Raman Spectroscopy for the Analysis of Microplastics in Aquatic Systems

In situ surface-enhanced Raman spectroscopy for the detection of nanoplastics: A novel approach inspired by the aging of nanoplastics

Nanoplastics (NPs) present a hidden risk to organisms and the environment via migration and enrichment. Detecting NPs remains challenging because of their small size, low ambient concentrations, and environmental variability. There is an urgency to exploit detection approaches that are more compatible with real-world environments. Herein, this study provides a surface-enhanced Raman spectroscopy (SERS) technique for the in situ reductive generation of silver nanoparticles (Ag NPs), which is based on photoaging-induced modifications in NPs. The feasibility of generating Ag NPs on the surface of NPs was derived by exploring the photoaging mechanism, which was then utilized to SERS detection. The approach was applied successfully for the detection of polystyrene (PS), polyvinyl chloride (PVC), and polyethylene terephthalate (PET) NPs with excellent sensitivity (e.g., as low as 1 × 10-6 mg/mL for PVC NPs, and an enhancement factor (EF) of up to 2.42 × 105 for small size PS NPs) and quantitative analytical capability (R2 > 0.95579). The method was successful in detecting NPs (PS NPs) in lake water. In addition, satisfactory recoveries (93.54-105.70 %, RSD < 12.5 %) were obtained by spiking tap water as well as lake water, indicating the applicability of the method to the actual environment. Therefore, the proposed approach offers more perspectives for testing real environmental NPs.

Photodegradation Processes and Weathering Products of Microfibers in Aquatic Environments

Microplastics, particularly microfibers (MFs), pose a significant threat to the environment. Despite their widespread presence, the photochemical reactivity, weathering products, and environmental fate of MFs remain poorly understood. To address this knowledge gap, photodegradation experiments were conducted on three prevalent MFs: polyester (POL), nylon (NYL), and acrylic (ACR), to elucidate their degradation pathways, changes in surface morphology and polymer structure, and chemical and colloidal characterization of weathering products during photochemical degradation of MFs. The results showed that concentrations of dissolved organic carbon, chromophoric dissolved organic matter (DOM), and fluorescent components consistently increased during weathering, exhibiting a continuous release of DOM. Scanning electron microscopy and Raman spectroscopy revealed changes in the surface morphology and polymer spectra of the MFs. During the weathering experiments, DOM aromaticity (SUVA254) decreased, while spectral slope increased, indicating concurrent DOM release and degradation of aromatic components. The released DOM or nanoplastics were negatively charged with sizes between 128 and 374 nm. The production rate constants of DOM or the photochemical reactivity of MFs followed the order ACR > NYL ≥ POL, consistent with their differences in chemical structures. These findings provide an improved understanding of the photochemical reactivity, degradation pathways, weathering products, and environmental fate of microfibers in the environment.

Characterization and ecological risk assessment of microplastics accumulated in sea water, sand, sediment, shell water and selected tissues of hermit crab of Sundarban Biosphere Reserve

Sundarban, a Ramsar site of India, has been encountering an ecological threat due to the presence of microplastic (MP) wastes generated from different anthropogenic sources. Clibanarius longitarsus, an intertidal hermit crab of Sundarban Biosphere Reserve, resides within the abandoned shell of a gastropod mollusc, Telescopium telescopium. We characterized and estimated the MP in the gills and gut of hermit crab, as well as in the water present in its occupied gastropod shell. The average microplastic abundance in sea water, sand and sediment were 0.175 ± 0.145 MP L-1, 42 ± 15.03 MP kg-1 and 67.63 ± 24.13 MP kg-1 respectively. The average microplastic load in hermit crab was 1.94 ± 0.59 MP crab-1, with 33.89 % and 66.11 % in gills and gut respectively. Gastropod shell water exhibited accumulation of 1.69 ± 1.43 MP L-1. Transparent and fibrous microplastics were documented as the dominant polymers of water, sand and sediment. Shell water exhibited the prevalence of green microplastics followed by transparent ones. Microscopic examination revealed microplastics with 100-300 μm size categories were dominant across all abiotic compartments. ATR-FTIR and Raman spectroscopy confirmed polyethylene and polypropylene as the prevalent polymers among the five identified polymers of biotic and abiotic components. The target group index indicated green and black as the preferable microplastics of crab. The ecological risk analysis indicated a considerable level of environmental pollution risk in Sundarban and its inhabiting organisms. This important information base may facilitate in developing a strategy of mitigation to limit the MP induced ecological risk at Sundarban Biosphere Reserve.

Transport and Accumulation of Microplastics from Biosolids to Australian Agricultural Soils: Detection of Microplastics Down to 1 μm

The shift toward sustainable agriculture involves replacing inorganic fertilizers with organic alternatives like biosolids. However, concerns arise over emerging contaminants, such as microplastics (MPs), which remain largely unregulated. Despite their common use in Australia, the transfer of MPs from biosolids to agricultural soils remains largely unknown. Herein, we have investigated the abundance, characteristics, and transport of MPs resulting from biosolids application in two Queensland agricultural sites. MP concentrations were significantly higher in biosolid-amended soils (average of 1137 MPs/kg) than in reference sites (average of 36 MPs/kg), correlating with the volume, time since application, and frequency of biosolids application. MPs > 25 μm were predominantly polyethylene, polypropylene, and poly(methyl methacrylate) fragments (up to 85%). Fibers constitute only 15-30% of MPs and mainly in larger sizes (average 1011 μm), whereas fragments (average 188 μm) and beads (average 72 μm) had smaller size ranges. Despite analytical challenges using Raman spectroscopy, detected smaller MPs (1-25 μm) were fragments composed of polyethylene, polypropylene, and poly(vinyl alcohol). This study provides the first report of MPs down to 1 μm in Australian agricultural soils. Our findings suggest a need to assess the long-term impact of MPs in biosolids on soil health and food safety. We call on policymakers to consider the implementation of effective MP source control strategies and the development of guidelines for acceptable biosolids application rates.

Critical evaluation of hyperspectral imaging technology for detection and quantification of microplastics in soil

In this study, we critically evaluated the performance of an emerging technology, hyperspectral imaging (HSI), for detecting microplastics (MPs) in soil. We examined the technology's robustness against varying environmental conditions in five groups of experiments. Our findings show that near-infrared (NIR) hyperspectral imaging (HSI) effectively detects microplastics (MPs) in soil, though detection efficacy is influenced by factors such as MP concentration, color, and soil moisture. We found a generally linear relationship between the levels of MPs in various soils and their spectral responses in the NIR HSI imaging spectrum. However, effectiveness is reduced for certain MPs, like polyethylene, in kaolinite clay. Furthermore, we showed that soil moisture considerably influenced the detection of MPs, leading to nonlinearities in quantification and adding complexities to spectral analysis. The varied responses of MPs of different sizes and colors to NIR HSI present further challenges in detection and quantification. The research suggests pre-grouping of MPs based on size before analysis and proposes further investigation into the interaction between soil moisture and MP detectability to enhance HSI's application in MP monitoring and quantification. To our knowledge, this study is the first to comprehensively evaluate this technology for detecting and quantifying microplastics.

The use of vibrational spectroscopy and supervised machine learning for chemical identification of plastics ingested by seabirds

Plastic pollution is now ubiquitous in the environment and represents a growing threat to wildlife, who can mistake plastic for food and ingest it. Tackling this problem requires reliable, consistent methods for monitoring plastic pollution ingested by seabirds and other marine fauna, including methods for identifying different types of plastic. This study presents a robust method for the rapid, reliable chemical characterisation of ingested plastics in the 1-50 mm size range using infrared and Raman spectroscopy. We analysed 246 objects ingested by Flesh-footed Shearwaters (Ardenna carneipes) from Lord Howe Island, Australia, and compared the data yielded by each technique: 92 % of ingested objects visually identified as plastic were confirmed by spectroscopy, 98 % of those were low density polymers such as polyethylene, polypropylene, or their copolymers. Ingested plastics exhibit significant spectral evidence of biological contamination compared to other reports, which hinders identification by conventional library searching. Machine learning can be used to identify ingested plastics by their vibrational spectra with up to 93 % accuracy. Overall, we find that infrared is the more effective technique for identifying ingested plastics in this size range, and that appropriately trained machine learning models can be superior to conventional library searching methods for identifying plastics.

Critical review on unveiling the toxic and recalcitrant effects of microplastics in aquatic ecosystems and their degradation by microbes

Production of synthetic plastic obtained from fossil fuels are considered as a constantly growing problem and lack in the management of plastic waste has led to severe microplastic pollution in the aquatic ecosystem. Plastic particles less than 5mm are termed as microplastics (MPs), these are pervasive in water and soil, it can also withstand longer period of time with high durability. It can be broken down into smaller particles and can be adsorbed by various life-forms. Most marine organisms tend to consume plastic debris that can be accumulated easily into the vertebrates, invertebrates and planktonic entities. Often these plastic particles surpass the food chain, resulting in the damage of various organs and inhibiting the uptake of food due to the accumulation of microplastics. In this review, the physical and chemical properties of microplastics, as well as their effects on the environment and toxicity of their chemical constituents are discussed. In addition, the paper also sheds light on the potential of microorganisms such as bacteria, fungi, and algae which play a pivotal role in the process of microplastics degradation. The mechanism of microbial degradation, the factors that affect degradation, and the current advancements in genetic and metabolic engineering of microbes to promote degradation are also summarized. The paper also provides information on the bacterial, algal and fungal degradation mechanism including the possible enzymes involved in microplastic degradation. It also investigates the difficulties, limitations, and potential developments that may occur in the field of microbial microplastic degradation.

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.

Locally Self-Adjustive Smoothing for Measurement Noise Reduction with Application to Automated Peak Detection

Smoothing is a widely used approach for measurement noise reduction in spectral analysis. However, it suffers from signal distortion caused by peak suppression. A locally self-adjustive smoothing method is developed that retains sharp peaks and less distorted signals. The proposed method uses only one parameter that determines the global smoothness of data, while balancing the local smoothness using the data itself. Simulation and real experiments in comparison with existing convolution-based smoothing methods indicate both qualitatively and quantitatively improved noise reduction performance in practical scenarios. We also discuss parameter selection and demonstrate an application for the automated smoothing and detection of a given number of peaks from noisy measurement data.

Plastic pollution affects ecosystem processes including community structure and functional traits in large rivers

Plastics in aquatic ecosystems rapidly undergo biofouling, giving rise to a new ecosystem on their surface, the 'plastisphere.' Few studies quantify the impact of plastics and their associated community on ecosystem traits from biodiversity and functional traits to metabolic function. It has been suspected that impacts on ecosystems may depend on its state but comparative studies of ecosystem responses are rare in the published literature. We quantified algal biomass, bacterial and algal biodiversity (16S and 18S rRNA), and metabolic traits of the community growing on the surface of different plastic polymers incubated within rivers of the Lower Mekong Basin. The rivers selected have different ecological characteristics but are similar regarding their high degree of plastic pollution. We examined the effects of plastics colonized with biofilms on ecosystem production, community dark respiration, and the epiplastic community's capability to influence nitrogen, phosphorus, organic carbon, and oxygen in water. Finally, we present conceptual models to guide our understanding of plastic pollution within freshwaters. Our findings showed limited microalgal biomass and bacterial dominance, with potential pathogens present. The location significantly influenced community composition, highlighting the role of environmental conditions in shaping community development. When assessing the effects on ecosystem productivity, our experiments showed that biofouled plastics led to a significant drop in oxygen concentration within river water, leading to hypoxic/anoxic conditions with subsequent profound impacts on system metabolism and the capability of influencing biogeochemical cycles. Scaling our findings revealed that plastic pollution may exert a more substantial and ecosystem-altering impact than initially assumed, particularly in areas with poorly managed plastic waste. These results highlighted that the plastisphere functions as a habitat for biologically active organisms which play a pivotal role in essential ecosystem processes. This warrants dedicated attention and investigation, particularly in sensitive ecosystems like the Mekong River, which supports a rich biodiversity and the livelihoods of 65 million people.

Characterization of HDPE microparticles in sludge aerobic digestion and their influence on the process

The occurrence of microplastics (MPs) in wastewater has been studied in the last years. The high efficiency of their removal from wastewater is linked to their transfer to the sludge. In this work, the effect of high-density polyethylene (HDPE) on aerobic digestion was evaluated and these MPs were monitored, characterizing them by three different techniques. Two parallel batch digesters were monitored. AD-Control (meaning Aerobic Digester) operated as a reference, with no external HDPE particles, whereas these polymeric fragments were introduced to the second aerobic digester (AD-HDPE) using ring pulls as microplastic support. FTIR, Raman spectroscopies and fluorescence analysis of these microparticles showed some relevant results that should be highlighted. Higher fluorescence appeared after 7 days in the digester. It coincided with an increase of active volatile suspended solids (AVSS) in the AD-HDPE, which means that an increase of the microbial activity took place. Despite the presence of HDPE particles in the sludge, the digester performance was not compromised. Besides, the HDPE particles did not affect the microbial diversity (Shannon index) of the bacterial community at the end of the experiment compared to the bacterial community of the aerobic digester control tank. Based on the analysis of the relative abundances of microbial taxa, it was concluded that HDPE had selective effects on sludge microbial community, increasing the relative abundance of Bacteroridota phylum.

Surface enhanced raman spectroscopy based sensitive and onsite detection of microplastics in water utilizing silver nanoparticles and nanodendrites

Plastics, of the order of microns in size, being not visible to the naked eye, are one of the significant contributors to pollution in the environment. Thus, the detection of micron-sized plastics (microplastics (MPs)) is crucial because of its hazardous toxic effects on our surroundings. In this work, we have proposed a quick and on-site detection of MPs, such as, polyvinyl chloride (PVC), polyvinyl alcohol (PVA) and polystyrene (PS) at ultra trace level using surface-enhanced Raman spectroscopy (SERS). To detect and analyse the spectra, two different nanostructures, such as, spherical shaped Ag nanoparticles (NPs), and shape anisotropic Ag nano-dendrites (NDs) were utilised to acquire the SERS spectra. A comprehensive analysis was further performed to check and investigate the amount of enhancements due to the mentioned nanostructures. We observed the Ag NDs exhibited amplified signal intensity compared to the Ag NPs due to the shape anisotropy leading to the surface charge confinement effect to create highly dense hotspots. However, the spherical shaped polystyrene beads of micron size exhibited better enhancement in Raman signal intensity when mixed with Ag NPs due to increased surface adsorption with the NPs. Therefore, the comparative study emphasizes the ability of using solution-based nanostructure as SERS for the onsite detection of microplastics having diverge size range at low concentration.

Reducing microplastics in tea infusions released from filter bags by pre-washing method: Quantitative evidences based on Raman imaging and Py-GC/MS

Microplastics released from plastic-based filter bags during tea brewing have attracted widespread attention. Laser confocal micro-Raman and direct classical least squares were used to identify and estimate micron-sized microplastics. Characteristic peaks from pyrolysis-gas chromatography/mass spectrometry of polyethylene terephthalate, polypropylene, and nylon 6 were selected to construct curves for quantification submicron-sized microplastics. The results showed that microplastics released from tea bags in the tea infusions ranged from 80 to 1288 pieces (micron-sized) and 0 to 63.755 μg (submicron-sized) per filter bag. Nylon 6 woven tea bags released far fewer microplastics than nonwoven filter bags. In particular, a simple strategy of three pre-washes with room temperature water significantly reduced microplastic residues with removal rates of 76 %-94 % (micron-sized) and 80 %-87 % (submicron-sized), respectively. The developed assay can be used for the quantitative evaluation of microplastics in tea infusions, and the pre-washing reduced the risk of human exposure to microplastics during tea consumption.

Research on the Migration and Adsorption Mechanism Applied to Microplastics in Porous Media: A Review

In recent years, microplastics (MPs) have emerged as a significant environmental pollutant, garnering substantial attention for their migration and transformation behaviors in natural environments. MPs frequently infiltrate natural porous media such as soil, sediment, and rock through various pathways, posing potential threats to ecological systems and human health. Consequently, the migration and adsorption mechanisms applied to MPs in porous media have been extensively studied. This paper aims to elucidate the migration mechanisms of MPs in porous media and their influencing factors through a systematic review. The review encompasses the characteristics of MPs, the physical properties of porous media, and hydrodynamic factors. Additionally, the paper further clarifies the adsorption mechanisms of MPs in porous media to provide theoretical support for understanding their environmental behavior and fate. Furthermore, the current mainstream detection techniques for MPs are reviewed, with an analysis of the advantages, disadvantages, and applications of each technique. Finally, the paper identifies the limitations and shortcomings of current research and envisions future research directions.

Basin scale monitoring of microplastics and phthalates in sediments from the Persian Gulf and the Gulf of Makran using GIS-based algorithms: Insights towards spatial variation and potential risk assessment

Information on sedimentary microplastics and phthalates has been restricted to the coastal regions of the Persian Gulf and the Gulf of Makran. Our basin-wide study monitored their levels, spatial behaviors, and potential risks using GIS-based techniques. Microplastics and phthalates ranged from 5 to 75 particles/kg d.w and 0.004-1.219 μg g-1 d.w, respectively. Microplastics were in the size category of 100 μm to 3 mm, and black microfibers (< 1 mm) and high-density polymers were dominant. The total number of microplastics was between 356.333 × 1012 and 469.075 × 1012 particles in the surface sediments of the studied regions (confidence interval = 99 %). Diethylhexyl phthalate (DEHP) and Di-isobutyl phthalate contributed 88 % of detected phthalates. Significant correlations among microplastic abundance, total phthalates, and DEHP were distinguished (p < 0.05). Overall, the findings reiterated the widespread presence of microplastics and a potential link between phthalates and microplastics. Semi-variogram, cluster Voronoi polygons, and Trend analysis identified spatial outliers and major deposition sites of microplastics and phthalates and consequently outlined the localities where upcoming studies should be concentrated. A hotspot of potential risks was marked using Fuzzy logic and GIS-based algorithms in the Sea of Makran, covering an area equal to 342. 99 km2.

A Study of High-Frequency Noise for Microplastics Classification Using Raman Spectroscopy and Machine Learning

Given the growing urge for plastic management and regulation in the world, recent studies have investigated the problem of plastic material identification for correct classification and disposal. Recent works have shown the potential of machine learning techniques for successful microplastics classification using Raman signals. Classification techniques from the machine learning area allow the identification of the type of microplastic from optical signals based on Raman spectroscopy. In this paper, we investigate the impact of high-frequency noise on the performance of related classification tasks. It is well-known that classification based on Raman is highly dependent on peak visibility, but it is also known that signal smoothing is a common step in the pre-processing of the measured signals. This raises a potential trade-off between high-frequency noise and peak preservation that depends on user-defined parameters. The results obtained in this work suggest that a linear discriminant analysis model cannot generalize properly in the presence of noisy signals, whereas an error-correcting output codes model is better suited to account for inherent noise. Moreover, principal components analysis (PCA) can become a must-do step for robust classification models, given its simplicity and natural smoothing capabilities. Our study on the high-frequency noise, the possible trade-off between pre-processing the high-frequency noise and the peak visibility, and the use of PCA as a noise reduction technique in addition to its dimensionality reduction functionality are the fundamental aspects of this work.

Where the rubber meets the road: Emerging environmental impacts of tire wear particles and their chemical cocktails

About 3 billion new tires are produced each year and about 800 million tires become waste annually. Global dependence upon tires produced from natural rubber and petroleum-based compounds represents a persistent and complex environmental problem with only partial and often-times, ineffective solutions. Tire emissions may be in the form of whole tires, tire particles, and chemical compounds, each of which is transported through various atmospheric, terrestrial, and aquatic routes in the natural and built environments. Production and use of tires generates multiple heavy metals, plastics, PAH's, and other compounds that can be toxic alone or as chemical cocktails. Used tires require storage space, are energy intensive to recycle, and generally have few post-wear uses that are not also potential sources of pollutants (e.g., crumb rubber, pavements, burning). Tire particles emitted during use are a major component of microplastics in urban runoff and a source of unique and highly potent toxic substances. Thus, tires represent a ubiquitous and complex pollutant that requires a comprehensive examination to develop effective management and remediation. We approach the issue of tire pollution holistically by examining the life cycle of tires across production, emissions, recycling, and disposal. In this paper, we synthesize recent research and data about the environmental and human health risks associated with the production, use, and disposal of tires and discuss gaps in our knowledge about fate and transport, as well as the toxicology of tire particles and chemical leachates. We examine potential management and remediation approaches for addressing exposure risks across the life cycle of tires. We consider tires as pollutants across three levels: tires in their whole state, as particulates, and as a mixture of chemical cocktails. Finally, we discuss information gaps in our understanding of tires as a pollutant and outline key questions to improve our knowledge and ability to manage and remediate tire pollution.

Detection of submicron- and nanoplastics spiked in environmental fresh- and saltwater with Raman spectroscopy

Detection of small plastic particles in environmental water samples has been a topic of increasing interest in recent years. A multitude of techniques, such as variants of Raman spectroscopy, have been employed to facilitate their analysis in such complex sample matrices. However, these studies are often conducted for a limited number of plastic types in matrices with relatively little additional materials. Thus, much remains unknown about what parameters influence the detection limits of Raman spectroscopy for more environmentally relevant samples. To address this, this study utilizes Raman spectroscopy to detect six plastic particle types; 161 and 33 nm polystyrene, < 450 nm and 36 nm poly(ethylene terephthalate), 121 nm polypropylene, and 126 nm polyethylene; spiked into artificial saltwater, artificial freshwater, North Sea, Thames River, and Elbe River water. Overall, factors such as plastic particle properties, water matrix composition, and experimental setup were shown to influence the final limits of detection.

Effects of Gamma Irradiation on Polyethylene Terephthalate and Detection of Microplastic Particles Down to 1 μm

In response to increasing concern about the impact of plastic degradation on the environment, this study investigates the degradation of virgin and recycled polyethylene terephthalate (PET) under γ-irradiation in aqueous solutions, with particular focus on the resulting formation of microplastic particles (MP). By exposing both virgin and recycled PET samples to different doses of γ-irradiation (10, 50, and 100 kGy), a comprehensive analysis using UV-vis spectroscopy, dynamic light scattering (DLS) and micro-Raman spectroscopy is presented. The results, highlighted by micro-Raman spectroscopy, show that γ-irradiation produces micrometer-sized plastic particles, with the recycled PET having a significantly higher MP content than its original counterpart. Careful examination reveals the presence of a stabilizer in samples of recycled PET juice bottles. This study not only contributes to our understanding of the effects of γ-irradiation on PET but also highlights the need for further research into the environmental impact of such processes. The insights gained shed light on the behavior of PET under γ-irradiation and the resulting impact on microplastic pollution and make an important contribution to our understanding of the broader environmental context.

Detection of microplastics via a confocal-microscope spatial-heterodyne Raman spectrometer with echelle gratings

Microplastic pollution has become a global environmental problem that cannot be ignored. Raman spectroscopy has been widely used for microplastics detection because it can be performed in real-time and is non-destructive. Conventional detection techniques have had weak signals and low signal-to-noise ratios (SNR). Here, an efficient and reliable detection method is demonstrated. Specifically, a confocal microscope combined with an echelle-grating spatial-heterodyne Raman spectrometer (CM-ESHRS) was constructed. The confocal microscopy and the characteristics of the echelle grating enabled high optical throughput, high SNR, high spectral resolution, and a wide spectral detection band. After spectral calibration, the resolution approached 0.67 cm-1, moreover, the spectral detection range for a single order was 1372.16 cm-1. We detected and analyzed nineteen kinds of microplastics, such as polyamide, polypropylene, and polymethylmethacrylate, and the main vibrational spectral bands were categorized. Compared with commercial dispersive spectrometers, CM-ESHRS has a higher optical throughput. In addition, we examined microplastics with various particle sizes, microplastics mixed in flour, and microplastic particles of different materials under mixed conditions, all of which yielded complete spectral information. Overall, CM-ESHRS exhibits good potential applications for the detection of microplastics.

An analytical strategy for challenging members of the microplastic family: Particles from anti-corrosion coatings

Potentially hazardous particles from paints and functional coatings are an overlooked fraction of microplastic (MP) pollution since their accurate identification and quantification in environmental samples remains difficult. We have applied the most relevant techniques from the field of microplastic analysis for their suitability to chemically characterize anti-corrosion coatings containing a variety of polymer binders (LDIR, Raman and FTIR spectroscopy, Py-GC/MS) and inorganic additives (ICP-MS/MS). We present the basis of a possible toolbox to study the release and fate of coating particles in the (marine) environment. Our results indicate that, due to material properties, spectroscopic methods alone appear to be unsuitable for quantification of coating/paint particles and underestimate their environmental abundance. ICP-MS/MS and an optimized Py-GC/MS approach in combination with multivariate statistics enables a straightforward comparison of the multi-elemental and organic additive fingerprints of paint particles. The approach can improve the identification of unknown particles in environmental samples by an assignment to different typically used coating types. In future, this approach may facilitate allocation of emission sources of different environmental paint/coating particles. Indeed, future work will be required to tackle various remaining analytical challenges, such as optimized particle extraction/separation of environmental coating particles.

Monitoring plastic pellet pollution in coastal environments through handheld Raman spectroscopy: Data from the Mediterranean coasts (Southern Italy)

This paper examines the distribution and chemical properties of beached plastic pellets along the Ionian and Tyrrhenian coasts of Southern Italy. Three locations have been sampled: Agnone Bagni (SR) and Paradiso (ME) on the Ionian coast of Sicily, Baia del Tono in Milazzo (ME) on the Sicilian Tyrrhenian coast, and Pizzo Calabro (VV) in Calabria on the Tyrrhenian coast. Variations in shape, size, compactness, color, and other physical features, correlated with residence times and transport, has been highlighted. Raman spectroscopy, used in a portable configuration, enabled rapid identification of polymer types, demonstrating its utility for on-site plastic pollutant monitoring. Polyethylene and polypropylene were the predominant polymers. Principal component analysis of the spectra determined the optimal chemometric classification of pellets by composition, avoiding interference or distortion. In conclusion, the study provided preliminary insights into pellet abundance, composition, weathering extent, and distribution across these shorelines, underscoring the importance of regular beach monitoring.

Combined effects of polyethylene microplastics and carbendazim on Eisenia fetida: A comprehensive ecotoxicological study

Microplastic (MP) pollution is becoming an emerging environmental concern across aquatic and terrestrial ecosystems. Plastic mulching and the use of pesticides in agriculture can lead to microplastics and agrochemicals in soil, which can result in unintended exposure to non-target organisms. The combined toxicity of multiple stressors represents a significant paradigm shift within the field of ecotoxicology, and its exploration within terrestrial ecosystems involving microplastics is still relatively limited. The present study investigated the combined effects of polyethylene MP (PE-MP) and the agrochemical carbendazim (CBZ) on the earthworm Eisenia fetida at different biological levels of organization. While E. fetida survival and reproduction did not exhibit significant effects following PE-MP treatment, there was a reduction in cocoon and hatchling numbers. Notably, prolonged exposure revealed delayed toxicity, leading to substantial growth impairment. Exposure to CBZ led to significant alterations in the endpoints mentioned above. While there was a decrease in cocoon and hatchling numbers, the combined treatment did not yield significant effects on earthworm reproduction except at higher concentrations. However, lower concentrations of PE-MP alongside CBZ induced a noteworthy decline in biomass content, signifying a form of potentiation interaction. In addition, concurrent exposure led to synergistic effects, from oxidative stress to modifications in vital organs such as the body wall, intestines, and reproductive structures (spermathecae, seminal vesicles, and ovarian follicles). The comparison of multiple endpoints revealed that seminal vesicles and ovarian follicles were the primary targets during the combined exposure. The research findings suggest that there are variable and complex responses to microplastic toxicity in terrestrial ecosystems, especially when combined with other chemical stressors like agrochemicals. Despite these difficulties, the study implies that microplastics can alter earthworms' responses to agrochemical exposure, posing potential ecotoxicological risks to soil fauna.

Overcoming oxygen inhibition in UV photolithography for the fabrication of low-loss polymer waveguides

Perfluorinated acrylate polymer materials exhibit low absorption loss at 1310 and 1550 nm, but molecular oxygen inhibits their photocuring. We propose a novel, to our knowledge, UV photolithography method incorporating a pre-exposure process for fabricating low-loss perfluorinated acrylate polymer waveguides. During the pre-exposure process, a partially cured thin layer forms on the core layer, effectively overcoming oxygen inhibition in subsequent lithography. Furthermore, the functional group contents of the polymerized materials were characterized by a Raman spectrometer to analyze the development reaction under the pre-exposure layer. Utilizing this improved method, we fabricated a straight waveguide with a length of 21 cm. The experiments showed that the propagation losses are 0.14 dB/cm at 1310 nm and 0.51 dB/cm at 1550 nm. The inter-channel cross talk for a core pitch of 250 µm was measured as low as -49 dB at 1310 nm. Error-free NRZ data transmission over this waveguide at 25 Gb/s was achieved, showcasing the potential in optical interconnect and communication applications.

Identification and Visualization of Polystyrene Microplastics/Nanoplastics in Flavored Yogurt by Raman Imaging

The contamination of food by microplastics has garnered widespread attention, particularly concerning the health risks associated with small-sized microplastics. However, detecting these smaller microplastics in food poses challenges attributed to the complexity of food matrices and instrumental and method limitations. Here, we employed Raman imaging for visualization and identification of polystyrene particles synthesized in polymerization reactions, ranging from 400 to 2600 nm. We successfully developed a quantitative model of particle size and concentration for polystyrene, exhibiting excellent fit (R2 of 0.9946). We established procedures for spiked flavored yogurt using synthesized polystyrene, providing fresh insights into microplastic extraction efficiency. Recovery rates calculated from models validated the method's feasibility. In practical applications, the assessment of the size, type, shape, and quantity of microplastics in unspiked flavored yogurt was conducted. The most common polymers found were polystyrene, polypropylene, and polyethylene, with the smallest polystyrene sizes ranging from 1 to 10 μm. Additionally, we conducted exposure assessments of microplastics in branded flavored yogurt. This study established a foundation for developing a universal method to quantify microplastics in food, covering synthesis of standards, method development, validation, and application.

Evaluation of phthalate migration potential in vacuum-packed

In recent years, the presence and migration of PAEs in packaging materials and consumer products has become a serious concern. Based on this concern, the aim of our study is to determine the possible migration potential and speed of PAEs in benthic fish stored in vacuum packaging, as well as to monitor the storage time and type as well as polyethylene (PE) polymer detection.As a result of the analysis performed by µ-Raman spectroscopy, 1 microplastic (MP) of 6 µm in size was determined on the 30th day of storage in whiting fish muscle and the polymer type was found to be Polyethylene (PE) (low density polyethylene: LDPE). Depending on the storage time of the packaging used in the vacuum packaging process, it has been determined that its chemical composition is affected by temperature and different types of polymers are formed. 10 types of PAEs were identified in the packaging material and stored flesh fish: DIBP, DBP, DPENP, DHEXP, BBP, DEHP, DCHP, DNOP, DINP and DDP. While the most dominant PAEs in the packaging material were determined as DEHP, the most dominant PAEs in fish meat were recorded as BBP and the lowest as DMP. The findings provide a motivating model for monitoring the presence and migration of PAEs in foods, while filling an important gap in maintaining a safe food chain.

Evaluating the retention of airborne microplastics on plant leaf: Influence of leaf morphology

Airborne microplastics (AMPs) have been identified in both indoor and outdoor environments and account for a large portion of an individual's daily exposure to microplastics. Thus, it is crucial to find effective methods to capture and control the levels of AMPs and ultimately reduce human exposure. While terrestrial plants have been recognized for their effectiveness in capturing airborne particles, little is known about their ability to capture AMPs. This study investigated the ability of 8 natural plant species and 2 artificial plants to capture AMPs, as well as the influence of leaf morphology on this retention. Plant leaves were exposed to AMPs for two weeks, and deposited AMPs were characterized using a Micro-Fourier Transform Infrared (μ-FTIR)spectroscopy. Selected cleaned leaves were further digested, and the presence of subsurface AMPs was confirmed using μ-Raman spectroscopy. Results revealed that AMPs were retained on the leaves of all selected plant species at concentrations ranging from 0.02 to 0.87 n/cm2. The highest average concentration was observed on an artificial plant with fenestrated leaves, followed by natural plant species with trichomes and leaflets. The lowest concentration was observed on a natural plant with smooth leaves. The majority (90%) of retained AMPs were fibres, and the remaining were fragments. Polyethylene terephthalate (PET) was the prominent polymer type. Additionally, AMP fragments were observed in the leaf subsurface in one selected species, likely retained within the leaf cuticles. The results suggest that plant leaves can indiscriminately retain AMPs on their surfaces and act as temporary sinks for AMPs. Additionally, indoor plants may provide a useful functional role in reducing indoor AMP concentrations, although longer-term studies are needed to ascertain their retention capacity more accurately over time and to evaluate the capability of indoor plants to act as a suitable, cost-effective candidate for reducing AMPs.

Preparation of synthetic micro- and nano plastics for method validation studies

Microplastic (MP) pollution is a persisting global problem. Accurate analysis is essential in quantifying the effects of microplastic pollution and develop novel technologies that reliably and reproducibly measure microplastic content in various samples. The most common methods for this are FTIR and Raman spectroscopy. Coloured, standardized beads are often used for method validation tests, which limits the conclusions to a very specific case rarely observed in the natural environment. This study focuses on the preparation of reference micro- and nanoplastics via cryogenic milling and shows their use for FTIR and Raman method validation studies. MPs can now be reproducibly milled from various plastics, offering the advantages of a better representation of MPs in real environment. Moreover, this study highlights issues with the current detection methods, up to now considered as the most reliable ones for MP detection and identification. Such issues, e.g. misidentification, will need to be addressed in the future. Additionally, milled MPs were used in experiments with commercial high-resolution imaging device, enabling a possible in-situ optical detection of microplastics. These experiments represent a step forward in understanding MPs in a water sample and provide a basis for a more accurate detection and identification directly from water, which would considerably reduce the time of analysis.

Submicron- and nanoplastic detection at low micro- to nanogram concentrations using gold nanostar-based surface-enhanced Raman scattering (SERS) substrates

The presence of submicron- (1 μm-100 nm) and nanoplastic (<100 nm) particles within various sample matrices, ranging from marine environments to foods and beverages, has become a topic of increasing interest in recent years. Despite this interest, very few analytical techniques are known that allow for the detection of these small plastic particles in the low concentration ranges that they are anticipated to be present at. Research focused on optimizing surface-enhanced Raman scattering (SERS) to enhance signal obtained in Raman spectroscopy has been shown to have great potential for the detection of plastic particles below conventional resolution limits. In this study, we produce SERS substrates composed of gold nanostars and assess their potential for submicron- and nanoplastic detection. The results show 33 nm polystyrene could be detected down to 1.25 μg mL-1 while 36 nm poly(ethylene terephthalate) was detected down to 5 μg mL-1. These results confirm the promising potential of the gold nanostar-based SERS substrates for nanoplastic detection. Furthermore, combined with findings for 121 nm polypropylene and 126 nm polyethylene particles, they highlight potential differences in analytical performance that depend on the properties of the plastics being studied.

Spectral insights: Navigating the frontiers of biomedical and microbiological exploration with Raman spectroscopy

Raman spectroscopy (RS), a powerful analytical technique, has gained increasing recognition and utility in the fields of biomedical and biological research. Raman spectroscopic analyses find extensive application in the field of medicine and are employed for intricate research endeavors and diagnostic purposes. Consequently, it enjoys broad utilization within the realm of biological research, facilitating the identification of cellular classifications, metabolite profiling within the cellular milieu, and the assessment of pigment constituents within microalgae. This article also explores the multifaceted role of RS in these domains, highlighting its distinct advantages, acknowledging its limitations, and proposing strategies for enhancement.

Sediment-associated microplastics in Chilika lake, India: Highlighting their prevalence, polymer types, possible sources, and ecological risks

The primary objective of this research was to assess microplastics (MPs) in the sediments of Chilika lake. MPs were extracted from 22 sediment samples using the density separation method combined with vacuum pump filtration. A stereo-zoom microscope and Raman spectroscopy were employed to identify the sediment-associated MPs. The total MPs collected from all 22 sites was 440 ± 3.53 particles kg-1 wet sediments, with sizes ranging between 50 and 500 μm. In terms of morphology, fibers and fragments emerged as the dominant MP types, with counts of 210 ± 1.66 and 175 ± 1.76 particles kg-1 wet sediments, respectively. Raman spectroscopy verified the presence of various MP polymers in the sediments, predominantly HDPE (37 %), followed by PS (20 %), PET (18 %), PA (11 %), PP (7 %), and PC (7 %). A notable color variation was observed in MPs; black being the most prevalent (38.8 %), succeeded by blue (19.5 %), green (11.8 %), white (11.5 %), red (10.6 %), and transparent (7.5 %). ANOVA results indicated significant (p > 0.05) variations in MP abundance across the 22 sampling locations. However, principal component analysis (PCA) and multiple regression analysis indicated that water quality parameters did not significantly influence MP abundance, yet it was found that MP retention was higher in fine-grained sediments like clay and silt. The leading sources of MPs in Chilika lake were found to be aquafarming, trailed by river and sewage discharges, fishing activities, antifouling coatings and tourism. Additionally, the pollution load index (PLI) was employed to gauge the ecological risks, categorizing the lake under risk category 1, which implies a minimal level of MPs pollution. This research aims to serve as an early warning system for MPs pollution in productive brackish water habitats globally, including Chilika lake, guiding policymakers towards appropriate management strategies and preventive measures.

Visualization and characterisation of microplastics in aquatic environment using a home-built micro-Raman spectroscopic set up

Microplastics (MP) which are tiny plastic particles of sizes range from 1 μm (μm) to 5 mm (mm), have become a growing cause of concern due to their widespread presence in the environment and their potential impacts on ecosystems and human health. Marine organisms have the potential to consume microplastics, which could lead to physical injuries, blockages, or the transfer of harmful substances up the food chain. Humans may indirectly consume microplastics through contaminated seafood and water, although the complete scope of health risks is currently under investigation. An essential step in gaining a comprehensive understanding of microplastic pollution in waterbodies is the identification of microplastics, which is also crucial for further development of effective environmental regulations to address its adverse impacts. Majority of the researchers are accomplishing it globally using commercial platforms based on Raman spectroscopy. However, the development of indigenous Raman systems, which can enable microplastic identification, particularly in developing nations, is the need of the hour due to the outrageous cost of commercial platforms. In the current study, a custom-designed micro-Raman spectroscopy system was developed to detect and characterize microplastics from waterbodies. The developed system enabled visualization, size measurement and characterization of microplastics. Experimental parameters were fine-tuned, and a standardized Raman database was established for each type of plastic. This system exhibited high resolution which was capable of analysing microparticles of size up to 5 μm. Principal component analysis was carried out on the experimental Raman data, demonstrating good classification amongst different kinds of plastics. The performance of the developed system in analysing real samples was evaluated through experiments conducted on water samples obtained from the shore of Malpe Beach in Udupi district. The results revealed the presence of polyethylene and polyethylene terephthalate in the samples, along with the detection of pigments like copper phthalocyanine and indigo blue.

From cracks to secondary microplastics - surface characterization of polyethylene terephthalate (PET) during weathering

Secondary microplastics are a product of the fragmentation of plastic debris. Despite concerns regarding the omnipresence of microplastics in the environment, knowledge about the mechanics of their actual formation is still limited. Fragmentation is usually linked to weathering, which alters the properties of the plastic and allows fragmentation to occur. Therefore, in this study, polyethylene terephthalate (PET) samples were exposed to artificial UV light or a combination of UV light and water for a total of three months to simulate natural weathering. The samples included three forms of PET with different production histories: pellets, yarns, and films. The surface alterations to the samples during weathering were characterized using scanning electron microscopy and Raman spectroscopy. Results indicated that the three different types of PET developed markedly different surface defects and also exhibited signs of weathering within different time frames. Differences were also found between samples exposed only to UV and those exposed to UV and submerged in water. In water, the first surface changes were spotted within 30 days of initial submersion and later developed into an organized crack network. Upon the introduction of mild mechanical forces, pieces of the weathered surface started to delaminate. The fragments from films had an elongated shape with a median size of 16.1 × 2.1 × 1.8 μm, resembling a fibre. If the weathered surface of a film were to detach completely, it could create 1.4-7.9 million microplastic fragments/cm2. For pellets, this number would range between 0.4 and 2.2 million microplastics/cm2. In addition to particle formation by surface delamination, particles also emerged on the weathered surfaces of all studied samples, presenting another possible source of micro-sized particles during weathering. Overall, the results of this work show that the weathering of plastics and the formation of microplastics are heavily influenced not only by the weathering mechanism but also by the type and production history of the polymers.

How can contamination be prevented during laboratory analysis of atmospheric samples for microplastics?

Microplastics (MPs) in the air and indoor environments are of growing concern and have led to increased testing for MPs. This study draws attention to the quality and quantitative measures of MP studies by conducting laboratory experiments (on solutions, filters, and blank samples) that were rarely or were not adopted in the airborne and indoor MP literature. Experiments have been conducted to identify contaminations that may come from experimental procedures while determining MPs in the air samples. MPs in different matrices during experiments were counted and categorized by their shapes. Chemical characterization was performed by Raman Spectroscopy. Results showed that laminar flow is the best option over a fume hood or standard laboratory environment for detecting air MPs to reduce blank levels. Blue-green and Black-Grey were the dominant colors; fiber was the predominant type of MPs seen, and most of them fall under the size range from (1-1000 µm) in different indoor environments and blanks. Common MPs seen were PP, PVA, PTFE, PVC, and HDPE. Thermal treatment of fresh unused filters at 450 °C for 4 h was effective as it reduced the MP count by 50%. Working solutions are mainly contaminated, and their pre-filtration is essential. The average deposition of MPs in blank samples during seven days was around 55 MPs. There is an urgent need for studies on developing quality control and quality assurance of airborne and indoor MPs. Hence, a standard protocol needs to be accepted; by harmonizing procedures, comparable results can be found, uncovering the correct levels of MP contamination, as required for risk assessment.

Identification of microplastics extracted from field soils amended with municipal biosolids

Microplastic particles in arable soil are expected to impact the environment and potentially human health. The application of municipal biosolids (MBs) to agricultural land presents a further dilemma in that biosolids act as a fertilizer for crop growth, and a disposal pathway for wastewater treatment plants. They are also a direct path for emerging contaminants, such as microplastics to enter the terrestrial environment. Reliable methods are needed to identify and quantify microplastics, found in agricultural soils to determine how microplastics are being cycled in the terrestrial environment. In this study, we developed a method for extracting microplastics from soil, and characterized their composition and identity for particles sized 5 μm to 2 mm. Method development was initially completed using natural soils spiked with microplastics and MBs, followed by the analyses of soil sampled from an agricultural field where MBs were recently applied at a rate of 13 tons dw/ha. The procedures that used the spiked samples showed that microplastics can be reliably extracted from soil in a laboratory setting, and identified and semi-quantified by thermogravimetric analysis combined with Fourier-transform infrared spectroscopy (TGA-FTIR). However, when the same methods were applied to the soil samples collected from the agricultural field, reproducibility became a challenge, as the number and type of microplastics changed even within the same soils (i.e., collected the same day from the same exact location). The variation in reproducibility observed between laboratory and field samples underscores the significant heterogeneity present in the environment. This heterogeneity, in turn, affects the identification and quantity of microplastics detected, a phenomenon observed even when comparing different fields within a single treatment regimen.

Microplastics contamination in two species of gobies and their estuarine habitat of Indian Sundarbans

Sundarbans, a Ramsar site of India is contaminated with heterogeneous microplastic wastes. Boddart's goggle eye mudskipper and Rubicundus eelgoby, were common gobies of Sundarbans estuary which accumulated microplastics during their normal biological activities. We estimated the abundance of microplastics in water, sediment; skin, gills, bucco-opercular cavity and gastrointestinal tract of these two goby fishes. Microplastic load estimated in gobies were 0.84 and 2.62 particles per fish species with a dominance of transparent, fibrous microplastics with 100-300 μm in length. ATR-FTIR and Raman spectroscopy revealed polyethylene as prevalent polymer. Surface degradations and adsorption of contaminants on microplastic surface were investigated by SEM-EDX analysis. Presence of hazardous polymers influenced high polymer hazard index and potential ecological risk index which indicated acute environmental threat to Sundarbans estuary and its resident organisms. Current study will provide a new information base on the abundance of microplastics and its ecological hazard in this biosphere reserve.

Raman Spectroscopy Spectral Fingerprints of Biomarkers of Traumatic Brain Injury

Traumatic brain injury (TBI) affects millions of people of all ages around the globe. TBI is notoriously hard to diagnose at the point of care, resulting in incorrect patient management, avoidable death and disability, long-term neurodegenerative complications, and increased costs. It is vital to develop timely, alternative diagnostics for TBI to assist triage and clinical decision-making, complementary to current techniques such as neuroimaging and cognitive assessment. These could deliver rapid, quantitative TBI detection, by obtaining information on biochemical changes from patient's biofluids. If available, this would reduce mis-triage, save healthcare providers costs (both over- and under-triage are expensive) and improve outcomes by guiding early management. Herein, we utilize Raman spectroscopy-based detection to profile a panel of 18 raw (human, animal, and synthetically derived) TBI-indicative biomarkers (N-acetyl-aspartic acid (NAA), Ganglioside, Glutathione (GSH), Neuron Specific Enolase (NSE), Glial Fibrillary Acidic Protein (GFAP), Ubiquitin C-terminal Hydrolase L1 (UCHL1), Cholesterol, D-Serine, Sphingomyelin, Sulfatides, Cardiolipin, Interleukin-6 (IL-6), S100B, Galactocerebroside, Beta-D-(+)-Glucose, Myo-Inositol, Interleukin-18 (IL-18), Neurofilament Light Chain (NFL)) and their aqueous solution. The subsequently derived unique spectral reference library, exploiting four excitation lasers of 514, 633, 785, and 830 nm, will aid the development of rapid, non-destructive, and label-free spectroscopy-based neuro-diagnostic technologies. These biomolecules, released during cellular damage, provide additional means of diagnosing TBI and assessing the severity of injury. The spectroscopic temporal profiles of the studied biofluid neuro-markers are classed according to their acute, sub-acute, and chronic temporal injury phases and we have further generated detailed peak assignment tables for each brain-specific biomolecule within each injury phase. The intensity ratios of significant peaks, yielding the combined unique spectroscopic barcode for each brain-injury marker, are compared to assess variance between lasers, with the smallest variance found for UCHL1 (σ2 = 0.000164) and the highest for sulfatide (σ2 = 0.158). Overall, this work paves the way for defining and setting the most appropriate diagnostic time window for detection following brain injury. Further rapid and specific detection of these biomarkers, from easily accessible biofluids, would not only enable the triage of TBI, predict outcomes, indicate the progress of recovery, and save healthcare providers costs, but also cement the potential of Raman-based spectroscopy as a powerful tool for neurodiagnostics.

First attempt to quantify microplastics in Mediterranean Sabellaria spinulosa (Annelida, Polychaeta) bioconstructions

This work focuses on the arenaceous reefs by the polychaete Sabellaria spinulosa and addresses microplastics pollution. The main aim is to assess microplastics amount in a bioconstruction located in the Adriatic coast of Italy (Mediterranean Sea) through a comparative approach: sea-floor sediment and bioconstruction samples were analysed to quantify microplastics absolute abundance in both substrates. A total of 431 MPs were found in the investigated substrates: respectively 85 % fibers and 15 % fragments. Multivariate analysis indicates that MPs within bioconstruction occur in higher abundances and with different morphologies than in sediment samples. The analysis of bioconstruction polished sections allowed for observation of MPs agglutinated in their original position: higher concentration is reported in inter-tube areas. Results suggest that physical characteristics of MPs could play a key-role in bioconstruction inclusion processes and raise questions on effective role of sabellariid bioconstructions as a trap for this pollutant in the littoral environment.

Overcoming the fluorescent interference during Raman spectroscopy detection of microplastics

Owing to environmental concerns, microplastics pollution has been the object of increasing attention. Currently, the chemical composition of microplastics is commonly detected using Raman spectroscopy. Nevertheless, the Raman spectra of microplastics may be overlaid by signals derived from additives (e.g., pigment), resulting in serious interference. In this study, an efficient method is proposed to overcome the interference of fluorescence during Raman spectroscopic detection of microplastics. Four catalysts of Fenton's reagent (Fe2+, Fe3+, Fe3O4, and K2Fe4O7) have been investigated for their capacity to generate hydroxyl radical (•OH), thus potentially eliminating the fluorescent signals in microplastics. The results indicate that the Raman spectrum of microplastics treated with Fenton's reagent can be efficiently optimized in the absence of spectral processing. This method has been successfully applied to the detection of microplastics collected from mangroves, featuring a range of colours and shapes. Consequentially, after 14 h of treatment with sunlight-Fenton (Fe2+: 1 × 10-‍6 M, H2O2: 4 M), the Raman spectra matching-degree (RSMD) of all microplastics were >70.00 %. The innovative strategy discussed in this manuscript can greatly promote the application of Raman spectroscopy in the detection of real environmental microplastics, overcoming interfering signals derived from additives.

Quantitative and qualitative impacts of nitric acid digestion on microplastic identification via FTIR and Raman spectroscopy, implications for environmental samples

Quantification and characterization of microplastics, synthetic polymers less than 5 mm in diameter, requires extraction methods that can reduce non-plastic debris without loss or alteration of the polymers. Nitric acid has been used to extract plastic particles from zooplankton and other biota because it completely digests tissue and exoskeletons, thus reducing interferences. While the impact of acid digestion protocols on several polymers has been demonstrated, advice for quantifying microplastic and interpreting their spectra following nitric acid digestion is lacking. Fourier transform infrared (FTIR) and/or Raman spectroscopy was performed on plastics from > 50 common consumer products (including a variety of textiles) pre- and post-nitric acid treatment. The percent match and assigned polymer were tabulated to compare the accuracy of spectral identification before and after nitric acid digestion via two open spectral analysis software. Nylon-66, polyoxymethylene, polyurethane, polyisoprene, nitrile rubber, and polymethyl methacrylate had ≥ 90% mass loss in nitric acid. Other less-impacted polymers changed color, morphology, and/or size following digestion. Thus, using nitric acid digestion for microplastic extraction can impact our understanding of the particle sizes and morphologies ingested in situ. Spectral analysis results were compiled to understand how often (1) the best-hit matches were correct (30-60% of spectra), (2) the best-hit matches exceeding the (arbitrary) threshold of 65% match were correct (53-78% of spectra), and (3) the best-hit matches for anthropogenic polymers were incorrectly identified as natural polymers (12-15% of spectra). Based on these results, advice is provided on how nitric acid digestion can impact microplastics as well as spectral interpretation.

Microplastics' Shape and Morphology Analysis in the Presence of Natural Organic Matter Using Flow Imaging Microscopy

Ubiquitous microplastics in urban waters have raised substantial public concern due to their high chemical persistence, accumulative effects, and potential adverse effects on human health. Reliable and standardized methods are urgently needed for the identification and quantification of these emerging environmental pollutants in wastewater treatment plants (WWTPs). In this study, we introduce an innovative rapid approach that employs flow imaging microscopy (FlowCam) to simultaneously identify and quantify microplastics by capturing high-resolution digital images. Real-time image acquisition is followed by semi-automated classification using customized libraries for distinct polyethylene (PE) and polystyrene (PS) microplastics. Subsequently, these images are subjected to further analysis to extract precise morphological details of microplastics, providing insights into their behavior during transport and retention within WWTPs. Of particular significance, a systematic investigation was conducted to explore how the presence of natural organic matter (NOM) in WWTPs affects the accuracy of the FlowCam's measurement outputs for microplastics. It was observed that varying concentrations of NOM induced a more curled shape in microplastics, indicating the necessity of employing pre-treatment procedures to ensure accurate microplastic identification when utilizing the FlowCam. These observations offer valuable new perspectives and potential solutions for designing appropriate treatment technologies for removing microplastics within WWTPs.

Temporal trends in microplastic accumulation in placentas from pregnancies in Hawai'i

Microplastics are created for commercial use, are shed from textiles, or result from the breakdown of larger plastic items. Recent reports have shown that microplastics accumulate in human tissues and may have adverse health consequences. Currently, there are no standardized environmental monitoring systems to track microplastic accumulation within human tissues. Using Raman spectroscopy, we investigated the temporal exposures to plastic pollution in Hawai'i and noted a significant increase in the accumulation of microplastics in discarded placentas over the past 15 years, with changes in the size and chemical composition of the polymers. These findings provide a rare insight into the vulnerability and sensitivity of Pacific Island residents to plastic pollution and illustrate how discarded human tissues can be used as an innovative environmental plastic pollution monitoring system.

Application of Infrared and Near-Infrared Microspectroscopy to Microplastic Human Exposure Measurements

Microplastic pollution is a global issue for the environment and human health. The potential for human exposure to microplastic through drinking water, dust, food, and air raises concern, since experimental in vitro and in vivo toxicology studies suggest there is a level of hazard associated with high microplastic concentrations. However, to infer the likelihood of hazards manifesting in the human population, a robust understanding of exposure concentrations is needed. Infrared and near-infrared microspectroscopies have routinely been used to analyze microplastic in different exposure matrices (air, dust, food, and water), with technological advances coupling multivariate and machine learning algorithms to spectral data. This focal point article will highlight the application of infrared and Raman modes of spectroscopy to detect, characterize, and quantify microplastic particles, with a focus on human exposure to microplastic. Methodologies and state-of-the-art approaches will be reported and potential confounding variables and challenges in microplastic analysis discussed. The article provides an up-to-date review of the literature on microplastic exposure measurement using (near) infrared spectroscopies as an analytical tool, highlighting the recent advances in this rapidly advancing field.

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.

Microplastics in water: types, detection, and removal strategies

Microplastics are one of the most concerning groups of contaminants that pollute most of the surroundings of the Earth. The abundance of plastic materials available in the environment moved the scientific community in defining a new historical era known as Plasticene. Regardless of their minuscule size, microplastics have posed severe threats to the life forms like animals, plants, and other species present in the ecosystem. Ingestion of microplastics could lead to harmful health effects like teratogenic and mutagenic abnormalities. The source of microplastics could be either primary or secondary in which the components of microplastics are directly released into the atmosphere and the breakdown of larger units to generate the smaller molecules. Though numerous physical and chemical techniques are reported for the removal of microplastics, their increased cost prevents the large-scale applicability of the process. Coagulation, flocculation, sedimentation, and ultrafiltration are some of the methods used for the removal of microplastics. Certain species of microalgae are known to remove microplastics by their inherent nature. One of the biological treatment strategies for microplastic removal is the activated sludge strategy that is used for the separation of microplastic. The overall microplastic removal efficiency is significantly high compared to conventional techniques. Thus, the reported biological avenues like the bio-flocculant for microplastic removal are discussed in this review article.

Plastic debris in lakes and reservoirs

Plastic debris is thought to be widespread in freshwater ecosystems globally¹. However, a lack of comprehensive and comparable data makes rigorous assessment of its distribution challenging^2,3. Here we present a standardized cross-national survey that assesses the abundance and type of plastic debris (>250 μm) in freshwater ecosystems. We sample surface waters of 38 lakes and reservoirs, distributed across gradients of geographical position and limnological attributes, with the aim to identify factors associated with an increased observation of plastics. We find plastic debris in all studied lakes and reservoirs, suggesting that these ecosystems play a key role in the plastic-pollution cycle. Our results indicate that two types of lakes are particularly vulnerable to plastic contamination: lakes and reservoirs in densely populated and urbanized areas and large lakes and reservoirs with elevated deposition areas, long water-retention times and high levels of anthropogenic influence. Plastic concentrations vary widely among lakes; in the most polluted, concentrations reach or even exceed those reported in the subtropical oceanic gyres, marine areas collecting large amounts of debris⁴. Our findings highlight the importance of including lakes and reservoirs when addressing plastic pollution, in the context of pollution management and for the continued provision of lake ecosystem services.

Super-resolution imaging of micro- and nanoplastics using confocal Raman with Gaussian surface fitting and deconvolution

Confocal Raman imaging can directly identify and visualise microplastics and even nanoplastics. However, due to diffraction, the excitation laser spot has a size, which defines the image resolution. Consequently, it is difficult to image nanoplastic that is smaller than the diffraction limit. Within the laser spot, fortunately, the excitation energy density behaves an axially transcended distribution, or a 2D Gaussian distribution. By mapping the emission intensity of Raman signal, the imaged nanoplastic pattern is axially transcended as well and can be fitted as a 2D Gaussian surface via deconvolution, to re-construct the Raman image. The image re-construction can intentionally and selectively pick up the weak signal of nanoplastics, average the background noise/the variation of the Raman intensity, smoothen the image surface and re-focus the mapped pattern towards signal enhancement. Using this approach, along with nanoplastics models with known size for validation, real samples are also tested to image microplastics and nanoplastics released from the bushfire-burned face masks and water tanks. Even the bushfire-deviated surface group can be visualised as well, to monitor the different degrees of burning by visualising micro- and nanoplastics. Overall, this approach can effectively image regular shape of micro- and nanoplastics, capture nanoplastics smaller than the diffraction limit, and realise super-resolution imaging via confocal Raman.

Classification of household microplastics using a multi-model approach based on Raman spectroscopy

The extensive use of plastics leads to the release and diffusion of microplastics. Household plastic products occupy a large part and are closely related to daily life. Due to the small size and complex composition of microplastics, it is challenging to identify and quantify microplastics. Therefore,a multi-model machine learning approach was developed for classification of household microplastics based on Raman spectroscopy. In this study, Raman spectroscopy and machine learning algorithm are combined to realize the accurate identification of seven standard microplastic samples, real microplastics samples and real microplastic samples post-exposure to environmental stresses. Four single-model machine learning methods were used in this study, including Support vector machine (SVM), K-nearest neighbor (KNN), Linear discriminant analysis (LDA), and Multi-layer perceptron (MLP) model. The principal components analysis (PCA) was utilized before SVM, KNN and LDA. The classification effect of four models on standard plastic samples is over 88%, and reliefF algorithm was used to distinguish HDPE and LDPE samples. A multi-model is proposed based on four single models including PCA-LDA, PCA-KNN and MLP. The recognition accuracy of multi-model for standard microplastic samples, real microplastic samples and microplastic samples post-exposure to environmental stresses is over 98%. Our study demonstrates that the multi-model coupled with Raman spectroscopy is a valuable tool for microplastic classification.

Atmospheric microplastic and nanoplastic: The toxicological paradigm on the cellular system

The increasing demand for plastic in our daily lives has led to global plastic pollution. The improper disposal of plastic has resulted in a massive amount of atmospheric microplastics (MPs), which has further resulted in the production of atmospheric nanoplastics (NPs). Because of its intimate relationship with the environment and human health, microplastic and nanoplastic contamination is becoming a problem. Because microplastics and nanoplastics are microscopic and light, they may penetrate deep into the human lungs. Despite several studies demonstrating the abundance of microplastics and nanoplastics in the air, the potential risks of atmospheric microplastics and nanoplastics remain unknown. Because of its small size, atmospheric nanoplastic characterization has presented significant challenges. This paper describes sampling and characterization procedures for atmospheric microplastics and nanoplastics. This study also examines the numerous harmful effects of plastic particles on human health and other species. There is a significant void in research on the toxicity of airborne microplastics and nanoplastics upon inhalation, which has significant toxicological potential in the future. Further study is needed to determine the influence of microplastic and nanoplastic on pulmonary diseases.

Unveiling the noxious effect of polystyrene microplastics in aquatic ecosystems and their toxicological behavior on fishes and microalgae

Microplastic (MP) particles are considered noxious pollutants due to their presence in aquatic habitats at almost every level of the food chain. Thus, the entry of MP particles into marine waterbodies has triggered a common research interest. Until recently, the toxicity of polystyrene towards aquatic creatures in comparison to other polymers has not been widely investigated. This article provides an extensive overview of the occurrence of microplastic particles, the route of polystyrene (PS) in the aquatic ecosystem, the PS properties characterization, and its noxious effects on the aquatic biota, particularly fishes and microalgae. Alarming high levels of polystyrene were found in urban, coastal, and rural surface waters and sediments. The fast-screening technique began with a stereoscope to determine the polystyrene particles' shape, size, and color on the organism. SEM and complemented by micro FTIR or Raman spectroscopy were used to evaluate MP's polymer structures. The findings present evidence suggesting that polystyrene buildup in fish can have long-term and unknown consequences. Meanwhile, the presence of polystyrene on microalgae causes a decrease in chlorophyll concentration and photosynthetic activity, which may disrupt photosynthesis by interfering with the electron characters and leading to the production of reactive oxygen species (ROS).