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20 resultsShowing papers similar to Adding depth to microplastics for particle characterization and assessing settling behavior
ClearAdding depth to microplastics for particle characterization and assessing settling behavior
This study developed methods to characterize microplastics in three dimensions rather than the conventional two-dimensional approach, obtaining volume and shape data that improves predictions of how particles settle and transport in water systems. Three-dimensional characterization significantly improved settling rate predictions compared to 2D image-based estimates.
Adding Depth to Microplastics
Researchers developed a new model for converting 2D microplastic measurements from spectroscopic and image analysis into 3D parameters such as volume and surface area, without requiring calibration for each particle set. Accurate 3D characterization is important because the biological effects and environmental risks of microplastics depend on their volume and accessible surface area.
Inclusion of shape parameters increases the accuracy of 3D models for microplastics mass quantification
Researchers found that incorporating shape parameters into 3D geometric models significantly improves the accuracy of microplastic mass quantification, providing a more reliable method for measuring microplastic concentrations in environmental samples.
Mass concentration of plastic particles from two-dimensional images
Researchers developed methods to estimate the mass of microplastic particles from two-dimensional images, which is important because toxicity studies need mass-based exposure data rather than just particle counts. They found that reasonable mass estimates are possible but require additional information about particle thickness, especially for flat or elongated shapes. This methodological advance could improve the accuracy of microplastic exposure assessments used to evaluate human health risks.
Towards better predicting the settling velocity of film-shaped microplastics based on experiment and simulation data
Researchers combined experimental and simulation data to better predict how film-shaped microplastics settle through water, since most existing models are based on spherical particles. They found that the particle definition approach was more suitable than equivalent spherical diameter for characterizing flat, irregular microplastics. The improved settling velocity predictions could help scientists better understand how film-shaped microplastics travel and accumulate in aquatic environments.
Morphological description of microplastic particles for environmental fate studies
Researchers proposed a standardized morphological classification system for microplastic particles based on three-dimensional measurements of the smallest enclosing parallelepiped, offering a more objective framework for describing particle shape to improve cross-study comparability.
Three-Dimensional Settling Dynamics of Environmental Microplastics
Researchers measured the three-dimensional settling dynamics of environmental microplastic particles in water, including lateral drift, settling paths, and horizontal velocities—dimensions poorly understood beyond simple vertical settling rates. The findings are essential for developing accurate models of how MPs distribute across river channels and water columns.
An Accurate Size-Probability Distribution Method for Converting Microplastic Counts to Mass
Researchers developed a size-probability distribution method to convert microplastic particle counts into mass estimates without requiring detailed morphological measurements for every particle, addressing a key gap in environmental monitoring where mass-based reporting is needed but count-based data is more commonly generated.
A new model for the terminal settling velocity of microplastics
A new empirical model for the terminal settling velocity of microplastics was developed and validated using 1,343 experimental measurements covering a range of particle shapes and materials. The model improves predictions of microplastic sedimentation rates, which are critical for understanding how plastic particles are transported and deposited in water bodies.
Introduce multivariate two-dimensional information to establish a data-driven volume estimation model for complex microplastic fibers
Researchers introduced a machine learning framework using image recognition to estimate the volume of microplastic fibers from 2D images without relying on geometric simplifications, achieving more accurate volume estimates for curved and irregular fibers than traditional length-width calculations.
Modeling Microplastic Transport in the Marine Environment: Testing Empirical Models of Particle Terminal Sinking Velocity for Irregularly Shaped Particles
Researchers tested multiple drag models for predicting the terminal settling velocity of irregularly shaped microplastic particles in seawater, identifying three high-precision models and demonstrating that settling velocity is largely stable across ocean depths and independent of initial particle velocity, improving the accuracy of marine microplastic transport simulations.
Improving Environmental Microplastic Extrapolation: From Field of View to Full Sample, and from Microplastic 2D‐Morphology to Mass
Measuring microplastics in environmental samples using microscopy is time-consuming, so researchers typically examine only a small portion of each sample and extrapolate — but current methods introduce errors of 50–80%. This study introduces a more reliable area-based extrapolation technique and a simplified formula for estimating the mass of microplastic particles from their two-dimensional shapes under a microscope. These methodological advances are important because without accurate and standardized measurement methods, it is difficult to compare microplastic pollution levels across different studies or track changes over time.
A new modeling approach for microplastic drag and settling velocity
Researchers developed a novel machine learning-based modelling framework to predict drag coefficients and settling velocities for microplastics of varying shapes (1D, 2D, 3D, and mixed) in aquatic environments. The framework achieved coefficient of determination values of 0.86-0.95 for drag models, outperforming traditional theoretical and data-fitting approaches in both speed and accuracy.
Shape analysis of microplastic fragments: A computed microtomography study
Researchers applied X-ray microtomography (microCT) to characterize the 3D morphology of five secondary PET microplastic fragments approximately 2 mm in diameter, achieving a voxel size of 6.0 micrometers through optimized scanning and image processing, providing more detailed shape characterization of irregular fragments than conventional 2D microscopy allows.
Empirical Shape-Based Estimation of Settling Microplastic Particles Drag Coefficient
This study experimentally measured the settling behavior of flat square microplastic particles in water, finding that shape significantly affects sinking speed and drag compared to spherical particles. Understanding how microplastic shapes influence settling is essential for modeling where plastics accumulate in rivers and ocean sediments.
Rapid Mass Conversion for Environmental Microplastics of Diverse Shapes
Researchers developed a faster and more accurate method for converting microplastic counts into mass estimates, which is critical for calculating how much plastic rivers carry to the ocean. Using deep learning to classify microplastic shapes and a new approach to estimating thickness, the models reduced estimation errors by sevenfold compared to previous methods while saving about two hours per hundred particles analyzed.
Coupled CFD-DEM modelling to assess settlement velocity and drag coefficient of microplastics
Researchers used computational fluid dynamics coupled with particle simulations to model how the size, shape, and density of microplastics affect their settling velocity and drag in water. Accurate physical models of microplastic behavior are essential for predicting where particles accumulate in rivers, lakes, and the ocean.
Characterizing the multidimensionality of microplastics across environmental compartments
Researchers characterized the size, shape, polymer type, volume, and mass of over 60,000 individual microplastic particles collected from various aquatic environments including surface water, sediments, and organisms. They found that particle size distributions follow predictable mathematical patterns that differ by environmental compartment and polymer type. The findings provide a framework for more realistic risk assessments by capturing the full diversity of microplastic characteristics relevant to toxicology.
On some physical and dynamical properties of microplastic particles in marine environment
This study examined the physical and dynamical properties of microplastic particles in marine environments, using modeling to predict how particle shape, density, and size govern transport, dispersion, and accumulation patterns.
Evaluating factors influencing microplastic mobility in sediments through visualization and experiments
Researchers used micro-CT imaging to visualize three-dimensional transport pathways of microplastics through gravel and sand sediments relevant to riverbank filtration, finding that smaller sediment pore sizes restrict microplastic mobility and that particle properties such as shape, size, and polymer density influence infiltration depth.