ena-STUDY-NEWCASTLE UNIVERSITY, UK-08-10-2019-22:02:35:712-13
Detection of Toxic Compounds using Multi-stage Microbial Fuel Cells
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 linear correlation was observed between the 4-NP concentrations and the current peak 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 current following a toxic event comprising 500 mg/L 4-NP after 4 hours. 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 recalibration 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.
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 linear correlation was observed between the 4-NP concentrations and the current peak 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 current following a toxic event comprising 500 mg/L 4-NP after 4 hours. 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 recalibration 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.