Air quality monitoring in communities of the Canadian Arctic during the high shipping season with a focus on local and marine pollution
Bibliographic record
Abstract
Abstract. The Canadian Arctic has experienced decreasing sea ice extent and increasing shipping activity in recent decades. While there are economic incentives to develop resources in the north, there are environmental concerns that increasing marine traffic will contribute to declining air quality in northern communities. In an effort to characterize the relative impact of shipping on air quality in the north, two monitoring stations have been installed in Cape Dorset and Resolute, Nunavut, and have been operational since 1 June 2013. The impact of shipping and other sources of emissions on NOx, O3, SO2, BC, and PM2.5 pollution have been characterized for the 2013 shipping season from 1 June to 1 November. In addition, a high-resolution Air Quality Health Index (AQHI) for both sites was computed. Shipping consistently increased O3 mixing ratio and PM2.5 concentration. The 90% confidence interval for mean difference in O3 mixing ratio between ship- and no ship-influenced air masses were up to 4.6–4.7 ppb and 2.5–2.7 ppb for Cape Dorset and Resolute, respectively. The same intervals for PM2.5 concentrations were up to 1.8–1.9 μg m−3 and 0.5–0.6 μg m−3. Ship-influenced air masses consistently exhibited an increase of 0.1 to 0.3 in the high-resolution AQHI compared to no ship-influenced air masses. Trajectory cluster analysis in combination with ship traffic tracking provided an estimated range for percent ship contribution to NOx, O3, SO2, and PM2.5 that were 12.9–17.5 %, 16.2–18.1 %, 16.9–18.3 %, and 19.5–31.7 % for Cape Dorset and 1.0–7.2 %, 2.9–4.8 %, 5.5–10.0 %, and 6.5–7.2 % for Resolute during the 2013 shipping season. Additional measurements in Resolute suggested that percent ship contribution to black carbon was 4.3–9.8 % and that black carbon constituted 1.3–9.7 % of total PM2.5 mass in ship plumes. Continued air quality monitoring in the above sites for future shipping seasons will improve the statistics in our analysis and characterize repeating seasonal patterns in air quality due to shipping, local pollution, and long-range transport.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".