A statistical model for predicting the inter-annual variability of birchpollen abundance in Northern and North-Eastern Europe

The paper suggests amethodology for predicting next-year seasonal pollen index (SPI, a sumof daily-mean pollen concentrations)over large regions and demonstrates its performance for birch in Northern andNorth-Eastern Europe. Astatistical model is constructed using meteorological, geophysical and biological characteristics of the previous year).A cluster analysis of multi-annual data of European Aeroallergen Network (EAN) revealed several large regions inEurope, where the observed SPI exhibits similar patterns of the multi-annual variability.We built the model for thenorthern cluster of stations, which covers Finland, Sweden, Baltic States, part of Belarus, and, probably, Russia andNorway,where the lack of data did not allow for conclusive analysis. The constructed modelwas capable of predictingthe SPI with correlation coefficient reaching up to 0.9 for somestations, odds ratio is infinitely high for 50% of sites insidethe region and the fraction of prediction fallingwithin factor of 2 from observations, stays within 40–70%. In particular,model successfully reproduced both the bi-annual cycle of the SPI and years when this cycle breaks down

An operational model for forecasting ragweed pollen release and dispersion in Europe

The paper considers the possibilities of modelling the release and dispersion of the pollen of common ragweed (Ambrosia artemisiifolia L.), a highly allergenic invasive weed, which is spreading through southern and central Europe. In order to provide timely warnings for the allergy sufferers, a model was developed for forecasting ragweed pollen concentrations in the air. The development was based on the system for integrated modelling of atmospheric composition (SILAM) and concentrated on spatio-temporal modelling of ragweed flowering season and pollen release, which constitutes the emission term. Evaluation of the new model against multi-annual ragweed pollen observations demonstrated that the model reproduces well the main ragweed pollen season in the areas with major plant presence, such as the Pannonian Plain, the Lyon area in France, the Milan region in Italy, Ukraine and southern Russia. The predicted start of the season is mostly within 3 days of the observed for the majority of stations in these areas. The temporal correlation between modelled and observed concentrations exceeds 0.6 for the bulk of the stations. Model application to the seasons of 2005–2011 indicated the regions with high ragweed pollen concentrations, in particular the areas where allergenic thresholds are exceeded. It is demonstrated that, due to long-range transport of pollen, high-concentration areas are substantially more extensive than the heavily infested territories