Cryosphere as a temporal sink and source of microplastics in the Arctic region
Bibliographic record
Abstract
a b s t r a c t Microplastics (MPs) pollution has become a serious environmental issue of growing global concern due to the increasing plastic production and usage.Under climate warming, the cryosphere, defined as the part of Earth's layer characterized by the low temperatures and the presence of frozen water, has been experiencing significant changes.The Arctic cryosphere (e.g., sea ice, snow cover, Greenland ice sheet, permafrost) can store and release pollutants into environments, making Arctic an important temporal sink and source of MPs.Here, we summarized the distributions of MPs in Arctic snow, sea ice, seawater, rivers, and sediments, to illustrate their potential sources, transport pathways, storage and release, and possible effects in this sentinel region.Items concentrations of MPs in snow and ice varied about 1-6 orders of magnitude in different regions, which were mostly attributed to the different sampling and measurement methods, and potential sources of MPs.MPs concentrations from Arctic seawater, river/ lake water, and sediments also fluctuated largely, ranging from several items of per unit to >40,000 items m À3 , 100 items m À3 , and 10,000 items kg À1 dw, respectively.Arctic land snow cover can be a temporal storage of MPs, with MPs deposition flux of about (4.9-14.26)Â 10 8 items km À2 yr À1 .MPs transported by rivers to Arctic ocean was estimated to be approximately 8-48 ton/yr, with discharge flux of MPs at about (1.65-9.35)Â 10 8 items/s.Average storage of MPs in sea ice was estimated to be about 6.1Â10 18 items, with annual release of about 5.1Â10 18 items.Atmospheric transport of MPs from long-distance terrestrial sources contributed significantly to MPs deposition in Arctic land snow cover, sea ice and oceanic surface waters.Arctic Great Rivers can flow MPs into the Arctic Ocean.Sea ice can temporally store, transport and then release MPs in the surrounded environment.Ocean currents from the Atlantic brought high concentrations of MPs into the Arctic.However, there existed large uncertainties of estimation on the storage and release of MPs in Arctic cryosphere owing to the hypothesis of average MPs concentrations.Meanwhile, representatives of MPs data across the large Arctic region should be mutually verified with in situ observations and modeling.Therefore, we suggested that systematic monitoring MPs in the Arctic cryosphere, potential threats on Arctic ecosystems, and the carbon cycle under increasing Arctic warming, are urgently needed to be studied in future.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".