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Record W4411398464 · doi:10.1017/plc.2025.10004.pr8

Decision: Atmospheric microplastics must be addressed in the global plastics treaty — R1/PR8

2025· peer-review· en· W4411398464 on OpenAlexaffabout

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMicroplasticsTreatyEnvironmental scienceBusinessEnvironmental chemistryChemistryPolitical scienceLaw

Abstract

fetched live from OpenAlex

The goal of the Global Plastics Treaty is to “end plastic pollution and to protect human and environmental health.” Despite overwhelming evidence of the adverse impacts of microplastics on human and environmental health, the inclusion of how microplastics will be addressed within the Global Plastics Treaty remains unclear. Yet, a contaminant as morphologically and chemically diverse as microplastics should be considered a priority for regulation under the Global Plastics Treaty like the 1979 Convention on Long-Range Transboundary Air Pollution (CLRTAP). As the goal of finalizing the Global Plastics Treaty at INC-5 was not realized, a valuable opportunity to push for more inclusion and objectives that include atmospheric microplastics exists. To ensure that atmospheric microplastics are present within the Global Plastics Treaty text, the following are recommended. Ensure that inclusion of terms “air” and/or “atmosphere” and/or “atmospheric microplastics” be present alongside other environmental compartments like terrestrial and aquatic (marine and freshwater) environments. Capping plastic production is critical to reducing subsequent microplastic pollution. Improving product design or developing microplastic capture technologies should be prioritized for plastic products known to contribute to atmospheric microplastic pollution. Empirical targets should be established to mitigate emissions of atmospheric microplastics from “leaky” regions (e.g., urban centres and industrial regions), and targets should also be placed on activities that result in generation and release of secondary microplastics (e.g., dryer emissions and automotive tires). A framework to reduce pollution should be informed by the structure of other relevant successful multilateral air pollution agreements (e.g., the Montreal Protocol and CLRTAP), and goals should be informed by the present science and data obtained from monitoring. A global network of atmospheric monitoring observatories should be established to identify “leaky” regions or sources/activities and monitor temporal changes in microplastic concentrations via long-range processes. Establish specialized working groups of global experts that can develop and harmonize atmospheric microplastic monitoring and analytical methods. Assess effectiveness of mitigation and reduction strategies for atmospheric microplastics in relation to the empirical targets established by the Global Plastics Treaty. Additionally, atmospheric microplastics can be used as a metric to ensure that broader scale changes to pollution reduction strategies implemented by the Global Plastics Treaty are effective.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.047
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0060.005
Open science0.0040.003
Research integrity0.0470.016
Insufficient payload (model declined to judge)0.0360.027

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 head0.017
GPT teacher head0.273
Teacher spread0.255 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2025
Admission routes2
Has abstractyes

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