Google’s electricity demand is skyrocketing

We got two big pieces of energy news from Google this week. The company announced that it’s signed an agreement to purchase electricity from a fusion company’s forthcoming first power plant. Google also released its latest environmental report, which shows that its energy use from data centers has doubled since 2020.

Taken together, these two bits of news offer a fascinating look at just how desperately big tech companies are hunting for clean electricity to power their data centers as energy demand and emissions balloon in the age of AI. Of course, we don’t know exactly how much of this pollution is attributable to AI because Google doesn’t break that out. (Also a problem!) So, what’s next and what does this all mean? 

Let’s start with fusion: Google’s deal with Commonwealth Fusion Systems is intended to provide the tech giant with 200 megawatts of power. This will come from Commonwealth’s first commercial plant, a facility planned for Virginia that the company refers to as the Arc power plant. The agreement represents half its capacity.

What’s important to note here is that this power plant doesn’t exist yet. In fact, Commonwealth still needs to get its Sparc demonstration reactor, located outside Boston, up and running. That site, which I visited in the fall, should be completed in 2026.

(An aside: This isn’t the first deal between Big Tech and a fusion company. Microsoft signed an agreement with Helion a couple of years ago to buy 50 megawatts of power from a planned power plant, scheduled to come online in 2028. Experts expressed skepticism in the wake of that deal, as my colleague James Temple reported.)

Nonetheless, Google’s announcement is a big moment for fusion, in part because of the size of the commitment and also because Commonwealth, a spinout company from MIT’s Plasma Science and Fusion Center, is seen by many in the industry as a likely candidate to be the first to get a commercial plant off the ground. (MIT Technology Review is owned by MIT but is editorially independent.)

Google leadership was very up-front about the length of the timeline. “We would certainly put this in the long-term category,” said Michael Terrell, Google’s head of advanced energy, in a press call about the deal.

The news of Google’s foray into fusion comes just days after the tech giant’s release of its latest environmental report. While the company highlighted some wins, some of the numbers in this report are eye-catching, and not in a positive way.

Google’s emissions have increased by over 50% since 2019, rising 6% in the last year alone. That’s decidedly the wrong direction for a company that’s set a goal to reach net-zero greenhouse-gas emissions by the end of the decade.

It’s true that the company has committed billions to clean energy projects, including big investments in next-generation technologies like advanced nuclear and enhanced geothermal systems. Those deals have helped dampen emissions growth, but it’s an arguably impossible task to keep up with the energy demand the company is seeing.

Google’s electricity consumption from data centers was up 27% from the year before. It’s doubled since 2020, reaching over 30 terawatt-hours. That’s nearly the annual electricity consumption from the entire country of Ireland.

As an outsider, it’s tempting to point the finger at AI, since that technology has crashed into the mainstream and percolated into every corner of Google’s products and business. And yet the report downplays the role of AI. Here’s one bit that struck me:

“However, it’s important to note that our growing electricity needs aren’t solely driven by AI. The accelerating growth of Google Cloud, continued investments in Search, the expanding reach of YouTube, and more, have also contributed to this overall growth.”

There is enough wiggle room in that statement to drive a large electric truck through. When I asked about the relative contributions here, company representative Mara Harris said via email that they don’t break out what portion comes from AI. When I followed up asking if the company didn’t have this information or just wouldn’t share it, she said she’d check but didn’t get back to me.

I’ll make the point here that we’ve made before, including in our recent package on AI and energy: Big companies should be disclosing more about the energy demands of AI. We shouldn’t be guessing at this technology’s effects.

Google has put a ton of effort and resources into setting and chasing ambitious climate goals. But as its energy needs and those of the rest of the industry continue to explode, it’s obvious that this problem is getting tougher, and it’s also clear that more transparency is a crucial part of the way forward.

This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here.

It’s officially summer, and the grid is stressed

It’s crunch time for the grid this week. As I’m writing this newsletter, it’s 100 °F (nearly 38 °C) here in New Jersey, and I’m huddled in the smallest room in my apartment with the shades drawn and a single window air conditioner working overtime.  

Large swaths of the US have seen brutal heat this week, with multiple days in a row nearing or exceeding record-breaking temperatures. Spain recently went through a dramatic heat wave too, as did the UK, which is unfortunately bracing for another one soon. As I’ve been trying to stay cool, I’ve had my eyes on a website tracking electricity demand, which is also hitting record highs. 

We rely on electricity to keep ourselves comfortable, and more to the point, safe. These are the moments we design the grid for: when need is at its very highest. The key to keeping everything running smoothly during these times might be just a little bit of flexibility. 

While heat waves happen all over the world, let’s take my local grid as an example. I’m one of the roughly 65 million people covered by PJM Interconnection, the largest grid operator in the US. PJM covers Virginia, West Virginia, Ohio, Pennsylvania, and New Jersey, as well as bits of a couple of neighboring states.

Earlier this year, PJM forecast that electricity demand would peak at 154 gigawatts (GW) this summer. On Monday, just a few days past the official start of the season, the grid blew past that, averaging over 160 GW between 5 p.m. and 6 p.m. 

The fact that we’ve already passed both last year’s peak and this year’s forecasted one isn’t necessarily a disaster (PJM says the system’s total capacity is over 179 GW this year). But it is a good reason to be a little nervous. Usually, PJM sees its peak in July or August. As a reminder, it’s June. So we shouldn’t be surprised if we see electricity demand creep to even higher levels later in the summer.

It’s not just PJM, either. MISO, the grid that covers most of the Midwest and part of the US South, put out a notice that it expected to be close to its peak demand this week. And the US Department of Energy released an emergency order for parts of the Southeast, which allows the local utility to boost generation and skirt air pollution limits while demand is high.

This pattern of maxing out the grid is only going to continue. That’s because climate change is pushing temperatures higher, and electricity demand is simultaneously swelling (in part because of data centers like those that power AI). PJM’s forecasts show that the summer peak in 2035 could reach nearly 210 GW, well beyond the 179 GW it can provide today. 

Of course, we need more power plants to be built and connected to the grid in the coming years (at least if we don’t want to keep ancient, inefficient, expensive coal plants running, as we covered last week). But there’s a quiet strategy that could limit the new construction needed: flexibility.

The power grid has to be built for moments of the absolute highest demand we can predict, like this heat wave. But most of the time, a decent chunk of capacity that exists to get us through these peaks sits idle—it only has to come online when demand surges. Another way to look at that, however, is that by shaving off demand during the peak, we can reduce the total infrastructure required to run the grid. 

If you live somewhere that’s seen a demand crunch during a heat wave, you might have gotten an email from your utility asking you to hold off on running the dishwasher in the early evening or to set your air conditioner a few degrees higher. These are called demand response programs. Some utilities run more organized programs, where utilities pay customers to ramp down their usage during periods of peak demand.

PJM’s demand response programs add up to almost eight gigawatts of power—enough to power over 6 million homes. With these programs, PJM basically avoids having to fire up the equivalent of multiple massive nuclear power plants. (It did activate these programs on Monday afternoon during the hottest part of the day.)

As electricity demand goes up, building in and automating this sort of flexibility could go a long way to reducing the amount of new generation needed. One report published earlier this year found that if data centers agreed to have their power curtailed for just 0.5% of the time (around 40 hours out of a year of continuous operation), the grid could handle about 18 GW of new power demand in the PJM region without adding generation capacity. 

For the whole US, this level of flexibility would allow the grid to take on an additional 98 gigawatts of new demand without building any new power plants to meet it. To give you a sense of just how significant that would be, all the nuclear reactors in the US add up to 97 gigawatts of capacity.

Tweaking the thermostat and ramping down data centers during hot summer days won’t solve the demand crunch on their own, but it certainly won’t hurt to have more flexibility.

This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here.

Inside the US power struggle over coal

Coal power is on life support in the US. It used to carry the grid with cheap electricity, but now plants are closing left and right.

There are a lot of potential reasons to let coal continue its journey to the grave. Carbon emissions from coal plants are a major contributor to climate change. And those facilities are also often linked with health problems in nearby communities, as reporter Alex Kaufman explored in a new feature story on Puerto Rico’s only coal-fired power plant.

But the Trump administration wants to keep coal power alive, and the US Department of Energy recently ordered some plants to stay open past their scheduled closures. Here’s why there’s a power struggle over coal.

Coal used to be king in the US, but the country has dramatically reduced its dependence on the fuel over the past two decades. It accounted for about 20% of the electricity generated in 2024, down from roughly half in 2000.

While the demise of coal has been great for US emissions, the real driver is economics. Coal used to be the cheapest form of electricity generation around, but the fracking boom handed that crown to natural gas over a decade ago. And now, even cheaper wind and solar power is coming online in droves.

Economics was a major factor in the planned retirement of the J.H. Campbell coal plant in Michigan, which was set to close at the end of May, Dan Scripps, chair of the Michigan Public Service Commission, told the Washington Post.

Then, on May 23, US Energy Secretary Chris Wright released an emergency order that requires the plant to remain open. Wright’s order mandates 90 more days of operation, and the order can be extended past that, too. It states that the goal is to minimize the risk of blackouts and address grid security issues before the start of summer.

The DOE’s authority to require power plants to stay open is something that’s typically used in emergencies like hurricanes, rather than in response to something as routine as … seasons changing. 

It’s true that there’s growing concern in the US about meeting demand for electricity, which is rising for the first time after being basically flat for decades. (The recent rise is in large part due to massive data centers, like those needed to run AI. Have I mentioned we have a great package on AI and energy?)

And we are indeed heading toward summer, which is when the grid is stretched to its limits. In the New York area, the forecast high is nearly 100 °F (38 °C) for several days next week—I’ll certainly have my air conditioner on, and I’m sure I’ll soon be getting texts asking me to limit electricity use during times of peak demand.

But is keeping old coal plants open the answer to a stressed grid?

It might not be the most economical way forward. In fact, in almost every case today, it’s actually cheaper to build new renewables capacity than to keep existing coal plants running in the US, according to a 2023 report from Energy Innovation, an energy think tank. And coal is only getting more expensive—in an updated analysis, Energy Innovation found that three-quarters of coal plants saw costs rising faster than inflation between 2021 and 2024.

Granted, solar and wind aren’t always available, while coal plants can be fired up on demand. And getting new projects built and connected to the grid will take time (right now, there’s a huge backlog of renewable projects waiting in the interconnection queue). But some experts say we actually don’t need new generation that urgently anyway, if big electricity users can be flexible with their demand. 

And we’re already seeing batteries come to the rescue on the grid at times of stress. Between May 2024 and April 2025, US battery storage capacity increased by about 40%. When Texas faced high temperatures last month, batteries did a lot to help the state make it through without blackouts, as this Bloomberg story points out. Costs are falling, too; prices are about 19% lower in 2024 than they were in 2023. 

Even as the Trump administration is raising concerns about grid reliability, it’s moved to gut programs designed to get more electricity generation and storage online, like the tax credits that support wind, solar, and battery production and installation. 

This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here.

These new batteries are finding a niche

Lithium-ion batteries have some emerging competition: Sodium-based alternatives are starting to make inroads.

Sodium is more abundant on Earth than lithium, and batteries that use the material could be cheaper in the future. Building a new battery chemistry is difficult, mostly because lithium is so entrenched. But, as I’ve noted before, this new technology has some advantages in nooks and crannies. 

I’ve been following sodium-ion batteries for a few years, and we’re starting to see the chemistry make progress, though not significantly in the big category of electric vehicles. Rather, these new batteries are finding niches where they make sense, especially in smaller electric scooters and large energy storage installations. Let’s talk about what’s new for sodium batteries, and what it’ll take for the chemistry to really break out.

Two years ago, lithium prices were, to put it bluntly, bonkers. The price of lithium hydroxide (an ingredient used to make lithium-ion batteries) went from a little under $10,000 per metric ton in January 2021 to over $76,000 per metric ton in January 2023, according to data from Benchmark Mineral Intelligence.

More expensive lithium drives up the cost of lithium-ion batteries. Price spikes, combined with concerns about potential shortages, pushed a lot of interest in alternatives, including sodium-ion.

I wrote about this swelling interest for a 2023 story, which focused largely on vehicle makers in China and a few US startups that were hoping to get in on the game.

There’s one key point to understand here. Sodium-based batteries will need to be cheaper than lithium-based ones to have a shot at competing, especially for electric vehicles, because they tend to be worse on one key metric: energy density. A sodium-ion battery that’s the same size and weight as a lithium-ion one will store less energy, limiting vehicle range.

The issue is, as we’ve seen since that 2023 story, lithium prices—and the lithium-ion battery market—are moving targets. Prices for precursor materials have come back down since the early 2023 peak, with lithium hydroxide crossing below $9,000 per metric ton recently.

And as more and more battery factories are built, costs for manufactured products come down too, with the average price for a lithium-ion pack in 2024 dropping 20%—the biggest annual decrease since 2017, according to BloombergNEF.

I wrote about this potential difficulty in that 2023 story: “If sodium-ion batteries are breaking into the market because of cost and material availability, declining lithium prices could put them in a tough position.”

One researcher I spoke with at the time suggested that sodium-ion batteries might not compete directly with lithium-ion batteries but could instead find specialized uses where the chemistry made sense. Two years later, I think we’re starting to see what those are.

One growing segment that could be a big win for sodium-ion: electric micromobility vehicles, like scooters and three-wheelers. Since these vehicles tend to travel shorter distances at lower speeds than cars, the lower energy density of sodium-ion batteries might not be as big a deal.

There’s a great BBC story from last week that profiled efforts to put sodium-ion batteries in electric scooters. It focused on one Chinese company called Yadea, which is one of the largest makers of electric two- and three-wheelers in the world. Yadea has brought a handful of sodium-powered models to the market so far, selling about 1,000 of the scooters in the first three months of 2025, according to the company’s statement to the BBC. It’s early days, but it’s interesting to see this market emerging.

Sodium-ion batteries are also seeing significant progress in stationary energy storage installations, including some on the grid. (Again, if you’re not worried about carting the battery around and fitting it into the limited package of a vehicle, energy density isn’t so important.)

The Baochi Energy Storage Station that just opened in Yunnan province, China, is a hybrid system that uses both lithium-ion and sodium-ion batteries and has a capacity of 400 megawatt-hours. And Natron Energy in the US is among those targeting other customers for stationary storage, specifically going after data centers.

While smaller vehicles and stationary installations appear to be the early wins for sodium, some companies aren’t giving up on using the alternative for EVs as well. The Chinese battery giant CATL announced earlier this year that it plans to produce sodium-ion batteries for heavy-duty trucks under the brand name Naxtra Battery.

Ultimately, lithium is the juggernaut of the battery industry, and going head to head is going to be tough for any alternative chemistry. But sticking with niches that make sense could help sodium-ion make progress at a time when I’d argue we need every successful battery type we can get. 

This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here.

Over $1 billion in federal funding got slashed for this polluting industry

The clean cement industry might be facing the end of the road, before it ever really got rolling. 

On Friday, the US Department of Energy announced that it was canceling $3.7 billion in funding for 24 projects related to energy and industry. That included nearly $1.3 billion for cement-related projects.

Cement is a massive climate problem, accounting for roughly 7% of global greenhouse-gas emissions. What’s more, it’s a difficult industry to clean up, with huge traditional players and expensive equipment and infrastructure to replace. This funding was supposed to help address those difficulties, by supporting projects on the cusp of commercialization. Now companies will need to fill in the gap left by these cancellations, and it’s a big one. 

First up on the list for cuts is Sublime Systems, a company you’re probably familiar with if you’ve been reading this newsletter for a while. I did a deep dive last year, and the company was on our list of Climate Tech Companies to Watch in both 2023 and 2024.

The startup’s approach is to make cement using electricity. The conventional process requires high temperatures typically achieved by burning fossil fuels, so avoiding that could prevent a lot of emissions. 

In 2024, Sublime received an $87 million grant from the DOE to construct a commercial demonstration plant in Holyoke, Massachusetts. That grant would have covered roughly half the construction costs for the facility, which is scheduled to open in 2026 and produce up to 30,000 metric tons of cement each year. 

“We were certainly surprised and disappointed about the development,” says Joe Hicken, Sublime’s senior VP of business development and policy. Customers are excited by the company’s technology, Hicken adds, pointing to Sublime’s recently announced deal with Microsoft, which plans to buy up to 622,500 metric tons of cement from the company. 

Another big name, Brimstone, also saw its funding affected. That award totaled $189 million for a commercial demonstration plant, which was expected to produce over 100,000 metric tons of cement annually. 

In a statement, a Brimstone representative said the company believes the cancellation was a “misunderstanding.” The statement pointed out that the planned facility would make not only cement but also alumina, supporting US-based aluminum production. (Aluminum is classified as a critical mineral by the US Geological Survey, meaning it’s considered crucial to the US economy and national security.) 

An award to Heidelberg Materials for up to $500 million for a planned Indiana facility was also axed. The idea there was to integrate carbon capture and storage to clean up emissions from the plant, which would have made it the first cement plant in the US to demonstrate that technology. In a written statement, a representative said the decision can be appealed, and the company is considering that option.

And National Cement’s funding for the Lebec Net-Zero Project, another $500 million award, was canceled. That facility planned to make carbon-neutral cement through a combination of strategies: reducing the polluting ingredients needed, using alternative fuels like biomass, and capturing the plant’s remaining emissions. 

“We want to emphasize that this project will expand domestic manufacturing capacity for a critical industrial sector, while also integrating new technologies to keep American cement competitive,” said a company spokesperson in a written statement. 

There’s a sentiment here that’s echoed in all the responses I received: While these awards were designed to cut emissions, these companies argue that they can fit into the new administration’s priorities. They’re emphasizing phrases like “critical minerals,” “American jobs,” and “domestic supply chains.” 

“We’ve heard loud and clear from the Trump administration the desire to displace foreign imports of things that can be made here in America,” Sublime’s Hicken says. “At the end of the day, what we deliver is what the policymakers in DC are looking for.” 

But this administration is showing that it’s not supporting climate efforts—often even those that also advance its stated goals of energy abundance and American competitiveness. 

On Monday, my colleague James Temple published a new story about cuts to climate research, including tens of millions of dollars in grants from the National Science Foundation. Researchers at Harvard were particularly hard hit. 

Even as there’s interest in advancing the position of the US on the world’s stage, these cuts are making it hard for researchers and companies alike to do the crucial work of understanding our climate and developing and deploying new technologies. 

This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here.

What will power AI’s growth?

It’s been a little over a week since we published Power Hungry, a package that takes a hard look at the expected energy demands of AI. Last week in this newsletter, I broke down the centerpiece of that package, an analysis I did with my colleague James O’Donnell. (In case you’re still looking for an intro, you can check out this Roundtable discussion with James and our editor in chief Mat Honan, or this short segment I did on Science Friday.)

But this week, I want to talk about another story that I also wrote for that package, which focused on nuclear energy. I thought this was an important addition to the mix of stories we put together, because I’ve seen a lot of promises about nuclear power as a saving grace in the face of AI’s energy demand. My reporting on the industry over the past few years has left me a little skeptical. 

As I discovered while I continued that line of reporting, building new nuclear plants isn’t so simple or so fast. And as my colleague David Rotman lays out in his story for the package, the AI boom could wind up relying on another energy source: fossil fuels. So what’s going to power AI? Let’s get into it. 

When we started talking about this big project on AI and energy demand, we had a lot of conversations about what to include. And from the beginning, the climate team was really focused on examining what, exactly, was going to be providing the electricity needed to run data centers powering AI models. As we wrote in the main story: 

“A data center humming away isn’t necessarily a bad thing. If all data centers were hooked up to solar panels and ran only when the sun was shining, the world would be talking a lot less about AI’s energy consumption.” 

But a lot of AI data centers need to be available constantly. Those that are used to train models can arguably be more responsive to the changing availability of renewables, since that work can happen in bursts, any time. Once a model is being pinged with questions from the public, though, there needs to be computing power ready to run all the time. Google, for example, would likely not be too keen on having people be able to use its new AI Mode only during daylight hours.

Solar and wind power, then, would seem not to be a great fit for a lot of AI electricity demand, unless they’re paired with energy storage—and that increases costs. Nuclear power plants, on the other hand, tend to run constantly, outputting a steady source of power for the grid. 

As you might imagine, though, it can take a long time to get a nuclear power plant up and running. 

Large tech companies can help support plans to reopen shuttered plants or existing plants’ efforts to extend their operating lifetimes. There are also some existing plants that can make small upgrades to improve their output. I just saw this news story from the Tri-City Herald about plans to upgrade the Columbia Generating Station in eastern Washington—with tweaks over the next few years, it could produce an additional 162 megawatts of power, over 10% of the plant’s current capacity. 

But all that isn’t going to be nearly enough to meet the demand that big tech companies are claiming will materialize in the future. (For more on the numbers here and why new tech isn’t going to come online fast enough, check out my full story.) 

Instead, natural gas has become the default to meet soaring demand from data centers, as David lays out in his story. And since the lifetime of plants built today is about 30 years, those new plants could be running past 2050, the date the world needs to bring greenhouse-gas emissions to net zero to meet the goals set out in the Paris climate agreement. 

One of the bits I found most interesting in David’s story is that there’s potential for a different future here: Big tech companies, with their power and influence, could actually use this moment to push for improvements. If they reduced their usage during peak hours, even for less than 1% of the year, it could greatly reduce the amount of new energy infrastructure required. Or they could, at the very least, push power plant owners and operators to install carbon capture technology, or ensure that methane doesn’t leak from the supply chain.

AI’s energy demand is a big deal, but for climate change, how we choose to meet it is potentially an even bigger one. 

Three takeaways about AI’s energy use and climate impacts

This week, we published Power Hungry, a package all about AI and energy. At the center of this package is the most comprehensive look yet at AI’s growing power demand, if I do say so myself. 

This data-heavy story is the result of over six months of reporting by me and my colleague James O’Donnell (and the work of many others on our team). Over that time, with the help of leading researchers, we quantified the energy and emissions impacts of individual queries to AI models and tallied what it all adds up to, both right now and for the years ahead. 

There’s a lot of data to dig through, and I hope you’ll take the time to explore the whole story. But in the meantime, here are three of my biggest takeaways from working on this project. 

1. The energy demands of AI are anything but constant. 

If you’ve heard estimates of AI’s toll, it’s probably a single number associated with a query, likely to OpenAI’s ChatGPT. One popular estimate is that writing an email with ChatGPT uses 500 milliliters (or roughly a bottle) of water. But as we started reporting, I was surprised to learn just how much the details of a query can affect its energy demand. No two queries are the same—for several reasons, including their complexity and the particulars of the model being queried.

One key caveat here is that we don’t know much about “closed source” models—for these, companies hold back the details of how they work. (OpenAI’s ChatGPT and Google’s Gemini are examples.) Instead, we worked with researchers who measured the energy it takes to run open-source AI models, for which the source code is publicly available. 

But using open-source models, it’s possible to directly measure the energy used to respond to a query rather than just guess. We worked with researchers who generated text, images, and video and measured the energy required for the chips the models are based on to perform the task.  

Even just within the text responses, there was a pretty large range of energy needs. A complicated travel itinerary consumed nearly 10 times as much energy as a simple request for a few jokes, for example. An even bigger difference comes from the size of the model used. Larger models with more parameters used up to 70 times more energy than smaller ones for the same prompts. 

As you might imagine, there’s also a big difference between text, images, or video. Videos generally took hundreds of times more energy to generate than text responses. 

2. What’s powering the grid will greatly affect the climate toll of AI’s energy use. 

As the resident climate reporter on this project, I was excited to take the expected energy toll and translate it into an expected emissions burden. 

Powering a data center with a nuclear reactor or a whole bunch of solar panels and batteries will not affect our planet the same way as burning mountains of coal. To quantify this idea, we used a figure called carbon intensity, a measure of how dirty a unit of electricity is on a given grid. 

We found that the same exact query, with the same exact energy demand, will have a very different climate impact depending on what the data center is powered by, and that depends on the location and the time of day. For example, querying a data center in West Virginia could cause nearly twice the emissions of querying one in California, according to calculations based on average data from 2024.

This point shows why it matters where tech giants are building data centers, what the grid looks like in their chosen locations, and how that might change with more demand from the new infrastructure. 

3. There is still so much that we don’t know when it comes to AI and energy. 

Our reporting resulted in estimates that are some of the most specific and comprehensive out there. But ultimately, we still have no idea what many of the biggest, most influential models are adding up to in terms of energy and emissions. None of the companies we reached out to were willing to provide numbers during our reporting. Not one.

Adding up our estimates can only go so far, in part because AI is increasingly everywhere. While today you might generally have to go to a dedicated site and type in questions, in the future AI could be stitched into the fabric of our interactions with technology. (See my colleague Will Douglas Heaven’s new story on Google’s I/O showcase: “By putting AI into everything, Google wants to make it invisible.”)

AI could be one of the major forces that shape our society, our work, and our power grid. Knowing more about its consequences could be crucial to planning our future. 

To dig into our reporting, give the main story a read. And if you’re looking for more details on how we came up with our numbers, you can check out this behind-the-scenes piece.

There are also some great related stories in this package, including one from James Temple on the data center boom in the Nevada desert, one from David Rotman about how AI’s rise could entrench natural gas, and one from Will Douglas Heaven on a few technical innovations that could help make AI more efficient. Oh, and I also have a piece on why nuclear isn’t the easy answer some think it is. 

Find them, and the rest of the stories in the package, here. 

This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here.

How US research cuts are threatening crucial climate data

Over the last few months, and especially the last few weeks, there’s been an explosion of news about proposed budget cuts to science in the US. One trend I’ve noticed: Researchers and civil servants are sounding the alarm that those cuts mean we might lose key data that helps us understand our world and how climate change is affecting it.

My colleague James Temple has a new story out today about researchers who are attempting to measure the temperature of mountain snowpack across the western US. Snow that melts in the spring is a major water source across the region, and monitoring the temperature far below the top layer of snow could help scientists more accurately predict how fast water will flow down the mountains, allowing farmers, businesses, and residents to plan accordingly.

But long-running government programs that monitor the snowpack across the West are among those being threatened by cuts across the US federal government. Also potentially in trouble: carbon dioxide measurements in Hawaii, hurricane forecasting tools, and a database that tracks the economic impact of natural disasters. It’s all got me thinking: What do we lose when data is in danger?

Take for example the work at Mauna Loa Observatory, which sits on the northern side of the world’s largest active volcano. In this Hawaii facility, researchers have been measuring the concentration of carbon dioxide in the atmosphere since 1958.

The resulting graph, called the Keeling Curve (after Charles David Keeling, the scientist who kicked off the effort) is a pillar of climate research. It shows that carbon dioxide, the main greenhouse gas warming the planet, has increased in the atmosphere from around 313 parts per million in 1958 to over 420 parts per million today.

Proposed cuts to the National Oceanic and Atmospheric Administration (NOAA) jeopardize the Keeling Curve’s future. As Ralph Keeling (current steward of the curve and Keeling’s son) put it in a new piece for Wired, “If successful, this loss will be a nightmare scenario for climate science, not just in the United States, but the world.”

This story has echoes across the climate world right now. A lab at Princeton that produces what some consider the top-of-the-line climate models used to make hurricane forecasts could be in trouble because of NOAA budget cuts. And last week, NOAA announced it would no longer track the economic impact of the biggest natural disasters in the US.

Some of the largest-scale climate efforts will feel the effects of these cuts, and as James’s new story shows, they could also seep into all sorts of specialized fields. Even seemingly niche work can have a huge impact not just on research, but on people.

The frozen reservoir of the Sierra snowpack provides about a third of California’s groundwater, as well as the majority used by towns and cities in northwest Nevada. Researchers there are hoping to help officials better forecast the timing of potential water supplies across the region.

This story brought to mind my visit to El Paso, Texas, a few years ago. I spoke with farmers there who rely on water coming down the Rio Grande, alongside dwindling groundwater, to support their crops. There, water comes down from the mountains in Colorado and New Mexico in the spring and is held in the Elephant Butte Reservoir. One farmer I met showed me pages and pages of notes of reservoir records, which he had meticulously copied by hand. Those crinkled pages were a clear sign: Publicly available data was crucial to his work.

The endeavor of scientific research, particularly when it involves patiently gathering data, isn’t always exciting. Its importance is often overlooked. But as cuts continue, we’re keeping a lookout, because losing data could harm our ability to track, address, and adapt to our changing climate. 

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Did solar power cause Spain’s blackout?

At roughly midday on Monday, April 28, the lights went out in Spain. The grid blackout, which extended into parts of Portugal and France, affected tens of millions of people—flights were grounded, cell networks went down, and businesses closed for the day.

Over a week later, officials still aren’t entirely sure what happened, but some (including the US energy secretary, Chris Wright) have suggested that renewables may have played a role, because just before the outage happened, wind and solar accounted for about 70% of electricity generation. Others, including Spanish government officials, insisted that it’s too early to assign blame.

It’ll take weeks to get the full report, but we do know a few things about what happened. And even as we wait for the bigger picture, there are a few takeaways that could help our future grid.

Let’s start with what we know so far about what happened, according to the Spanish grid operator Red Eléctrica:

• A disruption in electricity generation took place a little after 12:30 p.m. This may have been a power plant flipping off or some transmission equipment going down.
• A little over a second later, the grid lost another bit of generation.
• A few seconds after that, the main interconnector between Spain and southwestern France got disconnected as a result of grid instability.
• Immediately after, virtually all of Spain’s electricity generation tripped offline.

One of the theories floating around is that things went wrong because the grid diverged from its normal frequency. (All power grids have a set frequency: In Europe the standard is 50 hertz, which means the current switches directions 50 times per second.) The frequency needs to be constant across the grid to keep things running smoothly.

There are signs that the outage could be frequency-related. Some experts pointed out that strange oscillations in the grid frequency occurred shortly before the blackout.

Normally, our grid can handle small problems like an oscillation in frequency or a drop that comes from a power plant going offline. But some of the grid’s ability to stabilize itself is tied up in old ways of generating electricity.

Power plants like those that run on coal and natural gas have massive rotating generators. If there are brief issues on the grid that upset the balance, those physical bits of equipment have inertia: They’ll keep moving at least for a few seconds, providing some time for other power sources to respond and pick up the slack. (I’m simplifying here—for more details I’d highly recommend this report from the National Renewable Energy Laboratory.)

Solar panels don’t have inertia—they rely on inverters to change electricity into a form that’s compatible with the grid and matches its frequency. Generally, these inverters are “grid-following,” meaning if frequency is dropping, they follow that drop.

In the case of the blackout in Spain, it’s possible that having a lot of power on the grid coming from sources without inertia made it more possible for a small problem to become a much bigger one.

Some key questions here are still unanswered. The order matters, for example. During that drop in generation, did wind and solar plants go offline first? Or did everything go down together?

Whether or not solar and wind contributed to the blackout as a root cause, we do know that wind and solar don’t contribute to grid stability in the same way that some other power sources do, says Seaver Wang, climate lead of the Breakthrough Institute, an environmental research organization. Regardless of whether renewables are to blame, more capability to stabilize the grid would only help, he adds.

It’s not that a renewable-heavy grid is doomed to fail. As Wang put it in an analysis he wrote last week: “This blackout is not the inevitable outcome of running an electricity system with substantial amounts of wind and solar power.”

One solution: We can make sure the grid includes enough equipment that does provide inertia, like nuclear power and hydropower. Reversing a plan to shut down Spain’s nuclear reactors beginning in 2027 would be helpful, Wang says. Other options include building massive machines that lend physical inertia and using inverters that are “grid-forming,” meaning they can actively help regulate frequency and provide a sort of synthetic inertia.

Inertia isn’t everything, though. Grid operators can also rely on installing a lot of batteries that can respond quickly when problems arise. (Spain has much less grid storage than other places with a high level of renewable penetration, like Texas and California.)

Ultimately, if there’s one takeaway here, it’s that as the grid evolves, our methods to keep it reliable and stable will need to evolve too.

If you’re curious to hear more on this story, I’d recommend this Q&A from Carbon Brief about the event and its aftermath and this piece from Heatmap about inertia, renewables, and the blackout.

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A long-abandoned US nuclear technology is making a comeback in China

China has once again beat everyone else to a clean energy milestone—its new nuclear reactor is reportedly one of the first to use thorium instead of uranium as a fuel and the first of its kind that can be refueled while it’s running.

It’s an interesting (if decidedly experimental) development out of a country that’s edging toward becoming the world leader in nuclear energy. China has now surpassed France in terms of generation, though not capacity; it still lags behind the US in both categories. But one recurring theme in media coverage about the reactor struck me, because it’s so familiar: This technology was invented decades ago, and then abandoned.

You can basically copy and paste that line into countless stories about today’s advanced reactor technology. Molten-salt cooling systems? Invented in the mid-20th century but never commercialized. Same for several alternative fuels, like TRISO. And, of course, there’s thorium.

This one research reactor in China running with an alternative fuel says a lot about this moment for nuclear energy technology: Many groups are looking into the past for technologies, with a new appetite for building them.

First, it’s important to note that China is the hot spot for nuclear energy right now. While the US still has the most operational reactors in the world, China is catching up quickly. The country is building reactors at a remarkable clip and currently has more reactors under construction than any other country by far. Just this week, China approved 10 new reactors, totaling over $27 billion in investment.

China is also leading the way for some advanced reactor technologies (that category includes basically anything that deviates from the standard blueprint of what’s on the grid today: large reactors that use enriched uranium for fuel and high-pressure water to keep the reactor cool). High-temperature reactors that use gas as a coolant are one major area of focus for China—a few reactors that use this technology have recently started up, and more are in the planning stages or under construction.

Now, Chinese state media is reporting that scientists in the country reached a milestone with a thorium-based reactor. The reactor came online in June 2024, but researchers say it recently went through refueling without shutting down. (Conventional reactors generally need to be stopped to replenish the fuel supply.) The project’s lead scientists shared the results during a closed meeting at the Chinese Academy of Sciences.

I’ll emphasize here that this isn’t some massive power plant: This reactor is tiny. It generates just two megawatts of heat—less than the research reactor on MIT’s campus, which rings in at six megawatts. (To be fair, MIT’s is one of the largest university research reactors in the US, but still … it’s small.)

Regardless, progress is progress for thorium reactors, as the world has been entirely focused on uranium for the last 50 years or so.

Much of the original research on thorium came out of the US, which pumped resources into all sorts of different reactor technologies in the 1950s and ’60s. A reactor at Oak Ridge National Laboratory in Tennessee that ran in the 1960s used Uranium-233 fuel (which can be generated when thorium is bombarded with radiation).

Eventually, though, the world more or less settled on a blueprint for nuclear reactors, focusing on those that use Uranium-238 as fuel and are cooled by water at a high pressure. One reason for the focus on uranium for energy tech? The research could also be applied to nuclear weapons.

But now there’s a renewed interest in alternative nuclear technologies, and the thorium-fueled reactor is just one of several examples. A prominent one we’ve covered before: Kairos Power is building reactors that use molten salt as a coolant for small nuclear reactors, also a technology invented and developed in the 1950s and ’60s before being abandoned. 

Another old-but-new concept is using high-temperature gas to cool reactors, as X-energy is aiming to do in its proposed power station at a chemical plant in Texas. (That reactor will be able to be refueled while it’s running, like the new thorium reactor.) 

Some problems from decades ago that contributed to technologies being abandoned will still need to be dealt with today. In the case of molten-salt reactors, for example, it can be tricky to find materials that can withstand the corrosive properties of super-hot salt. For thorium reactors, the process of transforming thorium into U-233 fuel has historically been one of the hurdles. 

But as early progress shows, the archives could provide fodder for new commercial reactors, and revisiting these old ideas could give the nuclear industry a much-needed boost. 

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