# Polar organic pollutants, micro-nano plastics and nanomaterials: Analytical techniques to reveal the still invisible human physico-chemical exposome

Andrew Chetwynd, Mari-Vorgan Louyer, Fabien Mercier, Vincent Bessonneau, Arthur David

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Andrew Chetwynd, Mari-Vorgan Louyer, Fabien Mercier, Vincent Bessonneau, Arthur David. Polar organic pollutants, micro-nano plastics and nanomaterials: Analytical techniques to reveal the still invisible human physico-chemical exposome. Trends in Analytical Chemistry, 2024, 177, pp.117816. 10.1016/j.trac.2024.117816. hal-04646636

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# Polar organic pollutants, micro-nano plastics and nanomaterials: Analytical techniques to reveal the still invisible human physico-chemical exposome

Andrew J. Chetwynd<sup>a</sup>, Mari-Vorgan Louyer<sup>b</sup>, Fabien Mercier<sup>b</sup>, Vincent Bessonneau<sup>b</sup>,
Arthur David<sup>b,*</sup>

<figure><img src="image_2.png" /></figure>

## ARTICLE INFO

### Keywords:

Human biomonitoring

Polar organic contaminants

Particulate contaminants

Plastics

Nanomaterials

Exposome

Mass spectrometry

## ABSTRACT

Large international biomonitoring initiatives have emerged to start mapping the exposure of humans to environmental contaminants. However, data are only available for a very limited number of contaminants, which reflects the lack of methods available for some chemicals (e.g., polar and ionic organic contaminants), or the lack of standardized methods for particulate contaminants such as micro-nano plastics and engineered nanomaterials. Here, we explore the advantages of analytical techniques that could improve the coverage of the human physico-chemical exposome. We first focus on the advantages of alternative methods, i.e., ion chromatography and capillary electrophoresis coupled to mass spectrometry, to improve the detection of polar and ionic substances. We then reviewed methods that have been used so far for the particulate characterization of human exposure, and discuss their applicability in large-scale programs. The complementary nature of the skill sets from exposure communities have the potential to close some current gaps in knowledge.

## 1. Introduction

Environmental chemical pollution is a major and growing global concern [1]. Several hundreds of thousands of new chemicals have been synthesised since 1950, and the production of chemicals is predicted to increase until 2030 [1,2]. Many of these chemicals have been shown to accumulate in humans (e.g. pesticides, plasticisers, personal care products, persistent organic pollutants), alone or as mixtures, and can negatively affect our health by interacting with nuclear receptors [3,4], inhibiting key enzymatic activities [3] or inducing epigenetic changes [4], and are consequently suspected to contribute to a number of chronic diseases [1]. However, human chemical exposure and toxicological data are available for a small fraction of these chemicals [5], meaning that a large proportion of chemicals susceptible to impair human health have never been examined so far, alone, or as complex mixtures [1,6].

Recent studies [5,7] have suggested that this bias toward repeated measurements of the same compounds and a lack of studies on a broader suite of substances may reflect a tendency to avoid the risks associated with unstudied chemicals such as the lack of analytical methods and standards. For instance, very polar and ionic substances are often poorly

covered in conventional human biomonitoring (HBM) programs, partly due to the fact that conventional analytical methods are not well adapted for these chemicals. These substances include, among others, some pesticides and their biotransformation products, ultra-short chain perfluoroalkyl substances (PFAS)- which are replacements for long chain legacy PFAS, with similar toxicity, negative health effects, and high persistence, or disinfectant by-products such as haloacetic acids known to be mutagenic, cytotoxic, genotoxic, teratogenic, and carcinogenic [8].

Besides the gap in knowledge related to polar organic chemicals, the impacts of particulate matter such as micro-nano plastics (MNP) and engineered nanomaterials (ENM) exposure on the human non-communicable disease risk is still yet ill-defined. Microplastics are typically defined as plastics smaller than 5 mm while nanomaterials can be made of any material with at least one dimension smaller than 100 nm. As for nanoparticles, all dimensions are smaller than 100 nm [9]. MNPs come in two forms, primary which is microplastic produced at a microplastic scale, and secondary which describe microplastic debris that degrade into micro and nanoscale plastic debris through weathering, ageing and mechanical abrasions/transport [9].

MNP exposure in humans comes from a multitude of sources with

<footnote><sup>a</sup> Centre for Proteome Research, Department of Biochemistry, Cell and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK</footnote>

<footnote><sup>b</sup> Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, Rennes, France</footnote>

<footnote>* Corresponding author.
E-mail address: arthur.david@ehesp.fr (A. David).</footnote>
Abbreviations

CE capillary electrophoresis chromatography

EDX dispersive X-ray microanalysis

EELS electron energy loss spectroscopy

ENM: engineered nanomaterial

FTIR: Fourier Transform Infra-Red

GC gas chromatography

HBM human biomonitoring

HRMS high-resolution mass spectrometry

IC ion chromatography

LC liquid chromatography

LDIR: Laser direct infrared spectroscopy

MP / MNP micro plastics / micro-nano plastics

pyGC-MS pyrolysis gas chromatography-mass spectrometry

spICP-MS Coupled Plasma-Mass Spectrometry

TGA-FTIR-GC-MS Fourier Transform Infra-Red-gas chromatography-mass spectrometry

millions of particles being detected in formula baby milk and their bottles [10,11], to MNPs being found to be highly prevalent in seafood [12,13], drinking water [14] and cosmetics [15] to name just a few sources. Routes of exposure comes via inhalation of MNPs suspended in the air, ingestion, and dermal contact [16]. Recent studies showed that MNPs can be found in human blood [17], lungs [18,19], sputum [20], faeces [21–23], urine [24], colectomy samples [25], placenta [21, 26–28], breast milk [21,29], and more recently the carotid artery plaque [30]. It is well established that the human exposure to both MNP is extensive and is only going to grow at least in the short term, however, evidence on the effects of MNPs on human health remains limited [31].

ENM use is growing with a wide range of commercial and medical products containing nano TiO₂, SiO₂, carbon nanomaterials and CeO particles amongst many. There is a growing body of evidence showing that they can translocate around the body and pass the blood brain barrier in models [32], and in human cerebrospinal fluid (CSF) samples [33] and placental barrier [34–36], potentially raising the risk of neurological impacts and exposure and toxicity in utero. In addition, recent evidence has shown that small nanoparticles around 10 nm can penetrate the full thickness of human skin [37]. Studies have also shown

that inhalation via the nose allows particles that deposit within the olfactory bulb can migrate to the brain. A key driver of this translocation around the body appears to be the so called “biomolecular corona” which describes the adsorbed exogenous and endogenous biomolecules such as proteins, metabolites and pollutants which provide the particle with a biological identity rather than being seen as a foreign entity [38, 39]. However, due to the difficulties in the characterisation of particulates, there is a fundamental lack of information on the true burden posed to humans by particulate exposures.

In this review, we aimed to explore the potential of promising analytical techniques that could help to improve the coverage of two different groups of environmental contaminants, i.e., polar organic contaminants and particulates such as MNP and ENM. These groups of contaminants often remain out of the scope of large HBM programs mostly because of the lack of analytical methods or the lack of standardized methods, despite the great efforts that are continuously made to analyse more deeply the diversity of the human physico-chemical exposome (i.e. chemicals and particulates accumulating in human) (Fig. 1). Here, we first focus on the advantages of ion chromatography and capillary electrophoresis coupled to mass spectrometry that could be used as alternative methods to improve the detection of overlooked polar and ionic chemical substances. We then describe analytical methods that have been used so far the particulate characterization of human exposure, and discuss the applicability of these methods in HBM programs. The complementary nature of the skill sets needed to analyse chemicals and particulates exposures in human biological samples have the potential to accelerate our understanding of the impact of the physico-chemical exposome on human health.

## 2. Analytical methods for polar organic substances

For the chemical exposome, recent reviews and articles [6,40–43] have already covered the need for analytical development (including sample preparation), method harmonisation and multi-platform integration for conventional gas chromatography (GC) and liquid chromatography (LC) mass spectrometry to capture the wide diversity of the chemical exposome. However, most of these applications are mainly focused on mid-polar to apolar chemicals. Major limitations in the analysis of very polar and ionic compounds are sample preparation and chromatographic separation [44] because such compounds are not well retained on conventional polymeric materials such as Waters Oasis HLB

<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Conceptual visualisation of the diversity of contaminants from the chemical (i.e., organic and inorganic chemicals) and the particulate exposome (micro- and nano-plastics and nanomaterials) that can accumulate in human biological matrices, adapted from David et al. [6]. A wide range of analytical techniques are required to analyse these contaminants but standardised analytical methods are still missing for polar organic contaminants and particulates.</figcaption></figure>
or Phenomenex Strata-X and on conventional reversed-phase liquid chromatographic columns often used for separation in human bio- monitoring [45]. This issue can be remedied to some extent with the application of ion-exchange functionalized polymeric sorbents, HILIC-LC-MS, ion pair chromatography or a derivatization step to make the target substance compatible with GC or LC conventional methods [45,46]. However, these methods often increase the time of analyses, and are generally more difficult to implement and/or less robust than conventional methods. Supercritical fluid chromatography has been proposed for several years for polar compound analysis in bioanalysis, -omics sciences, plant, and food analysis, however this technology still remains uncommon in the field of human biomonitoring [47,48]. Many significant chemicals such as glyphosate furthermore still remain diffi- cult to analyse in complex matrices. As such, techniques such as ion chromatography (IC) or capillary electrophoresis (CE) require increased prominence in the field. Both techniques are becoming more widely utilised in metabolomics and could prove useful for MS-based exposo- mics applications (both tandem MS/MS or HRMS). A recent interna- tional ring-trial of CE-MS confirm is highly reproducible nature for small polar metabolites, allaying previous issues over migration time and peak area reproducibility of the technique [49].

## 2.1. Ion chromatography coupled to mass spectrometry

Separation techniques using ion chromatography are based on the principles of ion exchange, i.e., on interactions between charged or ionisable analytes and the opposite charged particles of the stationary phase. As a result, the separation of anions and cations cannot be carried out simultaneously and requires different columns and eluents. This technique can separate and analyse ions of interest in complex biofluids such as urine [50] or plasma [51], using stationary phases such as functionalized resins, porous polymeric phase (i.e., polystyrene-divinylbenzene particles), modified by different techniques such as encapsulation, polymeric grafting, or chemical derivatization. Importantly, these IC systems are usually entirely non-metallic to avoid interactions with analytes of interest. Likewise, polyetheretherketone (peek) should be used for tubing, valves and injectors for the same reasons.

With the reduction of particle size, column diameter and increased porosity of resins in modern IC columns, it is now possible to analyse a wide range of samples (including biofluids) with an increased peak capacity. However, it must be noted that chromatographic peaks are generally broader than with conventional LC methods (which could impact on data processing for non-targeted HRMS-based analyses). Mobile phases are strong ionic solutions, commonly hydroxide or carbonate based for anionic IC while methane sulfonic acid or nitric acid are used for cationic IC. Modern IC systems are mostly equipped with electrolytic eluent generation meaning that the mobile phase and gradients are generated by an electrolytic system, allowing consistency of retention times and robustness.

Another specificity of IC systems lies in the use of suppressors (chemical/electrolytic suppressor/ inline suppressor with auto regeneration) which allow to minimize the background conductivity of the eluent. The suppressor applies direct current to cleave water into $H^+$ and oxygen at the anode and reduces water to $OH^-$ and hydrogen gas at the cathode. The $H^+$ ions are then transported across a membrane into the eluent to neutralize the highly basic eluent, while counter-ion is driven towards the cathode and transported into the waste, thus preventing this counter-ion build-up and corrosive damage to the mass spectrometry ESI source.

IC systems are usually equipped with a conductivity detector in front of the ESI source in order to visualize ionic interferences coming from the matrix. Using this system, separation parameters are adjusted to isolate ions of interest from ionic matrix components (e.g., salts from urine samples). Adding a diverter valve between conductivity detector and mass spectrometry and programming collect windows prevents

these salts fouling the ion source. To improve the ionisation efficiency of certain compounds, an organic solvent can be added upstream of the electrospray ionisation (ESI).

Compared to conventional (e.g., GC- and LC-MS), alternative methods (IC and CE-MS) usually do not offer a better sensitivity to detect polar organic contaminants such as pesticide metabolites, ultra-short chain PFAS or HAA (even though these data remain scare for these chemical families, see Table 1). However, the main advantage of ion chromatography lies in the possibility of injecting the sample directly ("dilute and shoot") without time-consuming preparation steps that may be subject to substance loss or sample contamination, and analyse an- ions and cations in multiresidue methods, which make it theoretically compatible in terms of cost and throughput with very large-scale anal- ysis campaigns such as national biomonitoring programs. Moreover, this technique can be considered "greener" because it is mostly solvent free (a small amount can be used in the ESI source to improve the ionisation efficiency). Recent studies have shown that IC-MS/MS could be the technique of choice for the determination of certain substances such as glyphosate [50], fosetyl aluminium [71], urinary dialkyl phosphate metabolites [50], ultra-short chain PFAS (C2–C4) [62], halo acetic acids (e.g., trichloroacetic acid) [65] or nerve agent markers [70] (e.g., alkylphosphonic acids and alkyl methylphosphonic acid), that are particularly difficult to determine in complex matrices without extrac- tion or derivatization steps using conventional methods. Few data are currently available for these substances in HBM and recent studies showed, for instance, a growing abundance of ultrashort chain PFAS in the environment and in the human body and, therefore, requiring robust high-throughput analytical methods to quantify these substances [72].

Nevertheless, it must be noted that, ion chromatography hyphenated to mass spectrometry is a relatively new technique in the field of HBM, and it requires a dedicated, specific and relatively expensive system not available from all manufacturers. Furthermore, the stationary phases available to date are few and not sufficiently "universal" to cover a very wide panel of anions or cations in the same run, which limits the development of high throughput multi-residue methods to date.

## 2.2. Capillary electrophoresis coupled to mass spectrometry

Capillary Electrophoresis (CE) is a greatly underutilised separation technique in metabolomics and MS-based chemical exposomics. Like IC, CE offers an orthogonal separation to reversed phase LC and offers higher peak capacity and resolution compared to both RP and HILIC LC separations [73]. CE separates analytes according to their intrinsic electrophoretic mobility based upon their charge and size as they pass through a capillary under the influence of an electric field [73]. Simi- larly, to other separation techniques the surface chemistry of the capillary can be altered to optimise separations [74], which typically have much higher separation efficiency than other technologies due to the flat flow profile greatly reducing peak broadening [75]. CE is particularly well suited for highly charged polar metabolites such as amino acids, carbohydrates and nucleotides, in addition to a range of environmental contaminants such as biomarkers of smoking, plasticisers and drugs [76,77]. CE also benefits from being able to perform injection from 5 µL or less and the ability to pre-concentrate samples rapidly during the injection cycle by injecting via electrokinetic injections whereby an electric current draws the sample into the capillary. This approach means only charged analytes enter the capillary as opposed to a hydrodynamic injection, which performs an injection in a similar manner to LC whereby a defined volume is injected and thus the sample is diluted. Samples with low concentration or large volumes can also be concentrated via stacking, this occurs where injections are concentrated at the front of the capillary prior to separation using a pH, or conduc- tivity barrier against which the sample concentrates into a minimal volume [78,79]. The ability to inject from volume limited samples and apply a rapid on-line preconcentration makes CE an exciting prospect from MS-based chemical exposomics, furthermore the throughput of CE
<caption>**Table 1**</caption>

Sample preparation, chromatographic setup and detection/quantification limits for polar organic contaminants detected and quantified using conventional (GC- and LC-MS) and alternative methods (IC and CE-MS) in human biological matrices (or environmental matrices when the information was not available). The potential for high-throughput was estimated based on the sample preparation and the chromatographic setup used (e. g., need for clean-up and/or derivatization versus direct injection).

<table><thead><tr><th rowspan="2">List of substances</th><th colspan="5">Conventional methods (LC- and GC-MS)</th><th colspan="5">Alternative methods (IC- and CE-MS)</th></tr><tr><th>matrice [ref]</th><th>sample preparation</th><th>chromatographic set-up</th><th>Potential for high-throughput</th><th>LOD/LOQ (ng/mL)</th><th>matrice [ref]</th><th>sample preparation</th><th>chromatographic set-up</th><th>Potential for high-throughput</th><th>LOD/LOQ (ng/mL)</th></tr></thead><tbody><tr><td><strong>Pesticides and metabolites</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>glyphosate</td><td>Urine [52]</td><td>derivatization / SPE (Oasis HLB)</td><td>UHPLC-MSMS</td><td>low</td><td>0.02/ 0.05</td><td>Urine [50]</td><td>direct injection</td><td>IC-IC-MSMS</td><td>high</td><td>0.2 /n.a.</td></tr><tr><td></td><td>Urine [46]</td><td>derivatization</td><td>GC-MSMS</td><td>low</td><td>0.05/n.a.</td><td>Water [53]</td><td>online isotachophoresis pre-concentration</td><td>CE-MSMS</td><td>medium</td><td>0.025/ n.a.</td></tr><tr><td></td><td>Urine [54]</td><td>liquid-liquid extraction</td><td>LC-MSMS</td><td>medium</td><td>n.a./ 0.1</td><td>Beer [55]</td><td>direct injection</td><td>CE-MSMS</td><td>high</td><td>&lt;5 /n.a.</td></tr><tr><td></td><td>Urine [56]</td><td>SPE (Oasis HLB)</td><td>LC-MSMS</td><td>medium</td><td>n.a./0.6</td><td>Urine <sup>b</sup></td><td>direct injection</td><td>IC-MSMS</td><td>high</td><td>n.a. / 0.1</td></tr><tr><td></td><td>Milk [54]</td><td>liquid-liquid extraction</td><td>LC-MSMS</td><td>medium</td><td>n.a./ 10</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>Urine [57]</td><td>SPE (SCX et NH2)</td><td>LC-MSMS</td><td>medium</td><td>0.1 / 0.3</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>dialkyl phosphates (DMP/ DEP/DMTP/DETP/ DMDTP/DEDTP) <sup>d</sup></td><td>Urine [58]</td><td>SPE (Strata-X-AW)</td><td>UHPLC-HRMSMS</td><td>low</td><td>DMP/DMTP/ DEP: 0.63 / 1.3 DMDTP: 0.25/ 0.5 DEDTP: 0.13/ 0.25 DEDTP excluded</td><td>Urine [50]</td><td>direct injection</td><td>IC-IC-MSMS</td><td>high</td><td>0.2 /n.a. except DEDTP: 0.8/n.a.</td></tr><tr><td>valone (rodenticide)</td><td>Serum [59]</td><td>SPE (Oasis HLB)</td><td>LC-MSMS</td><td>medium</td><td>n.a./ 0.5</td><td>Serum [59]</td><td>SPE (Oasis HLB)</td><td>IC-MSMS</td><td>medium</td><td>n.a./ 0.5</td></tr><tr><td>chlorothalonil metabolites</td><td>Water [60]</td><td>Concentration (evaporation)</td><td>LC-HRMS</td><td>medium</td><td>R417888 n.a./ 0.003 SYN507900 n. a./0.0013</td><td>Water [44]</td><td>SPE cleanup</td><td>IC-HRMS</td><td>medium</td><td>chlorothalonil metabolites R417888 n.a./ 0.031 R419492 n.a./ 0.018 SYN548008 n.a./ 0.009</td></tr><tr><td><strong>Ultra-short chain PFAS (C2-C4)</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>trifluoroacetic acid (TFAA) perfluoropropanoic acid (PFPrA) perfluorobutanoic acid (PFBA) trifluoromethane sulhonic acid (TFMS) TFMS</td><td>Water [61]</td><td>evaporation/ derivatization</td><td>GC-MSD</td><td>low</td><td>TFAA: n.a./ 0.0005 PFPrA: n.a./ 0.0002 PFBA: n.a./ 0.0002</td><td>Soils [62]</td><td>extraction/clean-up (solid matrice)</td><td>IC-MSMS</td><td>medium</td><td>TFAA: n.a./ 0.061 PFPrA: n.a./ 0.034 PFBA: n.a. / 0.052</td></tr><tr><td></td><td>Water [63]</td><td>SPE (Oasis WAX)</td><td>ion exchange HPLC (JJ-50) -MSMS</td><td>low</td><td>TFAA: n.a./ 0.0005 PFPrA: n.a./ 0.0001 PFBA: n.a./ 0.0001</td><td>Water <sup>b</sup></td><td>direct injection</td><td>IC-MSMS</td><td>high</td><td>TFAA: n.a./0.25 PFPrA: n.a./0.25 TFMS: n.a./0.05</td></tr><tr><td><strong>Halo Acetic acids (HAA)</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Monochloroacetic acid (MCAA) Dichloroacetic acid (DCAA) trichloroacetic acid (TCAA) Monobromoacetic acid</td><td>Urine [64]</td><td>headspace solid phase microextraction (HS-SPME)</td><td>HS-GC-ECD</td><td>medium</td><td>TCAA: 10/n.a.</td><td>Water [65]</td><td>direct injection</td><td>IC-MSMS</td><td>high</td><td>0.03 / n.a.</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td>tap water [66]</td><td>ion exchange resin</td><td>Field amplified sample stacking CE-MS</td><td>high</td><td>DCAA 0.08 / n.a. TCAA 0.009 / n. a.</td></tr></tbody></table>

(continued on next page)
<table><caption>**Table 2**

Review of preparation and analytical methods applied to human samples for micro-nano plastic characterization.</caption><thead><tr><th>Matrix</th><th>Digestion</th><th>Filter</th><th>Analytical method</th><th>No. of MPs</th><th>Polymers</th><th>MP density</th><th>Ref</th></tr></thead><tbody><tr><td>Faeces</td><td>10 % KOH &amp; 15 % EDTA<br>40 °C 12 h then<br>30 % H<sub>2</sub>O<sub>2</sub> 48 h then<br>AMIM-Cl 24 h</td><td>0.22 µm</td><td>Raman Microspectroscopy</td><td>117</td><td>PS, PP, PES, PET, PVC</td><td>50.3 ± 39.0<br>mp/g</td><td>[88]</td></tr><tr><td>Faeces</td><td>H2O2 for 20 days</td><td>ND</td><td>FTIR</td><td>ND</td><td>PP, PET, PS, PES, PA, PC, PVC, PU</td><td>1-36 mp/g</td><td>[23]</td></tr><tr><td>Faeces</td><td>30 % H<sub>2</sub>O<sub>2</sub> at 25 °C for 30 days<br>0.05 M NaOH 25 °C<br>Imidazolium salts</td><td>50 µm</td><td>FTIR</td><td>747</td><td>PP, PET, PS, PES, POM, PC, PA, PVC PU</td><td>8-416/<br>person</td><td>[22]</td></tr><tr><td>Infant faeces</td><td>68 % Nitric acid 48 h RT,<br>then 95 °C 3 h</td><td>13 µm</td><td>LDIR</td><td>ND</td><td>PA, PU, PES, PET, PP, PVC, POM, EVA, PTFE, CPE, PS,<br>PMMA, PLA, polysulphones, polybutadiene</td><td>26.6 mp/g</td><td>[21]</td></tr><tr><td>Meconium</td><td>68 % Nitric acid 48 h RT,<br>then 95 °C 3 h</td><td>13 µm</td><td>LDIR</td><td>ND</td><td>PA, PU, PES, PET, PP, PVC, POM, EVA, PTFE, CPE, PS,<br>PMMA, PLA, polysulphones</td><td>54.1 mp/g</td><td>[21]</td></tr><tr><td>Meconium</td><td>30 % H<sub>2</sub>O<sub>2</sub>, 80 C, 5 weeks</td><td>0.2 µm</td><td>µFTIR</td><td>ND</td><td>PES, PP, PS, PU</td><td>ND</td><td>[89]</td></tr><tr><td>Urine</td><td>10 % KOH 40 °C 48 h</td><td>1.2 µm</td><td>Raman microspectroscopy</td><td>7</td><td>PP, PES, PVC, PEVA</td><td>ND</td><td>[24]</td></tr><tr><td>Blood</td><td>60 °C 1h, enzymatic digest<br>proteinase K in 5 mM CaCl<sub>2</sub><br>2 50 °C, 20 min 60 °C</td><td>0.7 µm</td><td>pyGC-MS</td><td>ND</td><td>PMMA, PP, PS, PES, PET</td><td>1.6 µg/mL</td><td>[17]</td></tr><tr><td>Breastmilk</td><td>10 % KOH 40 °C 48 h</td><td>1.6 µm</td><td>Raman microspectroscopy</td><td>58</td><td>PE, PVC, PP, CPE, NC, PS, PC, PA, PES, ABS &lt; PEMA,<br>PEVA, PVOH</td><td>2.4 mp/g</td><td>[29]</td></tr><tr><td>Breastmilk</td><td>68 % Nitric acid 48 h RT,<br>then 95 °C 3 h</td><td>13 µm</td><td>LDIR</td><td>ND</td><td>PA, PU, PES, PET, PP, PVC, POM, EVA, PTFE, CPE, PS,<br>PMMA, PLA, polysulphones, polybutadiene</td><td>20.2 mp/g</td><td>[24]</td></tr><tr><td>Sputum</td><td>68 % concentrated nitric<br>acid 1 h, AnCl<sub>2</sub> density<br>separation</td><td>0.45 µm</td><td>µFTIR</td><td>565</td><td>Acrylate, acrylonitrile butadiene, alkyd varnish,<br>ethylene vinyl acetate, polyacetal, polybutadiene, PE,<br>PES, PI, chlorinated polyisoprene, PMMA, PP, PS, PU,<br>PVA, PVC, rubber, silicone, PC, PTFE</td><td>56.5 mp/mL</td><td>[90]</td></tr><tr><td>Saliva</td><td>35 % H2O2 for 2–10 days at<br>80 °C<br>ZnCl2 density separation</td><td>2 µm</td><td>Raman microspectroscopy</td><td>645</td><td>Not clearly described but spanning PP, PET, PP, PS,<br>PVC across skin, hair and saliva.</td><td>Circa. 0.33<br>MPs/<br>person/day</td><td>[91]</td></tr><tr><td>Placenta</td><td>10 % KOH, 50 °C, 3 days,<br>120 rpm</td><td>10 µm</td><td>LDIR</td><td>149</td><td>PVC, PP, PBS, PET, PC, PS, PA, PES, PSF, PE fibre</td><td>2.8 mp/g</td><td>[27]</td></tr><tr><td>Placenta</td><td>10 % KOH, room<br>temperature, 7 days</td><td>1.6 µm</td><td>Raman microspectroscopy</td><td>12</td><td>PP, others unknown only ID the pigment</td><td>ND</td><td>[26]</td></tr><tr><td>Placenta</td><td>30 % H<sub>2</sub>O<sub>2</sub>, 80 C, 7 weeks</td><td>0.2 µm</td><td>µFTIR</td><td>ND</td><td>PES, PP, PS, PU</td><td>ND</td><td>[89]</td></tr><tr><td>Lung tissue</td><td>Enzymatic COROLASE®<br>7089 digest, 12h 60 °C</td><td>0.45 µm</td><td>Raman microspectroscopy</td><td>31</td><td>PP, cotton, PES, CA, PVC, PS, PU, PA</td><td>ND</td><td>[18]</td></tr><tr><td>Lung tissue</td><td>30 % H<sub>2</sub>O<sub>2</sub>, 55 °C for 11 days</td><td>0.02 µm</td><td>µFTIR</td><td>39</td><td>PET, PP, PS, PTFE, TPE, Resin, PE, SEBS, PAN, PU,<br>PES, PMMA</td><td>0.69 mp/g</td><td>[19]</td></tr><tr><td>Colectomy<br>tissue</td><td>10 % KOH, 60 °C, 7–10 h</td><td>0.45 µm</td><td>µFTIR</td><td>3,638</td><td>PC, PA, PP</td><td>14.99 mp/g</td><td>[25]</td></tr><tr><td>Liver<sup>a</sup></td><td>40.5 % 10 M KOH + 6–14 %<br>hypochlorite (2:1 ratio)<br>40 °C 72 h</td><td>0.45 µm</td><td>Fluorescent microscopy<br>(NR), Raman<br>microspectroscopy</td><td>ND</td><td>PS, PVC, PET, PMMA, POM, PP<br>9 = unknown</td><td>3.2 mp/g</td><td>[92]</td></tr><tr><td>Kidney<sup>a</sup></td><td>40.5 % 10 M KOH + 6–14 %<br>hypochlorite (2:1 ratio)<br>40 °C 72 h</td><td>0.45 µm</td><td>Fluorescent microscopy<br>(NR), Raman<br>microspectroscopy</td><td>0</td><td>N/A</td><td>N/A</td><td>[92]</td></tr><tr><td>Spleen<sup>a</sup></td><td>40.5 % 10 M KOH + 6–14 %<br>hypochlorite (2:1 ratio)<br>40 °C 72 h</td><td>0.45 µm</td><td>Fluorescent microscopy<br>(NR), Raman<br>microspectroscopy</td><td>ND</td><td>PS, PVC, PET, PMMA, POM, PP<br>9 = unknown</td><td>0.9 mp/g</td><td>[92]</td></tr><tr><td>Saphenous<br>vein</td><td>30 % H<sub>2</sub>O<sub>2</sub> 60 °C 7 days 85 rpm</td><td>0.02 m</td><td>µFTIR</td><td>20</td><td>Resin, PVA, Ethylene, PU</td><td>29.28 mp/g</td><td>[93]</td></tr><tr><td>Face Skin</td><td>35 % H2O2 for 2–10 days at<br>80 °C<br>ZnCl2 density separation</td><td>2 µm</td><td>Raman microspectroscopy</td><td>4,265</td><td>Not clearly described but spanning PP, PET, PP, PS,<br>PVC across skin, hair and saliva.</td><td>Circa. 2.1<br>MPs/<br>person/day</td><td>[91]</td></tr><tr><td>Hand skin</td><td>35 % H2O2 for 2–10 days at<br>80 °C<br>ZnCl2 density separation</td><td>2 µm</td><td>Raman microspectroscopy</td><td>4,051</td><td>Not clearly described but spanning PP, PET, PP, PS,<br>PVC across skin, hair and saliva.</td><td>Circa. 2.0<br>MPs/<br>person/day</td><td>[91]</td></tr><tr><td>Hair</td><td>35 % H2O2 for 2–10 days at<br>80 °C<br>ZnCl2 density separation</td><td>2 µm</td><td>Raman microspectroscopy</td><td>7,462</td><td>Not clearly described but spanning PP, PET, PS, PVC<br>across skin, hair and saliva.</td><td>Circa. 3.5<br>MPs/<br>person/day</td><td>[91]</td></tr></tbody></table>

<footnote>a total of 56 samples seen across liver kidney and spleen in this single study, unclear which polymers were seen in which organ. ABS: acrylonitrile butadiene styrene, CPE: chlorinated polyethylene, EVA: ethylene vinyl acetate copolymer, NC: nitrocellulose, PAN: polyacrylonitrile, PC: polycarbonate, PEMA: poly(ethyl methacrylate), PES: polyester, PET: Polyethylene terephthalate, PEVA: polyethylene vinyl acetate, PI: polyimide, PLA: polylactic acid, PMMA: polymethylmethacrylate, POM: polyoxymethylene PP: polypropylene, PS: polystyrene, PTFE: polytetrafluoroethylene, PU: polyurethane, PVA: polyvinylacrylate, PVC: polyvinylchloride, PVOH: polyvinyl alcohol, SEBS: styrene-ethylene-butylene co-polymer, TPE: thermoplastic elastomer. In general, chemical methods are very efficient at removing biological debris and allowing for the recovery of MPs. However, there is a significant risk of damaging the MPs with this technique. These methods also require temperature control as they are exothermic, and peak temperature needs to remain below the glass transition temperature to avoid loss of MP [87].</footnote>
adequate controls and thresholds can be applied with minimal inter-
ference with organic matter that was not destroyed during the digestion
process [94,95]. While there is limited evidence to suggest it is possible
to identify the MP polymer due to differences in fluorescence, more in
depth chemical characterisation is required to have any confidence in
polymer ID [94]. In the one study of human samples that reported using
Nile red to detect MPs in liver, kidney and spleen samples, Nile red was
used to quantify the total number of MPs while Raman micro-
spectroscopy was used to identify the polymer.

3.2.1.2. Micro-FTIR. Micro-FTIR has grown to become one of the most predominant methods for the chemical characterisation of MPs in a wide range of human samples (Table 2). This technique combined FTIR spectroscopy with microscopy thus allowing both the chemical and physical characteristics of MPs to be determined in a single technique. In the case of human samples the MNPs are likely to be on the smaller side of the size scale, making micro-FTIR (µFTIR) more desirable due to its detection limit of down to 20 µm [96]. Scanning a large number of MNPs on a filter paper is well suited to focal plane array FTIR an automated imagine technique [96]. The studies so far on humans using µFTIR have been used for biofluids, faeces and tissue samples and been able to identify over 20 different polymers (Table 2).

3.2.1.3. *Confocal Raman*. Raman spectroscopy is a complementary vibrational method to FTIR and when combined with microscopy also allows chemical identification and visualisation of particles. Raman directs a laser at a MNP and measures the resulting excitation, the shift in frequency is indicative of the chemical and molecular basis of the substrate. When combined with microscopy it is possible to obtain polymer identified on particles as small at 1 µm [96]. Unlike FTIR the spectral libraries are note as well established and the quality and properties of the surface being analyses can significantly impact upon the quality of the obtained data [96]. Thus far in the study of human exposure to MNPs, Raman microspectroscopy has been applied to different biofluids, faeces and tissues and over 15 polymers have been identified.

3.2.1.4. Laser direct infrared spectroscopy. Laser direct infrared spec-
troscopy (LDIR) also known as quantum cascade laser-based hyper-
spectral infrared chemical imaging, is rapidly becoming the go-to optical
method for MP characterisation. Unlike micro FTIR, data acquisition is
quicker allowing a much greater sample throughput, 7 seconds to ac-
quire a spectrum vs >30 seconds compared to a focal plane array µFTIR,
and able to identify MPs down to 20 µM in size [97]. LDIR performs an
initial scan of the filter and then focuses solely on the identification of
particles excluding “empty space” [97]. However, LDIR offers a lower
resolution meaning that particles next to each other can be counted as a
single particle rather than 2 and the narrower wave length window
scanned means less data is being used to assign a polymer identify
compared to conventional µFTIR thus increasing the risk of misidenti-
fication [98]. Unlike µFTIR and Raman microspectroscopy, LDIR is a
relatively new technique to the field and has only been applied to faeces,
breast milk and placenta but has been able to identify over 15 different
polymers.

3.2.2. *Mass spectrometry*

3.2.2.1. Pyrolysis GC-MS. In recent years, there has been a significant shift in interest from simply quantifying the number of plastic particles to the identification of the polymer and their additives. As such, pyrolysis gas chromatography-mass spectrometry (pyGC-MS) has grown in popularity. This technique allows individual or collections of particles to be pyrolyzed before the evolved gas is trapped and injected onto a GC-MS platform for the separation and identification of the complex pyrolyte to confirm the identity of the polymer. The application of py-GC-MS to synthetic polymers has been extensively reviewed elsewhere [99].

This is a powerful technique which does not have the limitation asso-
ciated with optical detection such as colour or fluorescence and is also
capable of simultaneously being used to characterise additives within
the MNPs. Recent advances in this technology have allowed a more
extensive hyphenated system to be applied to MP analysis namely
thermogravimetric analysis-Fourier Transform Infra-Red -gas
chromatography-mass spectrometry (TGA-FTIR-GC-MS). This combined
both physical and chemical property characterisation of nanomaterials
but to date has been limited to environmental research [100,101].

3.2.2.2. spICP-MS. Single-particle Inductively Coupled Plasma-Mass Spectrometry (spICP-MS) has become an established yet highly specialised analytical tool in the nanoscientists arsenal. Here, nanoparticles are isolated from biological or environmental matrices, then sequentially introduced to a hot argon plasma to generate discrete pulses of ionised atoms relating to individual nanoparticles [102,103]. The intensity of the peaks generated by these pulses within short dwell times is used to determine the size of the ENM. Due to the part per trillion level dilution required for spICP-MS the application to the expected low environmentally relevant concentrations in humans is ideal [103–105]. The theory of spICP-Ms has been extensively reviewed elsewhere [102, 103].

In the case of MNPs the isolation methods that have been described previously are ideal for application to sp-ICP-MS. However, the analysis of MNPs is complicated by their carbon-based composition and the high levels of carbon from biological matrices and the air of this atmospheric ionisation method. Methods have been developed whereby nanoplastics are quantified by measuring discrete pulses of ¹³C but suffer from poor detection limits due to carbons high ionisation potential, interferences with ambient ¹³C from the samples and atmosphere [103,105]. Alternatively, it is possible to take advantage of the aged surface of nano-plastics to conjugate functionalized gold nanoparticles to enable a more sensitive detection with spICP-MS by quantifying the signal gold [106]. This was validated using a range of environmental waters and was well suited for the realistic environmental concentrations of nanoplastics [106]. These studies demonstrate spICP-MS to be a potentially exciting future prospect for the analysis of MNPs in human samples, but still remains a relatively specialised technique.

3.3. *Isolation of nanomaterials*

In a similar vein to MPs, the direct detection of ENMs initially de-
pends upon the isolation of the ENMs which gain is a balancing act
between removing unnecessary organic matrix while not dissolving any
of the ENM itself.

The isolation of ENMs typically revolves around digestion using an
alkaline solution or enzymatic degradation of the biological material.
Acidic digests are unsuitable as many of the most common metals in
ENMs such as gold and silver are readily dissolved in acid. This means
that only an ionic concentration for each metal can be ascertained with
all of the particulate information being lost. Ishizuka et al. [107] eval-
uated acidic, basic and proteinase K digests for the characterisation of
silver ENMs following Ag ENM dosing into mice and quantifying in liver
and blood. Both nitric and hydrochloric acid resulted in the loss of the
Ag ENMs due to dissolution. Ultimately NaOH was deemed the optimal
digest solution for recovery and maintaining particulate information
[107]. However, another study found enzymatic digest with proteinase
K and 0.5 % SDS was preferable than tetramethylammonium hydroxide
alkaline digest to characterise Ag ENMs in placenta ex-vivo.

3.3.1. *Detection of ENMs*

3.3.1.1. spICP-MS. Unlike with MNPs, spICP-MS has been extensively utilised for the characterisation of metallic NPs, typically in pristine form, Lee et al. validated detection limits for 40 elements with 7
recording a minimal diameter of detection <10 nm, 13 were between 11 and 20 nm, 17 between 21-80 nm and 3 were greater than 200 nm but less than 1000 nm [104].

To date, there have been several feasibility studies investigating the potential for spICP-MS to detect human exposures to ENMs. These methods have been applied to urine for Au [103], Ag [108,109], Pt [110] and TiO₂ [109,111] ENMs, blood products looking at Au [108, 112] and Ag [108,112] ENMs and placental tissue investigating Ag ENMs exposure with an ex-vivo model [113,114]. All of which return a very high degree of particle recoveries and particle number and diameters that reflect the properties of the particles used to dose the various matrices.

However, so far there has only been a single study utilising spICP-MS to characterise human exposure to ENMs using cadavers and taking the spleen and liver to quantify human exposure to TiO₂. Here fixed tissue samples were depolymerised and enzymatically digested with proteinase K prior to spICP-MS. TiO₂ NMs were detected in 47 % of liver samples and 93 % of spleen samples ranging between 85 and 720 nm in diameter. The composition of TiO₂ was confirmed by energy dispersive X-ray microanalysis (EDX), in addition, it was determined that 67 % of all Ti detected in the liver was in the form of TiO₂ NMs [115].

Realistically at the nanoscale range ICP-MS run in single particle mode is the likely to be the only reasonable high throughput method for the detection and quantification of nanoscale particulate matter to characterise this aspect of the particle exposome. The methods to achieve this have been growing over the past decade with a growing presence in the literature and the application of time-of-flight mass spectrometers allowing multi element ENM analysis.

### 3.3.1.2. Magnetic analysis.
Iron particulate matter within the body is a well-established biological process for iron storage. Indeed, this has been observed in the brain with elevated levels being associate with a range of neurological diseases [116–118].

Two studies have focussed upon combustion and friction derived magnetic air pollution nanoparticles in human brains and hearts. To differentiate from the naturally occurring magnetic nanoclusters, these groups investigate spherical magnetic nanoparticles as this form is the most common shape for combustion derived particles compared to the crystalline structure of biogenic particles [119,120]. These works used magnetometry to quantify the total magnetic content of the organs of freeze dried brain and heart material [119,120]. Both studies utilised donor tissues from deceased patients and used a papain enzymatic digest as a sample clean up method for confirmation of shape, size and composition using high resolution transmission electron microscopy in conjunction with EDX and electron energy loss spectroscopy (EELS) [119,120]. In the heart study, patients from metropolitan Mexico city had much higher numbers of nanoparticles in their hearts compared to control patients from a low pollution area [119]. In the case of the brain samples those with Alzheimer's disease and from areas of high airborne pollution typically had much higher numbers of nanoparticles in their brains [120].

These two studies in particular demonstrate the significance of the particle exposome for human health with iron nanoparticles being a known risk factor for Alzheimer's disease. Environmental factors such as pollution are also a significant risk factor for cardiovascular disease (CVD) and airborne nanoparticle pollution is a potential new avenue for research into CVD pathogenesis. However, the use of magnetic analysis is limited to only magnetic particles and precludes other materials, however the use of enzymatic digest and TEM with EELS and EDX can be used for any tissue samples to characterise ENM exposures.

## 4. Conclusion

With increasing concerns about the chemical pollution, some large research programs on HBM such as the US National Health and Nutrition

Evaluation Survey (NHANES), or more recently, the large-scale European Human Biomonitoring Initiative (HBM4EU) (followed by the Partnership for the Assessment of Risks from Chemicals – PARC initiative) have started to demonstrate that the general US and EU population are commonly exposed to metals, some persistent organic pollutants, solvents and ubiquitous non-persistent chemicals. Some gaps in knowledge remain, in particular for non-polar and ionic substances, and methods such as IC-MS/MS and CE-MS/MS could help to provide data at large scale as they present the advantages to be equally sensitive, often less timely (and costly) and more adapted to high-throughput (and to some extent “greener” than the conventional ones). Furthermore, these large HBM initiatives did not cover particulates such MNP and NP, which could be explained, to some extent, by the lack of expertise from the MS-based exposure community. Bridges could be made between the HBM programs and the current five EU research initiatives focusing on MNPs that have been united in one large cluster (CUSP cluster) in order to better understand exposure routes and hazard and risk assessment of MNP but also to develop new analytical tools.

The analysis of MNPs and ENMs currently presents a bit of a bottleneck in terms of throughput due to the sample processing step required to isolate the particles. Some of these methods are days long and require additional thought and development to try and expedite without losing particulate information. However, methods utilising spICP-MS are particularly well suited for high-throughput analysis with each element of interest taking less than 3 minutes to analyse, and can be automated using autosamplers. For polymer identification, methods such as LDIR offers a very high throughout high accuracy option, while pyGC-MS offers more in depth analysis of MNPs either on a particle by particle basis or as a collection and provide feedback on what polymers and additives are present.

Another understudied part of MNP that still remains to be addressed regards the plastic leachate (current plastics contain up to four hundred additives). In the case of MNP leachates, chemical exposomics science based on MS methodologies is well versed in the detection and characterisation of plasticisers such as bisphenols [121], flame retardants [122] and phthalates [123] in humans. However, it has typically assumed the exposure to these is via leaching into foodstuffs or from clothing as opposed to the inadvertent consumption of MNPs. This raises interesting possibilities due to the different mechanical and pH stresses particles may pass through following inhalation or ingestion meaning there may be localised concentration gradients which may have different impacts on human health [124,125]. It is hoped that this review could help bridge the gap between nanoscientists and MS-based HBM scientists particularly in the area of characterising the chemical leaching from MNPs to avoid duplicating work that has already been done in previous decades in HBM, but also providing methodological expertise, human cohorts and epidemiological backgrounds. On the other hand, nanoscientists who already interact with omics researchers for nanotoxicology and protein corona analysis offer a wealth of knowledge in particle characterisation and modelling of transport in biological systems.

### CRediT authorship contribution statement

**Andrew J. Chetwynd:** Writing – review & editing, Writing – original draft, Supervision, Methodology, Investigation, Conceptualization.
**Mari-Vorgan Louyer:** Writing – review & editing, Investigation.
**Fabien Mercier:** Writing – review & editing, Investigation.
**Vincent Besson-neau:** Writing – review & editing.
**Arthur David:** Writing – review & editing, Writing – original draft, Supervision, Methodology, Investigation, Conceptualization.

### Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence
the work reported in this paper.

## Data availability

No data was used for the research described in the article.

## Acknowledgments

A.J.C acknowledges funding from a tenure track fellowship from the Institute of Systems, Molecular and Integrative Biology, University of Liverpool. MVL, FM, VB and AD acknowledge the research infrastructure France Exposome.

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