Sustainable Development Goals > Planet

CONTRAILS: MAKING FLYING MORE SUSTAINABLE WITH GOOGLE AI

GOOGLE, Mountain View / GOOGLE / 2024

Awards:

Silver Cannes Lions
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Overview

Credits

Overview

Why is this work relevant for Sustainable Development Goals?

Google has conducted research, in partnership with Breakthrough Energy and American Airlines, on one of the lowest-cost climate solutions to aviation emissions, powered by AI. This research is a significant proof point that commercial airlines can verifiably avoid contrails and thereby reduce their climate impact.

Please provide any cultural context that would help the Jury understand any cultural, national or regional nuances applicable to this work.

Aviation is one of the hardest-to-decarbonize sectors in our transport infrastructure. It accounts for around 2.5% of global CO2 emissions, but the industry contributes closer to 3.5% of global warming. According to IPCC’s Sixth Assessment Report (AR6), contrails are responsible for a disproportionately large share – approximately 35% – of aviation’s global warming impact.

The good news is that planes can fly without creating contrails, but the challenge is knowing the routes that will create them. A team at Google Research learned of the impact of contrails and realized that they might be able to identify contrail-forming regions by training a machine learning algorithm to detect contrails in satellite imagery.

How does this campaign fit into the overall brand objectives? How is this part of the brand's wider commitment towards the UN’s Sustainable Development Goals?

Google is committed to sustainability. One of the ways we invest in sustainability is by collaborating with our partners to explorate AI-enabled climate solutions. Our contrails research is an example of collaborating with our partners - American Airlines and Breakthrough Energy - to see how AI could enable climate-beneficial action.

The core technical capabilities include computer vision algorithms and large scale data processing. The solution requires processing large amounts of satellite, weather, and flight data. We applied the same technology that powers Waymo’s self-driving car to identify clouds from satellite imagery.

Background

Contrails constitute ⅓ of aviation’s warming effect. Mitigating contrail formation through altitude changes has been discussed in academic literature as a potential cost-effective climate solution. Our goal was to test in a world-first real-world demonstration that verifiable contrail reduction is possible. We created a substantial dataset of labeled contrail images to use in developing precise models to guide real flights and detect whether or not they created contrails. We were able to demonstrate a 54% reduction of contrail creation using our approach.

Describe the cultural / social / political climate and the significance of the work within this context

Contrails — the thin, white lines you sometimes see behind airplanes — have a surprisingly large impact on our climate. The 2022 IPCC report noted that clouds created by contrails account for roughly 35% of aviation's global warming impact, over half the impact of the world’s jet fuel. Though planes can’t currently fly without burning fuel, they can fly without creating contrails. The challenge is knowing which flight routes will create them. Google Research teamed up with American Airlines and Breakthrough Energy to bring together huge amounts of data — like satellite imagery, weather and flight path data — and used AI to develop contrail forecast maps to test if pilots can choose routes that avoid creating contrails.

Describe the creative idea

The film “Can Google AI help make flying more sustainable?” highlights the unique combination of curiosity and expertise that led to the development of the research project, told by the passionate scientists driving it forward. The project was initiated by an engineer who read a paper that described the impact of contrails on the environment. He realized that with image understanding of satellite imagery at scale, it might be possible to detect where contrail-forming regions could be and to ultimately direct planes away from them. This led to a whole new area of research at Google and to the partnership with Breakthrough Energy and American Airlines. This collaboration brought together each team’s unique expertise to achieve the industry’s first proof point that commercial airlines can verifiably avoid contrails and thereby reduce their climate impact. This is a significant accomplishment in aviation, which is a notoriously difficult sector to decarbonize.

Describe the strategy

Using AI-based image recognition technology and satellite imagery, Google identified contrail forming regions and made slight adjustments to traditional flight paths that would avoid those areas.

Similar to the machine learning algorithms that are trained to pick out a cat in your photos, the team at Google Research spent hours training algorithms to identify contrails in satellite imagery. From there, they were able to predict ‘contrail likely zones’ for future flights and provide recommendations on what upper atmosphere zones planes should avoid when flying routes. The core technical capabilities include computer vision algorithms and large scale data processing. The solution requires processing large amounts of satellite, weather, and flight data.

Describe the execution

We started working with American Airlines and Breakthrough Energy in 2021. We took time to develop the operational protocols and ensure the pilot and passenger experience would in no way be negatively affected. We flew our first flights in 2022 and completed our proof of concept earlier in 2023.

A group of pilots at American Airlines then flew 70 test flights over six months using the AI-based predictions. After these test flights, the team analyzed satellite imagery and found that the predictions reduced contrails by 54% compared to when pilots didn’t use the predictions. We also saw that flights that avoided contrails burned 2% more fuel, which would translate to 0.3% more fuel when scaled across an airline’s fleet. Together, this suggests contrail avoidance costs could be in the range of $5-25/ton CO2e, which would make it one of the most cost-effective climate solutions.

Describe the results/impact

Using AI-based image recognition technology and satellite imagery, we identified contrail forming regions and made slight adjustments to traditional flight paths that would avoid those areas. After running live trials with pilots as they flew domestic American Airlines routes, we achieved our first proof point demonstrating verifiable, statistically significant, scalable and cost-effective contrail avoidance. A key accomplishment of this collaboration was the ability to safely integrate these new AI-based insights into the pilot’s workflow.

The work catalyzed investment in developing contrail avoidance as a scaled, cost-effective climate solution. The work catalyzed interest in contrails across the aviation industry, and the video has been shown from boardrooms to conferences. The video was shared with executives across the aviation industry and accelerated industry investment in contrails research. We plan to continue working with more aviation partners to scale the technology industry-wide.

Describe the long-term expectations/outcome for this work

Contrail avoidance has the potential to be a cost-effective, scalable solution to reduce the climate impact of flying. We will continue research and development to automate avoidance, target the highest impact contrails and improve satellite-based verification. We’re committed to working across the aviation industry to use AI to make contrail avoidance a reality over the coming years.

Were the carbon emissions of this piece of work measured? For additional context, what consideration was given to the sustainable development, production and running of the work?

We did not measure the carbon emissions of the work but were mindful of reducing travel and team size in order to minimize environmental impact. Approximately 90% of the non-interview footage uses stock imagery. Editorial, design, and animation was completed remotely, with participants dialing in from two different countries and 4 different cities. Interviews were conducted using local crew and resources wherever possible, and the total production team size was kept small, under 8 people. On set, sustainable production practices were used, employing reusable materials whenever possible to reduce waste.

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