Transport of Anthropogenic Pollution and Boreal Forest Fire Emissions to the Arctic during Summer 2008
Bibliographic record
Abstract
Aircraft measurements taken as part of POLARCAT campaign (the Polar Study using Aircraft, Remote Sensing, Surface Measurements and Models, of Climate, Chemistry, Aerosols, and Transport) in the Arctic were aimed at investigating pollution transport and atmospheric chemistry. Anthropogenic pollution and boreal forest fire emissions followed by subsequent transport to the Arctic were measured in summer 2008. We combine aircraft measurements with simulations using the WRF-Chem model (Weather Research and Forecasting Model including aerosol and chemistry) to investigate cases of pollution transport to the Arctic during summer 2008. Two case studies are investigated in this work. The dynamics for transport of fire plumes originating over Canada that as well as anthropogenic pollution plumes primarily from the north east US will be presented to gain insight into the origin and fate of pollution transported to the Arctic. We also investigate the transport and evolution of anthropogenic pollution from East Asia. Model results are compared with high-resolution aircraft data obtained during POLARCAT in order to investigate the critical processes responsible for horizontal and vertical transport. We also investigate the impact of boreal fire and anthropogenic emissions on the subsequent production of ozone in plumes during transport to the Arctic. The WRF-Chem model simulates the emission, transport, mixing, and chemical transformation of trace gases and aerosols simultaneously with the meteorology. The treatment of forest fire emissions is taken into account using the online plume-rise model that predicts fire plume injection height. By comparing model results with POLARCAT aircraft data from summer 2008, we provide a means for interpreting the POLARCAT aircraft data set with the goal of improving our understanding of pollution transport to the Arctic. The contribution of the processes leading to Arctic pollution will be discussed including stratosphere to troposphere exchange, import of pollutants from remote sources through longrange transport, and local photochemistry.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".