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Entrainment and vertical mixing of aquatic microplastics in turbulent flow: The coupled role of particle size and density

2022· article· en· W4298130356 on OpenAlexafffund
Arefeh Shamskhany, Shooka Karimpour

Bibliographic record

VenueMarine Pollution Bulletin · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMicroplasticsEntrainment (biomusicology)SettlingTurbulenceMixing (physics)Environmental scienceDispersion (optics)Particle (ecology)Particle sizeOceanographyMechanicsGeologyPhysicsEnvironmental engineering

Abstract

fetched live from OpenAlex

Diversity in microplastics' characteristics, including their size, affects their transport and distribution in aquatic systems. Furthermore, turbulent induced mixing is often considered dominant in the dispersion of sediments and contaminants in marine and freshwater systems, which is also affected by particle size. The aim of this study is to investigate the effect of microplastics' size and polymer density on their mixing behaviour in response to turbulent structures. Using sediment analogy, several parameters are defined to describe entrainment patterns of microplastic particles of common polymers. Our results indicate that the level of mixing of microplastics in turbulent flow can vary several orders of magnitude. While large particles' vertical motion may be dominated by gravitational settling or rising, the motion of fine microplastics is mainly governed by the ambient turbulent flow. Our findings provide a plausible explanation for the presence of fine microplastics in remote areas.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.737
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.004
GPT teacher head0.168
Teacher spread0.165 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations54
Published2022
Admission routes2
Has abstractyes

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