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使用基于形态的模型量化pH值和表面负载对纳米活性氧化铝吸附砷的影响。

Quantifying effects of pH and surface loading on arsenic adsorption on NanoActive alumina using a speciation-based model.

作者信息

Guan Xiao-Hong, Su Tingzhi, Wang Jianmin

机构信息

School of Municipal and Environmental Engineering, Harbin Institute of Technology, Harbin, PR China.

出版信息

J Hazard Mater. 2009 Jul 15;166(1):39-45. doi: 10.1016/j.jhazmat.2008.10.121. Epub 2008 Nov 7.

Abstract

Arsenic (As) poses a significant water quality problem and challenge for the environmental engineers and scientists throughout the world. Batch tests were carried out in this study to investigate the adsorption of As(V) on NanoActive alumina. The arsenate adsorption envelopes on NanoActive alumina exhibited broad adsorption maxima when the initial As(V) loading was less than a 50 mg g(-1) sorbent. As the initial As(V) loading increased to 50 mg g(-1) sorbent, a distinct adsorption maximum was observed at pH 3.2-4.6. FTIR spectra revealed that only monodentate complexes were formed upon the adsorption of arsenate on NanoActive alumina over the entire pH range and arsenic loading conditions examined in this study. A speciation-based adsorption model was developed to describe arsenate adsorption on NanoActive alumina and it could simulate arsenate adsorption very well in a broad pH range of 1-10, and a wide arsenic loading range of 0.5-50 mg g(-1) adsorbent. Only four adjustable parameters, including three adsorption constants, were included in this model. This model offers a substantial improvement over existing models in accuracy and simplification in quantifying pH and surface loading effects on arsenic adsorption.

摘要

砷(As)给全球环境工程师和科学家带来了重大的水质问题与挑战。本研究开展了批次试验,以探究纳米活性氧化铝对五价砷(As(V))的吸附情况。当初始As(V)负载量低于50 mg g(-1)吸附剂时,纳米活性氧化铝上的砷酸盐吸附包络线呈现出宽泛的吸附最大值。随着初始As(V)负载量增加至50 mg g(-1)吸附剂,在pH 3.2 - 4.6时观察到明显的吸附最大值。傅里叶变换红外光谱(FTIR)表明,在本研究考察的整个pH范围和砷负载条件下,砷酸盐吸附到纳米活性氧化铝上仅形成单齿络合物。开发了一种基于形态的吸附模型来描述纳米活性氧化铝对砷酸盐的吸附,该模型能在1 - 10的宽泛pH范围以及0.5 - 50 mg g(-1)吸附剂的宽广砷负载范围内很好地模拟砷酸盐吸附。该模型仅包含四个可调参数,其中包括三个吸附常数。在量化pH和表面负载对砷吸附的影响方面,此模型在准确性和简化程度上比现有模型有显著改进。

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