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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.”
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The data center boom is everywhere you look in U.S. economic and emissions data.
This is an edition of Heatmap Daily, an evening review of the day’s news written by our executive editor. Sign up for it here.
It isn’t exactly a new thought, but I’ve been struck recently by how many trends in America’s economic and environmental data are fundamentally about the data center boom and the return of electricity demand:
First, the Energy Information Administration reported this week that U.S. emissions grew by more than 2% last year, driven by surging electricity demand and an increase in coal-fired generation.What caused that higher power demand? New factories and data centers — as well as record summertime cooling demand.
Second, many of the new factories driving that higher power demand are themselves producing goods that are … let’s say … data center-adjacent. There are the enormous new semiconductor fabs, of course. But Ford and General Motors have also set up new production lines (or repurposed old ones) to manufacture grid-scale batteries to meet power demand.
Third, take a look at the recent U.S. spending on private non-residential construction — in other words, everything American companies are building that is not houses, condos, or apartments.
The construction industry’s spent almost $60 billion on data centers over the past year, which is more than it spent on all other office buildings combined (and more than it spent building warehouses, too). Just a handful of categories — data centers, power plants, electricity infrastructure, and certain kinds of electronics manufacturing — now make up a third of all U.S. private non-residential construction investment. They’ve never made up such a large share of construction spending since data collection began in 2014.
As The New York Times recently noted, the American economy is unusually dependent on the American stock market right now — and the stock market is unusually dependent on artificial intelligence. This week, investors started to balk at the enormous spending hyperscalers are planning to keep building out the AI boom; Alphabet’s shares dropped 8% this week after it boosted its planned 2026 capital expenditure and signaled 2027 will be even bigger. If the data center boom started to slow down in earnest, then more than just that budget will change.
Speaking of which, my colleague Emily Pontecorvo wrote earlier this week about how many businesses are struggling to even estimate their carbon emissions from artificial intelligence. The carbon accounting startup Watershed recently unveiled a new formula to help companies get a sense of their AI-related emissions.
But even that formula is still limited by the amount of data hyperscalers publish — and they don’t publish that much. Google, for instance, is the only AI company that has (laudably) provided estimates of its emissions on a per-prompt basis. Yet no company has published its per-token emissions, or how emissions sync up with particular models or regions.
So Emily asked Google: Why aren’t you — or any other model provider — disclosing this kind of data yet?
The tech company didn’t get back to us until after we’d published Emily’s story. But its response was interesting enough that I wanted to quote some of it here.
The problem is “industry consensus,” Cooper Elsworth, a Google spokesperson, told us. “There is currently very little consensus on how to comprehensively and fairly measure the serving environmental impact of generative AI (such as text generation),” he wrote. “Without standardized, ‘apples-to-apples’ frameworks, it is difficult to compare different providers accurately.”
That’s partly because energy use — and emissions data — can vary from site to site and depend on “custom-built hardware, software compilers, and advanced inference techniques.” And he claimed Google doesn’t always have the measurement hardware in place to provide such specific estimates: “Providing precise, repeatable data requires highly advanced measurement infrastructure,” he said. “For example, software-based energy monitoring tools often suffer from sampling biases. For our study, we had to step away from top-down averages and directly measure actual energy at the physical power supply unit (PSU) level across our deployed fleet. Not all providers have the telemetry or data sets required to benchmark their operations at this level of granularity.”
Read Emily’s story to understand the other reasons why estimating — or even “guesstimating” — AI-related carbon emissions is so challenging.
A conversation with Emma Uridge of the Kansas Health Institute.
This week’s conversation is with Emma Uridge, analyst with the Kansas Health Institute. Uridge spent copious hours analyzing state and local laws on data center development to best understand how policymakers are responding to the potential environmental public health impacts of large AI infrastructure, including power and water. The report, which came out this week, also goes in depth into those health impacts. I reached out to her to discuss what she sees as must-watch territory for our readers on this emerging policy arena.
Our conversation was lightly edited for clarity.
What is actually being done on policy when it comes to data centers — beyond moratoria of course?
So first I’d like to just talk about the point of moratoria. It’s helpful to talk about how these policies emerge in the first place. One area where moratoria are helpful is when a data center is proposed but the county has no approach for how they’d like to potentially regulate them. That’s temporary, most of the time. It lets local governments conduct research on the various impacts and also negotiate community benefits, ones that can mitigate any potential negative impacts — like Lancaster Pennsylvania, which instituted a community benefit agreement that maximized the potential benefits of development while mitigating what large data centers can do. That agreement looked at capping municipal water use at 20,000 gallons per day and requiring 100% clean energy. It had financial penalties for non-compliance. The company also committed $20 million to their local economic development and clean energy fund. There are ways to negotiate with developers.
We also see amendments to existing zoning. Data center proposals are increasingly popping up in rural areas, many of which are unzoned, so there’s no way a county can negotiate unless there’s a moratorium in place.
Other policy solutions include different performance standards or requiring on-site renewable energy, like what Jefferson County, Missouri, looked at. Also setback requirements, mandatory noise buffers, ending by-right zoning.
Where are local governments getting ideas for regulating data centers?
A lot of the technical information comes from developers. That can in cases be seen as a biased source of information. I wouldn’t say there’s a dedicated group providing assistance to local governments when a project is proposed — which is a similar story to wind industry development, where we have only a handful of consultants who provide technical advice. It can be really helpful to get a multi-disciplinary approach to hearing information. It can be helpful to have the utility commission, public health folks, those in academia, as well as the developer.
As of right now, especially in rural areas, local governments have a hard task of balancing pushback while getting the most accurate, evidence-based, neutral information to make decisions. That balance can be contentious.
What is the federal government doing on data center policy? How is the Trump administration approaching it?
A few things there. In the early days, the drive was for AI expansion and to be competitive with foreign adversaries. Now due to the amount of public pushback in red and blue localities and a more cautious approach.
I’m not seeing a lot of actual policy movement at this time.
I know the EPA is looking at the chemicals used in cooling data centers because when that water is cycled through the system, some of it is discharged into the water system, so they’re looking at the Toxic Substances and Control Act for monitoring that.
How much of an impact does this minimal federal role have on industry behavior?
Y’know, this isn’t specific to data centers. This is true for all kinds of large-scale development: there’s a need to require some sort of federal monitoring and regulation.
That’s where I see an emerging role for public health. At the federal level, there could be policy movement towards requiring some sort of environmental monitoring at data centers to make sure they’re operating responsibility. Looking at specific water use relative to water availability and what happens when there’s a time of severe, persistent drought. With air quality too — we’ve seen areas where the grid isn’t as reliable so their diesel generators are kicking on more and affecting air quality for residents.
We’re just not seeing all of that right now. We need corporate disclosure.
What do you see as the most important public health impacts from data center development?
It varies by localities. The most discussed obviously is water usage. One thing I’d note about my conversations with folks enthusiastic around emerging tech is, there are still questions that need to be asked about the capacity of localities to support a data center. Like a small town in Kansas may only be using 40% of their water for their utility needs. If a data center came online, how much of that water goes to the data center?
One area underexplored within the public health discipline is energy poverty and energy security. The ability of a household to meet the needs of everything energy provides in our lives. It’s known we have an aging electric grid but we’re not talking enough about large-scale blackouts when the grid is not sufficient to support some of these new data centers.
Plus more of the week’s big development fights.
1. Laramie County, Wyoming — Meta is fighting the fine it received in the Cheyenne data center water pollution controversy, and the conflict between the tech giant and the city’s small board of public utilities is continuing to spill out into the public.
2. Niagara County, New York — This county just rejected a solar project’s highway work permits in a show of retaliation against the state’s Office of Renewable Energy Siting.
3. Barron County, Wisconsin — The anti-solar protest is the new campaign stop in deep red Wisconsin.
4. Chesapeake, Virginia — A large battery storage project on the Virginia coastline is on the rocks amidst rampant local opposition.
5. Lewis County, West Virginia — West Virginia is now a key battleground in the fight over transmission, as a line spanning all of West Virginia and Maryland — and cutting through Data Center Alley in Virginia — causes compounding consternation.