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Experimental design and response surface modeling for optimization of fluoroquinolone removal from aqueous solution by NaOH-modified rice husk

机译:优化NaOH改性稻壳去除水溶液中氟喹诺酮的实验设计和响应面建模。

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The aim of this study is to obtain optimal adsorption conditions for enrofloxacin (ENR) as a fluoroquinolone antibiotic onto NaOH-modified rice husk using response surface methodology (RSM). On the basis of a four variable Box-Behnken design (BBD), RSM was used to determine the effect of adsorbent dose (0.25, 0.5, and 0.75gL(-1)), pH (5, 7, and 9), ENR initial concentration (25, 75, and 125mgL(-1)), and temperature (15, 30, and 45 degrees C) on adsorption efficiency. By applying the quadratic regression analysis, among the main parameters, the removal efficiency was significantly affected by all the four variables. The results showed that the predicted values for ENR adsorption were close to the experimental values and were in good agreement. In addition, the R-2 value (R-2=0.9705) indicates that the regression is able to give a good predict of response for the adsorption process in the studied range. From the BBD predictions, the optimal conditions for 92.25% ENR removal were found to be 0.69gL(-1) of adsorbent dose, pH 5.11, and initial concentration of ENR 25.02mgL(-1), at temperature 36.43 degrees C.
机译:这项研究的目的是使用响应表面方法(RSM)获得作为氟喹诺酮抗生素的恩诺沙星(ENR)在NaOH改性稻壳上的最佳吸附条件。基于四变量Box-Behnken设计(BBD),RSM用于确定吸附剂量(0.25、0.5和0.75gL(-1)),pH(5、7和9),ENR的影响初始浓度(25、75和125mgL(-1))和温度(15、30和45摄氏度)对吸附效率的影响。通过应用二次回归分析,在主要参数中,去除效率受到所有四个变量的显着影响。结果表明,ENR吸附的预测值与实验值接近,吻合良好。此外,R-2值(R-2 = 0.9705)表示回归分析能够很好地预测研究范围内吸附过程的响应。根据BBD预测,发现在温度36.43摄氏度下,去除92.25%ENR的最佳条件是0.69gL(-1)的吸附剂剂量,pH 5.11和ENR的初始浓度25.02mgL(-1)。

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