An isotopic view on the connection between photolytic emissions of NO<sub><i>x</i></sub> from the Arctic snowpack and its oxidation by reactive halogens
Bibliographic record
Abstract
We report on dual isotopic analyses (δ15N and Δ17O) of atmospheric nitrate at daily time‐resolution during the OASIS intensive field campaign at Barrow, Alaska, in March–April 2009. Such measurements allow for the examination of the coupling between snowpack emissions of nitrogen oxides (NOx = NO + NO2) and their involvement in reactive halogen‐mediated chemical reactions in the Arctic atmosphere. The measurements reveal that during the spring, lowδ15N values in atmospheric nitrate, indicative of snowpack emissions of NOx, are almost systematically associated with local oxidation of NOx by reactive halogens such as BrO, as indicated by 17O‐excess measurements (Δ17O). The high time‐resolution data from the intensive field campaign were complemented by weekly aerosol sampling between April 2009 and February 2010. The dual isotopic composition of nitrate (δ15N and Δ17O) obtained throughout this nearly full seasonal cycle is presented and compared to other seasonal‐scale measurements carried out in the Arctic and in non‐polar locations. In particular, the data allow for the investigation of the seasonal variations of reactive halogen chemistry and photochemical snowpack NOx emissions in the Arctic. In addition to the well characterized peak of snowpack NOx emissions during springtime in the Arctic (April to May), the data reveal that photochemical NOx emissions from the snowpack may also occur in other seasons as long as snow is present and there is sufficient UV radiation reaching the Earth's surface.
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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 | 0.000 | 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) | 0.001 | 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".