📣 Help Shape the Future of UKRI's Gateway to Research (GtR)

We're improving UKRI's Gateway to Research and are seeking your input! If you would be interested in being interviewed about the improvements we're making and to have your say about how we can make GtR more user-friendly, impactful, and effective for the Research and Innovation community, please email gateway@ukri.org.

From anther to atmosphere: building a better pollen forecast for human health

Lead Research Organisation: UNIVERSITY OF EXETER
Department Name: Geography

Abstract

Background: Approximately ten million people in the UK suffer from hay fever and pollen allergies. The UK pollen forecast provided by the Met Office is used by millions of hay fever sufferers to manage the impact of allergenic pollen on their lives. As our climate and land use changes, so will the distribution and timing of pollen released to the atmosphere, and so understanding what triggers the onset of pollen allergies is critical. This project involves working with scientists from the Met Office and the University to develop and validate new biological and atmospheric models to improve the operational pollen forecast in the future and make a real difference to the quality of life of hay fever sufferers.
Project Aims and Methods: This project aims to improve our ability to forecast pollen concentrations by developing our understanding of when and where wind-borne pollen is released into the atmosphere by plants and how and where it is dispersed. It will involve both collecting ecological observations and mathematical modelling, with the aim of understanding processes across spatial scales from pollen release from a single flower head, and the density of flowers within rural and urban landscapes, to the movement of pollen over large distances in the atmosphere. Key methods will involve: setting up and running controlled field experiments to measure the daily and seasonal cycles of pollen release in a range of species of plants and their response to weather and climate; carrying out field surveys and developing species distribution models (SDMs) to estimate the changing density of key pollen-producing species within rural and urban landscapes; implementing and validating the Met Office numerical dispersion model (NAME) to predict long-distance transport of pollen grains.
Project Partners: The student will be co-supervised by scientists at the Met Office, and will have regular supervisory meetings with Met Office staff.

Publications

10 25 50

Studentship Projects

Project Reference Relationship Related To Start End Student Name
NE/S007504/1 30/09/2019 30/11/2028
2698476 Studentship NE/S007504/1 30/09/2022 05/05/2026 Mirjana Markovic