Quantification and Clustering of Inorganic Nanoparticles in Wastewater Treatment Plants across Switzerland#
Open access
Date
2021-08Type
- Journal Article
Abstract
Single particle Inductively Coupled Plasma Time-of-Flight Mass Spectrometry (sp-ICP-TOFMS), in combination with online microdroplet calibration, allows the determination of particle number concentrations (PNCs) and the masses of elements in individual particles. Because sp-ICP-TOFMS analyses of environmental samples produce rich datasets composed of both single-metal nanoparticles (smNPs) and many types of multi-metal NPs (mmNPs), interpretation of these data is well suited to automated analysis schemes. Here, we present a data analysis approach that includes automatic particle detection and elemental mass determinations based on online microdroplet calibration, and unsupervised clustering analysis of mmNPs to identify unique classes of NPs based on their element compositions. To demonstrate the potential of our approach, we analyzed wastewater samples collected from the influent and effluent of five wastewater treatment plants (WWTPs) across Switzerland. We determined elemental masses in individual NPs, as well as PNCs, to estimate the NP removal efficiencies of the individual WWTPs. Through hierarchical clustering, we identified NP classes conserved across all WWTPs; the most abundant particle types were those rich in Ce-La, Fe-Al, Ti-Zr, and Zn-Cu. In addition, we found particle types that are unique to one or a few WWTPs, which could indicate point sources of anthropogenic NPs. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000508475Publication status
publishedExternal links
Journal / series
ChimiaVolume
Pages / Article No.
Publisher
Swiss Chemical SocietySubject
Clustering; ICP-TOFMS; Microdroplet calibration; Nanoparticle; WastewaterOrganisational unit
03512 - Günther, Detlef / Günther, Detlef
03832 - Morgenroth, Eberhard / Morgenroth, Eberhard
Funding
174061 - Toward High-Throughput Quantitative Analysis of Nanoparticle Pollution in Environmental Samples (SNF)
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