Climate change influence on the levels and trends of persistent organic pollutants (POPs) and chemicals of emerging Arctic concern (CEACs) in the Arctic physical environment – a review
Bibliographic record
Abstract
<p>Climate change brings about significant changes in the physical environment in the Arctic. Increasing temperatures, sea ice retreat, slumping permafrost, changing sea ice regimes, glacial loss and changes in precipitation patterns can all affect how contaminants distribute within the Arctic environment and subsequently impact the Arctic ecosystems. In this review, we summarized observed evidence of the influence of climate change on contaminant circulation and transport among various Arctic environment media, including air, ice, snow, permafrost, fresh water and the marine environment. We have also drawn on parallel examples observed in Antarctica and the Tibetan Plateau, to broaden the discussion on how climate change may influence contaminant fate in similar cold-climate ecosystems. Significant knowledge gaps on indirect effects of climate change on contaminants in the Arctic environment, including those of extreme weather events, increase in forests fires, and enhanced human activities leading to new local contaminant emissions, have been identified. Enhanced mobilization of contaminants to marine and freshwater ecosystems has been observed as a result of climate change, but better linkages need to be made between these observed effects with subsequent exposure and accumulation of contaminants in biota. Emerging issues include those of Arctic contamination by microplastics and higher molecular weight halogenated natural products (hHNPs) and the implications of such contamination in a changing Arctic environment is explored. </p>
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".