Spatio-Temporal Modeling of Grass and Birch Pollen in Belgium

Andy Delcloo, Willem W. Verstraeten, Rostislav Kouznetsov, Nicolas Bruffaerts, Sébastien Dujardin, Marijke Hendrickx, Mikhail Sofiev

Research output: Contribution in Book/Catalog/Report/Conference proceedingChapter

Abstract

The contribution of biogenic aerosols such as pollen to air pollution effects on the human wellbeing is substantial. Recently there is a global increase in the burden of allergic respiratory diseases. In Europe, a quarter of the population suffers from pollinosis, whereas in some countries the prevalence is over 40%. To date, pollen of various trees and grasses in Belgium are monitored by the Belgian Scientific Institute for Public Health (Sciensano) at five stations on a daily basis. This sampling is rather general and cannot retrieve the spatial representativeness of the airborne pollen into enough detail for individual use. Chemistry Transport Models (CTM’s) are able to quantify the spatial and temporal distributions of airborne pollen at different scales and frequencies. Moreover, CTM’s are useful for short-term forecasting of the intensities of pollen levels. Here we show the results of the modelled spatio-temporal distributions of grass and birch pollen over Belgium for 2008 using SILAM driven by ECMWF meteorological data, an updated MACCIII birch tree areal fraction map based on local information, and a grass pollen emission map showing the spatial distribution of the potential grass pollen sources updated with Copernicus grassland data.
Original languageEnglish
Title of host publicationAir Pollution Modeling and its Application XXVII. ITM 2019
EditorsClemens Mensink, Volker Matthias
PublisherSpringer
Pages113-118
Number of pages6
ISBN (Electronic)978-3-662-63760-9
ISBN (Print)978-3-662-63759-3
DOIs
Publication statusPublished - 2021

Publication series

NameSpringer Proceedings in Complexity
ISSN (Print)2213-8684
ISSN (Electronic)2213-8692

Keywords

  • Birch
  • CTM
  • Grass
  • Health
  • Pollen
  • Pollinosis
  • SILAM

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