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Inside Climeworks’ big experiment to wrest carbon from the air

In the spring of 2021, the world’s leading authority on energy published a “roadmap” for preventing the most catastrophic climate change scenarios. One of its conclusions was particularly daunting. Getting energy-related emissions down to net zero by 2050, the International Energy Agency said, would require “huge leaps in innovation.”
Existing technologies would be mostly sufficient to carry us down the carbon curve over the next decade. But after that, nearly half of the remaining work would have to come from solutions that, for all intents and purposes, did not exist yet. Some would only require retooling existing industries, like developing electric long-haul trucks and carbon-free steel. But others would have to be built from almost nothing and brought to market in record time.
What will it take to rapidly develop new solutions, especially those that involve costly physical infrastructure and which have essentially no commercial value today?
That’s the challenge facing Climeworks, the Swiss company developing machines to wrest carbon dioxide molecules directly from the air. In September 2021, a few months after the IEA’s landmark report came out, Climeworks switched on its first commercial-scale “direct air capture” facility, a feat of engineering it dubbed “Orca,” in Iceland.
The technology behind Orca is one of the top candidates to clean up the carbon already blanketing the Earth. It could also be used to balance out any stubborn, residual sources of greenhouse gases in the future, such as from agriculture or air travel, providing the “net” in net-zero. If we manage to scale up technologies like Orca to the point where we remove more carbon than we release, we could even begin cooling the planet.
As the largest carbon removal plant operating in the world, Orca is either trivial or one of the most important climate projects built in the last decade, depending on how you look at it. It was designed to capture approximately 4,000 metric tons of carbon from the air per year, which, as one climate scientist, David Ho, put it, is the equivalent of rolling back the clock on just 3 seconds of global emissions. But the learnings gleaned from Orca could surpass any quantitative assessment of its impact. How well do these “direct air capture” machines work in the real world? How much does it really cost to run them? And can they get better?
The company — and its funders — are betting they can. Climeworks has made major deals with banks, insurers, and other companies trying to go green to eventually remove carbon from the atmosphere on their behalf. Last year, the company raised $650 million in equity that will “unlock the next phase of its growth,” scaling the technology “up to multi-million-ton capacity … as carbon removal becomes a trillion-dollar market.” And just last month, the U.S. Department of Energy selected Climeworks, along with another carbon removal company, Heirloom, to receive up to $600 million to build a direct air capture “hub” in Louisiana, with the goal of removing one million tons of carbon annually.
Two years after powering up Orca, Climeworks has yet to reveal how effective the technology has proven to be. But in extensive interviews, top executives painted a picture of innovation in progress.
Chief marketing officer Julie Gosalvez told me that Orca is small and climatically insignificant on purpose. The goal is not to make a dent in climate change — yet — but to maximize learning at minimal cost. “You want to learn when you're small, right?” Gosalvez said. “It’s really de-risking the technology. It’s not like Tesla doing EVs when we have been building cars for 70 years and the margin of learning and risk is much smaller. It’s completely new.”
From the ground, Orca looks sort of like a warehouse or a server farm with a massive air conditioning system out back. The plant consists of eight shipping container-sized boxes arranged in a U-shape around a central building, each one equipped with an array of fans. When the plant is running, which is more or less all the time, the fans suck air into the containers where it makes contact with a porous filter known as a “sorbent” which attracts CO2 molecules.

When the filters become totally saturated with CO2, the vents on the containers snap shut, and the containers are heated to more than 212 degrees Fahrenheit. This releases the CO2, which is then delivered through a pipe to a secondary process called “liquefaction,” where it is compressed into a liquid. Finally, the liquid CO2 is piped into basalt rock formations underground, where it slowly mineralizes into stone. The process requires a little bit of electricity and a lot of heat, all of which comes from a carbon-free source — a geothermal power plant nearby.
A day at Orca begins with the morning huddle. The total number on the team is often in flux, but it typically has a staff of about 15 people, Climeworks’ head of operations Benjamin Keusch told me. Ten work in a virtual control room 1,600 miles away in Zurich, taking turns monitoring the plant on a laptop and managing its operations remotely. The remainder work on site, taking orders from the control room, repairing equipment, and helping to run tests.
During the huddle, the team discusses any maintenance that needs to be done. If there’s an issue, the control room will shut down part of the plant while the on-site workers investigate. So far, they’ve dealt with snow piling up around the plant that had to be shoveled, broken and corroded equipment that had to be replaced, and sediment build-up that had to be removed.

The air is more humid and sulfurous at the site in Iceland than in Switzerland, where Climeworks had built an earlier, smaller-scale model, so the team is also learning how to optimize the technology for different weather. Within all this troubleshooting, there’s additional trade-offs to explore and lessons to learn. If a part keeps breaking, does it make more sense to plan to replace it periodically, or to redesign it? How do supply chain constraints play into that calculus?
The company is also performing tests regularly, said Keusch. For example, the team has tested new component designs at Orca that it now plans to incorporate into Climeworks’ next project from the start. (Last year, the company began construction on “Mammoth,” a new plant that will be nine times larger than Orca, on a neighboring site.) At a summit that Climeworks hosted in June, co-founder Jan Wurzbacher said the company believes that over the next decade, it will be able to make its direct air capture system twice as small and cut its energy consumption in half.
“In innovation lingo, the jargon is we haven’t converged on a dominant design,” Gregory Nemet, a professor at the University of Wisconsin who studies technological development, told me. For example, in the wind industry, turbines with three blades, upwind design, and a horizontal axis, are now standard. “There were lots of other experiments before that convergence happened in the late 1980s,” he said. “So that’s kind of where we are with direct air capture. There’s lots of different ways that are being tried right now, even within a company like Climeworks."
Although Climeworks was willing to tell me about the goings-on at Orca over the last two years, the company declined to share how much carbon it has captured or how much energy, on average, the process has used.
Gosalvez told me that the plant’s performance has improved month after month, and that more detailed information was shared with investors. But she was hesitant to make the data public, concerned that it could be misinterpreted, because tests and maintenance at Orca require the plant to shut down regularly.
“Expectations are not in line with the stage of the technology development we are at. People expect this to be turnkey,” she said. “What does success look like? Is it the absolute numbers, or the learnings and ability to scale?”
Danny Cullenward, a climate economist and consultant who has studied the integrity of various carbon removal methods, did not find the company’s reluctance to share data especially concerning. “For these earliest demonstration facilities, you might expect people to hit roadblocks or to have to shut the plant down for a couple of weeks, or do all sorts of things that are going to make it hard to transparently report the efficiency of your process, the number of tons you’re getting at different times,” he told me.
But he acknowledged that there was an inherent tension to the stance, because ultimately, Climeworks’ business model — and the technology’s effectiveness as a climate solution — depend entirely on the ability to make precise, transparent, carbon accounting claims.
Nemet was also of two minds about it. Carbon removal needs to go from almost nothing today to something like a billion tons of carbon removed per year in just three decades, he said. That’s a pace on the upper end of what’s been observed historically with other technologies, like solar panels. So it’s important to understand whether Climeworks’ tech has any chance of meeting the moment. Especially since the company faces competition from a number of others developing direct air capture technologies, like Heirloom and Occidental Petroleum, that may be able to do it cheaper, or faster.
However, Nemet was also sympathetic to the position the company was in. “It’s relatively incremental how these technologies develop,” he said. “I have heard this criticism that this is not a real technology because we haven’t built it at scale, so we shouldn’t depend on it. Or that one of these plants not doing the removal that it said it would do shows that it doesn’t work and that we therefore shouldn’t plan on having it available. To me, that’s a pretty high bar to cross with a climate mitigation technology that could be really useful.”
More data on Orca is coming. Climeworks recently announced that it will work with the company Puro.Earth to certify every ton of CO2 that it removes from the atmosphere and stores underground, in order to sell carbon credits based on this service. The credits will be listed on a public registry.
But even if Orca eventually runs at full capacity, Climeworks will never be able to sell 4,000 carbon credits per year from the plant. Gosalvez clarified that 4,000 tons is the amount of carbon the plant is designed to suck up annually, but the more important number is the amount of “net” carbon removal it can produce. “That might be the first bit of education you need to get out there,” she said, “because it really invites everyone to look at what are the key drivers to be paid attention to.”
She walked me through a chart that illustrated the various ways in which some of Orca’s potential to remove carbon can be lost. First, there’s the question of availability — how often does the plant have to shut down due to maintenance or power shortages? Climeworks aims to limit those losses to 10%. Next, there’s the recovery stage, where the CO2 is separated from the sorbent, purified, and liquified. Gosalvez said it’s basically impossible to do this without losing some CO2. At best, the company hopes to limit that to 5%.
Finally, the company also takes into account “gray emissions,” or the carbon footprint associated with the business, like the materials, the construction, and the eventual decommissioning of the plant and restoration of the site to its former state. If one of Climeworks’ plants ever uses energy from fossil fuels (which the company has said it does not plan to do) it would incorporate any emissions from that energy. Climeworks aims to limit gray emissions to 15%.
In the end, Orca’s net annual carbon removal capacity — the amount Climeworks can sell to customers — is really closer to 3,000 tons. Gosalvez hopes other carbon removal companies adopt the same approach. “Ultimately what counts is your net impact on the planet and the atmosphere,” she said.
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Despite being a first-of-its-kind demonstration plant — and an active research site — Orca is also a commercial project. In fact, Gosalvez told me that Orca’s entire estimated capacity for carbon removal, over the 12 years that the plant is expected to run, sold out shortly after it began operating. The company is now selling carbon removal services from its yet-to-be-built Mammoth plant.
In January, Climeworks announced that Orca had officially fulfilled orders from Microsoft, Stripe, and Shopify. Those companies have collectively asked Climeworks to remove more than 16,000 tons of carbon, according to the deal-tracking site cdr.fyi, but it’s unclear what portion of that was delivered. The achievement was verified by a third party, but the total amount removed was not made public.
Climeworks has also not disclosed how much it has charged companies per ton of carbon, a metric that will eventually be an important indicator of whether the technology can scale to a climate-relevant level. But it has provided rough estimates of how much it expects each ton of carbon removal to cost as the technology scales — expectations which seem to have shifted after two years of operating Orca.
In 2021, Climeworks co-founder Jan Wurzbacher said the company aimed to get the cost down to $200 to $300 per ton removed by the end of the decade, with steeper declines in subsequent years. But at the summit in June, he presented a new cost curve chart showing that the price was currently more than $1,000, and that by the end of the decade, it would fall to somewhere between $400 to $700. The range was so large because the cost of labor, energy, and storing the CO2 varied widely by location, he said. The company aims to get the price down to $100 to $300 per ton by 2050, when the technology has significantly matured.
Critics of carbon removal technologies often point to the vast sums flowing into direct air capture tech like Orca, which are unlikely to make a meaningful difference in climate change for decades to come. During a time when worsening disasters make action feel increasingly urgent, many are skeptical of the value of investing limited funds and political energy into these future solutions. Carbon removal won’t make much of a difference if the world doesn’t deploy the tools already available to reduce emissions as rapidly as possible — and there’s certainly not enough money or effort going into that yet.
But we’ll never have the option to fully halt climate change, let alone begin reversing it, if we don’t develop solutions like Orca. In September, the International Energy Agency released an update to its seminal net-zero report. The new analysis said that in the last two years, the world had, in fact, made significant progress on innovation. Now, some 65% of emission reductions after 2030 could be accounted for with technologies that had reached market uptake. It even included a line about the launch of Orca, noting that Climeworks’ direct air capture technology had moved from the prototype to the demonstration stage.
But it cautioned that DAC needs “to be scaled up dramatically to play the role envisaged,” in the net zero scenario. Climeworks’ experience with Orca offers a glimpse of how much work is yet to be done.
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A new dashboard from the Sustainable AI Group, founded by artificial intelligence alums, estimates the relative energy intensity of proprietary tools.
The rise of artificial intelligence is driving an historic surge in electricity demand that’s boosting fossil fuel use and threatening climate progress. All this electricity doesn’t power AI in some generalized, always-on way, though. Data centers’ energy consumption is a function of the millions of individual queries users submit to AI programs such as Claude and ChatGPT.
When it comes to how efficiently models process those queries and generate responses, AI models are not interchangeable. Some are more like gas guzzlers, others more like Priuses. When a user engages an AI chatbot or AI agent, however, there’s essentially no way for them to know which kind of vehicle they are stepping into. They may know which company built it, and even the precise model name and number, but no AI company has published information about how much energy one model uses compared to another.
In the absence of corporate disclosure from the big three proprietary AI developers — Anthropic, OpenAI, and Google — researchers with the Sustainable AI Group, a research and advisory company, developed a backdoor method to estimate and compare the amount of energy these developers’ models consume. They published their findings on Tuesday in an interactive dashboard that ranks AI programs by energy intensity.
“We think this is an important next step to get some science-based information out there to help folks start making better decisions,” Boris Gamazaychikov, the CEO of the Sustainable AI Group, told me. “We also hope that if the model providers think that this is really wrong, that they can come out and prove it with some actual data.”
In general, the researchers found that larger, higher-capability models, such as Anthropic’s Opus and OpenAI’s Sol, used nearly four times as much energy on average as smaller, nimbler models from those companies, Haiku and Terra. Newer iterations of each model also weren’t necessarily more efficient than their predecessors.
While the group has yet to evaluate the latest models that hit the market during the research period, so far the researchers found that for the same task, the least efficient models can consume more than 30 times the energy of the most efficient models. They also found a significant difference between “chat” sessions, where a user asks an AI chatbot a question, and “agentic” sessions,” where a user asks the AI to perform a series of tasks. A typical agentic session used 27 times more energy, on average, than a typical chat session conducted using the same AI model.
The Sustainable AI Group was founded by Sasha Luccioni, the former AI and climate lead at the open source AI platform Hugging Face, and Gamazaychikov, who previously led AI sustainability at Salesforce. In their earlier roles, the two collaborated on a project called AI Energy Score, which is similar in spirit to the Environmental Protection Agency’s EnergyStar program for home appliances. They developed a method to directly measure the energy efficiency of “open-weight” AI models, or those that fully disclose their inner workings, and published the results in a public leaderboard.
Luccioni and Gamazaychikov founded the Sustainable AI Group because they wanted to give AI users, particularly large corporate users, the tools to understand the relative emissions impacts of proprietary AI models. Gamazaychikov told me that Salesforce had tried to get energy-use data from its AI providers for years to no avail.
Their first hire was Nidhal Jegham, a graduate student at the University of Rhode Island who published a landmark paper last year called “How Hungry is AI?” Jegham and his co-authors developed a method to estimate the energy, water, and carbon effects of proprietary models at the level of a single prompt or query. The paper was accepted by the journal Communications of the Association for Computing Machinery, and the peer-reviewed version will come out in January.
The approach the Sustainable AI Group developed builds on both Jegham’s paper and the AI Energy Score project. The work began with testing open-weight models to see how they perform in realistic deployment configurations and directly measuring their energy consumption. From there the researchers identified mathematical relationships between various open models’ energy use and other measurable statistics, such as their size.
The next step was to take those statistical relationships from the open-weight models and apply them to similarly-sized proprietary models. The problem is, no one knows how “big” proprietary models are. The size of an AI model usually refers to the number of parameters it contains, i.e. the quantity of numerical representations of what the model has learned that it uses to produce a response.
“When we have a closed model, we don't have the model size. We don't have the deployment conditions. We don't have anything, so we need to find things we can observe from this closed model that can reflect its size,” Jegham explained to me. One key discovery, he said, was that “knowledge retention,” or how well the model can remember factual information, is a strong predictor of model size. A company called Artificial Analysis tests models for knowledge retention, so the researchers compared those results to model size for open models and applied the same statistical relationship to estimate the size of closed models.
This is a simplified explanation — there were many other variables and data points that went into the Sustainable AI Group’s estimates. The researchers also had to develop a separate methodology to evaluate Google’s models, since those mostly run on the company’s proprietary “tensor processing units,” rather than the Nvidia chips the researchers’ initial measurements were based on.
The group’s main findings are based on a per-token estimate of each model’s energy use, i.e. the energy required to process the smallest units of data that an AI deals with. Every time you type a question into a chatbot, the model breaks down the words into smaller bits — i.e. tokens — each just a few characters long, usually. The model also first formulates its response in tokens before translating it to text, an image, or whatever you’re requesting; input tokens are less energy-intensive than the tokens the models spit out. The Sustainable AI Group reports each of its per-token estimates as a range to reflect uncertainty.
For now, the firm is keeping its per-token estimates behind a paywall, but it has already started to use them to advise corporate clients in estimating their AI-related emissions, Gamazaychikov said. For example, he mentioned working with Etsy to help the online retailer develop a “model router,” essentially some software that routes a given query to the most appropriate model for the task, taking into account carbon and cost. It’s also partnering with the corporate emissions accounting platform Watershed to explore how to integrate its model-specific energy numbers into Watershed’s system.
Instead of displaying per-token energy use, the Sustainable AI Group’s public dashboard ranks models’ energy intensity per “typical” session, whether chat or agentic. It defines a typical chat session as “a short back-and-forth” with “a question, an answer, and a follow-up or two to refine or clarify it,” whereas a typical agentic session is “an hour or two of the assistant reading files, making changes and checking its own work across a project.” There are also results for a “heavier” or “lighter” session — generally tasks that take more or less time or require greater or fewer back-and-forths with the AI.
The least efficient AI model for both a typical chat and agentic session, per the dashboard, is Anthropic’s Claude Fable 5. A typical agentic session uses 76 watt-hours, according to the Sustainable AI Group’s estimate, or about the amount of electricity it would take to charge four smartphones, per Department of Energy estimates. The most efficient model for a typical chat session was Claude Haiku 4.5, while the most efficient model for a typical agentic session was Open AI’s GPT-5 nano.
Jegham said the point of the dashboard is not to villainize particular companies or models or to argue that more efficient models are superior. He acknowledged that a more complex task may require a larger model, and a larger model is likely going to be more energy intensive than a smaller one.
The ranking is also flawed in that it assumes every model delivers responses with the same amount of verbosity. In reality, some models may use more words, and therefore more tokens, to answer the same question. Jegham gave the example of Anthropic’s Sonnet and Opus models: Sonnet is less energy intensive per token, but it typically requires more tokens for the same task, so sometimes it’s more energy intensive than Opus. The dashboard doesn’t reflect these differences.
While energy intensity is the core of the dashboard’s function, it also includes estimates of each model’s carbon emissions per session. That calculation opens up many more cans of worms, since actual emissions depend on where in the country the hardware that’s processing the AI session is located and what’s powering it. There’s no easy way to know which data center is processing a given AI request. Instead, the dashboard offers users the option to toggle between different emissions intensities to reflect different scenarios — a data center powered by behind-the-meter natural gas plants, for example, versus one located on a relatively clean grid.
A typical agentic session with Claude Fable 5 powered by a behind-the-meter gas plant emits roughly 52 grams of CO2, it says, while a heavy session emits just over 200 grams — equivalent to driving about half a mile in a gasoline-powered vehicle.
I reached out to OpenAI and Anthropic to ask why they don’t publish energy intensity data, whether there are barriers to doing so, and whether they have plans to do so in the future. A spokesperson from OpenAI told me the company relies “on infrastructure partners to operate the data centers that run our models, so we don’t directly collect the underlying energy data. That’s an important consideration in how we assess and provide this information.” Anthropic declined to comment.
Google, on the other hand, has published an energy use estimate for “the median Gemini Apps text prompt in May 2025,” but has not provided an update for subsequent model versions. In response to my request for comment, the company reiterated statements from Cooper Elsworth, a senior technical manager for AI energy, which Google shared with me for a previous story on Watershed’s efforts to calculate AI-related emissions. He said there is no industry consensus for how to measure and disclose the environmental footprint of frontier AI models. He also echoed OpenAI’s comments, noting that gathering accurate energy use data requires “highly advanced measurement infrastructure,” which not all AI providers have access to.
“We believe there is immense value in aligning the industry on comparable metrics to fairly compare and incentivize action,” he said.
Current conditions: Last weekend’s nor’easter caused up to $13 billion in damages across the Mid-Atlantic and Northeast regions of the United States • Hurricane Nolo shut down a major highway on Hawaii’s Big Island • A heat dome forming over eastern Africa is driving temperatures in Juba, the impoverished capital of South Sudan, past 100 degrees Fahrenheit.
At last, right after hopes dimmed, we have a deal. Senate negotiators reached a bipartisan agreement on a package of federal permitting reforms, locking in what Politico described as “the contours of long-sought legislation to speed up approvals for new energy projects in the U.S.” Democratic negotiators Senators Martin Heinrich of New Mexico and Sheldon Whitehouse of Rhode Island told the news outlet they were withholding endorsements of a final deal as “the last five yards” of the agreement are hammered out. Whitehouse cautioned that he needed “more clarity from the Trump administration” on what their easing of the blockade on wind and solar approvals would mean. Neither Democrats nor Republicans released text of the bill, which both parties said should come out this week.
The Nuclear Regulatory Commission is set to issue only its second construction permit for a novel type of nuclear reactor in decades. At 11 a.m. EDT, the agency is scheduled to give the Tennessee Valley Authority the go ahead to begin building what could be the nation’s first commercial small modular reactor, a 300-megawatt unit at the federally-owned utility’s Clinch River site. The project is one of two the Department of Energy is financing to support deployment of third-generation SMRs, a technology based on existing large-scale reactors but shrunken down to force developers to buy more and help the industry bring down the cost of atomic power through repeatedly building the same design. (The second one is Holtec’s expansion of the Palisades nuclear plant in Michigan.) The permit comes six months after the NRC gave TerraPower, the Bill Gates-backed fourth-generation nuclear developer, the green light to start constructing its liquid sodium-cooled reactor at the site of an old coal plant in Kemmerer, Wyoming. The unit planned at Clinch River is a BWRX-300, a boiling water reactor from GE Vernova Hitachi Nuclear Energy that borrows from the technology behind roughly a third of the American nuclear fleet. Boiling water reactors, pioneered by General Electric in the mid-20th century, traditionally represented a competitor to the more dominant pressurized water reactor invented by Westinghouse. By the time Clinch River comes online, North America may already have its first BWRX-300 in operation in Canada, where Ontario Power Generation is building the first reactor at its Darlington plant. TVA has said it plans to bring its debut BWRX-300 online by the end of 2033 at the latest. Yet, despite the forthcoming permit, no start date for construction has been announced.
The NRC, meanwhile, has sought to advance plans to restart the functional reactor at Constellation Energy’s Christopher Crane Clean Energy Center, the facility formerly known as Three Mile Island. Last week, the agency issued an environmental assessment finding no significant impact from plans to begin generating electricity at the plant again. While America’s attempt at restarting a permanently shuttered reactor for the first time are largely going according to plan, regulators are investigating what the Detroit Free-Press described as a “mishap” in the handling of fuel for Holtec’s Palisades nuclear plant in Michigan, which could come online in a matter of weeks. The company said nuclear fuel rods “tipped” during installation, halting the refueling process and forcing plant operators to return to the NRC for approval to retrieve the assembly from within the reactor vessel.
Arevia Power marketed itself as a renewable energy powerhouse led by solar industry veterans. Now, my colleague Jael Holzman reported yesterday, the company is making data centers and gas turbines central to its business. “Arevia is an energy company that delivers reliable and affordable electricity to the communities and utilities we serve,” Ricardo Graf, the company’s chief development officer, told her via email, acknowledging that “in some cases, that energy may be solar; in others, it may be gas.” He added that “yes, we also develop data center projects, but ones with accompanying power solutions to ensure ratepayers are not impacted by the data center’s energy needs.”
The shift in focus comes right as American solar offers a major new business opportunity. Solar panels are aging, and newer technologies are as much as 70% more efficient than those designed and built two decades ago. “All across the United States, solar panels are withering on the vine. Equipment installed 10 to 15 years ago is still capturing sunlight and pumping out electricity, but significantly less of it than when the cells were new,” my colleague Emily Pontecorvo wrote yesterday about a new report examining the potential to swap out the country’s existing panels for new ones. “This is not a story about decline, however, but about growth. America’s aging solar farms represent an opportunity to expand clean energy capacity without using more land — and potentially without having to wait years for new projects to get through the grid’s interconnection queue.”
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The TVA isn’t the only government-owned utility making progress on clean power plants. The New York Power Authority — the state electrical company that then-Governor Franklin Delano Roosevelt established in the 1930s and later used as a model for New Deal investments such as the TVA — said Monday that it will take a 51% stake in a 240-megawatt solar plant in the state’s rural northern reaches, according to the Watertown Daily Times. The Rich Road solar farm in Canton, near the Canadian border, will follow a model promoted by progressive legislators with a bill meant to encourage the state to finance and own renewable projects to speed up decarbonization of the grid. Governor Kathy Hochul, a Democrat, has used that authority to support her plans to build at least 1 gigawatt of new nuclear power through NYPA. (That effort, as I told you yesterday, has drawn some blowback from left-wing Democrats who oppose nuclear energy.) EDF Power Solutions North America, a subsidiary of the French electrical giant, will own the other 49% share of the project, which is set to begin construction next year. Once completed, the facility is expected to provide credits to low-income New Yorkers to lower bills.

When I used to think about the Rhine River, the first thing that came to mind was a song off my favorite album from high school. Written and performed by Beirut, the stage name of an American guy who galavanted around Europe making folksy songs that sounded straight out of an American teenager’s romantic notion of an Old World beer hall, the song was called “Rhineland.” Over mournful horns and a plunky mandolin, the song repeats a refrain: “Life, life was all right on the Rhine,” bringing to mind some kind of bucolic interwar existence in an ill-fated era of European history. Two decades later, I can’t tell which has changed more, me or the place I was imagining. The correct answer is probably “both,” but the clearest answer today is the latter. Levels at a key gauge of the mostly German waterway dropped to 1.2 inches below the threshold ship operators use to determine how much cargo their vessel can safely carry down the river without risking damage or running aground, Bloomberg reported. Despite a slight recovery on Monday, the cost of shipping diesel from Rotterdam to Karlsruhe hit a record €260 per ton (equal to just under $296), after more than doubling this month amid the aftershocks of the summer’s record heat waves and droughts.
The latest trouble comes as the Trump administration weighs the merits of a ban on diesel exports. At Heatmap’s Climate Week event last Wednesday, Secretary of Energy Chris Wright ruled out such a step. But Trump said he was “very seriously” considering the step, despite warnings from Goldman Sachs that doing so would raise prices in Europe.
TotalEnergies may be taking up President Donald Trump on his legally sketchy offer of nearly $1 billion to abandon its offshore wind ambitions in the U.S. But the French energy giant — the second-largest European oil company after Shell — sees the energy shock brought on by the U.S. war against Iran as a boon to that very business. CEO Patrick Pouyanne said “high oil prices” are “accelerating electrification,” according to a snippet shared on X by Bloomberg columnist Javier Blas. “We have seen a huge surge in EV sales,” he added, noting that sales are booming well beyond China, in India, Latin America, and Europe. Increased profits from higher crude prices spurred the company to start buying back roughly $5 billion in shares over the next two quarters.
By neutering the Corporate Average Fuel Economy standards, the Trump administration cements the country’s dependence on oil and liquid fuels.
This is Heatmap Daily, a weekday news digest written by our executive editor.
President Trump’s big fuel efficiency rollback is here. This afternoon, the Department of Transportation significantly weakened the Corporate Average Fuel Economy standards, the federal government’s rules that encourage new cars and trucks to get gradually more fuel-efficient over time. Instead of mandating that new cars and trucks hit a target of more than 50 miles per gallon, as the old Biden-era rules had required, new vehicles sold in the U.S. will now need to average only 34.9 miles per gallon.
That target is below the level that most automakers have already achieved in their vehicle fleet. (For reasons too obscure to recount here, the regulatory standard of 34 miles per gallon aligns to real-world gas mileage in the mid-to-high 20s — something my 15-year-old hatchback manages to achieve without much straining.) The new rules also retroactively rewrite the standard back to 2022, meaning that automakers whose fleets once broke the law may now be in the clear.
These changes, in other words, render the fuel economy law, first enacted in 1975, is now moot. But Republicans in Congress had arguably already achieved this last year, when they zeroed out all of the law’s fines for automakers as part of the president’s tax and spending bill. These two changes, taken together, mean that the Trump administration has successfully neutered the U.S. fuel efficiency rules.
We are digging into the rule-making here at Heatmap, and I hope to have more on the documents in the days to come. But one of the lasting ironies of President Trump’s approach to fuel efficiency will be that his own presidency demonstrates its strategic inadequacy.
The Corporate Average Fuel Economy law, after all, did not originate as an environmental policy — climate change had scarcely emerged as a pressing issue in the mid-1970s — but as a national security and economic sovereignty measure. In the aftermath of the oil embargo, American politicians realized that the U.S. economy was far too dependent on oil for its long-term good. This set off a scramble to find new energy sources, prompting a dash back to coal in the electricity sector and a surge in federal R&D spending on alternative energy. (This funding boost eventually created the modern solar, wind, battery, and fracking industries.)
It also led to a successful push to regulate gas mileage. Crucially, this effort did not limit emissions from any one type of vehicle, as the Environmental Protection Administration’s toxic air pollution rules aim to do. Rather, it targeted the average fuel efficiency of cars and light-duty trucks sold in the United States in each model-year. The point was not to regulate any one type of vehicle out of existence, but to increase the country’s overall fuel efficiency over time.
That decades-long effort was never perfect. It created in American statute, for instance, a lasting distinction between cars and trucks, which has bedeviled regulators as SUVs have taken up a larger portion of the new vehicle fleet. But it has also inarguably succeeded: The United States ekes far more value out of every barrel of oil today than it did half a century ago.
Yet the time is ripe to keep making progress. President Trump’s administration has illustrated the persistence of our oil dependence — and the political and strategic problems that it can still engender. Even though the United States has since become the world’s largest producer of oil, the linked and globalized nature of fuel markets means that a supply shock anywhere leads to price hikes everywhere. When an oil crisis arrives — even a largely self-inflicted one, as in the case of the Iran war — then the price of moving things and people rises, the economy suffers, and the president’s popularity falls. Countries can protect themselves from these shocks on a short-term basis by stockpiling oil (as the United States, in fact, does), but they can avoid them only by switching to a far more efficient and electrified transportation system.
President Trump, in other words, may regret the current oil and refining crisis. But by gutting the fuel economy standards — and waging war on electric vehicle incentives more broadly — he is increasing the likelihood that America will face many more crises like it in future years. Consider it his particular gift to his successors.