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Single particle ICP-TOFMS is used to measure isotope ratios within individual sub-micron particles. We explore the advantages and limitations of this method through the analysis of stable and radiogenic isotope pairs in monazite and galena particles. 

Zirconium (Zr) is an important material in the field of ceramics, dentistry, and nuclear energy. It is also present in particulate form in our environment and can come from naturally occurring minerals such as zircon (ZrSiO4) or from anthropogenic sources such as zirconia (ZrO₂). In this study, we present the detection and classification of Zr-particles at the individual particle level by using single-particle inductively coupled plasma time-of-flight mass spectrometry (spICP-TOFMS). Neat suspensions of engineered zirconia particles (Zr-eng) and natural zircon particles (Zr-nat) were analyzed by spICP-TOFMS, and a decision tree-based classification strategy was developed to distinguish the particle types based on their multi-elemental compositions. In both Zr-eng and Zr-nat particles, the only well-correlated element with Zr was hafnium (Hf), with Zr:Hf mass ratios converging to 47:1 and 75:1 for Zr-eng and Zr-nat, respectively. The detection of Hf along with Zr is indicative of both Zr-eng and Zr-nat particle types; however, the Zr:Hf mass ratios are too similar to be used to distinguish between individual nano- and sub-micron Zr-eng and Zr-nat particles. Instead, Zr-nat particles can be distinguished from Zr-eng particles based on the detection of minor elements, such as iron, yttrium, lanthanum, cerium, and thorium, along with Hf in the Zr-nat particles. With our classification scheme, we demonstrate true-positive classification rates of 40% and 80% for Zr-eng and Zr-nat particle types, respectively. False-positive classification of Zr-nat as Zr-eng was below 2%. We validate our classification scheme by classifying the Zr-particles in controlled mixtures of Zr-nat and Zr-eng particles. In these mixtures, Zr-eng particles are classified at particle-number concentrations (PNCs) down to 49-times lower than that of Zr-nat particles and across a PNC range of 3 orders of magnitude. 

Titanium dioxide (TiO₂) and zinc oxide (ZnO) engineered nanoparticles (NPs) are used in mineral-based sunscreens due to their excellent ultraviolet light protection abilities. Over time, surface water can become contaminated... 

Titanium-containing nanoparticles (NPs) and sub-micron particles (µPs) in the environment can come from natural or anthropogenic sources. In this study, we investigate the use of single-particle inductively coupled plasma time-of-flight mass spectrometry (spICP-TOFMS) to measure and classify individual Ti-containing particles as either engineered (Ti-eng) or naturally occurring (Ti-nat) based on elemental composition and multi-element mass ratios. We analyze mixtures of four Ti-containing particle types: anthropogenic food-grade TiO2 particles and particles from rutile, ilmenite, and biotite mineral samples. Through characterization of neat particle suspensions, we develop a decision-tree-based classification scheme to distinguish Ti-eng from Ti-nat particles, and to classify individual Ti-nat particles by mineral type. Engineered TiO2 and rutile particles have the same major-element composition. To distinguish Ti-eng particles from rutile, we develop particle-type detection limits based on the average crustal abundance ratio of titanium to niobium. For our measurements, the average Ti mass needed to classify Ti-eng particles is 9.3 fg, which corresponds to a diameter of 211 nm for TiO2. From neat suspensions, we demonstrate classification rates of 55%, 32%, 75%, and 72% for Ti-eng, rutile, ilmenite, and biotite particles, respectively. Our classification approach minimizes false-positive classifications, with rates below 5% for all particle types. Individual Ti-eng particles can be accurately classified at the sub-micron size range, while the Ti-nat particles are classified in the nano-regime (diameter < 100 nm). Efficacy of our classification approach is demonstrated through the analysis of controlled mixtures of Ti-eng and Ti-nat and the analysis of natural stream water spiked with Ti-eng particles. In control mixtures, Ti-eng particles can be measured and classified at particle-number concentrations (PNCs) 60-times lower than that of Ti-nat particles and across a PNC range of at least three orders of magnitude. In the stream water sample, Ti-eng particles are classified at environmentally relevant PNCs that are 44-times lower than the background Ti-nat PNC and 2850-times lower than the total PNC.