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A summer school program in Roanoke, Virginia, could change the way people think about heat.

According to legend, the ghost of Lucy Addison still roams the halls of her namesake middle school in Roanoke, Virginia. She’s particularly fond of the basement, where the art and technology rooms are.
So when Brian Kreppeneck got a few thermal cameras for a summer program he was running this year, he knew exactly how he was going to teach his students how to use them: with a ghost hunt. He took them downstairs to the auditorium, shut off the lights, and had them train the cameras on things like the air-conditioning vents, a digital clock blinking in one corner, and the empty auditorium stage.
“And wouldn't you know it, as we're looking at the auditorium stage, a little mouse ran across the auditorium,” Kreppeneck, a science teacher at the school, told me. “They screamed and ran out, and that’s how they learned to use the thermal cameras.”
The cameras had a use beyond ghost-hunting and scaring schoolchildren (and mice): The students were going to use them to measure temperatures in and around their school. Over the course of a week, they pointed the cameras at all kinds of things in the world around them, from basketball courts baking in the sun to the shady ground underneath trees. They also clipped sensors to their shoes, which measured ambient temperatures as the kids went about their days. But that was just the beginning.
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“We wanted to develop a curriculum where students learn both about the problem of urban heat, and then also are able to connect that with potential solutions that come from urban planning,” said Theodore Lim, assistant professor of urban affairs and planning at Virginia Tech and the designer of the summer program. “We want them to feel like there are things that [they] could do in [their] own neighborhoods to help mitigate some of those temperatures.”
Urban heat is a longstanding, intractable problem. Study after study has shown that cities are noticeably hotter than surrounding rural areas; this is called the Urban Heat Island effect. Many studies have also shown that the hottest parts of most cities tend to be the areas that house lower-income communities and communities of color, thanks to a dearth of vegetation, tightly packed buildings, and an overabundance of construction materials that radiate heat like concrete. Richer neighborhoods, meanwhile, tend to be lusher, with more space between buildings and, often, building materials like wood or brick that do a better job of dissipating heat.
But understanding just how the built environment affects heat is pretty hard. Meteorologists and weather apps tend to draw data from sensors at airports, which can’t give us any insight into the contours of heat within specific neighborhoods. The numbers we see on our phones often don’t reflect the temperatures we feel; a neighborhood by a river or a park, for example, would be much cooler than a neighborhood with high concentrations of concrete and asphalt, yet residents in both places would see the same temperature in their apps or on TV.
After a week of collecting data with another teacher, the middle-schoolers came back to Kreppeneck’s classroom to figure out what all the numbers had to say. Put together, the data from the thermal cameras and the shoe sensors created something few of us get to see: a personalized look at how the built world around them shaped the way heat worked in their lives. As Lim and Kreppeneck expected, the temperatures the kids experienced were often higher than the temperatures measured by the sensors at a nearby airport, sometimes by as much as 30 degrees Fahrenheit:

Each colored line represents the data from a student at one of the five schools that participated, while the black line represents the temperature reported by the weather station at a nearby airport. If we follow a few of the blue lines, which represent students from Addison middle school — the one with the ghost — we see some of their personal temperatures spiking high above the black line. This could be for a few reasons: maybe they’re playing basketball on a concrete court, or eating lunch outside, or walking around a neighborhood with few trees.
But on each day, when the black line is at its peak, we see almost all of the students’ temperatures dip far below it. That was when the kids were cooling off indoors, often in air-conditioned buildings. As day turns to night, we see temperatures at the weather station dip below what some of the kids experienced indoors. By the next morning, as the kids start going about their days, their lines spike above the weather station again.
“Before they did this activity, if you asked one of these middle school kids if humans can control the temperature outside, they’d say no way,” Lim said. “But then they start to make these correlations: Humans make decisions about where to plant trees, or where to build parking lots, or what color different surfaces should be. And so we kind of do control the outdoor temperature.”
This kind of realization also shifts heat away from being a personal issue that can be solved by, say, drinking water or cranking the air conditioner, to a systemic one. There’s something kind of freeing about this: Lim said that instead of being ashamed that their families might not be able to afford air conditioning, the students came to recognize that their neighborhoods were historically hotter because of decisions made by other people. Northeast and Southeast Roanoke, for example, both saw higher temperatures than the Northwest and Southwest quadrants, and the entire city was significantly hotter than the rest of Roanoke County:

Armed with their temperature data, the students spent the second week of their summer program in Kreppeneck’s class learning about urban planning and mapping out ways their own neighborhoods could be redesigned to mitigate heat.
“As science teachers, we’ve always struggled to make the connection between science in the classroom and home,” Kreppeneck told me. “There’s always been some sort of a wall there, where the kids just think science takes place in the classroom. But giving them a real-world project made these concepts transcend the classroom.”
Kreppeneck also talked to his students about activism and advocating for change. This was the idea of Virginia Tech’s Lim; activism gives the kids a sense of agency over their built environment, and it also encourages them to start conversations with the adults in their lives who previously might not have paid much attention to climate change, whether due to a lack of information or the impression that it didn’t impact them. But climate change continues to push global temperatures higher — this September was the hottest on record — and the effect of climate change on heat is becoming increasingly harder to ignore. Creating policy to deal with those changes, however, is a difficult task.
“In Roanoke, as is probably the case in many cities, there's kind of a lot of contention between the government and some of these more vulnerable communities because of the history of urban renewal,” Lim said.
As Martha Park writes in a beautiful illustrated history for Bloomberg, northeast Roanoke was a thriving home for black and immigrant residents prior to urban renewal, a policy James Baldwin once called “negro removal.” Then, in 1955, the city declared the area “blighted,” seized the entire neighborhood through eminent domain, burned the buildings to the ground, and even exhumed nearly a thousand bodies from the local cemetery, dumping them in a mass grave outside town. Today, the area is mostly pavement and industrial parks.
“There’s a lot of mistrust on both sides,” Lim told me. “I’ve found that using youth-based community science is a relatively uncontroversial way of getting at some issues that actually do have very deep systemic causes.”
This was the third year Lim ran his program in Roanoke. In earlier years, Lim ran the program by himself at just one of the schools; this summer’s group, consisting of 130 students from all five Roanoke middle schools over the course of six weeks, was by far the largest, and Kreppeneck and another teacher took over most of the day-to-day. Going forward, Lim hopes it’ll turn into something more than a middle-school summer program; community leaders are talking about putting together a climate action plan for the city, and he’s exploring the possibility of creating programs at local high schools and churches that build on the middle school curriculum. The idea is to get the message about heat, and the solutions for it, out into the community in as many ways as possible.
Kreppeneck’s already planning on incorporating urban heat into his syllabus for the spring semester, expanding the two-week summer program into something that the students can engage with on a deeper level.
“My hope is that the kids will start talking about it, and start taking ownership,” Kreppeneck said. “Watching the looks on their faces, watching how the wheels started turning as to how they would change their neighborhood, it was very rewarding. If they believe in something, they can make change. It starts with them.”
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Can AI help emergency managers make faster decisions when every second counts?
Meteorologists had nothing polite to say about Tropical Storm Bertha. The “weak, disorganized, and lopsided” system made initial landfall in Louisiana last week as a “hot, sheared mess,” one that forecasters doubted would reach Texas with much oomph at all. Still, the Galveston County Consolidated Drainage District — the local flood mitigation and drainage management entity for the state’s most flood-prone county — had stood at the ready, posting updates on the storm’s progress to its Facebook feed in the lead-up.
There had been action behind the scenes, too. Since this spring, the county has relied on a new “AI-powered flood warning solution” pilot program to help local administrators identify the gaps in their understanding of the county’s flood risk and monitor rising water levels in real time. In a crisis, a chatbot could even advise them on when to issue an evacuation order.
“Imagine you’re an operator and you have to tell people to leave their homes because of floods coming in,” Todd Barr, the CEO of Axonis Decision Intelligence, which has partnered with the smart water-level sensor company Simplicity Integration in Texas’ Galveston County, told me. Axonis provides AI-assisted decision-making tools to clients in a number of time-sensitive industries, and in every case, “You want a paper trail of the data you used to make the decision — the reasoning and the model you used — and our platform does all of that,” Barr went on.
Issuing evacuation notices is a famously thorny business, and one that has resulted in high-profile and high-casualty failures, including in the Paradise, California, and Maui wildfires. Particularly noteworthy were the 2025 Kerr County floods that killed more than 100 people in Texas’ Hill Country after local officials took 90 minutes to send phone alerts once they became aware of the rising river.
In many cases, particularly in more rural counties, the teams making the evacuation decisions are small and lack sufficient training not only on when to make such a call, but even on how to word it. “The people who are put in the position of issuing the messages are doing 20 other things at the same time,” Jeannette Sutton, a researcher at the University at Albany’s Emergency and Risk Communication Message Testing Lab, told me when I reported on evacuation notices after the Los Angeles fires.
As for Galveston, “100%” of the buildings on the densely populated island are at flood risk, with modeling suggesting a worst-case-scenario hurricane could produce 26 feet of storm surge. Much of the city’s stormwater infrastructure additionally predates modern climate-change-intensified rainfall probabilities, with the district in the midst of a $54 million drainage project aimed at mitigating future flooding by building a pump station and enlarging sewer lines.
As part of the region’s ongoing resiliency work, the Galveston County Consolidated Drainage District installed seven of Simplicity’s water-level sensors —the county’s first — at locations on the mainland. (There are no sensors currently on Galveston Island proper.) Simplicity’s Axonis-powered system, SI-Ai, also pulls in data from NOAA, the U.S. Geological Survey, and Houston’s Harris County to present residents of the entire region with a live flood-risk dashboard, complete with intuitive green-yellow-red indicators to evaluate their neighborhood hazard level in real time. Operators also have their own proprietary dashboard where they can monitor sensors and are prompted to ask questions to interpret readings and open “investigations” if something appears amiss.

“If I’m the municipality, I can say, ‘Okay, here’s what the forecast is looking like and what is potentially going to happen,” Alison Reese, the COO and co-founder of Simplicity, explained to me. “Then I could ask a question like, ‘Hey, what other locations in this watershed are at high risk for flash flooding?’”
That’s where Axonis, the artificial intelligence company, comes in. “Today you would have to be like, ‘Alright! Get the weather report, quick! What’s happening? What are the sensors saying? Okay Bill, now what’s the upstream sensor saying?’” Barr said, acting out the frantic scenario of trying to source data from multiple streams at once. “All of that is what we’re automating.” (Galveston’s Office of Emergency Management is “not the POC for the flood sensor operations,” a representative told me; the drainage district oversees the Axonis-Simplicity partnership, and did not return a request for an interview. The mayor of League City, a city 35-minutes north of Galveston that is also managed by the district, has publicly criticized the SI-Ai program as a separate sensor network that duplicates the work of the Harris County Flood Control District.)
Working from the assumption that emergency managers have to parse reams of data in short periods of time — flash floods can rise as much as 10 feet in an hour — Axonis provides what is essentially a chatbot for authorities to query potential decisions ranging from road closures to evacuation notices, based on feedback from the sensors. It stops short, however, of having a dialogue box that pops up to tell operators, EVACUATE THIS NEIGHBORHOOD NOW.
When Barr demoed the program to me, he had the tool configured to create a credit risk review memo for a would-be banking client. (Axonis also has customers in the banking and defense sectors.) The dashboard essentially functioned the same as it would for Galveston County, though, and his investigation returned the kind of simplified, emoji-studded one-sheet that users of large language model-powered AI interfaces would immediately recognize. In this case, the tool identified a “🔴Risk Alert CANDIDATE” — Barr said that would be a particular sensor, in the case of Galveston — and followed it with a summary and bullet-pointed sections breaking down “⚠️Credit Risk Indicators” and “💧Liquidity Position.” (In a screenshot of an example flood report for Simplicity, shared with me, those sections were replaced by “📍Site Location” and “💧Water Level — Last 72 Hours.” I wondered what else was possible: “🌊Historic hydraulic risk”? “💀Vulnerable Populations”? )

The system then takes operators through a four-step decision-making model based on the OODA Loop, a common workflow in military contexts that involves justifying actions through evidence-based observations. “We always keep a human in the loop on these things, at least today in 2026 — though who knows in two or three years,” Barr said. He clarified in a later conversation with me, though, that “Axonis and [AI] tools should never tell you to evacuate now. It should tell you the information you need to make that decision.”
That was a point Barr stressed numerous times during our conversation: That Axonis’ chatbot is intended as a brainstorming tool or sounding board, and one that keeps a careful paper trail, “cryptographically sealing” any eventual decisions for review and attestation later. I likened it to a police body camera, and Barr didn’t dispute the similarities. “It’s an accountability tool,” he told me.
Of course, that means the burden of decision-making still falls on potentially fallible humans. I worried in particular that by sharing the responsibility with AI, human operators might get lazy or fail to properly question a decision the program might be leading them toward, particularly in an instance of hallucinated data. To the latter point, Barr told me that this is part of what Axonis is designed to address. “You can’t just take the sensor data and throw it into Claude and be like, ‘Alright, go make a decision for me.’ You need to set guard rails,” he said.
As to the former point, Barr told me the chat includes a disclaimer reminding its users that AI can make mistakes, and that the company trains its customers on how LLM technology works. “At the end of the day, it’s a tool, not a decider,” he said, although he allowed that it might be used to automatically trigger warning lights, sirens, or barriers, such as closing a flooded roadway.
I also posed the concern about complacency to Ali Mostafavi, a professor who supervises the UrbanResilience.AL Lab at Texas A&M, which researches, among other things, how artificial intelligence might be utilized in emergency contexts. Mostafavi agreed that there is always a risk in cognitive outsourcing, but that there is a “counter-argument that is also valid — that without these technologies, we have seen what can happen. We had the catastrophic floods last year in Kerr County, and if a similar technology had existed back then, an automated system could have identified the flash flood, and many young children would be alive today.”
Still, Barr told me he isn’t aware of Axonis advising in an actual evacuation order yet. While it is operational, the predictive model remains untested against its highest-stakes use case: the extremes of a climate-changed world, where formerly unthinkable outcomes may be one storm away.
“The more we can stress-test these technologies in real operational settings and use that feedback loop to improve the technologies, the better,” Mostafavi said. “But that’s easier said than done, because to have a technology implemented in an operational setting it should already be stress-tested, right?”
Bertha, though, was not that reckoning; the gusty squalls blew through Galveston last week without even disturbing the dinner reservations at the marina. But although it was already back to 90 and sunny by Monday morning on the Texas Gulf, the drainage in Galveston County, as in many places around the country, remains outdated and easily overwhelmed. One day, inevitably, the water will come. Hopefully when it does, someone or something will be watching.
The large renewables developer changes tack “in response to federal energy objectives.”
Trump’s solar freeze is now so tough that at least one renewable energy developer has asked his administration to turn their permitting application into a data center and gas-fired power plant instead.
Renew Development HoldCo – an LLC created by Clearway Energy Group – wrote the Bureau of Land Management in April asking if they could amend their 2021 application to build the Amber solar project, a 500-megawatt solar project in the Nevada desert that would require building on federal land. Their requested change? “[T]o formally remove the proposed solar facility and replace it with the development of a proposed data center and natural gas facility,” according to a copy of the letter I obtained.
“This amendment is the result of a shift in our internal development priorities and an updated assessment of project timing, in order to better align with the goals of our Administration,” reads the letter, which is dated April 3 and signed by Clearway’s chief development officer John Woody. “The data center concept is in exploratory early stages and as such has a longer and more flexible development horizon, and we believe its schedule will better align with the Bureau’s current workload and staffing plans.”
Now, this swap is somewhat shocking but shouldn’t exactly be a surprise. Companies with federal energy leases are struggling to get their renewable projects permitted by a hostile Trump administration. We’ve already seen some offshore wind developers ditch their leases in favor of payouts and commitments to build more fossil infrastructure. Clearway Energy Group is owned by Global Infrastructure Partners and TotalEnergies, the latter of which struck such a deal in March.
But this does appear to represent an aberration for Clearway, one of the nation’s largest operators of renewable energy projects and whose marketing materials primarily focus on “clean energy.” Nearly all of the company’s portfolio is carbon-free power or energy storage generation sans a handful of “flexible generation” energy projects in California, according to an online map of their project pipeline. The company did not disclose in the documents I reviewed if the gas plant itself would power the data center, provide power to the wider grid, or both.
Candidly, I’ve been watching like a hawk to see if Trump’s chokehold on solar and wind permits would lead to more gas infrastructure and data centers on federal property instead. And companies are getting data center permits when they ask to swap out their solar farm for AI infrastructure. On Friday, I reported that a joint venture involving renewables developer Arevon and energy trader Bill Perkins got permission from BLM to switch an environmental permit tied to a solar farm for one allowing a new data center. Environmentalists plan to legally challenge BLM’s determination as they say it’s a test case for the future of federal land policy.
It’s unclear if Clearway would be the one to build and construct this hypothetical data center and power plant. I for one can’t find any evidence of Clearway developing data centers before. My best guess is that if they do move forward with this, it would look like the joint venture I covered on Friday, where Arevon distanced itself from the actual day-to-day operations of the development and a new firm specializing in data centers came in. But that’s just a hunch and there’s a saying about assumptions.
Nevertheless, Clearway is clearly handling the permitting side. Attached to the Clearway letter was an application also sent to BLM for constructing utility and telecommunications facilities on federal lands, a document technically known as an SF299. The application states Clearway considered using solar energy for the data center as well as using private land, but their alternative designs weren’t selected because they had “higher environmental and stakeholder conflicts.”
Also, in a section of the document requesting Clearway provide a “statement of need for the project,” the developer said it was submitting this proposal “in response to federal energy objectives” and specifically cited Trump’s Day 1 executive order which the company said “encourage[d] development of reliable energy projects on federal lands.”
I reached out to Clearway asking for more information on the letter and application. In response, the company claimed the solar project wasn’t being killed – it simply was moved to private land. They also declined to comment on the data center and gas project. Instead, I was provided a statement attributable to an unnamed spokesperson that “while we do not comment on any individual application while it moves through federal approval processes, we are pleased to be advancing more than 4 GW of solar and battery resources in Nevada on private and public lands and expect those projects to deliver tremendous economic benefits to the communities where they’re built.”
“Clearway values its strong working partnership with the BLM, its Southern Nevada office, and also with state and local interests in Nevada. Across all of these relationships, we continuously assess how best to develop and deliver infrastructure that meets needs and aligns with local and national policies and goals.”
Current conditions: Hurricane Genevieve formed into the first major storm of the season, strengthening to Category 4 off Mexico’s Pacific Coast on Sunday but steering clear of any land for now • Hurricane Fausto, meanwhile, is weakening as it heads toward Hawaii • China evacuated hundreds of thousands of people as Typhoon Noul made landfall.

Wildfires in France and Spain forced roughly 300,000 people to evacuate their homes in what the French Interior Minister Laurent Nuñez called an “unprecedented” blaze. In Spain, the central western province of Avila suffered what the broadcaster France24 described as its “worst blaze in recent history” as Prime Minister Pedro Sanchez directly linked the disaster to climate change. By Sunday evening, in France, flames had come within nine miles of the southwestern city of Bordeaux in the heart of the nation's storied winelands as President Emmanuel Macron vowed to “rebuild.” Others saw the disaster as a sign of overdue lifestyle and infrastructure changes in the face of a warming planet. In Le Monde, the newspaper of record, the philosopher Cynthia Fleury and the Socialist mayor of the town of Saint-Médard-en-Jalles, Stéphane Delpeyrat-Vincen, argued: “What is burning is not just forests, but a way of inhabiting the land that is no longer possible.” The fires come weeks after a series of historic heat waves in Europe, including the hottest June on record, which made tinderboxes of parched woodlands.
President Donald Trump last week announced a landmark deal with Saudi Arabia to help build the kingdom’s first nuclear power station, besting the Russians and the Chinese in a race to tap into one of the world’s most coveted new export markets for atomic power technology. While the White House has yet to release all the details on the geopolitically meteoric agreement with Riyadh, sources with knowledge of the deal have confirmed to me what’s been reported elsewhere — that the deal will almost certainly include new large-scale Westinghouse AP1000s. Over the weekend, The New York Times identified another element to the partnership: Trump’s family and personal friends may benefit. The newspaper pointed to ties between a firm owned by Secretary of Commerce Howard Lutnick’s sons and Westinghouse; links between Eric Trump and Donald Trump Jr.’s investments into quantum computing and former Texas Governor Rick Perry’s Fermi America project to build AP1000s in Texas; and suggested that TAE Technologies, the fusion company merging with the corporate parent of Trump’s Truth Social platform, could see potential benefits from the Saudi deal. “There is no evidence at this point that Mr. Trump’s friends or family helped orchestrate the Saudi nuclear deal,” reporters Eric Lipton and Kate Kelly wrote. “Yet a number of the president’s allies and relatives, including members of his cabinet, stand to benefit if his big bet on nuclear power pays off. Certain investors with ties to these deals are positioned to profit, even if the delivery of large new loads of nuclear-powered electricity remains years away.”
The Trump administration is, in fact, making a real attempt at building new AP1000s at home. As my colleague Robinson Meyer wrote last month, a major Department of Energy deal would help utilities buy the parts needed to build more Westinghouse reactors.
Chip giant Nvidia is considering providing a $250 billion backstop to fund OpenAI’s data center project in southern Ohio, The Wall Street Journal reported on Sunday. The deal would guarantee up to half of the capital needed to lease SoftBank’s 10-gigawatt data center to supply computing power to the ChatGPT maker.
GE Vernova’s backlog of orders for gas turbines, meanwhile, now stretches to 2031 and accounts for a cumulative 116 gigawatts of power-producing capacity. In its latest earnings call, covered in Utility Dive at the end of last week, the company posted double-digit revenue and order growth in the division that supplies equipment for gas, hydro, nuclear, and grid facilities.
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Back in February, I told you that Japan was stepping up its efforts to extract rare earths from seabed minerals. On Friday, Tokyo confirmed it had discovered that medium and heavy rare earth elements accounted for about 54% of the rare earths mined from mud recovered from a remote Pacific island, Mining.com reported. The finds come after the government-backed vessel Chikyu sucked nearly 50 metric tons of mud from Minamitori Island, an uninhabited atoll located closer to Wake Island than Tokyo. Heavy rare earths, such as dysprosium, terbium, and yttrium — and medium rare earths such as samarium, europium, and gadolinium — are trickier to process. China controls the market for both categories by a wider margin than for light rare earths. That makes Japan’s discovery so exciting. Separating metals out of the mud could be an easier process than from other ores, potentially supplying the democratic world with a new source of non-Chinese minerals.
When the Biden administration tried putting rules in place for producing clean hydrogen, as my colleague Emily Pontecorvo explained nicely at the time, the regulations posed a problem for efforts to make fuel through nuclear-powered electrolysis. That’s because the incentives to ensure developers built new solar and wind rather than cannibalizing existing grid resources for hydrogen production made it impossible for nuclear reactors to qualify. Companies such as Constellation Energy, which had the nation’s leading experiment in nuclear-powered hydrogen production, protested. It all turned out to be for nought, since Trump ultimately wiped out the tax credits. As with so much nuclear technology that faces political tumult in America, South Korea is moving in to try its hand at hydrogen fuel production. Korea Hydro & Nuclear Power, the country’s state-owned nuclear giant, said it will launch a pilot program to produce hydrogen using heat and electricity from reactors, Hydrogen Insight reported last week.
India, meanwhile, is beefing up its plans for small modular reactors. Earlier this month, I reminded you about New Delhi’s plans to open its nuclear sector to foreign investments after years of icing out all but Russia’s state nuclear vendor. That isn’t to say India isn’t looking to continue building its own indigenously-designed units. On Friday, NucNet reported that the country plans to develop and operate at least five of its own SMR designs by 2033.
Last week, Heatmap editorial fellow Ameya Hadap broke news that Koloma, a startup seeking to spur natural production of hydrogen, had inked a deal to look for gas deposits across 817 square miles of the Philippines’ largest island, Luzon. It’s not the only subsurface search for clean energy. Last week, the country’s Economy and Development Council approved the Philippines’ first financing package to de-risk geothermal investments, Think Geo Energy reported.