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With both temperatures and electricity prices rising, many who are using less energy are still paying more, according to data from the Electricity Price Hub.

In 135 years of record-keeping, Tampa, Florida, has never been hotter than it was last July.
Though often humid, the city on the bay is typically breezy, even in summer. But on July 27, it broke 100 degrees Fahrenheit on the thermometer for the first time ever; two days later, it hit its highest-ever heat index, 119 degrees. The family of Hezekiah Walters, the 14-year-old who died of heat stroke during football practice in Tampa in 2019, urged neighbors at a local CPR certification event to take the heat warnings seriously. Local HVAC companies complained about the volume of calls. Area hospitals struggled to keep their rooms and clinics comfortable. Experts later said the record temperatures were made five times more likely by climate change.
But according to data from Heatmap and MIT’s Electricity Price Hub, Tampa Electric customers used 14% less electricity in July 2025 than they did in the same month of 2020, which was Tampa’s previous hottest July on record — about 216 kilowatt-hours per household less, roughly the equivalent of running a central AC a couple hours fewer per day for an entire month. Tellingly, Tampa Electric raised rates over that period by 84%, with the average bill growing from $111 to $190 per month.
Though there are many instances in many places around the country where usage has dropped as rates rose, the correlation doesn’t necessarily mean people were rationing their electricity. Climate-related factors like anomalously cool summers can lower summer bills, while energy efficiency upgrades can also result in changes to residential consumption. Southern California Edison customers, for example, used 24% less electricity in 2025 than they did in 2020, at least in part due to the widespread adoption of rooftop solar.
Thanks to recent efforts by the Energy Information Agency to track energy insecurity and utility disconnections, however, we can start to tease out deficiency from efficiency. By cross-referencing that data with rate and usage statistics from the Electricity Price Hub, we find a handful of places like Tampa, where people have seemingly reduced their electricity usage because they couldn’t afford the added cost, even during a deadly heatwave. (Tampa Electric did not return our request for comment.)
The EIA’s tracking program, known as the Residential Energy Consumption Survey, tells a clear story: Across the country, people are struggling to absorb the rising costs of electricity. In 2020, nearly one in four Americans reported some form of energy insecurity, meaning they were either unable to afford to use heating or cooling equipment, pay their energy bills, or pay for other necessities due to energy costs. By 2024, the most recent data available, that number had risen to a third — and two-thirds of households with incomes under $10,000. In 2024 alone, utilities sent 94.9 million final shutoff notices to residential electricity customers.
Since 2020, 98% of the more than 400 utilities in the Heatmap-MIT dataset have raised their rates — more than half of them by greater than 20%; about one in 10 utilities have raised their rates by 50% or more. And 219 of those utilities raised rates even as usage in their service area fell, meaning that as customers used less, they still paid more.
“I don’t feel like [the rates have] ever been all that affordable, but they have steadily increased more and more and more,” Janelle Ghiorso, a PG&E customer in California who recently filed for bankruptcy due to the debt she incurred from her electricity bills, told me. She added: “When do I get relief? When I’m dead?”
The people hit hardest by rate increases tend to be those already struggling the most. For example, about 30% of Kentucky residents reported going without heat or AC, leaving their homes at unsafe temperatures, or cutting back on food or medicine to pay energy bills, per the EIA’s 2020 RECS report. Since then, Kentucky Power has raised rates in the eastern part of the state by 45%, adding about $64 to the average monthly bill in a service area where the median monthly household income can be less than $4,000.
The Department of Energy’s Low-income Energy Affordability Data, which measures energy affordability patterns, actually obscures some of this burden. It reports that for all of Kentucky, annual electricity costs account for about 2% of the state’s median household income, which is about average for the nation. But in Kentucky Power’s Appalachian service area specifically, many households live under 200% of the poverty level, and $15 of every $100 someone earns might go toward their energy costs, Chris Woolery, the residential energy coordinator at Mountain Association, a nonprofit economic development group that serves the region, told me. “The situation is just dire for many folks,” he said.
Kentucky Power is aware of this; its low-income assistance charge has grown by 110% since 2020, the Heatmap-MIT data shows. Woolery also noted that the utility agreed to voluntary protections against disconnections, such as a 24-hour moratorium during extreme weather, in a rate case settlement with the Kentucky Public Service Commission. The commission rejected the proposal, but the utility kept the protections anyway, Woolery told me.
Customers in other areas are not so lucky.
In states like Oklahoma, where one in three households reported energy insecurity in 2020, rates rose about 30% from 2020 to 2025, according to our data. Per the EIA survey, Oklahoma’s monthly disconnection rate is more than three times the national average. Oklahoma doesn’t have the highest electricity rates in the country — far from it. But median incomes there are low enough that even moderate rate increases leave some with hard choices.
Interestingly, in bottom-income-quartile states, where median household incomes are below $81,337, only about 30% of utilities show a pattern of rising bills and falling electricity usage, which would suggest energy rationing. The other 70% of utilities show the opposite effect: usage is rising despite electricity rates becoming a bigger burden of customers’ incomes. In Kentucky Power’s service area, for example, bills may be up $64 a month, but usage remained essentially flat.
“Think of it this way: The electric company goes to the front of the line,” Mark Wolfe, the executive director of the National Energy Assistance Directors Association, a policy group for administrators of the Low-Income Home Energy Assistance Program, told me of how households triage their bills. If you need to buy something from the grocery store, the drug store, or pay your electricity bill, then “the utility goes to the front of the line because they can shut off your power, which causes lots of other problems.”
Wolfe added, “Plus, if you’re really in dire straits, you can go to the food bank. You can’t go to the ‘other’ utility company.”
Even as resource-strapped households put a higher share of their income toward electricity, they’re also least able to afford energy efficiency upgrades like newer appliances, smart thermostats, or solar panels. The pattern is prevalent in places with extreme climates, such as Louisiana, Mississippi, and Alabama, where turning off the AC in the middle of summer could mean death. It shows up most starkly among the most extreme rate examples in our data set, like the utilities serving remote Alaska villages — despite astronomical electricity prices, usage hasn’t fluctuated much because its customers are already using it as little as they can afford. The elderly and other individuals living on fixed incomes are also often unable to cut their electricity usage beyond what little they’re already using.
In middle-income states like Florida, roughly 60% of the utilities in our dataset show rising bills and falling electricity use — more than twice the rate we see in the lowest-income states. While the poorest Americans have already reduced their electricity use to the bare minimum and are cutting groceries and medicine in order to keep the heat and AC on, in places like Tampa, where the median income is $96,480, the electricity rate shocks have caused even middle- and even high-earning households to start worrying about their bills. According to a new survey released Tuesday by Ipsos and the energy policy nonprofit PowerLines, 74% of respondents with household incomes over $100,000 said they are worried about their utility bills increasing.
“People are seeing their utility bill as one of the few things that changes so much month to month, that is so unpredictable, and that they don’t have any control over,” Charles Hua, the founder and executive director of PowerLines, told me.
Wolfe, the executive director at NEADA, agreed, saying that for the first time, the association has begun hearing from families with incomes above the threshold who need assistance. “An extra $100 a month for a family, but they’re middle class — that shouldn’t push them over the edge,” at least in theory, Wolfe said. But for those with no flexibility in their budgets, anything additional or unpredictable “pushes them close to the edge — from going from middle class to lower middle class — and I think that’s why this affordability crisis is becoming such an issue.”
We can also see this phenomenon in the explosion of line items on utility bills going toward funding assistance programs. Appalachian Power Co.’s low-income surcharge, for instance, is up 3,200% for customers in Virginia; Puget Sound Energy’s low-income program is up 970% for customers in Washington; and PacifiCorp Oregon’s low-income cost-recovery charge, up 879%.
The EIA data, too, bears this out: Florida had one of the highest rates of people reporting they were “unable to use air conditioning equipment” due to costs in the RECS data, and in 2024, there were 186,202 disconnections in the state in July alone — every one of which would have meant people no longer had the power to run their ACs. (FPL and Duke Energy Florida also show usage declines as rates rose, although neither raised rates as much as Tampa.)
The data also shows places where higher-income earners have aggressively pursued efficiency upgrades to lower their usage. In the LA Department of Water and Power service area in California, usage is down more than 11% overall between 2020 and 2025, one of the biggest drops in our dataset. But the lower usage is more evenly distributed month to month, indicating that things like solar adoption and efficiency programs are likely behind the drop, rather than cost pressures. (Rates there still rose more than 28%, or about $15 per month.)
Even doing everything right wasn’t enough to save customers in the end — households that cut their electricity use still saw their bills rise by an average of $20 a month, our data shows.
Perhaps most concerning, though, is the relentless upward trajectory. PowerLines reports that utilities have submitted $9.4 billion in new requests in the first quarter of 2026 alone. Heatmap and MIT’s numbers show that 79% of utilities raised rates in 2025, and 55% have raised them again already this year.
But the advocates I talked to stressed that utilities have more agency than they get credit for. Take Kentucky Power, for example, with its voluntary disconnection protections. “It just shows that you don’t necessarily have to make disconnections to be financially solvent,” Woolery of the Mountain Association pointed out. Or take Ouachita Electric in Arkansas, which passed a 4.5% rate decrease after investing in efficiency upgrades in consumers’ homes through a pay-as-you-save model.
But that’s the rare exception. For most customers, relief is not obviously on the way. Signs increasingly point to the imminent onset of a super El Niño, which could bring punishing, climate-change-intensified heat waves across the United States. The July 2025 record in Tampa will almost certainly not stand; someday, it’ll be the second-hottest summer, or the third. In a few decades, it might even look cool.
And still there will be bills to pay.
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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.