Abstract
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 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 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.
Highlights
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 (Quevauviller et al, 2007)
Substrates Concentration TOC, chemical oxidation demand (COD) and volatile fatty acid (VFA) were measured at different positions in the tubular reactor to determine substrate utilization through the Microbial Fuel Cells (MFCs) stages (Figure 2, Table S1)
4-Nitrophenol Detection Using Multi-Stage MFCs the main VFAs detected with concentrations of 82.6 and 45.3 mg/L respectively in MFC1 to 178.5 and 102.8 mg/L in MFC4
Summary
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 (Quevauviller et al, 2007). Online toxicity analyzers predominantly measure indirect proxies for the treatment microbial communities [e.g., oxygen uptake rate (OUR) or methane production] and it can take several hours before results are generated. This is too slow to allow operators to respond to a shock loading (Kong et al, 1996; Xiao et al, 2015). Microbial fuel cells (MFCs) which generate electricity from organic matter oxidation by microorganisms have shown potential as online toxicity sensors (Abrevaya et al, 2015; Xiao et al, 2015; Yu et al, 2017; Chouler et al, 2018; Adekunle et al, 2019). The goal of this study was to explore the potential of using multistage MFCs as a biosensor for enhanced, online detection of toxic compounds in wastewater
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