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Having a true green hydrogen industry depends on that not happening.
In late December, the Treasury Department proposed draft regulations to implement the Inflation Reduction Act’s generous hydrogen production tax credit. Under Section 45V of the tax code, eligible projects must show that their life cycle greenhouse gas emissions fall below exacting benchmarks. Treasury’s final rules will determine how hydrogen projects are allowed to calculate their emissions and direct the flow of tens of billions of tax dollars — or more.
Most of the discussion that followed focused on the draft rule’s proposed guardrails for green hydrogen, which is produced from water using clean electricity. The climate policy community in particular largely approved of Treasury’s approach, in part because it lays the groundwork for hourly emissions accounting in the electricity sector — essentially, making sure that clean energy is being made and used in real time, a foundational shift needed for deep decarbonization.
But when it comes to producing hydrogen from methane — which is how nearly all hydrogen is made today — Treasury’s draft was incomplete. In place of a concrete proposal, the draft regulations raised detailed technical questions about what should be allowed in the final rule. Among these was the suggestion that hydrogen production from fossil fuels might qualify for tax credits by using methane offsets. This, quite simply, would undermine the tax credit’s entire purpose.
If the final regulations authorize methane offsets, then the 45V tax credit could end up subsidizing fossil fuel projects, stifling the nascent green hydrogen industry and locking in emissions-intensive infrastructure for decades to come. Just as concerning, authorizing offsets for the hydrogen production tax credit would also pave the way for similar treatment in the upcoming implementation of technology-neutral clean energy production ( Section 45Y) and investment tax credits (Section 48E).
To understand how offsets could affect the strategic outlook for the hydrogen industry, we looked at how the Treasury Department calculates the life cycle emissions of hydrogen production from natural gas, which is essentially just methane. Treasury’s draft regulations propose to use a bespoke life cycle analysis model to determine whether hydrogen projects qualify for the tax credit, and if so, what level of support they will receive.
This model has several important features: It accounts for CO2 emitted in the process of producing hydrogen from methane, which is straightforward, as well as methane emissions from upstream gas production, processing, and pipeline transportation, which is not. (Unfortunately, it doesn’t include impacts from hydrogen, which itself is an indirect greenhouse gas that contributes to global warming.)
The model’s treatment of methane emissions is particularly important. Although the academic literature suggests a national average above 2% and finds impacts above 9% in some cases, the model assumes that gas supply chains emit only 0.9% of the methane they deliver. Differences in methane emissions matter a lot, even when they look small. That’s because methane traps about 30 times as much heat as CO2 over a 100-year period, so its calculated CO2-equivalence is that much larger.
As a result, Treasury’s proposed approach undercounts the true climate impacts of hydrogen production, particularly hydrogen made from methane. Even so, fossil hydrogen production faces a narrow path to qualifying for the tax credit. For example, a fossil hydrogen project would have to capture more than 70% of its CO2 emissions and buy enough clean electricity to power all its operations — either directly as energy or indirectly as energy credits — even to qualify for the lower tiers of the tax credit. And even though projects’ actual methane emissions are likely to be undercounted, the model’s assumptions are enough to disqualify fossil projects from the highest tax credit tier, which is substantially more lucrative than any of the others.
Because of the difficulty of achieving high CO2 capture rates, some analysts have argued that fossil hydrogen projects will instead wind up applying for tax credits under Section 45Q of the IRA, which provides incentives for sequestering CO2 underground without the hydrogen tax credit’s exacting emissions standards.
But a fossil hydrogen project can claim totally different outcomes if it’s allowed to buy environmental certificates that claim to avoid methane emissions in the first place, a.k.a. methane offsets. The logic goes like this: If someone else was going to emit methane to the atmosphere, but agrees instead to capture and inject it into a gas pipeline network, then a hydrogen producer can buy a certificate from that other methane producer representing that same captured gas and potentially treat their own fossil gas as negative emissions.
For example, consider a large dairy that sends cow manure to uncovered manure lagoons, which produce significant methane emissions. Suppose the dairy installs a methane capture system and sells credits to a hydrogen producer, which then claims to have avoided the dairy’s methane emissions — even if these emissions could be avoided in other ways, like alternative manure management or flaring. Because methane is considered almost 30 times more impactful than CO2 over a 100-year period, the CO2-equivalence of avoiding methane emissions is larger than the project’s direct CO2 emissions, and therefore the resulting hydrogen production process gets a negative carbon intensity score.
If your head is spinning at this point, welcome to the world of offsets. Outcomes depend on counterfactual scenarios that can’t be measured or observed, burning fossil fuels can supposedly reduce pollution, and even the verb tenses are hard to parse.
Vertigo aside, the practical implications of methane offsets for the hydrogen production tax credit are enormous. Without methane offsets, fossil hydrogen projects couldn’t benefit much from the hydrogen tax credit; even with strict carbon capture and storage pollution controls, they can't meet the life cycle requirements for the top tier and would likely prefer to claim a smaller carbon storage tax credit instead. But if projects can use methane offsets, they can easily reduce their calculated emissions to qualify for the top tier of the hydrogen production tax credit.
This would also mean these fossil projects could undercut truly clean hydrogen projects. Green hydrogen projects that comply with the draft guardrails will have to invest in novel electrolyzer technologies and new clean power sources. The top tier of the tax credit provides enough money to make clean hydrogen projects competitive, but methane offsets are a lot less expensive than electrolyzers. If fossil producers can qualify with cheap offsets, they can pocket the difference and outcompete clean producers who have to invest in costly infrastructure.
We set out to estimate the amount of methane offsetting needed to qualify fossil projects for the top production tax credit tier. You can review our calculations here; for the carbon intensity of putatively negative emissions feedstocks, we used a conservative estimate that is about half the level of what other researchers use.
Remarkably, a fossil hydrogen project without carbon capture could qualify for the top production tax credit by offsetting just 25% of its fuel use. And a fossil hydrogen project that abates 90% of its CO2 emissions could earn the top tier of the tax credit if it bought offsets for just 4% of its fuel use.
So far a lot of the discussion about negative carbon intensity scores has focused on methane captured from livestock manure, but Treasury’s draft regulations also make reference to the possibility of capturing “fugitive emissions,” which could include methane emitted from the oil and gas sector or even from coal mines. If methane offsets are made eligible across a wide range of fugitive emissions, the hydrogen tax credit — which was designed as a generous incentive to promote innovation in new technologies — could end up subsidizing incumbent emitters.
Treasury’s hydrogen regulations will also set an important precedent for how offsets are treated in other government policies. The last set of tax credits in the IRA, a pair of technology-neutral investment and production tax credits for clean electricity generation, are under development this year. It’s great news that soon the U.S. federal government will support a full range of clean technologies, not just solar and wind — but not if those policies encourage higher-emitting activities that claim to be clean through the use of offsets. There are a few existing markets for methane offsets already, and certain segments of the economy — particularly the dairy industry — are hungry for more.
At the end of the day, the Biden administration faces a similar set of issues when it comes to producing hydrogen from methane that it did with clean hydrogen produced from electricity and water. If the tax credits encourage green hydrogen projects in places where it is difficult to supply cheap and clean electricity, then those projects risk becoming stranded assets when the tax credits expire. Similarly, if the tax credits encourage hydrogen production from chemical feedstocks and methane offsets, they will prop up fossil fuel infrastructure that could keep operating long after the requirement to buy offsets expires.
For all the complexity, though, one thing is clear: We won’t get a true green hydrogen industry if the Treasury Department decides to subsidize methane offsets — which, when you put it like that, doesn’t make much sense in the first place.
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Geothermal is getting closer to the big time. Last week, Fervo Energy — arguably the country’s leading enhanced geothermal company — announced that its Utah demonstration project had achieved record production capacity. The new approach termed “enhanced geothermal,” which borrows drilling techniques and expertise from the oil and gas industry, seems poised to become a big player on America’s clean, 24/7 power grid of the future.
Why is geothermal so hot? How soon could it appear on the grid — and why does it have advantages that other zero-carbon technologies don’t? On this week’s episode of Shift Key, Rob and Jesse speak with a practitioner and an expert in the world of enhanced geothermal. Sarah Jewett is the vice president of strategy at Fervo Energy, which she joined after several years in the oil and gas industry. Wilson Ricks is a doctoral student of mechanical and aerospace engineering at Princeton University, where he studies macro-energy systems modeling. Shift Key is hosted by Robinson Meyer, the founding executive editor of Heatmap, and Jesse Jenkins, a professor of energy systems engineering at Princeton University.
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Here is an excerpt from our conversation:
Robinson Meyer: I just wanted to hit a different note here, which is, Sarah, you’ve alluded a few times to your past in the oil and gas industry. I think this is true across Fervo, is that of course, the technologies we’re discussing here are fracking derived. What has your background in the oil and gas industry and hydrocarbons taught you that you think about at Fervo now, and developing geothermal as a resource?
Sarah Jewett: There are so many things. I mean, I’m thinking about my time in the oil and gas industry daily. And you’re exactly right, I think today about 60% of Fervo’s employees come from the oil and gas industry. And because we are only just about to start construction on our first power facility, the percentage of contractors and field workers from the oil and gas industry is much higher than 60%.
Jesse Jenkins: Right, you can’t go and hire a bunch of people with geothermal experience when there is no large-scale geothermal industry to pull from.
Jewett: That’s right. That’s right. And so the oil and gas industry, I think, has taught us, so many different types of things. I mean, we can’t really exist without thinking about the history of the oil and gas industry — even, you know, Wilson and I are sort of comparing our learning rates to learning rates observed in various different oil and gas basins by different operators, so you can see a lot of prior technological pathways.
I mean, first off, we’re just using off the shelf technology that has been proven and tested in the oil and gas industry over the last 25 years, which has been, really, the reason why geothermal is able to have this big new unlock, because we’re using all of this off the shelf technology that now exists. It’s not like the early 2000s, where there was a single bit we could have tried. Now there are a ton of different bits that are available to us that we can try and say, how is this working? How is this working? How’s this working?
So I think, from a technological perspective, it’s helpful. And then from just an industry that has set a solid example it’s been really helpful, and that can be leveraged in a number of different ways. Learning rates, for example; how to set up supply chains in remote areas, for example; how to engage with and interact with communities. I think we’ve seen examples of oil and gas doing that well and doing it poorly. And I’ve gotten to observe firsthand the oil and gas industry doing it well and doing it poorly.
And so I’ve gotten to learn a lot about how we need to treat those around us, explain to them what it is that we’re doing, how open we need to be. And I think that has been immensely helpful as we’ve crafted the role that we’re going to play in these communities at large.
Wilson Ricks: I think it’s also interesting to talk about the connection to the oil and gas industry from the perspective of the political economy of the energy transition, specifically because you hear policymakers talk all the time about retraining workers from these legacy industries that, if we’re serious about decarbonizing, will unavoidably have to contract — and, you know, getting those people involved in clean energy, in these new industries.
And often that’s taking drillers and retraining some kind of very different job — or coal miners — into battery manufacturers. This is almost exactly one to one. Like Sarah said, there’s additional expertise and experience that you need to get really good at doing this in the geothermal context. But for the most part, you are taking the exact same skills and just reapplying them, and so it allows for both a potentially very smooth transition of workforces, and also it allows for scale-up of enhanced geothermal to proceed much more smoothly than it potentially would if you had to kind of train an entire workforce from scratch to just do this.
This episode of Shift Key is sponsored by …
Watershed’s climate data engine helps companies measure and reduce their emissions, turning the data they already have into an audit-ready carbon footprint backed by the latest climate science. Get the sustainability data you need in weeks, not months. Learn more at watershed.com.
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Music for Shift Key is by Adam Kromelow.
Why the new “reasoning” models might gobble up more electricity — at least in the short term
What happens when artificial intelligence takes some time to think?
The newest set of models from OpenAI, o1-mini and o1-preview, exhibit more “reasoning” than existing large language models and associated interfaces, which spit out answers to prompts almost instantaneously.
Instead, the new model will sometimes “think” for as long as a minute or two. “Through training, they learn to refine their thinking process, try different strategies, and recognize their mistakes,” OpenAI announced in a blog post last week. The company said these models perform better than their existing ones on some tasks, especially related to math and science. “This is a significant advancement and represents a new level of AI capability,” the company said.
But is it also a significant advancement in energy usage?
In the short run at least, almost certainly, as spending more time “thinking” and generating more text will require more computing power. As Erik Johannes Husom, a researcher at SINTEF Digital, a Norwegian research organization, told me, “It looks like we’re going to get another acceleration of generative AI’s carbon footprint.”
Discussion of energy use and large language models has been dominated by the gargantuan requirements for “training,” essentially running a massive set of equations through a corpus of text from the internet. This requires hardware on the scale of tens of thousands of graphical processing units and an estimated 50 gigawatt-hours of electricity to run.
Training GPT-4 cost “more than” $100 million OpenAI chief executive Sam Altman has said; the next generation models will likely cost around $1 billion, according to Anthropic chief executive Dario Amodei, a figure that might balloon to $100 billion for further generation models, according to Oracle founder Larry Ellison.
While a huge portion of these costs are hardware, the energy consumption is considerable as well. (Meta reported that when training its Llama 3 models, power would sometimes fluctuate by “tens of megawatts,” enough to power thousands of homes). It’s no wonder that OpenAI’s chief executive Sam Altman has put hundreds of millions of dollars into a fusion company.
But the models are not simply trained, they're used out in the world, generating outputs (think of what ChatGPT spits back at you). This process tends to be comparable to other common activities like streaming Netflix or using a lightbulb. This can be done with different hardware and the process is more distributed and less energy intensive.
As large language models are being developed, most computational power — and therefore most electricity — is used on training, Charlie Snell, a PhD student at University of California at Berkeley who studies artificial intelligence, told me. “For a long time training was the dominant term in computing because people weren’t using models much.” But as these models become more popular, that balance could shift.
“There will be a tipping point depending on the user load, when the total energy consumed by the inference requests is larger than the training,” said Jovan Stojkovic, a graduate student at the University of Illinois who has written about optimizing inference in large language models.
And these new reasoning models could bring that tipping point forward because of how computationally intensive they are.
“The more output a model produces, the more computations it has performed. So, long chain-of-thoughts leads to more energy consumption,” Husom of SINTEF Digital told me.
OpenAI staffers have been downright enthusiastic about the possibilities of having more time to think, seeing it as another breakthrough in artificial intelligence that could lead to subsequent breakthroughs on a range of scientific and mathematical problems. “o1 thinks for seconds, but we aim for future versions to think for hours, days, even weeks. Inference costs will be higher, but what cost would you pay for a new cancer drug? For breakthrough batteries? For a proof of the Riemann Hypothesis? AI can be more than chatbots,” OpenAI researcher Noam Brown tweeted.
But those “hours, days, even weeks” will mean more computation and “there is no doubt that the increased performance requires a lot of computation,” Husom said, along with more carbon emissions.
But Snell told me that might not be the end of the story. It’s possible that over the long term, the overall computing demands for constructing and operating large language models will remain fixed or possibly even decline.
While “the default is that as capabilities increase, demand will increase and there will be more inference,” Snell told me, “maybe we can squeeze reasoning capability into a small model ... Maybe we spend more on inference but it’s a much smaller model.”
OpenAI hints at this possibility, describing their o1-mini as “a smaller model optimized for STEM reasoning,” in contrast to other, larger models that “are pre-trained on vast datasets” and “have broad world knowledge,” which can make them “expensive and slow for real-world applications.” OpenAI is suggesting that a model can know less but think more and deliver comparable or better results to larger models — which might mean more efficient and less energy hungry large language models.
In short, thinking might use less brain power than remembering, even if you think for a very long time.
On Azerbaijan’s plans, offshore wind auctions, and solar jobs
Current conditions: Thousands of firefighters are battling raging blazes in Portugal • Shanghai could be hit by another typhoon this week • More than 18 inches of rain fell in less than 24 hours in Carolina Beach, which forecasters say is a one-in-a-thousand-year event.
Azerbaijan, the host of this year’s COP29, today put forward a list of “non-negotiated” initiatives for the November climate summit that will “supplement” the official mandated program. The action plan includes the creation of a new “Climate Finance Action Fun” that will take (voluntary) contributions from fossil fuel producing countries, a call for increasing battery storage capacity, an appeal for a global “truce” during the event, and a declaration aimed at curbing methane emissions from waste (which the Financial Times noted is “only the third most common man-made source of methane, after the energy and agricultural sectors”). The plan makes no mention of furthering efforts to phase out fossil fuels in the energy system.
The Interior Department set a date for an offshore wind energy lease sale in the Gulf of Maine, an area which the government sees as suitable for developing floating offshore wind technology. The auction will take place on October 29 and cover eight areas on the Outer Continental Shelf off Massachusetts, New Hampshire, and Maine. The area could provide 13 gigawatts of offshore wind energy, if fully developed. The Biden administration has a goal of installing 30 GW of offshore wind by 2030, and has approved about half that amount so far. The DOI’s terms and conditions for the October lease sale include “stipulations designed to promote the development of a robust domestic U.S. supply chain for floating wind.” Floating offshore wind turbines can be deployed in much deeper waters than traditional offshore projects, and could therefore unlock large areas for clean power generation. Last month the government gave the green light for researchers to study floating turbines in the Gulf of Maine.
In other wind news, BP is selling its U.S. onshore wind business, bp Wind Energy. The firm’s 10 wind farm projects have a total generating capacity of 1.3 gigawatts and analysts think they could be worth $2 billion. When it comes to renewables, the fossil fuel giant said it is focusing on investing in solar growth, and onshore wind is “not aligned” with those plans.
The number of jobs in the U.S. solar industry last year grew to 279,447, up 6% from 2022, according to a new report from the nonprofit Interstate Renewable Energy Council. Utility-scale solar added 1,888 jobs in 2023, a 6.8% increase and a nice rebound from 2022, when the utility-scale solar market recorded a loss in jobs. The report warns that we might not see the same kind of growth for solar jobs in 2024, though. Residential installations have dropped, and large utility-scale projects are struggling with grid connection. The report’s authors also note that as the industry grows, it faces a shortage of skilled workers.
Interstate Renewable Energy Council
Most employers reported that hiring qualified solar workers was difficult, especially in installation and project development. “It’s difficult because our projects are built in very rural areas where there just aren't a lot of people,” one interviewee who works at a utility-scale solar firm said. “We strive to hire as many local people as possible because we want local communities to feel the economic impact or benefit from our projects. So in some communities where we go, it is difficult to find local people that are skilled and can perform the work.”
The torrential rain that has battered central Europe is tapering off a bit, but the danger of rising water remains. “The massive amounts of rain that fell is now working its way through the river systems and we are starting to see flooding in areas that avoided the worst of the rain,” BBC meteorologist Matt Taylor explained. The Polish city of Nysa told its 44,000 residents to leave yesterday as water rose. In the Czech Republic, 70% of the town of Litovel was submerged in 3 feet of flooding. The death toll from the disaster has risen to 18. Now the forecast is calling for heavy rain in Italy. “The catastrophic rainfall hitting central Europe is exactly what scientists expect with climate change,” Joyce Kimutai, a climate scientist with Imperial College London’s Grantham Institute, toldThe Guardian.
A recent study examining the effects of London’s ultra-low emissions zone on how students get to school found that a year after the rules came into effect, many students had switched to walking, biking, or taking public transport instead of being driven in private vehicles.