No abstract

The European Commission Cooperation in Science and Technology (COST) Action FA1203 “SMARTER” aims to make recommendations for the sustainable management of Ambrosia across Europe and for monitoring its efficiency and cost-effectiveness. The goal of the present study is to provide a baseline for spatial and temporal variations in airborne Ambrosia pollen in Europe that can be used for the management and evaluation of this noxious plant. The study covers the full range of Ambrosia artemisiifolia L. distribution over Europe (39°N–60°N; 2°W–45°E). Airborne Ambrosia pollen data for the principal flowering period of Ambrosia (August–September) recorded during a 10-year period (2004–2013) were obtained from 242 monitoring sites. The mean sum of daily average airborne Ambrosia pollen and the number of days that Ambrosia pollen was recorded in the air were analysed. The mean and standard deviation (SD) were calculated regardless of the number of years included in the study period, while trends are based on those time series with 8 or more years of data. Trends were considered significant at p < 0.05. There were few significant trends in the magnitude and frequency of atmospheric Ambrosia pollen (only 8% for the mean sum of daily average Ambrosia pollen concentrations and 14% for the mean number of days Ambrosia pollen were recorded in the air). The direction of any trends varied locally and reflected changes in sources of the pollen, either in size or in distance from the monitoring station. Pollen monitoring is important for providing an early warning of the expansion of this invasive and noxious plant.Electronic supplementary materialThe online version of this article (doi:10.1007/s10453-016-9463-1) contains supplementary material, which is available to authorized users.

No operational forecasting model for allergenic fungal spore exposure exists in Europe.• Potential exposure in Europe was assessed and predicted for 2 major allergenic fungi. • Random forest modelling was applied to N7000 daily time series. • Air temperature and vapour pressure were the most significant variables. • Classification models showed higher capacity for large-scale spore predictions.

No abstract

No abstract