More than 80% of wastewater from industries is discharged into receiving water bodies without any pollution control. Microbial fuel cells (MFCs) are a promising technology for the simultaneous treatment of wastewater and electricity production. With regard to azo-dye containing wastewater (e.g., from textile manufacturing), the dye may be fed via the anode chamber containing electrochemically active bacteria or via the cathode chamber containing laccase enzyme as catalyst for oxygen reduction. This study investigated which of the two approaches is the best with regard to rate of decolourization of the dye (Acid orange 7), COD reduction and electricity production. The power density was higher for the MFC_{Dye Cathode} (50 ± 4 mW m⁻², COD reduction 80.4 ± 1.2%) compared with 42.5 ± 2.6 mW m⁻² (COD reduction 69 ± 2%) for MFC_{Dye Anode}. The time required for decolourization was longer in the MFC_{Dye Anode} (Shewanella oneidensis) where only 20% decolourization was obtained after 24 h compared to 80% for the MFC_{Dye Cathode}. The anodic dye degradation products were unstable when exposed to air resulting in regaining of color. In case of degradation by laccase in the cathode chamber, the decolourization products were stable and simpler in chemical structure as determined by GC-MS. This work suggests that feeding azo dyes in cathode chambers of MFCs containing laccase is a better way of treating the dyes compared to the commonly used approach of feeding the dye in the anode chamber provided enzyme activity can be sustained.

Traditional wastewater treatment methods have become aged and inefficient, meaning alternative methods are essential to protect the environment and ensure water and energy security worldwide. The use of microbial electrolysis cells (MEC) for wastewater treatment provides an innovative alternative, working towards circular wastewater treatment for energy production. This study evaluates the factors hindering industrial adoption of this technology and proposes the next steps for further research and development. Existing pilot-scale investigations are studied to critically assess the main limitations, focusing on the electrode material, feedstock, system design and inoculation and what steps need to be taken for industrial adoption of the technology. It was found that high strength influents lead to an increase in energy production, improving economic viability; however, large variations in waste streams indicated that a homogenous solution to wastewater treatment is unlikely with changes to the MEC system specific to different waste streams. The current capital cost of implementing MECs is high and reducing the cost of the electrodes should be a priority. Previous pilot-scale studies have predominantly used carbon-based materials. Significant reductions in relative performance are observed when electrodes increase in size. Inoculation time was found to be a significant barrier to quick operational performance. Economic analysis of the technology indicated that MECs offer an attractive option for wastewater treatment, namely greater energy production and improved treatment efficiency. However, a significant reduction in capital cost is necessary to make this economically viable. MEC based systems should offer improvements in system reliability, reduced downtime, improved treatment rates and improved energy return. Discussion of the merits of H₂ or CH₄ production indicates that an initial focus on methane production could provide a stepping-stone in the adoption of this technology while the hydrogen market matures.

This study explores the application of various machine learning (ML) models for the real-time prediction of the FOS/TAC ratio in microbial electrolysis cell anaerobic digestion (MEC-AD) systems using data collected during a 160-day trial treating brewery wastewater. This study investigated models including decision trees, XGBoost, support vector regression, a variant of support vector machine (SVM), and artificial neural networks (ANNs) for their effectiveness in the soft sensing of system stability. The ANNs demonstrated superior performance, achieving an explained variance of 0.77, and were further evaluated through an out-of-fold ensemble approach to assess the selected model’s performance across the complete dataset. This work underscores the critical role of ML in enhancing the operational efficiency and stability of bio-electrochemical systems (BES), contributing significantly to cost-effective environmental management. The findings suggest that ML not only aids in maintaining the health of microbial communities, which is essential for biogas production, but also helps to reduce the risks associated with system instability.

A pilot-scale (4000 L) continuous flow electromethanogenic reactor (EMR), also known as a microbial electrochemical cell coupled with an anaerobic digester (MEC-AD), treating brewery wastewater was designed and installed at Hepworth’s Brewery, UK. This investigation presents a 4-fold increase in size compared to the next largest pilot-scale MEC-AD system presented in the literature, providing findings to inform the operation of a 52,000 L MEC-AD system (currently under construction). Housed in a 20 ft shipping container, the pilot system features four 1000 L reaction vessels arranged in series, each with a working volume of 900 L. Each reaction vessel contained 8 electrode modules. The system was tested over varying organic loading rates (OLRs), achieved through systematic reductions in hydraulic retention time (HRT). HRTs between 24 and 1.8 days were investigated to align with commercial viability targets. OLRs were observed from 0.4 to 7.5 kgCOD/m³/d. A maximum stable OLR of 6.75 kgCOD/m³/d at a HRT of 2.3 days was observed while maintaining COD removal of 65 and 88% over the first two vessels. This pilot demonstrated commercially viable performance of an EMR at a brewery, resulting in the purchase of the technology at commercial scale (52,000 L) to form part of a wastewater treatment system.

The aim of the present work was to increase bacterial adhesion on anode via inducing membrane modifications to enhance textile wastewater treatment in Microbial Fuel Cell (MFC). Real textile wastewater was used in mediator-less MFCs for bacterial enrichment. The enriched bacteria were pre-treated by exposure to 1 KGy gamma radiation and were tested in MFC setup. Bacterial cell membrane permeability and cell membrane charges were measured using noninvasive dielectric spectroscopy measurements. The results show that pre-treatment using gamma radiation resulted in biofilm formation and increased cell permeability and exopolysaccharide production; this was reflected in both MFC performance (average voltage 554.67 mV) and decolorization (96.42%) as compared to 392.77 mV and 60.76% decolorization for non-treated cells. At the end of MFC operation, cytotoxicity test was performed for treated wastewater using a dermal cell line, the results obtained show a decrease in toxicity from 24.8 to 0 (v/v%) when cells were exposed to gamma radiation. Fourier-transform infrared (FTIR) spectroscopy showed an increase in exopolysaccharides in bacterial consortium exposed to increasing doses of gamma radiation suggesting that gamma radiation increased exopolysaccharide production, providing transient media for electron transfer and contributing to accelerating MFC performance. Modification of bacterial membrane prior to MFC operation can be considered highly effective as a pre-treatment tool that accelerates MFC performance.