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离子交换树脂可改善使用单颗粒电感耦合等离子体质谱法分析废水中的金属纳米颗粒。

Ion-exchange resins improve the analysis of metal nanoparticles in wastewater using single-particle inductively coupled plasma-mass spectrometry.

机构信息

Environmental Analysis Center, Gwangju Institute of Science and Technology, Gwangju, 61005, South Korea.

GIST Advanced Institute of Instrumental Analysis (GAIA), Environmental Analysis Laboratory, Gwangju Institute of Science and Technology, Gwangju, 61005, South Korea.

出版信息

Environ Sci Pollut Res Int. 2024 Aug;31(40):53090-53099. doi: 10.1007/s11356-024-34735-3. Epub 2024 Aug 23.

Abstract

Improved measurement and analysis technologies are needed for investigating nanoparticle generation characteristics in sewage treatment plants. Single-particle inductively coupled plasma-mass spectrometry (spICP-MS) can be used to analyze metal nanoparticle characteristics. However, during spICP-MS analysis of environmental samples, high concentrations of ionic materials obscure the signals of particulate materials by increasing background signals. This can increase the threshold value for separating background and particle signals and increase the background-equivalent diameter (BED). In this study, particle size distributions in influent and effluent collected from sewage treatment plants were investigated using an improved spICP-MS method combining spICP-MS with ion-exchange resin (IER) column pretreatment. The ion removal effect of the IER column was first examined using a synthetic mixture of Ag nanoparticles (AgNPs) and ions. The method was then applied to wastewater from six different sewage treatment plants using an optimal IER packing of 5 g. The ion removal efficiency for samples containing a proper mixture of AgNPs and Ag ions was 99.98%, and the BED significantly decreased from 73.0 ± 1.0 to 6.1 ± 0.3 nm. Particle size distributions measured in the treatment plant influent and effluent ranged from 28.5 nm (Co) to 220.3 nm (Mg) and from 26.8 nm (Co) to 291.8 nm (Mg), respectively. spICP-MS/IER enabled the detection of smaller particles by removing ions from the sample and significantly decreasing the size detection limit. The results of this study offer a reference for developing predictive models for removing metal nanoparticles during sewage/wastewater treatment.

摘要

需要改进的测量和分析技术来研究污水处理厂中纳米颗粒的生成特性。单颗粒电感耦合等离子体质谱(spICP-MS)可用于分析金属纳米颗粒特性。然而,在 spICP-MS 分析环境样品时,高浓度的离子材料会通过增加背景信号来掩盖颗粒物质的信号。这会增加分离背景和颗粒信号的阈值,并增加背景等效直径(BED)。在这项研究中,使用 spICP-MS 与离子交换树脂(IER)柱预处理相结合的改进 spICP-MS 方法,研究了从污水处理厂收集的进水和出水的颗粒粒径分布。首先使用 Ag 纳米颗粒(AgNPs)和离子的合成混合物来检验 IER 柱的离子去除效果。然后,使用 5 g 最佳 IER 填充,将该方法应用于来自六个不同污水处理厂的废水。对于含有适当混合的 AgNPs 和 Ag 离子的样品,离子去除效率为 99.98%,BED 从 73.0 ± 1.0 nm 显著降低至 6.1 ± 0.3 nm。在处理厂进水和出水中测量的颗粒粒径分布范围从 28.5 nm(Co)到 220.3 nm(Mg)和从 26.8 nm(Co)到 291.8 nm(Mg)。spICP-MS/IER 通过从样品中去除离子,显著降低了尺寸检测下限,从而能够检测到更小的颗粒。本研究结果为开发污水处理/废水处理过程中去除金属纳米颗粒的预测模型提供了参考。

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