the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 21 Apr 2026
Efficacy of Scalable Airline-led Contrail Avoidance
Abstract. Contrails account for a large portion of aviation's contribution to anthropogenic climate change. Navigational contrail avoidance is a promising solution to mitigate the warming caused by contrails. Prior trials testing navigational contrail avoidance have relied on bespoke integrations of contrail forecasts into airline operations. Here, we use a randomized control trial to test the feasibility of dispatcher-led contrail avoidance integrated into standard flight planning operations using a workflow that scales to an airline's entire network. We validated the efficacy of this intervention using satellite imagery and an automated flight-contrail attribution algorithm. Using this system, we observed an 11.6 % reduction in contrail formation rate for the 1232 flights marked as eligible for contrail avoidance (intent-to-treat) relative to the flights in the control group (p = 0.011). In the 112 flights that flew contrail avoidance as planned (per-protocol flights), we observed a 62.0 % lower contrail formation rate relative to the flights in the control group (p < 0.001). No statistically significant difference in fuel usage was observed between the two groups.
Competing interests: As denoted by their affiliations, some authors are employed by Google LLC, Flightkeys GmbH, and American Airlines. Contrails.org is operated by Breakthrough Energy, a family of organizations and activities committed to transitioning the world to net zero by 2050. All other authors declare no competing interests.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.- Preprint
(1578 KB) - Metadata XML
- BibTeX
- EndNote
Status: open (until 16 Jun 2026)
- RC1: 'Comment on jecats-2026-4', Anonymous Referee #1, 25 May 2026 reply
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 142 | 48 | 24 | 214 | 23 | 26 |
- HTML: 142
- PDF: 48
- XML: 24
- Total: 214
- BibTeX: 23
- EndNote: 26
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
Review of
Efficacy of scalable airline-led contrail avoidance
by T. Sankar et al., JECATS-2026-4
General comments
Contrail avoidance is often seen as a possibility to quickly lessen the rate at which aviation's climate warming contribution rises. For this reason it is important to conduct tests that occur not only in computer simulations but as well in the operational environment. A few such trials did occur in the recent past but they involved only few flights to evaluate, and the planning and evaluation was done manually which takes too much time for an operational system. The trial described in this manuscript intends to overcome some of these problems, the much manual work and the low number of flights for evaluation which is a step forward. But the paper also demonstrates that there are still difficulties and room for improvements, issues that must be tackled before contrail-avoidance flight-planning can actually become operational. These issues are discussed in Sect. 4, and this is the best part of the manuscript.
Otherwise, I admit that it was difficult for me to understand how this trial was operated although the authors tried to explain it. Things and notions are not clear to me. Thus I recommend to work especially on an exact description of what has been done, explaining all the steps.
I have also a problem with the climatological evaluation of the trial. The evaluation of how much contrail coverage was avoided is ok, but the evaluation of how much forcing or climate impact was avoided is not. Since this evaluation is based on a climatology, I believe that the results are more or less random, and that therefore the statistical evaluation ("statistically significant...") does not say anything for the real world. Please consider that the actual weather is the most dominant influencing factor on contrail radiative impacts. For this reason, I think, the ideas of conducting contrail-avoidance in a "climatological sense" have been abandoned about 20 years ago. I hope that this is acknowledged in the revised version.
Major comments:
1) I had problems to understand how this trial had been performed. I have a lot of questions for clarification:
1.1) There is a control group and an intent-to-treat group. There are also "non-avoidance" plans and "contrail-optimized" plans. It is unclear how these two pairs of notions are related. Is the control group equivalent to the group with the "non-avoidane" plans? Still another expression is "per-protocol flights". I am confuesed by this multiplicity of notions.
1.2) Flights with a "non-avoidance" plan were re-optimized including the contrail cost term. Why and for what purpose?
1.3) Why and for what purpose were dispatchers presented with one or more non-avoidance plans? Is it a common process to generate several flight plans for the dispatcher to select one?
1.4) Initially I thought Flightkeys computes an optimal route, either cost or contrail-optimized, and that this is given to the dispatcher. I thought that neither the dispatcher nor the pilot knows on what kind of optimization the flight was planned. But this impression later turns out wrong.
1.5) Please define the L1,2,3 groups with more details. My questions were: Does the L1 group contain routes for which no (strong) contrail was forecasted? If so, then the L2 group is the one where contrails were forecasts, but not all of them have been avoided when the dispatcher had other priorities? And the, L3 is the group where contrails have been avoided acitvely by dispatcher and pilots. Is this correct?
2.) As stated above, I find the evaluation of the contrail impact (or the avoided impact), based on climatological fields, insufficient. I wonder whether the derived values have any significance. You can say, if we assume that the actual weather were like the climatology, the results were x and y, and the difference were statistically significant. BUT, the weather is generally not like the climatology on a certain day, and thus we must expect large deviations of the actual forcings from the obtained ones. As these values are not known, their differences cannot be determined. To my opinion, the corresponding tables and statements should be removed from the paper in order not no rise wrong expectations in uncautious readership.
Minor comments:
1.) I suggest to spend a bit more time to explain a bit how the ML-contrail forecast works. A short overview is sufficient. This is for the convenience of the reader, who otherwise has to change to the paper by Sonabend-W (and in fact, I did not remember that a description of the ML-based contrail forecast was given there, but that may be my fault). I wonder how satellite images of contrails or series of images can be used for contrail forecasting. The contrails in the images already exist and stem from past flights where contrail formation has not been avoided. Please help the reader with a short text to an imagination how this system works.
2.) The trial took place mainly over the western part of the Atlantic ocean where flight density is probably low. Do the authors think that the methods investigated in this trial can be used in similar way in more congested regions like continental US or even Europe?
3.) "The results provide strong evidence... physically effective and operationally feasible." This is an unclear statement. I believe that contrail avoidance is operationally feasible, under certain circumstances, as you show in the paper, namely when the dispatcher does not have other problems to solve. Whether it is feasible in congested air-spaces remains doubtful. What do you mean with "physically effective"? If you mean the reduction of contrail coverage, please say so. If you however mean the calculated reduction of warming impact, I do not agree unless you change your method from a climatologically based one to a actual-weather based one. The expression "climatological warming" makes no sense for single flights.
Miscellaneous:
L 29-31: One should remark here that at least in the paper by Frias et al. a perfect weather forecast was assumed which renders results doubtful.
L 51 ff: "Per-contrail estimates": what do you mean, estimates of what?
L 85 ff: it is unclear where in this conversion the ERF/RF ratio applies. RF and ERF have units w/m², but if the conversion is J/tonne, I don't see how this matches. I have a conjecture, but please write it down clearly. Further: The (quite uncertain) ERF/RF ratio is a climatological quantity and cannot be applied to evaluate the impact of single flights. I would find it acceptable if the impact evaluation would have been perfomed on an actual instead of a climatological basis, since then it is just a change of units and is transparent for statistical analyses.
Sect. 2.2 first par: as the trial was restricted to eastbound flights which take place predominantly at local night and whose contrails therefore are probably warming, would you recommend to make such a system operational on eastbound flights only, or perhaps to begin the operational phase with eastbound flights?
L 102: "forecasted contrail EF". To make it clear, please state whether this prediction was done with the actual weather or with the climatology mentioned before.
L 380: Please note that a fuel penalty is accompanied whith higher emissions of CO2 and non-CO2 gases and aerosols, and with their corresponding impacts.
Appendix B1, L 419: 789 m is more than 2000 ft, that is more than 2 flight levels. Is this altitude definition good enough?
Appendix B2, L 432: 1615 m is even more than 5 flight levels. So, same question.