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Before that can happen, though, we need megawatt chargers.

The electrification of semi trucks started with baby steps. First came EV semis for short-haul routes, those where the vehicle can do all its business on a single charge. We’re talking big rigs that make drayage runs to ferry shipping containers between ports and nearby warehouses, or delivery vans that spend their day puttering around the city.
It makes sense. Semis are huge and heavy; it takes a long time to charge a big enough battery to move one. That first batch of EV trucks could return to base and recharge their batteries overnight, with no rush to get them right back on the road. But for electric semis to make regional runs — and someday national ones — they need fast-charging truck stops that can deploy much more juice than an ordinary passenger EV requires.
That infrastructure is coming. At last week’s ACT Expo in Las Vegas — where trucking and fleet professionals trade notes on how electrification, advanced fuels, and AI — the conversation centered on the rise of megawatt charging, tech that will make it possible for electric trucks to make runs that are viable only for diesel-powered trucks today.
Most EV semi truck charging to date has been done at speeds of up to 350 kilowatts. That’s fast for a passenger vehicle. Hyundai, for example, claims that a car like the Ioniq 5 can go from 10% to 80% charge in around 15 minutes. But a semi’s energy requirements are a different ballgame. At those speeds, a truck needs hours to top off — unacceptable for a trucker on a tight schedule.
The next step, megawatt charging, is a misnomer. Technically, this category includes any charger over 600 kilowatts, though it stretches up to 1.2 megawatts. That is the theoretical maximum of the Tesla Megacharger, the high-speed charger built specifically for the Tesla Semi that has just gone into mass production. The 1.2-megawatt version is promised to fill about 60% of the truck battery in about half an hour (the duration of the mandated break a trucker must take after eight hours on the road). Henry Johnson of Alpitronic, a company building out high-powered charging in Europe, said even just 700 to 800 kilowatts is enough to charge trucks with all the juice they’ll need for the rest of their journey in about 45 minutes.
Indeed, megawatt charging has already taken root in Europe, which is ahead of the United States in EV trucking (one of the ACT panels was titled, “Megawatt Charging in Europe: Lessons for the U.S. Market”). The availability of such speeds will soon accelerate here, though. “Megawatt charging is coming this year,” said Patrick Macdonald-King, CEO of the Daimler-backed group Greenlane that is set to build a network of electric and hydrogen refueling stations for trucks in America. “We’re not building anything without it,” he says.
Greenlane has a flagship station open near San Bernardino, California, including a couple dozen plugs at around 400 kilowatts, but future stations planned to service trucks traveling between L.A. and Phoenix or Dallas and Houston will feature megawatt-speed plugs. Tesla has built Megachargers stations at its factories and opened one specifically for Pepsi, an early adopter client. Its first public megawatt charging station in the Inland Empire, the urban sprawl inland of Los Angeles, opened for business in March.
Part of what makes this leap possible is the plug. Existing EV trucks have used the CCS charging standard, but an increasing number of them are now equipped to work with MCS, the Megawatt Charging Standard, which can reach speeds beyond CCS. The MCS plug is not only fast, it’s also unique to big trucks, which negates current problems such as a semi truck pulling up to a charging station only to find that a CCS-using passenger car is hogging the plug.
The megawatt era could also lead to consolidation that makes it simpler to expand semi charging around the country. There’s a case to be made for both the CCS and MCS plugs to stay in use, with CCS serving the cheaper, slower kind of charging that some need. But just as passenger EVs have now almost universally coalesced around the NACS plug that Tesla invented, the same thing could happen for MCS. Tesla, for example, is offering a 125-kilowatt Basecharger for companies who want Tesla Semis but don’t need the power of a 1.2-megawatt Megacharger, with the less powerful option going for $40,000 rather than $188,000. But it, too, uses only MCS. John Smith, incoming CEO of the spun-off company FedEx Freight, called for as much during his conference keynote. “We need a universal standard,” he said. “Every truck must be able to go to every charger.”
It will be years before there is a nationwide patchwork of megawatt truck stops along all of America’s major highways, the kind that exists now to make it possible to drive nearly anywhere in this country in an electric car. The good thing about trucking, though, is that it’s predictable. You don’t need to build a whole network of chargers anywhere ordinary citizens might want to drive. You only need it where you already know trucks are destined to go.
Providing fast-charging on heavily used freight corridors in California and Texas can allow fleets to electrify those routes — and see a preview of life with the benefits of electrification, such as more predictable maintenance and the freedom from wartime diesel price shocks.
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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.