Optimization of process variables for treatment of food industry effluents by electrocoagulation

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引用次数: 4

Abstract

The present study investigates the process optimization for treatment of potato processing industry wastewater by electrocoagulation. Performance of treatability was evaluated by achieved chemical oxygen demand (COD) removal efficiencies. Response Surface Methodology was applied to determine individual and interactive impacts of the selected operation variables (pH, conductivity, current density and duration period) on COD removal. Optimization studies were also performed for energy consumption costs which still remain as the major drawback of the electrocoagulation applications. Interactions between dependent and independent process variables were interpreted by the relevant surface plots. Sufficient correlation coefficients were obtained for the predictive regression models of the optimization. Results of the ANOVA tests showed that both of the models are statistically significant. Impacts of the process parameters on response values have been evaluated numerically by Pareto analysis. Furthermore, validation studies were conducted to confirm the accuracy of the model developed for prediction of COD removal efficiencies.
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电凝法处理食品工业废水工艺变量的优化
研究了电絮凝法处理马铃薯加工废水的工艺优化。通过化学需氧量(COD)去除率来评价处理性能。响应面法用于确定所选操作变量(pH、电导率、电流密度和持续时间)对COD去除率的单独和交互影响。优化研究还进行了能源消耗成本,这仍然是电絮凝应用的主要缺点。相关的表面图解释了依赖和独立过程变量之间的相互作用。得到了充分的相关系数,建立了优化的预测回归模型。方差分析的结果表明,这两个模型都具有统计学意义。通过Pareto分析,数值计算了工艺参数对响应值的影响。此外,还进行了验证研究,以确认用于预测COD去除效率的模型的准确性。
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