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23NRM03 BioAirMet

Biological aerosols (mainly pollen and fungal spores, but also bacteria, viruses and plant debris) are ubiquitous in the atmosphere. They influence the hydrological cycle and climate, and some of them are known human and plant pathogens and/or allergens. Newly developed systems to monitor airborne biological particles, based on automatic bioaerosol monitors and machine learning, have revolutionised the field by providing real-time information on particle number concentration and taxa/species. However, traceability is incomplete and measurement uncertainties are poorly understood. This project will provide input to a new documentary standard on automatic pollen and fungal spore monitoring within the CEN/TC 264/WG 39 and will develop quality assurance procedures for this new class of bioaerosol monitors.

Objectives

The overall objective of this project is to provide input to a new documentary standard on automatic pollen and fungal spore monitoring within the CEN/TC 264/WG 39 and to develop quality assurance procedures for state‑of-the-art bioaerosol monitors. The specific objectives of the project are:

  1. To further develop two traceable methods (light scattering and particle flow visualisation) for the calibration of automatic bioaerosol monitors with respect to particle size and number concentration (target expanded uncertainty ≤15 %). To provide clear guidelines to end users about the specifications, limitations and application range of each primary method.

  2. To develop methods for training and validating machine learning (ML) algorithms, which identify airborne pollen taxa and fungal spore species in real-time, based on the collection of bioaerosol particles from natural sources, appropriate conditioning/treatment in the laboratory and controlled re‑dispersion in air. To develop methods for quantifying the accuracy of the algorithms and for deriving a combined uncertainty arising from uncertainties in both particle counting and particle identification (target expanded uncertainty ≤30 %).

  3. To standardise the data output, interface and metadata of automatic bioaerosol monitors. To develop guidelines on data storage, handling and distribution, ensuring data availability and accessibility compliant with EU environmental regulations, in particular with the Inspire Directive.

  4. To contribute to the development of a new standard on automatic pollen and fungal spore monitoring within the CEN/TC 264/WG 39 – Sampling and Analysis of Airborne Pollen Grains and Fungal Spores, and to contribute to the revision of existing standards published by CEN/TC 264/WG 28 – Measurement of Airborne Microorganisms in Ambient Air.

  5. To address stakeholder needs regarding automatic bioaerosol monitoring highlighted at the BIPM/CCQM Workshop on Particle Metrology and establish strong collaboration with EMN Pollution Monitoring. To facilitate the uptake of the technology and measurement methodologies developed in the project by the EUMETNET AutoPollen community, the EU Horizon Europe project SYLVA, (national/regional) bioaerosol monitoring networks and instrument manufacturers.

Publishable Summary

The publishable summary describes the need, progress beyond the state of the art and potential outcomes and impact of the project.

Poster

The poster presenting the project to the review conference can be seen here.