Temporal Archive of Atmospheric Microplastic Deposition Presented in Ombrotrophic Peat
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Ombrotrophic peatland─fed solely from atmospheric deposition of nutrients and precipitation─provide unique archives of atmospheric pollution and have been used to illustrate trends and changes in atmospheric trace element composition from the recent decadal to the Holocene period. With the acknowledgment of atmosphere plastic pollution, analysis of ombrotrophic peat presents an opportunity to characterize the historical atmospheric microplastic pollution prevalence. Ombrotrophic peatland is often located in comparatively pristine mountainous and boreal areas, acting as sentinels of environmental change. In this paired site study, a Sphagnum ombrotrophic peat record is used for the first time to identify the trend of atmospheric microplastic pollution. This high altitude, remote location ombrotrophic peat archive pilot study identifies microplastic presence in the atmospheric pollution record, increasing from <5(±1) particles/m 2 /day in the 1960s to 178(±72) particles/m 2 /day in 2015–2020 in a trend similar to the European plastic production and waste management. Compared to this catchment’s lake sediment archive, the ombrotrophic peat core appears to be effective in collecting and representing atmospheric microplastic deposition in this remote catchment, collecting microplastic particles that are predominantly ≤20 μm. This study suggests that peat records may be a useful tool in assessing the past quantities and trends of atmospheric microplastic.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".