An Atmospheric Chemistry Perspective on Airborne Micro- and Nanoplastic Particles
Bibliographic record
Abstract
Micro- and nanoplastic particles (MNPPs) are emerging pollutants with significant environmental impacts due to their persistence, increasing concentrations, and potential health risks. Most MNPP studies have focused on identifying, quantifying, and assessing their ecotoxicological impacts in water or soil. However, the atmosphere is crucial in transporting and chemically transforming MNPPs. Further, well-established aerosol particle characterization techniques are underutilized and inconsistently applied in existing atmospheric MNPP studies. This perspective synthesizes the existing literature and addresses future research needs unique to atmospheric MNPPs, highlighting the need to bridge the microplastics and atmospheric aerosol communities to better understand their sources, chemical transformations, transport mechanisms, as well as their health effects and ecological impacts, which differ from those in soil and water. Advancing research in these areas requires standardized methods and a multidisciplinary approach to comprehensively assess MNPP interactions across environmental compartments, providing essential insights into their environmental fate and risks.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".