Pollen Sources

This chapter reviews what is known about abundance and distribution of the 12 most important aeroallergenic pollens in Europe: Ambrosia, Alnus, Artemisia, Betula, Chenopodiaceae, Corylus, Cupressaceae/Taxaceae, Olea, Platanus, Poaceae, Quercus and Urtica/Parietaria. Abundance is based on 10 years of pollen records from 521 stations of the European Aeroallergen Network that were interpolated into 12 distribution maps covering most of Europe. The chapter compares the distribution maps with other types of distribution maps that are available for selected tree species and discuss two methods for making harmonized pollen source inventories: “bottom-up” and “top-down”. Both methods have advantages and disadvantages, and both need to be explored and further developed. Remote sensing has shown to be a valuable method to improve the inventories, especially the use of satellites. The full potential as well as limitations of remote sensing in relation to pollen sources remains to be explored. The review suggests that the most probable way of obtaining inventories of all 12 pollen species is to use top-down methods that use an ecosystem-based approach that for each particular species connects ecological preference, pollen counts and remote sensing.

Improvement in the Accuracy of Back Trajectories Using WRF to Identify Pollen Sources in Southern Iberian Peninsula

Airborne pollen transport at micro-, meso-gamma and meso-beta scales must be studied by atmospheric models, having special relevance in complex terrain. In these cases, the accuracy of these models is mainly determined by the spatial resolution of the underlying meteorological dataset. This work examines how meteorological datasets determine the results obtained from atmospheric transport models used to describe pollen transport in the atmosphere. We investigate the effect of the spatial resolution when computing backward trajectories with the HYSPLIT model. We have used meteorological datasets from the WRF model with 27, 9 and 3 km resolutions and from the GDAS files with 1 ° resolution. This work allows characterizing atmospheric transport of Olea pollen in a region with complex flows. The results show that the complex terrain affects the trajectories and this effect varies with the different meteorological datasets. Overall, the change from GDAS to WRF-ARW inputs improves the analyses with the HYSPLIT model, thereby increasing the understanding the pollen episode. The results indicate that a spatial resolution of at least 9 km is needed to simulate atmospheric flows that are considerable affected by the relief of the landscape. The results suggest that the appropriate meteorological files should be considered when atmospheric models are used to characterize the atmospheric transport of pollen on micro-, meso-gamma and meso-beta scales. Furthermore, at these scales, the results are believed to be generally applicable for related areas such as the description of atmospheric transport of radionuclides or in the definition of nuclear-radioactivity emergency preparedness.