Analysis of ozone and nitric acid in spring and summer Arctic pollution using aircraft, ground-based, satellite observations and MOZART-4 model: source attribution and partitioning
Bibliographic record
Abstract
Abstract. In this paper, we analyze tropospheric O3 together with HNO3 during the POLARCAT (Polar Study using Aircraft, Remote Sensing, Surface Measurements and Models, of Climate, Chemistry, Aerosols, and Transport) program, combining observations and model results. Aircraft observations from the NASA ARCTAS (Arctic Research of the Composition of the Troposphere from Aircraft and Satellites) and NOAA ARCPAC (Aerosol, Radiation and Cloud Processes affecting Arctic Climate) campaigns during spring and summer of 2008 are used together with the Model for Ozone and Related Chemical Tracers, version 4 (MOZART-4) to assist in the interpretation of the observations in terms of the source attribution and transport of O3 and HNO3 into the Arctic (north of 60° N). The MOZART-4 simulations reproduce the aircraft observations generally well (within 15%), but some discrepancies in the model are identified and discussed. The observed correlation of O3 with HNO3 is exploited to evaluate the MOZART-4 model performance for different air mass types (fresh plumes, free troposphere and stratospheric-contaminated air masses). Based on model simulations of O3 and HNO3 tagged by source type and region, we find that the anthropogenic pollution from the Northern Hemisphere is the dominant source of O3 and HNO3 in the Arctic at pressures greater than 400 hPa, and that the stratospheric influence is the principal contribution at pressures less 400 hPa. During the summer, intense Russian fire emissions contribute some amount to the tropospheric columns of both gases over the American sector of the Arctic. North American fire emissions (California and Canada) also show an important impact on tropospheric ozone in the Arctic boundary layer. Additional analysis of tropospheric O3 measurements from ground-based FTIR and from the IASI satellite sounder made at the Eureka (Canada) and Thule (Greenland) polar sites during POLARCAT has been performed using the tagged contributions. It demonstrates the capability of these instruments for observing pollution at northern high latitudes. Differences between contributions from the sources to the tropospheric columns as measured by FTIR and IASI are discussed in terms of vertical sensitivity associated with these instruments. The first analysis of O3 tropospheric columns observed by the IASI satellite instrument over the Arctic is also provided. Despite its limited vertical sensitivity in the lowermost atmospheric layers, we demonstrate that IASI is capable of detecting low-altitude pollution transported into the Arctic with some limitations.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".