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A just-released MIT paper argues that the energy transition is still largely following the trajectory laid out in the Inflation Reduction Act.

When President Joe Biden signed the Inflation Reduction Act into law in 2022, climate observers — myself included — marked it as a landmark victory in the history of climate policy.
For the first time since global warming arose as a major issue more than three decades earlier, the United States had enacted a comprehensive policy to do something about it. America could boast a generous set of incentives meant to spur new solar farms, electric vehicle factories, and other zero-carbon industries nationwide. The law was projected to bring down U.S. emissions by at least 36% by the mid-2030s, compared to the all-time high they had reached in 2005.
Then Donald Trump declared that the law was in fact a “Green New Scam” and resolved to repeal it. Scarcely half a year into his second term, President Trump and Republicans in Congress terminated many of the climate law’s most important provisions in the One Big Beautiful Bill Act, their tax cuts and spending package passed last summer.
Was the Biden law a false dawn? A new report, released on Monday by MIT’s Center for Energy and Environmental Policy Research and entitled “Glass Half Full,” argues that its influence will live on — at least in the electricity system.
Most of the Biden policies’ expected climate benefits in the power sector — including the amount of renewables that will get built nationwide, and the projected declines in greenhouse gas emissions — are still likely to happen by 2035, even under the Trump administration’s policies, the report finds.
“The glass is substantially full,” Lily Bermel, the report’s author and a visiting fellow at the Columbia Center on Global Energy Policy, told me. “It’s not barely half full. It’s like three-quarters full.” Her study compared not only the effects of Biden and Trump’s tax and spending laws, but also the environmental rules that each administration fought for.
Roughly 74% of new clean energy capacity that would have gotten built under Biden’s policies by 2035 will still get built under Trump’s policies by that year, the report estimates. Those new renewables and zero-carbon power plants will generate about 71% of the electricity that would have been expected had Biden’s policies remained law.
About 67% of the decline in climate pollution that would have occurred over the next decade under Biden’s policies will still happen under Trump’s policies, the report estimates.
Coal- and gas-fired power plants are also likely to generate less electricity over time in both the Biden and Trump scenarios. But under Trump that story is not quite as rosy: The coal-powered fleet will retire more slowly than it would have had Biden’s laws stayed on the books, and the natural gas fleet will run more often than it would have needed to.
The report does not analyze what Trump’s climate and energy policies will do to emissions from every sector of the economy. It focuses only on the electricity system and omits, for instance, any discussion of transportation or heavy industry, even though Trump’s tax and spending law repealed incentives for electric vehicle buyers and hydrogen production.
But the power sector drove the largest share of emissions declines that were expected from the IRA, and other estimates of President Trump’s tax law have suggested that repealing the wind and solar incentives would do more harm to the climate than any other provision. In those studies, the law’s termination of the EV tax credits is often the No. 2 driver of higher emissions.
When Bermel began writing her paper, she wasn’t sure the results would be so optimistic. She compared two scenarios produced by a mathematical model prepared by Energy Innovation, a nonpartisan energy and climate policy think tank, which seeks to simulate the country’s energy system.
In the first scenario, the Biden administration’s climate law and other policies — such as Environmental Protection Agency rules restricting carbon emissions from coal and some natural gas power plants — remain on the books through 2035.
The second scenario looks more like the world we live in. In that run, the Trump administration passes the One Big Beautiful Bill Act, repealing the solar and wind tax credits but preserving incentives for other zero-carbon technologies, such as nuclear power plants and batteries. It also withdraws the EPA’s power plant rules and weakens other regulations on pollution.
The models do not simulate everything the White House has done to stymie renewables and climate policy. Simulations cannot capture, for instance, Trump’s bureaucratic and sometimes extralegal war on solar and wind power because the administration has changed tactics — and gotten blocked by courts — too often to model effectively, Bermel said.
But the models do try to estimate some of the real-world constraints that limit the construction of new clean power plants. In both scenarios, the country’s lack of new interregional transmission — and the long queues to connect new energy projects in many power markets — imposes a “speed limit” on new wind and solar construction, regardless of other incentives on the books.
Despite those constraints, the report finds that more than 80% of the utility-scale solar and battery storage that would have been built under the Biden scenario by 2035 will still be deployed under Trump’s policies.
Only one clean electricity technology stands to do much worse than it would have had the IRA remained on the books: onshore wind. The country will build less than half of the new onshore wind capacity that it would have built had the IRA remained on the books.
In the U.S., new onshore wind installation has declined every year since its peak in 2020. The lack of new large-scale power lines — and a deteriorating local permitting environment — has hampered wind energy’s expansion.
Ultimately, policymakers should prioritize easing construction of new transmission lines and other forms of energy infrastructure, Bermel asserts in the report. Amending the country’s permitting system — and raising the de facto speed limit on new clean energy construction — is likely far more important for lowering emissions than restoring the tax credits, she told me in a conversation for Heatmap’s Shift Key podcast.
“By solving one problem — by making clean energy a little bit cheaper and by incentivizing the demand of it — we therefore exposed how supply-side constrained we are and how awful and burdensome the permitting barrier process is,” she said.
Though there is broad agreement among researchers about the need for a smoother permitting process to allow more renewables development, Bermel’s direct comparison of counterfactuals is an unusually direct way of trying to answer policy questions. “In general, I think the findings are reasonably consistent with what we’d say, but this is a bit of a different way of looking at these questions than energy modelers typically take,” Ben King, an energy and climate analyst at the Rhodium Group, which also operates an energy system model, told me.
Energy analysts often try to examine a range of outcomes and assumptions in their models, such as by varying natural gas prices or electricity demand, he said. The new report does not do that, instead comparing the same baseline energy demand assumptions under the two differing policy regimes. That means the results are less likely to capture what will actually happen in the real world, but still “illustrate the economic competitiveness of these technologies no matter what,” King said — as well, for the moment, as the surging hunger for electricity from AI companies.
Noah Kaufman, a Columbia economist and senior research scholar, told me Bermel’s technical analysis made sense. But he differed sharply with her conclusion that the IRA’s most important benefits had been preserved, even in the power sector. The law’s most important benefits, he said, were never measured in gigatons alone.
“I don’t agree at all with the ‘glass half full’ framing of the situation,” he said. “To me, the importance of the Inflation Reduction Act wasn’t the tax credits or how many gigawatts of solar we will deploy. It was that, for the first time, the U.S. was able to go out to the world and say, ‘We have a strategy now.’”
“I don’t think we have 50% of that now, or 70% of that now,” he said. “I think we have basically none of that now.”
Repealing the IRA and the Biden administration’s other policies has returned the country to something closer to its pre-2021 status quo, he said, where the country is slowly reducing its emissions but not using the energy transition to generate new jobs or economic opportunities for fossil-fuel-dependent communities.
“If you’re not decarbonizing in a way that works for big parts of the country, then you’re not going to be able to sustain the strategy over long periods of time,” he said.
The MIT report does not try to examine whether clean energy manufacturing has declined under the Trump scenario, and concedes that “the Glass Half Full reading is limited to … the power sector, not the broader economic-transformation strategy a successful energy transition requires.” The One Big Beautiful Bill Act retained some of the Biden law’s manufacturing tax credits, including subsidies for solar panel and battery component production.
For at least one technology, Bermel believes the report is not optimistic enough.
The Trump tax law preserved tax credits for technologies such as enhanced geothermal and nuclear fusion — “clean firm” power plants that can produce electricity on a 24/7 basis, regardless of the wind or weather. These technologies will be essential to eventually replacing fossil fuel-burning power plants on the grid.
Yet the energy system models on which Bermel’s report depends hold that companies will build essentially no new sources of zero-carbon electricity by 2035. That’s partly because the policies to support those technologies still aren’t generous enough, because in some cases companies developing them are still building first-of-a-kind facilities.
“Tax credits are best for a technology that is mature enough to respond to price signals,” Bermel said. “They’re helpful, but ironically they’re more helpful for a later stage technology.”
Yet in this case, the real world is already diverging from the models. The artificial intelligence boom has driven hyperscalers to invest in clean firm technologies in ways the model does not predict. Even the models Bermel uses in her report, for instance, do not account for the more than 5 gigawatts of new nuclear power that is expected to come online due to new plant openings, canceled plant closures, and planned upgrades.
The models also don’t reflect the gigawatt of enhanced geothermal-produced electricity Google plans to buy from the energy developer Fervo by 2028. That deal could scale to 3 gigawatts in the 2030s.
Despite those additions, she argues that the next stage of federal climate policy should emphasize public investment that helps expand the power grid and commercialize the next generation of clean firm technologies. That could look like expanding the manufacturing tax credit to cover transformers and other grid equipment. It could also entail offering more direct financial support — either through cheap loans, federal guarantees, or even direct government procurement — to clean firm energy developers. Only through building the next generation of zero-carbon of power plants, she told me, will the country begin to retire its fossil fuel fleet in earnest.
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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.