Oxidation and fragmentation of plastics in a changing environment; from UV-radiation to biological degradation
Bibliographic record
Abstract
Understanding the fate of plastics in the environment is of critical importance for the quantitative assessment of the biological impacts of plastic waste. Specially, there is a need to analyze in more detail the reputed longevity of plastics in the context of plastic degradation through oxidation and fragmentation reactions. Photo-oxidation of plastic debris by solar UV radiation (UVR) makes material prone to subsequent fragmentation. The fragments generated following oxidation and subsequent exposure to mechanical stresses include secondary micro- or nanoparticles, an emerging class of pollutants. The paper discusses the UV-driven photo-oxidation process, identifying relevant knowledge gaps and uncertainties. Serious gaps in knowledge exist concerning the wavelength sensitivity and the dose-response of the photo-fragmentation process. Given the heterogeneity of natural UV irradiance varying from no exposure in sediments to full UV exposure of floating, beach litter or air-borne plastics, it is argued that the rates of UV-driven degradation/fragmentation will also vary dramatically between different locations and environmental niches. Biological phenomena such as biofouling will further modulate the exposure of plastics to UV radiation, while potentially also contributing to degradation and/or fragmentation of plastics independent of solar UVR. Reductions in solar UVR in many regions, consequent to the implementation of the Montreal Protocol and its Amendments for protecting stratospheric ozone, will have consequences for global UV-driven plastic degradation in a heterogeneous manner across different geographic and environmental zones. The interacting effects of global warming, stratospheric ozone and UV radiation are projected to increase UV irradiance at the surface in localized areas, mainly because of decreased cloud cover. Given the complexity and uncertainty of future environmental conditions, this currently precludes reliable quantitative predictions of plastic persistence on a global scale.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".