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Unlike with climate change, however, there are some straightforward fixes.

New clean energy projects have a lot going for them. For one, building them has gotten extremely cheap. At the same time, because the wind blowing and the sun shining are unlimited free resources, operating costs for a clean energy power plant are also pretty low. That’s the beauty of a clean energy economy — it reduces our exposure to the price swings, recessions, political instability, and surging inflation that come with fossil fuels.
The problem is that the cure for surging inflation — hiking up interest rates — is having a big, bad impact on clean energy. Elevated interest rates directly and disproportionately raise costs for clean power projects, throwing a handbrake on the clean energy transition and its deflationary impacts exactly when we need them most.
Here’s how it happens: Nearly all the costs of clean energy projects are upfront capital expenditures to cover things like building wind turbines and installing solar panels. And as anyone with a mortgage or car loan can tell you, the higher the amount you need to finance up front, the more you care about your interest rate.
By comparison, a fossil fuel power plant will pay as they go for the fuel they need to operate, meaning they have less to finance. And there’s the rub — those extra financing costs get passed on to clean energy consumers. Even if a fossil fuel power plant and a clean energy power plant have equivalent associated costs, if one has to finance more of that cost upfront at higher and higher interest rates, it’s going to be less competitive. Estimates suggest that as interest rates rise, the total cost of energy from a gas power plant might rise 8%, but for a clean energy project the same cost could rise as much as 47%.
That impact is being felt across the developed world — Bloomberg’s clean energy research division, BNEF, estimates that 60% of the cost increase for offshore wind is the direct result of rising interest rates — but the impact in the developing world is even more insidious. In emerging markets, the financing cost to deploy the exact same technology can be as much as seven times higher. That’s a big part of the reasoning behind the International Energy Agency’s estimate that we’ll have a $2 trillion clean finance gap in emerging and developing economies by 2030.
In one respect, however, we are in luck — financial regulators have a wide variety of tools they could deploy to solve this problem by creating lower, dual rates for clean energy.
One way to do that is to create dedicated central bank programs that give banks access to cheap credit if they pass it on to sectors of the economy that align with key industrial policy goals — like, say, solving climate change. If this kind of facility existed, your local bank could decide that because you put solar panels on your roof, bought an electric car, or installed a heat pump, it could offer you a mortgage at 4% instead of today’s 7% rate. Or it could finance an offshore wind developer’s first projects at below-market rates, helping to make them competitive in a challenging economic environment.
As we all know, however, creating new programs or passing new policies is hard. Instead, we might want to just make existing lending programs greener. In the EU, for example, leaders at the European Central Bank are considering using existing programs to provide banks with financing at favorable rates if they use it to support clean energy.
Meanwhile, here in the U.S., the Fed could reduce discount window interest rates and adjust collateral policies to incentivize clean energy lending — in other words, it could set the terms on which banks borrow from the Fed to support green loans and discourage dirty loans. Intervening this way would incentivize banks to lend more to clean energy at lower rates.
The Fed could also use its emergency powers to create a new program just to provide clean energy with cheaper capital because of the adverse impacts of high interest rates. It recently used these powers to create the Bank Term Funding Program explicitly to mitigate the impact of higher rates on banks; in “unusual and exigent circumstances” and with the Department of the Treasury’s approval, it could adopt a new program to provide similar direct support for clean energy. A once-in-a-civilization clean energy transition to head off a climate crisis, underwritten by historic climate legislation whose impact is now threatened by rising interest rates, would seem to qualify.
But wait, there’s more! The Fed, along with its fellow banking regulators the Federal Deposit Insurance Corporation and the Office of the Comptroller of the Currency, could leverage the new Community Reinvestment Act regulations to encourage certain clean energy investments, including community solar and “microgrid and battery” projects that could help smooth out power supply to public housing in extreme weather.
And of course, it’s not just central banks that can create lower dual rates for clean energy. Public finance institutions can also play an instrumental role by using their own lower cost of finance to bring down the cost of credit. For instance, the EU is providing financial support for the wind industry in the form of loan guarantees from the European Investment Bank. Loan guarantees work by putting the full credit of the government behind a particular project, thereby giving lenders more confidence they won’t lose their money, which brings down the cost of finance.
In the U.S., subsidized loans and guarantees funded by the Inflation Reduction Act and administered by the Department of Energy’s Loan Programs Office are already helping to create dual rates for offshore wind — which, thanks to new Treasury guidance, can now be extended to cover associated infrastructure like sub-sea cables. Still, that’s nowhere near what the Fed could do. Add in the new green bank capitalized with funding from the IRA that could extend low-interest loans for everything from electric vehicles to heat pumps and we’ve got a bevy of tools at our disposal.
For those wondering whether this kind of Fed policy could be co-opted to support everything from defense manufacturing to fossil fuel production, the answer is that industries always lobby for favorable policy wherever they can get them. But dual interest rates and targeted lending programs are common practice around the world, even in free market economies, with no such terrible consequences. At the end of the day, policy is just a tool, and it’s up to us to make sure it is used to achieve society's goals, not corporate profits.
Concern over the impact of rising interest rates on clean energy and the economy more broadly is hitting a crescendo, and for good reason. This week the Fed governors will meet to decide whether further rate increases are still warranted. Most Fed-watchers think this cycle of rising interest rates is finally over, but there’s no such thing as a guarantee.
More importantly, even if the Fed says “enough,” the reality is that our currently elevated rates will almost certainly take years to come down. Meanwhile, we have a rapidly vanishing window of time to reach peak emissions to stay under the Paris Agreement’s limit of 1.5 degrees Celsius of temperature rise. That means we need new targeted policy interventions that bring down the cost of finance to keep the clean energy transition humming. Unlike climate change, the impact of high interest rates on clean energy is not a force of nature. It’s one we can control.
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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.