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The vibes are shifting yet again.

Stop me if you’ve heard this one already, but the supposed EV sales slump isn’t real. The overall growth rate has slowed somewhat, crushing any fantasy that America would accelerate to mostly electric driving in just a few years. But electric vehicles sales have been steadily rising amid a negative narrative, and they rose yet again in the third quarter of 2024.
Carmakers sold 346,309 of them from July to September, a 5% increase over the second quarter of this year and an 11% jump year-over-year. EVs reached 8.9% of all vehicles sold in America in the third quarter, prompting Cox Automotive (which owns Kelley Blue Book) to opine that 10% looks well within reach.
A look inside the numbers behind the news tells us a few important things about the state of EVs.
A lightning rod on wheels, the Cybertruck became a focal point for the anger and contempt lots of very online people feel toward Elon Musk and his support for Donald Trump. But as I noted a year ago for Heatmap, plenty of people want this car — either out of genuine affection for what it is and what it can do, or for the political statement they can make by owning one.
The numbers don’t lie. Despite a slow start, Tesla sold 16,692 Cybertrucks during the third quarter. That made it the number three EV in America behind Tesla’s Model Y and Model 3. The Cybertruck’s emergence, combined with better sales by a refreshed Model 3, helped to stop a slide at Tesla earlier this year caused by falling sales of the aging Models S, X, and Y.
As Tesla goes, so goes today’s EV market. Its slump in 2024 had hampered the growth of the industry at large; a rumored update to the industry-leading Model Y would be a shot in the arm for everybody. Yet even with Tesla stabilizing, Elon Musk’s dominance isn’t what it once was. The company’s market share, which hovered in the 70% range in 2019 and 2020, has fallen below 50%. With a growing slate of competitors, it may never cross above that threshold again.
Korean brands Hyundai and Kia had been the non-Tesla success story of the past year-plus, with American EV shoppers falling in love with the quirky Hyundai Ioniq 5 in particular. But General Motors seized second place in Q3 as some of its plans finally came to fruition. Chevy sold nearly 8,000 Blazer EVs and almost 10,000 Equinox EVs last quarter. That latter figure is particularly impressive given that the $35,000 base-level Equinox, which could fall below $30,000 after incentives, didn’t hit the market until October. The Cadillac Lyric found a niche. Even the preposterous GMC Hummer EV saw a big sales bump.
GM’s solid numbers don’t include the remarkable success of its partnership with Honda, who borrowed GM’s Ultium platform to build its first American EV, the Prologue. That vehicle sold 12,644 in the third quarter, outpacing GM’s own EV crossovers. (Perhaps the legion of loyal Honda buyers in America were just waiting for the brand to sell them an electric car.)
Chevy and Honda’s success came at the expense of some brands whose electric crossovers aren’t quite so new and exciting anymore. The Ioniq 5 dropped a tiny bit compared to the third quarter of 2023, just 0.5%. However, Ford’s Mustang Mach-E dropped by nearly 10% year over year, while the Volkswagen ID.4 tumbled by 57.8%.
Speaking of Ford, it wasn’t all bad news for GM’s rival. Ford’s EV division did better than Wall Street expected. Overall sales actually rose, with gains from the E-transit van and F-150 Lightning pickup truck balancing out falling numbers from the Mustang Mach-E. Even so, Ford is losing billions of dollars on its electric vehicles. The blue oval brand faces a double challenge: It needs to get a new EV on sale to juice sales while figuring out how to dramatically cut manufacturing costs.
Watch any car commercial and you’ll be reminded that incentives aren’t the sole domain of EVs. Brands and dealerships offer all kinds of rebates and discounts to move gasoline cars off the lot. Yet because of the size of the federal and state tax credits and rebates for buying electric, those incentives retain an outsized impact on sales. Cox points out that incentives made up 12% of the average price of an EV sold in the third quarter of this year, compared to just above 7% for other kinds of cars.
What’s especially dramatic, though, is the incentive-driven rise of the leased EV. Overall, Americans lease just over 20% of their new cars, not far from where the figure stood two years ago. At the end of 2022, less than 10% of Americans who got a new EV leased it. But in December of that year, the federal government announced many EVs that weren’t ineligible for tax credits when purchased outright would be eligible for those incentives if people leased them. Cox’s chart paints a stark picture, showing leases rocketing from about 9% to 43% of EV sales.
In their own EV makeup, that is. There are six car brands that have 10% of their U.S. sales or more from EVs: Mercedes-Benz, BMW, Jaguar, Audi, and Cadillac — luxury brands all — are five of them. (The other is Mini.)
This makes perfect sense, of course. Luxury brands sell fewer vehicles overall, so it’s easier for EVs to make a big dent in sales. They sell expensive cars, which makes it easier for buyers to swallow the higher cost of EVs. Their drivers have always been more likely to lease cars, even before leasing EVs in particular became so appealing.
In sum, it means that the luxury car brands — while selling fewer overall EVs than Chevy and Honda will eventually sell — will be the first to experience what it’s like for a legacy car brand when the scales tip to more EVs than not.
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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.