D. Sivakumar
Abstract
Taguchi L9 orthogonal array was implemented to select optimum values of process parameters and to attain the maximum removal of pollutants and power generation from dairy industry wastewater using double chambered salt bridge microbial fuel cell. The maximum chemical oxygen demand reduction, current, ...
Read More
Taguchi L9 orthogonal array was implemented to select optimum values of process parameters and to attain the maximum removal of pollutants and power generation from dairy industry wastewater using double chambered salt bridge microbial fuel cell. The maximum chemical oxygen demand reduction, current, voltage, power, current density and power density in double chambered salt bridge microbial fuel cell from dairy industry wastewater was found to be 86.30 %, 16.10 mA, 886.34 mV, 14.27 mW, 1219.69 mA/m2 and 1081.06 mW/m2 respectively for the optimum value of 1M NaCl concentration, 10 % agar concentration and 0.10 m salt bridge length. Double chambered salt bridge microbial fuel cell was not only removed chemical oxygen demand and produced power, but it also removed other pollutants at the maximum level against the best optimum value of process parameters from the dairy industry wastewater. The proposed regression model was used to select the right combination of process parameters for obtaining a maximum reduction of pollutants and simultaneous power production from the dairy industry wastewater.
B. Te; B. Wichitsathian; C. Yossapol; W. Wonglertarak
Abstract
Mesoporous pellet adsorbent developed from mixing at an appropriate ratio of natural clay, iron oxide, iron powder, and rice bran was used to investigate the optimization process of batch adsorption parameters for treating aqueous solution coexisting with arsenate and arsenite. Central composite design ...
Read More
Mesoporous pellet adsorbent developed from mixing at an appropriate ratio of natural clay, iron oxide, iron powder, and rice bran was used to investigate the optimization process of batch adsorption parameters for treating aqueous solution coexisting with arsenate and arsenite. Central composite design under response surface methodology was applied for optimizing and observing both individual and interactive effects of four main influential adsorption factors such as contact time (24-72 h), initial solution pH (3-11), adsorbent dosage (0-20 g/L) and initial adsorbate concentration (0.25-4.25 mg/L). Analysis of variance suggested that experimental data were better fitted by the quadratic model with the values of regression coefficient and adjusted regression coefficient higher than 95%. The model accuracy was supported by the correlation plot of actual and predicted adsorption efficiency data and the residual plots. The Pareto analysis suggested that initial solution pH, initial adsorbate concentration, and adsorbent dosage had greater cumulative effects on the removal system by contributing the percentage effect of 47.69%, 37.07% and 14.26%, respectively. The optimum values of contact time, initial solution pH, adsorbent dosage and initial adsorbate concentration were 52 h, 7, 10 g/L and 0.5 mg/L, respectively. The adsorption efficiency of coexisting arsenate and arsenite solution onto the new developed adsorbent was over 99% under the optimized experimental condition.