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How size-dependent settling can both bias and inform microplastics observations
Summary
Scientists studying how microplastics move and settle in water found that a particle's shape and size matter far more than the math formulas used to predict its movement — and shape/size data is often missing from real-world studies. This matters because tiny and large plastic particles sink or float at very different rates, which means water samples may be over- or under-counting certain particle sizes, making it harder to accurately assess how much microplastic — and what sizes — people and marine life are actually exposed to.
Abstract Particle settling and rise velocities play a central role in modeling microplastic (MP) transport, residence times, and distributions in aquatic systems. Recent studies have focused on deriving accurate models for MP settling velocities, but the detailed particle-shape information required is usually unavailable in real-world data. Here, we investigate the relative importance of settling velocity model choice versus particle size and shape information using a previously published laboratory dataset of measured settling velocities for irregular MP fragments. We find that uncertainty in particle geometry dominates model error, while differences between commonly used settling velocity models are comparatively small. Settling and rise velocities vary widely across realistic MP sizes and shapes, which leads to orders-of-magnitude differences in residence times. We show how this differential settling can alter observed particle size distributions: for example, even when the underlying fragmentation spectrum follows a power law, we find separate power-law exponents for large and small particles due to differential vertical transport. Our results imply that improving geometric characterization of particles is more critical for modeling vertical transport than further refinement of settling formulas, and that commonly used power-law extrapolations across size classes may be physically inconsistent. These findings have direct implications for interpreting MP observations and for the harmonization and risk-assessment frameworks that rely on size-distribution corrections.