Application of Single-Particle ICP-MS to Determine the Mass Distribution and Number Concentrations of Environmental Nanoparticles and Colloids

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Mansor, Muammar ; Drabesch, Sören ; Bayer, Timm ; Van Le, Anh ; Chauhan, Ankita ; Schmidtmann, Johanna ; Peiffer, Stefan ; Kappler, Andreas:
Application of Single-Particle ICP-MS to Determine the Mass Distribution and Number Concentrations of Environmental Nanoparticles and Colloids.
In: Environmental Science & Technology Letters. Bd. 8 (2021) Heft 7 . - S. 589-595.
ISSN 2328-8930
DOI: https://doi.org/10.1021/acs.estlett.1c00314

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Abstract

Analyzing the elemental compositions and size distributions of nanoparticles, colloids, and their aggregates in environmental samples represents a key task in understanding contaminant, substrate, and nutrient cycling. Single-particle ICP-MS (spICP-MS) is a high-throughput method that is capable of providing the elemental mass of thousands of particles within minutes. The challenge, however, lies in data analysis and interpretation, especially for complex environmental samples. Here we present successful applications of spICP-MS for environmental samples. We first analyzed the homoaggregation behavior of synthetic microplastic and magnetite (abiogenic and biogenic) nanoparticles. The measured distribution of aggregate mass was described as a function of the number of primary particles/aggregate (Npp). In tandem with dynamic light scattering data, differences in aggregates’ compactness (primary particles per nanometer) between samples can be determined. Second, we showed how sequential elemental analysis allows evaluation of the mobility of a toxic arsenic metalloid and its inferred association with colloidal Fe(III)(oxyhydr)oxides. Finally, we investigated the composition of heterogeneous iron−carbon-rich colloidal flocs, highlighting distinct colloidal Fe and C distributions and C/Fe ratios between samples from different permafrost thawing stages. On the basis of our results, we provide guidelines for successful sample preparation and promising future spICP-MS opportunities and applications with environmental samples.