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“I was a little bit bearish on Tesla for this quarter — and I should’ve been darker.”

The electric vehicle market is anyone’s game.
That’s the takeaway from this year’s first tranche of EV sales data, which saw the two global market leaders — Tesla and BYD — turn in dismal sales for the first three months of the year. Those were in contrast to other automakers including Rivian, Hyundai, and Toyota, all of which reported healthier numbers.
Tesla’s deliveries, which Wall Street uses as a decent proxy for sales, came up well short of analysts’ expectations at 386,810 vehicles for the quarter — down about 9% from the first quarter of 2023. Analysts have consistently cut their estimates for this quarter’s deliveries over the past few weeks, but even so, the real numbers came in well below even the lowest expectations.
“I was a little bit bearish on Tesla for this quarter — and I should’ve been darker,” Corey Cantor, an EV analyst for BloombergNEF, a new-energy research firm, told me.
But despite those meager results, Tesla edged out BYD on sales for the quarter. The Chinese EV giant — whose new $9,000 Seagull hatchback has stunned Western automakers and triggered protectionist impulses around the world — reported far less stunning sales data. BYD sold 300,114 vehicles in the first three months of 2024, down 42% compared to a year before.
That means Tesla is once again the world’s No. 1 seller of electric vehicles, after ceding that title to BYD last year. But little else is going right for Elon Musk’s car company.
Tesla has an aging vehicle line-up, and its newest North American offering, the Cybertruck, has not impressed reviewers. By its own admission, the company is struggling to scale up the Cybertruck’s production as well.
Perhaps most worrying for Musk is that Tesla produced almost 47,000 more vehicles during the first quarter than it sold, suggesting that it is beginning to hit real limits on customer demand for its cars.
“There must be some kind of supply-demand imbalance here,” Cantor said. Tesla has slashed its vehicle prices by thousands of dollars over the past year in order to stimulate demand. Tesla doesn’t break out its sales data by region, which is a shame because that could help clarify what is going on. If Tesla’s sales are flagging in China and Europe, that could be because consumers are flocking to a new set of EV options. A sales decline in the U.S. would indicate that one of the company’s cash cows, the Model Y crossover, is beginning to falter.
“If you look at this, you can see where there are yellow flags here,” Cantor said. “Tesla can explain it however you want but the numbers speak for themselves. Anytime you’re down 9% year on year is a challenge.”
It’s harder to know how to read BYD’s fillip. Other Chinese automakers reported surging March sales. Xiaomi, a Chinese phone maker, has reported almost 90,000 preorders for its first-ever electric car, the SU7. Cantor speculated that the hiccup may be due to Lunar New Year, which tends to depress sales in January and February.
Elsewhere in the car market, other EV makers did better — although few reported surging sales. One exception was Hyundai, which reported EV sales up more than 60% from the first quarter of 2023.
General Motors’ electric vehicle sales fell 20.5% compared to the first quarter of 2023, even as the company’s overall sales of personal-use vehicles rose slightly. It reported higher sales for the Lyriq, its EV SUV, Cantor said.
Toyota says that it sold 206,850 “electrified” cars across North America in the first quarter, a gain of 74% over the year before. “Electrified,” however, is a Toyota term of art — it includes conventional hybrids, plug-in hybrids, and hydrogen fuel cell vehicles. About a third of Toyota’s North American sales now fall in this category.
The electric truck maker Rivian modestly surpassed expectations, beating both analysts’ and its own estimates with 13,588 deliveries in the first few months of 2024. While its total production of 13,980 vehicles for the quarter came in marginally below predictions, Rivian reaffirmed its earlier estimates for full-year production.
Even so, by late afternoon, Rivian’s stock was down 5% for the day. That might be partially explained by the planned weeks-long shutdown of its factory in Normal, Illinois, scheduled to begin at the end of this week. While the pause will allow for renovations designed to reduce costs and increase efficiency, it will also mean that next quarter is guaranteed to be a “wash” for Rivian, Cantor said.
As of last quarter, Rivian was losing about $43,000 on every vehicle it produced. Whether it can stem those losses and get on the “bridge to profitability” executives say is within sight remains, apparently, an open question for shareholders. Rivian is now focused on surviving long enough to sell the R2 SUV. “Every single thing we do within the business is focused on driving costs on this,” RJ Scaringe, Rivian’s CEO, told CNBC last month.
Tesla's and BYD’s flagging sales may also be signaling to investors that a general EV slowdown is coming. And then, of course, there's the general malaise that descended over the EV industry in 2023 as the big legacy American automakers reported sluggish sales for their splashy new electric models and planned to scale back production in the coming year. Though the data don’t present as clear a picture as the doomers might suggest, it is undeniable that, as Princeton energy systems professor and Shift Key podcast co-host Jesse Jenkins wrote for Heatmap, “the vibes are bad.”
“The narrative now will be harsh on Tesla and BYD,” Cantor said. “But if you’re another automaker, you should see this as an opportunity. We’re in the early stages here. None of this is written.”
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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.