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Record W4281687667 · doi:10.1021/acs.est.2c01599

Transport of Microplastics in Shore Substrates over Tidal Cycles: Roles of Polymer Characteristics and Environmental Factors

2022· article· en· W4281687667 on OpenAlexafffund
Feng Qi, Zhi Chen, Charles W. Greer, Chunjiang An, Zheng Wang

Bibliographic record

VenueEnvironmental Science & Technology · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsMcGill UniversityNational Research Council CanadaConcordia University
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaFisheries and Oceans CanadaEnvironment and Climate Change Canada
KeywordsMicroplasticsSeawaterWater columnShoreSubstrate (aquarium)Environmental scienceSalinityOceanographyPolyethyleneHydrology (agriculture)Environmental chemistryChemistryGeologyGeotechnical engineering

Abstract

fetched live from OpenAlex

Tidal zones providing habitats are particularly vulnerable to microplastic (MP) pollution. In this study, the effects of tidal cycles on the transport of MPs (4-6 μm polyethylene, PE1; 125 μm polyethylene, PE2; and 5-6 μm polytetrafluoroethylene, PFTE) in porous media combined with various environmental and MPs properties were systemically investigated. The results indicated that smaller substrate sizes exhibited higher retention percentages compared to those of larger substrate sizes under different tidal cycles. In terms of the size of MPs, a larger size (same density) was found to result in enhanced retention of MPs in the column. As the number of tidal cycles increased, although the transport of MPs from the substrate to the water phase was enhanced, PE1 was washed out more with the change in water level, compared to PTFE. Additionally, more MPs were retained in the column with the increase of salinity and the decrease of flow velocity under the same tidal cycles. Ultraviolet and seawater aged PE1 showed enhanced transport, while aged PTFE showed enhanced retention under the same tidal cycles. These results can help understand the MP behaviors in the shoreline environment and provide support for future cleanup and sampling in tidal zones.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.235
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 studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.177
Teacher spread0.173 · 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 designObservational
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

Citations55
Published2022
Admission routes2
Has abstractyes

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