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Record W2141306952 · doi:10.5194/acp-14-1881-2014

Black carbon emissions from in-use ships: a California regional assessment

2014· article· en· W2141306952 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAtmospheric chemistry and physics · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicMaritime Transport Emissions and Efficiency
Canadian institutionsYork UniversityEnvironment and Climate Change Canada
FundersNatural Sciences and Engineering Research Council of CanadaAustralian GovernmentCalifornia Air Resources BoardNational Oceanic and Atmospheric AdministrationU.S. Environmental Protection Agency
KeywordsSootEnvironmental scienceCarbon blackAerosolDiesel fuelAtmospheric sciencesMass concentration (chemistry)PlumePhotometerCarbon dioxideCarbon fibersAbsorption (acoustics)MeteorologyAnalytical Chemistry (journal)ChemistryEnvironmental chemistryCombustionMaterials scienceOpticsGeologyGeographyPhysics

Abstract

fetched live from OpenAlex

Abstract. Black carbon (BC) mass emission factors (EFBC; g BC (kg fuel)−1) from a variety of ocean-going vessels have been determined from measurements of BC and carbon dioxide (CO2) concentrations in ship plumes intercepted by the R/V Atlantis during the 2010 California Nexus (CalNex) campaign. The ships encountered were all operating within 24 nautical miles of the California coast and were utilizing relatively low sulphur fuels (average fuel sulphur content of 0.4%, 0.09% and 0.03% for vessels operating slow-speed, medium-speed and high-speed diesel engines, respectively). Black carbon concentrations within the plumes, from which EFBC values are determined, were measured using four independent instruments: a photoacoustic spectrometer and a particle soot absorption photometer, which measure light absorption, and a single particle soot photometer and soot particle aerosol mass spectrometer, which measure the mass concentration of refractory BC directly. These measurements have been used to assess the level of agreement between these different techniques for the determination of BC emission factors from ship plumes. Also, these measurements greatly expand upon the number of individual ships for which BC emission factors have been determined during real-world operation. The measured EFBC's have been divided into vessel type categories and engine type categories, from which averages have been determined. The geometric average EFBC (excluding outliers) determined from over 71 vessels and 135 plumes encountered was 0.31 ± 0.31 g BC (kg fuel)−1, where the standard deviation represents the variability between individual vessels. The most frequent engine type encountered was the slow-speed diesel (SSD), and the most frequent SSD vessel type was the cargo ship sub-category. Average and median EFBC values from the SSD category are compared with previous observations from the Texas Air Quality Study (TexAQS) in 2006, during which the ships encountered were predominately operating on high-sulphur fuels (average fuel sulphur content of 1.6%). There is a statistically significant difference between the EFBC values from CalNex and TexAQS for SSD vessels and for the cargo and tanker ship types within this engine category. The CalNex EFBC values are lower than those from TexAQS, suggesting that operation on lower sulphur fuels is associated with smaller EFBC values.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.542
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.009
GPT teacher head0.215
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it