Papers

Assessment of environmental and socioeconomic drivers of urban stormwater microplastics using machine learning

Using machine learning on data from 107 urban areas worldwide, researchers identified the key factors driving microplastic levels in stormwater runoff, including weather patterns, land use, and waste management practices. The study found that inconsistent definitions of what counts as a "microplastic" across different studies is a major barrier to comparing contamination levels between cities.

An introduction to machine learning tools for the analysis of microplastics in complex matrices

This paper introduces machine learning tools that can speed up the identification and counting of microplastics in complex samples like soil and water. While focused on analytical methods rather than health effects, faster and more accurate detection of microplastics is essential for understanding how much exposure humans actually face through food, water, and the environment.

Form and Function: The Factors That Influence the Efficacy of Nanomaterials for Gene Transfer to Plants

This review discusses using nanoparticles to deliver genes into plant cells for crop improvement, covering factors like particle size, cell wall barriers, and potential toxicity concerns. While focused on agricultural biotechnology rather than microplastics directly, it highlights how nanoscale particles interact with plant biology. Understanding how tiny particles enter and affect plant cells is relevant to research on how nanoplastics may similarly penetrate food crops.

Evaluation of phenotypic and behavioral toxicity of micro- and nano-plastic polystyrene particles in larval zebrafish (<i>Danio rerio</i>)

Researchers exposed zebrafish embryos to polystyrene particles ranging from 50 nanometers to 10 micrometers and found that nearly all sizes caused physical abnormalities and changes in swimming behavior. Smaller particles were taken up more readily and distributed to organs including the brain and gut. These findings are relevant to human health because zebrafish share many biological pathways with humans, and the results suggest that both micro- and nano-sized plastics can cause developmental harm.

Label-Free Identification and Imaging of Microplastic and Nanoplastic Biouptake Using Optical Photothermal Infrared Microspectroscopy

Researchers developed a new imaging technique that can locate and identify microplastic and nanoplastic particles inside whole organisms without needing fluorescent labels. Using a method called optical photothermal infrared microscopy, they tracked polystyrene particles as small as 1 micrometer in roundworms. This tool could help scientists better understand how plastic particles are taken up by living things and where they accumulate in the body.

Automated Machine-Learning-Driven Analysis of Microplastics by TGA-FTIR for Enhanced Identification and Quantification

Researchers developed an automated machine-learning system to identify and measure microplastics using a combination of heat analysis and infrared spectroscopy. The system can distinguish between different plastic types more accurately and faster than manual methods. Better detection tools like this are important because reliable measurement of microplastics in food, water, and the environment is essential for understanding human exposure levels.

Interlaboratory Comparison Reveals State of the Art in Microplastic Detection and Quantification Methods

This large international study compared how 84 laboratories around the world performed when identifying and measuring microplastics using five common detection methods. The results showed significant differences between labs, with spectroscopy-based methods generally outperforming heat-based techniques for accuracy. The findings highlight that standardized methods are urgently needed so that microplastic measurements in food, water, and the environment can be reliably compared across studies.

The exploitation of bio-electrochemical system and microplastics removal: Possibilities and perspectives

This review explores bio-electrochemical systems as a sustainable alternative for removing microplastics from water, since current removal methods are costly, energy-intensive, and can release toxic chemicals. Bio-electrochemical systems use microorganisms to generate electricity while simultaneously treating wastewater, offering a cleaner approach. Though still in early research stages, this technology could provide an efficient and environmentally friendly way to reduce microplastic contamination in water supplies.

Tissue-Specific Biomarker Responses in the Blue Mussel Mytilus spp. Exposed to a Mixture of Microplastics at Environmentally Relevant Concentrations

Researchers exposed blue mussels to an environmentally relevant mixture of polyethylene and polypropylene microplastics at three concentrations and examined tissue-specific responses over 10 days of exposure and 10 days of depuration. They found that microplastics triggered different antioxidant responses in the digestive gland versus the gills, with some evidence of DNA damage and immune system changes. The study highlights that even low, environmentally realistic concentrations of microplastics can induce measurable biochemical stress in marine bivalves.

Nanoplastics in Water: Artificial Intelligence-Assisted 4D Physicochemical Characterization and Rapid In Situ Detection

Researchers developed an artificial intelligence-powered holographic microscopy system that can detect and classify nanoplastics in water in real time, without any sample preparation. The technology identified particles as small as 135 nanometers and tracked their movement in three dimensions. This represents a significant advancement in environmental monitoring, as previous methods required extensive lab processing to detect plastic particles this small.

Identification of microplastics extracted from field soils amended with municipal biosolids

Researchers developed a method for extracting and identifying microplastics from agricultural soils that had been treated with municipal biosolids, a common fertilizer derived from wastewater treatment. They found a variety of plastic polymer types in the soil, confirming that biosolid application is a pathway for microplastic contamination of farmland. The study provides a reliable technique for tracking how microplastics cycle through agricultural environments.

A numerical framework for modeling fate and transport of microplastics in inland and coastal waters

Researchers developed a new three-dimensional numerical framework called CaMPSim-3D for predicting microplastic fate and transport in rivers, lakes, estuaries, and coastal waters. The model couples Lagrangian particle tracking with hydrodynamic modeling to help identify pollution sources and accumulation hotspots, providing a tool for informed decision-making on microplastic prevention and cleanup.

Quantification of microplastics in complex environmental matrices using a tiered approach with modulated differential scanning calorimetry (MDSC)

Researchers developed a method using modulated differential scanning calorimetry to quantify microplastics in biosolids and soil, achieving 1.4-2.5 times higher sensitivity than conventional thermal analysis with detection limits as low as 7 micrograms per gram. They demonstrated an average recovery rate of 93% for four common plastic types extracted from biosolid samples. The study suggests this thermal approach, combined with complementary spectroscopic techniques, provides a reliable and cost-effective tool for measuring microplastics in complex environmental samples.

Dynamic prediction of large spherical and cylindrical microplastic deposition: a machine learning approach for transport and deposition

Researchers developed a machine learning model combined with dimensionless analysis to predict the deposition patterns of spherical and cylindrical microplastics in aquatic environments. The model accounts for varied flow conditions and particle shapes to improve predictions of where microplastics settle in water bodies. The study offers a practical tool for pollution monitoring efforts by helping predict microplastic accumulation hotspots in rivers and oceans.

Analytical chemistry of engineered nanomaterials: Part 1. Scope, regulation, legislation, and metrology (IUPAC Technical Report)

This IUPAC technical report provides a comprehensive overview of analytical chemistry approaches for engineered nanomaterials, covering definitions, regulatory frameworks, metrology standards, and available reference materials for characterizing nanomaterials in consumer products and environmental samples.

Ferroptosis and Wnt/β-Catenin Signaling Triggered by Environmentally Relevant Nanoscale Polypropylene Plastics in Human Intestinal Models

Researchers exposed human intestinal organoids and epithelial cells to environmentally weathered nanoscale polypropylene particles, finding they induce ferroptosis as the primary cell death pathway alongside Wnt/beta-catenin activation as a compensatory protective response, highlighting the importance of using realistic aged nanoplastics and 3D organoid models in health risk assessments.

Quantifying UVC-Induced Aging of Microplastics Using a Multivariate Aging Score

Researchers examined how UVC radiation ages three common types of microplastics and found that polypropylene degraded far more rapidly than polyethylene or PET, developing widespread surface cracks and generating secondary plastic fragments. They developed a multivariate aging score that combines chemical and physical measurements to better quantify how microplastics deteriorate over time. The study also found that colored polypropylene products aged faster than transparent ones, highlighting how product formulation influences environmental breakdown.

Thermogravimetric analysis of microplastics: A mini review

Researchers reviewed thermogravimetric analysis (TGA) — a technique that measures how materials break down with heat — as a tool for identifying and measuring microplastics, finding it promising but underutilized compared to methods like infrared spectroscopy. The review advocates for developing stand-alone TGA methods that could offer a faster and simpler approach to microplastic identification in environmental samples.

Sizing Microplastic Particles Using Acoustic Imaging and Deep Neural Network

Researchers developed an acoustic imaging-based deep neural network system to size microplastic particles in real time, comparing Total Focusing Method and Circular Wave Imaging strategies and achieving accurate particle segmentation from acoustic signals.

Identification of Microplastic Accumulation Zones in a Tidal River: A Case Study of the Fraser River, British Columbia, Canada

Researchers used a 3D hydrodynamic model coupled with a Lagrangian particle tracking model to simulate microplastic transport and identify accumulation zones in the tidal Fraser River in British Columbia. The modelling identified specific depositional hotspots linked to flow velocity gradients, providing a framework for targeted monitoring and remediation.

Quantification and characterization of manufactured nanomaterials shed from face masks

This study measured titanium dioxide nanoparticle shedding from face masks that use TiO2 for antimicrobial properties, finding measurable particle release during simulated wearing conditions — raising concerns about inhalation exposure to manufactured nanomaterials from respiratory protective equipment.

Evaluation of phenotypic and behavioral toxicity of micro- and nano-plastic polystyrene particles in larval zebrafish ( Danio rerio )

Researchers exposed larval zebrafish (Danio rerio) to six sizes (0.05–10.2 µm) and multiple concentrations of polystyrene micro/nanoplastics and assessed toxicity using embryo and behavioral assays. Smaller particles and higher concentrations caused greater phenotypic and behavioral toxicity, with particle uptake and organ distribution confirmed, establishing size as a key determinant of polystyrene MP toxicity in a vertebrate developmental model.

A Laboratory Dataset on Transport and Deposition of Spherical and Cylindrical Large Microplastics for Validation of Numerical Models

This paper presents a laboratory dataset on the transport and deposition of spherical microplastic particles under controlled flow conditions, providing empirical data on how particle size and flow velocity influence settling and lateral dispersion. The dataset is intended to support calibration of microplastic transport models.

Physical and mechanical properties of thermoplastic starch/montmorillonite nanocomposite films