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Application of the central composite design and response surface methodology to the advanced treatment of olive oil processing wastewater using Fenton's peroxidation

机译:中心复合设计和响应面法在Fenton过氧化法深度处理橄榄油加工废水中的应用

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The central composite design (CCD) technique was used to study the effect of the Fenton's peroxidation on the removal of organic pollutants from olive oil mill wastewater (OMW). The ratio of hydrogen peroxide-to-Fe(Ⅱ) (x_1) was between 1.67 and 8.33. Fe(Ⅱ) concentration was constant at 0.03 M while the H_2O_2 concentration was set at three levels: 0.05, 0.15 and 0.25 M. Based on the molarity ratio, the selected ratio were in the low range of Fe(Ⅱ)-to-H_2O_2 ratio (1). While based on the wt/wt ratio, the tested Fe(Ⅱ)-to-H_2O_2 ratios were in the range of ≤ 1:5. pH (x_2) was between 3 and 5. The concentration of OMW (x_3) was varied between 40 and 100%. The influence of these three independent variables on the four dependent variables, i.e. COD, total phenolics (TP), color and aromatocity removal was evaluated using a second-order polynomial multiple regression model. Analysis of variance (ANOVA) showed a high coefficient of determination (R~2) value of 0.902-0.998, thus ensuring a satisfactory adjustment of the second-order regression model with the experimental data. H_2O_2-to-Fe(Ⅱ) ratio had significant effect on all the four dependent variables. The positive sign for the regression coefficient of this regressor variable indicated that the level of the pollutant removal increased with the increased levels of factor x_1 from 1.67 to 8.33 and this effect was the most pronounced for TP removal. pH had also significant effect on the pollutant removal and the effect was the most noticeable for TP reduction. The negative coefficient of this variable (pH) indicated that level of the pollutant removal decreased as the pH increased from 3 to 5. The negative coefficient of the interaction between variable x_1 and x_2 indicated that a simultaneous increase in H_2O_2-to-Fe(Ⅱ) ratio with decrease in the pH of the reaction led to an increase in the COD, TP and color removal. Quadratic models were predicted for the response variable, i.e. pollutant removal, and the maximum model-predicted removals were 56, 100, 33 and 32% for COD, TP, color and aromatocity, respectively. Optimum conditions for this wastewater treatment was obtained based on the performance of the Fenton's peroxidation in the experiment where the H_2O_2-to-Fe(Ⅱ) ratio was at its high level (8.33) and the pH and OMW concentration were 4 and 70%, respectively.
机译:中央复合设计(CCD)技术用于研究Fenton过氧化对从橄榄油厂废水(OMW)中去除有机污染物的影响。过氧化氢与Fe(Ⅱ)的比(x_1)在1.67和8.33之间。 Fe(Ⅱ)的浓度恒定为0.03 M,而H_2O_2的浓度设置为0.05、0.15和0.25 M这三个水平。基于摩尔比,选择的比率在Fe(Ⅱ)与H_2O_2的较低范围内比率( 1)。基于重量/重量比,测试的Fe(Ⅱ)与H_2O_2的比例在≤1:5的范围内。 pH(x_2)在3-5之间。OMW(x_3)的浓度在40%至100%之间变化。使用二阶多项式多元回归模型评估了这三个自变量对四个因变量(即COD,总酚(TP),颜色和香气去除)的影响。方差分析(ANOVA)显示出0.902-0.998的高确定系数(R〜2)值,从而确保用实验数据对二阶回归模型进行满意的调整。 H_2O_2与Fe(Ⅱ)之比对所有四个因变量都有显着影响。该回归变量的回归系数的正号表示,污染物去除水平随因子x_1的水平从1.67增加到8.33而增加,而这种效果对于TP去除最为明显。 pH值对污染物的去除也有显着影响,并且这种影响对于TP降低最为明显。 pH的负系数表示pH值从3增加到5时,污染物去除水平降低。变量x_1和x_2相互作用的负系数表示H_2O_2-Fe(Ⅱ)同时增加。比率随反应pH值的降低而导致COD,TP和颜色去除的增加。预测了响应变量(即污染物去除)的二次模型,并且模型预测的最大去除量分别为COD,TP,颜色和芳香度的56%,100%,33%和32%。在H_2O_2与Fe(Ⅱ)之比处于高水平(8.33),pH和OMW浓度分别为4和70%的实验中,根据芬顿过氧化的性能获得了该废水处理的最佳条件。分别。

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