Modeling and Multiresponse Optimization for Anaerobic Codigestion of Oil Refinery Wastewater and Chicken Manure by Using Artificial Neural Network and the Taguchi Method.

To study the optimum process conditions for pretreatments and anaerobic codigestion of oil refinery wastewater (ORWW) with chicken manure, L9 (34) Taguchi's orthogonal array was applied. The biogas production (BGP), biomethane content (BMP), and chemical oxygen demand solubilization (CODS) in stabilization rate were evaluated as the process outputs. The optimum conditions were obtained by using Design Expert software (Version 7.0.0). The results indicated that the optimum conditions could be achieved with 44% ORWW, 36°C temperature, 30 min sonication, and 6% TS in the digester. The optimum BGP, BMP, and CODS removal rates by using the optimum conditions were 294.76 mL/gVS, 151.95 mL/gVS, and 70.22%, respectively, as concluded by the experimental results. In addition, the artificial neural network (ANN) technique was implemented to develop an ANN model for predicting BGP yield and BMP content. The Levenberg-Marquardt algorithm was utilized to train ANN, and the architecture of 9-19-2 for the ANN model was obtained.

Alkaline Pretreatment of Sugarcane Bagasse and Filter Mud Codigested to Improve Biomethane Production.

To enhance the codigestion of degradation and improve biomethane production potential, sugarcane bagasse and filter mud were pretreated by sodium hydroxide NaOH 1 N at 100°C for 15, 30, and 45 minutes, respectively. Biomethane generation from 1-liter batch reactor was studied at mesophilic temperature (37 ± 1)°C, solid concentrations of 6%, and five levels of mixing proportion with and without pretreatment. The results demonstrate that codigestion of filter mud with bagasse produces more biomethane than fermentation of filter mud as single substrate; even codigested substrate composition presented a better balance of nutrients (C/N ratio of 24.70) when codigestion ratio between filter mud and bagasse was 25 : 75 in comparison to filter mud as single substrate (C/N ratio 9.68). All the pretreatments tested led to solubilization of the organic matter, with a maximum lignin reduction of 86.27% and cumulative yield of biomethane (195.8 mL·gVS-1, digestion of pretreated bagasse as single substrate) obtained after 45 minutes of cooking by NaOH 1 N at 100°C. Under this pretreatment condition, significant increase in cumulative methane yield was observed (126.2 mL·gVS-1) at codigestion ratio of 25 : 75 between filter mud and bagasse by increase of 81.20% from untreated composition.

Methane enhancement through oxidative cleavage and alkali solubilization pre-treatments for corn stover with anaerobic activated sludge.

In the present study, thermo-chemical pre-treatment was adopted to evaluate methane production potential from corn stover by co-digesting it with anaerobic activated sludge. Three chemicals H2O2, Ca(OH)2 and NaOH were selected with two levels of concentration. All thermo-chemical pre-treatments were found significant (P<0.05) to enhance lignocellulosic digestibility and methane production. The results indicated that the methane yield by H2O2-1, H2O2-2, and NaOH-2 treated corn stover were 293.52, 310.50 and 279.42ml/g.VS which were 57.18%, 66.27% and 49.63% higher than the untreated corn stover respectively. In the previous studies pre-treatment time was reported in days but our method had reduced it to about one hour. H2O2-2 and NaOH-2 treatments remained prominent to increase lignocellulosic degradation vigorously up to 45% and 42% respectively. Process biochemistry during the anaerobic digestion process was taken into consideration to optimize the most feasible thermo-chemical pre-treatment for corn stover.