Surface snow bromide and nitrate at Eureka, Canada in early spring and implications for polar boundary layer chemistry
Bibliographic record
Abstract
<!--!introduction!--> Surface snow samples were collected daily, at several sites representing distinct environments: sea ice, inland close to sea level, and a hilltop ~600 m above sea level (asl), from a Canadian high Arctic location at Eureka, Nunavut (80°N, 86°W) from the end of February to the end of March in 2018 and 2019. Snow samples were under ionic and salinity analysis. The aim of this study is to explore the role of snowpack in polar spring boundary layer chemistry, especially as a direct source of reactive bromine (BrOX=BrO+Br) and nitrogen (NOX=NO+NO2). We find that surface snow bromide at sea level is significantly enriched, indicating a net sink of atmospheric bromine. Both surface snow bromide and nitrate at sea level have an increasing trend over the measurement time period. Using these trends, we derive an integrated net deposition flux of bromide of 1.01×107 molecules cm-2 s-1 and of nitrate of 2.6×108 molecules cm-2 s-1. In addition, nitrate and bromide in the morning samples are significantly higher than the afternoon samples, indicating a strong photochemistry effect, however the bromide loss rate is smaller than the nitrate loss rate by more than an order of magnitude. Also, surface snow nitrate and bromide at inland sites are significantly correlated (R=0.48-0.76), with a [NO3-]/[Br-] ratio of 4-7 indicating a possible acceleration effect of reactive bromine in atmospheric NOX-to-nitrate conversion. This is the first time we see such an effect from snow chemistry data obtained with a sampling frequency as short as one day.
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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".