Skip to main content

Award details

University of Exeter funding: NERC GW4+ DTP PhD studentship

Applying emulation techniques to Air Quality modelling. Mathematics PhD Studentship (NERC GW4+ DTP funded) Ref: 4017

About the award

Supervisors

Lead Supervisor

Doug McNeall, University of Exeter, Mathematics

Additional Supervisors

Peter Challenor, University of Exeter, Global Systems Institute

Florent Malavelle, Met Office, ADAQ

Paul Agnew, Met Office, ADAQ

Location: Streatham Campus, University of Exeter, Exeter, Devon.

This project is one of a number that are in competition for funding from the NERC Great Western Four+ Doctoral Training Partnership (GW4+ DTP).  The GW4+ DTP consists of the Great Western Four alliance of the University of Bath, University of Bristol, Cardiff University and the University of Exeter plus five Research Organisation partners:  British Antarctic Survey, British Geological Survey, Centre for Ecology and Hydrology,  the Natural History Museum and Plymouth Marine Laboratory.  The partnership aims to provide a broad training in earth and environmental sciences, designed to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/

For eligible successful applicants, the studentships comprises:

  • An stipend for 3.5 years (currently £15,285 p.a. for 2020-21) in line with UK Research and Innovation rates
  • Payment of university tuition fees;
  • A research budget of £11,000 for an international conference, lab, field and research expenses;
  • A training budget of £3,250 for specialist training courses and expenses.
  • Up to £750 for travel and accomodation for compulsory cohort events.


Project details

Project Background

Air pollution is one of the most pressing challenges as it is the single largest environmental health risk in Europe (EEA). Even though air quality across the UK has improved significantly over recent decades and is now considered mostly good, elevated pollution concentrations still occur in many urban locations. Elevated levels or long-term exposure to air pollution can lead to more serious symptoms and conditions affecting human health including respiratory and inflammatory systems.

The UK Air quality forecast is provided to DEFRA by the Met Office using the deterministic AQUM model (Savage et al., 2013). AQUM performance is generally good except under episode conditions when biases persist resulting in over-forecasting. This occurred in April 2020 when the UK was under lockdown and emissions significantly reduced (fig. 1). AQUM predicted a strong pollution event (Fig. 2a) at odds with observations (Fig. 2c). An ad-hoc rescaling of the emissions was applied to maintain satisfactory forecast skill (Fig. 1b). Adjusting input parameters empirically is time consuming and inefficient. Statistical techniques such as emulation have gained lots of attention in Climate and Environmental Sciences (e.g. McNeall et al., 2020) as they provide efficient frameworks for systematic uncertainty quantification. This PhD project aims to apply these methods to air quality modelling with an endeavour to improve Air Quality forecasting.

Figure 1. Nitrogen dioxide seen by Sentinel-5P on January 2020 (top) and March 2020 (bottom). Courtesy of ESA.

Figure 2. Daily Air Quality Index (DAQI) at AURN measurement sites on the 10th of April 2020 from (a) the Met Office operational forecast, (b) modified forecast considering the effect of COVID restrictions and (c) AURN observations.

Project Aims and Methods

• Construct an emulator for AQUM to develop an understanding of uncertainties in the AQ forecast.

• Identify most important parameters in AQUM that affect forecast skill.

• Use Air Quality observations and emulators to constrain spread in forecast (model calibration).

• Can emulation be used as a fast decision-making tool (e.g. emission sector scenarios)?

• Investigate added value of more advanced schemes available in UKCA.

Candidate requirements

The project is inter-disciplinary in nature as it seeks to bring mathematical expertise to air quality modelling. It would suit a numerate scientist passionate to understand environmental challenges. The project involves working with numerical models and experience in programming is preferred. Backgrounds such as mathematics/physics/environmental science/computer science would all be acceptable.

CASE partner

With the Met Office as a CASE partner, unparalleled support will be provided in using state of the art air quality model in a world-renowned forecasting centre. This will be achieved through direct interaction with scientists of the Atmospheric Dispersion and Air Quality group responsible for the development and evaluation of AQUM. This group carries out research which are particularly applicable for Government emergency response and policy and use by regulatory bodies. The Met Office and the University of Exeter recently announced the creation of a Joint Centre for Excellence in Environmental Intelligence to pioneer the development of environmental intelligence research. It is a fantastic opportunity to be part of an exciting ecosystem of world-leading researchers who use Environmental Intelligence to enhance society’s resilience to environmental and climatic change and build a more sustainable future. Training In addition to the DTP, training courses on running AQUM, using air quality observations and learning how to work with HPC environments will be provided. Opportunity to attend specialised workshops on statistics (e.g. ATP) or atmospheric composition (e.g. NCAS) as well as international conferences (e.g. EGU). Opportunity to take part in Alan Turing Institute events as one of the supervisors is an Alan Turing Fellow.

Background reading and references

McNeall, D. et al. (2020), doi: 10.5194/gmd-13-2487-2020

Savage, N. H. et al. (2013), doi:10.5194/gmd-6-353-2013

Eligibility

NERC GW4+ DTP studentships are open to UK and Irish nationals who, if successful in their applications, will receive a full studentship including payment of university tuition fees at the home fees rate.

A limited number of full studentships are also available to international students which are defined as EU (excluding Irish nationals), EEA, Swiss and all other non-UK nationals.  For further details please see the NERC GW4+ website.

Those not meeting the nationality and residency requirements to be treated as a ‘home’ student may apply for a limited number of full studentships for international students. Although international students are usually charged a higher tuition fee rate than ‘home’ students, those international students offered a NERC GW4+ Doctoral Training Partnership full studentship starting in 2021 will only be charged the ‘home’ tuition fee rate (which will be covered by the studentship). International applicants need to be aware that you will have to cover the cost of your student visa, healthcare surcharge and other costs of moving to the UK to do a PhD. More information on this is available from the universities you are applying to (contact details are provided in the project description that you are interested in

The conditions for eligibility of home fees status are complex and you will need to seek advice if you have moved to or from the UK (or Republic of Ireland) within the past 3 years or have applied for settled status under the EU Settlement Scheme.
 

 

Entry requirements

Applicants should have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK.   Applicants with a Lower Second Class degree will be considered if they also have Master’s degree.  Applicants with a minimum of Upper Second Class degree and significant relevant non-academic experience are encouraged to apply.

All applicants would need to meet our English language requirements by the start of the  project http://www.exeter.ac.uk/postgraduate/apply/english/.

 

How to apply

In the application process you will be asked to upload several documents.  Please note our preferred format is PDF, each file named with your surname and the name of the document, eg. “Smith – CV.pdf”, “Smith – Cover Letter.pdf”, “Smith – Transcript.pdf”.

  • CV
  • Letter of application outlining your academic interests, prior research experience and reasons for wishing to undertake the project.
  • Transcript(s) giving full details of subjects studied and grades/marks obtained.  This should be an interim transcript if you are still studying.
  • If you are not a national of a majority English-speaking country you will need to submit evidence of your current proficiency in English.

Reference information
You will be asked to name 2 referees as part of the application process, however we will not expect receipt of references until after the shortlisting stage. Your referees should not be from the prospective supervisory team.

If you are shortlisted for interview, please ensure that your two academic referees email their references to the pgr-recruitment@exeter.ac.uk, 7 days prior to the interview dates.  Please note that we will not be contacting referees to request references, you must arrange for them to be submitted to us by the deadline.

References should be submitted by your referees to us directly in the form of a letter. Referees must email their references to us from their institutional email accounts. We cannot accept references from personal/private email accounts, unless it is a scanned document on institutional headed paper and signed by the referee.

All application documents must be submitted in English. Certified translated copies of academic qualifications must also be provided.

The closing date for applications is Friday 8 January 2021 2359 GMT .  Interviews will be held between 8th and 19th February 2021.  For more information about the NERC GW4+ DPT please visit https://nercgw4plus.ac.uk

If you have any general enquiries about the application process please email pgrenquiries@exeter.ac.uk.  Project-specific queries should be directed to the lead supervisor.


Data Sharing
During the application process, the University may need to make certain disclosures of your personal data to third parties to be able to administer your application, carry out interviews and select candidates.  These are not limited to, but may include disclosures to:

  • the selection panel and/or management board or equivalent of the relevant programme, which is likely to include staff from one or more other HEIs;
  • administrative staff at one or more other HEIs participating in the relevant programme.

Such disclosures will always be kept to the minimum amount of personal data required for the specific purpose. Your sensitive personal data (relating to disability and race/ethnicity) will not be disclosed without your explicit consent.

Summary

Application deadline:8th January 2021
Value:£15,285 per annum for 2020-21
Duration of award:per year
Contact: PGR Enquiries pgrenquiries@exeter.ac.uk