Incorporation of pollen data in source maps is vital for pollen dispersion models
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
Forlagets udgivne version, 9,04 MB, PDF-dokument
Information about distribution of pollen sources, i.e. their presence and abundance in a specific region, is important, especially when atmospheric transport models are applied to forecast pollen concentrations. The goal of this study is to evaluate three pollen source maps using an atmospheric transport model and study the effect on the model results by combining these source maps with pollen data. Here we evaluate three maps for the birch taxon: (1) a map derived by combining a land cover data and forest inventory, (2) a map obtained from land cover data and calibrated using model simulations and pollen observations, and (3) a statistical map resulting from analysis of forest inventory and forest plot data. The maps were introduced to the Enviro-HIRLAM (Environment - High Resolution Limited Area Model) as input data to simulate birch pollen concentrations over Europe for the birch pollen season 2006. A total of 18 model runs were performed using each of the selected maps in turn with and without calibration with observed pollen data from 2006. The model results were compared with the pollen observation data at 12 measurement sites located in Finland, Denmark, and Russia. We show that calibration of the maps using pollen observations significantly improved the model performance for all three maps. The findings also indicate the large sensitivity of the model results to the source maps and agree well with other studies on birch showing that pollen or hybrid-based source maps provide the best model performance. This study highlights the importance of including pollen data in the production of source maps for pollen dispersion modelling and for exposure studies.
|Tidsskrift||Atmospheric Chemistry and Physics|
|Status||Udgivet - 26 feb. 2020|
Antal downloads er baseret på statistik fra Google Scholar og www.ku.dk