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Shorter “shoulder seasons” mean fewer opportunities for necessary grid maintenance. What could go wrong?

It’s getting hot in Texas. Forecast highs for Tuesday are 89 degrees Fahrenheit in Houston, 92 in San Antonio, and 90 in Dallas. ERCOT, which operates the energy market that covers around 90% of the state, issued an “extreme hot weather event” warning and a “weather watch” due to “unseasonably high temperatures” — and “high levels of expected maintenance outages.”
The whole country, but particularly Texas, is playing chicken with its existing fleet of natural gas-powered electricity infrastructure. While the weather-dependence of solar and wind are both obvious and well-known, gas, too, can be susceptible to nature’s fluctuations. High temperatures mean high demand, while very low temperatures can literally freeze whole gas production, distribution, and generation system, with catastrophic consequences.
Natural gas powers around 60% of Texas’ electricity. While Tuesday’s is far from the hottest weather the state will face this year, it comes at what can be a fragile time for the grid. This is the end of the spring maintenance season, when power plant operators have a window to schedule outages necessary to perform maintenance after winter and ahead of summer, when electricity demand spikes again — what ERCOT calls the “shoulder seasons.”
But weather increasingly does not conform to the plans of market regulators, with temperatures rising earlier in the year and falling later, impinging on that shoulder space. In April, ERCOT had to ask power plants to delay outages they had already planned due to high temperatures in parts of the state.
Shutting down a natural gas power plant can be fraught in Texas, where authorities are wary of destabilizing the grid. Other than 2021’s Winter Storm Uri, which caused days of blackouts and hundreds of deaths, one of the state’s worst-ever blackouts happened in April 2006, when high temperatures coincided with — you guessed it — planned outages for maintenance. Texas is not the only place that gets hot in the summer, of course, but its grid is both isolated from the rest of the country and is dealing with substantial growth in power demand, which means it’s more likely to bump up against its limits.
“We’ve had a couple of pretty hot days and have more hot weather this week,” University of Texas professor Hugh Daigle told me. “What’s happening is that we’ve been operating close to the limit of available supply at peak demand.”
While the grid in Texas has remained stable so far this spring — albeit with some wild price spikes at times — delaying planned outages risks future unplanned power failures if operators fall behind on maintenance. Those failures are most likely to occur during the summer months, when high demand from air conditioning adds to stresses caused by the heat and ERCOT is less likely to allow the plants to come offline. In the best case scenario, a strained grid “only” results in electricity prices spiking. In the worst, it leads to blackouts and deaths from extreme heat.
Along with three of his University of Texas colleagues, Joshua Rhodes, Aidan Pyrcz, and Michael Webber, Daigle recently published a paper showing that as Texas warms, the times when it’s “safe” to have a large number of planned outages may shrink.
Average temperatures in the state rose 0.8 degrees Celsius from 1895 to 2021, and are projected to go up another whole degree by 2036. While that may sound like a small change, this would increase the number of 100 degree Fahrenheit days — which often mean record-breaking electricity usage — by some 40%.
While it may seem like a warming trend could have a symmetric and offsetting effect on the grid — hotter summer days that lead to record air conditioning demand but also warmer winter days that create less strain on electric heat — the researchers found that instead, the shoulder seasons were getting impinged on both sides. Compared to the 1950s, mild spring weather has been starting and ending earlier. At mid-century, spring started near the beginning of March; now it’s closer to the beginning of February. The start of fall, meanwhile, slid from the beginning of November later toward the middle of the month.
If maintenance in the spring shoulder season can just occur just from March to May, “maintenance periods will no longer coincide with periods of low expected demand,” Daigle told me. And if it’s just in the fall season, which could shrink to October and November, “it may be unreasonable to expect power plants to be able to forgo spring maintenance.”
“If you look at climate models and how average temperatures change,” Daigle said, “those two periods” — before the cold of winter and the heat of summer — “could merge into a single period in December and January.”
Just one shoulder season introduces extreme risks, Daigle explained. “We still do get winter storms. It’s December and January and you have a lot of stuff down for planned maintenance, and something like Uri comes through — we’re up a creek.”
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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.