Chemical\nCharacterization of Exhaust Emissions from\nSelected Canadian Marine Vessels: The Case of Trace Metals and Lanthanoids
Bibliographic record
Abstract
This paper reports the chemical composition\nof exhaust emissions\nfrom the main engines of five ocean going cargo vessels, as they traveled\nin Canadian waters. The emission factors (EFs) of PM<sub>2.5</sub> and SO<sub>2</sub> for vessels tested on various intermediate fuel\noils (IFO), ranged from 0.4 to 2.2 g kW<sup>–1</sup> hr<sup>–1</sup> and 4.7 to 10.3 g kW<sup>–1</sup> hr<sup>–1</sup>, respectively, and were mainly dependent on the content of sulfur\nin the fuel. Average NO<sub><i>x</i></sub>, CO, and CO<sub>2</sub> EFs for these tests were 12.7, 0.45, and 618 g kW<sup>–1</sup> hr<sup>–1</sup>, respectively and were generally below benchmark\nvalues commonly used by regulatory agencies. The composition of PM<sub>2.5</sub> was dominated by hydrated sulfates, organic carbon and\ntrace metals which accounted for 80–97% of total PM<sub>2.5</sub> mass. A substantial decrease of measured emission factors for PM<sub>2.5</sub> and SO<sub>2</sub> was observed when the fuel was changed\nfrom IFO to marine diesel oil (MDO), in one of the tested vessels.\nThe main component of PM<sub>2.5</sub> in this case was organic carbon\naccounting for 65% of PM<sub>2.5</sub> mass. In addition to commonly\nreported pollutants, this study presents EFs of the lanthanoid elements\nand showed that their distribution patterns in ship-exhaust PM<sub>2.5</sub> were very similar to the PM<sub>2.5</sub> emitted by oil\nrefining facilities. Hence, using La:Ce:V tertiary diagrams and La/V\nratios is necessary to distinguish ship plumes from primary emissions\nrelated to accidental and/or routine operation of oil-refining industry.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.415 | 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 teacher head, 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".