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That’s how much the U.S. should be spending per year by 2050 to achieve net zero, according to a new Rhodium Group report.

Money seems to be pouring into the field of carbon removal from every direction. Every other week there’s an announcement about a new project. Multimillion dollar carbon removal procurement deals are on the rise. The Department of Energy is rolling out grants as part of its $3.5 billion “direct air capture” hubs program and also funding research and development. Some carbon removal companies can even start claiming a $130 tax credit for every ton of CO2 they suck up and store underground.
The federal government alone spends just under $1 billion per year on carbon removal research, development, and deployment. According to a new report from the Rhodium Group, however, the U.S. is going to have to spend a lot more — roughly $100 billion per year by 2050 — if carbon dioxide removal, or CDR, is ever going to become a viable climate solution.
“The current level of policy support is nowhere near what's needed for CDR to play the role that people say it needs to play in solving climate change,” Jonathan Larsen, one of the authors, told me. “We wanted to reset the policy conversation with that in mind.”
Carbon removal is what’s implied by the “net” in net-zero — a way to compensate for whatever polluting activities are going to take longer to replace with clean solutions. It will be impossible to achieve net-zero emissions by 2050, either at the national or global level, without removing carbon from the atmosphere. But how much carbon removal will we need, and how do we make sure we’re ready to deploy it?
These questions are, in a sense, unique to the field. When we talk about cutting carbon emissions from buildings or transportation, experts are relatively confident in the set of solutions and the scale of the task — they know how many buildings and cars there are and can make reasonable estimates of growth rates.
But carbon removal is a moving target. We know how much we’re removing today — roughly 5 million metric tons, mostly from nature-based solutions like planting trees. Based on current policies, Rhodium estimates we could scale that up to about 50 million metric tons by 2035. But figuring out how much we need depends entirely on how successful we are at decarbonizing everything else. Even if we know we need to electrify all our cars, for example, no one can say whether that will happen by 2050, or at least not with any meaningful degree of certainty.
The Rhodium Group report attempts to narrow the range of this uncertainty so that policymakers can better attack the problem. The authors looked at a handful of different decarbonization roadmaps for the U.S. and found that the minimum amount of carbon removal needed to compensate for residual emissions in 2050 is 1 gigaton, which is the same as one billion metric tons, or a 20x increase from where current policies will get us. It's also equal to about 20% of the carbon that the U.S. emitted last year. “There's a very likely scenario where we need a lot more than that,” said Larsen. “There's scenarios where we need less. But most of the studies out there say at least a gigaton.”
Even if it’s only a rough estimate, landing on a number is useful, he told me. Rhodium Group spends a lot of time answering questions about, for example, what some new policy means for achieving Biden’s goal of cutting emissions in half by 2030. “I don't know if we’d get those questions if there wasn't a 50% target to shoot for,” he said. “So I think this way, people can be like, what does this next wave of policy support for CDR do for getting the U.S. on track for a gigaton?”
The level of investment it will take to get there is also highly uncertain. The authors did a quick back-of-the-envelope calculation to land on $100 billion by 2050: We need to be removing a minimum of one billion tons by then, and the Department of Energy has a goal to bring the cost of carbon removal down to $100 per ton.
The meat of the new report focuses on how to bridge the gap between the roughly $1 billion we spend today and $100 billion, which starts, according to the authors, with treating carbon removal as a public service. It’s not like other climate solutions such as wind turbines or heat pumps, they write, which can rely on private markets to provide predictable demand or to stimulate innovation. “There are very few pathways one can envision where the private sector is going to both scale and deliver those tons,” Larsen told me. Voluntary carbon removal purchases by companies could play a role, he said, but it will not be big enough to get to a gigaton.
Rhodium recommends expanding and extending many of the federal policy programs that already exist — by, for example, providing more R&D funding, doing more government procurement, handing out more loan guarantees, and creating more “hubs” centered on other approaches besides direct air capture, like enhanced weathering or biomass burial. Right now, the tax credit for capturing carbon from the air and burying it underground can only be claimed for 12 years, and projects have to start construction by 2032. The authors call for extending the claim period and moving up the construction start deadline. They also recommend expanding the program to apply to a wider range of carbon removal methods.
A common criticism of government support for carbon removal is that policy makers will over-rely on it. If we aim to do 1 gigaton of carbon removal, does that mean we won’t cut emissions as much as we could have? What happens if, for whatever reason, we can’t achieve the 1 gigaton?
Larsen disagreed with that framing. For one, it’s easy to turn it around: If we don’t scale up the capacity to remove carbon, and we also don’t eliminate emissions by mid-century, we’re not even going to have the option to halt climate change at that point.
But also, decarbonization shouldn’t stop in 2050, he said. If we can achieve that 1 gigaton of annual removal and then keep cutting emissions from remaining sources, we could eventually get to net-negative emissions — even without more CDR. In other words, if we reach a point where we’re removing more than we’re emitting, we could start to reverse global warming, not just stop it.
“I know that's, like, sci-fi,” he told me. “But that's ultimately where we as a species have to go and that’s why setting a target here of at least a gigaton, to me, does not take away the need to reduce elsewhere.”
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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.