Published December 18, 2017 | Version v1
Journal article Open

Measurements and modeling of surface–atmosphere exchange of microorganisms in Mediterranean grassland

  • 1. Institute of Ecology, University of Innsbruck, Sternwartestrasse 15, Innsbruck, 6020, Austria
  • 2. Institute of Biometeorology (IBIMET), Consiglio Nazionale delle Ricerche (CNR), Via G. Caproni 8, 50145, Florence, Italy
  • 3. Plant Pathology Research Unit, French National Institute for Agricultural Research (INRA), Allée des Chênes 67, Montfavet, 84143, France
  • 4. FoxLab, Joint Research Unit Fondazione Edmund Mach – CNR IBIMET, Via E. Mach 1, San Michele all'Adige, 38010, Italy
  • 5. IMèRA, Universitè Aix-Marseille 2, Place le Verrier, Marseille, 13004, France

Description

Microbial aerosols (mainly composed of bacterial and fungal cells) may constitute up to 74 % of the total aerosol volume. These biological aerosols are not only relevant to the dispersion of pathogens, but they also have geochemical implications. Some bacteria and fungi may, in fact, serve as cloud condensation or ice nuclei, potentially affecting cloud formation and precipitation and are active at higher temperatures compared to their inorganic counterparts. Simulations of the impact of microbial aerosols on climate are still hindered by the lack of information regarding their emissions from ground sources. This present work tackles this knowledge gap by (i) applying a rigorous micrometeorological approach to the estimation of microbial net fluxes above a Mediterranean grassland and (ii) developing a deterministic model (the PLAnET model) to estimate these emissions on the basis of a few meteorological parameters that are easy to obtain. The grassland is characterized by an abundance of positive net microbial fluxes and the model proves to be a promising tool capable of capturing the day-to-day variability in microbial fluxes with a relatively small bias and sufficient accuracy. PLAnET is still in its infancy and will benefit from future campaigns extending the available training dataset as well as the inclusion of ever more complex and critical phenomena triggering the emission of microbial aerosol (such as rainfall). The model itself is also adaptable as an emission module for dispersion and chemical transport models, allowing further exploration of the impact of land-cover-driven microbial aerosols on the atmosphere and climate.

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Funding

AIRFORS – Aircraft for Environmental and Forest Science 286079
European Commission