PM and PAHs emissions of ship auxiliary engine fuelled with waste cooking oil biodiesel and marine gas oil
Bibliographic record
Abstract
Clean fuels are recommended for ships at berth to reduce air pollutant emissions. This study aimed to evaluate the feasibility of waste cooking oil (WCO) biodiesel application on board with regard to particle matter (PM) and polycyclic aromatic hydrocarbon (PAH) emissions. An experiment was conducted on a marine auxiliary engine for three different fuels: WCO biodiesel, formulation blends with marine gas oil (MGO) and neat MGO. Results revealed that WCO biodiesel could reduce PM and PAHs emissions. WCO exhaust also exhibited differences in PAH profile and phase distribution as compared to MGO, depending on the operation modes and the proportion of biodiesel in the formulation blends. Consequently, WCO biodiesel could dramatically reduce the total carcinogenic potencies related to PAHs of exhausts. Moreover, PAH source recognition pair ratios of tested fuels were observed to deviate from the widely accepted values. This study highlights that WCO biodiesel is a cleaner fuel for operating ship auxiliary engines with respect to PM and PAHs emissions and has the potential to moderate the severe effects of PM and PAHs on an air of coastal areas.
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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) | 0.000 | 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) | 0.001 | 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".