Abstract

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 (CO₃^2‒, Cl^‒, PO₄^3‒, SO₄^2‒, and NO₃^‒) with their different concentrations to simulate the field condition. The experimental results indicated that Ca²⁺, Mg²⁺_, and Fe³⁺ have a synergistic effect on removal efficiency of As(V), whereas PO₄^3‒ and CO₃^2‒ 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^–<SO₄^2–<CO₃² Costa, M. Review of Arsenic Toxicity, Speciation and Polyadenylation of Canonical Histones. Toxicol. Appl. Pharmacol. 2019, 375, 1–4. DOI: 10.1016/j.taap.2019.05.006.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]^–<PO₄³ Liem-Nguyen, V.; Sjöberg, V.; Dinh, N. P.; Huy, D. H.; Karlsson, S. Removal Mechanism of Arsenic (V) by Stainless Steel Slags Obtained from Scrap Metal Recycling. J. Environ. Chem. Eng. 2020, 8, 103833. DOI: 10.1016/j.jece.2020.103833.[Crossref], [Web of Science ®] , [Google Scholar]^–. 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 R², high F-value, and low error values.

摘要

各种浓度的共存离子的存在会显着影响从水中吸附去除污染物。在这里，我们研究了煅烧的Mg–Fe–（CO ₃）–LDH在不同阳离子（Mg 2 ⁺，Na ⁺，K ⁺，Ca ²⁺和Fe ³的存在下）对砷酸盐[As（V）]的吸附⁺）和阴离子（CO ₃ ^2-，氯^-，PO ₄ ^3-，SO ₄ ^2-和NO ₃ ^- ）与他们的不同浓度来模拟场条件。实验结果表明，Ca 2 ⁺，Mg ²⁺ _，和Fe ³⁺对的As（V）的去除效率的协同效果，而PO ₄ ^3-和CO ₃ ^2-离子具有显著拮抗影响。总体而言，抑制共存对As（V）吸附阴离子的效果的顺序乃为NO ₃ ^- CL ^- <SO ₄ ^2- <CO ₃ ² Costa，M .规范组蛋白的砷毒性，形态和聚腺苷酸综述。毒药。应用 药理学。2019，375，1 - 4。DOI：10.1016 / j.taap.2019.05.006。[Crossref]，[PubMed]，[Web of Science®]，[  Google Scholar] ^–<PO₄ ³ Liem-Nguyen，V .；Sjöberg，V .；Dinh，NP；休，DH；Karlsson，S .废金属回收获得的不锈钢渣去除砷（V）的机理。J.环境。化学 。 2020，8，103833。DOI：10.1016 / j.jece.2020.103833。[Crossref]，[Web of Science®]， [Google Scholar] ^–。其中，发现在不同的初始磷酸盐浓度下，砷对磷酸盐的竞争性吸附对形成二元吸附体系具有响应性。我们还开发了改进的非竞争性Langmuir和Langmuir–Freundlich模型；然而，经过修改的竞争性朗缪尔模型已被认为是该二元系统最合适的模型。建立了基于人工神经网络的多元预测模型，描述了共存离子对吸附系统的影响。所提出的方法可以适当地演示整个系统，并展现出具有足够高的R ²，较高的F值和较低的误差值的充分预测模型。