Standardisation of bioaerosol monitoring for air quality and climate modelling

Biological aerosols such as pollen, fungal spores, planet debris, bacteria and viruses are found throughout the atmosphere. These bioaerosols effect the environment as they can act as nuclei for cloud condensation or ice formation, and many are also allergenic or pathogenic to humans. Pollen allergy and asthma are among the most common chronic health conditions, affecting 15-40 % of the population of Europe and costing over €50 billion per year in direct and indirect health costs. In recent years, bioaerosol monitoring has been transformed by machine learning (ML), which has allowed monitoring to be automated. However, these new technologies require the development of a robust metrology framework, including training in well-controlled environments using real bioaerosol particles, output standardisation and validated calibration procedures for larger particle sizes.

This project will develop traceable methods for calibrating bioaerosol monitors, including guidelines for end users. Methods to train and validate ML algorithms will be developed to identify airborne pollen and fungal spores in real-time alongside methods to quantify their accuracy and uncertainty. Data output, interfaces and metadata for automatic bioaerosol monitors will be standardised, including guidelines on data storage and handling. A new standard on automatic pollen and fungal spore monitoring within CEN/TC 264/WG 39 will be developed and revisions will be made to existing standards within CEN/TC 264/WG 28.

The project’s work will improve bioaerosol monitoring, helping environmental monitoring and reducing exposure to potentially harmful aerosols.