Historical variations of mercury stable isotope ratios in Arctic glacier firn and ice cores
Bibliographic record
Abstract
Abstract The concentration and isotopic composition of mercury (Hg) were determined in glacier core samples from Canadian Arctic ice caps dating from preindustrial to recent time (early 21st century). Mean Hg levels increased from ≤ 0.2 ng L−1in preindustrial time to ~0.8–1.2 ng L−1in the modern industrial era (last ~200 years). Hg accumulated on Arctic ice caps has Δ199Hg and Δ201Hg that are higher (~ −1 to 2.9‰) than previously reported for Arctic snow impacted by atmospheric Hg depletion events (mostly < −1‰), suggesting that these events contribute little to Hg accumulation on ice caps. The range of δ202Hg, Δ199Hg, and Δ201Hg in glacier cores overlaps with that of Arctic Hg0(g)and of seawater in Baffin Bay and also with that of midlatitude precipitation and industrial Hg sources, including coal and Hg ores. A core from Agassiz ice cap (80.7°N) shows a ~ +1‰ shift in δ202Hg over the nineteenth to twentieth centuries that could reflect changes in the isotopic composition of the atmospheric Hg pool in the High Arctic in response to growing industrial emissions at lower latitudes. This study is the first ever to report on historical variations of Hg stable isotope ratios in Arctic ice cores. Results could help constrain future modeling efforts of the global Hg biogeochemical cycle and the atmosphere's response to changing Hg emissions, past and future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".