Quantification and Clustering of Inorganic Nanoparticles in Wastewater Treatment Plants across Switzerland

Abstract

Single particle Inductively Coupled Plasma Time-of-Flight Mass Spectrometry (sp-ICP-TOFMS), in combination with online microdroplet calibration, allows for 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 waste water 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.