Micro- and nanoplastics as transport vectors for organic contaminants in the environment: A critical review
Bibliographic record
Abstract
The impact of micro- and nanosized plastic particles on the mobility of organic contaminants in the environment is a topic of ongoing scientific debate. Their extensive surface area and capacity to interact with organic contaminants have led to frequent concerns that micro- and nanoplastics significantly enhance their mobility and facilitate contaminant uptake by marine biota. For terrestrial systems, this hypothesis has been adopted, raising concerns that plastic particles could facilitate the transport of contaminants into deeper soil layers, thereby posing a threat to groundwater resources, especially in agricultural soils. These soils receive substantial plastic input through various sources, such as organic soil amendments, mulch, recycled wastewater, and atmospheric deposition. This review examines the molecular interactions between organic contaminants, including a wide range of non-intentionally added substances and additives, and plastic interfaces. We critically analyze the role of micro- and nanoplastics as vectors for contaminants in both marine environments and agricultural soils. Our analysis suggests that the vector effect of contaminants via micro- and nanoplastics in the marine environment is generally insignificant compared to other exposure routes. Our calculations regarding the mass transfer of common plastic additives indicate that the role of micro- and, particularly, nanoplastics as carriers for the majority of organic contaminants in agricultural soils is limited due to rapid desorption rates. Although micro- and nanoplastics do not considerably contribute to transport phenomena as vectors, it is crucial to recognize that they are significant sources of potentially harmful contaminants. These issues must be addressed in the forthcoming INC-5 plastic treaty.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".