Impact of Biomass Burning and Anthropogenic Emissions on the Chemical Composition of the summertime Arctic Troposphere - Aircraft Observations during POLARCAT-GRACE
Bibliographic record
Abstract
We report on chemical aircraft measurements in pollution plumes transported into the European sector of the Arctic from forest fires and urban sources in North America and Siberia. Our observations were part of the POLARCAT subproject GRACE (Greenland Aerosol and Chemistry Experiment (GRACE) performed in July 2008 using the DLR Falcon research aircraft. Data were sampled during 16 flights covering altitudes up to 12 km in order to study the pathways, dispersion and chemical processing of pollution during long-range transport into the Arctic. \nWe found that the entire free troposphere above 4 km was strongly polluted and detected more than 30 distinct pollution plumes with enhanced CO and NOy mixing ratios of up to 300 and 1.5 nmol/mol (ppbv), respectively. According to FLEXPART analysis, the plumes were sampled after transport times of 5-10 days from Canadian fires and 10-15 days from Siberian fires. Interestingly, an anthropogenic pollution plume originating from East Asia was sampled in the lowermost stratosphere at an altitude of 11.3 km after being transported over the North pole. \nWe will discuss differences in the chemical composition of the probed pollution plumes (e.g. in the ozone mixing ratios) dependent on the source region and transport history. Simulations with a photochemical model, CiTTyCAT, were used to study the chemical evolution in the pollution plumes during transport from the measurement area to Europe.
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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 | 0.000 |
| 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) | 0.000 | 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".