Inhale project studentship 2020 entry

Numerical simulation of the influence of urban trees on roadside pollutant dispersion.

The aim of this PhD study is to investigate the influence of trees (height, leaf density, spacing, etc.) on particulate pollutants in urban and build a biology-greening model using CFD, which is to predict the particles concentrations and contribute to the tree planting schemes so as to improve urban air quality.

Start date
4 January 2021
Duration
3 years
Application deadline
Funding information

The funding covers academic fees for UK/EU students. You will also receive a stipend of £15,500 per annum to cover your living expenses. Additional funding is available to present your work in a conference and for project related costs. Opportunities for tutorial support in the department are available and will enhance your teaching experience as well as provide further income (approximately £1,200-£1,500 per annum).

About

Passive pollution mitigation in near-road environments

Urban roadside green furniture such as trees, hedges and green walls could efficiently reduce exposure to roadside pollutants. Their physical properties, such as leaf surfaces, can act as biological filters. Complementing the scope of EPSRC funded INHALE (Health assessment across biological length scales for personal pollution exposure and its mitigation) project (EP/T003189/1), this studentship project will investigate the influence of passive barriers on reduced exposure to air pollutants in near-road outdoor and indoor environments such as schools via experimental and appropriate modelling techniques. The project offers a substantial opportunity to work with a variety of low-cost and research-grade instruments as well as dispersion modelling tools and to become part of a vibrant team.

Objectives

While the detailed specific objectives of this project will be defined in discussion with the student at the beginning of the project considering the candidate’s strength and the opportunities available, they will be expected to contribute to the one or more following areas:

  1. Assessment of passive mitigations and indoor-outdoor ingress of air pollutants via experiments.
  2. Developing a simple greening model that considers particle physics and green infrastructure properties, to allow assessment of the trees/hedges under different configurations such as their efficacy for roadside schools and parks.
  3. Developing recommendations on optimal solutions.

The candidates who have a background or interest in air pollution monitoring and/or modelling, and especially data collection and analysis using statistical tools, will be well-suited for this project. GCARE has a multidisciplinary team where researchers from all backgrounds are most welcome.

Supervisor

The PhD project will be supervised by Professor Prashant Kumar, who is a founding Director of the Global Centre for Clean Air Research (GCARE). He has extensive experience in air pollution and green infrastructure monitoring/modelling and particle dynamics modelling. The candidate will have the opportunity to closely work with the diverse and multidisciplinary GCARE team and collaborate with various relevant projects ongoing within the centre and beyond with Imperial College London partners of INHALE project.

Related links
INHALE project Project news piece Global Centre for Clean Air Research Team members Research projects

Eligibility criteria

Candidates are expected to have:

  • A MEng/MSc in Environmental/Chemical/Civil/ Mechanical/Aeronautical/Automotive/Fluid Mechanics/Particle Physics/ /Transportation Engineering/Science or relevant discipline with a UK equivalent 2:1 classification or above.

    or
     

  • A BEng in Environmental/Chemical/Civil/ Mechanical/Aeronautical/Automotive/Fluid Mechanics/Particle Physics/Transportation Engineering/Science or relevant discipline with a UK equivalent 2:1 classification or above and MSc/MEng degree in relevant discipline.

In addition to the academic qualifications listed above, skills in computational fluid dynamics modelling of air pollution using ANYSYS/OpenFoam, as well as background/interest in air pollution monitoring/particle physics/statistical data analysis, are desirable. Relevant work experience is also useful (please provide sufficient detail so that its relevance can be established).

Non-native speakers of English will normally be required to have IELTS 6.5 or above (or equivalent) with 6.0 in each individual category.

*The funding for this project is primarily available to citizens of UK/EU. Any interested overseas candidates need to cover the difference between the home and overseas fee difference by themselves. In case of exceptional overseas candidates, options to cover this difference may be explored.

How to apply

The interested candidates are requested to send their CV directly to Professor Prashant Kumar . Upon his confirmation, you are welcome to make a formal application via the Civil and Environmental Engineering PhD programme page. 

The formal end date of making an application is 15 April 2021. However, the candidates are encouraged to send their CVs as early as they can to Prof Kumar since we will regularly interview candidates on a first-come, first-serve basis and given preference to those able to firmly start the programme by 1 July 2021.


Application deadline

Contact details

Prashant Kumar
26 AA 03
Telephone: +44 (0)1483 682762
E-mail: P.Kumar@surrey.ac.uk

About GCARE

GCARE is a multidisciplinary centre, headed by Professor Prashant Kumar, researching in areas of air pollution, air-climate interactions, built and natural environments in the context of cities, megacities and rural areas, with an aim to develop engineering-driven solutions and regulatory strategies for mitigation of environmental risks by means of advanced measurements and modelling techniques. The GCARE’s research projects are funded by the UKRI (e.g., EPSRC, NERC, ESRC, Innovate UK), numerous national and international funding bodies (e.g., EU H2020, British Council, UKIERI) and the industry. Further information can be found here

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