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This was the year of the fire sale. With the $7,500 federal electric vehicle tax credit expiring at the end of September, buyers raced to get good deals on EVs and made sales numbers shoot up. Then, predictably, sales fell off a cliff at the end of the year, when those offers-you-can’t-refuse disappeared.
Now that a new year has arrived, the word might be “uncertain.” Tariffs and the loss of federal incentives have tossed a heavy dose of chaos into the EV industry, causing many automakers to reconsider their plans for what electric cars they’re going to build and where they’re going to make them. And yet, at the same time, some of the most anticipated new electric models we’ve seen in years are supposed to be coming to America next year. Here’s what to know.
Just as changes in federal policy threaten to make electric cars more expensive — at a moment when Americans are clearly tiring of out-of-control car prices — here comes a new batch of long-overdue affordable EVs. Among the most important is the Chevy Bolt, a fan favorite from the previous generation of electric vehicles that ended its first run in 2023. With the basic version starting at $29,000 for a car with 250-plus miles of range, the little Chevy might inspire a new legion of fans — perhaps one large enough to convince General Motors to extend what they’re calling a limited Bolt resurrection into a car that’s on sale for good.
The Nissan Leaf, another name from a bygone era, is also coming back to the States. The Leaf, you may recall, was arguably the car that started this electric era, hitting the market ahead of the much-more-beloved Tesla Model S. The second version of the Leaf that came out in the mid-2010s was a pretty darn good hatchback, but one that lasted too long without an update and paled in comparison to the better models that came along this decade. Nissan as a company has been adrift the past several years, but it built a winner in the new Leaf 3.0, an attractive small crossover set to arrive in 2026.
Next year also should see heel-draggers Toyota and Subaru finally coming to market with winning EVs. The uninspired Toyota bZ4x/Subaru Solterra, which the two Japanese brands developed together, had been their only pure EVs. In 2026, however, Subaru is set to launch the Outback EV and Toyota the electrified version of the C-HR small crossover, putting all-electric power into some of their well-known gasoline nameplates.
Battery-powered adventure vehicles make up some of the most exciting EVs for 2026. Perhaps the most-anticipated arrival is the Rivian R2, poised to be not only the model that brings that brand to the masses, with its $45,000 starting price, but also serve as the launchpad for Rivan’s aspirations in autonomous driving and AI. It’ll face new competition in the form of the Jeep Recon, that iconic brand’s first all-electric SUV, and of the Range Rover Electric, which seeks to win back some of the drivers who ditched their Range Rovers for the Rivian R1.
The electric pickup market, by comparison, has gone cold. Rivian, which launched its all-electric company with a pickup trick, isn’t planning a truck version for the smaller R2 platform. Ford, amidst yet another upheaval in its EV plans, is killing the all-electric version of the F-150 Lightning and plans to produce a 700-mile extended range hybrid in its place (though it says plans for the mid-sized EV truck due in 2027 will go on).
The great truck hope for EVs in 2026 is the much-awaited launch of Slate, the truly compact electric truck backed by Jeff Bezos, among others. Slate’s pitch is affordability via personalization: The bare-bones, doesn’t-even-have-power-windows version is supposed to start in the mid-$20,000s, on par with the cheapest new gasoline cars you can buy in America. Buyers can spend as much as they want to add bells and whistles.
Of the new high-end EVs coming to America, the most compelling may be the BMW i3. The last car to bear that name was the little urban future cube the German automaker sold in decent numbers back in the 2010s, despite that older vehicle having just 150 miles of range. The new i3 is a fully realized electrified version of the best-selling BMW 3 Series, one of the icons of the auto industry.
Despite the arrival of new and affordable EVs, the industry still has a big affordability problem. Too many electric cars are still too expensive and not competitive price-wise with their gasoline counterparts. Meanwhile, Americans are getting fed up with out-of-control car prices.
A consequence of this, industry insiders say, could be that 2026 is the year of the used EV. Tons of electric cars that were leased under very favorable terms during the Biden years will be coming back to dealerships as those leases end, ready to become very affordable used cars. With batteries having markedly improved since the 2010s, those three-year-old electric cars should have decent driving ranges to go with their low sticker prices.
The other big question mark is the promise of the autonomous age. Tesla, still the EV market leader in America, hasn’t offered an entirely new one since the disastrous launch of the Cybertruck. This year, though, Elon Musk says he will start building Cybercab, the supposedly fully autonomous car that will never be driven by its human occupants. Maybe it will upend the entire automotive industry as drivers say goodbye to the act of driving. Or maybe, like most Tesla endeavors, it will come in behind schedule and not work quite as well as Musk promises.
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The data center boom is everywhere you look in U.S. economic and emissions data.
This is an edition of Heatmap Daily, an evening review of the day’s news written by our executive editor. Sign up for it here.
It isn’t exactly a new thought, but I’ve been struck recently by how many trends in America’s economic and environmental data are fundamentally about the data center boom and the return of electricity demand:
First, the Energy Information Administration reported this week that U.S. emissions grew by more than 2% last year, driven by surging electricity demand and an increase in coal-fired generation.What caused that higher power demand? New factories and data centers — as well as record summertime cooling demand.
Second, many of the new factories driving that higher power demand are themselves producing goods that are … let’s say … data center-adjacent. There are the enormous new semiconductor fabs, of course. But Ford and General Motors have also set up new production lines (or repurposed old ones) to manufacture grid-scale batteries to meet power demand.
Third, take a look at the recent U.S. spending on private non-residential construction — in other words, everything American companies are building that is not houses, condos, or apartments.
The construction industry’s spent almost $60 billion on data centers over the past year, which is more than it spent on all other office buildings combined (and more than it spent building warehouses, too). Just a handful of categories — data centers, power plants, electricity infrastructure, and certain kinds of electronics manufacturing — now make up a third of all U.S. private non-residential construction investment. They’ve never made up such a large share of construction spending since data collection began in 2014.
As The New York Times recently noted, the American economy is unusually dependent on the American stock market right now — and the stock market is unusually dependent on artificial intelligence. This week, investors started to balk at the enormous spending hyperscalers are planning to keep building out the AI boom; Alphabet’s shares dropped 8% this week after it boosted its planned 2026 capital expenditure and signaled 2027 will be even bigger. If the data center boom started to slow down in earnest, then more than just that budget will change.
Speaking of which, my colleague Emily Pontecorvo wrote earlier this week about how many businesses are struggling to even estimate their carbon emissions from artificial intelligence. The carbon accounting startup Watershed recently unveiled a new formula to help companies get a sense of their AI-related emissions.
But even that formula is still limited by the amount of data hyperscalers publish — and they don’t publish that much. Google, for instance, is the only AI company that has (laudably) provided estimates of its emissions on a per-prompt basis. Yet no company has published its per-token emissions, or how emissions sync up with particular models or regions.
So Emily asked Google: Why aren’t you — or any other model provider — disclosing this kind of data yet?
The tech company didn’t get back to us until after we’d published Emily’s story. But its response was interesting enough that I wanted to quote some of it here.
The problem is “industry consensus,” Cooper Elsworth, a Google spokesperson, told us. “There is currently very little consensus on how to comprehensively and fairly measure the serving environmental impact of generative AI (such as text generation),” he wrote. “Without standardized, ‘apples-to-apples’ frameworks, it is difficult to compare different providers accurately.”
That’s partly because energy use — and emissions data — can vary from site to site and depend on “custom-built hardware, software compilers, and advanced inference techniques.” And he claimed Google doesn’t always have the measurement hardware in place to provide such specific estimates: “Providing precise, repeatable data requires highly advanced measurement infrastructure,” he said. “For example, software-based energy monitoring tools often suffer from sampling biases. For our study, we had to step away from top-down averages and directly measure actual energy at the physical power supply unit (PSU) level across our deployed fleet. Not all providers have the telemetry or data sets required to benchmark their operations at this level of granularity.”
Read Emily’s story to understand the other reasons why estimating — or even “guesstimating” — AI-related carbon emissions is so challenging.
A conversation with Emma Uridge of the Kansas Health Institute.
This week’s conversation is with Emma Uridge, analyst with the Kansas Health Institute. Uridge spent copious hours analyzing state and local laws on data center development to best understand how policymakers are responding to the potential environmental public health impacts of large AI infrastructure, including power and water. The report, which came out this week, also goes in depth into those health impacts. I reached out to her to discuss what she sees as must-watch territory for our readers on this emerging policy arena.
Our conversation was lightly edited for clarity.
What is actually being done on policy when it comes to data centers — beyond moratoria of course?
So first I’d like to just talk about the point of moratoria. It’s helpful to talk about how these policies emerge in the first place. One area where moratoria are helpful is when a data center is proposed but the county has no approach for how they’d like to potentially regulate them. That’s temporary, most of the time. It lets local governments conduct research on the various impacts and also negotiate community benefits, ones that can mitigate any potential negative impacts — like Lancaster Pennsylvania, which instituted a community benefit agreement that maximized the potential benefits of development while mitigating what large data centers can do. That agreement looked at capping municipal water use at 20,000 gallons per day and requiring 100% clean energy. It had financial penalties for non-compliance. The company also committed $20 million to their local economic development and clean energy fund. There are ways to negotiate with developers.
We also see amendments to existing zoning. Data center proposals are increasingly popping up in rural areas, many of which are unzoned, so there’s no way a county can negotiate unless there’s a moratorium in place.
Other policy solutions include different performance standards or requiring on-site renewable energy, like what Jefferson County, Missouri, looked at. Also setback requirements, mandatory noise buffers, ending by-right zoning.
Where are local governments getting ideas for regulating data centers?
A lot of the technical information comes from developers. That can in cases be seen as a biased source of information. I wouldn’t say there’s a dedicated group providing assistance to local governments when a project is proposed — which is a similar story to wind industry development, where we have only a handful of consultants who provide technical advice. It can be really helpful to get a multi-disciplinary approach to hearing information. It can be helpful to have the utility commission, public health folks, those in academia, as well as the developer.
As of right now, especially in rural areas, local governments have a hard task of balancing pushback while getting the most accurate, evidence-based, neutral information to make decisions. That balance can be contentious.
What is the federal government doing on data center policy? How is the Trump administration approaching it?
A few things there. In the early days, the drive was for AI expansion and to be competitive with foreign adversaries. Now due to the amount of public pushback in red and blue localities and a more cautious approach.
I’m not seeing a lot of actual policy movement at this time.
I know the EPA is looking at the chemicals used in cooling data centers because when that water is cycled through the system, some of it is discharged into the water system, so they’re looking at the Toxic Substances and Control Act for monitoring that.
How much of an impact does this minimal federal role have on industry behavior?
Y’know, this isn’t specific to data centers. This is true for all kinds of large-scale development: there’s a need to require some sort of federal monitoring and regulation.
That’s where I see an emerging role for public health. At the federal level, there could be policy movement towards requiring some sort of environmental monitoring at data centers to make sure they’re operating responsibility. Looking at specific water use relative to water availability and what happens when there’s a time of severe, persistent drought. With air quality too — we’ve seen areas where the grid isn’t as reliable so their diesel generators are kicking on more and affecting air quality for residents.
We’re just not seeing all of that right now. We need corporate disclosure.
What do you see as the most important public health impacts from data center development?
It varies by localities. The most discussed obviously is water usage. One thing I’d note about my conversations with folks enthusiastic around emerging tech is, there are still questions that need to be asked about the capacity of localities to support a data center. Like a small town in Kansas may only be using 40% of their water for their utility needs. If a data center came online, how much of that water goes to the data center?
One area underexplored within the public health discipline is energy poverty and energy security. The ability of a household to meet the needs of everything energy provides in our lives. It’s known we have an aging electric grid but we’re not talking enough about large-scale blackouts when the grid is not sufficient to support some of these new data centers.
Plus more of the week’s big development fights.
1. Laramie County, Wyoming — Meta is fighting the fine it received in the Cheyenne data center water pollution controversy, and the conflict between the tech giant and the city’s small board of public utilities is continuing to spill out into the public.
2. Niagara County, New York — This county just rejected a solar project’s highway work permits in a show of retaliation against the state’s Office of Renewable Energy Siting.
3. Barron County, Wisconsin — The anti-solar protest is the new campaign stop in deep red Wisconsin.
4. Chesapeake, Virginia — A large battery storage project on the Virginia coastline is on the rocks amidst rampant local opposition.
5. Lewis County, West Virginia — West Virginia is now a key battleground in the fight over transmission, as a line spanning all of West Virginia and Maryland — and cutting through Data Center Alley in Virginia — causes compounding consternation.