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A new Searchlight Institute report joins a growing chorus arguing that corporate climate targets do more harm than good.

When Jane Flegal was working in market development for Frontier Climate, a $1 billion initiative to catalyze advances in carbon removal, she had what she called a “radicalizing experience.”
Frontier went out to corporate sustainability teams, selling them on large carbon removal offtake agreements with vetted startups that were developing technologies to suck measurable amounts of carbon directly out of the air. These were more expensive than the carbon offsets companies could buy to support forest conservation or clean cookstoves in Africa, but the investment would support innovation important for fighting climate change. In return, the companies would eventually be able to count the resulting carbon removal toward their net zero emissions targets.
Most companies, however, were more concerned about the cost. “We were trying to get companies to spend more than $1,000 per ton on a new technology we know the world needs,” Flegal told me. “Making that pitch to a corporation when they could also just go make the exact same claim with a $4-a-ton carbon offset credit was a crazy-making experience.”
The revelation, for Flegal, was that the prevailing paradigm for corporate climate action — a single-minded focus on carbon accounting — was not just inadequate, but actively harmful to bringing about the systems-level change required to decarbonize the economy. It incentivized companies to optimize for reducing their individual carbon footprints and failed to recognize the arguably more impactful contributions they could be making to systems change. “Most of the best things they could be doing are just not legible at all in the existing accounting frameworks,” she said.
Flegal fleshed out her critique in a paper published Monday by the Searchlight Institute, a center-left think tank where she is now a senior fellow. The data center boom has exacerbated these perverse incentives, she argues. Tech companies are pursuing corporate power purchase agreements to fulfill their individual clean energy commitments, but mostly failing to help break down the structural barriers to decarbonizing the grid, such as transmission constraints and interconnection backlogs.
The paper challenges the logic of treating a “complex, global, sociotechnical problem as if it were a matter of property rights,” where investors and the public expect companies to own their individual carbon messes. Flegal proposes some alternative measures by which to evaluate corporate climate ambition. One is the quality of a company’s investments — are they causing more clean energy or crucial climate infrastructure to get built than would be otherwise based on market conditions? How many miles of transmission have they financed, or policy proceedings have they influenced? She also calls for companies to be explicit about their theory of change and report how they are taking action consistent with that theory.
“I recognize that these are not perfect metrics, but let’s be real, neither are the ones we have today,” she told me. “The danger of the ones we have today is that they imply a false precision that could be worse for climate outcomes than just being honest about uncertainty.”
The climate community has always fought about carbon accounting, but recently the quarrel has reached a fever pitch. The Greenhouse Gas Protocol, a nonprofit that sets voluntary standards for how companies should measure their emissions, is in the middle of overhauling its rules, a process that has sparked major schisms over how to account for companies’ clean electricity purchases, the carbon stored in forests, and other complex aspects of corporate carbon bookkeeping.
At the same time, the Science Based Targets Initiative, a separate group that acts as an arbiter of whether companies’ climate plans are consistent with the goal of limiting global warming to 1.5 degrees Celsius, has been updating its own standard for “corporate net zero.” A third group, the International Organization for Standardization, is also revising its greenhouse gas reporting rulebooks.
The challenge across all of these efforts is developing standards that are scientifically rigorous but not so rigid as to discourage companies from acting. Companies are lobbying these revision processes to get the rules they want, but many experts worry the outcomes will enable greenwashing.
Flegal joins a growing chorus of thought leaders arguing that this system that feigns precision and prioritizes compliance with an impossible bottom line risks pushing companies away from doing anything at all. Some propose getting rid of individual carbon targets altogether in favor of more qualitative reporting, while others advocate for creating a separate space for companies to earn recognition for their harder-to-measure “contributions” to fighting climate change.
In September, Michael Gillenwater, the executive director of the Greenhouse Gas Management Institute, who has been working on carbon accounting issues for more than 20 years, called for a “paradigm shift” in corporate climate reporting. He and Derik Broekhoff of the Stockholm Environment Institute, another 20-year soldier in this space, argue that boiling down a company’s climate impact to a single inventory of emissions traps “companies in a ’doom loop’ where they are simultaneously criticized for not taking full responsibility for indirect emissions and for greenwashing when they attempt to address these emissions through market-based mechanisms,” such as renewable energy certificates.
They propose instead a “multi-statement” reporting framework in which companies would separate their actual, physical emissions from their investments in carbon offsets, renewable energy certificates, and other market-based tools for climate mitigation. This system reframes carbon credits from “compensating” for a company’s ongoing emissions to playing a more philanthropic role in achieving global net zero and “eliminates the perception that companies can be absolved of responsibility through offsetting,” they write. They also propose a third section where companies would report on remaining barriers to decarbonizing their particular business. Companies could set targets for each section individually, but would not be allowed to combine them into a single performance metric.
Robert Hoglund, the co-founder of the carbon removal tracking site CDR.fyi and head of climate at Milkywire, a corporate advisory firm, published yet another idea in a paper earlier this month. He and his co-author argue that the distinction existing frameworks make between a company’s “direct” and “indirect” emissions doesn’t actually illuminate what’s within its control to reduce. They recommend companies split their net zero targets into two categories, separating “unconditional” emissions cuts — those that are currently feasible — from “conditional” reductions, or those that depend on changes in policy, infrastructure, technoeconomics, etc.
Creating a conditional target “does not make it optional,” they write. “It creates an obligation to help build the world the target assumes. That means policy advocacy, supplier engagement, financing climate solutions, supporting carbon removal, and other system-changing actions are not side activities but flow from the target itself.”
The Science Based Targets Initiative published its new net zero standard this past week, and it appears to adopt at least some of the ideas Flegal, Gillenwater, and Hoglund proposed — namely, attention to systemic constraints. It shifts from looking only at absolute emission reductions to recognizing companies for putting their “best efforts” toward net zero. It stops short, however, of explaining how SBTi will judge what counts as a “best effort.” It also allows companies to use some kinds of carbon certificates to lower their emissions on paper.
Based on an initial read, Hoglund told me he thought SBTi made some positive changes. Flegal hadn’t had a chance to dig into them yet when we spoke. Another critic I spoke to was less pleased.
If Lisa Sachs, the director of Columbia University’s Center on Sustainable Investment, had her way, companies would get rid of net zero targets altogether. She published her own treatise on the subject in May, pointing out that corporate net zero “relies on a mistaken aggregation logic.” It assumes that if every company works to reduce, offset, or neutralize their own emissions, the efforts will sum up to global net zero. Like Flegal, she told me that not only is that impossible without systems change, but she fears that company-level net zero goals “disincentivize the things companies can and should do that would have maximum systems impact.”
While it’s relatively common today for companies to talk openly about the systemic barriers they face in decarbonizing, it’s much more rare for them to say what they’re doing about it. I asked Flegal whether she truly believed sustainability officers would be able to get CEO approval for investments in “systems change,” which is more difficult to break down into clear KPIs.
She pointed out that a lot of companies already make significant philanthropic investments, and this could be put in that bucket. In some cases, like when grid constraints are a barrier to powering a new facility, they could argue that investing in transmission lines is a strategic move and not just part of their climate commitment.
Actions like lobbying in support of regulatory reform and other policy changes seem like a harder sell. The investor-led initiative Climate Action 100+ tracks how companies are attempting to influence climate-related policy debates, and has consistently found that few companies — just 2%, in the latest count — align their lobbying activities with their climate goals.
Reading these papers took me back to 2019 and 2020, when many companies first made net zero commitments. In one sense, it felt like a sea change — all these powerful corporations publicly dedicating themselves to a net zero future — but it was also dubious. They all seemed to have a different definition of what “net zero” meant. For some oil and gas companies, it meant zero-ing out the emissions from their operations, but not from the oil and gas they sold. A lot of companies made the pledge without providing any details about how they would achieve it. SBTi started developing its first net zero standard in 2020 to address this problem by creating a common definition and set of expectations. While having SBTi validate a company’s net zero target is entirely voluntary, more than 11,000 companies have done it.
When I mentioned this history to Flegal and Sachs, they countered that the problem SBTi is trying to address is downstream of the actual problem — that a voluntary net zero framework for companies creates incentives that are not aligned with what really matters for decarbonization.
Both also raised the opportunity cost of the enormous intellectual and financial capital that has gone into refining all of these accounting methodologies and producing reams of reporting to comply with them. “All of these organizations and rule setters for the rule setters for the rule setters, I think we’ve gotten lost in the sauce a bit,” Flegal said.
“These frameworks have become a business — literally a business, in SBTi’s case,” Sachs said, since it has a for-profit arm that validates companies’ reporting for a fee. “I’d rather have a few leaders who raise the tide than to have 11,000 companies aligned with SBTi, and to be finding ourselves in five years figuring out another way to lower the standard.”
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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.