Irreversible Plastic Flows and Sedimentary Ecological Entrapment: A Critical Review of Legacy Risks and Governance Strategies for Planetary Health
Bibliographic record
Abstract
Plastic pollution has emerged as a pervasive and systemic driver of ecological and biogeochemical disruption in freshwater and marine environments. Unlike natural materials that circulate within closed biogeochemical loops, synthetic polymers predominantly follow unidirectional and irreversible trajectories, a phenomenon we describe as "irreversible plastic transport." These flows culminate in sedimentary entrapment, where plastics persist as long-term ecological stressors and potential vectors of contaminant transfer. Recent global syntheses indicate that sedimentary microplastic loads can exceed 27,000 particles/kg dry weight in certain river systems, highlighting the urgency of sediment-inclusive risk assessments. This review synthesizes interdisciplinary findings to conceptualize plastics as both pollutants and governance challenges. We highlighted the dominant transport pathways of micro- and nanoplastics and emphasize that sedimentary sinks are critical long-term retention zones. Current monitoring frameworks often underestimate sedimentary burdens by focusing on surface water and overlooking subsurface ecological legacies. We propose an integrated governance approach combining cross-media monitoring, Earth system modeling, and adaptive policies to address these persistent synthetic agents. Embedding plastic dynamics within comprehensive risk assessment frameworks is essential for sustainable water management during the Anthropocene. Our synthesis supports risk-based decision-making and encourages proactive, transdisciplinary global governance strategies that integrate sediment-focused monitoring and long-term ecological risk management.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".