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


College of Engineering, Mathematics and Physical Sciences

Dr D McNeall , Prof P Challenor Friday, January 08, 2021 Competition Funded PhD Project (Students Worldwide)

About the Project

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.

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.

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.

Studentships for international students will only cover fees at the UK home fees rate. However, university tuition fees for international students are higher than the UK home fees rate therefore the difference will need to be funded from a separate source which the student or project supervisor may have to find. Unfortunately, the NERC GW4+ DTP cannot fund this difference from out studentship funding Further guidance on how this will work will be issued in November.

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.

Funding Notes

NERC GW4+ funded studentship available for September 2021 entry. For eligible students, the studentship will provide funding of fees and a stipend which is currently £15,285 per annum for 2020-21.

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


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