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The founder of one-time sustainable apparel company Zady argues that policy is the only that can push the industry toward more responsible practices.

Everlane’s reported sale to Shein has left many shocked and saddened. How could the millennial “radical transparency” fashion brand be absorbed by the company that has become shorthand for ultra-fast fashion? While I feel for the team within the company that cares about impact reduction, I am not surprised by the news.
Everlane was built around a theory of change that was always too small for the problem it claimed to address — that better brands and more conscientious consumers could redirect a coal-powered, chemically intensive, globally fragmented industry.
The theory had real appeal, but it was wrong. Yes, it created some better products, but it was never going to remake the fashion industry on its own.
This is the tension at the center of sustainable fashion: Consumer demand can create a niche, even a meaningful one, but it cannot reconfigure the economics of global supply chains. What is needed are common sense laws that require all significant players to play by the same basic rules: reduce emissions, ban toxic chemicals, and maintain basic labor standards.
A company I used to run, Zady, was an early competitor to Everlane, and we were part of the same cultural and commercial moment. When we raised money, we told investors that while our Boomer parents may have thought that changing the world meant marching on the streets, we knew better. Change was going to happen through business.
The problem was that, while our market was growing, fast fashion was growing faster. There was a small but passionate group of consumers trying to buy better, but the overall system drove companies to produce more — more units, more emissions, more chemicals, and more waste.
The truth is that brands do not have direct control over the environmental impacts of their products. Most of the emissions and applications of chemicals are not happening at the brand level, but are instead in fiber production, textile mills, dyehouses, finishing facilities, and laundries, all of which the brands do not own. These factories operate on the thinnest of margins, and the open secret is that brands share these suppliers. No one brand wants to pay the cost for their shared factories to make the necessary upgrades to address their impacts. It’s a classic collective action problem.
Everlane’s capital story matters here, too. Unless a founder arrives with substantial personal wealth, outside investment is often the only path to scale. A company can remain small, independent, and slow-growing, but then it will likely be more expensive, more limited in reach, and less able to influence factories.
Everlane chose the other path. It took institutional growth capital from storied venture firms more closely associated with the digital revolution (including some that also fund clean energy technologies) and became a recognizable national brand. This obligated the company to operate inside a financial structure that leads inexorably toward some kind of exit, whether through a sale, an initial public offering, or some other liquidity event. Once that is the operating system, sustainability can remain a real and important goal, but it is not the final governing logic — investor return is.
“Radical transparency” was never enough to solve the fashion industry’s or venture capital model’s structural problems. Naming a factory is not the same as knowing what happens inside it. Publishing a supplier list does not tell us whether the facility runs on coal, whether wastewater is treated before being released back into the ecosystem, or whether restricted substances are present in dyes, finishes, trims, or coatings.
We already have many forms of transparency in American capitalism. Public companies, for example, are required to disclose executive compensation and the average pay of their workers; this transparency has done exactly nothing to close the pay gap. A disclosure is not the same thing as a legal standard.
So what does this mean for all of us? We don’t know exactly how Shein will absorb Everlane. I could guess that this is a Quince play for Shein, a way to access higher-end consumers that would otherwise never go on the Shein site.
What this tragicomedy reveals is that the idea born from Obama-era optimism, that the arc of history naturally bends toward justice and sustainability, was ephemeral.
The work to make this coal-powered industry sustainable will come from regulation. The technology to decarbonize is there, and unlike with aviation, for instance, it would cost the apparel industry a mere 2 cents per cotton t-shirt to get it done. But unlike with aviation, there are no requirements or incentives that these investments be made, so they are not.
The electric vehicle industry got a head start through direct subsidies and fuel efficiency standards. Apparel needs the same.
If you’re disappointed or angry about this turn of events, I ask you to channel those feelings into citizenship. Help pass the New York or California Fashion Acts that would require all large fashion companies that sell into the states to reduce their emissions and ban toxic chemicals. It’s currently legal to have lead on adult clothing, and Shein is consistently found to have it on their products. The industry is pushing back through their trade associations, so people power is needed so that legislators know it needs to be their priority.
But if you want to shop sustainably, you don’t need a brand. What is most helpful is understanding your own style and lifestyle — that’s how we know what we actually need and what we don’t. There are apps to help on that front. (I love Indyx, for instance, but there are others.)
The only way forward is together, and that means political solutions — emissions requirements, chemical requirements, labor requirements — not just consumer ones.
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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.