From anther to atmosphere: building a better pollen forecast for human health (ref:4250)

从花药到大气：为人类健康建立更好的花粉预测（参考：4250）

• 批准号: 2698476
• 金额: --
• 依托单位: UNIVERSITY OF EXETER
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2698476
• 关键词: anther; atmosphere; building; better; pollen

Project 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. Based at the University of Exeter's Penryn campus in Cornwall, this exciting 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. You will have a unique opportunity to work in interdisciplinary science at the interface between biology, ecology, meteorology and human health, and to be trained in a wide range of skills, from field biology to atmospheric modelling.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. It is expected that you will develop skills in both biological field work and mathematical modelling, but there is scope for you to develop the project to suit your existing skills and areas of interest.Project Partners:The student will be co-supervised by scientists at the Met Office, and will have regular supervisory meetings with Met Office staff. They will also spend six months working at the Met Office in Exeter, working closely with scientists in the Atmospheric Dispersion and Air Quality group for the atmospheric dispersion modelling component of the PhD.Training:The Met office will provide training in atmospheric dispersion modelling, and the supervisory team will provide project-specific training in field skills as required. Exeter University will provide training in transferable skills (e.g. time management, employability, statistics, teaching skills) as part of its graduate training programme. The student will be able to attend regular departmental seminars in the Centre for Geography and Environmental Science and the Centre for Ecology and Conservation

项目背景：英国约有1000万人患有花粉热和花粉过敏症。英国气象局提供的英国花粉预报被数百万花粉热患者用来管理过敏花粉对他们生活的影响。随着气候和土地利用的变化，释放到大气中的花粉的分布和时间也会发生变化，因此了解是什么触发了花粉过敏的发生是至关重要的。这个令人兴奋的项目位于康沃尔的埃克塞特大学Penryn校区，涉及与英国气象局和该大学的科学家合作，开发和验证新的生物和大气模型，以改进未来可操作的花粉预测，并真正改变花粉热患者的生活质量。你将有一个独特的机会从事生物学、生态学、气象学和人类健康之间的跨学科科学工作，并接受从田间生物学到大气建模的广泛技能的培训。该项目的目标和方法：该项目旨在通过发展我们对植物将风媒花粉释放到大气中的时间和地点以及如何和在哪里散布的理解，来提高我们预测花粉浓度的能力。它将涉及收集生态观测和数学模型，目的是了解从单个花头释放花粉、乡村和城市景观中的花的密度，到花粉在大气中长距离移动的跨空间尺度的过程。主要方法将包括：建立和开展受控田间试验，以测量一系列植物释放花粉的每日和季节周期及其对天气和气候的反应；开展实地调查和开发物种分布模型(SDMS)，以估计主要产粉物种在农村和城市景观中的变化密度；实施和验证气象局数值扩散模型(NAME)，以预测花粉颗粒的长途运输。预计你将在生物野外工作和数学建模方面发展技能，但你仍有机会发展该项目，以适应你现有的技能和兴趣领域。项目合作伙伴：该学生将由英国气象局的科学家共同监督，并将与英国气象局工作人员定期举行监督会议。他们还将在埃克塞特的气象局工作六个月，与大气扩散和空气质量组的科学家密切合作，研究博士学位的大气扩散模型部分。培训：气象局将提供大气扩散模型方面的培训，监督小组将根据需要提供实地技能方面的具体项目培训。埃克塞特大学将提供可转让技能(如时间管理、就业能力、统计、教学技能)方面的培训，作为其研究生培训方案的一部分。学生将能够参加在地理和环境科学中心以及生态和自然保护中心举行的定期部门研讨会