Project Background
Atmospheric dispersion models are used to predict the transport and dispersion of potentially hazardous material in the atmosphere. Large uncertainties exist in the source term describing accidental emissions (e.g., release rate, release height) and this impacts on the accuracy of, and confidence in, predictions. Inverse modelling techniques can be used to constrain the uncertain source term, combining atmospheric dispersion modelling, observations and a first-guess estimate of the emissions.
Source inversion work at the Met Office has largely focussed on estimating greenhouse gas and volcanic ash emissions, although there is interest in extending these techniques to other applications. The Met Office is keen to develop an operational source inversion capability for radiological releases, with potential to significantly improve the advice provided in the response to accidental releases of radioactivity into the environment. The project will draw upon established collaborations between the Met Office, the University of Bristol and Public Health England on modelling of radioactivity in the environment and previous source inversion studies, including determining the location of an unexpected release of ruthenium-106 in 2017.
Project Aims and Methods
The aim of the project is to explore the best way of combining a range of sparse radiological measurements and radiological expertise to constrain estimates of radionuclide emissions for different scenarios (e.g., an accident at a nuclear power plant or an unexpected detection of radioactivity from an unknown source). Radiological source inversion is a complex problem. Releases are often a cocktail of multiple radionuclides, which are subject to radioactive decay, and transformation into daughter decay products, and removal by dry and wet deposition processes. Furthermore, radiological observations may comprise of a range of measurements of different quantities (e.g., gamma dose, air activity or deposition), which may or may not be speciated, and which can span various timescales (e.g., weekly, daily, or hourly).
Bayesian spatio-temporal modelling will be used to integrate radiological measurements, transport and dispersion modelling and initial (prior) estimates of radiological emissions. The relationships between emissions and the radiological measurement quantities are non-trivial, requiring suitable approximations such as Markov Chain Monte Carlo or history matching. Covariance matrices can be used to represent expert knowledge in terms of prior uncertainties and correlations. Uncertainties and spatio-temporal dependencies in observations and numerical model predictions can also be incorporated within error covariance matrices. The inversion problem is under-determined and hence prior assumptions, making use of expert radiological knowledge, are key. It is important, therefore, to construct a prior wisely and to understand the influence of the chosen prior on emissions estimates. The project will build on the current state-of-the-art, working with experts to develop techniques for different radiological release scenarios, incorporating additional types of measurements and expert knowledge, whilst overcoming limitations and reducing assumptions made.
Candidate requirements
Mathematics / Physics / Statistics / Computing
Project partners
The student will join an established and exciting collaboration between academia, the Met Office and Public Health England, offering the opportunity to develop new research for operational services. The collaboration with project partners will provide data, environmental models, and expertise, as well as access to a wealth of on-going science activities at partner organisations, including seminars and wider team involvement.
Training
The student will have access to training and activities in statistics and applications of statistical methods to environmental problems (for example, through the CDT in Environmental Intelligence (www.eicdt.ac.uk). The Met Office offers training on their atmospheric dispersion model, NAME, and their source inversion model, InTEM for volcanic ash.
Useful links
For information relating to the research project please contact the lead Supervisor via Dr Helen Webster ([Email Address Removed]), http://emps.exeter.ac.uk/mathematics/staff/hw600
How to apply
In order to formally apply for the PhD Project you will need to go to the following web page.
https://www.exeter.ac.uk/study/funding/award/?id=4261
The closing date for applications is 1600 hours GMT on Friday 10th January 2022.
Interviews will be held between 28th February and 4th March 2022.
If you have any general enquiries about the application process please email [Email Address Removed] or phone: 0300 555 60 60 (UK callers) or +44 (0) 1392 723044 (EU/International callers). Project-specific queries should be directed to the main supervisor