Abstract

Introduction (contexte de la recherche) Recent advances in real-time bioaerosol detection has boosted research in geophysics (in relation with the Earth's hydrological cycle) and respiratory health (allergy & infectious diseases). The physicochemical properties of bioaerosols differ according to their composition, size and ecosystem of origin. Thus, novel online instruments both commercially available and/or under development utilize different detection methodologies for bioaerosol characterization. Among these techniques, light induced fluorescence of individual particles in the size range to 0.3 to 100 μm stands as the predominant solution. However, the current “gold” standard of pollen grains and fungal spores analysis is the Hirst method (NF EN 16868) which is based on the collection of bio-particles on an adhesive tape, followed by optical microscopy analysis. In this context, OBERON SCIENCES (France) has developed an instrument called Aerōtape, which utilizes a similar principle as that used for the Hirst procedure. The Aerōtape uses optical image recognition and machine learning to differentiate between particles. Initial results obtained during laboratory and field experiments showed that the Aerōtape can collect particulate matter from 1 μm up to 100 μm, and produce real-time characterization of pollen taxa, fungal spores and mineral dust. The Aerōtape thus represents an innovative approach, which may contribute to automated and simultaneous observations of bioaerosols and other particle matter components. Hence, it will aid both research and operational networks in the evaluation of air quality.

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