Exploring the use of Microbial Fuel Cells for the online detection of organic micropollutants in water

  • Stephen Bradley

Student thesis: Doctoral ThesisPhD

Abstract

This work explores the possibilities for the use of Microbial Fuel Cells (MFCs) as biosensors for the detection of biologically active organic micropollutants in water streams. The work centred on the detection of the molecules bisphenol-a (BPA), 17β-estradiol (estradiol), naproxen and diclofenac, which are contained within a European Union “watch-list” of emerging micropollutants. This lists them as chemicals of concern which require monitoring due to their potential effects of the environment and on human health. As such there is a pressing need for detection methods for effective monitoring.
All four micropollutants were detected at concentrations at or near the range found in wastewaters. Triclosan was detected at 0.10 µg mL-1, diclofenac at 0.05 µg mL-1, bisphenol-a at 0.1 µg mL-1, and estradiol at 0.5 µg mL-1.
The study also investigated the effects of long-term exposure to these toxicants, which seem to have an effect on the performance of MFCs over time, although this effect is not yet fully understood or quantified.
It was noted that control of anode potential (and therefore chemical overpotential) was particularly effective in stabilising the baseline current of the MFC-based biosensors, and dramatically improved repeatability of results. As such it is a promising way forward for the control of MFC-based biosensors.
This work also investigated the simultaneous detection and removal of these micropollutants and for the first time, reports that these micropollutants can be almost completely removed using a cascade of MFCs, whereby they are fed through several MFCs in succession, although some of the removal is attributed to absorption processes rather than metabolism of the substrate.
Date of Award3 Apr 2019
Original languageEnglish
Awarding Institution
  • University of Bath
SupervisorMirella Di Lorenzo (Supervisor) & Barbara Kasprzyk-Hordern (Supervisor)

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