Self-funded PhD opportunities
Fast repetition rate fluorometry as an early warning system for algal blooms in rivers.
- Application end date: Applications open all year round
- Funding Availability: Self-funded PhD students only
- Department: School of Earth and Environmental Sciences
- PhD Supervisor: Dr. Michelle Hale, Prof Jim Smith, Dr. Mike Bowes
Project code: SEES4441018
UK water companies regularly suffer problems associated with blooms caused by algae and cyanobacteria. Algal blooms can contaminate water supplies with toxins, cause taste and odour problems, and impact on the effectiveness of equipment used for water treatment. It is estimated that eutrophication costs the UK over £114 million per year, and problems of excessive algal growth are predicted to get worse under future climate change scenarios (3). This project proposes to use a novel application of Fast Repetition Rate fluorometry (Frrf) to measure quantum yield (Fv/Fm), an indicator of algal 'health', to better understand and predict algal blooms. Of particular interest to the water industry is the potential of FRRf, together with easily-measurable environmental variables such as light, temperature, flow and nutrients, to provide an early warning system for bloom development.
In the first ever use of Frrf in rivers to measure Fv/Fm, a pilot study on the River Thames (conducted with Project Partner CEH), found a strong relationship between the Fv/Fm of chlorophytes and cyanobacteria, and algal and cyanobacterial biomass. These initial results suggest that FRRf can provide powerful new insights into phytoplankton dynamics in rivers and allow water companies to rapidly intervene to prevent bloom formation.
Working closely with CEH, the project will monitor sites on the River Thames, which often suffers from eutrophication problems, leading to algal blooms that cause problems with taste and odour in drinking water. High-frequency (hourly) monitoring of nutrient concentrations, temperature, dissolved oxygen, light and flow, alongside sub-daily biological data from flow cytometry and FRRf (blue and red PhytoFlash) will produce a truly unique dataset that will allow us to better understand the controls on blooms in rivers (timing, duration and magnitude). These data will be analysed using time series analysis (7) to determine whether changes in Fv/Fm can provide an early warning system for algal blooms, so that UK water companies can act quickly to avoid and mitigate any harmful or unpleasant effects, and better manage water supplies.
You’ll need a good first degree from an internationally recognised university (depending upon chosen course, minimum second class or equivalent) or a Master’s degree in an appropriate subject. Exceptionally, equivalent professional experience and/or qualifications will be considered. English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.
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How to Apply
You can apply online at www.port.ac.uk/applyonline. You are required to create an account which gives you the flexibility to save the form, log out and return to it at any time convenient to you.
A link to the online application form and comprehensive guidance notes can be found at www.port.ac.uk/pgapply.
When applying, please quote project code: SEES4441018
Interview date: TBC
Start date: October 2018.
This is self-funded project, for infomration on fees and funding, please see our webpages.
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