Multi-Parameter Analysis of Nanoplastics in Flow: Taking Advantage of High Sensitivity and Time Resolution Enabled by Stimulated Raman Scattering.

Here, we demonstrate the detection of nanoplastics (NPLs) in flow with stimulated Raman scattering (SRS) for the first time. NPLs (plastic particles <1000 nm) have recently been detected in different environmental samples and personal care products. However, their characterization is still an analytical challenge. Multiple parameters, including size, chemical composition, and concentration (particle number and mass), need to be determined. In an earlier paper, online field flow fractionation (FFF)-Raman analysis with optical trapping was shown to be a promising tool for the detection of particles in this size range. SRS, which is based on the enhancement of a vibrational transition by the matching energy difference of two laser beams, would allow for much more sensitive detection and, hence, much shorter acquisition times compared to spontaneous Raman microspectroscopy (RM). Here, we show the applicability of SRS for the flow-based analysis of individual, untrapped NPLs. It was possible to detect polyethylene (PE), polystyrene (PS), and poly(methyl methacrylate) (PMMA) beads with diameters of 100-5000 nm. The high time resolution of 60.5 µs allows us to detect individual signals per particle and to correlate the number of detected particles to the injected mass concentration. Furthermore, due to the high time resolution, optically trapped beads could be distinguished from untrapped beads by their peak shapes. The SRS wavenumber settings add chemical selectivity to the measurement. Whereas optical trapping is necessary for the flow-based detection of particles by spontaneous RM, the current study demonstrates that SRS can detect particles in a flow without trapping. Additionally, the mean particle size could be estimated using the mean width (duration) and intensity of the SRS signals.

Towards a reference material for microplastics' number concentration-case study of PET in water using Raman microspectroscopy.

Increasing demand for size-resolved identification and quantification of microplastic particles in drinking water and environmental samples requires the adequate validation of methods and techniques that can be used for this purpose. In turn, the feasibility of such validation depends on the existence of suitable certified reference materials (CRM). A new candidate reference material (RM), consisting of polyethylene terephthalate (PET) particles and a water matrix, has been developed. Here, we examine its suitability with respect to a homogeneous and stable microplastic particle number concentration across its individual units. A measurement series employing tailor-made software for automated counting and analysis of particles (TUM-ParticleTyper 2) coupled with Raman microspectroscopy showed evidence of the candidate RM homogeneity with a relative standard deviation of 12% of PET particle counts involving particle sizes >30 µm. Both the total particle count and the respective sums within distinct size classes were comparable in all selected candidate RM units. We demonstrate the feasibility of production of a reference material that is sufficiently homogeneous and stable with respect to the particle number concentration.

TUM-ParticleTyper 2: automated quantitative analysis of (microplastic) particles and fibers down to 1 [Formula: see text]m by Raman microspectroscopy.

Accurate quantification of small microplastics in environmental and food samples is a prerequisite for studying their potential hazard. Knowledge of numbers, size distributions and polymer type for particles and fibers is particularly relevant in this respect. Raman microspectroscopy can identify particles down to 1 [Formula: see text]m in diameter. Here, a fully automated procedure for quantifying microplastics across the entire defined size range is presented as the core of the new software TUM-ParticleTyper 2. This software implements the theoretical approaches of random window sampling and on-the-fly confidence interval estimation during ongoing measurements. It also includes improvements to image processing and fiber recognition (when compared to the previous software TUM-ParticleTyper for analysis of particles/fibers [Formula: see text] [Formula: see text]m), and a new approach to adaptive de-agglomeration. Repeated measurements of internally produced secondary reference microplastics were evaluated to assess the precision of the whole procedure.

Physicochemical characterization and quantification of nanoplastics: applicability, limitations and complementarity of batch and fractionation methods.

A comprehensive physicochemical characterization of heterogeneous nanoplastic (NPL) samples remains an analytical challenge requiring a combination of orthogonal measurement techniques to improve the accuracy and robustness of the results. Here, batch methods, including dynamic light scattering (DLS), nanoparticle tracking analysis (NTA), tunable resistive pulse sensing (TRPS), transmission electron microscopy (TEM), and scanning electron microscopy (SEM), as well as separation/fractionation methods such as centrifugal liquid sedimentation (CLS) and field-flow fractionation (FFF)-multi-angle light scattering (MALS) combined with pyrolysis gas chromatography mass spectrometry (pyGC-MS) or Raman microspectroscopy (RM) were evaluated for NPL size, shape, and chemical composition measurements and for quantification. A set of representative/test particles of different chemical natures, including (i) polydisperse polyethylene (PE), (ii) (doped) polystyrene (PS) NPLs, (iii) titanium dioxide, and (iv) iron oxide nanoparticles (spherical and elongated), was used to assess the applicability and limitations of the selected methodologies. Particle sizes and number-based concentrations obtained by orthogonal batch methods (DLS, NTA, TRPS) were comparable for monodisperse spherical samples, while higher deviations were observed for polydisperse, agglomerated samples and for non-spherical particles, especially for light scattering methods. CLS and TRPS offer further insight with increased size resolution, while detailed morphological information can be derived by electron microscopy (EM)-based approaches. Combined techniques such as FFF coupled to MALS and RM can provide complementary information on physical and chemical properties by online measurements, while pyGC-MS analysis of FFF fractions can be used for the identification of polymer particles (vs. inorganic particles) and for their offline (semi)quantification. However, NPL analysis in complex samples will continue to present a serious challenge for the evaluated techniques without significant improvements in sample preparation.

Multi-element stable isotope Raman microspectroscopy of bacterial carotenoids unravels rare signal shift patterns and single-cell phenotypic heterogeneity.

The combination of single-cell Raman microspectroscopy (SCRM) and stable isotope probing (SIP) enables in situ tracking of carbon or hydrogen fluxes into microorganisms at the single-cell level. Therefore, it has high potential for the analysis of metabolic processes and biogeochemical cycles. However, especially for high throughput applications such as imaging or cell sorting, it is hampered by low Raman scattering intensities (and therefore long acquisition times). In order to overcome these limitations, this study brings forward a systematic investigation of Resonance Raman (RR) enhanced SCRM for SIP of bacterial carotenoids. Dynamic carbon uptake from 13C-glucose was successfully monitored and quantified utilizing 13C stable isotope-induced red-shifts of RR signals. High single-cell phenotypic heterogeneity was revealed in terms of carbon uptake and, unlike in previous studies, clear evidence for de novo synthesis of carotenoids was found. For the first time, hydrogen uptake into carotenoids was systematically investigated by deuterium labeling (providing a direct probe for metabolic activity of single cells). In carotenoid single-cell Resonance Raman (SCRR) spectra, a unique pattern of signal red-shifts and apparent blue-shifts was observed and quantitatively evaluated. Finally, a novel combined approach for simultaneous monitoring of carbon and hydrogen uptake revealed complementary effects in carotenoid SCRR spectra that can be analyzed in parallel. Overall, it was shown that the high RR intensity, simplicity of spectral features and straightforward signal processing make microbial carotenoids an ideal target for quantitative multi-element SIP, with great potential for high throughput applications.

Fructobacillus cardui sp. nov., isolated from a thistle (Carduus nutans) flower.

A Fructobacillus strain was isolated from the flower of a nodding thistle (Carduus nutans) collected in Bavaria, Germany. The strain is Gram-positive, rod-shaped, non-motile, non-sporulating, catalase- and oxidase-negative, and facultatively anaerobic. Growth can be detected at 10-37 °C and pH 4 to 9. The genome size is about 1.56 Mbp and the G+C content is 43.76 mol%. Assignment to the genus Fructobacillus was done by average nucleotide identity (ANI), 16S rRNA gene sequence and multilocus sequence analyses. Calculations of ANI and digital DNA-DNA hybridization values indicate a novel species with Fructobacillus tropaeoli DSM 23246T (93.58% ANI and 57.9 % dDDH) being its closest relative. Therefore, a new species named Fructobacillus cardui sp. nov. with TMW 2.2452T (=DSM 113480T=CECT 30515T) as type strain is proposed.

Microplastic sampling from wastewater treatment plant effluents: Best-practices and synergies between thermoanalytical and spectroscopic analysis.

Wastewater treatment plants (WWTPs) may represent point sources for microplastic discharge into the environment. Quantification of microplastic in effluents of WWTPs has been targeted by several studies although standardized methods are missing to enable a comparability of results. This study discusses theoretical and practical perspectives on best practices for microplastic sampling campaigns of WWTPs. One focus of the study was the potential for synergies between thermoanalytical and spectroscopic analysis to gain more representative sampling using the complementary information provided by the different analytical techniques. Samples were obtained before and after sand filtration from two WWTPs in Germany using cascade filtration with size classes of 5,000 - 100 µm, 100 - 50 µm, and 50 - 10 µm. For spectroscopic methods samples were treated by a Fenton process to remove natural organic matter, whereas TED-GC-MS required only sample extraction from the filter cascade. µFTIR spectroscopy was used for the 100 µm and 50 µm basket filters and µRaman spectroscopy was applied to analyze particles on the smallest basket filter (10 µm). TED-GC-MS was used for all size classes as it is size independent. All techniques showed a similar trend, where PE was consistently the most prominent polymer in WWTP effluents. Based on this insight, PE was chosen as surrogate polymer to investigate whether it can describe the total polymer removal efficiency of tertiary sand filters. The results revealed no significant difference (ANOVA) between retention efficiencies of tertiary sand filtration obtained using only PE and by analyzing all possible polymers with µFTIR and µRaman spectroscopy. Findings from this study provide valuable insights on advantages and limitations of cascade filtration, the benefit of complementary analyses, a suitable design for future experimental approaches, and recommendations for future investigations.

Chemical Analysis of Microplastics and Nanoplastics: Challenges, Advanced Methods, and Perspectives.

Microplastics and nanoplastics have become emerging particulate anthropogenic pollutants and rapidly turned into a field of growing scientific and public interest. These tiny plastic particles are found in the environment all around the globe as well as in drinking water and food, raising concerns about their impacts on the environment and human health. To adequately address these issues, reliable information on the ambient concentrations of microplastics and nanoplastics is needed. However, micro- and nanoplastic particles are extremely complex and diverse in terms of their size, shape, density, polymer type, surface properties, etc. While the particle concentrations in different media can vary by up to 10 orders of magnitude, analysis of such complex samples may resemble searching for a needle in a haystack. This highlights the critical importance of appropriate methods for the chemical identification, quantification, and characterization of microplastics and nanoplastics. The present article reviews advanced methods for the representative mass-based and particle-based analysis of microplastics, with a focus on the sensitivity and lower-size limit for detection. The advantages and limitations of the methods, and their complementarity for the comprehensive characterization of microplastics are discussed. A special attention is paid to the approaches for reliable analysis of nanoplastics. Finally, an outlook for establishing harmonized and standardized methods to analyze these challenging contaminants is presented, and perspectives within and beyond this research field are discussed.

Analysis of microplastics in drinking water and other clean water samples with micro-Raman and micro-infrared spectroscopy: minimum requirements and best practice guidelines.

Microplastics are a widespread contaminant found not only in various natural habitats but also in drinking waters. With spectroscopic methods, the polymer type, number, size, and size distribution as well as the shape of microplastic particles in waters can be determined, which is of great relevance to toxicological studies. Methods used in studies so far show a huge diversity regarding experimental setups and often a lack of certain quality assurance aspects. To overcome these problems, this critical review and consensus paper of 12 European analytical laboratories and institutions, dealing with microplastic particle identification and quantification with spectroscopic methods, gives guidance toward harmonized microplastic particle analysis in clean waters. The aims of this paper are to (i) improve the reliability of microplastic analysis, (ii) facilitate and improve the planning of sample preparation and microplastic detection, and (iii) provide a better understanding regarding the evaluation of already existing studies. With these aims, we hope to make an important step toward harmonization of microplastic particle analysis in clean water samples and, thus, allow the comparability of results obtained in different studies by using similar or harmonized methods. Clean water samples, for the purpose of this paper, are considered to comprise all water samples with low matrix content, in particular drinking, tap, and bottled water, but also other water types such as clean freshwater.

Which particles to select, and if yes, how many? : Subsampling methods for Raman microspectroscopic analysis of very small microplastic.

Micro- and nanoplastic contamination is becoming a growing concern for environmental protection and food safety. Therefore, analytical techniques need to produce reliable quantification to ensure proper risk assessment. Raman microspectroscopy (RM) offers identification of single particles, but to ensure that the results are reliable, a certain number of particles has to be analyzed. For larger MP, all particles on the Raman filter can be detected, errors can be quantified, and the minimal sample size can be calculated easily by random sampling. In contrast, very small particles might not all be detected, demanding a window-based analysis of the filter. A bootstrap method is presented to provide an error quantification with confidence intervals from the available window data. In this context, different window selection schemes are evaluated and there is a clear recommendation to employ random (rather than systematically placed) window locations with many small rather than few larger windows. Ultimately, these results are united in a proposed RM measurement algorithm that computes confidence intervals on-the-fly during the analysis and, by checking whether given precision requirements are already met, automatically stops if an appropriate number of particles are identified, thus improving efficiency. To provide quality control in the MP quantification by Raman microspectroscopy, a window subsampling and bootstrap protocol is presented, which can provide confidence intervals that enable the assessment of the reliability of the data. This is brought together with a proposed on-the-fly algorithm that assesses the precision during the measurement and stops at the optimal point.

TUM-ParticleTyper: A detection and quantification tool for automated analysis of (Microplastic) particles and fibers.

TUM-ParticleTyper is a novel program for the automated detection, quantification and morphological characterization of fragments, including particles and fibers, in images from optical, fluorescence and electron microscopy (SEM). It can be used to automatically select targets for subsequent chemical analysis, e.g., Raman microscopy, or any other single particle identification method. The program was specifically developed and validated for the analysis of microplastic particles on gold coated polycarbonate filters. Our method development was supported by the design of a filter holder that minimizes filter roughness and facilitates enhanced focusing for better images and Raman measurements. The TUM-ParticleTyper software is tunable to the user's specific sample demands and can extract the morphological characteristics of detected objects (coordinates, Feret's diameter min / max, area and shape). Results are saved in csv-format and contours of detected objects are displayed as an overlay on the original image. Additionally, the program can stitch a set of images to create a full image out of several smaller ones. An additional useful feature is the inclusion of a statistical process to calculate the minimum number of particles that must be chemically identified to be representative of all particles localized on the substrate. The program performance was evaluated on genuine microplastic samples. The TUM-ParticleTyper software localizes particles using an adaptive threshold with results comparable to the "gold standard" method (manual localization by an expert) and surpasses the commonly used Otsu thresholding by doubling the rate of true positive localizations. This enables the analysis of a statistically significant number of particles on the filter selected by random sampling, measured via single point approach. This extreme reduction in measurement points was validated by comparison to chemical imaging, applying both procedures to the same area at comparable processing times. The single point approach was both faster and more accurate proving the applicability of the presented program.

Simple Generation of Suspensible Secondary Microplastic Reference Particles via Ultrasound Treatment.

In the environment the weathering of plastic debris is one of the main sources of secondary microplastic (MP). It is distinct from primary MP, as it is not intentionally engineered, and presents a highly heterogeneous analyte composed of plastic fragments in the size range of 1 µm-1 mm. To detect secondary MP, methods must be developed with appropriate reference materials. These should share the characteristics of environmental MP which are a broad size range, multitude of shapes (fragments, spheres, films, fibers), suspensibility in water, and modified particle surfaces through aging (additional OH, C=O, and COOH). To produce such a material, we bring forward a rapid sonication-based fragmentation method for polystyrene (PS), polyethylene terephthalate (PET), and polylactic acid (PLA), which yields up to 105/15 mL dispersible, high purity MP particles in aqueous media. To satisfy the claim of a reference material, the key properties-composition and size distribution to ensure the homogeneity of the samples, as well as shape, suspensibility, and aging -were analyzed in replicates (N = 3) to ensure a robust production procedure. The procedure yields fragments in the range of 100 nm-1 mm (<20 µm, 54.5 ± 11.3% of all particles). Fragments in the size range 10 µm-1 mm were quantitatively characterized via Raman microspectroscopy (particles = 500-1,000) and reflectance micro Fourier transform infrared analysis (particles = 10). Smaller particles 100 nm-20 µm were qualitatively characterized by scanning electron microcopy (SEM). The optical microscopy and SEM analysis showed that fragments are the predominant shape for all polymers, but fibers are also present. Furthermore, the suspensibility and sedimentation in pure MilliQ water was investigated using ultraviolet-visible spectroscopy and revealed that the produced fragments sediment according to their density and that the attachment to glass is avoided. Finally, a comparison of the infrared spectra from the fragments produced through sonication and naturally aged MP shows the addition of polar groups to the surface of the particles in the OH, C=O, and COOH region, making these particles suitable reference materials for secondary MP.

Nanoplastic Analysis by Online Coupling of Raman Microscopy and Field-Flow Fractionation Enabled by Optical Tweezers.

Nanoplastic pollution is an emerging environmental concern, but current analytical approaches are facing limitations in this size range. However, the coupling of nanoparticle separation with chemical characterization bears potential to close this gap. Here, we realize the hyphenation of particle separation/characterization (field-flow fractionation (FFF), UV, and multiangle light scattering) with subsequent chemical identification by online Raman microspectroscopy (RM). The problem of low Raman scattering was overcome by trapping particles with 2D optical tweezers. This setup enabled RM to identify particles of different materials (polymers and inorganic) in the size range from 200 nm to 5 µm, with concentrations in the order of 1 mg/L (109 particles L-1). The hyphenation was realized for asymmetric flow FFF and centrifugal FFF, which separate particles on the basis of different properties. This technique shows potential for application in nanoplastic analysis, as well as many other fields of nanomaterial characterization.

Nondestructive Chemical Analysis of the Iron-Containing Protein Ferritin Using Raman Microspectroscopy.

Ferritin is a ubiquitous intracellular iron storage protein of animals, plants, and bacteria. The cavity of this protein acts like a reaction chamber for natural formation and storage of nano-sized particles via biomineralization. Knowledge of the chemical composition and structure of the iron core is highly warranted in the fields of nano technologies as well as biomolecules and medicine. Here, we show that Raman microspectroscopy (RM) is a suitable nondestructive approach for an analysis of proteins containing such nano-sized iron oxides. Our approach addresses: (1) synthesis of suitable reference materials, i.e., ferrihydrite, maghemite and magnetite nanoparticles; (2) optimization of parameters for Raman spectroscopic analysis; (3) comparison of Raman spectra from ferritin with apoferritin and our reference minerals; and (4) validation of Raman analysis by X-ray diffraction and Mössbauer spectroscopy as two independent complementary approaches. Our results reveal that the iron core of natural ferritin is composed of the iron(III) hydroxide ferrihydrite (Fe2O3 ∙ 0.5 H2O).

Comment on "exposure to microplastics (<10 µm) associated to plastic bottles mineral water consumption: The first quantitative study by Zuccarello et al. [Water Research 157 (2019) 365-371]".

Microplastics in food is a relatively new research field with only few studies available so far. Scientists have been pointing out that some of these studies apply questionable analytical methods. Nevertheless, media often use such results to gain attention of the readers. It is therefore of particular significance, that only those scientific studies are published, clearly presenting valid data on the content of microplastics in food. Unfortunately, the study by Zuccarello et al. shows very critical aspects regarding analytical methods used and conclusions made. The applied procedure is not described and, therefore, does not allow any assessment by other groups, which is indispensable prerequisite of any scientific publication. Moreover, the analytical method used for the identification and quantification of microplastic particles - SEM-EDX - is not sound and not validated. Therefore, in our opinion the results on the contamination of bottled mineral water with microplastics published by Zuccarello et al. are more than questionable.

Investigation of multiple polymers in a denitrifying sulfur conversion-EBPR system: The structural dynamics and storage states.

Polyhydroxyalkanoates (PHAs), polyphosphate (poly-P) and polysulfide or elemental sulfur (poly-S) are the key functionally relevant polymers involved in the recently reported Denitrifying Sulfur conversion-associated Enhanced Biological Phosphorus Removal (DS-EBPR) process. However, little is known about the structural dynamics and storage states of these polymers. In particular, investigating the poly-S generated in this process is quite a superior challenge. This study was thus aimed at simultaneously qualitative-quantitative investigating poly-S and associated poly-P and PHAs through the integrated chemical analysis and Raman micro-spectroscopy coupled with multiple microscopic methods (i.e. optical microscopy, confocal laser scanning microscopy, and differential interference contrast microscopy). The chemical analytical results displayed a stable DS-EBPR phenotype in terms of sulfur conversion, P release/uptake and the dynamics of relevant polymers. The multiple microscopic images and Raman spectrum profiles further clearly demonstrated the existence of the polymers and their dynamic changes under alternating anaerobic-anoxic conditions, consistent with the chemical analytical results. In particular, Raman analysis for the first time unraveled the co-existence of S0/Sn2- species stored either intracellularly or extracellularly; and the dynamic conversions between S0/Sn2- and other sulfur species suggest that there might be a universal pool of bioavailable sulfur. The results reveal the mechanisms underlying the structural dynamics and changes in storage states of the relevant polymers that are functionally relevant to the carbon/phosphorus/sulfur-cycles during different metabolic phases. These mechanisms would otherwise not be obtained only using a traditional chemical analysis-based approach.

Are We Speaking the Same Language? Recommendations for a Definition and Categorization Framework for Plastic Debris.

The accumulation of plastic litter in natural environments is a global issue. Concerns over potential negative impacts on the economy, wildlife, and human health provide strong incentives for improving the sustainable use of plastics. Despite the many voices raised on the issue, we lack a consensus on how to define and categorize plastic debris. This is evident for microplastics, where inconsistent size classes are used and where the materials to be included are under debate. While this is inherent in an emerging research field, an ambiguous terminology results in confusion and miscommunication that may compromise progress in research and mitigation measures. Therefore, we need to be explicit on what exactly we consider plastic debris. Thus, we critically discuss the advantages and disadvantages of a unified terminology, propose a definition and categorization framework, and highlight areas of uncertainty. Going beyond size classes, our framework includes physicochemical properties (polymer composition, solid state, solubility) as defining criteria and size, shape, color, and origin as classifiers for categorization. Acknowledging the rapid evolution of our knowledge on plastic pollution, our framework will promote consensus building within the scientific and regulatory community based on a solid scientific foundation.