Source apportionment of circum-Arctic atmospheric black carbon from isotopes and modeling
Bibliographic record
Abstract
Black carbon (BC) contributes to Arctic climate warming, yet source attributions are inaccurate due to lacking observational constraints and uncertainties in emission inventories. Year-round, isotope-constrained observations reveal strong seasonal variations in BC sources with a consistent and synchronous pattern at all Arctic sites. These sources were dominated by emissions from fossil fuel combustion in the winter and by biomass burning in the summer. The annual mean source of BC to the circum-Arctic was 39 ± 10% from biomass burning. Comparison of transport-model predictions with the observations showed good agreement for BC concentrations, with larger discrepancies for (fossil/biomass burning) sources. The accuracy of simulated BC concentration, but not of origin, points to misallocations of emissions in the emission inventories. The consistency in seasonal source contributions of BC throughout the Arctic provides strong justification for targeted emission reductions to limit the impact of BC on climate warming in the Arctic and beyond.
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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 | 0.000 | 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 teacher head, 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".