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The effort to measure companies’ carbon footprints is remarkably imprecise — and suddenly more important than ever.

Large companies generate a gargantuan amount of carbon-dioxide pollution.
Take the big-box retailer Costco. During the financial year 2020, it emitted 144.5 million metric tons of carbon dioxide — a number on par with the Philippines’ annual emissions. Nike pumped out the equivalent of 11 million metric tons of carbon during the same period, a footprint roughly equal to Zimbabwe’s. Apple, meanwhile, was somewhere on the order of Estonia.
You’ve probably seen data like this before. But here’s a question: How do companies actually arrive at these numbers? How did Costco know its carbon footprint in 2020? Carbon dioxide and other climate-warming gases are invisible, potent even in trace amounts, and constantly absorbed and produced by hundreds of billions of different organisms and chemicals around the world. Costco alone directly or indirectly choreographs the actions of millions of people and things: sailors and longshoremen, factory workers and cotton farmers, employees coming in for their shift and marketing managers spending down an advertising budget.
How could a company like that possibly know its carbon footprint?
Here’s the sorry answer: Most companies don’t. They estimate.
Those estimates are suddenly looking more important. New laws and a proposal from the U.S. Securities and Exchange Commission could soon require that companies treat this data with the same seriousness that they devote to their accounting books. Companies now need their corporate climate data to do something that it was never meant to do: help them make decisions.
So the race is on to help companies estimate better. On Wednesday, Watershed, a startup that helps companies run their climate programs, bought VitalMetrics, a climate-data mainstay that owns and manages one of the most important tools that companies use to estimate their carbon footprints.
That tool, called the Comprehensive Environmental Data Archive, or CEDA, provides what’s known as carbon-intensity data for hundreds of products as made in more than 140 countries. It is one of several tools that has been used to advise Microsoft, Kellogg’s, and Virgin Atlantic since Sangwon Suh, an industrial-ecology professor and Intergovernmental Panel on Climate Change author, founded VitalMetrics in 2005.
Watershed’s acquisition of VitalMetrics signals that corporate climate data is entering a new stage, Taylor Francis, one of the company’s cofounders, told me. Watershed, at least, is a different kind of company than the climate bean counters of yore: Founded by former employees of the payments behemoth Stripe, it has raised $84 million from the venture-capital firms Kleiner Perkins, Sequoia Capital, as well as the billionaire Laurene Powell Jobs.
“The traditional corporate climate complex was basically designed for a world of numbers in the corporate social responsibility report, and a pledge, and a press release,” he said. ”We’re shifting to the new world of numbers in a 10-K,” the annual financial report that public companies must file with the government, “and a planet running out of time.”
I will admit I had it all wrong. I had assumed that because corporate carbon footprints sounded precise and vaguely science-adjacent, they were produced by something like a scientific methodology themselves. I imagined a company’s employees — or at least their consultants — collecting emissions data smokestack by smokestack, pacing around factories while studying air-quality monitors, and doing careful math somewhere in the vicinity of a bunsen burner or two. (I believed this, I should add, despite knowing that many corporate climate reports contain glaring arithmetic errors and sometimes literally do not add up.)
That sort of methodology is the “platonic ideal of carbon accounting,” Francis, the Watershed cofounder, told me. In a perfect world, a company would have measured the per-ton emissions of each of its processes, and it would know these for each of its suppliers down to the raw material.
Yet this is still a ways off for most companies. Instead, the bulk of carbon accounting today now happens in spreadsheets, and it uses dollars, not tons, as an input. Each consumer good or raw commodity aligns to a “factor,” a multiplier that says that for every dollar spent on, say, glass or aluminum, a certain amount of carbon is emitted. A climate team inputs the dollar amount, multiplies it by the factor, and arrives at a result: a company’s annual carbon footprint.
Until now, Watershed and other firms have often calculated corporate climate emissions by using a U.S. Environmental Protection Agency-made database called the Environmentally Extended Input-Output, or EEIO, model, Francis said. “You start with very coarse input data like, we spent $100 million on marketing. So you go to the old EEIO database, and the EEIO says that in the U.S. 10 years ago, the carbon emissions per dollar of marketing spend was X, and you multiply that to get your emissions number.”
“I think that gets you into the right order of magnitude,” he said, but it was messy. The EEIO data is roughly a decade out of date, meaning it overstates climate pollution from the power grid and understates the role of inflation.
VitalMetrics’ CEDA database, on the other hand, is updated every year. It contains carbon-intensity factors for more than 300 products and — most important — it varies these factors based on the country of origin. Going forward, Watershed will calculate corporate emissions data using these CEDA estimates.
This kind of data-gathering isn’t fine-tuned enough for companies to actually make better decisions with their data, Madison Condon, a law professor at Boston University who has criticized the reigning approach, told me. Under the current approach, a company can improve their carbon-accounting data only by shifting production to countries with lower emissions factors. It doesn’t get credit for, say, installing technologies at its existing factories that lower emissions.
That is unsustainable because corporate carbon accounting is becoming important to governments around the world. The Securities and Exchange Commission has proposed requiring publicly traded companies to disclose carbon data and major climate-related risks. Even if that rule is swatted away by the Supreme Court, the European Union will soon require tens of thousands of companies to disclose sustainability and emissions data; these rules could apply to more than 10,000 foreign companies, including many mainstream American brands. California could soon pass its own law mandating that companies produce carbon-accounting data.
Even apart from those disclosure requirements, carbon-footprint requirements are now written into laws. Some of the Inflation Reduction Act’s subsidies will pay out only if a product’s carbon intensity is below a certain threshold.
Eventually, Watershed hopes to produce a hybrid tool that can use dollar-based production factors, tonnage estimates, and technology-based improvements together, Francis told me. More broadly, Watershed’s acquisition of Vitalmetrics — not to mention Watershed itself — is a gamble about how the climate economy will eventually work.
“Five years from now, the disclosure piece is just part of the water. No one talks or writes about it because it is an expected part of doing business for every company. And it’s relatively low friction. It’s a part of your annual close, your quarterly close,” Francis told me. “We don’t really talk about climate as a political issue because businesses don't think of climate as a political issue because they see it as, you know, the biggest growth sector of the decade.”
Of course, if that’s true, then companies may not need a startup like Watershed to do their climate counting for them. Bog-standard corporate accountants, like KPMG or Deloitte, will do the task just fine.
But Watershed is betting that climate accounting will remain both more technical and more central to a company’s employee and investor relationships than, say, its power bill. Just as companies use Salesforce specifically to manage customer relationships, or Justworks to manage payroll and benefits, Watershed hopes they will need a single place to manage all their climate data — a single source of emissions truth. It’s investing in its database to try to make that bet payoff.
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What 700 math problems say about the AI economy’s biggest open question
This is Heatmap Daily, an evening news digest written by our executive editor. Subscribe here.
Happy Monday and welcome back.
It’s been a big weekend: I’m fairly certain Saturday Night Live mentioned Heatmap’s data center polling in one of its Weekend Update segments over the weekend. Watch here.
There are 22 days to the midterm elections here in the United States. We’ll soon enter that pre-election wormhole where only national politics can break through. So today I wanted to look at a story that might, on its face, seem like it has nothing to do with climate or energy. And warning: It’s a little bit of a weird one.
Last week, OpenAI released what it described as the solution to more than 700 open problems in mathematics. Many of the problems, such as the Quasi-Riemann hypothesis, had gone unsolved for decades. Some of the solutions came with proofs written in the programming language Lean.
The release made a stir in part because OpenAI had reached the solutions by using an internal model — that is, a version of ChatGPT not yet open to the general public. In a statement, the Association for Human Mathematics lambasted OpenAI for using an internal model to do research, violating what it described as a precept of AI-driven math research. (I’ve since seen speculation that OpenAI may not have even meant to solve the problems, but gave them to the internal model as a test … and then got the answers.) It’s also not clear whether all of OpenAI’s 700 solutions are correct — in many cases the proofs are so intricate that mathematicians are still wrapping their heads around them.
“There are some sad stories related to their users getting scooped [and] conflicts of interest,” Levent Alpöge, a mathematician at Anthropic, posted on X. “It’s obviously the most significant moment in mathematical history.”
On Friday night, the UCLA mathematician Terence Tao gave a pre-planned lecture at Caltech about what he called “Math 2.0”; it considered the revolution the field had seemingly undergone in the previous few days. (He posted the slides to his blog over the weekend, and I’m using them to summarize his talk here.) For most of math’s history, he said, the field operated under “proof scarcity,” in which finding a solution to an open math problem and confirming it as true was “difficult and rare,” requiring “significant human expertise.”
But AI, it has turned out, is well suited to solving math problems. This is partly because math, like the large language models themselves, is entirely conceptual, so confirming a proof as true requires no recourse to the physical. But it’s also because math’s solutions are “objectively verifiable”: “There is broad consensus on what constitutes a correct and complete proof of a given problem,” and thanks to the existence of proof programming languages like Lean, they can even be checked by computer.
The end result is that math is now entering a world of “proof abundance,” he said.
That is, perhaps surprisingly, a problem for math’s practitioners, and it will mandate a new intellectual regime for the discipline. Mathematicians have often used open problems as “lighthouses,” Tao wrote, “not destinations to be reached … but useful guides to explore the mathematical landscape.” Mathematicians often learn more in the solving than in the solution, in other words. But if mathematicians can now generate shortcuts to math problems without knowing how they got there, or even how the problem works, then actual human mathematical understanding will suffer. (One way to understand this is that mathematicians are now dealing with the same problem that math teachers have faced since the invention of the pocket calculator: How do you confirm students actually understand the material? Except the world’s most elite mathematicians themselves are the students in question.)
This disconnect can pose its own AI alignment problems, Tao said, analogizing math to pharmaceuticals. Suppose an advanced AI found what appears to be a cure for cancer that can pass a stage 3 clinical trial: “After a large amount of compute, it produces a cocktail of previously unknown chemicals which it claims, when mixed and injected into a patient, will kill all their cancer cells,” he said. It even generates a programmatic proof of the cocktail’s effectiveness.
“Before injecting this cocktail into your bloodstream,” he asked, “would you find it reassuring to know that there is at least one human cancer expert who understands — even partially — the mechanism behind this cure?” If not, you can see mathematicians’ problem, confronted by a surfeit of proofs that seem to work, but nobody who can explain how or why they do.
Now, Tao’s analogy is somewhat peculiar because something like this actually does happen all the time in medicine: Doctors still don’t fully understand how many drugs work, including acetaminophen, SSRIs, and lithium. (That said, those compounds were identified by trial and error, not by a mechanical superintelligence.) But the broader situation that Tao is painting — as well as the crisis posed by OpenAI’s 700 proofs — get at a significant question with economic importance far beyond just math: Will AI solve the economy’s secular attention shortage or worsen it?
This question has greater import than it may seem — but let me qualify what I mean by “attention shortage.” Writing in 1971, the economist Herber Simon observed the sudden superabundance of information that had exploded in every economic domain. There were more facts, data, news articles, and opportunities than any individual or organization knew what to do with. He pointed out that this newfound “wealth” of information implied an insufficiency of something else: attention.
“What information consumes is rather obvious: it consumes the attention of its recipients,” he wrote in Designing Organizations for an Information-Rich World. “Hence a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it.”
He wrote this, of course, well before the advent of internet, smartphones, sensors, or networked cameras — all of which have worsened the problem. But in the ensuing half century, the economy has learned to deal (or at least intermittently manage) this secular scarcity of attention. Much of what we now call knowledge work is devoted to filtering, siphoning, processing, and otherwise attending to the information superabundance.
AI is, in theory, supposed to help address this same set of problems. AI is commodified attention — or, at least, that is its promise. (The most important machine learning paper of the past decade, after all, is entitled “Attention Is All You Need.”) Many AI products, such as Meta’s Muse, now want you to believe that by ceding control of your email, your calendar, your restaurant reservations, and your digital life to AI, you will gain an attentional edge. The AI will do the grunt-work of attending to boring things for you, and you will feel less overwhelmed. If this vision comes true, the economy’s mismatch of information and attention will prove to be a short-lived historical blip.
But the past week of math news and Tao’s “Math 2.0” regime suggest a different scenario is more likely, at least in the immediate near term. By allowing far faster and more automated information production, AI will create a new, more vicious, and even more abstract form of information overload. Every profession and intellectual discipline will be overwhelmed with new papers, ideas, observations, proofs, or choices. Yet the human understanding required to convert this new information into useful action will become even more scarce. In such a world, AI will not solve the economy’s attention shortage, but worsen it.
I’m not sure which world would be worse for humanity, to be candid. One world suggests the eventual automation of all human effort. But in Tao’s world, many of us might still have jobs — they will just involve even more filtering, sorting, and processing of an ever-deepening pile of automated idea generation than we do today.
And what is the connection to climate and energy? One easy connection might be to the permitting process: If you think a new transit line (at the local level) or transmission line (at the state or federal level) could be overwhelmed with procedural concerns 10 years ago, wait until you see what happens when information itself can be mechanically produced. But that is only one example of a more general problem. Soon, if not already, any process of providing input to an important policy question — on energy, decarbonization, or anything else — will be overwhelmed with facially high-quality analysis. It will be left to policy officials and elected leaders to sort through it.
This past weekend’s storms caused flooding and property damage up and down the coast — and it’s going to get worse.
California has around 3,400 miles of shoreline, ranging from the wild, foggy beaches of the North Coast to the sunbather-studded sands of Orange and San Diego counties. That’s a whole lot of border to share with the Pacific Ocean, especially when the water is as hot and tempestuous a neighbor as it is right now.
Just ask the city of Long Beach, which this weekend was on the receiving end of some Super El Niño mischief. Swells from the storm briefly dubbed Hurricane Rachel “annihilated” beachfront mansions and flooded city streets, causing pieces of the local boardwalk to “shred away.” “It’s never happened like this before,” one resident of 64 years told the New York Post.
But while things might look bad in California at the moment, they can still get much worse. One disaster modeler recently estimated the state could see as much as $3 billion in flooding and mudslide-related losses alone this winter — not to mention coastal erosion, king tides, and storm swell. Governor Gavin Newsom declared a state of emergency at the end of September, while many cities, including San Diego, have declared their own local emergencies.
El Niño will likely peak in December, meaning that towns and cities across the state have just a few remaining weeks to finalize projects, whether that means improving drainage in landslide-prone environments such as Rancho Palos Verdes or distributing NOAA weather radios in areas likely to lose power, as emergency managers are in Santa Cruz. The approaching winter storms, combined with El Niño, represent “a humbling reminder of the ongoing effects of climate change and the importance of emergency preparedness,” Laath Martin, the public affairs lead for the city of Long Beach, wrote to me in an email.
El Niño is a cyclical phenomenon, occurring when temperatures in a particular stretch of the Pacific Ocean rise half-a-degree Celsius above the average of the preceding 30 years. But there are signs these natural variations are happening less predictably because of climate change, and we know for sure that a warmer atmosphere makes the baseline for its impacts worse: king tides, Kelvin waves, and storm surge piggyback on top of rising sea levels to result in more severe coastal flooding and erosion. A warmer atmosphere also holds more water, which means more rain — perhaps 200% above normal — which, in turn, results in flooding and mudslides further inland, as well.
“Based on what I am seeing now, I am officially concerned,” Daniel Swain, a climate scientist at the University of California Agriculture and Natural Resources, said last week after reviewing the latest outlook. There’s a reason this year’s El Niño is being called a Godzilla.
In general, the weather pattern causes the jet stream to shift south in the winter, bringing wetter and snowier conditions to the lower U.S. while the northern part of the country stays drier and mild. (It’s also responsible for a weaker Atlantic hurricane season, as we’ve already seen this year.) In addition to El Niño-driven Kelvin waves, warm bulges of water that raise the sea level on the coast by as much as 18 inches, the state of California — and particularly southern California — sits directly in a storm track that will deliver “atmospheric rivers” of heavy rain to a region prone to landslides and flash floods.
In many parts of the state, that rain will test the best-made plans in addition to plans deferred. In Los Angeles, the Department of Sanitation and Environment, or LASAN, has told the City Council it has concerns about the ability of the aging wastewater pipes and plants to handle heavy rainfall associated with a supercharged El Niño. In San Diego, which requires some $3.3 billion to upgrade what is in some places a century-old wastewater system, emergency managers are preparing to work with what they have by clearing debris and brush that could back up in the drains, CalMatters reports. In both cases, the time required for systemwide repairs far exceeds the time remaining before the winter’s supercharged atmospheric rivers are due to arrive. (Rezende told me inland flooding affects more businesses and residents in San Diego than coastal flooding, since the population in the city is set further back from the coastline.)
The city of Roseville, northeast of Sacramento, by contrast, is leaning on decades of flood planning to get through the season. After a series of back-to-back storms in 1986 that killed 13 people and caused $400 million in damage, the city and FEMA invested $39 million to upgrade Roseville’s infrastructure, including widening streams and adding levees and stormwater bypass channels. With more accurate floodplain modeling that has “helped keep new construction at higher elevations,” Helen Dyda, the city manager’s public information officer told me that “less than 7% of the city is within a floodplain” today. Dyda added that the city prepares for winter storms every year — it has some 160 miles of creek shoreline, after all — but that the El Niño-specific preparations are, as a result, more similar to routine maintenance: “clearing more dense vegetation and fallen trees from key creek areas.”
Long Beach is caught somewhere in the middle. After swells from Hurricanes Marie and Polo hammered the city in September, Long Beach hastily developed a seven-point plan to strengthen its peninsula in the near and long term. It will also begin a $11.4 million dredging project this fall that will place 415,000 cubic yards of sand on the beach as a buffer zone. “While this effort will achieve a much-desired result, it will not stop the ocean from pulling sand from the peninsula with every wave, especially during the significant weather systems Long Beach continues to experience,” Martin, the city’s public affairs lead, wrote to me. “Back-passing will need to continue to return sand back to the peninsula each day until more permanent, long-term man-made and environmental solutions can be identified, permitted and implemented.”
In certain cities, preparations for the peak of El Niño overlap with ongoing repairs from the last bad storm season. In Santa Cruz County, the 2016 El Niño caused an estimated $9 million in damage, while many in the community of Pajaro are still recovering from the flood damage caused by a series of severe atmospheric rivers in 2023. “We have a list of hazards that the city is vulnerable to, and we plan for all of them not individually, but all together,” Meredith Albert, Santa Cruz’s emergency management manager, told me. She added that many of the city’s preparedness activities and El Niño initiatives, like urging the community to be prepared to spend 72 hours unsupported, overlap with other disasters it works year-round to prepare for, like earthquakes, landslides, and wildfires.
“El Niño turns up the volume a little bit, but it doesn’t necessarily change our hazard landscape,” is how Albert put it to me.
Santa Cruz has not declared a local state of emergency, and Albert told me they won’t until they “run out of resources.” Other cities, like San Diego, have declared one preemptively. “In the past, you’d have to go through a longer review if you wanted to make some headway on projects, and sometimes that would take many weeks or many months of permitting,” Rezende said. “With a state of emergency, we streamline that process and get projects in the queue.”
Both Rezende and Albert told me the governor's statewide emergency declaration mostly helps state agencies position themselves for a faster response or has implications for higher-level permitting processes. (In Carlsbad, for example, which has seven miles of badly eroding beach, just one mile is controlled by the city; the other six are managed by the State Parks.) The state has also teamed up with ICEYE, a satellite imaging company, to receive information about flooding even in the dark or through rain clouds.
No state of emergency, though, can make it so a city can replace a century-old sewer system by Christmas or reengineer a beach by the time January’s storms begin to make landfall. But if a Godzilla analogy fits the onslaught of a super El Niño, it also offers a classic disaster-movie lesson on how to survive it.
Albert’s advice for how to prepare? Ask a neighbor for a cup of sugar. Take their dog for a walk. Build a relationship that could prevent a tragedy. “We know that our city will be cut off for at least a couple of days,” she told me of a hypothetical major disaster, referring back to Santa Cruz’s experience after the 1989 Loma Prieta earthquake, which cut off the city’s power, communication, and supply lines. “And we also know that we can’t build those relationships during the disaster. We’re trying to build them before.”
The city is doing a lot to prepare for the storm, she said. “But the question is also, what are all of us doing?” Albert went on. “You know better than I do, at the city level, who’s not going to receive that alert,” whether that be an elderly or unhoused neighbor or a nonnative English speaker who might not receive or understand emergency communications.
“Check in on a neighbor” is easier said than done — active engagement and connection to one’s community is trending downward in most parts of the U.S. But the people and places that bounce back from disaster and tragedy are almost uniformly the ones that look after each other. Borrowing a cup of sugar, to this introvert, sounds like a nightmare. But there’s never been a better time than a Godzilla El Niño to bake a poorly resourced cake.
Heatmap News is looking for an ambitious, energetic senior editor to join our growing newsroom.
The senior editor will report to the deputy editor of the website and will be tasked with assisting in running all aspects of our coverage. This individual will be the primary editor on many of the site’s stories, including breaking news, features, and long-term projects, on topics ranging from permitting reform to decarbonized fuels to greenhouse gas accounting to the electric vehicle market. This person will also play a role in overseeing and furthering our cross-platform efforts such as newsletters, events, and podcasts. Additional duties will include managing and maintaining the site’s social media presence and digital production on stories, newsletters, and podcasts.
Candidates should be intellectually curious news junkies with a deep interest in climate change and the energy transition. They should have a proven ability to work in a fast-paced digital newsroom, spot great angles, line edit stories, and change hats quickly as needed. They should also be responsible, reliable, and a good colleague.
Candidates should have 5+ years experience editing for a digital publication. A background in climate or energy coverage is an obvious plus, but compelling candidates from other verticals, particularly politics and business, will also be considered. Heatmap is a fully remote workplace, so candidates from all U.S. locales are encouraged to apply.
Above all, candidates should be passionate about Heatmap’s mission and absolutely thrilled about building something from the ground up.
The salary minimum is $100,000 and the maximum is $120,000. Competitive benefits, unlimited paid time off, and a generous equity plan, which gives employees a real stake in the company, are also offered. This position is remote.
Interested candidates should send a brief cover letter and resume to editors@heatmap.news with the subject line ‘Senior Editor Application.’
Heatmap News is a media platform focused on the energy transition.
Heatmap News is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected veteran status, age, or any other characteristic protected by applicable law.
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