Ice core studies of anthropogenic sulfate and nitrate trends in the Arctic
Bibliographic record
Abstract
Ice core studies have shown that sulfate and nitrate concentrations in Arctic snow have increased significantly since the end of the 19th century due to the influx of anthropogenic pollutants transported from industrialized regions. Trends of increasing sulfate and nitrate concentrations in snow are evident in all the ice core data from Greenland, the Canadian Arctic, and Svalbard. Temporal patterns, however, show spatial variation. In the area around Dye 3, south Greenland, significant increases in sulfate are found beginning in the 1890s. Increases in nitrate began ∼50 years later. A similar pattern is seen at Penny Ice Cap, Baffin Island, in the Canadian low Arctic. In contrast, both sulfate and nitrate concentrations started to increase significantly in the 1940s on Agassiz Ice Cap, Ellesmere Island, in the Canadian high Arctic; and Snøfjellafonna, Svalbard. At Summit, central Greenland, and sites in north Greenland, sharp sulfate increases occurred at about the turn of the 20th century and again about 1940 or 1950, where the latter increase is the greater of the two. At these central and north Greenland sites, significant increases in nitrate began about 1940 or 1950. The difference between the magnitude and timing of increasing trends of the sulfate ions at these sites can be attributed to their having different source regions and pathways for these pollutant ions. The pollutant sources appear to be North America for south Greenland and Baffin Island, Eurasia, for Ellesmere Island and Svalbard, and both North America and Eurasia for central and north Greenland.
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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) | 0.000 | 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) | 0.001 | 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 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".