Do contemporary (1980–2015) emissions determine the elemental carbon deposition trend at Holtedahlfonna glacier, Svalbard?
Bibliographic record
Abstract
Abstract. The climate impact of black carbon (BC) is notably amplified in the Arctic by its deposition, which causes albedo decrease and subsequent earlier snow and ice spring melt. To comprehensively assess the climate impact of BC in the Arctic, information on both atmospheric BC concentrations and deposition is essential. Currently, Arctic BC deposition data are very scarce, while atmospheric BC concentrations have been shown to generally decrease since the 1990s. However, a 300-year Svalbard ice core showed a distinct increase in EC (elemental carbon, proxy for BC) deposition from 1970 to 2004 contradicting atmospheric measurements and modelling studies. Here, our objective was to decipher whether this increase has continued in the 21st century and to investigate the drivers of the observed EC deposition trends. For this, a shallow firn core was collected from the same Svalbard glacier, and a regional-to-meso-scale chemical transport model (SILAM) was run from 1980 to 2015. The ice and firn core data indicate peaking EC deposition values at the end of the 1990s and lower values thereafter. The modelled BC deposition results generally support the observed glacier EC variations. However, the ice and firn core results clearly deviate from both measured and modelled atmospheric BC concentration trends, and the modelled BC deposition trend shows variations seemingly independent from BC emission or atmospheric BC concentration trends. Furthermore, according to the model ca. 99 % BC mass is wet-deposited at this Svalbard glacier, indicating that meteorological processes such as precipitation and scavenging efficiency have most likely a stronger influence on the BC deposition trend than BC emission or atmospheric concentration trends. BC emission source sectors contribute differently to the modelled atmospheric BC concentrations and BC deposition, which further supports our conclusion that different processes affect atmospheric BC concentration and deposition trends. Consequently, Arctic BC deposition trends should not directly be inferred based on atmospheric BC measurements, and more observational BC deposition data are required to assess the climate impact of BC in Arctic snow.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".