利用铁基金属有机骨架有效去除受污染地下水中的砷

Porraket Dechdacho, Saige Howard, Ronald L. Hershey, Rishi Parashar, Lazaro J. Perez
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引用次数: 0

摘要

本研究探讨了铁基金属有机骨架(MOF)材料fe -苯-1,3,5-三羧酸铁(Fe-BTC)去除水中砷的潜力。我们进行了批式和柱式实验,以评估不同质量剂量的MOF和pH范围对砷吸附的影响。我们的批量实验表明,Fe-BTC MOF的质量越大,吸附能力越强。此外,在所分析的pH值范围内,Fe-BTC表现出稳定的砷吸附能力,表明pH条件对其性能没有显著影响。在柱式实验中,我们使用经过堆肥处理的花岗岩材料,比较了MOF存在和不存在时的砷浓度突破曲线,以评估其去除砷的效率。在没有MOF的情况下,我们观察到砷快速到达,随后浓度缓慢增加,表明堆肥引起的异常运输动力学。MOF的加入延长了砷的到达时间,并稳定了较低的浓度,表明砷的有效吸附。当Fe-BTC MOF添加到土壤材料中时,其对砷的吸附量比不添加时增加了6倍。我们采用分数阶平流-色散方程模型来表征和预测柱实验中的物理和化学动力学。该输运模型通过捕获非菲克式输运和吸附化学动力学,准确地匹配了砷在柱实验中的突破曲线。该模型表明,由于流动不均一性,堆肥对砷的吸附影响不显著,而MOF的添加增加了砷的吸附和非菲克动力学。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effective removal of arsenic from contaminated groundwater using an iron-based metal organic framework
This study investigates the potential of an iron-based metal–organic framework (MOF) material, Fe-benzene-1,3,5-tricarboxylate (Fe-BTC), for arsenic removal from water. We conducted batch and column experiments to evaluate the effects of varying mass dosages of MOF and pH ranges on arsenic adsorption. Our batch experiments revealed that increasing the mass of Fe-BTC MOF led to higher adsorption capacity. Furthermore, within the range of pH values analyzed, Fe-BTC demonstrated stable arsenic adsorption capacity, suggesting that pH conditions did not significantly affect its performance. In the column experiments, we used granitic material amended with compost and compared arsenic concentration breakthrough curves with and without the presence of MOF to assess its efficiency in arsenic removal. Without MOF, we observed rapid arsenic arrival followed by a slow increase in concentration, indicating anomalous transport dynamics induced by the compost. The addition of MOF resulted in prolonged arsenic arrival and a stabilized lower concentration, indicating effective arsenic adsorption. Fe-BTC MOF exhibited a six-fold increase in arsenic adsorption compared to its absence when added to the soil material. We employed a fractional order advection–dispersion equation model to characterize and predict the physical and chemical dynamics in the column experiments. The transport model accurately matched the arsenic breakthrough curves in the column experiments by capturing the non-Fickian transport and sorption chemical dynamics. The model indicated that compost had an insignificant impact on arsenic adsorption due to flow heterogeneity, while higher dosages of MOF resulted in increased arsenic adsorption and non-Fickian dynamics.
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