An automated GC-C-GC-IRMS setup to measure palaeoatmospheric δ <sup>13</sup> C-CH <sub>4</sub> , δ <sup>15</sup> N-N <sub>2</sub> O and δ <sup>18</sup> O-N <sub>2</sub> O in one ice core sample
Bibliographic record
Abstract
Abstract. Air bubbles in ice core samples represent the only opportunity to study the mixing ratio and isotopic variability of palaeoatmospheric CH4 and N2O. The highest possible precision in isotope measurements is required to maximize the resolving power for CH4 and N2O sink and source reconstructions. We present a new setup to measure δ13C-CH4, δ15N-N2O and δ18O-N2O isotope ratios in one ice core sample and with one single IRMS instrument, with a precision of 0.09, 0.6 and 0.7‰, respectively, as determined on 0.6–1.6 nmol CH4 and 0.25–0.6 nmol N2O. The isotope ratios are referenced to the VPDB scale (δ13C-CH4), the N2-air scale (δ15N-N2O) and the VSMOW scale (δ18O-N2O). Ice core samples of 200–500 g are melted while the air is constantly extracted to minimize gas dissolution. A helium carrier gas flow transports the sample through the analytical system. We introduce a new gold catalyst to oxidize CO to CO2 in the air sample. CH4 and N2O are then separated from N2, O2, Ar and CO2 before they get pre-concentrated and separated by gas chromatography. A combustion unit is required for δ13C-CH4 analysis, which is equipped with a constant oxygen supply as well as a post-combustion trap and a post-combustion GC column (GC-C-GC-IRMS). The post-combustion trap and the second GC column in the GC-C-GC-IRMS combination prevent Kr and N2O interferences during the isotopic analysis of CH4-derived CO2. These steps increase the time for δ13C-CH4 measurements, which is used to measure δ15N-N2O and δ18O-N2O first and then δ13C-CH4. The analytical time is adjusted to ensure stable conditions in the ion source before each sample gas enters the IRMS, thereby improving the precision achieved for measurements of CH4 and N2O on the same IRMS. The precision of our measurements is comparable to or better than that of recently published systems. Our setup is calibrated by analysing multiple reference gases that were injected over bubble-free ice samples. We show that our measurements of δ13C-CH4 in ice core samples are generally in good agreement with previously published data after the latter have been corrected for krypton interferences.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".