthma, with the number of allergy sufferers steadily increasing over the past few decades. This growing prevalence poses a substantial burden on public health systems and economies, with the annual costs related to allergies in Europe estimated to range between €50 and €150 billion.

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.