Civil Aviation Alternate Fuels Contrails and Emissions from high-Blend Biofuels (CAAFCEB): contrails analysis
Bibliographic record
Abstract
Over the period October 2017 to March 2018, the project Civil Aviation Alternate Fuels Contrails and Emissions with high Blend Biojet (CAAFCEB) was undertaken by the NRC, under sponsorship of Environment & Climate Change Canada, Transport Canada, Lanza Tech and the NRC. The NRC Falcon undertook flight operations on Jet A1, JP-5 (in particular, fuel ‘A-3’ of the North American Jet Fuel Combustion Program, NJFCP, and LanzaTech ATJ bio-jet. High altitude cruising flight contrails at typical air transport cruise Mach Number of 0.8 (M0.8) were sought for each flight, with engines at maximum continuous thrust (MCT). In cruise, contrails and emissions data was measured by the NRC CT-133 research aircraft, out to 50 km (4 minutes age) length contrails. This was sufficient length to identify the state of contrails, persistent or sublimating, as dictated by background atmospheric conditions – both states were encountered upon CAAFCEB flights. CT-133 measurements consisted of contrail ice particle size and number, particulate and gaseous emissions from the Falcon in cruise. The LT PNNL fuel was blended a priori by the NRC, with 8% Exxon Mobil Solvesso 150 ND mono-aromatics, in order to condition the fuel satisfactorily for the Falcon fuel system. Four LT PNNL fuel flights and two JP-5 flights were undertaken. Fuel samples were taken, from the port wing-tank (Jet A1) and the starboard engine fuel feeder tank (experimental fuel, either LT PNNL ATJ, or A-3 JP-5), for each CAAFCEB flight. Prior to the M0.8 cruising flight contrails on baseline and test fuels sequentially, M0.6 Jet A1 contrails were near/at top-of-climb, at contrail lengths of 0.3-3 km (ages of 0.03-0.30 minutes) at approximately 60% of the fuel-flow of M0.8 contrails. Particulate and gaseous emissions were measured, simultaneously with contrail measurements. Top-of-climb emissions were also measured in dry air (prior to the formation of contrails). All contrails were generated by the NRC Falcon, with the same engines. Individual engine emissions and ice particle formation were not measured. Rather, the wake and contrail cross-sections were measured holistically, over the full vertical and lateral extents. A number of lateral/vertical transects, typically nine, were concatenated in the line-of-flight (contrail axis) direction to form re-constructed contrails. Aggregated power-law parameter identification has been conducted to account for the effects of varying atmospheric background conditions (of RH over ice, RH lapse rate and air temperature) upon contrail ice particle numbers, for LT PNNL and Jet A1 fuels. These identifications have been used to adjust contrail ice particle number and size to the same reference atmospheric conditions, for each fuel type. The optical properties of extinction and effective particle size (properties that govern the global warming effects of contrails, by the processes of radiative forcing). Compared to Jet A1, particulate emissions from the LT PNNL fuel were reduced 80-90%: aerosols (>10 nano-m) by 82%, ultrafine particles (>2.5 nano-m) by 90% and non-volatiles (>2.5 nano-m) by 81%. Although greatly reduced in number, soot (essentially, non-volatile) particles were sufficient in number nevertheless, for the emissions environment to be categorised, for contrail production, as soot-rich. Contrail ice particle production was lessened proportionately to the reduction in soot particle number. Ice particle sizes did not vary significantly between fuels. Addressing radiative forcing characteristics, a new parameter has been introduced, namely the Apparent Emission Index of Extinction (AEIEX), defined as the lateral integrand of optical depth of a contrail cross-section, when fully measured at any longitudinal point of its length. This is from the CT-133 data, under the assumption of particle sphericity (measured data implies the development of non-sphericity >20 km contrail length), for ice particles >0.5μm in size. Data shows significant reduction in AEIEX for LT PNNL, c.f. Jet A1. Therefore, the present data are evidence of the desirability to holistically measure AEIEX for the complete contrail ice particle spectra, i.e. all ice particle sizes and shapes. This can be achieved by equipping the CT-133 with the ECCC extinction probe, for additional flights.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".