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We didn’t know it was coming. We didn’t know where it came from. We still can’t nail its climate change connection.

What happened?
No, seriously — what happened?
Last week, the American megalopolis, that string of jewels on the old Atlantic coast, found itself shrouded by wildfire smoke. New York City’s air turned ashen and dun, then glowed a supernatural amber. For the first time in who-knows, sightseers standing at the U.S. Capitol Building could not see the Washington Monument, a mile and change down the Mall.
You could list the sports games canceled or flights delayed, but what was oddest about the event was the sheer ubiquity of it. This was one of the few news stories I can remember where you could look up from whatever article you were reading and see the story itself, softly lapping at your window.
And then it was gone. By Friday, the haze had blown out to sea.
It was, in retrospect, a strange time — deeply strange, humblingly strange, strange before almost any other quality. More than 128 million Americans were under an air-quality alert on Wednesday night — roughly the population of Germany and Spain combined — but scarcely 36 hours earlier, nobody had known to prepare for anything worse than a moderate haze. The country’s biggest wildfire-pollution event on record arrived essentially out of nowhere.
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One of the main modes of journalism today — but also, frankly, one of the main frames of our whole cultural apparatus, from TikToks that lightly gloss Wikipedia articles to rampant right-wing conspiracism — is that of the explanation. Everyone explains what’s happening to each other, as it happens, at all times, and therefore makes the world seem rational, empirical, and less frightening. Yet with the wildfire smoke, what is so striking is how little we understood. Nearly every important step in the story was misapprehended as it happened.
We didn’t know that the smoke was coming, for instance. On Tuesday morning, meteorologists predicted that the same moderate haze that has hung around all season would again hit the East Coast. The New York Department of Environmental Conservation put out an alert saying that the air quality index, or AQI, might rise to 150 across the state.
They did not forecast — nobody, as far as I can tell, did — that the worst air pollution in decades would soon wallop the state. By Tuesday night, New York City’s AQI had already reached 174, according to Environmental Protection Agency data. As I walked home in D.C., I could see tendrils of visible smoke hugging the upper stories of apartment buildings.
This prediction failure gave the ensuing response a halting, confused quality. How could such a massive event come out of nowhere? Not until Thursday afternoon — when the smoke had nearly passed — did the federal government advise its workers that they could telework or take vacation time to avoid the bad air. On Friday, New York closed in-person schools, just in time for blue sky to return.
I find it hard to blame them. This was an unprecedented event in part because the fires were so far from where they affected. Everyone had seen the videos of smoke besieging Portland and San Francisco in 2020, but back then, the fires had been near those cities — a couple hundred miles away at most. Where was the smoke coming from now? The Adirondacks were fine. Vermont was’t burning.
Here, we misunderstood again. Many outlets — including this one, at first — initially reported that the smoke came from Nova Scotia, where large and destructive fires had raged the week before. But those fires had been doused over the weekend by some of the same weather pattern that was now ferrying smoke to us. In fact, the smoke had come from the boreal forests of northern Quebec, more than 500 miles from New York City.
Why were these fires raging? Not even Canadians could give a good answer. With fires in Alberta and Nova Scotia gobbling attention and resources, the Quebec fires had seemingly been an afterthought until their smoke blew into Toronto and Ottawa, which happened only a few hours before it arrived in New York. Suddenly, a secondary event had become the main event.
On Wednesday, I talked to a Canadian climatologist who seemed hazy about why Quebec was burning in the first place. “I think this situation is kind of similar to Nova Scotia,” he told me, blaming that province’s warm, dry spring for the blazes. But this explanation — which appeared in many outlets — was only somewhat true: While Quebec had suffered a warm May, it was not in drought.
We did not understand why these fires are burning — and honestly, we still don’t. President Joe Biden said that the smoke provided “another stark reminder of the impacts of climate change.” I am not so sure. There’s no doubt, to be clear, that climate change will make wildfires worse across North America: The Intergovernmental Panel on Climate Change says that hot, dry “fire weather” will increase throughout the 21st century. But, again, Quebec is not in drought. As for today, no climate-change signal has appeared in eastern Canadian wildfire data. Their connection to climate change is far less clear cut than it is in, say, California’s blazes.
Yet neither would I condescend to someone who does blame climate change here. When something like this happens, how can you not cite the planet’s biggest ongoing physical transformation? If climate change makes flukey weather more likely, shouldn’t we at least consider it being responsible for some of the flukiest weather in decades? The thing about unprecedented events is that you lack precedent for them.
Not that we completely lack an example for this. In 1780, the sun was blotted out across New England. Nocturnal animals came out; people fretted in the streets and abandoned their work; the Connecticut state legislature considered adjourning for doomsday. Not until a decade ago did we finally learn that the “dark day” was caused by Canadian wildfire smoke drifting south.
Which suggests that this might be a once-in-250-year event. But maybe it’s not any more. Maybe with climate change, it’s a once-a-century event. Or a once-in-a-decade event. For now, the sample size is two.
So I wonder: If it wasn’t climate change, would it matter? The pandemic has already taught us that indoor air quality matters, that unseen particles floating in the air can do serious harm. No matter what happens with the climate, Canada is too large and unpopulated to fight every wildfire; neither can it manage the same kind of labor-intensive forest management that California might attempt. East Coasters should come away from our own dark days with new compassion for people out West — and those across the world — who must deal with wildfire smoke on a seasonal basis, not to mention the fires themselves. Regardless of climate change’s role in this fire, it makes wildfires more likely: We should continue to try to decarbonize as fast as we can.
But as for local policy, perhaps our aims should be humbler. We now know (again) that a great cloud of wildfire smoke can blow up on the East Coast at any moment and poison our air. We don’t need to know everything to protect ourselves and our neighbors from that. Air filters cost hundreds of dollars, but not thousands; in new multi-family buildings, they are built into the ventilation system itself. Perhaps the right lesson from this outbreak should be to change our expectations, and think of indoor air filtering like brushing your teeth — a habit essential to our hygiene, to be used by all, and to be provisioned for those who cannot afford one at the public expense.
Maybe that’s prudent climate adaptation. Or maybe — in the wake of COVID, Canadian smoke, and who-knows-what-comes-next — it’s just new common sense.
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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.