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20 resultsShowing papers similar to Predicted settling velocity of sampled MPFs
ClearAdditional data for "Settling Velocities of Small Microplastic Fragments and Fibers"
This data repository provides raw settling velocity measurements for small microplastic fragments and fibers, supporting a publication on their transport behavior in water. Settling velocity data is critical for modeling where microplastics deposit in rivers, lakes, and ocean sediments.
Improved Settling Velocity for Microplastic Fibers: A New Shape-Dependent Drag Model
A new shape-dependent drag model was developed to improve the accuracy of settling velocity predictions for microplastic fibers, addressing a major limitation of existing drag models that significantly underpredict fiber settling in aquatic environments.
Settling velocity of submillimeter microplastic fibers in still water
The settling velocity of 519 submillimeter microplastic fibers (300-600 micrometers long) was measured in still water, finding that settling rates vary considerably by fiber length and orientation, informing models of microplastic fiber transport and deposition in aquatic systems.
Settling Velocities of Small Microplastic Fragments and Fibers
Researchers precisely measured the settling speeds of over 4,000 small microplastic particles in water and found that existing prediction models designed for larger microplastics do not work well for these tiny fragments and fibers. The settling speed depends on each particle's size, density, and shape, with the smallest particles sinking extremely slowly. Understanding how quickly microplastics settle in water is important because it determines how far they travel and how long they remain available to be consumed by aquatic organisms that humans may eventually eat.
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.
Additional data for "Settling Velocities of Small Microplastic Fragments and Fibers"
Researchers provided supplementary data for a study on settling velocities of small microplastic fragments and fibers, including single-particle raw data from settling experiments, computed drag coefficients for each measured MP fragment and fiber, and protocols for preparing microfibers for analysis.
Machine learning-based prediction for settling velocity of microplastics with various shapes
Researchers developed machine learning models to predict the settling velocity of microplastics based on their size, density, and shape. They classified microplastic shapes into fiber, film, and fragment categories and identified the optimal shape parameter for each, achieving significantly better prediction accuracy than existing theoretical models. The study reveals that particle size has the greatest influence on settling velocity, which is important for understanding how microplastics move and distribute in water environments.
Towards realistic predictions of microplastic fiber transport in aquatic environments: Secondary motions
Researchers developed an improved drag model for predicting microplastic fiber settling in water by incorporating secondary motions including tumbling and oscillation in addition to the standard drag forces. Secondary motions profoundly affect settling trajectories and deposited positions, and the new model outperforms existing approaches that neglect these behaviors.
Effects of Particle Properties on the Settling and Rise Velocities of Microplastics in Freshwater under Laboratory Conditions
Physical experiments quantified the settling and rise velocities of ~500 microplastic particles of varying shapes, sizes, and densities under controlled laboratory conditions, finding velocities ranging from 0.39 cm/s (settling polyamide fibers) to 31.4 cm/s (rising expanded polystyrene), with standard sediment transport formulas inadequate for fibers. The study provides empirical data needed to improve models of microplastic transport in rivers and lakes.
Towards A universal settling model for microplastics with diverse shapes: Machine learning breaking morphological barriers
Researchers developed a machine learning model to predict the settling velocity of microplastics across different shapes, including fragments, films, and fibers. Unlike existing models limited to specific morphologies, this approach works universally across all three particle types. The study provides a more reliable tool for modeling how microplastics move through and deposit in aquatic environments.
Settling velocity of microplastic particles having regular and irregular shapes
Researchers measured how quickly microplastic particles of various shapes settle through water, testing 66 different particle types including spheres, cylinders, fibers, and irregular fragments. They found that particle shape significantly affects settling speed, with fibers and flat shapes sinking more slowly than spheres of the same size. The study provides new equations for predicting where microplastics end up in oceans and waterways based on their shape.
Correction to “SettlingVelocities of SmallMicroplastic Fragments and Fibers”
This paper provides a published correction to a prior study on settling velocities of small microplastic fragments and fibers, addressing errors in the original data, calculations, or figures to ensure accurate reporting of particle sedimentation behavior relevant to environmental transport modeling.
Gravitational settling of microplastic fibers: experimental results and implications for global transport
This study measured the gravitational settling velocities of microplastic fibers and found that their non-spherical shape causes them to settle much more slowly than spheres of the same volume. Current atmospheric transport models that assume spherical particles significantly underestimate how long fibers remain airborne. These results have important implications for predicting how far microplastic fibers can travel before depositing.
Settling velocities of microplastics with different shapes in sediment-water mixtures
Researchers studied how the shape of microplastic particles affects how quickly they sink in water containing suspended sediment. They found that fibers and films settle much more slowly than fragments and pellets, and that sediment in the water significantly slows the settling of all microplastic types. These findings are important for predicting where microplastics accumulate in lakes, rivers, and oceans.
Settling and rising velocities of environmentally weathered micro- and macroplastic particles
Researchers measured settling and rising velocities of environmentally weathered micro- and macroplastic particles collected from rivers, finding that existing predictive formulas developed for virgin pellets, fragments, and foams transferred reasonably well to weathered particles but were less accurate for films and larger macroplastics.
Microfiber behavior in turbulence and in quiescent conditions: insights from 3D high-speed measurements
Researchers investigated the settling dynamics of microplastic fibers with high aspect ratios under turbulent and quiescent airflow conditions, using 3D high-speed measurements to show that existing drag models fail to accurately predict settling velocities of these anisotropic curved fibers with diameters of 10-100 micrometers.
Data on the gravitational settling experiment and FLEXPART simulations output
This is a dataset accompanying a research paper on long-range atmospheric transport of microplastic fibers, providing gravitational settling measurements and FLEXPART dispersion model simulation outputs. The companion paper demonstrates that the shape of microplastic particles significantly influences how far they can be carried in the atmosphere.
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.
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.
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.