Carbonate content and stable isotopic composition of aerosol carbon in the Canadian High Arctic
Bibliographic record
Abstract
Abstract. The carbon cycle in the Arctic atmosphere is important in understanding abrupt climate changes occurring in this region. Two-years of measurements (summer 2016–spring 2018) of carbonaceous aerosols at the High Arctic station Alert, Canada, showed that in addition to organic carbon (OC) and elemental carbon (EC), carbonate carbon (CC) was episodically but not negligibly present. The relative abundances of CC in total carbon (TC) ranged from 0–65 % with an average of approximately 11 % over the entire period. Also there was a strong correlation of CC with aerosol Ca2+ which is associated mostly with soil dust and to a lesser extent sea salt aerosol. Based on this and the analysis of air mass back trajectories (AMBT), we infer two possible sources of CC in the Arctic total suspended particles (TSP). The major one is the erosion and resuspension of limestone sediments, particularly in the semi-desert areas of the northern Canadian Arctic. Another potential more minor source of CC is from marine aerosol sources including calcified marine phytoplankton shells (coccoliths) introduced into the atmosphere via sea-to air emission. The CC content significantly influenced the stable carbon isotopic composition (δ13C) of TC. The higher the CC content, the higher the δ13C values, which is consistent with the strong 13C enrichment in carbonates. Therefore, carbonates in Arctic TSP must be taken into account not only in isotopic studies using δ13C analyses but also when assessing the impact of carbonaceous aerosols on the Arctic climate.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".