Emerging investigator series: automated single-nanoparticle quantification and classification: a holistic study of particles into and out of wastewater treatment plants in Switzerland

The evolution of data treatment tools in single-particle and single-cell ICP-MS analytics

Single-particle inductively coupled plasma-mass spectrometry (sp-ICP-MS) is one of the most powerful tools in the thriving field of nanomaterial analysis. Along the same lines, single-cell ICP-MS (sc-ICP-MS) has become an invaluable tool in the study of the variances of cell populations down to a per-cell basis. Their importance and application fields have been listed numerous times, across various reports and reviews. However, not enough attention has been paid to the immense and ongoing development of the tools that are currently available to the analytical community for the acquisition, and more importantly, the treatment of single-particle and single-cell-related data. Due to the ever-increasing demands of modern research, the efficient and dependable treatment of the data has become more important than ever. In addition, the field of single-particle and single-cell analysis suffers due to a large number of approaches for the generated data-with varying levels of specificity and applicability. As a result, finding the appropriate tool or approach, or even comparing results, can be challenging. This article will attempt to bridge these gaps, by covering the evolution and current state of the tools at the disposal of sp-ICP-MS users.

Past progress in environmental nanoanalysis and a future trajectory for atomic mass-spectrometry methods

The development of engineered nanotechnology has necessitated a commensurate maturation of nanoanalysis capabilities. Building off a legacy established by electron microscopy and light-scattering, environmental nanoanalysis has now benefited from ongoing advancements in instrumentation and data analysis, which enable a deeper understanding of nanomaterial properties, behavior, and impacts. Where once environmental nanoparticles and colloids were grouped into broad 'dissolved or particulate' classes that are dependent on a filter size cut-off, now size distributions of submicron particles can be separated and characterized providing a more comprehensive examination of the nanoscale. Inductively coupled plasma-quadrupole mass spectrometry (ICP-QMS), directly coupled to field flow fractionation (FFF-ICP-QMS) or operated in single particle mode (spICP-MS) have spearheaded a revolution in nanoanalysis, enabling research into nanomaterial behavior in environmental and biological systems at expected release concentrations. However, the complexity of the nanoparticle population drives a need to characterize and quantify the multi-element composition of nanoparticles, which has begun to be realized through the application of time-of-flight MS (spICP-TOFMS). Despite its relative infancy, this technique has begun to make significant strides in more fully characterizing particulate systems and expanding our understanding of nanoparticle behavior. Though there is still more work to be done with regards to improving instrumentation and data processing, it is possible we are on the cusp of a new nanoanalysis revolution, capable of broadening our understanding of the size regime between dissolved and bulk particulate compartments of the environment.

The elemental fingerprint as a potential tool for tracking the fate of real-life model nanoplastics generated from plastic consumer products in environmental systems

Metals and metalloids are widely used in producing plastic materials as fillers and pigments, which can be used to track the environmental fate of real-life nanoplastics in environmental and biological systems. Therefore, this study investigated the metal and metalloids concentrations and fingerprint in real-life model nanoplastics generated from new plastic products (NPP) and from environmentally aged ocean plastic fragments (NPO) using single particle-inductively coupled plasma-mass spectrometry (SP-ICP-TOF-MS) and transmission electron microscopy coupled with energy dispersive X-ray spectroscopy (TEM-EDX). The new plastic products include polypropylene straws (PPS), polyethylene terephthalate bottles (PETEB), white low-density polyethylene bags (LDPEB), and polystyrene foam shipping material (PSF). All real-life model nanoplastics contained metal and metalloids, including Si, Al, Sr, Ti, Fe, Ba, Cu, Pb, Zn, Cd, and Cr, and were depleted in rare earth elements. Nanoplastics generated from the white LDPEB were rich in Ti-bearing particles, whereas those generated from PSF were rich in Cr, Ti, and Pb. The Ti/Fe in the LDPEB nanoplastics and the Cr/Fe in the PSF nanoplastics were higher than the corresponding ratios in natural soil nanoparticles (NNPs). The Si/Al ratio in the PSF nanoplastics was higher than in the NNPs, possibly due to silica-based fillers. The elemental ratio of Si/Al, Fe/Cr, and Fe/Ni in the nanoplastics derived from ocean plastic fragments was intermediate between the nanoplastics derived from real-life plastic products and NNPs, indicating a combined contribution from pigments and fillers used in plastics and from natural sources. This study provides a method to track real-life nanoplastics in controlled laboratory studies based on nanoplastic elemental fingerprints. It expands the realm of nanoplastics that can be followed based on their metallic signatures to all kinds of nanoplastics. Additionally, this study illustrates the importance of nanoplastics as a source of metals and metal-containing nanoparticles in the environment.

Characterization and Quantification of Natural and Anthropogenic Titanium-Containing Particles Using Single-Particle ICP-TOFMS

Titanium-containing nanoparticles (NPs) and submicrometer 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 multielement 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 developed 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 submicron size range, while the Ti-nat particles are classified in the nanoregime (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 streamwater 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 3 orders of magnitude. In the streamwater 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.

Elemental Characterization of Leaded and Lead-Free Inorganic Primer Gunshot Residue Standards Using Single Particle Inductively Coupled Plasma Time-of-Flight Mass Spectrometry

This study describes the use of single particle inductively coupled plasma time-of-flight mass spectrometry (spICP-TOFMS) for the detection and classification of inorganic gunshot residue (IGSR) particles. To establish reliable multi-element criteria to classify IGSR particles, leaded and lead-free IGSR reference materials were analyzed, and the elemental compositions of the individual particles were quantified. The results suggest that expanded element compositions may be used to classify IGSR particles via spICP-TOFMS compared to those used in conventional IGSR analysis using scanning electron microscopy energy dispersive X-ray spectroscopy (SEM-EDS). For spICP-TOFMS analysis of leaded IGSR particles, classification may be based on the presence of lead (Pb), antimony (Sb), and barium (Ba) just as in SEM-EDS; however, additional particle types, such as lead-copper (Pb-Cu) particles, contribute significantly (∼30%) to the leaded IGSR particle population. In lead-free IGSR particles, the dominate multi-metal particle composition found is titanium-zinc (Ti-Zn) with a conserved Zn:Ti ratio of 1.4:1, but other elements, such as copper (Cu), are also characteristic. In mixtures of the two IGSR reference materials, we were able to classify over 80% of the multi-metal particles detected with no false-positive particle-type assignments. With spICP-TOFMS, particles smaller than those typically measured by SEM-EDS are detected, with estimated median diameters for leaded and lead-free IGSR of 180 and 320 nm, respectively. Through measuring these smaller particles, up to ∼two times more particles per mL are recorded by spICP-TOFMS compared to that found by SEM-EDS. Overall, high-sensitivity and high-throughput analysis using spICP-TOFMS enables quantitative, rapid multi-elemental characterization, and classification of individual IGSR particles.

Predicting accidental release of engineered nanomaterials to the environment

Challenges in distinguishing between natural and engineered nanomaterials (ENMs) and the lack of historical records on ENM accidents have hampered attempts to estimate the accidental release and associated environmental impacts of ENMs. Building on knowledge from the nuclear power industry, we provide an assessment of the likelihood of accidental release rates of ENMs within the next 10 and 30 years. We evaluate risk predictive methodology and compare the results with empirical evidence, which enables us to propose modelling approaches to estimate accidental release risk probabilities. Results from two independent modelling approaches based on either assigning 0.5% of reported accidents to ENM-releasing accidents (M1) or based on an evaluation of expert opinions (M2) correlate well and predict severe accidental release of 7% (M1) in the next 10 years and of 10% and 20% for M2 and M1, respectively, in the next 30 years. We discuss the relevance of these results in a regulatory context.

Application of Isotopically Labeled Engineered Nanomaterials for Detection and Quantification in Soils via Single-Particle Inductively Coupled Plasma Time-of-Flight Mass Spectrometry

Finding and quantifying engineered nanomaterials (ENMs) in soil are challenging because of the abundance of natural nanomaterials (NNMs) with the same elemental composition, for example, TiO₂. Isotopically enriched ENMs may be distinguished from NNMs with the same elemental composition using single-particle inductively coupled plasma time-of-flight mass spectrometry (spICP-TOF-MS) to measure multiple isotopes simultaneously within each ENM and NNM in soil, but the minimum isotope enrichment needed for detection of ENMs in soil is not known. Here, we determined the isotope enrichment needed for ⁴⁷Ti-enriched TiO₂ ENMs to be detectable in soil and assessed the effects of weathering on those requirements for less soluble TiO₂ and more soluble CuO ENMs. The isotope-enriched ENMs were dosed into two different soils and were extracted and measured by spICP-TOF-MS after 1, 7, and 30 days. Isotope-enriched ENMs were recovered and detected for all three time points. The ⁴⁷Ti-enriched TiO₂ ENMs were detectable in Lufa 2.2 soil at a nominal dosed concentration of 10 mg-TiO₂ kg^-1 which is an environmentally relevant concentration in biosolid-amended soils. For distinguishing an ∼70 nm diameter TiO₂ ENM from TiO₂ NNMs in Lufa 2.2 soil, an ∼10 wt % ⁴⁷Ti isotope-enrichment was required, and this enrichment requirement increases as the particle size decreases. This study is the first to evaluate the tracking ability of isotope-enriched ENMs at an individual particle level in soil and provides guidance on the isotope enrichment requirements for quantification of ENMs made from Earth-abundant elements in soils.

Detection of magnetic iron nanoparticles by single-particle ICP-TOFMS: case study for a magnetic filtration medical device

Nanoparticles are increasingly used in medical products and devices. Their properties are critical for such applications, as particle characteristics determine their interaction with the biological system, and, therefore, the performance and safety of the final product. Among the most important nanoparticle characteristics and parameters are particle mass distribution, composition, total particle mass, and number concentration. In this study, we utilize single-particle inductively coupled plasma time-of-flight mass spectrometry (spICP-TOFMS) for the characterization of inorganic nanoparticles in complex biological fluids. We report online microdroplet calibration for reference-nanomaterial-free and matrix-matched calibration of carbon-coated iron carbide nanoparticles (C/Fe₃C NPs). As a case study, we analyze C/Fe₃C NPs designed for targeted blood purification. Through the analysis of NP mass distributions, we study the effect of the NP surface modification on aggregation of C/Fe₃C NPs in whole blood. We also demonstrate the efficiency of removal of coated C/Fe₃C NP from saline by magnetically enhanced filters. Magnetic filtering is shown to reduce the mass concentration of detectable C/Fe₃C NPs by 99.99 ± 0.01% in water.

Exploring Nanogeochemical Environments: New Insights from Single Particle ICP-TOFMS and AF4-ICPMS

Nanogeochemistry is an emerging focus area recognizing the role of nanoparticles in Earth systems. Engineered nanotechnology has cultivated advanced analytical techniques that are also applicable to nanogeochemistry. Single particle inductively coupled plasma ICP-time-of-flight-mass spectrometry (ICP-TOF-MS) promises a significant step forward, as time-of-flight mass analyzers enable simultaneous quantification of the entire atomic mass spectrum (∼7-250 m/z ⁺). To demonstrate the utility of this approach, samples were collected and analyzed from a large, boreal river, and its surrounding tributaries. These samples provided us with a diversity of particle compositions and morphologies, while their interconnected nature allowed for an examination of the various nanogeochemical processes present in this system. To further expand on this effort, we combined this high-throughput technique with AF4-ICPMS, focusing on major carriers of trace elements. Using spICP-TOF-MS, Al, Si, and Fe were grouped into classes having all combinations of one or more of these elements. Particle-by-particle ICP-TOF-MS analysis found chemically heterogeneous populations, indicating the predominance of diverse mineralogy or heteroaggregates. The importance of suspended Fe and Mn for the speciation of Pb was observed by single particle ICP-TOF-MS and complemented by AF4-ICPMS analysis of dissolved organic matter and nanoparticulate Fe/Mn. Our study exploits the combination of spICP-TOF-MS and AF4-ICP-MS for studying isotopic and elemental ratios (mineralogy) of individual nanoparticles, which opens the door to further explore the mechanisms of colloid facilitated transport of trace elements.

Elemental fingerprints in natural nanomaterials determined using SP-ICP-TOF-MS and clustering analysis

Detection and quantification of engineered nanomaterials in environmental systems require precise knowledge of the elemental composition, association, and ratios in homologous natural nanomaterials (NNMs). Here, we characterized soil NNMs at the single particle level using single particle-inductively coupled plasma-time of flight-mass spectrometer (SP-ICP-TOF-MS) in order to identify the elemental purity, composition, associations, and ratios within NNMs. Elements naturally present as a major constituent in NNMs such as Ti, and Fe occurred predominantly as pure/single metals, whereas elements naturally present at trace levels in NNMs occurred predominantly as impure/multi-metal NNMs such as V, Nb, Pr, Nd, Sm, Eu, Gd, Tb, Er, Dy, Yb, Lu, Hf, Ta, Pb, Th, and U. Other elements occurred as a mixture of single metal and multi-metal NNMs such as Al, Si, Cr, Mn, Ni, Cu, Zn, Ba, La, Ce, W, and Bi. Thus, elemental purity can be used to differentiate ENMs vs. NNMs only for those elements that occur at trace level in NNMs. We also classified multi-metal NNM into clusters of similar elemental composition and determined their mean elemental composition. Six major clusters accounted for more than 95% of the detected multi-metal NNMs including Al-, Fe-, Ti-, Si-, Ce-, and Zr-rich particles' clusters. The elemental composition of these multi-metal NNM clusters is consistent with naturally occurring minerals. Titanium occurred as a major element (>70% of the total metal mass in NNMs) in Ti-rich cluster and as a minor (<25% of the total metal mass in NNMs) element in likely clay, titanomagnetite, and aluminum oxide phases. Two rare earth element (REE) clusters were identified, characteristic of light REEs and heavy REEs. The findings of this study provide a methodology and baseline information on the elemental composition, associations, and ratios of NNMs, which can be used to differentiate NNMs vs. ENMs in environmental systems.