Particle and Gaseous Emissions from Commercial Aircraft at Each Stage of the Landing and Takeoff Cycle
Bibliographic record
Abstract
A novel technique was used to measure emission factors for commonly used commercial aircraft including a range of Boeing and Airbus airframes under real world conditions. Engine exhaust emission factors for particles in terms of particle number and mass (PM<sub>2.5</sub>), along with those for CO<sub>2</sub> and NO<sub><i>x</i></sub>, were measured for over 280 individual aircraft during the various modes of landing/takeoff (LTO) cycle. Results from this study show that particle number, and NO<sub><i>x</i></sub> emission factors are dependent on aircraft engine thrust level. Minimum and maximum emissions factors for particle number, PM<sub>2.5</sub>, and NO<sub><i>x</i></sub> emissions were found to be in the range of 4.16 × 10<sup>15</sup>−5.42 × 10<sup>16</sup> kg<sup>−1</sup>, 0.03−0.72 g.kg<sup>−1</sup>, and 3.25−37.94 g.kg<sup>−1</sup>, respectively, for all measured airframes and LTO cycle modes. Number size distributions of emitted particles for the naturally diluted aircraft plumes in each mode of LTO cycle showed that particles were predominantly in the range of 4−100 nm in diameter in all cases. In general, size distributions exhibit similar modality during all phases of the LTO cycle. A very distinct nucleation mode was observed in all particle size distributions, except for taxiing and landing of A320 aircraft. Accumulation modes were also observed in all particle size distributions. Analysis of aircraft engine emissions during LTO cycle showed that aircraft thrust level is considerably higher during taxiing than idling suggesting that International Civil Aviation Organization (ICAO) standards need to be modified as the thrust levels for taxi and idle are considered to be the same (7% of total thrust) (<i>Environmental Protection, Annex 16, Vol. II, Aircraft Engine Emissions</i>, 2nd ed.; ICAOInternational Civil Aviation Organization: Montreal, 1993).
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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 | 0.000 | 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) | 0.032 | 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".