Characterizing aerosol transport into the Canadian High Arctic using aerosol mass spectrometry and Lagrangian modelling
Bibliographic record
Abstract
Abstract. We report the analysis of measurements made using an aerosol mass spectrometer (AMS; Aerodyne Research Inc.) that was installed in the Polar Environment Atmospheric Research Laboratory (PEARL) in summer 2006. PEARL is located in the Canadian high Arctic at 610 m above sea level on Ellesmere Island (80° N 86° W). PEARL is unique for its remote location in the Arctic and because most of the time it is situated within the free troposphere. It is therefore well suited as a receptor site to study the long range tropospheric transport of pollutants into the Arctic. Some information about the successful year-round operation of an AMS at a high Arctic site such as PEARL will be reported here, together with design considerations for reliable sampling under harsh low-temperature conditions. Computational fluid dynamics calculations were made to ensure that sample integrity was maintained while sampling air at temperatures that average −40 °C in the winter and can be as low as −55 °C. Selected AMS measurements of aerosol mass concentration, size, and chemical composition recorded during the months of August, September and October 2006 will be reported. During this period, sulfate was at most times the predominant aerosol component with on average 0.115 μg m−3 (detection limit 0.003 μg m−3). The second most abundant component was undifferentiated organic aerosol, with on average 0.11 μg m−3 detection limit (0.04 μg m−3). The nitrate component, which averaged 0.007 μg m−3, was above its detection limit (0.002 μg m−3), whereas the ammonium ion had an apparent average concentration of 0.02 μg m−3, which was approximately equal to its detection limit. A few episodes having increased mass concentrations and lasting from several hours to several days are apparent in the data. These were investigated further using a statistical analysis to determine their common characteristics. High correlations among some of the components arriving during the short term episodes provide evidence for common sources. Lagrangian methods were also used to identify the source regions for some of the episodes. These showed that the source regions for the two selected episodes were located in north-eastern North America and western Siberia. We believe the former is associated with sulfate emissions from motor vehicles, power plants and heavy industry. The latter coincides with the locations of the largest Russian oil and gas fields. These conclusions show that the Arctic is the destination for significant amounts of pollution from high- and mid-latitude industrial and resource activity.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".