Background : In Europe, grass pollen is the single most important outdoor aeroallergen; 27% of the population are sensitised to grass pollen leading to extensive negative health outcomes. Of particular importance to human health is allergic asthma, which can lead to hospitalisation and can be fatal. Sensitivity towards grass pollen varies between species, of which there are over 150 in the UK. However, due to few unique morphological features, grass pollen from different species cannot be discriminated easily using traditional observational methods. Currently, there is no way of detecting, modelling or forecasting the aerial- dispersion of taxon-specific pollen from the extensive biodiversity of UK grasses. PollerGEN is an interdisciplinary NERC project, in collaboration with the UK Met Office with the aim of advancing the way that pollen dispersion is measured and forecast. Emerging molecular data (targeted sequencing of DNA taxonomy markers, i.e. metabarcoding) have indicated that the species composition of aerial grass pollen communities varies significantly both temporally and spatially across the grass flowering season. Yet, the precise quantitative nature of the data, both from laboratory and field trials, remains unconfirmed.

Method : Here, we used quantitative PCR (qPCR) to analyse aerial environmental DNA (eDNA) from up to 14 sites across the UK during the 2016- 2017 grass pollen seasons. Our aim was to quantify phenological and geographical trends exhibited in pollen deposition of key known allergenic grasses, including Dactylis glomerata, Lolium perenne and Phleum pratense.
Results : The results confirm that the grass flowering season is heterogeneous, showing quantitative differences in taxon composition throughout the summer months. The data demonstrate that seasonal exposure to different types of grass pollen is not static, but features shifting abundances of different species of pollen that can be linked to health outcomes. 
Conclusion : The empirical findings will be discussed in addition to providing a broader perspective of the PollerGEN program, that integrates species vegetation mapping, advanced aerobiological modeling, environmental genomic, metabarcoding and qPCR genetic analyses and human epidemiology.