Predicting the severity of the grass pollen season and the effect of climate change in Northwest Europe
| Autor: | Nicolas Bruffaerts, Georgina Brennan, Geoff M. Petch, Letty A. de Weger, J. Satchwell, Rachel N. McInnes, Yolanda Clewlow, Karen Rasmussen, Francis M. Rowney, Alexander Kurganskiy, Nicholas J. Osborne, Carsten Ambelas Skjøth, Helen M. Hanlon, Natasha de Vere, Gareth W. Griffith, Simon Creer, Benedict W. Wheeler, Matthew J. Hegarty, Charlotte Sindt, Caitlin Potter, Gilles Oliver, Catherine H. Pashley, Adam Barber, Beverley Adams-Groom |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Atmospheric Science
Multidisciplinary 010504 meteorology & atmospheric sciences fungi Climate change SciAdv r-articles food and beverages macromolecular substances 010501 environmental sciences Biology medicine.disease 01 natural sciences Grass pollen Research Methods medicine otorhinolaryngologic diseases Hay fever Northwest europe Research Articles 0105 earth and related environmental sciences Demography Research Article |
| Zdroj: | Science Advances, 7(13). AMER ASSOC ADVANCEMENT SCIENCE Science Advances Online: 2375-2548 |
| Popis: | Hay fever patients can be helped in managing their symptoms by predicting the severity of the upcoming grass pollen seasons. Allergic rhinitis is an inflammation in the nose caused by overreaction of the immune system to allergens in the air. Managing allergic rhinitis symptoms is challenging and requires timely intervention. The following are major questions often posed by those with allergic rhinitis: How should I prepare for the forthcoming season? How will the season’s severity develop over the years? No country yet provides clear guidance addressing these questions. We propose two previously unexplored approaches for forecasting the severity of the grass pollen season on the basis of statistical and mechanistic models. The results suggest annual severity is largely governed by preseasonal meteorological conditions. The mechanistic model suggests climate change will increase the season severity by up to 60%, in line with experimental chamber studies. These models can be used as forecasting tools for advising individuals with hay fever and health care professionals how to prepare for the grass pollen season. |
| Databáze: | OpenAIRE |
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