Numerical simulations of non-buoyant plastic dispersion around the Iberian Peninsula
Bibliographic record
Abstract
The continuous release and accumulation of plastics in the ocean is a major environmental concern as shown by the ongoing negotiations for a Global Plastics Treaty led by the United Nations. Numerical models have proven to be valuable tools to improve our knowledge about how marine plastics disperse, identifying, for example, accumulation areas and the pathways followed by plastics to reach them. While models have been widely used for studying floating plastic, there are fewer studies focused on plastic accumulation on the seafloor. In this study, we used a 3D Eulerian model to predict the accumulation patterns of non-floating plastics around the Iberian Peninsula. We selected four of the most common types of plastics and distinguished two scenarios: one considering only plastics from land-based sources and another from sea-based activities. The integrations simulate the dispersion of plastics over 5 years, starting from a plastic-free sea and modeling the daily introduction of plastics into the sea as would be expected under real conditions. Our experiments show an area virtually free of plastics in the southwestern Gulf of Cadiz, likely due to the magnitude of the deep-sea currents occurring in this region, which prevent plastics from settling down. Non-buoyant plastics originating in the coast tend to accumulate on the continental shelf but can gradually disperse into the open ocean and even reach seamounts, depending on how far these seamounts are from land. The inclusion of sea-sourced plastics results, as expected, in a more widespread distribution of plastics towards the open sea. • Plastic pollution is a major threat, able to reach almost every part of the ocean. • The study shows how most plastic debris was transported and settled on the seafloor. • Marine currents are a key factor in the final location of plastic debris. • Marine-sourced plastic can reach areas inaccessible to land-based debris.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".