First record of pyroplastic and partially burnt plastic litter along South African shores
Bibliographic record
Abstract
As plastic pollution has accumulated in the natural environment over the last half-century, so too has the body of literature on plastic contamination assessment. Despite this growing research, new, and cryptic forms of plastic debris continue to emerge, with limited data on their composition and abundance. Among these novel pollutants is a type of marine litter derived from the burning or melting of manufactured plastics. In this study, we report for the first time the presence of burned plastic forms at selected intertidal sandy habitats along the South African coast. We examined both pyroplastics—molten items with rock-like properties due to environmental weathering—and partially burned plastics, which retain features of the original manufactured objects. Surveys conducted across 22 sites spanning over 2000 km revealed this new type of litter at 19 locations, predominantly composed of polyethylene (37 items), polyethylene terephthalate (12 items), polypropylene (5 items) and polystyrene (3 items), with an average weight of 5.4 g per item. These findings highlight the widespread presence of burned plastics in coastal environments in South Africa and emphasize the need for further research into their ecological impacts. • First report of pyroplastic litter along South African intertidal habitats. • Surveys across 22 sites revealed pyroplastics at 19 locations. • Pyroplastics predominantly composed of PE, PET, PP, and PS. • Average weight of pyroplastic items was 5.4 g. • Findings emphasize need for research on ecological impacts of pyroplastics.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".