TY - JOUR T1 - A statistical model for predicting the inter-annual variability of birch pollen abundance in Northern and North-Eastern Europe. JF - Sci Total Environ Y1 - 2017 A1 - Ritenberga, Olga A1 - Sofiev, Mikhail A1 - Siljamo, Pilvi A1 - Saarto, Annika A1 - Dahl, Aslog A1 - Ekebom, Agneta A1 - Sauliene, Ingrida A1 - Shalaboda, Valentina A1 - Severova, Elena A1 - Lucie Hoebeke A1 - Ramfjord, Hallvard AB -

The paper suggests a methodology for predicting next-year seasonal pollen index (SPI, a sum of daily-mean pollen concentrations) over large regions and demonstrates its performance for birch in Northern and North-Eastern Europe. A statistical 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 in Europe, where the observed SPI exhibits similar patterns of the multi-annual variability. We built the model for the northern cluster of stations, which covers Finland, Sweden, Baltic States, part of Belarus, and, probably, Russia and Norway, where the lack of data did not allow for conclusive analysis. The constructed model was capable of predicting the SPI with correlation coefficient reaching up to 0.9 for some stations, odds ratio is infinitely high for 50% of sites inside the region and the fraction of prediction falling within 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.

VL - 615 U1 - http://www.ncbi.nlm.nih.gov/pubmed/28972900?dopt=Abstract M3 - 10.1016/j.scitotenv.2017.09.061 ER -