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.