Data preprocessing & evaluation used in the microplastics identification process: A critical review & practical guide

Integrating automated machine learning and metabolic reprogramming for the identification of microplastic in soil: A case study on soybean

The accumulation of polyethylene microplastic (PE-MPs) in soil can significantly impact plant quality and yield, as well as affect human health and food chain cycles. Therefore, developing rapid and effective detection methods is crucial. In this study, traditional machine learning (ML) and H2O automated machine learning (H2O AutoML) were utilized to offer a powerful framework for detecting PE-MPs (0.1 %, 1 %, and 2 % by dry soil weight) and the co-contamination of PE-MPs and fomesafen (a common herbicide) in soil. The development of the framework was based on the results of the metabolic reprogramming of soybean plants. Our study stated that traditional ML exhibits lower accuracy due to the challenges associated with optimizing complex parameters. H2O AutoML can accurately distinguish between clean soil and contaminated soil. Notably, H2O AutoML can detect PE-MPs as low as 0.1 % (with 100 % accuracy) and co-contamination of PE-MPs and fomesafen (with 90 % accuracy) in soil. The VIP and SHAP analyses of the H2O AutoML showed that PE-MPs and the co-contamination of PE-MPs and fomesafen significantly interfered with the antioxidant system and energy regulation of soybean. We hope this study can provide a reliable scientific basis for sustainable development of the environment.

Identification of common textile microplastics via autofluorescence spectroscopy coupled with k-means cluster analysis

Microplastics are an emerging anthropogenic pollutant risk with a significant body of research dedicated to understanding the implications further. To generate the databases required to characterize the impact of microplastics on our environment, and improve recovery and recycling of current plastic materials, we need rapid, in-line characterization that can distinguish individual polymer types. Here, autofluorescence spectroscopy was investigated as an alternative characterization method to the current leading techniques based on vibrational spectroscopy. It was confirmed that the autofluorescence of seven common textile polymers (acrylic, polyester, nylon, polyethylene, polypropylene, cellulose/cotton, wool) arose due to the cluster-triggered emission phenomenon. Both simulated polymer aging via photooxidation and dyeing of the polymers were found to affect the resultant autofluorescence spectra. A total of 1485 spectra from 39 unique sample groups (polymer type, colour, and degree of photooxidation) were analysed via machine learning (k-means cluster analysis). Correct identification of the polymer type was achieved in 71% of the cases from only eight input values (normalized intensity values at three autofluorescence emission wavelengths, the total autofluorescence emission intensity, the sample RGB colour values, and the sample shape). This represents a significant step towards automated polymer identification at the sub-second time scales required for the in-line characterization of microplastics.

An automatic method for accurate signal-to-noise ratio estimation and baseline correction of Raman spectra of environmental microplastics

In this study, we introduced a k-iterative double sliding-window (DSW^k) method for the estimation of spectral noise, signal-to-noise ratio (SNR), and baseline correction. The performance was evaluated using simulated spectra and compared against other commonly employed methods. Convergent evaluation determined that a k value of 20 strikes an optimal balance between convergence and computational intensity. The DSW^k method demonstrated outstanding performance across different spectral types (flat baseline, baseline with elevation, baseline with fluctuation, baseline with elevation and fluctuation) coupled with SNR values from 10 to 1000, achieving results that ranged from 1.01 to 1.08 times of the reference value in estimating spectral noise. It also showed that the estimated SNR values are 0.89 to 0.93 times of the reference value, demonstrating a 74.5 % - 131.7 % improvement over the conventional method in spectra with elevated and/or fluctuating baselines. Additionally, the DSW^k method proved effective in correcting baselines and identifying polymers in environmental samples of polyethylene (PE), polypropylene (PP), and polystyrene (PS), despite the limitation of reducing the peak height in spectra with low SNR. This method offers the potential to enhance the automatic and accurate evaluation of spectral quality and could assist in the development of guidelines for more rapid parameter adjustments in Raman measurements.

Spectral analysis of environmental microplastic polyethylene (PE) using average spectra

In this study, microplastic samples from surface seawater of Tokyo Bay were collected, polyethylene (PE) microplastics were used to calculate carbonyl index (CI), and average spectra of PE were analyzed and compared with a previous study applying agitation during chemical treatment. It was found that PE and polypropylene (PP) were the predominant polymer type in the samples. Among PE samples, fragments were the most commonly observed shape, with white being the dominant color. Deviations were found in the average spectra among different shapes and colors when compared to the standard PE spectrum. A comparison of the average spectra between the two datasets suggests that pronounced peaks related to oxidation are most likely resulted from agitation during the chemical treatment. Additionally, it was found a closer spectral resemblance between the sample spectra and the spectrum of standard sample of oxidized PE (PEOx) than with the standard PE spectrum, suggesting that using the oxidized PE as a reference spectrum might be more effective for identification. These findings highlight the complex factors affecting the spectral properties of microplastics and highlight the importance of understanding these variations to enhance the accuracy of microplastic identification workflows and understanding of environmental fate of microplastics.

Incidence of microplastic contamination in fishes of the Ramsar Wetland, Loktak - The world's only floating lake from the Indian Himalayan region

Microplastics are ubiquitous, and their widespread prevalence in the ecosphere has generated concerns about their potential effects on terrestrial and aquatic organisms. However, studies pertaining to ecologically sensitive freshwater ecosystems, such as Ramsar wetlands, is scarce. Therefore, the study was conducted in Loktak, the world's only floating lake, and one of the largest wetland in the Indian Himalayan region. The wetland's degradation and pollution have resulted its inclusion in the Montreux Record, underscoring the need for studying this eco-sensitive freshwater system. This work investigated the (i) abundance, morphotype and size of microplastics in fish, and (ii) chemical composition of the microplastics consumed and accumulated in the fish of Loktak lake. Fish samples representing eight species were collected and analyzed for microplastics. Results revealed that ∼91% of the sampled fish ingested microplastics. Fragment was identified as the predominant morphotype (∼82%). Plastic polymers including polyamide (PA), polystyrene (PS), polycarbonate (PC) and carboxymethyl cellulose (CMC) were detected. The occurrence of heavy metals - chlorine (Cl), palladium (Pd), sodium (Na), zinc (Zn), lead (Pb) and copper (Cu) suggests their adhesion on the microplastics. The occurrence of microplastics in fish indicates pollution in the lake and poses a potential health risks to humans through consumption. Therefore, implementing comprehensive management approaches is imperative to mitigate this emerging pollution and uphold the ecological integrity of the Ramsar site. Substantial information on microplastics and their potential human exposure through fish consumption, particularly in the Indian Himalayan region, remains to be assessed, underscoring the need for extensive study.

Comparison of ATR-FTIR and NIR spectroscopy for identification of microplastics in biosolids

Biosolids are considered a potentially major input of microplastics (MPs) to agricultural soils. Our study aims to identify the polymeric origin of MPs extracted from biosolid samples by comparing their Attenuated Total Reflection (ATR) - Fourier-transform infrared (FTIR) spectra with the corresponding near-infrared (NIR) spectra. The reflectance spectra were preprocessed by Savitzky-Golay (SG), first derivative (FD) and compared with analogous spectra acquired on a set of fifty-two selected commercial plastic (SCP) materials collected from readily available products. According to the results portrayed in radar chart and built from both ATR-FTIR and NIR spectral datasets, the MPs showed high correlations with polymers such as polyethylene (LDPE, HDPE), polyethylene terephthalate (PET), polystyrene (PS), polypropylene (PP) and polyamide (PA), determined in SCP samples. Each unknown MP sample had on average three or more links to several types of SCP, according to the correlation coefficients for each polymer ranging from 0.7 up to 1. The comparison analysis classified the majority of MPs as composed mainly by LDPE/HDPE, according to the top correlation coefficients (r > 0.90). PP and PET were better identified with NIR than ATR-FTIR. In contrast to ATR-FTIR analysis, NIR was unable to identify PS. Based on these results, the primary sources of MPs in the biosolids could be identified as discarded consumer packaging (containers, bags, bottles) and fibers from laundry, disposable glove, and cleaning cloth. SYNOPSIS: Microplastics (MPs) are considered contaminants of emerging concern. This study compares two simple and fast spectroscopy techniques to identify microplastics in the biosolid matrix.

Micro- and nano-plastics in the atmosphere: A review of occurrence, properties and human health risks

The ubiquitous occurrence of micro/nano plastics (MNPs) poses potential threats to ecosystem and human health that have attracted broad concerns in recent decades. Detection of MNPs in several remote regions has implicated atmospheric transport as an important pathway for global dissemination of MNPs and hence as a global health risk. In this review, the latest research progress on (1) sampling and detection; (2) origin and characteristics; and (3) transport and fate of atmospheric MNPs was summarized. Further, the current status of exposure risks and toxicological effects from inhaled atmospheric MNPs on human health is examined. Due to limitations in sampling and identification methodologies, the study of atmospheric nanoplastics is very limited today. The large spatial variation of atmospheric MNP concentrations reported worldwide makes it difficult to compare the overall indoor and outdoor exposure risks. Several in vitro, in vivo, and epidemiological studies demonstrate adverse effects of immune response, apoptosis and oxidative stress caused by MNP inhalation that may induce cardiovascular diseases and reproductive and developmental abnormalities. Given the emerging importance of atmospheric MNPs, the establishment of standardized sampling-pretreatment-detection protocols and comprehensive toxicological studies are critical to advance environmental and health risk assessments of atmospheric MNPs.

Microplastic pollution on historic facades: Hidden 'sink' or urban threat?

Despite the increasing concerns surrounding the health and environmental risks of microplastics (MPs), the research focus has primarily been on their prevalence in air and the oceans, consequently neglecting their presence on urban facades, which are integral to our everyday environments. Therefore, there is a crucial knowledge gap in comprehending urban MP pollution. Our pioneering interdisciplinary study not only quantifies but also identifies MPs on historic facades, revealing their pervasive presence in a medium-sized urban area in the UK. In this case study, we estimated a mean density of 975,000 fibres/m^2 (0.10 fibres/mm^2) for fibre lengths between 30 and 1000 μm with a ratio of 1:5 for natural to artificial fibres. Our research identifies three groups of fibre length frequencies across varied exposure scenarios on the investigated urban facade. Sheltered areas (4m height) show a high prevalence of 60-120 μm and 180-240 μm fibres. In contrast, less sheltered areas at 3m exhibit lower fibre frequencies but similar lengths. Notably, the lowest area (2-1.5m) features longer fibres (300-1000 μm), while adjacent area S, near a faulty gutter, shows no fibres, highlighting the impact of exposure, altitude, and environmental variables on fibre distribution on urban facades. Our findings pave one of many necessary paths forward to determine the long-term fate of these fibres and provoke a pertinent question: do historic facades serve as an urban 'sink' that mitigates potentially adverse health impacts or amplifies the effects of mobile microplastics? Addressing MP pollution in urban areas is crucial for public health and sustainable cities. More research is required to understand the multi-scale factors behind MP pollution in large cities and to find mitigation strategies, paving the way for effective interventions and policies against this growing threat.

Mitigating tire wear particles and tire additive chemicals in stormwater with permeable pavements

6PPD-quinone (6PPDQ) is a recently discovered chemical that is acutely toxic to coho salmon (Oncorhynchus kisutch) and can form via environmental exposure of 6PPD, a compound found extensively in tire wear particles (TWPs). TWPs deposited on roads are transported to aquatic ecosystems via stormwater, contributing to microplastic pollution and organic contaminant loads. However, little is known about the fate of TWPs and their leachable contaminants in these systems. We conducted three experiments at a high school in Tacoma, Washington, to quantify the treatment performance of permeable pavement (PP) formulations, a type of green stormwater infrastructure (GSI), for TWPs and ten tire-associated contaminants, including 6PPDQ. The PPs comprised concrete and asphalt, with and without cured carbon fibers, to improve the mechanical properties of PPs. Pavements were artificially dosed and had underdrains to capture effluent. Three experiments were conducted to evaluate PP mitigation of tire-associated pollution using cryomilled tire particles (cTPs). The 1st and 3rd experiments established a baseline for TWPs and contaminants and assessed the potential for continued pollutant release. During experiment 2, cTPs were applied to each pavement. Our results showed that the PPs attenuated >96 % of the deposited cTPs mass. An estimated 52-100 % of potentially leachable 6PPDQ was removed by the PP systems between the influent and effluent sampling stations. Background 6PPDQ concentrations in effluents ranged from 0 to 0.0029 μg/L. Effluent 6PPDQ concentrations were not explained by effluent TWP concentrations in experiments 1 or 2 but were significantly correlated in experiment 3, suggesting that leaching of 6PPDQ from TWPs retained in the pavement was minimal during a subsequent storm. Our results suggest that PPs may be an effective form of GSI for mitigating tire-associated stormwater pollution. The improved strength offered by cured carbon fiber-amended pavements extends PP deployment on high-traffic roadways where tire-associated pollution poses the greatest environmental risk.

A beaker method for determination of microplastic concentration by micro-Raman spectroscopy

Fourier-transform infrared (FT-IR) spectroscopy method for measuring small microplastic (SMP) concentration in marine environment is time-consuming and labor-intensive due to sample pre-treatment. In contrast, Raman spectroscopy is less influenced by water and can directly measure SMP samples in water, making it a more efficient method to measure SMP concentration. Therefore, a method that can directly estimate the concentration of SMPs in water was developed, and the relationship between SMP concentration and experimental Raman spectra were established by testing with standard polyethylene (PE) samples. It was found that average spectra acquired in water solution could reflect characteristic peaks of the plastic after baseline correction. Further investigation found that there is a significant functional relationship between correlation coefficient of sample spectra and the concentration of PE particles, and such relationship can be modelled by Langmuir model. The empirical functional relationships can be used to estimate SMP concentrations by measuring average Raman spectra. The developed methodology is helpful for developing rapid SMP identification and monitoring methods in a more complex manner.•A method of directly measuring MP concentration in water is proposed.•Experimental procedures are provided.•Data analysis methods are outlined.

FRDA: Fingerprint Region based Data Augmentation using explainable AI for FTIR based microplastics classification

Marine microplastics (MPs) contamination has become an enormous hazard to aquatic creatures and human life. For MP identification, many Machine learning (ML) based approaches have been proposed using Attenuated Total Reflection Fourier Transform Infrared Spectroscopy (ATR-FTIR). One major challenge for training MP identification models now is the imbalanced and inadequate samples in MP datasets, especially when these conditions are combined with copolymers and mixtures. To improve the ML performance in identifying MPs, data augmentation method is an effective approach. This work utilizes Explainable Artificial Intelligence (XAI) and Gaussian Mixture Models (GMM) to reveal the influence of FTIR spectral regions in identifying each type of MPs. Based on the identified regions, this work proposes a Fingerprint Region based Data Augmentation (FRDA) method to generate new FTIR data to supplement MP datasets. The evaluation results show that FRDA outperforms the existing spectral data augmentation approaches.

Challenges of Raman spectra to estimate carbonyl index of microplastics: A case study with environmental samples from sea surface

This study investigates the feasibility of using the carbonyl index (CI) derived from Raman spectra as an indicator of plastic degradation and its relationship with the CI calculated from Fourier transform infrared (FTIR) spectra, using microplastic samples of polyethylene (PE) from surface seawater. Multiple methods were used to calculate the CI values of FTIR spectra, while proposed methods were used to calculate the corresponding CI values of Raman spectra. Some significant relations between FTIR CI and Raman CI were observed. However, small R2 values suggest weak functional relationships, which can be attributed to the low signal-to-noise ratio (SNR) of Raman spectra. These results highlight the challenges of establishing a functional relationship between FTIR CI and Raman CI, including challenges such as the uniformity of Raman spectra, determining optimal Raman measurement parameters, selecting appropriate peaks for Raman CI calculation, deciding on spectral processing methods, and addressing the interdependence of these issues.

Development of automated microplastic identification workflow for Raman micro-imaging and evaluation of the uncertainties during micro-imaging

In this study, an automated identification workflow for Raman micro-imaging (RMI) was developed, and the performance was evaluated by artificial samples of microplastic (MP) microsphere with different sizes and types. Theoretical detection rate and estimated particle size were derived and compared with experimental data. Results show that the proposed workflow can identify plastic types and estimate the size of the MP microspheres under different conditions for most cases. However, size of laser spot and discrepancy between sample surface and focal plane can influence RMI results in two ways. Firstly, small particles are more likely to be detected. Secondly, estimated sizes of particles are more likely to be overestimated. The derived uncertainties can serve as a reference for future experimental design and further investigation of more complex situations. The workflow is accessible online, and interested researchers can adjust the parameter values as necessary to suit their specific circumstances.

A double sliding-window method for baseline correction and noise estimation for Raman spectra of microplastics

When measuring microplastics of environmental samples, additives and attachment of biological materials may result in strong fluorescence in Raman spectra, which increases difficulty for imaging, identification, and quantification. Although there are several baseline correction methods available, user intervention is usually needed, which is not feasible for automated processes. In current study, a double sliding-window (DSW) method was proposed to estimate the baseline and standard deviation of noise. Simulated spectra and experimental spectra were used to evaluate the performance in comparison with two popular and widely used methods. Validation with simulated spectra and spectra of environmental samples showed that DSW method can accurately estimate the standard deviation of spectral noise. DSW method also showed better performance than compared methods when handling spectra of low signal-to-noise ratio (SNR) and elevated baselines. Therefore, DSW method is a useful approach for preprocessing Raman spectra of environmental samples and automated processes.

Localisation and identification of polystyrene particles in tissue sections using Raman spectroscopic imaging

The uptake of microplastic particles (MPP) by organisms is frequently described and poses a potential risk for these organisms and ultimately for humans either through direct uptake or trophic transfer. Currently, the in-situ detection of MPP in organisms is typically based on histological examination of tissue sections after uptake of fluorescently-labelled MPP and is thus not feasible for environmental samples. The alternative approach is purification of MPP from whole organisms or organs by chemical digestion and subsequent spectroscopic detection (FT-IR or Raman). While this approach is feasible for un-labelled particles it goes along with loss of any spatial information related to the location in the tissue. In our study we aimed at providing a workflow for the localisation and identification of non-fluorescent and fluorescent polystyrene (PS) particles (fragments, size range 2-130 μm) in tissue sections of the model organism Eisenia fetida with Raman spectroscopic imaging (RSI). We provide methodological approaches for the preparation of the samples, technical parameters for the RSI measurements and data analysis for PS differentiation in tissue sections. The developed approaches were combined in a workflow for the in-situ analysis of MPP in tissue sections. The spectroscopic analysis requires differentiation of spectra of MPP and interfering compounds, which is challenging given the complexity of tissue. Therefore, a classification algorithm was developed to differentiate PS particles from haem, intestinal contents and surrounding tissue. It allows the differentiation of PS particles from protein in the tissue of E. fetida with an accuracy of 95%. The smallest PS particle detected in the tissue was 2 μm in diameter. We show that it is possible to localise and identify non-fluorescent and fluorescent ingested PS particles directly in tissue sections of E. fetida in the gut lumen and the adjacent tissue.

Comparison of learning models to predict LDPE, PET, and ABS concentrations in beach sediment based on spectral reflectance

Microplastic (MP) contamination on land has been estimated to be 32 times higher than in the oceans, and yet there is a distinct lack of research on soil MPs compared to marine MPs. Beaches are bridges between land and ocean and present equally understudied sites of microplastic pollution. Visible-near-infrared (vis-NIR) has been applied successfully for the measurement of reflectance and prediction of low-density polyethylene (LDPE), polyethylene terephthalate (PET), and polyvinyl chloride (PVC) concentrations in soil. The rapidity and precision associated with this method make vis-NIR promising. The present study explores PCA regression and machine learning approaches for developing learning models. First, using a spectroradiometer, the spectral reflectance data was measured from treated beach sediment spiked with virgin microplastic pellets [LDPE, PET, and acrylonitrile butadiene styrene (ABS)]. Using the recorded spectral data, predictive models were developed for each microplastic using both the approaches. Both approaches generated models of good accuracy with R² values greater than 0.7, root mean squared error (RMSE) values less than 3 and mean absolute error (MAE) < 2.2. Therefore, using this study's method, it is possible to rapidly develop accurate predictive models without the need of comprehensive sample preparation, using the low-cost option ASD HandHeld 2 VNIR Spectroradiometer.

Congruence Concept for Comparison of Spectra

This paper introduces an alternative, easy-to-implement spectrum comparison concept. The evaluation procedure is illustrated by artificial and attenuated total reflection Fourier transform infrared (ATR FT-IR) spectra, which it can also be extended to other spectrometries (e.g., ultraviolet-visible or UV-Vis and Raman). The evaluation for the comparison of two spectra is divided into four phases: (i) spectrum pre-treatment (e.g., smoothing and background correction), (ii) standard normal variate (SNV) transformation, (iii) regression analysis of SNV spectra, and (iv) calculation of the quantification index (FG). The FG is derived from the formula of R². It characterizes and quantifies the identity and/or similarity of the compared spectra.

Sampling strategies and analytical techniques for assessment of airborne micro and nano plastics

The atmosphere is pervasively polluted by microplastics and nano plastics (M/NPs) released into indoor and outdoor areas. However, various methodologies and their limitations along with non-standardization make the comparison of information concerning their prevalence difficult. Such diversity in techniques greatly limits the interpretation of results. Herein, We extracted data from publications on PubMed and Embase database up to the year 2022 regarding sampling strategies, identification methods, and reporting data for M/NPs quantification. In this review, 5 major areas for measuring airborne M/NPs have been identified including pre-sampling/ sampling/ post-sampling/ analysis/ and contamination avoidance. There are many challenges specific to each of those sections that need to be resolved through further method development and harmonization. This review mainly focuses on the different methods for collecting atmospheric M/NPs and also the analytical tools which have been used for their identification. While passive sampling is the most user-friendly method, the most precise and reproducible approach for collecting plastic particles is an active method which is directly followed by visual counting as the most common physical analysis technique. Polymers collected using visual sorting are most frequently identified by spectroscopy (FTIR; Raman). However, destructive analytical techniques (thermal degradation) also provide precise chemical information. In all cases, the methods were screened for advantages, limitations, and fieldwork abilities. This review outlines and critiques knowledge gaps, and recommendations to support standardized and comparable future research.

Detection methods of micro and nanoplastics

Plastics and related contaminants (including microplastics; MPs and nanoplastics; NPs) have become a serious global safety issue due to their overuse in many products and applications and their inadequate management, leading to possible leakage into the environment and eventually to the food chain and humans. There is a growing literature reporting on the occurrence of plastics, (MPs and NPs) in both marine and terrestrial organisms, with many indications about the harmful impact of these contaminants on plants and animals, as well as potential human health risks. The presence of MPs and NPs in many foods and beverages including seafood (especially finfish, crustaceans, bivalves, and cephalopods), fruits, vegetables, milk, wine and beer, meat, and table salts, has become popular research areas in recent years. Detection, identification, and quantification of MPs and NPs have been widely investigated using a wide range of traditional methods, such as visual and optical methods, scanning electron microscopy, and gas chromatography-mass spectrometry, but these methods are burdened with a number of limitations. In contrast, spectroscopic techniques, especially Fourier-transform infrared spectroscopy and Raman spectroscopy, and other emerging techniques, such as hyperspectral imaging are increasingly being applied due to their potential to enable rapid, non-destructive, and high-throughput analysis. Despite huge research efforts, there is still an overarching need to develop reliable analytical techniques with low cost and high efficiency. Mitigation of plastic pollution requires establishing standard and harmonized methods, adopting holistic approaches, and raising awareness and engaging the public and policymakers. Therefore, this chapter focuses mainly on identification and quantification techniques of MPs and NPs in different food matrices (mostly seafood).

No evidence of microplastic ingestion in emperor penguin chicks (Aptenodytes forsteri) from the Atka Bay colony (Dronning Maud Land, Antarctica)

Microplastic (<5 mm; MP) pollution has been an emerging threat for marine ecosystems around the globe with increasing evidence that even the world's most remote areas, including Antarctica, are no longer unaffected. Few studies however, have examined MP in Antarctic biota, and especially those from Antarctic regions with low human activity, meaning little is known about the extent to which biota are affected. The aim of this study was to investigate, for the first time, the occurrence of MP in the emperor penguin (Aptenodytes forsteri), the only penguin species breeding around Antarctica during the austral winter, and an endemic apex predator in the Southern Ocean. To assess MP ingestion, the gizzards of 41 emperor penguin chicks from Atka Bay colony (Dronning Maud Land, Antarctica), were dissected and analyzed for MP >500 μm using Attenuated Total Reflection Fourier-transform Infrared (ATR-FTIR) spectroscopy. A total of 85 putative particles, mostly in the shape of fibers (65.9 %), were sorted. However, none of the particles were identified as MP applying state-of-the-art methodology. Sorted fibers were further evidenced to originate from contamination during sample processing and analyses. We find that MP concentrations in the local food web of the Weddell Sea and Dronning Maud Land coastal and marginal sea-ice regions; the feeding grounds to chick-rearing emperor penguin adults, are currently at such low levels that no detectable biomagnification is occurring via trophic transfer. Being in contrast to MP studies on other Antarctic and sub-Antarctic penguin species, our comparative discussion including these studies, highlights the importance for standardized procedures for sampling, sample processing and analyses to obtain comparable results. We further discuss other stomach contents and their potential role for MP detection, as well as providing a baseline for the long-term monitoring of MP in apex predator species from this region.

Screening of polymer types and chemical weathering in macro- and meso-plastics found on lake and river beaches using a combined chemometric approach

In the environment, synthetic polymers, commonly known as "plastics", are well-known to undergo various chemical weathering processes, which modify their surface chemistry by introducing new functional groups. Such changes are important to monitor, as they can severely influence the toxicity caused by plastic debris. Therefore, in this study, two chemometric models are proposed to accelerate the chemical classification of macro- and meso-plastics found in the environment. For this purpose, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were applied on preprocessed infrared spectra of 83 plastic fragments found on public lake and river beaches. HCA associated all beach samples with a known plastic, whereas PCA enabled the association of only 39.8% (33 out of 83) of the beach samples with a known plastic. However, both techniques agreed on 93.9% of the samples identified. According to PCA and HCA results, polypropylene and polyethylene were the most frequently identified polymers in the samples. PCA turned out to be a very promising tool for fast screening of weathered plastics, since the distance of samples from the polypropylene cluster in the PCA plot was correlated with weathering. This was later confirmed by employing other characterization techniques such as micro-Raman, X-ray photoelectron spectroscopy and scanning electron microscopy. Finally, future experiments should focus on the applicability of the proposed combined chemometric approach for very small microplastics (<100 μm), as they have more important effects than larger plastics on aquatic ecosystems.

Alcohol Pretreatment to Eliminate the Interference of Micro Additive Particles in the Identification of Microplastics Using Raman Spectroscopy

Raman spectroscopy is an indispensable tool in the analysis of microplastics smaller than 20 μm. However, due to its limitation, Raman spectroscopy may be incapable of effectively distinguishing microplastics from micro additive particles. To validate this hypothesis, we characterized and compared the Raman spectra of six typical slip additives with polyethylene and found that their hit quality index values (0.93-0.96) are much higher than the accepted threshold value (0.70) used to identify microplastics. To prevent this interference, a new protocol involving an alcohol treatment step was introduced to successfully eliminate additive particles and accurately identify microplastics. Tests using the new protocol showed that three typical plastic products (polyethylene pellets, polyethylene bottle caps, and polypropylene food containers) can simultaneously release microplastic-like additive particles and microplastics regardless of the plastic type, daily-use scenario, or service duration. Micro additive particles can also adsorb onto and modify the surfaces of microplastics in a manner that may potentially increase their health risks. This study not only reveals the hidden problem associated with the substantial interference of additive particles in microplastic detection but also provides a cost-effective method to eliminate this interference and a rigorous basis to quantify the risks associated with microplastic exposure.

Characterization of foamed plastic litter on Danish reference beaches - Pollution assessment and multivariate exploratory analysis

Foamed litter comprise a significant amount of the pollution at beaches globally. This group represents a variety of foamed items and fragments originating from different applications and sources. Although foamed plastic contributes importantly to the marine environmental pollution, there is generally limited knowledge of the composition of this litter pool. The aim of this study was to characterize item types and polymer materials of foamed litter from six Danish reference beaches during the period 2018-2021. The foamed litter were classified into ten categories, including identifiable items, as well as fragments of foamed PS, or pieces of other foamed polymers of rigid or flexible sponges. Foamed PS (42%) and PUR (49%) were identified as the dominant polymers by FTIR analysis. Multivariate exploratory analysis was performed to investigate PUR foam, and specific spectra features for rigid and flexible foam were demonstrated. Furthermore, we assessed different correlation methods for identification of PUR foams.

A Simple Sample Preparation Method to Significantly Improve Fourier Transform Infrared (FT-IR) Spectra of Microplastics

Spectroscopic analysis has become an essential part of the rapidly growing field of microplastic (MP) research. Here, we introduce a simple sample preparation method that dramatically improves results from Fourier transform infrared (FT-IR) analysis of MP and other environmental fibers. Our method provides cost-effective, reliable, high-quality spectra that achieve high-matching scores to polymer libraries. The efficacy of this method is demonstrated with two environmental datasets from Singapore and Phnom Penh that were collected while sampling for atmospheric MPs. The method developed and applied in this study is a simplification of the KBr method, where the analyzed fiber is pressed to a thickness of <10 μm; however, no KBr powder is required. For the combined dataset, 379 non-pressed fibers were analyzed with 193 (51%) returning a search score of ≥80% (chosen minimum search score threshold) and 259 pressed fibers, with 254 (98%) returning a search score of ≥80%. Direct comparisons of fibers before and after pressing show that the highest individual search score, and average search score from multiple single-point measurements, is overwhelmingly higher following our method. Our method immobilizes and improves the surface of the fiber, by creating a wider and uniform area for measurements. For FT-IR operators, this saves considerable time, improves reliability of the analysis, and, importantly, provides reproducibility of the spectra generated.

Microplastics in two German wastewater treatment plants: Year-long effluent analysis with FTIR and Py-GC/MS

Microplastics (MP) have been recorded in various environments around the globe. For a better understanding of distribution patterns and for providing a basis for risk assessments, detailed data on MP concentrations and polymer compositions are required. This study investigated the effluents of two German wastewater treatment plants (WWTP) monthly over one year, in order to better understand their temporal input of MP into the receiving river systems. MP item data down to 11 μm were obtained by means of Fourier Transform Infrared (FTIR) spectroscopy under the application of an improved polymer database. Complementary mass data were obtained by pyrolysis gas chromatography-mass spectrometry (Py-GC/MS) (for one WWTP). Both FTIR and Py-GC/MS analysis revealed a homogeneous polymer composition over the year, with a general dominance of polyolefins. Elevated MP item and mass concentrations (maximum: 3 × 10⁴ items m^-3 and 3.8 × 10³ μg m^-3) were observed during winter months and were accompanied by either heavy rainfall (increased discharge and total organic carbon) or elevated turbidity values. These observations emphasize the need for the assessment of background parameters in future MP monitoring studies. By providing monthly data over one year on MP items and masses in WWTP effluents, this study helps enhancing the understanding of temporal MP dynamics and can act as a valuable reference point for future assessments.

Abundance and characteristics of microplastics in treated organic wastes of Kaunas and Alytus regional waste management centres, Lithuania

The widespread use of plastic without the sustainable management of the plastic waste has led to its accumulation in the environment. The presence of microplastics even in drinking water and food products is of immense concern. This situation is getting even more complicated due to the limited knowledge about the sources of microplastics and their impact on the environment and human health. This article focuses on a poorly understood but potentially significant source of microplastic-treated organic waste. Quantitative and qualitative analyses of microplastics down to 50 µm in the stabilised organic waste (SOW) output after mixed municipal solid waste (MSW) processing and green and food composts are presented in the article. Nile Red staining and FTIR analysis were adopted for the identification of microplastics. The highest average microplastic abundance was found in the SOW: 17407 ± 1739 particles kg^-1 in autumn and 15400 ± 1217 particles kg^-1 in winter. Nevertheless, even separately collected treated organic waste contained a significant amount of microplastics. Green compost contained 5733 ± 850 particles kg^-1 in autumn and 6433 ± 751 particles kg^-1 in winter, while food compost 3783 ± 351 particles kg^-1 in autumn and 4066 ± 658 particles kg^-1 in winter. Microplastics < 1 mm accounted for 83.8-94.9% of all microplastics, which reflects the need to control not only large but also small microplastics in organic waste fertilisers to prevent soil pollution. The dominant shape of microplastics in compost samples was films, while in the SOW, it was fragments. Based on morphological and FTIR analyses, the majority of microplastics in green and food composts were considered as the residuals of plastic bags and packaging materials.

Emerging investigator series: microplastic sources, fate, toxicity, detection, and interactions with micropollutants in aquatic ecosystems - a review of reviews

Hundreds of review studies have been published focusing on microplastics (MPs) and their environmental impacts. With the microbiota colonization of MPs being firmly established, MPs became an important carrier for contaminants to step inside the food web all the way up to humans. Thus, the continuous feed of MPs into the ecosystem has sparked a multitude of scientific concerns about their toxicity, characterization, and interactions with microorganisms and other contaminants. The reports of common subthemes have agreed about many findings and research gaps but also showed contradictions about others. To unravel these equivocal conflicts, we herein compile all the major findings and analyze the paramount discrepancies among these review papers. Furthermore, we systematically reviewed all the highlights, research gaps, concerns, and future needs. The covered focus areas of MPs' literature include the sources, occurrence, fate, existence, and removal in wastewater treatment plants (WWTPs), toxicity, interaction with microbiota, sampling, characterization, data quality, and interaction with other co-contaminants. This study reveals that many mechanisms of MPs' behavior in aquatic environments like degradation and interaction with microbiota are yet to be comprehended. Furthermore, we emphasize the critical need to standardize methods and parameters for MP characterization to improve the comparability and reproducibility of the incoming research.

Characterizing photochemical ageing processes of microplastic materials using multivariate analysis of infrared spectra

Microplastics in the environment are an emerging concern due to impacts on human and environmental health. In addition to direct effects on biota, microplastics influence the fate and distribution of trace organic contaminants through sorption and transport. Environmental weathering may influence the rate and extent of chemical sorption. Changes in the surface characteristics of four common plastics including low-density polyethylene (LDPE), high-density polyethylene (HDPE), polypropylene (PP), and polystyrene (PS) were followed under the influence of both artificial light (UV-B) and natural sunlight for up to six months. Attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectra were collected at regular intervals. Principal component analysis (PCA) of the full dataset of UV-B weathered samples (n >500 spectra) simultaneously discriminated plastic type and extent of photochemical weathering. The magnitude of PCA scores correlated with exposure time and the loadings were consistent with surface chemistry changes including photooxidation. Projecting sunlight and UV-C exposed samples onto this PCA model demonstrated that similar chemical changes occurred, albeit at different rates. The results were compared to the carbonyl index (CI) with similar weathering trends indicating PP weathered at a faster initial rate than LDPE and HDPE. We propose that a multivariate approach is more widely applicable than CI as illustrated by PS, which lacked a stable reference peak. Kinetic analysis of the time series indicated that outdoor weathering occurred 5-12 times slower than the artificial exposure used here, depending on the plastic and the light source employed. The results provide unique insights into weathering processes and the photochemical age of naturally weathered plastics.

Micro-Nano Plastic in the Aquatic Environment: Methodological Problems and Challenges

Microplastic research has become a buzz word. It is seen as one of the most pressing issues of Anthropocene contamination. There is certainly no doubt about the ubiquitous presence of microplastic (MP) in almost all environmental matrices. However, the validity of considering them as a vector for contaminants needs some reconsideration, there are other more potent pathways. Their effect on marine biota also calls for some realistic experiments with environmental concentrations of MP and nanoplastic (NP). It has been observed that in most published literature, polymer characterization is performed. Is it necessary to do, or will merely finding and confirming the particle as plastic suffice for environmental research? Harmonization of protocols is necessary, and there is likely a need for some inter-laboratory comparison exercises in order to produce comparable data and reliable assessments across regions. Samples collected from the same area using different techniques show an order of magnitude difference in MP concentration. The issue of nanoplastic is more contentious; are we technologically ready to identify NP in environmental samples?

Training and evaluating machine learning algorithms for ocean microplastics classification through vibrational spectroscopy

Microplastics are contaminants of emerging concern - not only environmental, but also to human health. Characterizing them is of fundamental importance to evaluate their potential impacts and target specific actions aiming to reduce potential harming effects. This study extends the exploration of machine learning classification algorithms applied to FTIR spectra of microplastics collected at sea. A comparison of successful classification models was made in order to evaluate prediction performance for 13 classes of polymers. A rigorous methodology was applied using a pipeline scheme to avoid bias in the training and selection phases. The application of an oversampling technique also contributed by compensating unbalanceness in the dataset. The log-loss was used as the minimization function target and to assess performance. In our analysis, Support Vector Machine Classifier provides a good relationship between simplicity and performance, for a fast and useful automatic characterization of microplastics.

A Children's Health Perspective on Nano- and Microplastics

BACKGROUND

Pregnancy, infancy, and childhood are sensitive windows for environmental exposures. Yet the health effects of exposure to nano- and microplastics (NMPs) remain largely uninvestigated or unknown. Although plastic chemicals are a well-established research topic, the impacts of plastic particles are unexplored, especially with regard to early life exposures.

OBJECTIVES

This commentary aims to summarize the knowns and unknowns around child- and pregnancy-relevant exposures to NMPs via inhalation, placental transfer, ingestion and breastmilk, and dermal absorption.

METHODS

A comprehensive literature search to map the state of the science on NMPs found 37 primary research articles on the health relevance of NMPs during early life and revealed major knowledge gaps in the field. We discuss opportunities and challenges for quantifying child-specific exposures (e.g., NMPs in breastmilk or infant formula) and health effects, in light of global inequalities in baby bottle use, consumption of packaged foods, air pollution, hazardous plastic disposal, and regulatory safeguards. We also summarize research needs for linking child health and NMP exposures and address the unknowns in the context of public health action.

DISCUSSION

Few studies have addressed child-specific sources of exposure, and exposure estimates currently rely on generic assumptions rather than empirical measurements. Furthermore, toxicological research on NMPs has not specifically focused on child health, yet children's immature defense mechanisms make them particularly vulnerable. Apart from few studies investigating the placental transfer of NMPs, the physicochemical properties (e.g., polymer, size, shape, charge) driving the absorption, biodistribution, and elimination in early life have yet to be benchmarked. Accordingly, the evidence base regarding the potential health impacts of NMPs in early life remains sparse. Based on the evidence to date, we provide recommendations to fill research gaps, stimulate policymakers and industry to address the safety of NMPs, and point to opportunities for families to reduce early life exposures to plastic. https://doi.org/10.1289/EHP9086.

μATR-FTIR Spectral Libraries of Plastic Particles (FLOPP and FLOPP-e) for the Analysis of Microplastics

Raman spectral libraries specific to microplastics demonstrated improved spectral matching results when weathered plastics and a variety of particle colors and morphologies were included. Here, we explore if this is true for Fourier transform infrared (FTIR) spectroscopy as well. We present two novel databases specific to microplastics using attenuated total reflection (μATR-FTIR): (1) an FTIR library of plastic particles (FLOPP), containing 186 spectra from common plastic items, across 14 polymer types and (2) an FTIR library of plastic particles sourced from the environment (FLOPP-e), containing 195 spectra across 15 polymer types. Both libraries include particles from a variety of sources, morphologies, and colors. We demonstrate the applicability of these libraries for microplastics research by comparing spectral match results from two microplastic datasets. For this, we use different combinations of libraries including: commercially available reference libraries, an open-access polymer library, and FLOPP and FLOPP-e. Among tests, the greatest mean HQI result was achieved when the greatest number of libraries was included. This work demonstrates that spectral libraries specific to plastic particles found in the environment improve the accuracy of spectral matching and are best used in combination with commercial libraries containing chemical components that are commonly found within plastics and other anthropogenic particles. Multivariate principal component analyses of FLOPP and FLOPP-e spectra confirmed differences among polymer types and higher variation in principal component scores among weathered particles, but no patterns were observed among particle colors or morphologies. These results demonstrate that ATR-FTIR analyses are sensitive to weathering of plastics but not to particle color and morphology.

Microplastics in agricultural soils, wastewater effluents and sewage sludge in Mauritius

The rapid and silent emergence of microplastics (MPs) in the environment has recently become a global problem with more and more studies are showing the harmful effects of MPs on different ecosystems. The aim of this study was to investigate the presence of MPs in agricultural soils, wastewater effluents and sewage sludge in Mauritius. The soil samples were collected randomly from three different agricultural lands which have been used for conventional agriculture for more than 25 years. Wastewater effluents and sewage sludge were collected once, using the grab sampling method, from three main operating wastewater treatment plants (WWTP) across the island and were analysed in triplicate. MPs were extracted using the flotation technique, followed by hydrogen peroxide digestion. The abundance of MPs was found to be 320.0 ± 112.2 and 420.0 ± 244.0 particles.kg^-1 in shallow and deep soils, respectively, out of which 42.4% and 95.8% were less than 1 mm in size, respectively. Site 3 had the highest abundance of MPs due to cumulated plastic debris dumped on the field. In addition, the average MPs concentration in sewage sludge and in wastewater effluents were 14,750 ± 8612.9 particles.kg^-1 and 276.3 ± 137.3 particles.L^-1, respectively, whereby 90% of the MPs were less than 0.5 mm in size. WWTP 1 had the largest share of MPs in both sewage sludge and wastewater effluents. The attenuated total reflection Fourier transform infrared spectroscopy revealed that polypropylene (fibres, fragments, and flakes) was in abundance in agricultural soil samples by 56.26%, while in WWTP polyamide (fibres) was predominant by 88.85%. The findings of this preliminary study confirmed the presence of MPs in Mauritian lands, wastewater effluents and sewage sludge and therefore provide salient data to advocate for subsequent research on MPs.

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.

Microwave-Assisted Extraction for Quantification of Microplastics Using Pyrolysis-Gas Chromatography/Mass Spectrometry

Microplastics are now recognized as a persistent and global pollutant. To quantitively measure microplastics in environmental matrices, several techniques are used including new methods using pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS). In the present study, a new extraction method using microwave-assisted extraction (MAE) combined with Py-GC/MS was developed to extract and quantify a wide range of plastic polymers, and the method was validated using different environmental matrices. This new extraction method was able to extract polyethylene, polystyrene, polypropylene, poly(methyl-methacrylate) (PMMA), polyvinylchloride (PVC), and polycarbonate in dichloromethane with good recoveries (92.9-119.7%). The limit of detection and limit of quantification (LOQ) of the method ranged from 0.002 to 0.18 µg and from 1.2 to 5.8 µg, respectively. Intra- and interday repeatability values with coefficients of variation less than 25% for all polymers were obtained. Method validation also included a spike and recovery using all polymers from clean water, dirty water, and shrimp and salmon fillet samples, with recoveries of 85 to 111, 87 to 138, 81 to 122, and 50 to 151%, respectively. Finally, the method was tested on unspiked wild mussels and bottled water for proof-of-concept. Both polyethylene and PVC were detected and quantified in mussels, and polycarbonate and polypropylene were detected below the LOQ. For bottled water, polypropylene, polystyrene, and polycarbonate were all detected below the LOQ. We introduce a method combining MAE and Py-GC/MS as a tool for mass quantification of microplastics. This method can be used as a stand-alone, or as a complementary method to spectroscopic techniques. Environ Toxicol Chem 2021;40:2733-2741. © 2021 SETAC.

Microplastics and anthropogenic fibre concentrations in lakes reflect surrounding land use

Pollution from microplastics and anthropogenic fibres threatens lakes, but we know little about what factors predict its accumulation. Lakes may be especially contaminated because of long water retention times and proximity to pollution sources. Here, we surveyed anthropogenic microparticles, i.e., microplastics and anthropogenic fibres, in surface waters of 67 European lakes spanning 30° of latitude and large environmental gradients. By collating data from >2,100 published net tows, we found that microparticle concentrations in our field survey were higher than previously reported in lakes and comparable to rivers and oceans. We then related microparticle concentrations in our field survey to surrounding land use, water chemistry, and plastic emissions to sites estimated from local hydrology, population density, and waste production. Microparticle concentrations in European lakes quadrupled as both estimated mismanaged waste inputs and wastewater treatment loads increased in catchments. Concentrations decreased by 2 and 5 times over the range of surrounding forest cover and potential in-lake biodegradation, respectively. As anthropogenic debris continues to pollute the environment, our data will help contextualise future work, and our models can inform control and remediation efforts.

Microplastic pollution in Southern Atlantic marine waters: Review of current trends, sources, and perspectives

Microplastics (MPs) are emerging and ubiquitous contaminants which have been gaining prominence since the last decade to nowadays. This is due to their possible adverse effects in aquatic ecosystems as well as the huge amount of plastic waste exponentially generated around the globe. Plastics may be introduced either directly to water bodies or indirectly to the aquatic systems by being carried by the wind, from emissions of contaminated effluents, and soil leaching, among other processes. In turn, these debris may interact with organic and inorganic contaminants, such as polycyclic aromatic hydrocarbons (PAHs), polybrominated diphenyl ethers (PBDEs) and trace constituents, and with microorganisms. Although the abundance of microplastics from South Atlantic waters is among the highest found worldwide, the number of studies in these marine waters regarding MP contamination is still scarce. Additionally, there still are no consensus on the best sampling conditions, which may be underestimating MPs. In this way, adequate MPs studies regarding their distribution, exposure levels, chemical and biological interactions are highly suggested in order to better understand both environmental and human health potential risks. This review assessed advances in sampling, analytical methodologies, characterization and understanding of MP sources in these marine waters in comparison to data from other regions around the globe.

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.

The Proposal and Necessity of the Numerical Description of Nano- and Microplastics' Surfaces (Plastisphere)

The constantly growing amount of synthetic materials < 5 mm, called microplastics (MPs), is fragmented in the environment. Thus, their surface, Plastisphere, is substantially increasing forming an entirely new ecological niche. It has already been extensively studied by microbiologists observing the biofilm and by material scientists interested in the weathering of polymer materials. This paper aims to construct a bridge between the physical and chemical description of the Plastisphere and its microbiological and ecological significance. Various algorithms, based on the analysis of pictures obtained by scanning electron microscopy (SEM), are proposed to describe in detail the morphology of naturally weathered polymers. In particular, one can study the size and distribution of fibres in a standard filter, search the synthetic debris for mapping, estimate the grain size distribution, quantitatively characterize the different patterns of degradation for polymer spheres and ghost nets, or calculate the number of pores per surface. The description and visualization of a texture, as well as the classification of different morphologies present on a surface, are indispensable for the comprehensive characterization of weathered polymers found inside animals (e.g., fishes). All these approaches are presented as case studies and discussed within this work.

Optimising sample preparation for FTIR-based microplastic analysis in wastewater and sludge samples: multiple digestions

The lack of standardised methodologies in microplastic research has been addressed in recent years as it hampers the comparison of results across studies. The quantification of microplastics in the environment is key to the assessment of the potential eco-toxicological impacts that this new category of emerging pollutants could have on terrestrial and aquatic species. Therefore, the need for protocols that are robust, simple and reliable together with their standardisation are of crucial importance. This study has focused on removal of organic matter with Fenton reagent from wastewater and sludge samples. This step of analysis was optimised by implementing a multi-digestion treatment on these samples that have high concentration of complex mixtures of organic matter, which interfere with microplastic enumeration. Moreover, this study targeted the detection of microplastics in the sub-hundred-micron size range due to the potential higher risks associated with smaller-sized particles and the limited data available from previous wastewater research. To show the validity of the method, triplicate samples of raw sewage, final effluent and sludge were independently spiked with two different sizes and types of microplastic polymers. Due to the various analytical stages required for the isolation of microplastics, time is a limiting factor in sample processing. The sequential digestion with Fenton reagent represents an inexpensive and time-efficient procedure for wastewater research providing effective degradation of organic material. These advantages over other currently available methods mean the method is suitable for analysis of large numbers of samples allowing robust monitoring data sets to be generated.

Occurrence, distribution, and possible sources of microplastics in the surface river water in the Arakawa River watershed

Nowadays, efforts for complementing data concerning microplastics (MPs) in freshwater systems are required as MPs exist in many populated areas. The goal of this study is to investigate the distribution and profiles of riverine MPs along the Arakawa River watershed, which runs through the Tokyo Metropolitan area. The MPs were found in 10 of the 12 sampling sites in the watershed with the mean of 1.8 pieces/m³. Also, the spatial distribution of the MPs displayed the accumulation in the downstream and in the tributary areas with high populations, reflecting the levels of the local anthropogenic activities. In contrast to the heterogeneity of the floating concentrations, polymer type compositions were consistent with the predominance of polyethylene compared with polypropylene and polystyrene. Moreover, the size distributions of the particles were consistent among samples with the predominance of the relatively smaller size fractions. These results suggest that the sources of fragmented plastic debris are likely spread over terrestrial areas and that reducing burden from these land-based MPs is necessary for mitigating MPs pollution in urban aquatic environments.

A roadmap for a Plastisphere

The constantly growing production of synthetic materials and their presence in the environment gradually transform our Blue Planet into the Plastic One. Microplastics (MPs) enlarge significantly their surface during fragmentation processes. Undoubtedly, nanoplastics (NPs), emerging contaminants, and the Plastisphere, the total available surface of debris, are currently on the edge of science. Although a few research are dedicated to the analysis of MPs and NPs from the physical and chemical point of view, there is a lack of the correlation between the material characterization and the microbiological data. The ecological approach, covering the description of numerical antibiotic or metal resistance bacteria, dealing with toxicological issues or biodegradation, is of great importance. This paper creates the bridge between the material science approach and the eighth continent (as sometimes Plastisphere is called). It points out that the Plastisphere significance will grow within the coming years and it should not be regarded as one ecological niche, but a set of different ones. As the properties mainly depend on the surface morphology, its numerical characterization will be the base for the classification purposes to better describe and model this phenomenon. Apart from concerning the currently important issues of NPs and the Plastisphere, this paper presents the emerging area of research namely the numerical approach to their characterization. This proposal of an interdisciplinary approach to the classification of the Plastisphere's types might be interesting for the members of different scientific communities: nanotechnology, material science and engineering, chemistry, physics, ecology, microbiology, marine microplastics or picture analysis.

Raman Spectroscopy of Marine Microplastics - A short comprehensive compendium for the environmental scientists

The aim of this paper is to present a short practical introduction to Raman spectroscopy for all non-specialist in chemistry and physics who are working with (marine) microplastics and nanoplastics. The continually growing polymer presence in the global ocean system constitutes a crucial interdisciplinary issue. To adequately address the problem of microplastics impact on the marine environment, its ecotoxicity, fate, sources, accumulation and weathering, one should characterise the debris found. In order to identify and describe the samples, spectroscopy techniques are crucial as they enable qualitative as well as quantitative analyses. This work provides the shortlist of good practices developed during own research, method potential and drawbacks, case studies as examples, simple explanation of primary polymer spectra. Finally, some matters on the edge and future directions are shortly mentioned. The selected proper results of measurements of diversified types of samples are provided to better illustrate the problem.

Developing a systematic method for extraction of microplastics in soils

Microplastics are an environmental issue of global concern. Although they have been found in a range of environments worldwide, their contamination in the terrestrial environment is poorly understood. The lack of standardised methods for their detection and quantification is a major obstacle for determining the risk they pose to soil environments. Here we present a systematic comparison of microplastic extraction methods from soils, taking into account the characteristics of the soil medium to determine the best methods for quantification. The efficiency of organic matter removal using hydrogen peroxide, potassium hydroxide and Fenton's reagent was measured. Soils with a range of particle size distribution and organic matter content were spiked with a variety of microplastic types. Density separation methods using sodium chloride, zinc chloride and canola oil were tested. Recovery efficiencies were calculated and the impact of the reagents on the microplastics was quantified using Attenuated Total Reflectance (ATR) Fourier Transform-Infrared (FTIR) spectroscopy. The optimal organic removal method was found to be hydrogen peroxide. The recovery efficiency of microplastics was variable across polymer types. Overall, canola oil was shown to be the optimal method for density separation, however, efficiency was dependent on the amount of organic matter in the soil. This outcome highlights the importance of including matrix-specific calibration in future studies considering a wide range of microplastic types, to avoid underestimation of microplastic contamination. We show here that methods for extracting microplastics from soils can be simple, cost-effective and widely applicable, which will enable the advancement of microplastic research in terrestrial environments.

Fraud Detection of Herbal Medicines Based on Modern Analytical Technologies Combine with Chemometrics Approach: A Review

Fraud in herbal medicines (HMs), commonplace throughout human history, is significantly related to medicinal effects with sometimes lethal consequences. Major HMs fraud events seem to occur with a certain regularity, such as substitution by counterfeits, adulteration by addition of inferior production-own materials, adulteration by chemical compounds, and adulteration by addition of foreign matter. The assessment of HMs fraud is in urgent demand to guarantee consumer protection against the four fraudulent activities. In this review, three analysis platforms (targeted, non-targeted, and the combination of non-targeted and targeted analysis) were introduced and summarized. Furthermore, the integration of analysis technology and chemometrics method (e.g., class-modeling, discrimination, and regression method) have also been discussed. Each integration shows different applicability depending on their advantages, drawbacks, and some factors, such as the explicit objective analysis or the nature of four types of HMs fraud. In an attempt to better solve four typical HMs fraud, appropriate analytical strategies are advised and illustrated with several typical studies. The article provides a general workflow of analysis methods that have been used for detection of HMs fraud. All analysis technologies and chemometrics methods applied can conduce to excellent reference value for further exploration of analysis methods in HMs fraud.

Towards the Development of Portable and In Situ Optical Devices for Detection of Micro and Nanoplastics in Water: A Review on the Current Status

The prevalent nature of micro and nanoplastics (MP/NPs) on environmental pollution and health-related issues has led to the development of various methods, usually based on Fourier-transform infrared (FTIR) and Raman spectroscopies, for their detection. Unfortunately, most of the developed techniques are laboratory-based with little focus on in situ detection of MPs. In this review, we aim to give an up-to-date report on the different optical measurement methods that have been exploited in the screening of MPs isolated from their natural environments, such as water. The progress and the potential of portable optical sensors for field studies of MPs are described, including remote sensing methods. We also propose other optical methods to be considered for the development of potential in situ integrated optical devices for continuous detection of MPs and NPs. Integrated optical solutions are especially necessary for the development of robust portable and in situ optical sensors for the quantitative detection and classification of water-based MPs.

Quantitative Comparison of Experimental and Computed IR-Spectra Extracted from Ab Initio Molecular Dynamics

Experimentally measured infrared spectra are often compared to their computed equivalents. However, the accordance is typically characterized by visual inspection, which is prone to subjective judgment. The primary challenge for a similarity-based analysis is that the artifacts introduced by each approach are very different and, therefore, may require preprocessing steps to determine and correct impeding irregularities. To allow for automated objective assessment, we propose a practical and comprehensive workflow involving scaling factors, a novel baseline correction scheme, and peak smoothing. The resulting spectra can then easily be compared quantitatively using similarity measures, for which we found the Pearson correlation coefficient to be the most suitable. The proposed procedure is then applied to compare the agreement of the experimental infrared spectra from the NIST Chemistry Web book with the calculated spectra using standard harmonic frequency analysis and spectra extracted from ab initio molecular dynamics simulations at different levels of theory. We conclude that the direct, quantitative comparison of calculated and measured IR spectra might become a novel, sophisticated approach to benchmark quantum-chemical methods. In the present benchmark, simulated spectra based on ab initio molecular dynamics show in general better agreement with the experiment than static calculations.