With the rise in global plastic production, microplastics are an emerging environmental pollutant due to their ubiquitous presence in the environment. Human exposure and the impact of microplastics on human health warrants further research. Recent studies have confirmed the presence of microplastics in human tissues and several studies have noted toxicity in mammalian in vitro and in vivo models. In this 28-day gavage study, we investigated the effects of spherical and milled polystyrene nano- and microplastics in both male and female C57BL/6 mice. The results showed no significant changes in food consumption, body weights or organ weight coefficients. Additionally, there were no changes in hematological or clinical biochemistry parameters. Histological analysis revealed inflammation in the gallbladder of 9 male mice out of 23 and 2 female mice out of 24 exposed to both spherical and milled polystyrene. The adaptive and innate immune markers showed no major changes; however, pro-inflammatory cytokines were decreased in all polystyrene exposed males. Conversely, female mice exposed to both spherical and milled polystyrene showed mild pathological changes in the small intestine, with changes in goblet cell population and mucus production. The presence of polystyrene was detected in both the liver and intestines of both sexes. Sphereical and milled polystyrene particles showed similar toxicological results, but sex-associated differences were noted. Therefore, further research is warranted to explore the potential sex-specific response to microplastic exposure.
Microplastics (MPs) are a growing environmental concern, requiring effective methods for identification and quantification. This study develops and evaluates an application-oriented workflow combining near-infrared hyperspectral imaging (NIR-HSI) with a self-organizing map (SOM) and a percent-based expansion tolerance (PBET) for simultaneous microplastic mapping and semi-quantitative surface-coverage estimation. Spectral data were collected from MP fragments (PET, PE, PP, and PS; 1–5 mm) prepared from commercial household plastic source materials and experimentally distributed on sand surfaces at varying
Polyethylene is the most abundant microplastic in agricultural soils and can alter soil properties and plant health. However, microbial mineralization rates and the fate of polymer-derived carbon in soil remain poorly understood. We incubated UV-aged 13C-labeled polyethylene in agricultural soil for 22 months and monitored microbial mineralization by measuring 13CO2 production. After incubation, the spatial distribution of micro- and nanoplastics within individual soil aggregates and the incorporation of polyethylene-derived carbon into soil organic matter and soil microbial biomass were investigated. The results showed low mineralization of polyethylene (0.12
The degradation of paint is thought to be a major pathway of microplastics to the environment. However, pollution from paint microplastics is challenging to assess due to a lack of paint-specific spectral libraries and visual keys to aid in the differentiation of paint microplastics from non-paint microplastics. Here we begin to fill this gap is filled by creating a visual key for paint microplastic identification and a spectral library, the Paint Library of Plastic Particles (PLoPP), using attenuated total reflectance Fourier-transform infrared micro-spectroscopy (µATR-FTIR). PLoPP includes 263 spectra from 90 paints used in seven sectors (architectural, automotive, consumer, general industrial, marine, road markings, and wood) spanning 15 colors, five appearances (glitter, gloss, matte, pearl, and semi-gloss), and at least 25 polymers, though primarily polyurethane, polyurethane acrylics, and polyvinyl chloride. To assess the accuracy of the library in identifying paint microplastics from other microplastics, a spectral analysis pipeline using a machine learning model was developed to differentiate between pristine paint and non-paint microplastic samples with an overall accuracy of 92
Micro- and nanoplastic (MNP) particles are widely present in nature, mainly due to the extensive overuse of single-use plastics combined with poor waste management. Despite the diversity in the environment, many experimental studies still rely almost exclusively on polystyrene as a model plastic test material, while other environmentally relevant polymers remain underrepresented. In addition, labeled MNP test materials suitable for biological studies are still limited. In this study, nanosized polyethylene terephthalate (PET) and polypropylene (PP) particles were produced using a co-precipitation approach with the fluorescent π-conjugated polymer, poly(9,9-dioctylfluorene-alt-benzothiadiazole) (F8BT) at low (0.8
The rapid industrialisation, urbanisation, and population growth have led to hazardous pollutants contaminating aquatic environments with microplastics (MPs), dyes, and heavy metals, producing ecological problems and public health risks that require efficient advanced water purification approaches. Traditional treatment methods are often expensive, inefficient, and prone to secondary pollution, highlighting the need for innovative membrane-based treatments. This research work designed an innovative Polyethersulfone (PES) hollow fiber membrane (HFM) embedded with a metal organic framework composite for superior wastewater purification. The successful preparation of ZIF-8@NH2-MIL-125 (Ti) composite and its synergistic interaction were confirmed by comprehensive physicochemical characterisations. The innovative fabrication of HFM was examined by Field Emission Scanning Electron Microscopy, Contact Angle Measurement, Atomic Force Microscopy, a Universal Testing Machine, and Membrane Zeta Potential analysis. Membrane performance evaluation demonstrated in terms of Pure Water Flux (PWF), Anti-Fouling studies, and Rejection efficiency. Whereas, PWF increased from 90.49 L·m−2·h−1 for the pristine membrane (ZM-O) to 159.07 L·m−2·h−1 for the optimized membrane (ZM-2), with rejection efficiencies rose from 36.30
Microplastics represent an emerging threat to freshwater ecosystems. However, their seasonal deposition patterns in lake sediments remain poorly understood due to low number of studies, conflicting results and methodological inconsistencies. This study presents the first seasonal microplastic flux records in Icelandic freshwaters, obtained using sediment traps deployed in four lakes near the capital region, including Þingvallavatn, Iceland’s largest natural lake. Materials collected by sediment traps were sampled every six months over two years, yielding 13 samples in an attempt to capture winter versus summer deposition dynamics. All samples underwent standardised laboratory processing (density separation, enzymatic digestion) followed by micro-FTIR analysis (20 µm detection limit). Blank correction was applied based on the Minimum Detectable Amount method. Microplastics were detected in all lakes, with non-zero microplastic fluxes ranging from 54 to 1294 particles m− 2 d− 1. The highest microplastic flux was recorded in Meðalfellsvatn about 25 km NE of Reykjavík while the lowest non-zero flux was recorded for Hafravatn, located on the outskirts of the capital. The results indicated slightly higher winter fluxes, but also demonstrated the complex processes affecting seasonal patterns, linked to hydrological and meteorological variables. Results also highlighted the importance of using flux alongside concentration metrics, as concentration is more relevant for assessing direct exposure to microplastics, particularly for benthic communities, while flux accounts for differences in sediment accumulation rates and provides the temporal constraint necessary to define and compare pollution rates. These findings validate the reliability of using sediment traps for microplastic studies in low-pollution sub-Arctic systems, establish a first baseline for seasonal microplastic fluxes in Icelandic lakes, and demonstrate that flux metrics are essential to study processes affecting microplastic accumulation in sediments and to quantify microplastic pollution inputs.
Microplastics are a pervasive environmental pollutant originating from diverse sources and comprising a wide range of polymer types. Their persistence and widespread release have raised global concern about ecological and animal health risks. (Micro)Plastics are ingested by livestock and excreted in dung, making dung analysis a useful approach for assessing environmental contamination. However, detailed characterisation of microplastics in livestock dung remains limited. This study investigated the abundance and characteristics of microplastics in 499 dung samples collected from chickens, goats, and cattle across 29 farms in rural South Africa. Microplastics were extracted through dung digestion using 30
Plastic pollution has become a central concern for researchers, policymakers, and the public, particularly in light of the negotiations for the Global Plastics Treaty in Geneva in 2025. Over the past two decades extensive research has greatly improved our understanding of the severity of microplastic pollution through occurrence and impact studies. Recently, the focus has shifted from quantifying plastic abundance toward assessing the potential risks and impacts of microplastics on environmental, animal, and human health. Compared to marine, estuarine, and freshwater ecosystems, research on terrestrial ecosystems remains limited. The scarcity of monitoring data makes it hard to assess the current and future ecological risk of microplastic pollution. This lack of data, largely due to methodological challenges, introduces considerable uncertainty in evaluating the effects of microplastics on the environment. Regardless of the studied ecosystem, assessing microplastic risk is inherently complex. A single plastic polymer may contain hundreds of chemical additives (e.g. plasticizers, pigments), adsorb additional pollutants (e.g. pesticides), and even act as a vector for pathogenic organisms. Furthermore, potential effects depend not only on concentration but also on the polymer type, particle size distribution, and morphology. In this reflection paper, we examine these challenges and propose pathways toward more objective microplastic risk assessments.
Abstract Subsampling strategies are commonly employed in microplastic research to reduce the analytical burden associated with time-intensive techniques such as microscopy and Fourier-transform infrared (FTIR) spectroscopy. However, these strategies are often applied without prior validation. This study combined a systematic literature review and numerical simulations to evaluate the effectiveness of subsampling strategies in FTIR-based microplastic analysis. The review considered subtidal marine studies published between 2019 and 2024, revealing 46% applied subsampling. Of these, 50.8% used a constrained-quota random selection (CQRS) approach to select a random subset of putative microplastics for FTIR confirmation, with one-third of the studies analysing fewer than 25% of items. Notably, no standardized method was applied across studies, not even the minimum-percentage approach for subset selection, thereby limiting comparability and robust data interpretation. In addition, terminology used to describe subsampling approaches was inconsistent, further hindering cross-study comparisons. To evaluate how CQRS influences data representativeness, numerical simulations were conducted using a fully characterised (FTIR) real-world dataset comprising 2,137 putative microplastics from eight subtidal matrices (surface water, mid-column water, sediment, fish, coral, sponge, sea squirt, and sea cucumber), applying subsampling thresholds of 25%, 50%, and 75% across 1,000 iterations per matrix. While polymer representativeness improved with increased subsample size, the relationship was non-linear across all matrices and, even at the 75% threshold, reliable representativeness was rarely achieved. Only 15% of polymer types met the effectiveness criterion in at least one of the 1,000 iterations, yet these were not consistently the most abundant polymers found in the original dataset. These findings expose the limitations of current subsampling practices and underscore the need to exercise caution when extrapolating subsampled data to full populations. By demonstrating the risks associated with subsampling, this study highlights the vulnerability of highly heterogeneous samples to misrepresentation and mischaracterization. If subsampling is unavoidable, selection of at least 50% of items represents a practical minimum, and subsampling outcomes and any extrapolations must be reported explicitly and clearly justified. Finally, methodological and technological innovation is urgently needed to improve sample clarification and polymer identification, ensuring the long-term reliability of data used to inform monitoring, mitigation, and regulatory decisions.
Plastics used outdoors are exposed to UV radiation, humidity, and mechanical stress, which cause them to degrade and release degradation by-products. Although additives are commonly incorporated into plastic formulations to improve their durability, their role in micro- and nanoplastics release and other degradation by-product release remains unclear. This study investigated how the initial formulation of polypropylene (PP) influences its environmental degradation. Two formulations were compared: reference PP (without added additives) and PP + 6, containing six industrially representative additives. The pellets were subjected to accelerated UV weathering and subsequently exposed to mechanical agitation in water to simulate environmental mechanical stress. Mass loss, particle size and morphology, and soluble degradation products were quantified using gravimetric, morphometric, and total organic carbon analyses, while surface morphological changes were examined by scanning electron microscopy. The reference PP (without added additives) underwent a three-phase degradation process, reaching a cumulative mass loss of 82 ± 8
Ecological risk assessments for microplastics at steady-state environmental concentrations exist, but these are inherently retrospective and do not account for time-dependent fragmentation processes. As plastics degrade into smaller particles, their exposure, bioaccessibility and consequently their potential risk to biota increase. Here, we present the first prospective, temporally explicit risk assessment framework for fragmenting microplastics, in which exposure assessment is based on particle fragmentation modeling. We apply this framework to the use of polymer-coated fertilizer (PCF) in soils, an agricultural practice with growing demand. The fragmentation model reproduced the PCF concentration data well over the seven-year measurement period of a ten-year field experiment. Food-dilution-based effect thresholds for soil animals and physical-blocking-based effect thresholds for plants, both depending on particle volume, were used to construct species sensitivity distributions (SSDs) and to derive hazardous concentration for 5
Accurate quantification of microplastics (MPs) in soils remains analytically challenging due to complex mineral and organic soil matrices. Microscopy, spectroscopy and thermoanalytical techniques are widely applied to analyse MPs in soils. However, integrated workflows enabling simultaneous assessment of quantitative surface properties remain limited. Surface roughness and complexity may influence particle-environment interactions and are therefore relevant for understanding the environmental behaviour of MPs. This study developed and evaluated an oxidative- and corrosive-substance-free workflow for the simultaneous assessment of MP abundance, size, shape, and quantitative surface roughness and complexity in agricultural soils. The workflow combines density separation with freezing, 3D Laser Scanning Confocal Microscopy (3D LSCM; Keyence VK-X1000, Japan) and machine-learning-based automated detection. In addition to enabling time-efficient particle classification, machine-learning integrates multi-layer 3D LSCM outputs, including height, laser reflection, and colour (RGB) information. Data acquisition was performed at a pixelxy size of 2.7 μm and a height pitch of 4 μm. The method was evaluated using three agricultural topsoils spiked with transparent and black low-density polyethylene and polypropylene fragments (< 53 μm, 53–100 μm, 100–250 μm) and polypropylene fibres (1000 μm length). MPs ≥ 53 μm were reliably detected with a mean recovery of 80
Abstract Analyzing microplastics (MP) and nanoplastics (NP) in sediments remains challenging due to low particle concentrations and complex sample composition. We present an integrated workflow combining oil-based separation with differential scanning calorimetry (DSC) for the isolation and thermal quantification of MP from particulate environmental samples. While the present study focuses on micrometer-sized MP, the methodological principle of oil-based separation combined with DSC provides a scalable foundation for future extending monitoring toward NP. This dual perspective strengthens the relevance of the approach for future environmental analytics. The method enriches MP in an organic phase, facilitates substantial sediment removal, and yields a polymer-rich fraction suitable for DSC-based identification and quantification. Recovery experiments with four common polymers reveal that separation efficiency is primarily influenced by polymer-specific properties such as wettability and density, as well as particle size. Despite moderate recovery rates, the approach proved to be effective for isolating MP < 500 μm from sediment-rich matrices. Its operational simplicity, high matrix reduction, and compatibility with thermal analysis underscore its potential for routine environmental MP monitoring and offer a scalable foundation for future NP detection.
Abstract Studies reporting environmental microplastic (MP) concentrations typically do so for variable MP size ranges, depending on sampling, processing and analytical detection methods. However, MP number concentrations in the environment increase exponentially with decreasing particle size. This leads to difficulties in intercomparison and extrapolation of studies, which is critical for data reviews, plastic dispersion modeling, and environmental and human health risk assessment. In this study, we summarize the current understanding of environmental MP particle size distribution (PSD), based on the power law model. We highlight how standard linear regression of the power law slope is strongly biased by data binning, and show that fitting a cumulative PSD (C-PSD) removes the binning bias. The existing MP size-alignment framework is extended to C-PSDs to extrapolate observed MP number and mass concentrations to the full MP size range (1 to 5000 μm, noted $$\:{MP}_{1-5000\mu\:m}^{}$$ ), or any other sub-size range. We confront the C-PSD power law model with 81 published ocean and atmosphere PSDs from the literature, compiled in the MPsizeBase open access database. We find that fitted power law slopes for fragments (-2.66 ± 0.68) are steeper than for fibers (-1.86 ± 0.36), reflecting fragmentation dimensionality. Among MP fragments, PSD slopes do not vary significantly between the atmosphere, surface and subsurface ocean. We further demonstrate that the large discrepancy between surface ocean MP concentrations measured by net tows and discrete, pumped samples arise primarily from their different minimum detectable MP sizes. After aligning datasets to a common size range, net tow and pumped MP fragment concentrations converge satisfactorily, while MP fiber concentration alignment is more uncertain due to fiber sampling loss and detection limitations. Across all 81 MP PSD datasets analysed, size-aligned $$\:{MP}_{1-5000\mu\:m}^{}$$ number and mass concentrations are respectively 700x and 3x higher than reported concentrations, reflecting the high abundance of small particles predicted by the power law PSD. Together, these findings imply that size extrapolation to a common range is essential to intercompare datasets and to distinguish environmental patterns from methodological artifacts.
Microplastics (fragments < 5 mm) are increasingly studied around the world in a diversity of ecosystems. In contrast, small microplastics (1-100 microns in size) are subject to much less studies because of their small size, which makes them challenging to detect, and their ability to be both airborne and waterborne. Here, we performed epifluorescence imaging to detect small microplastics from fresh snow samples (50 mL) that were collected from 3 sites in the ski area and from 2 sites in the ski resort of Park City, UT, all exposed to different levels of traffic of people. Small microparticles concentrations ranged from 1,000–4,000/50 mL in the ski resort, whereas these numbers ranged from 30 to 3,000/50 mL in the ski area. Against expectations, the higher and most remote site contained the greatest concentrations of microparticles, which increased over the years for each site, as a possible sign to growing airborne sources, both at the local and global levels. As for microfibers concentrations, they ranged from 100 to 3,000/50 mL in the ski resort while these numbers were lower in the ski areas, ranging from 5 to 300/50 mL. These ranges remain similar across years for microfibers in the ski area as these concentrations in the snow seem to be dictated by the amount of snow fall. All the sites showed a percentage of different polymers, such as cotton (23
Abstract Detection of microplastics typically relies on Fourier-transform infrared (FT-IR) Imaging combined with spectral matching to reference polymer databases. However, these databases often lack truly representative spectra of environmentally aged particles, particularly those affected by UV-induced photo-oxidation. Furthermore, degradation mechanisms remain insufficiently understood. In this study, we investigate the UV-induced photo-oxidation of immobilized polyolefin microplastic particles using FT-IR Imaging to track spectral evolution over time. Unlike previous studies based on bulk polymer films, our method fixes microplastic particles on a potassium bromide (KBr) substrate, enabling controlled UV exposure and precise long-term tracking of individual particles throughout the entire process. We apply synchronous and asynchronous two-dimensional correlation spectroscopy (2D-COS), band deconvolution, and power spectrum analysis, to elucidate the evolution of key functional groups. On the example of the common polyolefins polypropylene and polyethylene, our findings show the progressive formation of carbonyl and hydroxyl functional groups, with the carbonyl stretching region undergoing complex spectral changes. Deconvolution analysis demonstrates that the spectral shift within the carbonyl band is predominantly due to the formation of peresters, γ-lactones, and γ-perlactones, rather than previously assumed ketone and ester dominance. Finally, we examine the impact of photo-oxidation on microplastic identification via spectral matching. The degradation process can significantly lower the hit quality index (HQI) when comparing degraded microplastics to standard reference spectra, raising concerns about the reliability of polymer identification in environmental samples. These results highlight the need to incorporate photo-oxidation effects into spectral reference databases to improve microplastic monitoring accuracy.
Abstract Microplastic (MP) pollution in agricultural soils presents emerging risks to soil health, crop productivity, and food safety, yet detecting MPs at low concentrations remains difficult. This study establishes an innovative mid-infrared (MIR) spectroscopy framework combining spectral analysis and wavelength selection to detect MPs in soils. Two common MPs, low-density polyethylene (LDPE) and polyethylene terephthalate (PET), were spiked into sand, loam, and clay soils at concentrations ranging from 0.01 to 0.6%, after which MIR spectra were acquired. The spectra were analysed by comparing selected plastic-indicative wavelengths (PIWs) with soil-indicative wavelengths (SIWs). Soil spectral detection limits (SSDLs) were subsequently derived using SIW: PIW band ratios and MP concentration relationships combined with a Partial Least Squares Regression (PLSR) - Cubist modelling approach. Results showed that soil matrix effects are more influential than polymer identity in controlling SSDL. Sand and loam soils produced the best performance, with low SSDLs and comparatively high R² values for both polymers. Clay, however, caused strong spectral interference, reducing predictive accuracy, although several PET and PE absorption features remained relatively detectable at low concentrations. These trends demonstrate the dominant role of soil texture and mineralogy in shaping the sensitivity and reliability of MIR detection. Overall, integrating soil-specific calibration, targeted wavelength selection, spectral processing, and a hybrid PLSR-Cubist framework enables detection of MPs at low concentrations, with performance dependent on soil mineralogy and texture. These findings highlight MIR spectroscopy, particularly with texture-stratified modelling, as a promising method for low-level MP detection in agricultural soils.
Micro- and nanoplastic particles (MNPs) have emerged as pollutants of high public concern. Assessing and managing the risks of these particles remains challenging for several reasons. A long-term goal is to establish a comprehensive risk-governance framework that includes risk framing, scientifically sound risk assessment that accounts for human and environmental safety, evaluation, and risk management/decision making. A realistic short-term goal is to develop a comprehensive human health risk assessment framework (RAF). Very recently, RAFs for evaluating the human-health risks of MNPs have become available; however, comparative analyses of these frameworks are lacking. Here, we discuss six established frameworks to assess their technological and regulatory readiness. We begin by proposing nine technical criteria that a risk-assessment framework should meet to inform policy and action. These include the degree of quantifiability of outputs; the provision for systematic evaluation of the quality of input data; the consistency between exposure and effect data with respect to underlying mechanisms; the extent to which the complexity and diversity of environmentally realistic microplastics are addressed; readiness for integration into existing regulatory approaches; and the extent of real-world implementation to date. We discuss the specific strengths of each framework and recommend combining them into a single overarching framework that integrates these strengths.
Our daily and continuous exposure to airborne micro- and nanoplastics (MNPs) together with the limited information on their potential hazards, warrants the need for more information on MNP-toxicity. In this study, we investigated the effects of diverse size ranges of amorphous MNPs from environmentally relevant polymers, on Air-Liquid-Interface (ALI)-cultured Normal Human Bronchial Epithelial cells (NHBEs) by analyzing immunological response parameters 24 h after exposure. In addition, we have used this setup to compare the responses of NHBEs to MNPs using nebulization or quasi-ALI (small droplet) exposure. NHBEs responded differently to exposures of polyamide (PA) or polyvinyl chloride (PVC) particles at nominal doses between 0.003 and 0.100 µg/cm2. PA particles < 1 μm (but not those > 1 μm) induced dose-dependent cell death, increased IL-8 secretion and decreased MCP-1 secretion. PVC particles (< 1 μm and 1–5 μm) induced cell death at lower concentrations than PA particles. Also, an increased IL-8 secretion and decreased MCP-1 secretion was observed for PVC particles in all size fractions (< 1 μm, 1–5 μm and 5–10 μm). Comparison of nebulization versus quasi-ALI exposure indicated differences related to the exposure method, but further experimental assessment is needed for definite conclusions and to ensure that the obtained data is relevant for toxicological effects occurring in humans. Our results indicate that PA and PVC particles increase IL-8 secretion and, PA only, decreases MCP-1 secretion. It needs to be established whether these effects on cytokines also indicate an activation of immune cells.
