The upstream protection of the biomass present in biological treatment processes is a vital challenge as the consequences of failure could include exposure of water users to hazardous chemicals in addition to loss of treatment performance. Online detection of toxic compounds in wastewater could enable processes to be monitored in real-time and promote pro-active responses to pollution incidents. Recently, Microbial Fuel Cells (MFCs) which generate electricity from organic matter oxidation have shown potential as sensors for online detection of toxicity. In this study, the detection of a model toxicant (4-nitrophenol) was investigated using a multi-stage MFC-based toxicity sensor. MFCs were operated with synthetic wastewater to maintain realistic conditions while enabling organic carbon levels to be controlled. A positive correlation was observed between the 4-NP concentrations and the current drop area showing that the response was proportional to the toxicity level. In addition, the sensor anodic biofilm exhibited resilience to acute toxic events with recovery of 75% of the initial current following a toxic event comprising 500 mg/L 4-NP after 4 h. However, repetitive toxicity events could lead to the selection of resistant bacteria able to degrade the toxic compounds. In this study, a maximal 4-NP degradation rate of 36 mg/h was observed. This limitation could be overcome by re-calibration after a determined number of toxic events. An additional feature of the multi-stage configuration of the sensor is that a drop in output caused by the presence of a toxic compound could be distinguished from a drop in output caused by a decrease in BOD. The microbial community on the sensor anode was characterized by 16S rRNA gene sequencing and shown to comprise an anaerobic community of fermentative bacteria capable of producing volatile fatty acids and hydrogen that were consumed by electrogenic Geobacter spp (2.76 to 21.39% of the anode community) that generated the electrical signal in the sensor. The multi-stage MFC biosensor could provide an early warning system capable of alerting process operators to the presence and level of toxicity in influent wastewater.
Microbial Fuel Cells (MFCs) operated as biosensors could potentially enable truly low-cost, real-time monitoring of organic loading in wastewaters. The current generated by MFCs has been correlated with conventional measures of organic load such as Biochemical Oxygen Demand (BOD), but much remains to be established in terms of the reliability and applicability of such sensors. In this study, batch-mode and multi-stage, flow-mode MFCs were operated for over 800 days and regularly re-calibrated with synthetic wastewater containing glucose and glutamic acid (GGA). BOD
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calibration curves were obtained by normalising the current measured as a percentage of maximum current. There was little drift between recalibrations and non-linear Hill models of the combined dataset had
R
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of 88–95%, exhibiting a stable response over time and across devices. Nonetheless, factors which do affect calibration were also assessed. Increasing external resistance (from 43.5 to 5100 Ω) above the internal resistance determined by polarisation curve decreased the calibration upper limit from 240 to 30 mg/l O
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BOD
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. Furthermore, more fermentable carbon sources increased the detection range, as tested with samples of real wastewater and synthetic media containing GGA, glucose-only and glutamic acid-only. Biofilm acclimatisation therefore did not account for differences between aerobic oxygen demand determinations and anaerobic MFC responses; these are likely attributable to competitive processes such as fermentation. This further highlights the potential for MFCs as real-time sensors for organic load monitoring and process control in addition to BOD-compliant measurement systems.
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