బయోప్రాసెసింగ్ & బయోటెక్నిక్స్ జర్నల్

Wastewater treatment has traditionally been an energy intensive process, consuming between 950 and 2850 kJ/m³ of wastewater treated. By one account, wastewater contains 9.3 times more energy than is used to treat an equivalent volume, thus creating the desire to harness this energy through the use of a Microbial Fuel Cell (MFC). MFCs oxidize organic substrates, allowing simultaneous wastewater treatment and electricity generation. Previous research has primarily focused on the development of MFCs for electricity generation, mainly at the small, laboratory scale. Herein, an industrial-scale MFC process is proposed for the treatment of wastewater from a microbrewery based on a previously published model describing MFC operation. Through optimization and scale-out, a two chamber MFC process is developed for the treatment of 84 L/hr of wastewater with an inlet Chemical Oxygen Demand (COD) of 3000 mg/L. An overall COD conversion of 91.9% is achieved allowing effluent to be discharged directly down a municipal sewer. Electricity generation is 26.4 kWh, 107% of the operational requirement. With a payback period of 5 years, this work shows that there is potential for the implementation of MFC technology in the food and beverage industry.

A simple mathematical model, taking into account substrate limitation and inhibition by both the product ethanol and the substrate, was proposed and used to interpret experimental data from a batch alcohol fermentation process, conducted at two different sets of initial concentrations of sugar and cells. A detailed sequence of mathematical model derivation and parameter estimation is presented. The temporal profiles of sugar, cell and ethanol concentrations in the culture medium were modeled by a set of ordinary differential equations, which were integrated numerically by the 4^th-order Runge-Kutta-Gill method. The model was validated by real laboratory fermentations and the accuracy of the model is acceptable. The agreement between the simulation and experimental results demonstrates that the model is sufficiently reliable for prediction of the dynamic behavior of the bioprocess. A study of process optimization by means of an approximate model, used to describe the dynamics of sugar consumption, revealed the need to employ a multi-objective approach, to maximize simultaneously the ethanol productivity, ethanol concentration and the conversion of sugars.