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If you care about climate change, this is a no-brainer.

Back in 2019, the year I bought my Tesla Model 3, Elon Musk was more nuisance than accused neo-Nazi. He released an offbeat autotuned rap song about Harambe the gorilla and was acquitted of defamation charges after calling a rescuer in the Thailand cave incident of being a “pedo guy.” Both events feel eons ago in internet time. They also feel ancient as part of the gradual progression of Tesla’s CEO from real-life Tony Stark to right-wing agitator and propagandist.
Lots of people who purchased Tesla EVs before Musk took off the mask are understandably miffed. Anyone who buys a Cybertruck and has been on the internet before should know they’re driving an extension of Elon’s id. But millions of people worldwide bought Teslas over the past several years with no intention of puttering around in a MAGA machine. The sentiment can be seen in the bumper stickers that now appear on Model 3s and Ys around blue states, declaring some version of “I bought it before Elon was crazy.” A new study in the Netherlands put a number to the notion: The survey found that one in three Tesla owners wants to unload their cars rather than continue to drive a vehicle associated with Musk.
This is a time when social media abounds with lists of companies to avoid because of their political stances and contributions; anyone who wants to vote with their wallet by not buying Tesla absolutely can and probably should buy some other carmaker’s EV instead (unless Tesla, which is slated to release its earning this week, winds up the last EV-maker standing). But don’t ditch your Model S or Y just to avoid driving around in an advertisement for his company.
I’ve thought a lot about this as a Model 3 owner for five-plus years. It’s not uncommon to meet someone who can’t wait to tell you they’d never buy a Tesla because of Musk’s politics or noxious behavior on X. Fair enough. But plenty of those people drive gas-only or hybrid vehicles. The oil company CEOs who make money selling gasoline and diesel have been far worse for the climate than Musk, even if his Trump-ward turn is closing the gap. They just know enough not to tweet. Or buy Twitter.
It certainly doesn’t make climate sense to dispose of a Tesla in favor of a non-EV. But even trading one in for another company’s EV just to get Musk out of your life is a bad deal. When you sell your car, it becomes somebody else’s car. That person inherits the symbolic weight of owning one of Musk’s products and takes over the Supercharging dole, paying Tesla for energy every time they need to charge away from home. More importantly, you’ll probably wind up purchasing a new EV that needed a reasonable amount of carbon emissions to create (not to mention water and other resources), and will need years of driving on cleaner energy to make up for it. What’s gained in virtue signaling is lost in carbon dioxide.
This personal conundrum is reminiscent of the macroeconomic controversy over fossil fuel divestment, where universities, companies, and other institutions have been pressured to rid themselves of investment that support coal, oil, and gas. In theory, selling off such assets is supposed to harm the fossil fuel industry. But as the Harvard Business Review writes: “What looks good on paper often falls short in practice. There’s one major problem with divestment: Selling an asset requires someone to buy it. In other words, for you to divest, someone else needs to invest.” Institutions get to pat themselves on the back and tell constituents they greened their portfolio, but the fossil fuel business carries on unchanged.
In fact, the Review directly compares divestment to the car problem. Companies, they say, should think about sunsetting their fossil fuel investments rather than selling immediately just to wash their hands of a dirty industry. It’s just like how driving an old car into the ground is better than selling it — since selling requires buying, and buying adds a new car to the roads.
So it goes for aging Teslas. You might feel a wave of satisfaction by selling off your Model Y and derive great pleasure from not having to think about Musk when you get in your car. But if, like me, you bought an electric car for climate reasons, and it just so happened that a Tesla was the most practical one you could get, then the best thing to do once it’s paid off is to keep it as long as it will run.
An owner can keep more of their money from lining Musk’s pocket by charging at home or at other companies’ DC fast-chargers instead of Superchargers, or by having the vehicle repaired and serviced by independent shops rather than by Tesla itself. But it is quite literally not worth it to sell your Tesla just to avoid having to explain to other people, or to yourself, why you drive one.
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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.