Light absorbing carbon emissions from commercial shipping
Bibliographic record
Abstract
Extensive measurements of the emission of light absorbing carbon aerosol (LAC) from commercial shipping are presented. Vessel emissions were sampled using a photoacoustic spectrometer in the Gulf of Mexico region. The highest emitters (per unit fuel burnt) are tug boats, thus making significant contributions to local air quality in ports. Emission of LAC from cargo and non cargo vessels in this study appears to be independent of engine load. Shipping fuel consumption data (2001) was used to calculate a global LAC contribution of 133(±27) Ggyr −1 , or ∼1.7% of global LAC. This small fraction could have disproportionate effects on both air quality near port areas and climate in the Arctic if direct emissions of LAC occur in that region due to opening Arctic sea routes. The global contribution of this LAC burden was investigated using the MOZART model. Increases of 20–50 ng m −3 LAC (relative increases up to 40%) due to shipping occur in the tropical Atlantic, Indonesia, central America and the southern regions of South America and Africa.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".