The Key To Predict Anaerobic Processes Performance: Bioelectrochemical Sensors

Introduction and Background
The use of bioelectrochemical sensors (BESs) to monitor biological processes in engineered environmental systems has received increasing interest in recent years. The BES is an electrochemical devise, based on the electrochemical interactions of microorganisms and enzymes with the electrodes. The signal produced using this sensor is a direct result of the microbial activity within the BES. In detail, it relies on the ability of some bacteria to transfer electrons from a reduced electron donor, the substrate, to a solid electrode material called anode, which is the electron acceptor. The anode is connected, via an external electrical circuit, to the cathode, which is covered by bacteria that catalyze the reduction of an oxidized electron acceptor (Lovley, 2011). The potential benefits of using these sensors include provide early warnings of biological process upsets, detect inhibitory effects of shock loads and toxic content and monitor nutrient depletion (Grattieri et al, 2017). Anaerobic processes, especially anaerobic digestion and co-digestion systems, could benefit from the implementation of these sensors to monitor the process performance, given their high operational complexity in managing the variation in feedstock composition, complex metabolic properties and feeding strategies. However, open questions remain on the efficacy and reproducibility of BESs. Our research aims to fill knowledge gaps related to feasibility of using BESs to monitor and predict the performance of anaerobic digesters. The specific objective of this study is to investigate the potential of a BES to identify the impact of a range of simple and complex organic substrates on digester performance and biokinetics.
Material and Methods
Experimental Set-up Lab-scale batch tests were performed using digestate from an operating anaerobic digester at a water resource recovery facility in California. Each test was performed at 35°C. The digestate was collected from the full-scale digester and mixed (mixer speed ~ 300 RPM) in a 15 L batch reactor (Figure 1). After a 2-hour acclimation period, an organic feedstock (0.6 L) was added to the batch reactor. The feedstocks evaluated in this research include acetate, isovalerate and primary sludge (PS).
Probes and Data collection The BES product SENTRY, manufactured by Island Water Systems (Charlottetown, PE, Canada) was employed in this research. The SENTRY BES reports a microbial electron transfer (MET) as a surrogate for biomass activity. One SENTRY probe, a pH sensor (DPD1, Hach Company, Loveland, CO) and an ORP sensor (DRD1, Hach Company, Loveland, CO) were installed in the batch reactor. In between each batch test, all the sensors were kept in the same mixed digestate and before each batch test the sensors were cleaned with a wet cloth. The SENTRY sensor did not require any calibration or chemical cleaning. Grab samples were collected throughout the experiments to measure Volatile Fatty Acids (VFA), soluble COD, NHx-N and Ortho P.
Preliminary Results and Discussion
Figure 2 and 3 show the results of the batch tests, where at time -2h the mixed liquor aliquot is added to the reactor and at time 0 the feedstock is added to the set up. The response of the BES system to different concentrations of acetate is markedly different (Figure 2). The use of an acetate feedstock of 2,000 mg/L and 22,500 mg/L resulted in an in-situ VFA concentration of 190 mg/L (Fig.2, top panel) and 950 mg/L at the start of the experiment (t=0), respectively. In both cases, the BES sensor responds rapidly to the feedstock addition, reaching a maximum level of metabolic activity (maximum MET value) within 1 hour. The complete depletion of acetate can be identified because the sensor response returns to steady state condition and the VFA concentration in the reactor returns to the baseline (i.e., pre-feedstock addition) level. Figure 3 shows the response of the sensor to three different sources of feedstock: Sodium Acetate (top), Isovaleric Acid (middle) and Primary Sludge (bottom). For the two complex feedstocks (isovaleric acid and primary sludge), the BES sensor response to the feedstock addition was slower and the metabolic activity (MET) continued to slowly increase while the substrate was converted to acetate (increase in VFA). Once the complex substrate was converted to acetate, the readily biodegradable matter was then depleted (decrease in VFA concentration) and the sensor response decreased until returning to the baseline level. Figure 4 shows, for all the experiments, the MET increase rate in the first 1 hour from the feedstock addition and the VFA decrease/increase rate in the first 2 hours. Initial VFA uptake rates increased proportionally with higher initial VFA concentrations. However, at high initial concentrations – the initial VFA degradation rates appear to have reached a maximum (Figure 4, top left), suggesting a Monod kinetics model. The change in the initial MET signal shows a similar trend (Figure 4, top right): at higher substrate concentrations corresponds a higher MET increased rate until it reaches a maximum response. Overall the BES response shows a strong correlation to the initial VFA uptake rates (Figure 4, bottom panel), although this correlation does not reflect the impact of the initial VFA concentration on the change in the BES signal. Preliminary results from this research suggest that the signal from a BES is influenced by the initial substrate concentration and substrate biodegradability. Our current experiments are focused on evaluating the reproducibility of these results using additional feedstocks and evaluating the reproducibility of BES results using digestate biomass from other WRRFs. These results will be included as part of the full paper submission and presentation. Collectively, our study suggests that a BES can be used to monitor anaerobic digesters and detect upset events, since the sensor's bacteria are a good reflection of the digester's biomass composition and behaviour. Furthermore, the BES signal can be employed as part of a process control strategy to optimize digester feeding and mitigate overloading the digesters.