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Where natural gas comes from matters for hydrogen production.

Oil giants Exxon and Chevron are among a group of energy companies that could receive up to $1.2 billion in federal grants to make so-called “clean” hydrogen in Texas. Their proposal to produce the clean-burning fuel using natural gas and carbon capture, in addition to other methods, was selected by the Biden administration a year ago to become one of the country’s seven clean hydrogen hubs. But a trio of researchers at the University of Texas at Austin just showed that there’s a dirty paradox at the heart of the plan.
In a study published in the journal Nature Energy on Monday, the researchers show that upstream emissions in the natural gas supply chain in Texas are so high that it’s essentially impossible to make hydrogen from it that would meet federal standards for “clean” hydrogen. But, the authors warn, the government’s proposed method for measuring the carbon intensity of hydrogen overlooks these emissions. That means these Texas hydrogen projects could get millions in public funding in the name of tackling climate change, all while making the problem worse.
“You’re investing so much in developing a hydrogen economy, and then it turns out, 10 years later, half of them are not even low carbon,” Arvind Ravikumar, an associate professor at the University of Texas at Austin and one of the authors of the new paper, told me. “I think that’s a real risk.”
This story might sound familiar. I’ve written extensively about the emissions accounting challenges plaguing another method for making clean hydrogen that requires only water and carbon-free electricity, known as electrolysis. The problem there is that the electric grid still runs largely on fossil fuels, and so plugging in a hydrogen plant will produce indirect emissions, even if the production process itself is clean.
The new study highlights a similar issue with hydrogen made from natural gas. Of course, since this method uses fossil fuels, it’s already substantially more difficult to prove it has any climate benefits at all. In theory, the emissions can be greatly reduced, although likely not entirely eliminated, by capturing the carbon emitted from the plant. The authors show, however, that the more important factor is where the natural gas comes from.
Natural gas is mostly methane, a greenhouse gas more than 80 times more potent than carbon dioxide in the short term, and leaks are notoriously underestimated. But any assessment of the benefits of hydrogen made from methane must take leakage into account, and some natural gas fields are leakier than others.
The paper analyzes a range of scenarios for two hypothetical hydrogen plants — one on the Gulf Coast that sources natural gas from the Permian Basin, and one in Ohio that gets gas from the Marcellus Shale. The Treasury Department’s draft rules for calculating the carbon intensity of hydrogen for the clean hydrogen tax credit say these two plants should assume that a national average of 1% of the natural gas extracted from the ground is leaked into the atmosphere where it warms the planet. But more than a decade of on-the-ground measurements, combined with more recent satellite data, has shown that methane leaks vary widely from well to well and basin to basin.
Using the more accurate, though still approximate, leakage rates of 5.2% in the Permian and 1.25% in the Marcellus, the authors calculated the carbon intensity of hydrogen produced at the two plants under various assumptions. What if the carbon capture system is more effective? Or less effective? What if the capture equipment is powered by renewables? What if we measure the warming effects of methane over 20 years versus over 100 years?
No matter which variable they changed, one result stayed the same: Hydrogen made from Permian Basin gas greatly exceeded the government’s definition of clean hydrogen, i.e. 4 kilograms of CO2 released per kilogram of hydrogen produced. In fact, the emissions from natural gas production in the Permian Basin alone pushed it over that standard. Hydrogen made from Marcellus Shale gas, on the other hand, has the potential to qualify as clean if at least 90% of the carbon at the plant is captured.
The findings suggest that without enormous efforts to reduce those upstream emissions, which come from leaks, venting, and flaring at the wellhead and along the pipeline system, natural gas-based hydrogen projects on the Gulf Coast should not qualify for federal subsidies.
The authors advocate for the Treasury’s final guidelines for calculating the carbon intensity of hydrogen to account for these regional differences. “I think that, to begin with, will make a huge difference in accurately estimating the emissions intensity of these projects,” Ravikumar said. As new methane regulations from the Environmental Protection Agency go into effect, it’s possible that projects that are not eligible today could become eligible in the future. “But the point is, you’ll only know that if you do your carbon accounting accurately across supply chains,” he said.
One problem with this solution is that hydrogen producers have access to another federal tax credit that doesn’t require any analysis of how clean the hydrogen is — up to $85 for every ton of carbon they capture and sequester underground. Indeed, at least one project developer has already said they will go after that subsidy instead of the one for clean hydrogen.
Ravikumar thinks those developers are facing a major risk. “At the end of the day, you’re going to buy hydrogen from these companies explicitly for its low-carbon attributes,” he said. “Right now we did this analysis, but very soon, you’re going to have satellites that are going to look at all these regions and be able to make emissions information publicly available. And once you’re able to do that, you can’t make up numbers on paper.”
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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.