Amount, Sources, and Dissolution of Aerosol Trace Elements in the Canadian Arctic
Bibliographic record
Abstract
Atmospheric deposition is an important source of trace elements (TEs) to the Arctic, including both anthropogenic (e.g., Pb) and micronutrient (e.g., Fe) metals. This study measured TE loadings, Pb isotopes, and dissolution in aerosols collected at Alert, Nunavut, Canada, from spring to summer of 2013 and 2014 and during the Canadian Arctic GEOTRACES Cruises (GN02 and GN03) in the summer of 2015. The aerosol loadings were 5–8 times higher and more enriched with anthropogenic metals (Pb and Cd) in the spring than in the summer consistent with the Arctic haze phenomenon. Pb isotopes reveal that Russia, Europe, and China were the likely source regions of this pollution in spring. Comparison of the Pb and Cd concentrations and Pb isotope data with previous studies suggests that atmospheric pollution in the Canadian Arctic has been relatively stable for the last couple of decades. Dissolution experiments were also performed to estimate the fraction of aerosol TEs that can potentially be dissolved and become bioavailable in seawater. The minimum and maximum dissolution estimates for Fe were 8 ± 5 and 65 ± 20%, respectively, which translate to a potential input of 5–40 kT year –1 of dissolvable Fe to the Canada Basin of the Arctic Ocean, comparable to the riverine Fe input (10–20 kT year –1 ) from Mackenzie River. Thus, aerosols could be an important Fe source to Arctic surface waters, especially with decreasing sea ice coverage, changes in stratification and in places far from shelf and river sources.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".