Mathematical Models for Adsorption Capacity and Percent Removal of Heavy Metals from Water Using Stat-Ease 360

Abstract

Heavy metal removal using adsorbent materials like watermelon rind, as investigated herein, will ensure a safe drinking water for consumption. For the first time, mathematical models taking A = adsorbent dosage, B = contact time and C = initial concentration as input variables were developed using Stat-Ease 360 design of experiment (DOE) tool for adsorption capacity (R1) and percent removal of heavy metals including, arsenic, cadmium, chromium, copper and lead (R2) in water, as two sole output variables. The models generated based on existing experimental observations (A, B, C) can be used to predict the responses or outputs of the adsorption process, especially looking at their respective satisfactory statistical performance parameters obtained. Several 3D surface and contour plots reveal the optimal factor combination for peak response performance for a particular metallic contaminant in the water. Optimal values for arsenic removal are 0.1g A, 120 min B, 3.12 mg/g R1 and 100% R2. Those of other metals present are as follows: 0.1g A, 60 min B, 0.17 mg/L C, 144.75 mg/g R1 and 85.78% R2 for cadmium; 0.1-1.2g A, 0

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使用 Stat-Ease 360 建立水中重金属吸附容量和去除百分比的数学模型

本文所研究的利用西瓜皮等吸附材料去除重金属的方法将确保饮用水的安全饮用。利用 Stat-Ease 360 实验设计（DOE）工具，首次建立了以 A = 吸附剂用量、B = 接触时间和 C = 初始浓度为输入变量的数学模型，将吸附容量（R1）和水中重金属（包括砷、镉、铬、铜和铅）的去除率（R2）作为两个唯一的输出变量。根据现有的实验观察结果（A、B、C）生成的模型可用于预测吸附过程的反应或输出，特别是看它们各自获得的令人满意的统计性能参数。一些三维表面图和等高线图揭示了针对水中特定金属污染物的峰值响应性能的最佳因子组合。砷去除的最佳值为 0.1g A、120 分钟 B、3.12 mg/g R1 和 100% R2。其他金属的最佳值如下镉的最佳去除率为 0.1g A，60 分钟 B，0.17 mg/L C，144.75 mg/g R1 和 85.78% R2；铬的最佳去除率为 0.1-1.2g A，0

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