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New York, New Jersey, and Pennsylvania advance a flurry of new ideas to manage the boom.

We know a little bit more about New York’s AI data center moratorium than we did yesterday. Here’s what stands out to me:
Governor Kathy Hochul says this won’t become a ban. “I’m not expecting the need for a ban. I want [the AI companies] to work with us,” she told Bloomberg’s “Odd Lots” podcast. “I understand how important AI is.”
The moratorium isn’t enough for some left-wing groups. As I wrote on Tuesday, Hochul’s order allowed her to avoid signing a more stringent moratorium that included wage requirements and renewable energy mandates for a much wider scope of projects. Kristen Gonzalez, a democratic socialist and a cosponsor of that bill, hailed Hochul anyway for “protecting everyday New Yorkers with a first in the nation moratorium on new large data centers.”
Some New York City progressive groups, while endorsing that more restrictive bill, suggested that she should have gone much further. The New York City chapter of the Sunrise Movement and other left-wing organizations, for instance, posted an Instagram carousel that said: “The dream isn’t better data centers. The dream is no data centers at all.”
New York is also exploring a grid acceleration fund. The governor’s order hints that a few policies should be in place by the time the moratorium ends. These include a new rule that data centers either bring their own power or “pay their fair share” for electricity, and a new state program to help local governments negotiate for community benefits with developers.
But it also opens the door for requiring projects to pay into a grid modernization fund. Such a fund could finance upgrades, set up new virtual power plants, or pay for new sources of zero-carbon energy, the order says. That idea — which resembles proposals from the Searchlight Institute and Groundwork Collaborative — suggests that the state is exploring ways to harness the AI boom for the public. “We want to make sure [data center developers] are investing in the grid,” Hochul said on Tuesday, “but they’re not being asked.”
Which brings me to my larger point. We’re seeing an efflorescence of interesting policymaking on data centers from Democratic governors and state legislators. New York has now enacted this moratorium, of course. Pennsylvania, a true national epicenter of data center construction, has passed new disclosure requirements, and Governor Josh Shapiro has pushed for serious reforms in the country’s largest electricity market.
In New Jersey — where surging power prices were central to last year’s gubernatorial election — the data center buildout has already produced a flurry of new laws. In its most recent session, the state legislature pared back tax incentives for data centers, required utilities to offer a rate for large electricity users, and required data center operators to publish water and energy data. It also set up a novel program that will let data centers pay to reduce electricity demand elsewhere on the grid, such as by setting up virtual power plants (or paying those who participate in them).
It’s been exciting to see different states — and, to be blunt, to see Democratic-governed states, particularly those in the Northeast and Mid-Atlantic — try to take on the data center boom. It’s good to see them test out ideas, solve problems through legislation, and harness this moment for the public good without strangling the buildout entirely. For too long, blue states have leaned into a particular economic model, one in which states want to attract varying forms of development but in fact succeed only in creating new suburbs, office buildings, and warehouses.
Soon after Democrats passed the Inflation Reduction Act, observers noticed that the law’s fruits — and notably its manufacturing investments — were sprouting in red or purple states, particularly in the Southeast and Sun Belt. The so-called Battery Belt bloomed in the Mid-South, for instance, not the Rust Belt. As I discussed with the political scientist Alexander Gazmararian on Heatmap’s podcast Shift Key, that was often due (counterintuitively, I think, for liberals) to a failure of governance: It is GOP-governed states that have the local expertise, institutional capacity, and political muscle memory to attract big new economic development projects.
If Democrats want to see their states do big things — build new housing and transit, decarbonize their power grids, or give birth to new industries — then they will need to develop the same kind of capability. That’s why I’ve so relished seeing blue states reckon with the data center boom. It should be encouraging that New Jersey policymakers, for instance, have to figure out how to manage a new and fast-growing industry on the technological frontier. Even questions that may seem troublesome right now — around land use, for instance, or how to relieve a congested power grid — will likely lead to policies that improve the state.
This kind of policymaking helps the Democratic Party, too. After all, the party’s future national leaders — its members of Congress, cabinet secretaries, and even presidents — are currently serving at the state and local level. The data center boom’s lessons — for good and ill — will resound among the party’s leadership for a long time.
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Can she appease AI skeptics, economic development advocates, and renewables boosters?
New York Governor Kathy Hochul tried to pick out a middle way with her data center moratorium, carefully charting a course between the demands of industry, advocacy groups, and voters who are increasingly suspicious of the data center and artificial intelligence industries. Did she succeed? Only time will tell.
Hochul’s first-in-the-nation permitting pause has been hailed by data center opponents who want to re-orient American politics around the artificial intelligence backlash and lamented by the technology sector and its allies, including several in the Trump administration. President Donald Trump himself wrote on Truth Social, “New York State has made a terrible decision.” adding that the “Radical Left Dumocrats must not be allowed to cause us to lose Data Centers, AI, and all of this incredible new Technology, to China.”
Before we discuss what Hochul did, we must first discuss what she didn’t do.
What Hochul’s moratorium is not is her signature on the Responsible Data Center Development Act, a data center moratorium that passed both houses of the state legislature in June. That moratorium had a lower energy use threshold for the moratorium: 20 megawatts, compared to Hochul’s 50 megawatts.
One of that bill’s sponsors, democratic socialist Kristen Gonzalez, appeared alongside Hochul when she signed the executive order Tuesday and hailed the governor for “protecting everyday New Yorkers with a first in the nation moratorium on new large data centers.” When asked about this discrepancy by reporters, Hochul said that “we want to make sure we didn’t touch the data centers that are powering hospitals and schools and research centers,” and specifically mentioned data centers used by “bank back-office operations.”
Protecting bank back-office operations is not typically top of mind for democratic socialists. Gonzalez’s office did not respond to a request for comment.
The goal of the moratorium, Hochul said, is to develop a process for data centers to pay their way in terms of grid costs and electricity rates.
“We expect this process, which we already launched, to be completed within the year,” she said. “Once this policy’s in place, the moratorium will be reviewed and lifted.”
What is still unclear is how this moratorium interacts with renewables development, especially upstate where there is enough open space for both wind and solar power as well as large data centers.
While the New York governor has pulled back on the state’s climate goals as renewable energy and transmission has come under the dual assault of the Trump administration and rising costs, Hochul has made a point of promoting clean power development across the state, especially nuclear and hydropower, which can be built and maintained close to her western New York home base.
A New York data center industry could — emphasis on could — be a major customer for renewable power in the state, especially as there’s little prospect of large-scale new natural gas development.
During her speech announcing the moratorium, Hochul emphasized that “we’ve invested so much in other forms of power to meet the current needs of New Yorkers and our businesses,” and that “New York will require data centers to either produce their own energy or pay a premium to tap into our grid.”
The executive order itself lays out a process whereby, once the moratorium is lifted, new data centers may be required “to fund new clean electric generation and/or battery storage dedicated to their operations, consistent with the State’s clean energy goals, including customer-sited distributed energy resources, to the greatest extent feasible.”
When discussing her energy and economic policies on Bloomberg’s “Odd Lots” podcast this week, Hochul connected her data center moratorium with economic development efforts, especially upstate, where large data centers are more likely to be sited.
Referring to Micron’s $100 billion Syracuse-area semiconductor manufacturing project, Hochul told hosts Joe Weisenthal and Tracy Alloway, “I’ll work with you to get the power you need.” (The state approved a transmission line for the project last year.)
“If I have to choose between powering a largely vacant data center with the same amount of power I can have with a Micron with 1,000 jobs, I can tell you right now where I’m going,” Hochul said. “They can come under the conditions we lay out.”
But it may be just as likely data center developers take the hint and avoid a state with expensive power and high costs of doing business in the best of times.
“I don’t think we know yet how this will impact what’s known as behind-the-meter or off-the-grid power solutions: natural gas, cogeneration, solar, wind, battery storage,” Jeffrey Moerdler, a partner at the law firm Haynes Boone who chairs the data center practice, told me. “I assume it will hold up data centers powered by alternative energy sources.”
As for whether Hochul can successfully keep the one-year moratorium a year (temporary policies have a tendency to become permanent), develop new rules to address her concerns about grid costs and local opposition, and then have data centers line up to get back into New York, Moerdler was skeptical.
“It’s going to take years to make up for that shift” against data center development, he told me, predicting that the moratorium could lead to “many years of new data centers not locating here because they already started during that one-year period somewhere else.”
Something else that must be noted in all of this: “New York is not a high priority location for data centers.” Whether the state’s governor wants it to be remains to be seen.
Where is the smoke worst, where will it go next, and what causes that color?
Before wildfire smoke turns the skies to a jaundiced yellow-gray, it might look almost pretty. Midday light grows diffuse, taking on a crepuscular golden hue. Shadows soften and stretch long. The sunsets are particularly incredible: radiant, neon red.
But as with oleander and poison dart frogs, beautiful things are often the most dangerous. The same wildfire particulates that scatter the light will, once dense enough, turn the air around you orange, then black. They will get into your lungs — slipping past your nose hairs and mucus, the body’s defenses that stop larger particulates — and provoke your immune system into an attack. The tiny air sacs at the ends of the bronchioles in your lungs, where the gas exchange of “breathing” actually happens, will become inflamed. You will become short of breath. You will cough. The smallest smoke particulates may even enter your bloodstream.
And if you are like 24,000 other Americans every year, this will kill you.
Though wildfire smoke exposure might seem to be more of a nuisance to a healthy person than anything else, experts agree it should be taken seriously. “In my profession, wildland firefighting, you make a decision that you run into that,” Nicholai Allen, a firefighter and founder of Safe Soss, a home-hardening product line, told me. “But for my family and my children, I don’t want them breathing in the smoke that’s traveling that far. We have air purifiers, and we’re taking similar precautions.”
On Wednesday, more than 100 million people in the Midwest and Northeast face unhealthy smoke conditions from fires burning up to 2,000 miles away. Here’s what you need to know.
The smoke is largely coming from 150 or so lightning-ignited fires in Ontario and northeastern Minnesota. Triple-digit temperatures, dry conditions, and high winds have fanned a “wall of fire” across the region, as the firefighting newsletter The Hotshot Wakeup put it, even as Canada is, on the whole, tracking behind its five-year average for area burned so far. Most of the fires sending smoke to the U.S. this week are still out of control and spreading rapidly.

A high-pressure area over the central U.S. and a low-pressure area over Eastern Canada are acting as a funnel, pulling bad air east across the Great Lakes region and into the populous Acela Corridor. Conditions are worst closest to the fires: Around 8 a.m. on Wednesday morning, Duluth, Minnesota had a “hazardous” air quality rating of 785 out of 800. By the afternoon, Toronto had the worst air quality of any major city in the world, and drivers in northern Michigan have been advised to slow down and turn on their low-beam headlights because visibility has been so reduced by the smoke. The eastern-moving plume has also blanketed large portions of Upstate New York.
Degraded air quality reached the Boston and New York City areas on Tuesday night and is expected to linger through Thursday. The smoke reaches as far north as Maine, having dimmed the morning light in New Hampshire, and could spread as far south as Washington, D.C. over the next 24 hours.
Though the smoke is staying largely to the north over the middle part of the country, forecasts show it could dip into downtown Chicago on Thursday as well.
Wednesday and early Thursday will be the worst days for the eastern U.S., per the current outlook. A cold front should help push the worst of the smoke out of the region as we head into the weekend.
So far it appears that much of the smoke has remained high enough in the atmosphere that while you’ll be able to see and likely smell it, it might not cause extreme air quality problems on the ground. As of Wednesday afternoon, New York City was recording some of the worst air on the East Coast, with an air quality index of around 160 — bad enough to trigger an “unhealthy” alert for the general public and to rank fifth-worst among major cities worldwide. The rest of the region still mostly showed orange readings designed to alert sensitive groups such as older adults, people with respiratory conditions, and pregnant women, or more moderate yellow ratings.
Conditions could still change, though. Heat, pressure, and winds can drive smoke down to ground level, where it becomes a threat to public health. In fact, the Fox Forecast Center’s models indicate that particulate matter concentrations around the Great Lakes and Northeast could be on par with the 2023 East Coast smoke event, during which New York had the world’s worst air quality, although The New York Times reports that “even the most severe forecasts” this week should not approach that level.
The best thing to do is to continue monitoring your local air quality. If you want help navigating what those readings mean, my colleague Emily Pontecorvo has written a great explainer.
For many on the East Coast, the orange skies are a flashback to the 2023 smoke event. While eerie and apocalyptic, the smoke also gives us an excuse to talk about Mie theory.
Air molecules are much smaller than the wavelength of light. When white light from the sun enters the atmosphere, nitrogen and oxygen scatter the short, higher-frequency blue light in multiple directions. This is known as Rayleigh scattering, and is also the answer to, “Why is the sky blue?” Under normal conditions, wherever you look in the sky, blue light is headed toward your eye.
Smoke particles, while small enough to enter our lungs when inhaled, are larger than air molecules — about the same size as light wavelengths. Because these particles are larger, they also scatter light more democratically, including the lower-frequency, longer reds and oranges. This is called Mie scattering. When sunlight passes through smoke, the reds, oranges, yellows, and blues are all mixed together as they reach our eyes, appearing as a hazy gray or white.
You might expect thicker smoke to result in a darker gray, then. But smoke also contains organic compounds from burned plants called brown carbon, plus soot, both of which absorb visible light. Brown carbon, in particular, prefers light at the shorter end of the spectrum, absorbing about three-quarters of the total light at blue wavelengths in smoke plumes, compared to about half at red wavelengths. That means that when the smoke thickens, the blue light doesn’t reach our eyes nearly as well, and the sky takes on an orange appearance.
One of the dangers of the current smoke event is that it coincides with high temperatures across the Central U.S. and New England. Both conditions together — high heat and smoke — can lead to some confusion over how to respond.
The best strategy is to keep your windows closed. But while it might feel safe side, wildfire smoke can still degrade indoor air quality. “If you have a fresh air intake on your air conditioning system, I would shut that off so that you’re recirculating just your purified air inside your house,” Allen, the firefighter, told me.
You can also install activated carbon exterior filters on attic and crawl space vents and run a purifier with a HEPA filter. (If you bought an air purifier during the last smoke event, consider this your reminder to replace your filter.) “Then I would avoid going outside or exercising outside if there’s smoke in the air,” Allen added. “When the particles are arriving to you from a great distance from the wildfire, they are the smaller particles that can get in your lungs. So not to create undue fear, but there’s definitely stuff in that air that you don’t want to breathe.”
Deciding what counts as a heat death is more difficult than it sounds.
Just last month, a heat wave killed an estimated 2,700 people in France. Think about that for a second: 2,700 people. That’s equivalent to the mortality of two Hurricane Katrinas or 10 Hurricane Sandys. In France, where there were roughly 970 murders in 2024, the heat wave killed more people in two weeks than almost three years’ worth of homicides.
But unlike floods, hurricanes, tornadoes, or murders, heat doesn’t leave behind much of a crime scene. Although heat kills people in obvious, direct ways like heat stroke, it also puts enormous strain on our hearts and kidneys as our bodies work to keep our internal temperature at 98.6 degrees Fahrenheit. Heart attacks spike during heat waves because vasodilation diverts blood to the skin’s surface to cool it down, in the process lowering blood pressure and forcing the heart to work harder and faster to circulate oxygen. Deaths from renal diseases also jump during periods of high temperatures due to severe dehydration and restricted blood flow to the kidneys.
“Let’s say you have two people with underlying heart disease; somebody has a heart attack versus somebody has a heart attack because it’s too hot,” Kristie Ebi, an epidemiologist at the University of Washington and an expert on heat-related mortality, explained to me. “Will the second one be recorded as a heat death or will it just be recorded as a heart attack? Frankly, when both go into the emergency department, the number one goal is to save a life — it’s not necessarily to record whether it was because of temperature.”
But if physicians don’t code the second heart attack as a heat death— a procedure designed for insurance and billing rather than getting to the root of underlying environmental conditions — then the headline number of heat wave-related deaths will almost certainly be an undercount. In Washington during the 2021 heat dome, for example, the state health department initially reported that 129 people died from the temperatures. But later analyses compared the overall number of people who died that week in the state to the average number of people who died during the same week from 2013-2019 and concluded that there were 485 “additional” deaths compared to what would have been expected during normal early summer conditions.
Those 485 deaths are called “excess deaths,” and the number offers a broader picture of who actually dies from a heat wave. The tally captures not only those heart attacks that are coded by physicians and medical examiners as caused by the heat, but also the ones the state may have overlooked or discounted. Air pollution deaths, homicides, drownings, and accidents, for example — all of which also spike in relation to heat waves — show up. As one epidemiologist explained it to the Seattle-area NPR affiliate KUOW, a boating death might count as an excess heat death, too, because while “not directly attributable to heat in the sense of heat stroke … it arguably is attributable to heat in the sense that had it not been hot, they would not have gone out.”
Excess death analyses are also methodical in what they don’t count. “After a heat wave, there’s a deficit in the number of deaths, which means that the heat wave brought forward deaths that would have occurred anyway,” Ebi told me. The analyses also take those into account to model only the “true” excess events. This, at least, is relatively simple in scope: The advantage of heat waves for mortality accounting is that they don’t have the long tails associated with hurricanes and other weather-related tragedies. “Deaths occur over a few days of a heat wave, and then it’s over,” Ebi added.
But the calculation, while relatively straightforward, has its critics, too. “The limitation of that approach is that it doesn’t actually quantitatively attribute that excess mortality to the heat,” Christopher Callahan, a climate scientist and assistant professor at Indiana University Bloomington, told me. Take the boating accident example: Maybe if it’d been a regular summer day, the enthusiast still would have taken his pontoon out and had all those beers. Maybe during the heat wave it was also smoky, and that caused some of the excess deaths. There’s also the possibility that the baseline number of deaths already includes some baked-in heat-related deaths, obscuring the cumulative total.
A third approach, favored by academics — and recently employed by Callahan to estimate the 2,700 heat-related deaths in France last month — involves using long-term data on both temperatures and mortality for a given location and then fitting a statistical model that relates the two. This method has the advantage of generating a U-shaped relationship that shows how mortality rates change once temperatures exceed a certain threshold (or drop below it, in the case of cold-weather-related deaths, hence the “U”). Like an excess death analysis, this method “has the benefit of, again, not having to rely on individual diagnoses,” Callahan said. “It has the drawback that there is no one right statistical model. Different people have different philosophies about how to fit those models.”
The other drawback is that creating such a model and subjecting it to the rigor of peer review is time-consuming — by the time you’re able to publish a death toll, the news cycle has probably moved on. Callahan got lucky: He had already created such a model for France to study the 2003 heat wave, which killed an estimated 15,000 in the country in a couple of weeks. The model relies on a historical understanding of the relationship between temperature and mortality in France — “not a crazy assumption, but an assumption,” he admitted to me — and he published the findings in Carbon Brief earlier this month. (Callahan also estimated that 20,000 people died continent-wide in Europe during the June 2026 heat wave — a number that circulated widely, but that he told me he’s now working to revise downward.)
Notably, the number Callahan arrived at for France does not represent “real” people or “real” deaths, at least as linked to death certificates. There are no biographical or even demographic numbers attached to it. (That said, you can create models of the same U-shaped relationship for anything: temperature and age, income, race.) More mind-bending, though, is that because of this, Callahan’s model can also be used to predict. Had there been a way to know the exact temperatures before the European heat wave, he could have told you how many people would likely die before they actually did.
In the case of France, the simple excess death count put the toll at 2,025, though officials say they expect the number to rise. While Callahan’s number and the official tally from France differ by what seemed to me to be a lot — 675 deaths — Callahan told me he’s actually encouraged by how close his model came to the government’s empirical count, given that the two use completely different methodologies.
After all, heat death counts can vary by orders of magnitude, including within a single government. Before 2020, the Centers for Disease Control and Prevention reported that only about 700 Americans died each year from heat, relying primarily on physician diagnostic codes. After moving in recent years to better incorporate underlying and contributing causes of death, the CDC adjusted its estimate upward to about 2,000 heat-related deaths per year in the United States. Still, the government’s numbers remain extremely conservative; independent researchers studying heat mortality say the figure is likely closer to 12,000.
But even more holistic heat-related mortality numbers have their critics. For example, models don’t work as well for many lower-income countries, where mortality may be reported monthly, thereby making day- or week-level heat attribution impossible.
Granularity presents its own set of problems. Excess deaths and modeling analyses both have to define the first “heat day” of an event. You can do that by setting a fixed threshold — say, anything above 90 degrees Fahrenheit counts as “high heat” — but Ebi told me there is little value in analyses or policies that take that approach. That’s because heat is contextual: “My standard joke is, if we had the temperatures here in Seattle that they have in Phoenix, we basically all die, because we don’t have the infrastructure and we’re not acclimatized,” she said.
A slightly better metric might be a relative threshold — say, temperatures above the 95th percentile of historical temperatures for a specific location count as “extreme heat.” The problem there, though, is that it may need to be stratified further by vulnerable populations that feel the effects much sooner, like adults over the age of 65, pregnant women, outdoor workers, or people with certain medical conditions. While that approach might seem overly complicated, parts of Asia already use nuanced thresholds to warn older adults to take precautions. “It’s going to be more challenging to communicate, I grant you that,” Ebi told me of such an approach — much less to try to model. “But it’s also going to be more useful.”
Even so, a larger problem remains: The multiple systems for calculating heat deaths are honed to address different questions, which makes them impossible to compare. The Federation of American Scientists has pushed for the CDC to upgrade and standardize its heat-mortality tracking. “We’ve thought about if it’s possible to ever set a goal of bringing heat-related deaths down by 50%, or something like that,” Grace Wickerson, the senior manager of climate and health at FAS, told me. “But we don’t even have a baseline number or a way to say, ‘This is the starting point for this goal or strategy.’”
Wickerson also suggested, though, that there might be things we lose in trying to nail down the most correct heat-related mortality number. “I’m almost a bit weary of the pursuit of large numbers,” she said. “At least to me, what feels more important is why people are suffering and dying, what types of people they are, and what stories, messages, and stakeholders we need to engage and target to actually build meaningful policy strategies.”
Despite being deeply engrossed in the calculations, Callahan stressed that he wants readers to have a similar takeaway from his own research. Improved “healthcare access and access to cooling, shade, and shelter” — or in the case of heat-related mortality from climate change, “reducing greenhouse gas emissions” — lead to fewer heat deaths, meaning the vast majority are preventable.
“The relationship between environmental conditions and a person’s mortality is not fixed or necessary,” he told me. “It can be stopped.”