High resolution measurements of carbon monoxide along a late Holocene Greenland ice core: evidence for in-situ production
Bibliographic record
Abstract
Abstract. We present high-resolution measurements of carbon monoxide (CO) concentrations from continuous analysis of a shallow ice core from the North Greenland Eemian Ice Drilling project (NEEM-2011-S1). An Optical Feedback – Cavity Enhanced Absorption Spectrometer (OF-CEAS) was coupled to a continuous melter system during a 4-week laboratory-based measurement campaign. This analytical setup generates highly stable measurements of CO concentrations with an external precision of 7.8 ppbv (1 sigma) based on a comparison of replicate cores. The NEEM-2011-S1 CO record spans 1800 yr and exhibits highly variable concentrations at the scale of annual layers, ranging from 75 to 1327 ppbv. The most recent section of this record (i.e. since 1700 AD) agrees with existing discrete CO measurements from the Eurocore ice core and the deep NEEM firn. However, it is difficult to interpret in terms of atmospheric CO variation due to high frequency, high amplitude spikes in the data. 68% of the elevated CO spikes are observed in ice layers enriched with pyrogenic aerosols. Such aerosols, originating from boreal biomass burning emissions, contain organic compounds, which can be oxidized or photodissociated to produce CO in-situ. We suggest that elevated CO concentration features could present a new integrative proxy for past biomass burning history. Furthermore, the NEEM-2011-S1 record reveals an increase in baseline CO level prior to 1700 AD (129 m depth), with the concentration remaining high even for ice layers depleted in dissolved organic carbon (DOC). Overall, the processes driving in-situ production of CO within the NEEM ice are complex and may involve multiple chemical pathways.
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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 | 0.000 | 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) | 0.000 | 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".