New method to compute the missed approach fuel consumption and its emissions
Bibliographic record
Abstract
ABSTRACT The aeronautical industry has set for itself important environmental goals, creating the need of improved tools for measuring the polluting emissions generated by fuel burn. This paper describes a new method to estimate the fuel burn and the pollution generated by a landing approach and also for a missed approach procedure. Fuel emission estimations can be used to compare the costs of different routes. The method developed in this paper uses the Emissions Guide Book developed by the European Environment Agency as the needed database for the computations. This method gives estimations of the fuel burn and emissions, including the amounts of CO, NOx, HC, EICO, EINOx and EIHC for a given flight as its output. The flight computation is divided into two sections: one section for the aircraft's travelled distance and a second section for the time an aircraft flies under certain flight modes. Since this method computes the missed approach fuel and emissions contribution, it computes the burn for a given descent approach for a successful landing, as well as for the same descent approach with a missed approach procedure followed by a successful landing. These two landings are verified in a complete flight to study the missed approach contribution for a conventional mid-range flight. The results show that a descent with the missed approach procedure requires 5.7 times more fuel than a normal, successful descent. This extra fuel burn increases the pollution released to the atmosphere and would impact the airlines’ profit margin due to the added fuel costs and longer flight times, as well as any future economic measures imposed on the increased air and noise pollution.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".