Trends in the characteristics of allergenic pollen circulation in central Europe based on the example of Szeged, Hungary

The aim of the study is to analyse trends of the pollination season with its start and end dates, as well as trends of the annual total pollen count and annual peak pollen concentration for the Szeged agglomeration in Southern Hungary. The data set covers an 11-year period (1999–2009) and includes one of the largest spectra, with 19 taxa, as well as seven meteorological variables (minimum-, maximum- and mean temperature, total radiation, relative humidity, rainfall and wind speed). For highly skewed data, such as the annual total number of pollen counts or annual peak pollen concentrations, the Mann–Kendall test has a substantially greater predictive power than the t-test. After performing Mann–Kendall tests, the annual cycles of daily slopes of pollen concentration trends and annual cycles of daily slopes of climate variable trends are calculated. This kind of trend analysis is a novel approach as it provides information on annual cycles of trends. In order to represent the strength of their relationships an association measure (AM) and a multiple association measure (MAM) are introduced. Based on climate sensitivity, the individual taxa are sorted into three categories. The results obtained for the pollen quantity and phenological characteristics are compared with two novel climate change related categories, namely risk and expansion potential due to the climate change for each taxon. The total annual pollen count and annual peak pollen concentrations indicate a small number of changes when using ordinary linear trends, while the total annual pollen count calculated via daily linear trends show significant trends (70% of them positive) for almost all taxa. However, except for Poaceae and Urtica, there is no significant change in the duration of the pollination season. The association measure performs well compared to the climate change related forces. Furthermore, remarkable changes in pollen season characteristics are also in accordance with the risk and expansion potential due to climate change.