Spotlight on the vertical migration of aged microplastics in coastal waters
Bibliographic record
Abstract
Coastal waters are complex and dynamic areas with unique environmental attributes that complicate the vertical migration of microplastics (MPs). The MPs that enter coastal waters from diverse sources, including terrestrial, riverine, oceanic, and shoreline inputs undergo various aging pathways. In this study, the variations in the physiochemical characteristics of MPs undergoing various aging pathways and their vertical migration under dynamic conditions subjected to the effects of different MP characteristics and coastal environmental features were comprehensively explored. Opposite effects of aging on the vertical migration of hydrophobic and hydrophilic MPs were observed, with aging appearing to promote the dispersion of hydrophobic MPs but enhance the vertical migration of hydrophilic ones. The positive role of salinity and the negative role of humic acid (HA) concentrations on MP vertical migration were identified, and the mechanisms driving these effects were analyzed. Notably, intense turbulence not only promoted the floating of positively buoyant MPs but also reversed the migration direction of negatively buoyant MPs from downward to upward. Aging-induced changes in MP characteristics had a limited effect on MP vertical migration. The inherent characteristics of MPs and the surrounding environmental features, however, played major roles in their vertical migration dynamics. ENVIRONMENTAL IMPLICATION: Microplastics (MPs) have emerged as a significant global environmental concern and the coastal zones are the hotspots for MP pollution due to their high population density. This study comprehensively investigated the variations in the physiochemical characteristics of MPs undergoing various aging pathways. Their vertical migration patterns under dynamic conditions subjected to the effects of different MP characteristics and coastal environmental features were revealed. The roles of turbulence and MP density in their migration were identified. The findings of this study have important implications for understanding the transport and determining the ecological risks of MPs in coastal waters.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 teacher head, 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".