The isotopic record of Northern Hemisphere atmospheric carbon monoxide since 1950, implications for the CO budget
Bibliographic record
Abstract
Abstract. We present a 60-yr record of atmospheric CO concentration and stable isotopic ratios at high northern latitude based on firn air samples collected in the frame of the North Greenland Eemian Ice Drilling (NEEM) project. Concentration, δ13C, and δ18O of CO from trapped gases in the firn were measured by gas chromatography coupled with isotope ratio mass spectrometry (gc-IRMS). Using models of trace gas transport in firn, the long-term trend of atmospheric CO and its stable isotopic composition at high northern latitudes since the 1950s were reconstructed. Our best firn air scenarios suggest that δ13C decreased slightly from −25.8‰ in 1950 to −26.4‰ in 2000, then dropped to −27.2‰ in 2008. δ18O decreased more regularly from 9.8‰ in 1950 to 7.1‰ in 2008. The best firn air scenarios also suggest that CO concentration increased gradually from 1950 and peaked likely in the late-1970s, followed by a gradual decrease by present day (Petrenko et al., 2011). An isotope mass balance model is applied to quantify the temporal evolution of CO source partitioning able to explain the combined mixing ratio and isotopic ratio changes. It suggests that a slight increase followed by a large reduction in CO derived from fossil fuel combustion occurred since 1950. The increase of CO concentration from 1950 to the mid-1970s is the result of a combined increase of multiple sources. The reduction of CO emission from fossil fuel combustion after the mid-1970s is the most plausible mechanism for the drop of CO concentration during this time. The mitigation policy for CO emission from vehicle exhaust such as application of catalytic converters and the growth of diesel engine vehicles market share are the main expected reasons for the CO source strength change from fossil fuel combustion.
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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) | 0.001 | 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".