A generalized whole-cell model for wastewater-fed microbial fuel cells

A comprehensive mathematical modeling of wastewater-fed microbial fuel cells (MFC) demands an in-depth process understanding of the main electrical and bioelectrochemical interactions at both electrodes. In this study, a novel holistic simulation approach using a low-parameterized model was applied to predict pollutant transport, conversion, and electrical processes of mixed-culture single-chamber MFCs. The proposed whole-cell model couples the combined bioelectrochemical-electrical model with the well-established Activated Sludge Model No.1 (ASM1) and specific equations from ASM2. The cathodic gas-liquid mass transfer of oxygen and free ammonia nitrogen was described in terms of a diffusion film model, while the diminishing diffusivity due to salt deposits was considered via a fouling decline kinetic model. The predictive capacity of the model was validated using experimental data of three continuous-flow single-chamber MFCs operated with municipal wastewater for 150 days. Electrochemical parameters were estimated in real-time by pulse-width modulated connection of the external electrical load resistance. Following a sensitivity analysis, the most relevant model parameters were optimized through the Monte-Carlo Markov-Chain method using the adaptive Metropolis algorithm. All other parameters were adopted from benchmark simulation studies. The simulated relative contributions of aerobic carbon oxidation, denitrification, electrogenesis, and methanogenesis to the total COD removal rate were 21-22%, 44-45%, 21-25%, and 9-14%. Overall, the presented whole-cell model is able to successfully predict the evolution of electricity generation, methane production, and effluent concentrations (soluble COD and total ammonia nitrogen) under different hydraulic conditions and organic loading rates.

Automated summary

This study successfully predicted the performance of wastewater-fed microbial fuel cells using comprehensive mathematical modeling and validation with experimental data, including the evolution of electricity generation, methane production, and effluent concentrations under different conditions.