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Twenty-five years ago, computers were on the verge of destroying America’s energy system.
Or, at least, that’s what lots of smart people seemed to think.
In a 1999 Forbes article, a pair of conservative lawyers, Peter Huber and Mark Mills, warned that personal computers and the internet were about to overwhelm the fragile U.S. grid.
Information technology already devoured 8% to 13% of total U.S. power demand, Huber and Mills claimed, and that share would only rise over time. “It’s now reasonable to project,” they wrote, “that half of the electric grid will be powering the digital-Internet economy within the next decade.” (Emphasis mine.)
Over the next 18 months, investment banks including JP Morgan and Credit Suisse repeated the Forbes estimate of internet-driven power demand, advising their customers to pile into utilities and other electricity-adjacent stocks. Although it was unrelated, California’s simultaneous blackout crisis deepened the sense of panic. For a moment, experts were convinced: Data centers and computers would drain the country’s energy resources.
They could not have been more wrong. In fact, Huber and Mills had drastically mismeasured the amount of electricity used by PCs and the internet. Computing ate up perhaps 3% of total U.S. electricity in 1999, not the roughly 10% they had claimed. And instead of staring down a period of explosive growth, the U.S. electric grid was in reality facing a long stagnation. Over the next two decades, America’s electricity demand did not grow rapidly — or even, really, at all. Instead, it flatlined for the first time since World War II. The 2000s and 2010s were the first decades without “load growth,” the utility industry’s jargon for rising power demand, since perhaps the discovery of electricity itself.
Now that lull is ending — and a new wave of tech-driven concerns has overtaken the electricity industry. According to its supporters and critics alike, generative artificial intelligence like ChatGPT is about to devour huge amounts of electricity, enough to threaten the grid itself. “We still don’t appreciate the energy needs of this technology,” Sam Altman, the CEO of OpenAI, has said, arguing that the world needs a clean energy breakthrough to meet AI’s voracious energy needs. (He is investing in nuclear fusion and fission companies to meet this demand.) The Washington Post captured the zeitgeist with a recent story: America, it said, “is running out of power.”
But … is it actually? There is no question that America’s electricity demand is rising once again and that load growth, long in abeyance, has finally returned to the grid: The boom in new factories and the ongoing adoption of electric vehicles will see to that. And you shouldn’t bet against the continued growth of data centers, which have increased in size and number since the 1990s. But there is surprisingly little evidence that AI, specifically, is driving surging electricity demand. And there are big risks — for utility customers and for the planet — by treating AI-driven electricity demand as an emergency.
There is, to be clear, no shortage of predictions that AI will cause electricity demand to rise. According to a recent Reuters report, nine of the country’s 10 largest utilities are now citing the “surge” in power demand from data centers when arguing to regulators that they should build more power. Morgan Stanley projects that power use from data centers “is expected to triple globally this year,” according to the same report. The International Energy Agency more modestly — but still shockingly — suggests that electricity use from data centers, AI, and cryptocurrency could double by 2026.
These concerns have also come from environmentalists. A recent report from the Climate Action Against Disinformation Commission, a left-wing alliance of groups including Friends of the Earth and Greenpeace, warned that AI will require “massive amounts of energy and water” and called for aggressive regulation.
That report focused on the risks of an AI-addled social media public sphere, which progressives fear will be filled with climate-change-denying propaganda by AI-powered bots. But in an interview, Michael Khoo, an author of the report and a researcher at Friends of the Earth, told me that studying AI made him much more frightened about its energy use.
AI is such an power-suck that it “is causing America to run out of energy,” Khoo said. “I think that’s going to be much more disruptive than the disinformation conversation in the mid-term.” He sketched a scenario where Altman and Mark Zuckerberg can outbid ordinary households for electrons as AI proliferates across the economy. “I can see people going without power,” he said, “and there being massive social unrest.”
These predictions aren’t happening in a vacuum. At the same time that investment bankers and environmentalists have fretted over a potential electricity shortage, utilities across the South have proposed a de facto solution: a massive buildout of new natural-gas power plants.
Citing the return of load growth, utilities across the South are trying to go around normal regulatory channels and build a slew of new natural-gas-burning power plants. Across at least six states, utilities have already won — or are trying to win — permission from local governments to fast-track more than 10,000 megawatts of new gas-fired power plants so that they can meet the surge in demand.
These requests have popped up across the region, pushed by vertically integrated monopoly power companies. Georgia Power won a tentative agreement to build 1,400 new megawatts of gas capacity, Canary reported. In the Carolinas, Duke Energy has asked to build 9,000 megawatts of new gas capacity, triple what it previously requested. The Tennessee Valley Authority has plans to add 6,600 megawatts of new capacity to its grid.
This buildout is big enough to endanger the country’s climate targets. Although these utilities are also building new renewable and battery farms, and shutting down coal plants, the planned surge in carbon emissions from natural gas plants would erase the reductions from those changes, according to a Southern Environmental Law Center analysis. Duke Energy has already said that it will not meet its 2030 climate goal in order to conduct the gas expansion.
In the popular press, AI’s voracious energy demand is sometimes said to be a major driver of this planned gas boom. But evidence for that proposition is slim, and the utilities have said only that data center expansion is one of several reasons for the boom. The Southeast’s population is growing, and the region is experiencing a manufacturing renaissance, due in part to the new car, battery, and solar panel factories subsidized by Biden’s climate law. Utilities in the South also face a particular challenge coping with the coldest winter mornings because so many homes and offices use inefficient and power-hungry space heaters.
Indeed, it’s hard to talk about the drivers of load growth with any specificity — and it’s hard to know whether load growth will actually happen in all corners of the South.
Utilities compete against each other to secure big-name customers — much like local governments compete with sweetheart tax deals — so when a utility asks regulators to build more capacity, it doesn’t reveal where potential power demand is coming from. (In other words, it doesn’t reveal who it believes will eventually buy that power.) A company might float plans to build the same data center or factory in multiple states to shop around for the best rates, which means the same underlying gigawatts of demand may be appearing in several different utilities’ resource plans at the same time. In other words, utilities are unlikely to actually see all of the demand they’re now projecting.
Even if we did know exactly how many gigawatts of new demand each utility would see, it’s almost impossible to say how much of it is coming from AI. Utilities don’t say how much of their future projected power demand will come from planned factories versus data centers. Nor do they say what each data center does and whether it trains AI (or mines Bitcoin, which remains a far bigger energy suck).
The risk of focusing on AI, specifically, as a driver of load growth is that because it’s a hot new technology — one with national security implications, no less — it can rhetorically justify expensive emergency action that is actually not necessary at all. Utilities may very well need to build more power capacity in the years to come. But does that need constitute an emergency? Does it justify seeking special permission from their statehouses or regulators to build more gas, instead of going through the regular planning process? Is it worth accelerating approvals for new gas plants? Probably not. The real danger, in other words, is not that we’ll run out of power. It’s that we’ll build too much of the wrong kind.
At the same time, we might have been led astray by overly dire predictions of AI’s energy use. Jonathan Koomey, a researcher who studies how the internet and data centers use energy (and the namesake of Koomey’s Law) told me that many estimates of Nvidia’s most important AI chips assume that their energy use is the same as their advertised “rated” power. In reality, Nvidia chips probably use half of that amount, he said, because chipmakers engineer their chips to withstand more electricity than is necessary for safety reasons.
And this is just the current generation of chips: Nvidia’s next generation of AI-training chips, called “Blackwell,” use 25 times less energy to do the same amount of computation as the previous generation of chips.
Koomey helped defuse the last panic over energy use by showing that the estimates Huber and Mills relied on were wildly incorrect. Estimates now suggest that the internet used less than 1% of total U.S. electricity by the late 1990s, not 13% as they claimed. Those percentages stayed roughly the same through 2008, he later found, even as data centers grew and computers proliferated across the economy. That’s the same year, remember, that Huber and Mills predicted that the internet would consume half of American energy.
These bad predictions were extremely convenient. Mills was a scientific advisor to the Greening Earth Society, a fossil-fuel-industry-funded group that alleged carbon dioxide pollution would actually improve the global environment. He aimed to show that climate and environmental policy would conflict with the continued growth of the internet.
“Many electricity policy proposals are on a collision course with demand forces,” Mills said in a Greening Earth press release at the time. “While many environmentalists want to substantially reduce coal use in making electricity, there is no chance of meeting future economically-driven and Internet-accelerated electric demand without retaining and expanding the coal component.” Hence the headline of the Forbes piece: “The PCs are coming — Dig more coal.”
What makes today’s AI-induced fear frenzy different from 1999 is that the alarmed projections are not just coming from businesses and banks like Morgan Stanley, but from environmentalists like Friends of the Earth. Yet neither their estimates of near-term, AI-driven power shortages — nor the analysis from Morgan Stanley that U.S. data-center use could soon triple within a year — make sense given what we know about data centers, Koomey said. It is not logistically possible to triple data centers’ electricity use in one year. “There just aren’t enough people to build data centers, and it takes longer than a year to build a new data center anyway,” he said. “There aren’t enough generators, there aren’t enough transformers — the backlog for some equipment is 24 months. It’s a supply chain constraint.”
Look around and you might notice that we have many more servers and computers today than we did in 1999 — not to mention smartphones and tablets, which didn’t even exist then — and yet computing doesn’t devour half of American energy. It doesn’t even get close. Today, computers use 1% to 4% of total U.S. power demand, depending on which estimate you trust. That’s about the same share of total U.S. electricity demand that they used in the late 1990s and mid-2000s.
It may well be that AI devours more energy in years to come, but utilities probably do not need to deal with it by building more gas. They could install more batteries, build new power lines, or even pay some customers to reduce their electricity usage during certain peak events, such as cold winter storms.
There are some places where AI-driven energy demand could be a problem — Koomey cited Ireland and Loudon County, Virginia, as two epicenters. But even there, building more natural gas is not the sole way to cope with load growth.
“The problem with this debate is everybody is kind of right,” Daniel Tait, who researches Southern utilities for the Energy and Policy Institute, a consumer watchdog, told me. “Yes, AI will increase load a little bit, but probably not as much as you think. Yes, load is growing, but maybe not as much as you say. Yes, we do need to build stuff, but maybe not the stuff that you want.”
There are real risks if AI’s energy demands get overstated and utilities go on a gas-driven bender. The first is for the planet: Utilities might overbuild gas plants now, run them even though they’re non-economic, and blow through their climate goals.
“Utilities — especially the vertically integrated monopoles in the South — have every incentive to overstate load growth, and they have a pattern of having done that consistently,” Gudrun Thompson, a senior attorney at the Southern Environmental Law Center, told me. In 2017, the Rocky Mountain Institute, an energy think tank, found in 2017 that utilities systematically overestimated their peak demand when compiling forecasts. This makes sense: Utilities would rather build too much capacity than wind up with too little, especially when they can pass along the associated costs to rate-payers.
But the second risk is that utilities could burn through the public’s willingness to pay for grid upgrades. Over the next few years, utilities should make dozens of updates to their systems. They have to build new renewables, new batteries, and new clean 24/7 power, such as nuclear or geothermal. They will have to link their grids to their neighbors’ by building new transmission lines. All of that will be expensive, and it could require the kind of investment that raises electricity rates. But the public and politicians can accept only so many rate hikes before they rebel, and there’s a risk that utilities spend through that fuzzy budget on unnecessary and wasteful projects now, not on the projects that they’ll need in the future.
There is no question that AI will use more electricity in the years to come. But so will EVs, new factories, and other sources of demand. America is on track to use more electricity. If that becomes a crisis, it will be one of our own making.
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Plus, Google and Amazon report on what hyperscaling has done to their emissions.
There’s an interesting new report out today from the progressive think tank Groundwork Collaborative that makes a case for how Democrats can harness the artificial intelligence and data center boom to help the power grid — while also cutting costs for electricity customers.
But first, some news. We’ve known for some time now that artificial intelligence is transforming America’s biggest technology companies, turning them into major energy consumers and even quasi-industrial firms. Now we have even more evidence that it’s driving up their carbon emissions, too.
Google and Amazon released their annual sustainability reports yesterday, and both show huge surges in their energy use and climate pollution. Google’s greenhouse gas pollution grew by 18% last year, its largest year-over-year jump on record, and its energy use leapt by 37%. The company’s energy use rose by more than a quarter last year; it now uses roughly 3.5 times as much energy as it did before the pandemic.
Amazon’s climate pollution, meanwhile, increased by more than 16%, surging by the equivalent of more than 10 million metric tons of carbon dioxide. Emissions from its purchased electricity increased 34% since last year. If you feel like you’re seeing more Rivian-made Amazon delivery vans on the road, you’re not wrong: The company claims it deployed an additional 21,000 last year.
What’s driving this surge? The AI boom, of course. “Our AI infrastructure buildout is currently accelerating faster than the grid is decarbonizing,” Kate Brandt, Google’s chief sustainability officer, said in a statement.
What to do about it? That’s what Groundwork’s report is about.
“How do we bring down costs now? How do we bring down costs in the long term? And how can we make those two things mutually reinforcing?” Grayson Flood, the report’s author and a former policy adviser to Representative Alexandria Ocasio-Cortez, told me. “We wanted to be pretty direct about addressing what we see as a broken incentive structure within the system, particularly for interregional transmission.”
The report outlines a few novel ideas about how to lower prices immediately, in part to get through a coming multi-year “crunch,” during which the power grid in some regions will be maximally constrained while utilities work to bring new power plants online:
The report also imagines several policy ideas to help build out the grid. One of them is a Grid Trust Fund, a new federal bank account funded through an excise tax on data centers and other large electricity loads.
The government has often turned to funds like these to support infrastructure that creates a natural monopoly at national scale, Flood said. “The interstate highway is the most notorious example, but you can look at airports, you can look at seaports — they have these types of trust funds. There’s a lot of precedent for this in the tax code, and they tend to be financed with excise taxes on some sort of corresponding usage of the infrastructure.”
Under his scheme, the new excise tax would fall on big power users like data centers or crypto miners that don’t generate many permanent local jobs — in other words, aluminum smelters, steel mills, and semiconductor fabs would be exempt from it. But even just taxing electricity for large loads at 1 or 1.5 cents per kilowatt-hour, he said, could throw off more than $100 billion in a decade. That money could then be used to fund new transmission projects, technical assistance for utilities, ratepayer relief, or economic development.
That trust fund would be partly overseen by a National Power Authority, a new government corporation modeled on the Tennessee Valley Authority or the Energy Department’s existing power marketing administrations. This authority would have limited powers and would be partly inspired by Texas’ successful effort to centrally plan transmission lines in order to expand its electricity market.
The new authority would plan and develop interregional transmission, linking far-flung regions of the country to create new power markets. It would also have the power to build new 24/7 zero-carbon electricity power plants with high up-front capital costs, such as new geothermal projects, offshore wind farms, or nuclear plants.
“People talk about the power grid as a platform,” Flood said. But “right now, the grid is not functioning as a backbone and platform, it’s functioning as a bottleneck.”
The goal of the report, he said, is to ask: “How do we build [the power grid] as a backbone to support the growth of private markets, whether that’s in renewable energy generation, or an AI data center, or a new hospital that’s showing up?”
It’s an interesting document. Many energy wonks have proposed plans to shift some of the costs of expanding the electricity system out of the ratebase — that is, out of customers’ power bills — and onto the tax base, which is funded in a more progressive way. (I recently argued for a national, publicly funded grid buildout in The New York Times.) The new Groundwork report, in essence, tries to reframe those ideas for an era of populist politics — and one in which Americans are suspicious of data centers, as Heatmap’s polling has shown.
In its fusion of populist and pro-growth attitudes, this new set of proposals reminds me of New York City Mayor Zohran Mamdani’s attempt to freeze the rent for some tenants while passing major supply-side reforms allowing new housing construction. That effort has won Mamdani praise from many housing advocates in New York (even as some remain dubious about his de facto rent freeze). Whether that kind of politics works at a national level remains to be seen.
The bill is part of a package now sitting on Governor Mikie Sherrill’s desk.
Data center politics are continuing to evolve rapidly, and almost always in the direction of increasing costs and restrictions for data center development.
In New Jersey, which has become ground zero for the political backlash to high electricity prices, a gaggle of bills relating to data centers and electricity prices just hit the desk of newly elected Governor Mikie Sherrill, including a large load tariff bill, a water and energy reporting bill, and a bill to scale back tax credits available to data center projects.
All of these pieces of legislation are consistent with national and local trends (federal regulators are encouraging regional electricity markets to come up with large load tariffs, for example), with tax credits getting an especially close look in statehouses across the country.
Thirty-eight states have “ dedicated tax incentives for data centers,” according to an April study by the National Conference on State Legislatures. These often include exemptions from sales taxes for data center equipment like servers and routers, or property tax abatements for newly constructed data centers.
In Virginia, which last year elected Sherrill’s former House colleague Abigail Spanberger as governor, the sales tax exemption has become a hot issue of political contestation, as powerful Virginia State Senator Louise Lucas has come out in opposition to it. A budget deal recently reached in the state’s General Assembly included a tax on data center electricity consumption, while the data center tax exemption question will be kicked to a working group for now, according to the Virginia Mercury.
The New Jersey bill currently on the governor’s desk targets a tax credit program called Next New Jersey, which has some $500 million to disburse for tax credits. Half of that has been allocated for a CoreWeave data center project on the site of an existing laboratory, State Senator Joseph Cryan told me. The remaining $250 million would be used to bolster a number of existing state programs.
“The reason for eliminating it was, frankly, because people are outraged over the amount of money CoreWeave got,” Cryan said.
CoreWeave did not respond to a request for comment. A Sherill spokesperson didn’t comment on the record about when or whether the bills would be signed.
New Jersey and Virginia’s examination of tax credits comes after another state with a Democratic governor, Illinois, paused tax incentives for data centers that had been worth almost $1 billion in the first five years of this decade.
The turn against tax incentives for data centers comes as the public is increasingly wary of the latter and their perceived effect on electricity prices. This turn in sentiment has forced governors — like, say, Indiana Governor Mike Braun — to pivot away from their typical cheerleading for new businesses.
“States are very focused on attracting industries of the future, attracting jobs for their residents, attracting business,” Justin Balik, a former economic development official in New Jersey and vice president for states at the climate group Evergreen Action, told me. But, he asked, “Does the economic development strategy for a state reflect its other policy priorities?”
New Jersey itself is an example of how quickly the politics of economic development can turn. When the bill establishing the Next New Jersey program passed in 2024, then-Governor Phil Murphy trumpeted the bill for “capitalizing on this moment to ensure we establish ourselves as a frontrunner in generative AI innovation.”
“AI has already started to revolutionize our everyday lives, and New Jersey is capitalizing on this moment to ensure we establish ourselves as a frontrunner in generative AI innovation,” Murphy said in a statement typical of the more boosterist era of, uhhh, two years ago. “AI will be a transformative industry that will change lives and grow our economy and New Jersey is ready to take the lead.”
That was in July 2024. Now it’s July 2026. Electricity bills in New Jersey have gone up from $108 per month in May 2024 to $140 this past May, according to the Heatmap-MIT Electricity Price Hub, while rates have gone up some 38%. And while it’s often difficult to attribute electricity rate hikes directly to data center development — or even determine whether data centers raise rates at all — New Jersey, which is part of the PJM Interconnection electricity market, is almost certainly seeing hikes due to data center construction. PJM has struggled to bring on new generation or adequate transmission, and its own market monitor said in March that “data center load growth is the primary reason for recent and expected capacity market conditions, including total forecast load growth, the tight supply and demand balance, and high prices.”
The conditions have forced lawmakers to reconsider their typical bias toward economic development, Balik told me. “I think we’re seeing a moment where there’s a reckoning with the energy affordability conversation,” he said, “Where folks are rightly saying, hey, we care about clean energy in some cases, and in a lot of cases we care about energy affordability. Does our economic development strategy match those priorities, or are these two things at odds with each other?”
Cryan, the state senator, put it more bluntly: “The reason for doing it was to show the public that we hear their outrage and can do something about it,” he said. “The governor and the legislature have heard the voices of the people of New Jersey.”
What the heck is “surficial mineralization”?
According to one of the world’s leading carbon removal buyers, the sector’s future lies in piles of industrial waste.
When Frontier, the Stripe-led coalition of carbon removal supporters, announced its latest $915 million funding commitment, it took the opportunity to lay out the five technologies it views as most promising. I was familiar with four of them — ocean alkalinity enhancement, biomass carbon removal and storage, enhanced rock weathering, and direct air capture. Heatmap has covered them all. But the name on the very top of the list stumped me: surficial mineralization.
It sounds technical, and like all methods of carbon removal, it is — sort of. The idea is to take advantage of the tailings ponds and slag heaps left behind by the mining and steelmaking industries. These piles of calcium- or magnesium-rich debris naturally capture and store carbon from the air — not enough to change the trajectory of our warming planet without any human intervention, but managed well, they could one day capture carbon at a significant scale.
How significant, exactly? While there’s been very little action in the space to date, Frontier says surficial mineralization has the potential to remove over 10 gigatons of carbon from the atmosphere per year — as much or more than any other pathway — at an eventual cost of $80 to $120 per ton. That would put it among the cheapest approaches on Frontier’s list, in part because those heaps of industrial waste alone could absorb anywhere from a gigaton to 4 gigatons of carbon before there’s a need to mine rocks solely for carbon removal purposes.
“The beauty of surficial mineralization is twofold,” Hannah Bebbington Valori, who heads the Frontier coalition, told me. “One, we are working with an abundant source of highly reactive rock, and so there is a significant opportunity for carbon dioxide drawdown. And two, it is carbonating in place, and so sufficient mineralization technologies can be considered closed system approaches, and have generally more straightforward measurement reporting and verification infrastructure.”
At a chemical level, the process resembles other carbon removal pathways Frontier champions, such as enhanced rock weathering and ocean alkalinity enhancement. All three rely on alkaline minerals reacting with moisture and ambient carbon dioxide to form stable carbonate compounds that permanently lock away the gas. The difference is exactly where this reaction takes place: While surficial mineralization contains it to waste piles at industrial sites, the other approaches disperse the reaction across open, difficult-to-monitor systems such as farmland soils and the ocean.
That makes measurement, reporting, and verification — known as MRV — far more challenging and expensive for ocean- and soil-based systems, as scientists must track carbon uptake across ecologically complex environments where countless biological and chemical processes are unfolding simultaneously. These intersecting processes makes it difficult to demonstrate that human intervention was responsible for any given ton of carbon removed, as opposed to natural variability. MRV for these pathways thus relies heavily on modeling, which can never provide the same level of certainty as direct measurement.
Surficial mineralization, however, can be measured much more directly. On-site sensors continuously monitor CO2 concentrations above mine tailings or steel slag, providing a real-time signal of how quickly and to what degree the materials are drawing down carbon. Scientists can then validate these measurements in the lab by comparing physical samples of the material taken before and after the reaction, quantifying exactly how much solid carbonate formed as a result of various engineered interventions. The primary tool for this is X-ray diffraction — a well-established geological technique that identifies a sample’s mineral composition like a chemical fingerprint, making it possible to directly measure how much carbon the material locked away.
Don’t mistake the relative simplicity of the MRV framework for evidence that surficial mineralization is a proven carbon removal pathway — the reality is far from it. While mineralization may look simpler than, say, direct air capture, which typically uses giant fans and specialized sorbents to pull CO2 from the air, there are very few companies working in this space today. All are extremely early stage, and the time and capital required to secure feedstock partnerships, gain site access, and acquire necessary industrial equipment remain significant barriers to getting these projects off the ground.
Why is this heavy equipment needed in the first place? Because these waste piles won’t do much carbon capture work if they’re simply left untouched. That’s because the minerals at the pile’s surface will begin to slowly carbonate, eventually becoming fully saturated and acting as a seal that blocks carbon from reaching the reactive minerals below. As yet there’s no consensus on how to most quickly and cost-effectively break through this natural process to maximize carbon uptake — companies are testing a range of approaches, from crushing and spreading material to maximize air exposure (similar to enhanced rock weathering) to actively churning piles of waste to constantly reveal fresh reactive surfaces.
“Understanding exactly what is the best system to use to maximize your carbon removal efficiency and minimize your cost — this is what we need real-world deployment to do, and to understand,” Bebbington Valori told me.
One of the seed-stage startups Frontier has supported with a small pre-purchase agreement, Arca, spun out of the University of British Columbia to commercialize its approach to carbon removal from mine tailings. The company’s focus is ultramafic waste — magnesium- and iron-rich rock that locks away carbon dioxide as stable magnesium carbonate. “My pathway for interest on that was knowing that there was already about 2 billion tons of ultramafic mine waste sitting on the surface of the Earth in Canada alone,” Greg Dipple, Arca’s co-founder and head of science, told me.
Arca proposes to increase the surface area available for carbon capture in two ways. The first is by using customized robots to continuously till and churn tailings piles, constantly exposing fresh feedstock to the air to maximize carbon uptake before the next layer of tailings is deposited on top. That strategy, Dipple told me, “can give us a five- to 10-fold increase in the rate of CO2 capture” at active mine sites.
It successfully demonstrated this approach in an 18-month pilot project with Australian mining giant BHP at an active mine in the country's Northern Goldfields region where Arca says it increased the tailings’ mineralization rate by an order of magnitude. But the startup plans to push the efficacy of its tech further through what it calls “mineral activation.” This technique uses industrial-scale microwaves to heat the minerals rapidly enough to drive off the water that’s chemically bound within their crystal structure. This essentially blows apart the minerals from the inside out, exposing fresh magnesium-rich surfaces primed to react with carbon dioxide. The expected result is faster mineralization and more carbon captured per ton of mine tailings — but the startup has yet to test it in the field.
“Essentially we’re making microwave popcorn out of silicate minerals,” Dipple explained. “The microwaves cause the release of that water in the same way that when you make popcorn, you’re essentially boiling the water out of the center of the kernel, and that’s what blows the kernel up and creates this high surface area.” The idea is to eventually integrate this step into the mine’s tailings processing stream, with minerals moving through the giant microwave before they’re deposited at the storage facility.
Dipple told me that mineral activation will be a core part of Arca’s future projects, including those intended to fulfill the company’s 10-year carbon removal offtake agreement with Microsoft. Signed last October, the deal calls for Arca to deliver nearly 300,000 metric tons of carbon removal to the software giant.
While no other startup in the space has landed an offtake agreement of that scale, several have secured early backing from Frontier through pre-purchase agreements. One of them, Karbonetiq, is working to capture carbon from steel slag, the calcium-rich byproduct of steel production that accumulates in large piles at processing sites. Like the magnesium-rich minerals in mine tailings, calcium compounds in steel slag naturally react with moisture and carbon dioxide to form a stable calcium carbonate — a.k.a. limestone — permanently locking up the CO2.
Unlike mine tailings however, slag doesn’t begin as a fine powder. Instead, the molten byproducts poured off from high-temperature steel furnaces cool into chunks the size of large rocks, leaving only their outer surfaces exposed to the air and able to react with CO2. Karbonetiq’s strategy is essentially to crush and disperse those rocks to increase their reactive surface area. As the company’s commercial vice president, Luke Rondel, explained, “We crush [the slag] down so you get smaller particle sizes. We then spread that out in a field of material, and we till that material with a tractor and plow, which is just turning over new surfaces.”
Each pathway has its advantages — while Arca’s magnesium-rich mine tailings are the most abundant feedstock, Rondel told me that the calcium-based reactions in slag happen significantly faster. For its part, Frontier hopes to test and evaluate a range of approaches at its new Surficial Mineralization Hub in Quebec, which it announced at the end of April. Located at a former asbestos mine, the hub will give participating startups access to “10,000 tons of serpentinite tailings and space for pilot scale testing,” Bebbington Valori told me, as well as local labs with specialized equipment.
This should eliminate some of the hurdles facing the nascent sector, chief among them being access to the right kinds of reactive rocks. Small startups “really need to either partner with large academic labs or with large mining companies to get access to that feedstock,” Bebbington Valori told me — a difficult and expensive proposition for a company that’s just getting off the ground.
While Frontier has yet to announce the cohort of participating startups, both Arca and Karbonetiq told me they hope to test their technology there, with the latter planning what would be one of its first mine tailings pilots through the program. Ultimately the goal is to generate the proof points needed to give both the startups and Frontier a clearer roadmap for which approaches can realistically scale — and what kind of support they’ll need to get there.
It certainly won’t be a straightforward process — bringing new technology into old-school industries never is — and the economics will only start to pencil if their operations reach meaningful scale. In theory, mining companies could benefit from hosting surficial mineralization projects, whether through site access fees, outsourcing elements of waste management, or even critical minerals recovery. Miners could even develop and scale the technology themselves, if they so desire. But the sector has historically been reluctant to adopt new tech. “The classic quote is, in mining you always want to be No. 2, you don’t want to be the first one,” Dipple told me. “You don’t want to put up a $2 billion plant that doesn’t work.”
So like nearly everything in the carbon removal space, early execution is falling to the startups that aren’t afraid of a little risk. “They’re watching for sure,” Dipple said of the mining industry at large. “But they want to be No. 2. We’re going to have to be No. 1.”