N.After spring arrives in the northern hemisphere, many people celebrate warmer weather and longer days. For people with hay fever, spring also means itchy eyes, runny noses, headaches and fatigue. One of the main triggers of seasonal allergic rhinitis, the official name for hay fever, is grass pollen. More pollen in the air usually means more severe hay fever. Therefore, accurate pollen predictions can help allergy sufferers better manage their symptoms.
Although weather apps can predict pollen levels a few days in advance, there aren’t any good tools for predicting the severity of the grass pollen season, says Carsten Skjøth, an atmospheric researcher and aerobiologist at the University of Worcester in the UK. In a study published today (March 26) in Advances in science, Skjøth, together with Alexander Kurganskiy, an air pollution modeler at the University of Exeter, and their colleagues describe mathematical models that could improve such long-term predictions.
To develop their model, the researchers analyzed the weather conditions and daily pollen concentrations at 34 observation stations in northwestern Europe from 1996 to 2016. They found that the severity of the annual pollen season could be predicted by the previous year’s rainfall and temperature conditions, but differed at each location, suggesting that pollen forecasts should be considered at a local rather than a regional level.
The team also created a second model to predict future pollen levels as the climate changes. The model suggests that the severity of the grass pollen season could increase by as much as 60 percent if carbon dioxide levels doubled in the future, similar to what was done in a laboratory study that bred Timothy Grass (Phleum pratense) in growth chambers and found that the plant produced about 50 percent more pollen when grown under elevated carbon dioxide conditions.
The scientist spoke to Skjøth and Kurganskiy to learn more about grass pollen prediction and how better forecasting tools can help people with seasonal allergies.
Anne Ambelas Skjøth
Carsten Skjøth: The severity of the grass pollen season varies [in different locations]. We found that every single place seemed to have its own pattern and found a way to describe it in mathematical terms. . . . If we go to Washington [DC]For example, spring rainfall and temperature might determine the season, but if you go to Seattle it might just be precipitation, and if you go to Baltimore it might just be temperature.
The second part is that we were able to apply common vegetation models to describe the effects of climate change – increased carbon dioxide. We developed a mechanistic model that describes how vegetation grows and then we used the same increase in carbon dioxide [i.e., doubled carbon dioxide] that was done in a few [growth] Chamber studies. . . . We do the same thing but use a mathematical model that can be applied anywhere. So different types of land cover, temperature, climate change, etc. are taken into account. And we get the same result [as chamber studies]
CS: Business as usual, yes we get more pollen. . . . A small increase in plant productivity leads to a relatively large increase in pollen productivity. . . which was also found in the chamber studies. But there is a huge difference between doing something in the chamber or in a laboratory and then actually doing something in the field or having a model of what is happening in the landscape and having it replicated with observations.
Alexander Kurganskiy: There have been some studies in [growth] Chambers for pollen concentration. . . . For one thing, they grew ragweed. The others grew grass. You have doubled the carbon dioxide concentration – this is a typical scenario for climate change. [And they found that pollen productivity increased by 50–55 percent.]
CS: How they are calculated is likely to vary from country to country. In most cases it is based on observation. So they have one [pollen] Trap or a network of traps. Or as we see now, they are moving into more automatic devices. But the principle is basically the same, you get the pollen concentration.
For example, these models can predict what’s going on tomorrow or two days from now. . . . You don’t really answer the question. . . What is [pollen severity] will be in 40 days or in the middle of the season? If you are just at the beginning of the grass pollen season, this is it [season] will be bad? . . . We have no idea. However, these are important questions for those suffering from hay fever.
[Grass productivity is] certainly not the same every year, and it can vary greatly from region to region
– Carsten Skjøth, University of Worcester.
[In this study] We go for the entire season and we find that the season [severity] is determined by how the plants grow when they produce their pollen. . . . The current understanding in the [previous] Models assume that the productivity of grasses is the same every year and is the same in all places. However, we show that it is certainly not the same every year and can vary greatly from region to region.
AK: I would be delighted if these models could be further developed and eventually used as forecasting tools to advise health professionals and pollen sufferers on preparing for the upcoming grass pollen season.
CS: Probably the biggest limitation we have is in the study of climate change, as these models only use grasses as a whole. . . . We don’t want to predict what will happen to each species – we don’t have any data. . . . And we are certainly not able to predict what will happen if we now have a region and it is dominated by species that prefer, for example, moist soil and a type of land, and then we have climate change and that changes the land cover, which becomes one Make transition of species. These models do not take this into account.
CS: There is very little knowledge. But just last week a group published a study on this very issue. That’s published in the magazine Current biology. . . . And that is what they found: It is important what kind it is.
Editor’s Note: This interview has been edited for brevity.
A. Kurganskiy et al., “Predicting the Severity of the Grass Pollen Season and the Impact of Climate Change in Northwestern Europe”, Sci Adv, doi: 10.1126 / sciadv.abe1260, 2021.