Avoidance of the allergen is the most important aim in the daily life of a pollen allergy sufferer and can lead to freedom of symptoms at best. Informed pollen allergy sufferers know how to help themselves. Information is the prerequisite for avoidance. The aim of the Austrian pollen information service is to provide as independent platform the best possible and scientifically sound information and to thereby facilitate the every day life of persons concerned. The pollen information service offers services which simplify allergen avoidance. Those include pollen forecasts, bi-hourly forecasts that show peak loads during the day, personalized pollen information and information about allergenic plants, their flowering periods and allergy information. The fundament of pollen information are air samples that are gathered with pollen traps (here more about pollen traps).
The road to pollen data takes time, because pollen in the sample has to be identified and counted. As an example: If a count of 1000 pollen grains per m3 air is reached during the high season of birches, some analyst counted all those 1000 birch pollen grains besides other pollen types (e.g. ash pollen). Therefore it is not possible to receive and distribute pollen data in real time.
Besides the conventional regional pollen forecasts, the short- and medium term forecasts, which are prepared also in cooperation with the ZAMG (Zentralanstalt für Meteorologie und Geodynamik) we provide on our pages more information about the current situation:
• Countdown to the flowering start of the most important allergenic plants
• Charts for the graphic display of the Pollen load (comparison of the current with the average load)
• Profiles with important information about allergenic plants
• bi-hourly forecasts for birch, grass and ragweed pollen with load development during the day
• Symptom load map with the indication where and how severe the burden persists
You can profit more from all those mentioned services if you read the notes for a better understanding. The Countdown shows the start of flower of a selected allergenic plant based on model and weather data. Exact data is prepared by the regional pollen information service when needed and directly related to the local situation. In any case the readiness to flower is not equal to the flowering start. Reaching the readiness of flower only indicates the potential for pollination. The start of pollination is induced by favorable weather conditions. There fore it is possible that first hazel catkins attain the readiness to flower quite early in the year and could pollinate, but pollination is postponed or interrupted due to wintery weather. Similarily a particular early plant can already flower while the majority is remaining dormant.
The bi-hourly forecasts are based on bi-hourly evaluated pollen data and forecast models. They are not so much focused on absolute pollen loads, but try to catch the peak pollen loads during the day.
Reliable pollen forecasts are based on different scientific sources like phenology (development of plants in nature), evaluation of the pollen content in the air (pollen traps), forecast models, land cover data, dispersal models and weather data. Alas there is taking advantage also in this field. Sometimes forecasts are provided by persons or institutions, who/which are not educated in the proper sense or do not dispose the needed knowledge and/or data situation. Therefore grossly misinformation of the public can occur from such sides. You should pay attention to information from reputable institutions (e.g. universities and the Zentralanstalt für Meteorologie und Geodynamik), which draw on profound data and education. In general, pollen forecasts reach nowadays high precision - with the limitation that pollen forecasts are not symptom forecasts. The burden from pollen does not always allow to be directly translated into the burden for allergy sufferers, as some pollen allergy sufferer may be able to report.
This phenomenon as well as the individual reaction pattern of pollen allergy sufferers motivated us to develop the personalized pollen information, that follows the personal reaction patter in forecasting. A symptom forecast is still up in the air, but a goal on the road that we chose to support pollen allergy sufferers better.