Atmospheric transport dynamics of microplastic fibres
Bibliographic record
Abstract
Microplastics have been identified in most terrestrial areas of Earth including rural, remote and isolated locations where the only likely source is through atmospheric transport and deposition.  To date there has been limited attention paid to the fundamentals of microplastic transport by wind, and in particular, the similarities and differences between the motion of mineral grains and microplastic particles within boundary layer flows.  These fundamentals are key to future modelling of mineral-microplastic interaction in the atmosphere.  This research examines the dynamics of microplastic entrainment and transport by wind, focusing on fibres which are one of the most common shapes associated with aeolian systems.  A series of particle tracking velocimetry (PTV) experiments was conducted in a boundary layer wind tunnel to determine how nylon fibres (4 mm length) travel through the air and interact with the ground surface. The high-speed camera images show that the silhouette area presented to the wind has a high degree of temporal variability for fibres, as compared to sedimentary particles, affecting the fluid drag (e.g. form versus skin friction), translational versus rotational energy, and lift.  The motion of plastic particles in the flow follows a variety of different patterns, including end-over-end cartwheeling and horizontal transport with the long-axis oriented flow parallel. The progression of an airborne plastic particle through different motion types (a "lifecycle") appears to be orderly, despite a wide variability in the length of time spent in each particular motion type. Travelling across a mobile sand bed, microplastic fibres are observed to dislodge and cause the ejection of sand particles suggesting they can contribute to the development of the saltation cloud and may have the potential to reduce the threshold velocity for sand transport.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".