Bibliographic record
Abstract
To reduce CO2 emissions, the aviation industry has begun looking into alternative biofuels as a replacement for conventional fossil-fuel based jet fuel. Although biofuels may reduce aircraft CO2 emissions, it is also important to consider how other emissions are effected such as particle emissions. Aircraft particle emissions have been studied extensively in the lab or on the ground with stationary aircrafts or test engine cells with few studies measuring emissions from aircraft in-flight. To study in-flight particle emissions, the National Research Council of Canada has equipped a measurement aircraft with condensation particle counters and a catalytic denuder to measure both non-volatile and total (volatile and non-volatile) particles. Two separate flight campaigns were undertaken to collect emissions data from aircrafts in-flight. The Civil Aviation Alternate Fuels Contrail and Emissions Research (CAAFCER) campaign involved the sampling of Air Canada Airbus A320 aircrafts during commercial flights. Two A320 aircraft equipped with CFM56-5A1 engines burning Jet A1 and a 43% hydrotreated esters and fatty acids (HEFA)/Jet A1 blend and another aircraft with CFM56-5B4/P engines burning Jet A1 were sampled. It was found that the particle number emission indices were similar amongst the tested engines and fuel types. The total particle emission index for particles greater than 7.7 nm ranged between 1.44 × 1017 to 2.17 × 1017 particles per kg of fuel, the total particle emission index for particles greater than 15.4 nm ranged between 1.73 × 1016 to 4.73 × 1016 kg-1, and the non-volatile particle emission index for particles greater than 13.3 nm ranged from 3.55 × 1015 to 6.76 × 1015 kg-1. In the Civil Aviation Alternate Fuels Contrails and Emissions with high Blend Biojet (CAAFCEB) campaign, the Falcon 20 research aircraft was sampled in-flight while fueled with an ethanol-based (ATJ) biofuel, JP-5 fuel and Jet A1 fuel. The objective of this flight campaign was to compare the particle emissions of the ATJ and JP-5 fuels to Jet A1 fuel. The total particle emissions for the JP-5 were found to be slightly larger than Jet A1 fuel with the total particle emissions for the JP-5 fuel being 1.29 to 1.52 times larger than for Jet A1. The ATJ biofuel on the other hand was found to significantly reduce total particle number emissions by up to 91% and non-volatile particle number emissions by 96% compared to Jet A1 fuel.
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.
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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".