Correlation between kinetic parameters, reactor performance, and biogas and methane potential of co-digestion and mono-digestion of active sludge and olive mill wastewater

Abstract

Abstract Anaerobic co-digestion(AcoD) of active sludge (AS) and olive mill wastewater (OMW) is becoming an increasingly recognized alternative to manage waste and generate renewable energy. A kinetic study of the performance of biochemical methane potential (BMP) and continuous stirred tank reactors (CSTR) bioreactors was conducted to identify critical parameters influencing. Substrates of 100%OMW, 100%AS, 25:75%, 75:25%, and 50:50 were utilized in the BMP and CSTR digesters. To identify the optimum mixing, BMP tests were conducted under three different operating conditions: no mixing (NM), low-continuous mixing intensity (LM) of 25 rpm, and high continuous mixing intensity (HM) of 60 rpm. CSTR with an optimum mixing regime is utilized to identify the optimum substrate. In particular, the removal efficiency of volatile solids (VSs), total chemical oxygen demand (TCOD), and the production of biogas and methane (CH4) were investigated to specify the performance of the anaerobic digestion (AD) process. The results revealed that the optimum mixing regime is LM with BMP tests. Also, the maximum performance in CSTR-ML was achieved by 75:25 AS:OMW, 0.339 Nm3/kg VS of biogas, 69.89% of CH4, and a removal efficiency of 87.12% of VS and 79.23% of TCOD. For BMP tests, the biogas and CH4 yield production kinetics were best fitted by the modified Gompertz models: mono-digestion and co-digestion 75:25 and 50:50 of AS:OMW, while the best-fit model for co-digestion 25:75 was achieved by the transfer model. The production kinetics were well described by modified Gompertz models in CSTR tests. These results point to the possibility of optimizing digester systems on a wide scale using the outputs that have been observed. Novelty statement.  This research work provides novel insights into the performance of the digester under diverse mixing conditions and varying co-substrate concentrations of AS:OMW and presents the best model to predicate the biogas and CH4 at various operation conditions.