Quantitative assessment of visual microscopy as a tool for microplastic research: Recommendations for improving methods and reporting

Microplastic and other anthropogenic microparticles in Arctic char (Salvelinus alpinus) and their coastal habitat: A first-look at a central Canadian Arctic commercial fishery

In the recent monitoring guidelines released by the Arctic Monitoring and Assessment Program's Litter and Microplastic Expert Group, Arctic salmonids were recommended as an important species for monitoring plastics in Arctic ecosystems, with an emphasis on aligning microplastic sampling and analysis methods in Arctic fishes. This recommendation was based on the minimal documentation of microplastics in Northern fishes, especially Arctic salmonids. In response, we worked collaboratively with local partners to quantify and characterize microplastics in Arctic char, Salvelinus alpinus, and their habitats in a commercial fishery near Iqaluktuuttiaq (Cambridge Bay), Nunavut. We sampled Arctic char, surface water, and benthic sediments within their summer foraging habitat at Palik (Byron Bay). We found microplastics in 95 % of char with an average of 26 (SD ± 19) particles per individual. On average, surface water samples had 23 (SD ± 12) particles/L and benthic sediment <1 particles/gww. This is the first documentation of plastic pollution in Arctic char and their coastal habitats. Future work should evaluate seasonal, temporal and spatial trends for long-term monitoring of microplastics in Arctic fishes and their habitats.

Nile red staining for rapid screening of plastic-suspect particles in edible seafood tissues

Concerns regarding microplastic (MP) contamination in aquatic ecosystems and its impact on seafood require a better understanding of human dietary MP exposure including extensive monitoring. While conventional techniques for MP analysis like infrared or Raman microspectroscopy provide detailed particle information, they are limited by low sample throughput, particularly when dealing with high particle numbers in seafood due to matrix-related residues. Consequently, more rapid techniques need to be developed to meet the requirements of large-scale monitoring. This study focused on semi-automated fluorescence imaging analysis after Nile red staining for rapid MP screening in seafood. By implementing RGB-based fluorescence threshold values, the need for high operator expertise to prevent misclassification was addressed. Food-relevant MP was identified with over 95% probability and differentiated from natural polymers with a 1% error rate. Comparison with laser direct infrared imaging (LDIR), a state-of-the-art method for rapid MP analysis, showed similar particle counts, indicating plausible results. However, highly variable recovery rates attributed to inhomogeneous particle spiking experiments highlight the need for future development of certified reference material including sample preparation. The proposed method demonstrated suitability of high throughput analysis for seafood samples, requiring 0.02-0.06 h/cm2 filter surface compared to 4.5-14.7 h/cm with LDIR analysis. Overall, the method holds promise as a screening tool for more accurate yet resource-intensive MP analysis methods such as spectroscopic or thermoanalytical techniques.

Pretreatment-free SERS sensing of microplastics using a self-attention-based neural network on hierarchically porous Ag foams

Low-cost detection systems are needed for the identification of microplastics (MPs) in environmental samples. However, their rapid identification is hindered by the need for complex isolation and pre-treatment methods. This study describes a comprehensive sensing platform to identify MPs in environmental samples without requiring independent separation or pre-treatment protocols. It leverages the physicochemical properties of macroporous-mesoporous silver (Ag) substrates templated with self-assembled polymeric micelles to concurrently separate and analyze multiple MP targets using surface-enhanced Raman spectroscopy (SERS). The hydrophobic layer on Ag aids in stabilizing the nanostructures in the environment and mitigates biofouling. To monitor complex samples with multiple MPs and to demultiplex numerous overlapping patterns, we develop a neural network (NN) algorithm called SpecATNet that employs a self-attention mechanism to resolve the complex dependencies and patterns in SERS data to identify six common types of MPs: polystyrene, polyethylene, polymethylmethacrylate, polytetrafluoroethylene, nylon, and polyethylene terephthalate. SpecATNet uses multi-label classification to analyze multi-component mixtures even in the presence of various interference agents. The combination of macroporous-mesoporous Ag substrates and self-attention-based NN technology holds potential to enable field monitoring of MPs by generating rich datasets that machines can interpret and analyze.

The distribution of sediment microplastics assemblages is driven by location and hydrodynamics, not sediment characteristics, in the Gulf of Maine, USA

Microplastics (MP) are found in marine sediments across the globe, but we are just beginning to understand their spatial distribution and assemblages. In this study, we quantified MP in Gulf of Maine, USA sediments. MP were extracted from 20 sediment samples, followed by polymer identification using Raman spectroscopy. We detected 27 polymer types and 1929 MP kg-1 wet sediment, on average. Statistical analyses showed that habitat, hydrodynamics, and station proximity were more important drivers of MP assemblages than land use or sediment characteristics. Stations closer to one another were more similar in their MP assemblages, tidal rivers had higher numbers of unique plastic polymers than open water or embayment stations, and stations closer to shore had higher numbers of MP. There was little evidence of relationships between MP assemblages and land use, sediment texture, total organic carbon, or contaminants.

Development of an accreditation process for analytical methods to measure microplastics in drinking water for regulatory monitoring

Development of a laboratory accreditation program to ensure competency of laboratories performing analytical measurements is a key step in adopting new analytical measurement methods for regulatory decision-making. Here, we describe California's three-part accreditation process for spectroscopically measuring microplastics in drinking water, and show how data from a multi-laboratory method comparison study informed development of accreditation programs for the resulting methods, which can inform analogous future work for other analytes. The first part is periodic performance evaluation (PE) samples, in which laboratories are provided blind samples of known composition to quantify within acceptable performance limits. The second is inspection, or audit, assessing whether the laboratory has the proper equipment to conduct the work and whether it is correctly employing proper procedures. The third is implementation of a quality management system providing documentation that protocols demonstrated during inspection are continuously maintained. These fell into three broad categories: instrument maintenance; laboratory cleanliness, especially important for microplastics and one that must be accompanied by a blanks measurement and correction process; and training so samples are being processed by qualified analysts. An intercomparison exercise among 22 laboratories was necessary to determine what parameter permutations were important for PE samples, and expected accuracy from competent laboratories. The recommended PE sample composition was two size categories (20-50um and 500um-1mm), two polymer types, and two morphologies (fibers and non-fibers). Discussions among intercomparison exercise participants were key in determining the factors that most contributed to laboratory variability, and the focus for both on-site inspections and quality management systems.

Development and validation of an acid/alkaline digestion method for efficient microplastic extraction from wastewater treatment plant effluents: Sulfuric acid concentration and contact time do matter

Accurate analysis of microplastic particles (MPs) in environmental samples requires removal of interferences during sample preparation. Wastewater samples are interference-rich and thus particularly challenging, with concentrated sulfuric acid currently deemed impractical as a reagent. Therefore, this study aimed to establish a straightforward, effective, and safe method employing concentrated sulfuric acid and potassium hydroxide to eliminate interferents from effluent samples obtained from wastewater treatment plants (WWTPs). We found that 80 % sulfuric acid at room temperature with a brief contact time of 5 min was viable through a qualitative spot test involving 37 plastics categorized into three types (I, II, and III) based on their polymer structure's oxygen position. A quantitative assessment revealed that treatments involving H2SO4 and KOH (20 %, 24 h, 48 °C), either separately or in combination, had no discernible physical impact on the overall plastics, except for a subtle one for Type III plastics (e.g., nylon and PMMA) known to be labile under harsh pH conditions. This acid/alkaline digestion (AAD) method, incorporating such conditions for H2SO4 and KOH treatments, yielded a high mass removal efficacy (97.8 ± 2.4 %, n = 13) for eliminating natural particle interferents for primary, secondary, and tertiary effluent samples. Furthermore, the AAD method allowed for the determination of MPs in effluents with high surrogate particle recoveries (e.g., 95.1 % for larger than 500 μm size fraction). This method is readily adaptable to create appropriate protocols for different types of environmental matrices.

Exposure of U.S. adults to microplastics from commonly-consumed proteins

We investigated microplastic (MP) contamination in 16 commonly-consumed protein products (seafoods, terrestrial meats, and plant-based proteins) purchased in the United States (U.S.) with different levels of processing (unprocessed, minimally-processed, and highly-processed), brands (1 - 4 per product type, depending on availability) and store types (conventional supermarket and grocer featuring mostly natural/organic products). Mean (±stdev) MP contamination per serving among the products was 74 ± 220 particles (ranging from 2 ± 2 particles in chicken breast to 370 ± 580 in breaded shrimp). Concentrations (MPs/g tissue) differed between processing levels, with highly-processed products containing significantly more MPs than minimally-processed products (p = 0.0049). There were no significant differences among the same product from different brands or store types. Integrating these results with protein consumption data from the American public, we estimate that the mean annual exposure of adults to MPs in these proteins is 11,000 ± 29,000 particles, with a maximum estimated exposure of 3.8 million MPs/year. These findings further inform estimations of human exposure to MPs, particularly from proteins which are important dietary staples in the U.S. Subsequent research should investigate additional drivers of MPs in the human diet, including other understudied food groups sourced from both within and outside the U.S.

No Effect of Realistic Concentrations of Polyester Microplastic Fibers on Freshwater Zooplankton Communities

Zooplankton are a conduit of energy from autotrophic phytoplankton to higher trophic levels, and they can be a primary point of entry of microplastics into the aquatic food chain. Investigating how zooplankton communities are affected by microplastic pollution is thus a key step toward understanding ecosystem-level effects of these global and ubiquitous contaminants. Although the number of studies investigating the biological effects of microplastics has grown exponentially in the last decade, the majority have used controlled laboratory experiments to quantify the impacts of microplastics on individual species. Given that all organisms live in multispecies communities in nature, we used an outdoor 1130-L mesocosm experiment to investigate the effects of microplastic exposure on natural assemblages of zooplankton. We endeavored to simulate an environmentally relevant exposure scenario by manually creating approximately 270 000 0.015 × 1- to 1.5-mm polyester fibers and inoculating mesocosms with zero, low (10 particles/L), and high (50 particles/L) concentrations. We recorded zooplankton abundance and community composition three times throughout the 12-week study. We found no effect of microplastics on zooplankton abundance, Shannon diversity, or Pielou's evenness. Nonmetric multidimensional scaling plots also revealed no effects of microplastics on zooplankton community composition. Our study provides a necessary and realistic baseline on which future studies can build. Because numerous other stressors faced by zooplankton (e.g., food limitation, eutrophication, warming temperatures, pesticides) are likely to exacerbate the effects of microplastics, we caution against concluding that polyester microfibers will always have no effect on zooplankton communities. Instead, we encourage future studies to investigate the triple threats of habitat degradation, climate warming, and microplastic pollution on zooplankton community health. Environ Toxicol Chem 2024;43:418-428. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Application of Pattern Recognition and Computer Vision Tools to Improve the Morphological Analysis of Microplastic Items in Biological Samples

Since, in many routine analytical laboratories, a stereomicroscope coupled with a digital camera is not equipped with advanced software enabling automatic detection of features of observed objects, in the present study, a procedure of feature detection using open-source software was proposed and validated. Within the framework of applying microscopic expertise coupled with image analysis, a set of digital images of microplastic (MP) items identified in organs of fish was used to determine shape descriptors (such as length, width, item area, etc.). The edge points required to compute shape characteristics were set manually in digital images acquired by the camera coupled with a binocular, and respective values were computed via the use of built-in MotiConnect software. As an alternative, a new approach consisting of digital image thresholding, binarization, the use of connected-component labeling, and the computation of shape descriptors on a pixel level via using the functions available in an OpenCV library or self-written in C++ was proposed. Overall, 74.4% of the images were suitable for thresholding without any additional pretreatment. A significant correlation was obtained between the shape descriptors computed by the software and computed using the proposed approach. The range of correlation coefficients at a very high level of significance, according to the pair of correlated measures, was higher than 0.69. The length of fibers can be satisfactorily approximated using a value of half the length of the outer perimeter (r higher than 0.75). Compactness and circularity significantly differ for particles and fibers.

The influence of complex matrices on method performance in extracting and monitoring for microplastics

Previous studies have evaluated method performance for quantifying and characterizing microplastics in clean water, but little is known about the efficacy of procedures used to extract microplastics from complex matrices. Here we provided 15 laboratories with samples representing four matrices (i.e., drinking water, fish tissue, sediment, and surface water) each spiked with a known number of microplastic particles spanning a variety of polymers, morphologies, colors, and sizes. Percent recovery (i.e., accuracy) in complex matrices was particle size dependent, with ∼60-70% recovery for particles >212 μm, but as little as 2% recovery for particles <20 μm. Extraction from sediment was most problematic, with recoveries reduced by at least one-third relative to drinking water. Though accuracy was low, the extraction procedures had no observed effect on precision or chemical identification using spectroscopy. Extraction procedures greatly increased sample processing times for all matrices with the extraction of sediment, tissue, and surface water taking approximately 16, 9, and 4 times longer than drinking water, respectively. Overall, our findings indicate that increasing accuracy and reducing sample processing times present the greatest opportunities for method improvement rather than particle identification and characterization.

Quantifying microplastic ingestion, degradation and excretion in insects using fluorescent plastics

Plastic pollution is a growing threat to our natural environment. Plastic waste/pollution results from high emissions of both macro (>5 mm) and microplastics (MPs; <5 mm) as well as environmental fractioning of macroplastics into MPs. MPs have been shown to have a range of negative impacts on biota. Harmonized methods to accurately measure and count MPs from animal samples are limited, but what methods exist are not ideal for a controlled laboratory environment where plastic ingestion, degradation and elimination can be quantified and related to molecular, physiological and organismal traits. Here, we propose a complete method for isolating and quantifying fluorescent MPs by combining several previously reported approaches into one comprehensive workflow. We combine tissue dissection, organic material digestion, sample filtering and automated imaging techniques to show how fluorescently labelled MPs provided to insects (e.g. in their diet) in a laboratory setting can be isolated, identified and quantified. As a proof of concept, we fed crickets (Gryllodes sigillatus) a diet of 2.5% (w/w) fluorescently labelled plastics and isolated and quantified plastic particles within the gut and frass.

How to establish detection limits for environmental microplastics analysis

Establishing analytical detection limits is crucial. Common methods to do so are suitable only for variables with continuous distributions. Because count data for microplastic particles is a discrete variable following the Poisson distribution, currently-used approaches for estimating the detection limit in microplastics analysis are inadequate. Here we evaluate detection limits with techniques for low-level discrete observations to develop proper approaches for estimating the minimum detectable amount (MDA) in microplastic particle analysis, using blank sample data from an interlaboratory calibration exercise for clean water (representing drinking water), dirty water (ambient water), sediment (porous media) and fish tissue (biotic tissues). Two MDAs are applicable: MDA_A to evaluate analytical methods, estimated with replicate blank data; and MDA_B for individual sample batches, calculated with a single blank count. For illustrative purposes, this dataset's overall MDA_A values were 164 counts (clean water), 88 (dirty water), 192 (sediment), and 379 (tissue). MDA values should be reported on a laboratory-specific basis and for individual size fractions, as this provides more useful information about capabilities of individual laboratories. This is due to wide variation in blank levels, as noted by MDA_B values (i.e., among different laboratories) from 14 to 158 (clean water), 9 to 86 (dirty water, 9 to 186 (sediment), and 9 to 247 (tissue). MDA values for fibers were considerably greater than for non-fibers, suggesting that separate MDA values should be reported. This study provides a guideline for estimation and application of microplastics MDA for more robust data to support research activities and environmental management decisions.

Assessment of filter subsampling and extrapolation for quantifying microplastics in environmental samples using Raman spectroscopy

A common method for characterizing microplastics (MPs) involves capturing the plastic particles on a filter after extraction and isolation from the sediment particles. Microplastics captured on the filter are then scanned with Raman spectroscopy for polymer identification and quantification. However, scanning the whole filter manually using Raman analysis is a labor-intensive and time-consuming process. This study investigates a subsampling method for Raman spectroscopic analysis of microplastics (operationally defined here as 45-1000 μm in size) present in sediments and isolated onto laboratory filters. The method was evaluated using spiked MPs in deionized water and two environmentally contaminated sediments. Based on statistical analyses, we found quantification of a sub-fraction of 12.5 % of the filter in a wedge form was optimal, efficient, and accurate for estimating the entire filter count. The extrapolation method was then used to assess microplastic contamination in sediments from different marine regions of the United States.

Innovative reference materials for method validation in microplastic analysis including interlaboratory comparison exercises

Reference materials (RMs) are vital tools in the validation of methods used to detect environmental pollutants. Microplastics, a relatively new environmental pollutant, require a variety of complex approaches to address their presence in environmental samples. Both interlaboratory comparison (ILC) studies and RMs are essential to support the validation of methods used in microplastic analysis. Presented here are results of quality assurance and quality control (QA/QC) performed on two types of candidate microplastic RMs: dissolvable gelatin capsules and soda tablets. These RMs have been used to support numerous international ILC studies in recent years (2019-2022). Dissolvable capsules containing polyethylene terephthalate (PET), polyvinyl chloride (PVC), polyethylene (PE), and polystyrene (PS), in different size fractions from 50 to 1000 µm, were produced for one ILC study, obtaining relative standard deviation (RSD) from 0 to 24%. The larger size fraction allowed for manual addition of particles to the capsules, yielding 0% error and 100% recovery during QA/QC. Dissolvable capsules were replaced by soda tablets in subsequent ILC studies and recovery test exercises because they were found to be a more reliable carrier for microplastic RMs. Batches of soda tablets were produced containing different single and multiple polymer mixtures, i.e., PE, PET, PS, PVC, polypropylene (PP), and polycarbonate (PC), with RSD ranging from 8 to 21%. Lastly, soda tablets consisting of a mixture of PE, PVC, and PS (125-355 µm) were produced and used for recovery testing during pretreatment of environmental samples. These had an RSD of 9%. Results showed that soda tablets and capsules containing microplastics >50 µm could be produced with sufficient precision for internal recovery tests and external ILC studies. Further work is required to optimize this method for smaller microplastics (< 50 µm) because variation was found to be too large during QA/QC. Nevertheless, this approach represents a valuable solution addressing many of the challenges associated with validating microplastic analytical methods.

Presence of microplastics and microparticles in Oregon Black Rockfish sampled near marine reserve areas

Measuring the spatial distribution of microparticles which include synthetic, semi-synthetic, and anthropogenic particles is critical to understanding their potential negative impacts on species. This is particularly important in the context of microplastics, which are a form of microparticle that are prevalent in the marine environment. To facilitate a better understanding of microparticle occurrence, including microplastics, we sampled subadult and young juvenile Black Rockfish (Sebastes melanops) at multiple Oregon coast sites, and their gastrointestinal tracts were analyzed to identify ingested microparticles. Of the subadult rockfish, one or more microparticles were found in the GI tract of 93.1% of the fish and were present in fish from Newport, and near four of five marine reserves. In the juveniles, 92% of the fish had ingested one or more microparticles from the area of Cape Foulweather, a comparison area, and Otter Rock, a marine reserve. The subadults had an average of 7.31 (average background = 5) microparticles detected, while the juveniles had 4.21 (average background = 1.8). In both the subadult and juvenile fish, approximately 12% of the microparticles were identified as synthetic using micro-Fourier Infrared Spectroscopy (micro-FTIR). Fibers were the most prevalent morphology identified, and verified microparticle contamination was a complex mixture of synthetic (∼12% for subadults and juveniles), anthropogenic (∼87% for subadults and 85.5% for juveniles), and natural (e.g., fur) materials (∼0.7% for subadults and ∼2.4% for juveniles). Similarities in exposure types (particle morphology, particle number) across life stages, coupled with statistical differences in exposure levels at several locations for subadult fish, suggest the potential influence of nearshore oceanographic patterns on microparticle distribution. A deeper understanding of the impact microplastics have on an important fishery such as those for S. melanops, will contribute to our ability to accurately assess risk to both wildlife and humans.

What determines accuracy of chemical identification when using microspectroscopy for the analysis of microplastics?

Fourier transform infrared (FTIR) and Raman microspectroscopy are methods applied in microplastics research to determine the chemical identity of microplastics. These techniques enable quantification of microplastic particles across various matrices. Previous work has highlighted the benefits and limitations of each method and found these to be complimentary. Within this work, metadata collected within an interlaboratory method validation study was used to determine which variables most influenced successful chemical identification of un-weathered microplastics in simulated drinking water samples using FTIR and Raman microspectroscopy. No variables tested had a strong correlation with the accuracy of chemical identification (r = ≤0.63). The variables most correlated with accuracy differed between the two methods, and include both physical characteristics of particles (color, morphology, size, polymer type), and instrumental parameters (spectral collection mode, spectral range). Based on these results, we provide technical recommendations to improve capabilities of both methods for measuring microplastics in drinking water and highlight priorities for further research. For FTIR microspectroscopy, recommendations include considering the type of particle in question to inform sample presentation and spectral collection mode for sample analysis. Instrumental parameters should be adjusted for certain particle types when using Raman microspectroscopy. For both instruments, the study highlighted the need for harmonization of spectral reference libraries among research groups, including the use of libraries containing reference materials of both weathered plastic and natural materials that are commonly found in environmental samples.

Critical gaps in nanoplastics research and their connection to risk assessment

Reports of plastics, at higher levels than previously thought, in the water that we drink and the air that we breathe, are generating considerable interest and concern. Plastics have been recorded in almost every environment in the world with estimates on the order of trillions of microplastic pieces. Yet, this may very well be an underestimate of plastic pollution as a whole. Once microplastics (<5 mm) break down in the environment, they nominally enter the nanoscale (<1,000 nm), where they cannot be seen by the naked eye or even with the use of a typical laboratory microscope. Thus far, research has focused on plastics in the macro- (>25 mm) and micro-size ranges, which are easier to detect and identify, leaving large knowledge gaps in our understanding of nanoplastic debris. Our ability to ask and answer questions relating to the transport, fate, and potential toxicity of these particles is disadvantaged by the detection and identification limits of current technology. Furthermore, laboratory exposures have been substantially constrained to the study of commercially available nanoplastics; i.e., polystyrene spheres, which do not adequately reflect the composition of environmental plastic debris. While a great deal of plastic-focused research has been published in recent years, the pattern of the work does not answer a number of key factors vital to calculating risk that takes into account the smallest plastic particles; namely, sources, fate and transport, exposure measures, toxicity and effects. These data are critical to inform regulatory decision making and to implement adaptive management strategies that mitigate risk to human health and the environment. This paper reviews the current state-of-the-science on nanoplastic research, highlighting areas where data are needed to establish robust risk assessments that take into account plastics pollution. Where nanoplastic-specific data are not available, suggested substitutions are indicated.