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Ion-exchange resins improve the analysis of metal nanoparticles in wastewater using single-particle inductively coupled plasma–mass spectrometry
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Ion-exchange resins improve the analysis of metal nanoparticles in wastewater using single-particle inductively coupled plasma–mass spectrometry
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Journal Article
Ion-exchange resins improve the analysis of metal nanoparticles in wastewater using single-particle inductively coupled plasma–mass spectrometry
2024
Overview
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.
Publisher
Springer Berlin Heidelberg,Springer Nature B.V
Subject
