The climate crisis could increase allergy season depth in the future by up to 60%, a new pollen prediction system suggests, while a separate system could predict how bad ‘ in which there would have been seasons of grass pollen months in advance.
Such devices could help health professionals prepare for an increase in hay fever cases, or get admitted to hospital for allergy-related asthma. Seasonal pollen predictions may also enable some people with hay fever to avoid certain seasons by, for example, traveling abroad.
Around a quarter of people in Britain get a pollen allergy or hay fever, with the numbers rising every year. While daily pollen counts can be predicted based on next day and time of year forecasts, it is more difficult to make long-term forecasts for specific cities or regions – meaning that there is no clear guide on how best to prepare for allergy seasons.
Although previous studies have predicted an increase in allergies due to the climate crisis, they have generally included consideration of greater pollen concentrations in recent decades. . “These studies are by nature retrospective and do not predict what will happen 30 years from now,” said Carsten Skjøth, a professor of atmospheric sciences at the University of Worcester.
To address these gaps, Skjøth and his colleagues built two different forecasting systems. The first, designed for long-term assessments such as the impact of climate emergencies or mitigation, brought together ideas on how carbon dioxide affects grass growth with data on how the weather will affect pollen productivity.
“Here we have a dynamic vegetation model that predicts – and displays on a map – the expected increase in pollen density in future climates,” said Skjøth.
Assuming doubling carbon dioxide levels, this would lead to an increase in grass pollen allergy season depth in the future, although the speed of this would depend on the effectiveness of strategies. climate crisis mitigation.
The second forecasting system brought together measurements of air temperature, precipitation and pollen density at 28 pollen monitoring stations in northwestern Europe over several years. Tests showed that it could predict the severity of a grass pollen season based on pre-seasonal weather patterns, which could affect grass growth and pollen production.
“This is a new type of information that can be used for long-term design instead of everyday design, and importantly for pre-season design,” said Skjøth, whose research has been published. in Science. “It won’t give you an exact number, but it will tell you if the coming season will be particularly bad – just like when the Met Office sends out the autumn predictions about whether we’ll have a wet winter. or hard.
“If we know in advance that we are going to have a very bad pollen season, it could provide information on what pharmacies need to put on their shelves. It can also help people plan when they should take annual leave, or even avoid the pollen season by traveling to a different country. ”
The new method could be combined with the latest generation of weather forecasting systems, to create more accurate daily forecasts, he said.
Dr Rachel McInnes, science manager on the impact of air quality at the Met Office, and co-author of the paper, said: “For sufferers, hay fever can be extremely debilitating and grass pollen is the worst culprit. . So any indication of how bad the upcoming pollen season is across the UK is to be welcomed.
“So far it has been beyond the power of science to produce a long-term forecast, partly because pollen counting depends on the characteristics of meteorology as well as land use. But by combining land use and weather models and monitoring results at several survey sites, the team has been able to make progress and provide the interesting view of pollen prediction. long-range.
“Further work is likely to involve linking the team’s methods to air distribution models, and detailed maps of different grass species to a growing luxury. ”