Air quality in Canadian port cities after regulation of low-sulphur marine fuel in the North American Emissions Control Area
Bibliographic record
Abstract
Large marine vessels have historically used high-sulphur (S) residual fuel oil (RFO), with substantial airborne releases of sulphur dioxide (SO₂) and fine particulate matter (PM2.5) enriched in vanadium (V), nickel (Ni) and other air pollutants. To address marine shipping air pollution, Canada and the United States have jointly implemented a North American Emissions Control Area (NA ECA) within which ships are regulated to use lower-sulphur marine fuel or equivalent SO2 scrubbers (i.e., 3.5% maximum fuel S reduced to 1% S in 2012 and 0.1% S in 2015). To investigate the effects of these regulations on local air quality, we examined changes in air pollutant (SO₂, PM2.5, NO₂, O₃), and related PM2.5 components (V, Ni, sulphate) concentrations over 2010–2016 at the Canadian port cities of Halifax, Vancouver, Victoria, Montreal, and Quebec City. SO2 concentrations showed large statistically significant decreases at all sites (−28% to −83% mean hourly change), with the largest improvements in the coastal cities when the 0.1% fuel S regulation took effect. Statistically significant PM2.5 but smaller fractional reductions were also observed (−7% to −37% mean hourly change), reflecting the importance of non-marine PM sources. RFO marker species V and Ni in PM2.5 dramatically declined following regulation implementation, consistent with decreased RFO use likely indicating the switch to low-S distillate fuel oil rather than exhaust scrubbers for initial compliance. Significant changes in other pollutants with non-marine sources (NO2, O3) were not contemporaneous with the regulatory timeline. The large SO2 improvements in the port cities have reduced 1-h concentrations to <30 ppb, comparable to Canadian urban locations with few local SO2 sources and likely reducing health risks to susceptible populations such as asthmatics and the elderly. Our findings indicate that the implementation of the NA ECA improved air quality at Canadian port cities immediately following the requirement for lower-S fuel. These air quality improvements suggest that large-scale international benefits can result from implementation of the 2020 global low-S marine fuel regulations.
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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 | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".