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New rules governing how companies report their scope 2 emissions have pit tech giant against tech giant and scholars against each other.

All summer, as the repeal of wind and solar tax credits and the surging power demands of data centers captured the spotlight, a more obscure but equally significant clean energy fight was unfolding in the background. Sustainability executives, academics, and carbon accounting experts have been sparring for months over how businesses should measure their electricity emissions.
The outcome could be just as consequential for shaping renewable energy markets and cleaning up the power grid as the aforementioned subsidies — perhaps even more so because those subsidies are going away. It will influence where and how — and potentially even whether — companies continue to voluntarily invest in clean energy. It has pitted tech heavyweights like Google and Microsoft against peers Meta and Amazon, all of which are racing each other to power their artificial intelligence operations without abandoning their sustainability commitments. And it could affect the pace of emissions reductions for decades to come.
In essence, the fight is over how to appraise the climate benefits of companies’ clean power purchases. The arena is the Greenhouse Gas Protocol, a nonprofit that creates voluntary emissions reporting standards. Companies use these standards to calculate emissions from their direct operations, from the electricity and gas that powers and heats their buildings, and from their supply chains. If you’ve ever seen a brand claim it “runs on 100% renewable energy,” that statement is likely backed by a Greenhouse Gas Protocol-sanctioned methodology.
For years, however, critics have poked holes in the group’s accounting rules and assumptions, charging it with enabling greenwashing. In response, the organization has decided to overhaul its standards, including for how companies should measure their electricity footprint, known as “scope 2” emissions.
The Greenhouse Gas Protocol first convened a technical working group to revise its Scope 2 Standard last September. By late June, the group had finalized a draft proposal with more rigorous criteria for clean energy claims, despite intense pushback on the underlying direction from companies and clean energy groups.
A flurry of op-eds, essays, and LinkedIn posts accused the working group of being on the “wrong track,” and called the proposal a “disaster” with “unintended consequences.” The Clean Energy Buyers Association, a trade group, penned a letter saying it was “inefficient and infeasible for most buyers and may curtail ambitious global climate action.” Similarly, the American Council on Renewable Energy warned that the plan “could unintentionally chill investment and growth in the clean energy sector.”
Next the draft will face a 60-day public consultation period that begins in early October. “There’ll be pushback from every direction,” Matthew Brander, a professor of carbon accounting at the University of Edinburgh and a member of the Scope 2 Working Group, told me. Ultimately, it will be up to the Working Group, the Protocol’s Independent Standards Board, and its Steering Committee, to decide whether the proposal will be adopted or significantly revised.
The challenge of creating a defensible standard begins with the fundamental physics of electricity. On the power grid, electrons from coal- and natural gas-fired power plants intermingle with those from wind and solar farms. There’s no way for companies hooking up to the grid to choose which electrons get delivered to their doors or opt out of certain resources. So if they want to reduce their carbon footprints, they can either decrease their energy consumption — by making their operations more efficient, say, or installing on-site solar panels — or they can turn to financial instruments such as renewable energy certificates, or RECs.
In general, a REC certifies that one megawatt-hour of clean power was generated, at some point, somewhere. The current Scope 2 Standard treats all RECs as interchangeable, but in reality, some RECs are far more effective than others at reducing emissions. The question now is how to improve the standard to account for these differences.
“There is no absolute truth,” Wilson Ricks, an engineering postdoctoral researcher at Princeton University and working group member, told me back in June. “I mean, there are more or less absolute truths about things like how much emissions are going into the atmosphere. But the system for how companies report a certain number, and what they’re able to claim about that number, is ultimately up to us.”
The current standard, finalized in 2015, instructs companies to report two numbers for their scope 2 emissions, based on two different methodologies. The formula for the first is straightforward: multiply the amount of electricity your facilities consume in a given year by the average emissions produced by the local power grids where you operate. This “location-based” number is a decent approximation of the carbon emitted as a result of the company’s actual energy use.
If the company buys RECs or similar market-based instruments, it can also calculate its “market-based” emissions. Under the 2015 standard, if a company consumed 100 megawatt-hours in a year and bought 100 megawatt-hours’ worth of certificates from a solar farm, it could report that its scope 2 emissions, under the market-based method, were zero. This is what enables companies to claim they “run on 100% renewable energy.”
RECs are fundamentally different from carbon offsets, in that they do not certify that any specific amount of emissions has been prevented. They can cut carbon indirectly by creating an additional revenue stream for renewable energy projects. But when a company buys RECs from a solar project in California, where the grid is saturated with solar, it will do less to reduce emissions than if it bought RECs from a solar project in Wyoming, where the grid is still largely powered by coal, or from a battery storage project in California, which can produce clean power at night.
There are other ways RECs can vary — for instance, companies can buy them directly from power producers by means of a long-term contract, or as one-off purchases on the spot market. Spot market REC purchases are generally less effective at displacing fossil fuels because they’re more likely to come from pre-existing wind and solar farms — sometimes ones that have been operating for years and would continue with or without REC sales. Long-term contracts, by contrast, can help get new clean energy projects financed because the guaranteed revenue helps developers secure financing. (There are exceptions to these rules, but these are broadly the dynamics.)
All this is to say that the current standard allows for two companies that consumed the same amount of power and bought the same number of RECs to report that they have “zero emissions,” even if one helped reduce emissions by a lot and the other did little to nothing. Almost everyone agrees the situation can be improved. The question is how.
The proposal set for public comment next month introduces more granularity to the rules around RECs. Instead of tallying up annual aggregate energy use, companies would have to tally it up by hour and location. To lower companies' scope 2 footprints further, purchased RECs will have to be generated within the same grid region as the company’s operations, and match a distinct hour of consumption. (This “hourly matching” approach may sound familiar to anyone who followed the fight over the green hydrogen tax credit rules.)
Proponents see this as a way to make companies’ claims more credible — businesses would no longer be able to say they were using solar power at night, or wind power generated in Texas to supply a factory in Maine. While companies would still not be literally consuming the power from the RECs they buy, it would at least be theoretically possible that they could be. “It’s really, in my view, taking how we do electricity accounting back to some fundamentals of how the power system itself works,” Killian Daly, executive director of the nonprofit EnergyTag, which advocates for hourly matching, told me.
The granularity camp also argues that these rules create better incentives. Today, companies mostly buy solar RECs because they’re cheap and abundant. But solar alone can’t get us to zero emissions electricity, Ricks told me. Hourly matching will force companies to consider signing contracts with energy storage and geothermal projects, for example, or reducing their energy use during times when there’s less clean energy available. “It incentivizes the actions and investments in the technologies and business practices that will be needed to actually finish the job of decarbonizing grids,” he said.
While the standard is technically voluntary, companies that object to the revision will likely be stuck with it, as governments in California and Europe have started to integrate the Greenhouse Gas Protocol’s methodologies into their mandatory corporate disclosure rules.
The proposal’s critics, however, contend that time and location matching will be so costly and difficult to implement that it may lead companies to simply stop buying clean energy. One analysis by the electricity data science nonprofit WattTime found that the draft revision could increase emissions compared to the status quo if it causes a decline in corporate clean power procurement. “We’re looking at a potentially really catastrophic failure of the renewable energy market,” Gavin McCormick, the co-founder and executive director of WattTime, told me.
Another concern is that companies with operations in multiple regions could shift from signing long-term contracts for RECs, often called power purchase agreements, to relying on the spot market. These contracts must be large to be beneficial for developers because negotiating multiple offtake agreements for a single renewable energy project increases costs and risk. Such deals may still make sense for big energy users like data centers, but a company like Starbucks, with cafes throughout the country, will have to start sourcing fewer RECs in more places to cover all the parts of the world where they operate.
The granularity fans assert that their proposal will not be as challenging or expensive as critics claim — and regardless, they argue, real decarbonization is difficult. It should be hard for companies to make bold claims like saying they are 100% clean, Daly told me. “We need to get to a place where companies can be celebrated for being like, I’m not 100% matched, but I will be in five years,” he said.
The proposal does include carve-outs allowing smaller companies to continue to use annual matching and for legacy clean energy contracts, even if they don’t meet hourly or location requirements. But critics like McCormick argue that the whole point of revising the standard is to help catalyze greater emission reductions. Less participation in the market would hurt that goal — but more than that, these accounting rules aren’t designed to measure emissions, let alone maximize real-world emission reductions. You could still have one company that spends the time and money to invest in scarce resources at odd hours and achieves 60% clean power, while another achieves the same proportion by continuing to buy abundant solar RECs. Both would still get to claim the same sustainability laurels.
The biggest corporate defender of time and location matching is Google. On the other side are tech giants Meta and Amazon, among others, arguing for an approach more explicitly focused on emissions. They want the Greenhouse Gas Protocol to endorse a different accounting scheme that measures the fossil fuel emissions displaced by a given clean energy purchase and allows companies to subtract that amount from their total scope 2 footprint — much more akin to the way carbon offsets work.
If done right, this method would recognize the difference between a solar REC in California and one in Wyoming. It would give companies more flexibility, potentially deploying capital to less developed parts of the world that need help to decarbonize. It could also, eventually, encourage investment in less mature and therefore more expensive resources, like energy storage and geothermal — although perhaps not until there’s solar panels on every corner of the globe.
This idea, too, is risky. Calculating the real-world emissions impact of a REC, which the scope 2 working group calls “consequential accounting” is an exercise in counterfactuals. It requires making assumptions about what the world would have looked like if the REC hadn’t been purchased, both in the near term and long term. Would the clean energy have been generated anyway?
McCormick, who is a proponent of this emissions-focused approach, argues that it’s possible to measure the counterfactual in the electricity market with greater certainty than with something like forestry carbon offsets. With electricity, he told me, “there's five minute-level data for almost every power plant in the world, as opposed to forests. If you're lucky, you measure some forests, once a year. It's like a factor of 10,000 times more data, so all the models are more accurate.”
Some granularity proponents, including Ricks, agree that consequential accounting is valuable and could have a place in corporate reporting, but worry that it’s ripe for abuse. “At the end of the day, you can't ever verify whether the system you're using to assign a given company a given number is right, because you can't observe that counterfactual world,” he said. “We need to be very cautious about how it’s designed, and also how companies actually report what they’re doing and what level of confidence is communicated.”
Both proposals are flawed, and both have potential to allow at least some companies to claim progress on paper while having little real-world impact. In some ways, the disagreement is more philosophical than scientific. What should this standard be trying to achieve? Should it be steering corporate dollars into clean energy, accuracy of claims be damned? Or should it be protecting companies from accusations of greenwashing? What impacts do we care about more, faster emissions reductions or strategic decarbonization?
“They’re actually not opposing views,” McCormick told me. “There’s these people making this point and there’s these people making this point. They’re running into each other, but they’re actually not saying opposite things.”
To Michael Gillenwater, executive director of the Greenhouse Gas Management Institute, a carbon accounting research and training nonprofit, people are attempting to hide policy questions within the logic and principles of accounting. “We’re asking the emissions inventories to do too much — to do more than they can — and therefore we end up with a mess,” he told me. Corporate disclosures serve many different purposes — helping investors assess risk, informing a company’s internal target setting and performance tracking, creating transparency for consumers. “A corporate inventory might be one little piece of that puzzle,” he said.
Gillenwater is among those that think the working group’s time- and location-matching proposal would stifle corporate investment in clean energy when the goal should be to foster it. But his preferred solution is to forget trying to come up with a single metric and to encourage companies to make multiple disclosures. Companies could publish their location-based greenhouse gas inventory and then use market-based accounting to make a separate “mitigation intervention statement.” To sum it up, Gillenwater said, “keep the emissions inventory clean.”
The risk there is that the public — or indeed anyone not deeply versed in these nuances — will not understand the difference. That’s why Brander, the Edinburgh professor, argues that regardless of how it all shakes out, the Greenhouse Gas Protocol itself needs to provide more explicit guidance on what these numbers mean and how companies are allowed to talk about them.
“At the moment, the current proposals don’t include any text on how to interpret the numbers,” he said. “It’s almost incredible, really, for an accounting standard to say, here’s a number, but we’re not going to tell you how to interpret it. It’s really problematic.”
All this pushback may prompt changes. After the upcoming comment period closes in late November or early December, the working group could decide to revise the proposal and send it out for public consultation again. The entire revision process isn’t estimated to be completed until the end of 2027 at the earliest.
With wind and solar tax credits scheduled to sunset around then, voluntary action by companies will take on even greater importance in shaping the clean energy transition. While in theory, the Greenhouse Gas Protocol solely develops accounting rules and does not force companies to take any particular action, it’s undeniable that its decisions will set the stage for the next chapter of decarbonization. That chapter could either be about solving for round-the-clock clean power, or just trying to keep corporate clean energy investment flowing and growing, hopefully with higher integrity.
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The administration filed to dismiss an appeal of a December ruling that overturned its offshore wind permitting freeze.
Trump’s Department of Justice is giving up on defending the president’s offshore wind permitting moratorium.
The DOJ filed a motion on Wednesday to dismiss its appeal of a federal court’s December decision vacating the order to halt offshore wind approvals. The plaintiffs in the case — New York and 16 other states, as well as the Alliance for Clean Energy New York, a trade group — did not oppose the motion. The case will not be officially dismissed, however, until the First Circuit Court of Appeals approves the request, which typically happens quickly when both parties support the dismissal.
The case stems from an executive order President Trump issued on the first day of his current term temporarily withdrawing all areas of the outer continental shelf from offshore wind leasing and pausing all federal authorizations for offshore wind projects while the administration conducted a review of leasing and permitting practices.
States took the administration to court last May, arguing that the order was arbitrary and capricious and violated the Administrative Procedures Act. They claimed it harmed their ability to source reliable and affordable energy and threatened billions of dollars in investment in supply chains, workforce development, and wind industry-related infrastructure.
On December 8, Judge Patti B. Saris of the U.S. District Court for the District of Massachusetts ruled in the states’ favor and vacated the offshore wind order. More specifically, the judge vacated the portion of the order directing agencies to pause permits and other authorizations. The withdrawal of areas eligible for new leases remains in effect.
The Trump administration appealed the ruling to the First Circuit in February, but never submitted an opening brief. The initial deadline was May 11, but on May 4, the DOJ requested additional time to file the brief. The judge gave the defendants until June 10. On that date, the defendants filed the motion to dismiss.
This is a developing story and we’ll update it as we learn more about the administration’s actions and their effects.
The data center water issues are real – but they aren’t what you think.
Too often, I hear people say the number one reason they’re against data center development is water use. Heatmap’s data shows water consumption is historically the reason cited most often by activists when opposing projects. This complaint, they often say, is rooted in the fear that this nascent buildout of AI infrastructure will simply draw so much H2O it will leave little liquid left for the rest of us.
I spent weeks trying to understand how real the water use problem is when it comes to data centers, reading research and speaking to some of the world’s leading academics, large tech firms, and environmental advocates to make my best attempt at answering some of the most important questions being asked about data centers.
Before I jump into this thicket, a few caveats. I’m not going to address the host of water pollution concerns many have raised about data centers because that is for a future article. If you want me to dissect how Rep. Alexandria Ocasio-Cortez got a jar of dirty water near a Meta data center, that was poor construction practices – not a data center’s water demand. By that same token, if you're itching for me to find out how much PFAS is in data center water, I’m not delving into that here, though I’ll just say PFAS is everywhere and isn’t a data center-specific issue.
So are there problems with AI data centers’ water use? Yes. Are data centers using too much water for society to handle? It depends on what “too much” means to you. Is the AI data center boom going to usher in a new era of drought across the United States? Probably not, but there’s a few places we should be mindful of.

Researchers told me data center water use is a painfully understudied topic rendered more obscure by a lack of public information about individual H2O consumption at the project level. Those I spoke to were split on how seriously to take the topic.
Some analyses insist the sector’s water use should be regulated and tackled head-on by the sector. I spoke with Yi Ding, an assistant professor at Purdue University, who co-authored a paper laying out a framework for evaluating the water impact of computing weighted specifically for water stress. Ding told me there is currently no set of industry-led best practices for sustainable water-conscious data center operation and her work aims to fill that gap.
When I asked Ding if data centers are actually threatening individual towns’ water supplies, she didn’t hesitate: “Yes, it’s significant.”
Others in this field have the opposite view.
“Water is often brought up as the primary concern when it’s less important,” David Mytton, a sustainable computing researcher at Oxford University, told me. “The more important thing is going to be how you bring more clean energy onto the grid, and nuclear power, so that we can generate sufficient energy to build these centers.”
Large tech companies are starting to spend less time debating the extent of the problem and more bandwidth addressing the PR crisis surrounding data center and AI water use.
Ben Townsend, Google’s head of infrastructure and sustainability, told me he believes that “from a comms and PR perspective” he has “no doubt” it would be easier to build data centers without the debate over water. “Data centers operators are not explaining why they’re using water or how much water they use. There’s a complete lack of transparency or discussion.”
Google has been getting splashy around this topic, a public relations strategy that reminds me of Meta’s recent workforce training investments. Last week, Google announced five fresh “commitments” towards its “climate-conscious approach” to water use, including a pledge to “replenish more water than we consume at our sites” by 2030.
This week, Amazon made a similar declaration and claimed its operations are 75% of the way to accomplishing this goal, which it’s calling “water positive.” Brandon Oyer, director of energy and water at Amazon Web Services, told me he thinks the industry “could’ve done better” and “come out earlier” to address its water use.
“There’s just been a lot of misinformation that has led people to [be] a little bit alarmist. And rightfully so. I would get alarmed if I thought that water was going to be impacted in my community,” Oyer said.
The basics of data center water use
Data centers need water to cool large server racks whizzing away to power AI and most other internet practices, from streaming to online banking. Normally, you don’t want computers to get too hot because then they can crash causing potentially catastrophic harm to the machine.
This water use presents a number of environmental challenges. Often, server farms rely on clean, fresh water, or filtered drinking water, a need largely for functionality reasons. They’re competing for this resource at a time when supply is dwindling amidst the crisis of global warming.
Making matters worse, much of the U.S. has faced drought conditions over the past year, including states that are typically water abundant, like Virginia and Georgia, that are at the center of the data center boom. On Monday, The Guardian reported that more than half of all planned data centers in the U.S. are in “locations that have been in drought conditions throughout the past year,” citing data center site information from federal agencies and the energy data firm Cleanview.
In the top data center destination of Texas, where peak electricity demand could more than quadruple in the near future, analysis from state university researchers released in May found data centers could wind up between 3% to 9% of water demand by 2040. Projects are being developed near cities like Corpus Christi and El Paso that were already fearful their drinking water supplies would dry up before the AI infrastructure boom came to town.
“The impact of building a data center in Arizona versus Wyoming is very different,” said Ding, the Purdue University researcher. “[Companies] will say different things because of their position. The problem is substantial and sometimes it’s not that they don’t want to use water – it means they don’t have water to use.”
The most water intensive version of data center cooling is called “evaporative cooling,” which mixes water evaporation and ventilation air flow to cool rooms in ways industry compares to human sweat. Evaporative cooling uses a lot of water and regular fresh supply because, well, the water goes away once it evaporates.
One Google data center using evaporative cooling in Council Bluffs, Iowa used more than 1 billion gallons of water in 2024, a stat that made the project a poster child for perceived excesses in water use. Somewhat ironically, we know this because Google is one of the few large tech companies to voluntarily disclose direct water consumption from individual data centers on an annual basis.
But cooling tech is becoming much more water efficient. You may have heard of “closed loop cooling” – that’s when a chilling system is supposedly self-contained. These systems as designed typically rely on loops of pipes filled with coolant flowing through them. This means they should not expel much liquid. If the modern trend in data center development skewed towards closed-loop systems, it would theoretically mean very little new water supply drawn on the average day.
“If you’re using a closed loop system, the water goes into the data center and then it doesn’t really require a refill every so often. It’s a one-time thing,” Mytton said. “If you’re using evaporative cooling, the water is continuously evaporating into the atmosphere. That’s when it’s being drawn from water sources.”
Closed-loop systems aren’t perfect because of ordinary issues like leaks. These flaws have meant this innovation has done little to assuage the loudest local concerns about water use. Critics of the sector have pointed to estimates pegging a closed-loop failure rate up to 25%. But Mytton said this criticism against closed-loop cooling systems is a little misguided. “They’re just wrong. They just don’t understand how data centers work.”
Closed loop systems and water-free cooling processes (like simple air vent-based cooling) also have trade-offs, particularly the extra energy and chemicals required to make these loops work to spec. Given data center developers are often choosing gas-fired power, which also requires water and produces greenhouse gas emissions, more power for less water is hardly a comfortable trade-off from an environmental perspective.
“‘Closed-loop cooling’ is a marketing gimmick,” proclaimed anti-data center group Food and Water Watch in an April blog post, calling the practice “greenwashing” and “just clever advertising.”
We do not know right now how much water most data centers are actually using, sans a handful of companies reporting individual facility use like Google. The data center development space – Big Tech, their subsidiaries, start ups, real estate firms – is mostly keeping their individual facility water usage private, and there isn’t really any regulation at any level of government to compel this information to be released in the United States, despite it being the number one destination for data center development. Corporations often consider these figures proprietary and municipal governments often consider this confidential business information, making it likely to be redacted or withheld from public records requests.
For example, in Wisconsin, an environmental group sued the city of Racine when officials refused to give water use projections for Microsoft’s data center campus in the nearby village of Mount Pleasant, about five miles from the shores of Lake Michigan. The projections were ultimately released under court order, showing Microsoft’s data center campus was projected to use up to 234,000 gallons of water on peak days or up to 2.8 million per year; eventually those numbers could almost triple to 702,000 gallons on peak days, or almost 8.5 million gallons a year.
These projections, according to Microsoft, are for a facility where more than 90% of the facility will rely on closed-loop cooling. The rest of the data center campus “will use outside air for cooling, switching to water only on the hottest days.” The company has called this design a “technological milestone” that’ll use “roughly the amount of water a typical restaurant uses annually.”
Microsoft is accurate here: the average eatery uses roughly 250,000-to-300,000 gallons of water a year according to restaurant sustainability advocates, a level of consumption that’s led restaurants to be roughly 15 percent of total water use in commercial facilities in the United States.
Personally I think it is easier and more useful to compare a data center to a farm, especially given how many are fighting to stop these projects to preserve prime farmland. Agriculture doesn’t measure water consumption by the gallon; farms use far too much water for those stats to work here. Instead farms use acre-feet, which is calculated using the volume of water necessary to entirely cover an acre of land with one foot of water. For posterity, one acre-foot is almost 326,000 gallons of water, which is about the maximum daily water consumption of that Microsoft data center in Mount Pleasant, Wisconsin. In 2023, the average amount of water applied to a single acre of farmland for irrigation was 1.5 acre-feet, rendering this figure comparable to a large Microsoft data center. This is still a lot of water and not a 1:1 comparison, since different crops require water at different times. But even if a data center consumed that much water every day for a full year, that’s 365 days. An average large farm is a little more than 1,400 acres and many farms span far more acreage. That’s the sort of relative scale we’re working with. So, for instance, a large family farm in Stafford County, Kansas, might use something like 420 million gallons of water over roughly 1,000 irrigated acres of corn in an average year.
I’m no farming expert – there might be things about farmland irrigation I don’t necessarily understand. But it's hard for me to look at these numbers and not long for some sort of rethinking about how we’re doing water math with data centers, especially given the environmental trade-offs around using less water.
Honestly I don’t think trying to explain this math helps anymore because secrecy may have spoiled the well in Racine, pun intended. In September, a peer-reviewed study by University of Wisconsin researchers found the Mount Pleasant datacenter had become “a microcosm of a macro problem with secrecy.” The paper stated that while closed-loop systems at the Mount Pleasant facility “may significantly reduce water use during some of the year, there is still a question of transparency and why it has been so difficult to obtain clear answers about water use.” Full transparency around water use, as well as the energy required for water-lite cooling practices, would be “essential” for any future research into industry practices “to have credibility,” the study stated.
Asked for comment on the study, a Microsoft spokesperson said via email: “Our datacenter campus in Mount Pleasant leverages the latest and most innovative cooling technology available. In past datacenter designs, water has played a key role in datacenter cooling and humidification, but our new designs aim to eliminate this continuous need for municipal water for cooling. The bottom line is that this data center, and others we build in the future, will not require massive amounts of water.”
When you zoom out further, water use by sector shows that U.S. data centers are not the leading driver of water use and its scarcity to date. Thermal power (fossil energy) and agriculture are by far the largest users of water in the U.S. economy, and it would be challenging for the data center industry to ever catch up. Industry figures collected in 2015 found thermo-electric power used roughly 132.4 billion gallons of water per day. Irrigation was a close second at 118 billion gallons of water daily. By comparison, researchers have noted International Energy Agency estimates that the entire global data center sector consumed a comparable amount of water during all of 2023. These are pre-AI boom numbers, but they tell us a lot about relative scale.
However, once again, researchers, tech companies, and advocates alike all told me they believe this macro picture elides individual communities and transparency issues are rendering these comparisons unhelpful for calming concerns down. The data center conflicts are local matters felt acutely, especially in places where drinking water is either hard to come by or expensive. Your average rural desert town or midwestern farming district cares little about the world; they want to know if their own wells will run dry. As Amazon’s Oyer told me, “The hyperlocal influence you can have on a water supply is why it becomes top of mind for people.”
One way to measure data center water impacts in aggregate may be to quantify the potential infrastructure upgrades necessary to meet the industry’s demand. A new study by researchers at University of California-Riverside and CalTech found that new water infrastructure spending for data centers alone could total as much as $58 billion in only four years time. These upgrades will be necessary in order for municipal water supplies to withstand peak demand on the hottest days of the year, a need akin to grid resilience upgrades. Not to mention our nation’s sewer systems are in desperate need of upgrades.
“If a data center was able to show they weren’t stripping our water resources and convinced a community they have mitigation strategies at the local level, that’s a theoretical path,” said Kathryn Hoffman, executive director of the Minnesota Center for Environmental Advocacy. Her organization has successfully stalled data center projects in the state with lawsuits arguing city and county environmental reviews are failing to account for the full extent of local resource usage, including water.
“Unfortunately, we’re a long way from that,” Hoffman added.
And more of this week’s biggest news around project fights.
1. Matagorda County, Texas – The bipartisan data center backlash is now so powerful that a top Republican Texas state official is doing an event with the Democrat vying to replace him.
2. Albany County, New York – As we await Gov. Kathy Hochul’s decision on whether to enact the nation’s first statewide moratorium on data centers, I wanted to bring up some pretty crucial facts about the situation in the Empire State.
3. Davidson County, Tennessee – Anyone who’s anyone should be talking about Nashville.
4. Lehigh County, Pennsylvania – I’m used to eagles halting wind turbines, but now people are trying to use the birds to stop data centers.
5. Laramie County, Wyoming – We had another anti-wind rally backed by national conservatives, this time in Wyoming.
6. Ellis County, Kansas – Let’s end on a sweet note: a giant solar farm getting its permits.