What a return to supersonic flight could mean for climate change

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What a return to supersonic flight could mean for climate change

This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here. As I’ve admitted in this newsletter before, I love few things more than getting on an airplane. I know, it’s a bold statement from a climate reporter because of all the associated emissions, but it’s true. So I’m as intrigued as the next person by efforts to revive supersonic flight. Last week, Boom Supersonic completed its first supersonic test flight of the XB-1 test aircraft. I watched the broadcast live, and the vibe was infectious, watching the hosts’ anticipation during takeoff and acceleration, and then their celebration once it was clear the aircraft had broken the sound barrier. And yet, knowing what I know about the climate, the promise of a return to supersonic flight is a little tarnished. We’re in a spot with climate change where we need to drastically cut emissions, and supersonic flight would likely take us in the wrong direction. The whole thing has me wondering how fast is fast enough. The aviation industry is responsible for about 4% of global warming to date. And right now only about 10% of the global population flies on an airplane in any given year. As incomes rise and flight becomes more accessible to more people, we can expect air travel to pick up, and the associated greenhouse gas emissions to rise with it. If business continues as usual, emissions from aviation could double by 2050, according to a 2019 report from the International Civil Aviation Organization. Supersonic flight could very well contribute to this trend, because flying faster requires a whole lot more energy—and consequently, fuel. Depending on the estimate, on a per-passenger basis, a supersonic plane will use somewhere between two and nine times as much fuel as a commercial jet today. (The most optimistic of those numbers comes from Boom, and it compares the company’s own planes to first-class cabins.) In addition to the greenhouse gas emissions from increased fuel use, additional potential climate effects may be caused by pollutants like nitrogen oxides, sulfur, and black carbon being released at the higher altitudes common in supersonic flight. For more details, check out my latest story. Boom points to sustainable aviation fuels (SAFs) as the solution to this problem. After all, these alternative fuels could potentially cut out all the greenhouse gases associated with burning jet fuel. The problem is, the market for SAFs is practically embryonic. They made up less than 1% of the jet fuel supply in 2024, and they’re still several times more expensive than fossil fuels. And currently available SAFs tend to cut emissions between 50% and 70%—still a long way from net-zero. Things will (hopefully) progress in the time it takes Boom to make progress on reviving supersonic flight—the company plans to begin building its full-scale plane, Overture, sometime next year. But experts are skeptical that SAF will be as available, or as cheap, as it’ll need to be to decarbonize our current aviation industry, not to mention to supply an entirely new class of airplanes that burn even more fuel to go the same distance. The Concorde supersonic jet, which flew from 1969 to 2003, could get from New York to London in a little over three hours. I’d love to experience that flight—moving faster than the speed of sound is a wild novelty, and a quicker flight across the pond could open new options for travel. One expert I spoke to for my story, after we talked about supersonic flight and how it’ll affect the climate, mentioned that he’s actually trying to convince the industry that planes should actually be slowing down a little bit. By flying just 10% slower, planes could see outsized reductions in emissions. Technology can make our lives better. But sometimes, there’s a clear tradeoff between how technology can improve comfort and convenience for a select group of people and how it will contribute to the global crisis that is climate change. I’m not a Luddite, and I certainly fly more than the average person. But I do feel like, maybe we should all figure out how to slow down, or at least not tear toward the worst impacts of climate change faster. Related reading We named sustainable aviation fuel as one of our 10 Breakthrough Technologies this year. The world of alternative fuels can be complicated. Here’s everything you need to know about the wide range of SAFs. Rerouting planes could help reduce contrails—and aviation’s climate impacts. Read more in this story from James Temple. SARAH ROGERS / MITTR | PHOTO GETTY Another thing DeepSeek has crashed onto the scene, upending established ideas about the AI industry. One common claim is that the company’s model could drastically reduce the energy needed for AI. But the story is more complicated than that, as my colleague James O’Donnell covered in this sharp analysis. Keeping up with climate Donald Trump announced a 10% tariff on goods from China. Plans for tariffs on Mexico and Canada were announced, then quickly paused, this week as well. Here’s more on what it could mean for folks in the US. (NPR)→ China quickly hit back with mineral export curbs on materials including tellurium, a key ingredient in some alternative solar panels. (Mining.com)→ If the tariffs on Mexico and Canada go into effect, they’d hit supply chains for the auto industry, hard. (Heatmap News) Researchers are scrambling to archive publicly available data from agencies like the National Oceanic and Atmospheric Administration. The Trump administration has directed federal agencies to remove references to climate change. (Inside Climate News)→ As of Wednesday morning, it appears that live data that tracks carbon dioxide in the atmosphere is no longer accessible on NOAA’s website. (Try for yourself here) Staffers with Elon Musk’s “department of government efficiency” entered the NOAA offices on Wednesday morning, inciting concerns about plans for the agency. (The Guardian) The National Science Foundation, one of the US’s leading funders of science and engineering research, is reportedly planning to lay off between 25% and 50% of its staff. (Politico) Our roads aren’t built for the conditions being driven by climate change. Warming temperatures and changing weather patterns are hammering roads, driving up maintenance costs. (Bloomberg) Researchers created a new strain of rice that produces much less methane when grown in flooded fields. The variant was made with traditional crossbreeding. (New Scientist) Oat milk maker Oatly is trying to ditch fossil fuels in its production process with industrial heat pumps and other electrified technology. But getting away from gas in food and beverage production isn’t easy. (Canary Media) A new 3D study of the Greenland Ice Sheet reveals that crevasses are expanding faster than previously thought. (Inside Climate News) In other ice news, an Arctic geoengineering project shut down over concerns for wildlife. The nonprofit project was experimenting with using glass beads to slow melting, but results showed it was a threat to food chains. (New Scientist)

This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here.

As I’ve admitted in this newsletter before, I love few things more than getting on an airplane. I know, it’s a bold statement from a climate reporter because of all the associated emissions, but it’s true. So I’m as intrigued as the next person by efforts to revive supersonic flight.

Last week, Boom Supersonic completed its first supersonic test flight of the XB-1 test aircraft. I watched the broadcast live, and the vibe was infectious, watching the hosts’ anticipation during takeoff and acceleration, and then their celebration once it was clear the aircraft had broken the sound barrier.

And yet, knowing what I know about the climate, the promise of a return to supersonic flight is a little tarnished. We’re in a spot with climate change where we need to drastically cut emissions, and supersonic flight would likely take us in the wrong direction. The whole thing has me wondering how fast is fast enough.

The aviation industry is responsible for about 4% of global warming to date. And right now only about 10% of the global population flies on an airplane in any given year. As incomes rise and flight becomes more accessible to more people, we can expect air travel to pick up, and the associated greenhouse gas emissions to rise with it.

If business continues as usual, emissions from aviation could double by 2050, according to a 2019 report from the International Civil Aviation Organization.

Supersonic flight could very well contribute to this trend, because flying faster requires a whole lot more energy—and consequently, fuel. Depending on the estimate, on a per-passenger basis, a supersonic plane will use somewhere between two and nine times as much fuel as a commercial jet today. (The most optimistic of those numbers comes from Boom, and it compares the company’s own planes to first-class cabins.)

In addition to the greenhouse gas emissions from increased fuel use, additional potential climate effects may be caused by pollutants like nitrogen oxides, sulfur, and black carbon being released at the higher altitudes common in supersonic flight. For more details, check out my latest story.

Boom points to sustainable aviation fuels (SAFs) as the solution to this problem. After all, these alternative fuels could potentially cut out all the greenhouse gases associated with burning jet fuel.

The problem is, the market for SAFs is practically embryonic. They made up less than 1% of the jet fuel supply in 2024, and they’re still several times more expensive than fossil fuels. And currently available SAFs tend to cut emissions between 50% and 70%—still a long way from net-zero.

Things will (hopefully) progress in the time it takes Boom to make progress on reviving supersonic flight—the company plans to begin building its full-scale plane, Overture, sometime next year. But experts are skeptical that SAF will be as available, or as cheap, as it’ll need to be to decarbonize our current aviation industry, not to mention to supply an entirely new class of airplanes that burn even more fuel to go the same distance.

The Concorde supersonic jet, which flew from 1969 to 2003, could get from New York to London in a little over three hours. I’d love to experience that flight—moving faster than the speed of sound is a wild novelty, and a quicker flight across the pond could open new options for travel.

One expert I spoke to for my story, after we talked about supersonic flight and how it’ll affect the climate, mentioned that he’s actually trying to convince the industry that planes should actually be slowing down a little bit. By flying just 10% slower, planes could see outsized reductions in emissions.

Technology can make our lives better. But sometimes, there’s a clear tradeoff between how technology can improve comfort and convenience for a select group of people and how it will contribute to the global crisis that is climate change.

I’m not a Luddite, and I certainly fly more than the average person. But I do feel like, maybe we should all figure out how to slow down, or at least not tear toward the worst impacts of climate change faster.

Another thing

DeepSeek has crashed onto the scene, upending established ideas about the AI industry. One common claim is that the company’s model could drastically reduce the energy needed for AI. But the story is more complicated than that, as my colleague James O’Donnell covered in this sharp analysis.

Keeping up with climate

Donald Trump announced a 10% tariff on goods from China. Plans for tariffs on Mexico and Canada were announced, then quickly paused, this week as well. Here’s more on what it could mean for folks in the US. (NPR)
→ China quickly hit back with mineral export curbs on materials including tellurium, a key ingredient in some alternative solar panels. (Mining.com)
→ If the tariffs on Mexico and Canada go into effect, they’d hit supply chains for the auto industry, hard. (Heatmap News)

Researchers are scrambling to archive publicly available data from agencies like the National Oceanic and Atmospheric Administration. The Trump administration has directed federal agencies to remove references to climate change. (Inside Climate News)
→ As of Wednesday morning, it appears that live data that tracks carbon dioxide in the atmosphere is no longer accessible on NOAA’s website. (Try for yourself here)

Staffers with Elon Musk’s “department of government efficiency” entered the NOAA offices on Wednesday morning, inciting concerns about plans for the agency. (The Guardian)

The National Science Foundation, one of the US’s leading funders of science and engineering research, is reportedly planning to lay off between 25% and 50% of its staff. (Politico)

Our roads aren’t built for the conditions being driven by climate change. Warming temperatures and changing weather patterns are hammering roads, driving up maintenance costs. (Bloomberg)

Researchers created a new strain of rice that produces much less methane when grown in flooded fields. The variant was made with traditional crossbreeding. (New Scientist)

Oat milk maker Oatly is trying to ditch fossil fuels in its production process with industrial heat pumps and other electrified technology. But getting away from gas in food and beverage production isn’t easy. (Canary Media)

A new 3D study of the Greenland Ice Sheet reveals that crevasses are expanding faster than previously thought. (Inside Climate News)

In other ice news, an Arctic geoengineering project shut down over concerns for wildlife. The nonprofit project was experimenting with using glass beads to slow melting, but results showed it was a threat to food chains. (New Scientist)

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Flexential Partners with Lonestar to Support First Lunar Data Center

Flexential, a leading provider of secure and flexible data center solutions, this month announced that it has joined forces with Lonestar Data Holdings Inc. to support the upcoming launch of Freedom, Lonestar’s second lunar data center. Scheduled to launch aboard a SpaceX Falcon 9 rocket via Intuitive Machines, this mission is a critical step toward establishing a permanent data center on the Moon. Ground-Based Support for Lunar Data Storage Flexential’s Tampa data center will serve as the mission control platform for Lonestar’s lunar operations, providing colocation, interconnection, and professional services. The facility was chosen for its proximity to Florida’s Space Coast launch operations and its ability to deliver low-latency connectivity for critical functions. Flexential operates two data centers in Tampa and four in Florida as part of its FlexAnywhere® Platform, comprising more than 40 facilities across the U.S. “Flexential’s partnership with Lonestar represents our commitment to advancing data center capabilities beyond conventional boundaries,” said Jason Carolan, Chief Innovation Officer at Flexential. “By supporting Lonestar’s space-based data center initiative, we are helping to create new possibilities for data storage and disaster recovery. This project demonstrates how innovative data center expertise can help organizations prepare for a resilient future with off-world storage solutions.” A New Era of Space-Based Resiliency The growing demand for data center capacity, with U.S. power consumption expected to double from 17 GW in 2022 to 35 GW by 2030 (according to McKinsey & Company), is driving interest in space-based solutions. Storing data off-planet reduces reliance on terrestrial resources while enhancing security against natural disasters, warfare, and cyber threats. The Freedom data center will provide resiliency, disaster recovery, and edge processing services for government and enterprise customers requiring the highest levels of data protection. The solar-powered data center leverages Solid-State Drives (SSDs) and a Field Programmable Gate Array (FPGA) edge

Why DeepSeek Is Great for AI and HPC and Maybe No Big Deal for Data Centers

In the rapid and ever-evolving landscape of artificial intelligence (AI) and high-performance computing (HPC), the emergence of DeepSeek’s R1 model has sent ripples across industries. DeepSeek has been the data center industry’s topic of the week, for sure. The Chinese AI app surged to the top of US app store leaderboards last weekend, sparking a global selloff in technology shares Monday morning. But while some analysts predict a transformative impact within the industry, a closer examination suggests that, for data centers at large, the furor over DeepSeek might ultimately be much ado about nothing. DeepSeek’s Breakthrough in AI and HPC DeepSeek, a Chinese AI startup, this month unveiled its R1 model, claiming performance on par with, or even surpassing, leading models like OpenAI’s ChatGPT-4 and Anthropic’s Claude-3.5-Sonnet. Remarkably, DeepSeek developed this model at a fraction of the cost typically associated with such advancements, utilizing a cluster of 256 server nodes equipped with 2,048 GPUs. This efficiency has been attributed to innovative techniques and optimized resource utilization. AI researchers have been abuzz about the performance of the DeepSeek chatbot that produces results similar to ChatGPT, but is based on open-source models and reportedly trained on older GPU chips. Some researchers are skeptical of claims about DeepSeek’s development costs and means, but its performance appears to challenge common assumptions about the computing cost of developing AI applications. This efficiency has been attributed to innovative techniques and optimized resource utilization. Market Reactions and Data Center Implications The announcement of DeepSeek’s R1 model led to significant market reactions, with notable declines in tech stocks, including a substantial drop in Nvidia’s valuation. This downturn was driven by concerns that more efficient AI models could reduce the demand for high-end hardware and, by extension, the expansive data centers that house them. For now, investors are re-assessing the

Microsoft will invest $80B in AI data centers in fiscal 2025

And Microsoft isn’t the only one that is ramping up its investments into AI-enabled data centers. Rival cloud service providers are all investing in either upgrading or opening new data centers to capture a larger chunk of business from developers and users of large language models (LLMs). In a report published in October 2024, Bloomberg Intelligence estimated that demand for generative AI would push Microsoft, AWS, Google, Oracle, Meta, and Apple would between them devote $200 billion to capex in 2025, up from $110 billion in 2023. Microsoft is one of the biggest spenders, followed closely by Google and AWS, Bloomberg Intelligence said. Its estimate of Microsoft’s capital spending on AI, at $62.4 billion for calendar 2025, is lower than Smith’s claim that the company will invest $80 billion in the fiscal year to June 30, 2025. Both figures, though, are way higher than Microsoft’s 2020 capital expenditure of “just” $17.6 billion. The majority of the increased spending is tied to cloud services and the expansion of AI infrastructure needed to provide compute capacity for OpenAI workloads. Separately, last October Amazon CEO Andy Jassy said his company planned total capex spend of $75 billion in 2024 and even more in 2025, with much of it going to AWS, its cloud computing division.

John Deere unveils more autonomous farm machines to address skill labor shortage

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Self-driving tractors might be the path to self-driving cars. John Deere has revealed a new line of autonomous machines and tech across agriculture, construction and commercial landscaping. The Moline, Illinois-based John Deere has been in business for 187 years, yet it’s been a regular as a non-tech company showing off technology at the big tech trade show in Las Vegas and is back at CES 2025 with more autonomous tractors and other vehicles. This is not something we usually cover, but John Deere has a lot of data that is interesting in the big picture of tech. The message from the company is that there aren’t enough skilled farm laborers to do the work that its customers need. It’s been a challenge for most of the last two decades, said Jahmy Hindman, CTO at John Deere, in a briefing. Much of the tech will come this fall and after that. He noted that the average farmer in the U.S. is over 58 and works 12 to 18 hours a day to grow food for us. And he said the American Farm Bureau Federation estimates there are roughly 2.4 million farm jobs that need to be filled annually; and the agricultural work force continues to shrink. (This is my hint to the anti-immigration crowd). John Deere’s autonomous 9RX Tractor. Farmers can oversee it using an app. While each of these industries experiences their own set of challenges, a commonality across all is skilled labor availability. In construction, about 80% percent of contractors struggle to find skilled labor. And in commercial landscaping, 86% of landscaping business owners can’t find labor to fill open positions, he said. “They have to figure out how to do

2025 playbook for enterprise AI success, from agents to evals

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More 2025 is poised to be a pivotal year for enterprise AI. The past year has seen rapid innovation, and this year will see the same. This has made it more critical than ever to revisit your AI strategy to stay competitive and create value for your customers. From scaling AI agents to optimizing costs, here are the five critical areas enterprises should prioritize for their AI strategy this year. 1. Agents: the next generation of automation AI agents are no longer theoretical. In 2025, they’re indispensable tools for enterprises looking to streamline operations and enhance customer interactions. Unlike traditional software, agents powered by large language models (LLMs) can make nuanced decisions, navigate complex multi-step tasks, and integrate seamlessly with tools and APIs. At the start of 2024, agents were not ready for prime time, making frustrating mistakes like hallucinating URLs. They started getting better as frontier large language models themselves improved. “Let me put it this way,” said Sam Witteveen, cofounder of Red Dragon, a company that develops agents for companies, and that recently reviewed the 48 agents it built last year. “Interestingly, the ones that we built at the start of the year, a lot of those worked way better at the end of the year just because the models got better.” Witteveen shared this in the video podcast we filmed to discuss these five big trends in detail. Models are getting better and hallucinating less, and they’re also being trained to do agentic tasks. Another feature that the model providers are researching is a way to use the LLM as a judge, and as models get cheaper (something we’ll cover below), companies can use three or more models to

OpenAI’s red teaming innovations define new essentials for security leaders in the AI era

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More OpenAI has taken a more aggressive approach to red teaming than its AI competitors, demonstrating its security teams’ advanced capabilities in two areas: multi-step reinforcement and external red teaming. OpenAI recently released two papers that set a new competitive standard for improving the quality, reliability and safety of AI models in these two techniques and more. The first paper, “OpenAI’s Approach to External Red Teaming for AI Models and Systems,” reports that specialized teams outside the company have proven effective in uncovering vulnerabilities that might otherwise have made it into a released model because in-house testing techniques may have missed them. In the second paper, “Diverse and Effective Red Teaming with Auto-Generated Rewards and Multi-Step Reinforcement Learning,” OpenAI introduces an automated framework that relies on iterative reinforcement learning to generate a broad spectrum of novel, wide-ranging attacks. Going all-in on red teaming pays practical, competitive dividends It’s encouraging to see competitive intensity in red teaming growing among AI companies. When Anthropic released its AI red team guidelines in June of last year, it joined AI providers including Google, Microsoft, Nvidia, OpenAI, and even the U.S.’s National Institute of Standards and Technology (NIST), which all had released red teaming frameworks. Investing heavily in red teaming yields tangible benefits for security leaders in any organization. OpenAI’s paper on external red teaming provides a detailed analysis of how the company strives to create specialized external teams that include cybersecurity and subject matter experts. The goal is to see if knowledgeable external teams can defeat models’ security perimeters and find gaps in their security, biases and controls that prompt-based testing couldn’t find. What makes OpenAI’s recent papers noteworthy is how well they define using human-in-the-middle

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