A case study into the measurement of ship emissions from plume intercepts of the NOAA ship <i>Miller Freeman</i>
Why this work is in the frame
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Bibliographic record
Abstract
Abstract. Emissions factors (EFs) for gas and sub-micron particle-phase species were measured in intercepted plumes as a function of vessel speed from an underway research vessel, the NOAA ship Miller Freeman, operating a medium-speed diesel engine on low-sulfur marine gas oil (fuel sulfur content ~0.1% by weight). The low-sulfur fuel in use conforms to the MARPOL fuel sulfur limit within emission control areas set to take effect in 2015 and to California-specific limits set to take effect in 2014. For many of the particle-phase species, EFs were determined using multiple measurement methodologies, allowing for an assessment of how well EFs from different techniques agree. The total sub-micron PM (PM1) was dominated by particulate black carbon (BC) and particulate organic matter (POM), with an average POM / BC ratio of 1.3. Consideration of the POM / BC ratios observed here with literature studies suggests that laboratory and in-stack measurement methods may overestimate primary POM EFs relative to those observed in emitted plumes. Comparison of four different methods for black carbon measurement indicates that careful attention must be paid to instrument limitations and biases when assessing EFBC. Particulate sulfate (SO42−) EFs were extremely small and the particles emitted by Miller Freeman were inefficient as cloud condensation nuclei (CCN), even at high super saturations, consistent with the use of very low-sulfur fuel and the overall small emitted particle sizes. All measurement methodologies consistently demonstrate that the measured EFs (fuel mass basis) for PM1 mass, BC and POM decreased as the ship slowed. Particle number EFs were approximately constant across the speed change, with a shift towards smaller particles being emitted at slower speeds. Emissions factors for gas-phase CO and formaldehyde (HCHO) both increased as the vessel slowed, while EFs for NOx decreased and SO2 EFs were approximately constant.
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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) | 0.002 | 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 it