3.8 Article

Adsorption of Cu(II), Ni(II), Pb(II) and Cd(II) from Ternary Mixtures: Modelling Competitive Breakthrough Curves and Assessment of Sensitivity

期刊

出版社

SPRINGER INTERNATIONAL PUBLISHING AG
DOI: 10.1007/s40710-017-0262-7

关键词

Homogeneous surface diffusion model; Metals; Overshoot; Grape stalks; Packed column; Sensitivity analysis

资金

  1. Ministerio de Economia y Competitividad, Spain [CTM2015-68859-C2-1-R]

向作者/读者索取更多资源

This study describes the competitive sorption of Cu(II), Ni(II), Pb(II) and Cd(II) onto grape stalks wastes (GS) in ternary mixtures in a continuous bed up-flow system. The characteristic breakthrough profile was observed for just one of the metals while the other two suffered overshoots. The elution profile showed that (i) lead is not overshot in any mixture, (ii) copper overshoots when lead occurs in the ternary mixture, and (iii) cadmium and nickel exhibit intense overshoots when either lead or copper are present. A kinetic model based on the Homogeneous Surface Diffusion Model (HSDM) was developed to describe the sorption profile of each metal in the mixtures. To simulate the breakthrough curves, the Extended Langmuir Model (MEL) has been incorporated into the HSDM to describe the equilibrium. The values of the Langmuir affinity constant, b, were found to follow the next ranking: Pb (54.5 +/- 0.2) >> Cu (15.2 +/- 0.3) >> Cd (9.4 +/- 0.1) > Ni (8.1 +/- 0.2). These constants successfully explain the competence that leads to the observed overshoots in the mixtures. The model successfully fits metal sorption kinetics and elution profile in the mixtures. A study of the model sensitivity was carried out to know how the uncertainty in the experimental data and the model parameters affect the uncertainty in the output of the model. This analysis highlighted the relevance of good estimation of K (max) , b and eta besides the need of gathering high quality experimental data for an accurate determination of the model parameters.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

3.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据