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首页> 外文期刊>Journal of Environmental Science and Health. A, Toxic/Hazardous Substances & Environmental Engineering >Effect of coexisting ions on adsorptive removal of arsenate by Mg-Fe-(CO_3) LDH: multi-component adsorption and ANN-based multivariate modeling
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Effect of coexisting ions on adsorptive removal of arsenate by Mg-Fe-(CO_3) LDH: multi-component adsorption and ANN-based multivariate modeling

机译：共存离子对Mg-Fe-（CO_3）LDH：多组分吸附和基于AnN的多变量建模的砷酸盐的效果

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摘要

The adsorptive removal of a pollutant from water is significantly affected by the presence of coexisting ions with various concentrations. Here, we have studied adsorption of arsenate [As(V)) by calcined Mg-Fe-(CO3)-LDH in the presence of different cations (Mg2+, Na+, K+, Ca2+, and Fe3+) and anions (Co-3(2)-, Cl-, PO43-, SO42-, and NO3-) with their different concentrations to simulate the field condition. The experimental results indicated that Ca2+, Mg2+, and Fe3+ at have a synergistic effect on removal efficiency of As(V), whereas PO43- and CO32- ions have a significant antagonistic impact. Overall, the order of inhibiting effect of coexisting anions on adsorption of As(V) was arrived as NO3- Cl- SO42- CO32- PO43-. Among them, competitive adsorption of phosphate with arsenic at different initial phosphate concentrations was found to be responsive to formulate a binary adsorption system. We have also developed a modified non-competitive Langmuir and Langmuir-Freundlich models; however, the modified competitive Langmuir model was arrived to be the most adequate model for this binary system. An Artificial Neural Network based multivariate prediction model was developed, delineating the impact of coexisting ions on the adsorption system. The proposed method may appropriately demonstrate the overall system and exhibited a significantly adequate prediction model with high R-2, high F-value, and low error values.
机译：受水的吸附除去污染物受到各种浓度的共存离子的显着影响。在此，我们研究了在不同阳离子（Mg2 +，Na +，K +，Ca2 +和Fe3 +）和阴离子（CO-3（CO-3（ 2） - 具有不同浓度的Cl-，PO43-，SO42-和NO3-）模拟现场条件。实验结果表明，Ca2 +，Mg2 +和Fe3 +对As（v）的去除效率具有协同效应，而PO43-和CO 32-离子具有显着的拮抗作用。总的来说，将共存阴离子的抑制效果的顺序达到（v）的吸附量为NO 3 - ＆ cl- SO42-＆ CO32-＆ po43-。其中，发现在不同初始磷酸盐浓度下具有砷的磷酸盐的竞争吸附是响应于配制二元吸附系统的响应性。我们还开发了一个改进的非竞争力的Langmuir和Langmuir-Freundlich模型;然而，修改过的竞争LangMuir模型被归入该二进制系统最适合模型。开发了一种人工神经网络的多变量预测模型，描绘了共存离子对吸附系统的影响。该方法可以适当地展示整个系统，并具有高R-2，高f值和低误差值的显着适当的预测模型。

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