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The decarbonization benefits abound.

Electric vehicles? Really?
Is it really true that Heatmap looked at every way that you can decarbonize your life, meditated upon the politics, did the math, and concluded … that you should buy an EV? Are EVs really that important to fighting climate change?
You’ll find more thorough answers to all those questions throughout Decarbonize Your Life (plus our guide to buying an EV), but the short answer is: Yes. If you really need a car, then switching from a gas car to an electric vehicle (or at least a plug-in hybrid) is the most important step you can take to combat climate change. And it’s not only good for your personal carbon footprint, it’s good for the entire energy system.
Here is why we make that recommendation — and why you should trust us:
The best reason to use an electric vehicle is the most straightforward one: Driving an EV produces fewer greenhouse gases than driving a gasoline- or diesel-burning car. The Department of Energy estimates that the average EV operating in the U.S. produces 2,727 pounds of carbon dioxide pollution each year, while the average gasoline-burning car emits 12,594 pounds of carbon dioxide. Even a conventional hybrid vehicle — like a Toyota Prius — emits 6,800 pounds of CO2, or roughly 2.5 times as much as an EV.
These gains hold almost regardless of how you analyze the question. Even in states where coal makes up a large share of the power grid — such as West Virginia, Wyoming, or Missouri — EVs produce half as much CO2 as gasoline vehicles, according to the DOE. That’s because EVs are much more energy efficient than internal combustion vehicles. So even though coal is a dirtier energy source than gasoline or diesel, EVs need to use far less of it (in the form of electricity) to drive an additional mile.
EVs retain this carbon advantage even when you take into account their full “lifecycle” emissions — the cost of mining minerals, refining them, building a battery, and shipping a vehicle to its final destination. Across the full lifetime of a vehicle, EVs will release 57% to 68% less climate pollution than internal-combustion cars in the United States, according to a landmark analysis from the International Council on Clean Transportation. (As the publication Carbon Brief has shown, many analyses of EVs versus gas cars fail to take into account the full lifecycle emissions of the fossil-fuel system: the carbon pollution produced by extracting, refining, and transporting a gallon of gasoline.)
Even if you only care about emissions math, two more important reasons justify switching to an EV.
First, when you switch to an EV, you cut down enormously on the marginal environmental cost of driving an additional mile. Most of an EV’s environmental harm is “front-loaded” in its lifetime; that is, it is associated with the cost of producing and selling that vehicle. (Most electronics, including smartphones and laptops, have a similarly front-loaded carbon cost.)
But the carbon emissions of driving an additional mile are relatively low. In other words, converting an additional kilowatt of electricity into a mile on the road is relatively benign for the climate.
That’s not the case for an internal combustion vehicle. In a conventional gasoline- or diesel-powered car, every additional mile you drive requires you to burn more fossil fuels.
Don’t overthink it: There is no way to operate a gasoline or diesel car without burning more fossil fuels. Conventional ICE cars are machines that turn fossil fuels into (1) miles on the road and (2) greenhouse gas pollution. This means that — importantly — using an internal combustion vehicle, or even a conventional hybrid vehicle, will never be climate-friendly.
That’s why the Intergovernmental Panel on Climate Change has concluded that switching to an electrified transportation system — in other words, switching from gas cars to EVs — is “likely crucial” for cutting climate pollution and meeting the Paris Agreement goals. As the International Council on Clean Transportation concluded recently, “There is no realistic pathway for deep decarbonization of combustion engine vehicles.”
This calculus is likely to improve over time. Over the past decade, the U.S. power grid’s climate pollution has plunged while emissions from the transportation sector have slightly risen; we anticipate that, over the next decade, the U.S. power grid’s greenhouse gas emissions are likely to decline at least moderately. Energy experts also expect more renewables to get built, and that natural gas will continue to drive coal off of the grid. These changes mean that the per-mile cost of driving an EV will likely fall. (If you’re in the market for an EV, Heatmap is here to guide you.)
When you switch to an EV, you do something else, too — something that may sound self-evident but is actually quite important: You increase demand for EVs and for the EV ecosystem.
To be painfully direct about why this is important, this means that you stop spending so much money into the gasoline-powered driving system — the network of car dealers, gas stations, and oil companies that subsist on fossil fuels — and begin paying for products and services from the car dealerships, charging stations, and automakers who have invested in the new, low-carbon future.
This is more important than it may seem at first. In the United States, automakers have struggled to ramp up their EV production in part because consumers haven’t been buying their EVs. EVs are a manufactured good, and the world is betting on their continued technological improvement. The more EVs get made at a company or industry level, the cheaper they should get. When you buy an EV, you prime the pump for further improvements in that manufacturing chain.
Under the Biden administration, the Environmental Protection Agency has adopted rules that could make EVs more than half of all new cars sold by 2032. But those rules are somewhat flexible — automakers could also meet them by selling a lot of conventional and plug-in hybrids — and they are under legal threat. If Donald Trump wins this year’s presidential election, then he will almost certainly roll them back, much as he reversed the Obama administration’s less ambitious car rules. And even if Kamala Harris wins, then the zealously conservative Supreme Court could easily throw out the rules.
Under most future scenarios, in other words, American consumers will have considerable power over how rapidly the country switches to electric vehicles. Even in a world where the federal government keeps subsidizing EV manufacturing and offers a $7,500 tax credit for EV buyers, the country’s transition to EVs will still depend on ordinary American families deciding to make a change and buy the cars.
So if you want to decarbonize your life, switching to an EV — provided that you drive enough for it to make sense — is one of the most important steps that you can take.
When you switch to an electric vehicle, you are doing several things. First, you are cutting off a source of demand for the oil industry. Second, you are creating a new source of demand for the EV industry. Third, you are generating new demand for the companies and infrastructure — such as charging stations — that will be needed for the entire transition.
Buying an EV is a climate decision that makes sense if you want to cut your carbon footprint and if you want to change the American energy system. That’s why it’s Heatmap’s No. 1 recommendation for how to decarbonize your life.
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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.