Tagged tracer simulations of black carbon in the Arctic: Transport, source contributions, and budget
Bibliographic record
Abstract
Abstract. We implemented a tagged tracer method of black carbon (BC) into a global chemistry-transport model GEOS-Chem, examined the pathways and efficiency of long-range transport from a variety of anthropogenic and biomass burning emission sources to the Arctic, and quantified the source contributions of individual emissions. Firstly, we evaluated the simulated BC by comparing it with observations at the Arctic sites and found that the simulated seasonal variations were improved by implementing an aging parameterization and reducing the wet scavenging rate by ice clouds. For tagging BC, we added BC tracers distinguished by source types (anthropogenic and biomass burning) and regions; the global domain was divided into 16 and 27 regions for anthropogenic and biomass burning emissions, respectively. Our simulations showed that BC emitted from Europe and Russia was transported to the Arctic mainly in the lower troposphere during winter and spring. In particular, BC transported from Russia was widely spread over the Arctic in winter and spring, leading to a dominant contribution of 62 % to the Arctic BC near the surface as the annual mean. In contrast, BC emitted from East Asia was found to be transported in the middle troposphere into the Arctic mainly over the Okhotsk Sea and East Siberia during winter and spring. We identified an important window area, which allowed a strong incoming of East Asian BC to the Arctic (130°–180° E and 3–8 km altitude at 66° N). The model demonstrated that the contribution from East Asia to the Arctic had a maximum at about 5 km altitude due to uplifting during the long-range transport in early spring. The efficiency of BC transport from East Asia to the Arctic was smaller than that from other large source regions such as Europe, Russia and North America. However, the East Asian contribution was most important for BC in the middle troposphere (41 %) and BC burden over the Arctic (27 %) because of the large emissions from this region. These results suggested that the main sources of the Arctic BC differed with altitude. The contribution of all the anthropogenic sources to Arctic BC concentrations near the surface was dominant (90 %) on an annual basis. The contributions of biomass burning in boreal regions (Siberia, Alaska and Canada) to the annual total BC deposition onto the Arctic were estimated to be 12–15 %, which became the maximum during summer.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".