A temporally and spatially explicit, data-driven estimation of airborne ragweed pollen concentrations across Europe.

Ongoing and future climate change driven expansion of aeroallergen-producing plant species comprise a major human health problem across Europe and elsewhere. There is an urgent need to produce accurate, temporally dynamic maps at the continental level, especially in the context of climate uncertainty. This study aimed to restore missing daily ragweed pollen data sets for Europe, to produce phenological maps of ragweed pollen, resulting in the most complete and detailed high-resolution ragweed pollen concentration maps to date. To achieve this, we have developed two statistical procedures, a Gaussian method (GM) and deep learning (DL) for restoring missing daily ragweed pollen data sets, based on the plant's reproductive and growth (phenological, pollen production and frost-related) characteristics. DL model performances were consistently better for estimating seasonal pollen integrals than those of the GM approach. These are the first published modelled maps using altitude correction and flowering phenology to recover missing pollen information. We created a web page (http://euragweedpollen.gmf.u-szeged.hu/), including daily ragweed pollen concentration data sets of the stations examined and their restored daily data, allowing one to upload newly measured or recovered daily data. Generation of these maps provides a means to track pollen impacts in the context of climatic shifts, identify geographical regions with high pollen exposure, determine areas of future vulnerability, apply spatially-explicit mitigation measures and prioritize management interventions.

High Ambrosia pollen concentrations in Poland respecting the long distance transport (LDT).

High Ambrosia pollen concentrations in Poland rather rarely come from the local sources. The aim of this study was to define the temporal and spatial differences of the high Ambrosia pollen concentrations by creating models for the pollen transport from the distant sources. This study was thought to determine the direction of the air masses inflow into Poland, carrying Ambrosia pollen, from areas of the bordering countries with the pollen concentrations higher than iSTOTEN_n Poland. Pollen and meteorological datasets at 8 monitoring sites in Poland, and daily pollen concentrations at 11 sites in the Czech Republic, 5 sites in Slovakia and 3 sites in Ukraine were analysed recently. Days with concentrations ≥10 Pollen/m3 and concurrent meteorological situations were analysed in great deal. The HYSPLIT model was applied to compute backward trajectories up to 4 days backward (96 h) and at three altitudes: 20, 500 and 1000 m above ground level (a.g.l.). High pollen concentrations occur most frequently when the air masses inflow into Poland from southerly (S, SE, SW, 44%) and easterly (E, 6%) directions and in no advection situations (25%). In years with the highest frequency of days over 10 Pollen/m3, the prevailing directions of the pollen influx into Poland were from the South (2004-2006, 2008, 2011) but in one year (2014) from the East. Trajectories for the studied period show that air masses come most frequently from Slovakia and the Czech Republic. Sometimes, the Ambrosia pollen transport happens from Ukraine.