Kinetic Modeling for Bioaugmented Anaerobic Digestion of the Organic Fraction of Municipal Solid Waste by Using Fe3O4 Nanoparticles

Abstract

Kinetic modeling helps in the process designing, reactor dimensioning, and up scaling of any system. A kinetic study of batch anaerobic digestion (AD) of food waste (FW), which is the organic fraction of municipal solid waste was conducted. Iron oxide (Fe3O4) nanoparticles (NPs) were added and their impact on methane generation and volatile solids (VS) removal was modeled through the existing kinetic models. AD of FW was carried out at a mesophilic temperature (37 ± 0.5 °C) for 60 days. Four different concentrations of Fe3O4 NPs, at 50, 75, 100, 125 mg L−1, were added, and the performance was evaluated by comparing it with the control (without NPs) and by kinetic modeling. The rate of reactions (k) was evaluated by using pseudo-first-order reaction kinetics by considering the initial and final data. The modified Gompertz model, Logistic, and Transference functions were fitted to the cumulative methane generation. The best fits of models were statistically determined by estimating the coefficient of correlation (R2), standard deviation residual (SDR) and least significant difference tools. The k values for all concentrations and the control were determined to be 6.1 × 10−3, 1.4 × 10−2, 1.8 × 10−2, 9.6 × 10−3, and 7.1 × 10−3 (day−1), respectively. The results of the study indicated that the modified Gompertz model produced a perfect fit with highiest R2 and the smallest value of SDR. Furthermore, more than 50% of VS reduction was achieved with the addition of 75 mg L−1 Fe3O4 NPs. The modified Gompertz model predicted the experimental results with a higher R2 and a lower SDR value at all concentrations of NPs.