大气颗粒物重金属元素消解方法的响应面优化
Optimization of Digestion Parameters for Heavy Metal in Atmospheric Particles Using Response Surface Methodology
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摘要: 运用Plackett-Burman法确定了影响滤膜颗粒物中重金属元素提取效果的显著因素,利用Box-Behnken试验设计法得出回归模型,通过Minitab软件进行响应面分析得到最优消解条件:HNO3-HF体积比3.6:1、恒温温度184.8℃、恒温时间13.8min。标准滤膜GBW(E)080212中元素Pb最大的预测浓度为63.3μg/L,验证试验测定值与回归方程预测值的相对误差为0.2%,与标准滤膜真实值的相对误差为-0.3%。预测值与验证试验平均值基本一致,模型能较好的反应消解的实际情况。
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关键词:
- 滤膜 /
- 消解 /
- 重金属 /
- 响应面分析 /
- Plackett-Burman设计法
Abstract: Plackett-Burman method was applied to determine the significant factors affecting the extraction efficiency of heavy metals in filter particulates, meanwhile, regression model was obtained by using Box-Behnken experimental design method. Response surface methodology was carried out by Minitab software to obtain the optimal digestion conditions:HNO3-HF volume ratio of 3.6:1, constant temperature of 184.8℃, with 13.8 min. The maximum predicted concentration of element Pb in standard filter membrane GBW (E) 080212 was 63.3 μg/L. The relative error between verification test value and predicted value of regression equation was 0.2%, the relative error between the verification test value and the true values of standard filter membrane was-0.3%. The predicted value was basically consistent with the average value of the validation test, and the model could properly reflect the actual situation of the digestion.-
Key words:
- Filter /
- Digestion /
- Heavy Metal /
- Response Surface Methodology /
- Plackett-Burman Method
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