First measurements of nitrous oxide in Arctic sea ice
Bibliographic record
Abstract
Nitrous oxide (N 2 O) contributes ∼6% of the total radiative forcing from long‐lived greenhouse gases. While tropospheric concentrations have increased by 20% since the beginning of the industrial revolution, sources and sinks of N 2 O are still poorly quantified. In the Arctic, N 2 O atmospheric concentrations vary seasonally, due mainly to vertical mixing. The contributions of local natural sources to this cycle are still unknown. Here we report on N 2 O measurements conducted in the bottom 10 cm of the sea ice and in the underlying surface water (USW) from late March to early May 2008 in the southeastern Beaufort Sea and Amundsen Gulf. Bulk N 2 O concentrations in ice were low (∼6 nM) and were consistently undersaturated with respect to the USW (∼40% saturation) and the atmosphere (∼30% saturation). Loss of N 2 O via brine rejection during sea ice formation in fall and winter can explain these low N 2 O ice concentrations. An unknown fraction of this rejected N 2 O is likely ventilated to the atmosphere either directly from the ice or through leads during ice formation, while in spring and early summer, melting of the N 2 O‐depleted sea ice is expected to lower the partial pressure of N 2 O of newly open waters which could act as a sink for atmospheric N 2 O. These first measurements indicate that sea ice formation and melt has the potential to generate sea‐air or air‐sea fluxes of N 2 O, respectively.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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 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".