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The eastern and northern United States are suffering under a hazy, poisonous cloud of wildfire smoke, produced by out-of-control forest fires in Quebec and Nova Scotia. The most toxic soot and ash are sitting virtually on top of North America’s most densely populated corridor, clouding the air in New York City; Toronto; Ottawa; Philadelphia, Washington, D.C.; and Norfolk, Virginia.
Air pollution alerts are in effect across the United States and Canada, affecting roughly 150 million people.
This is Heatmap’s set of commonly asked questions about the crisis. We’ll keep it updated throughout the event.
Hundreds of wildfires have raged across northern Quebec for the past few weeks, driven by unusually warm and dry conditions.
Then on Monday, a low-pressure system surrounded by counterclockwise winds moved just off New England’s coast. Its strong, dry gusts fanned the flames in Canada, then pushed the resulting smoke and ash into the eastern United States.
Intense Canadian fires are unusual this early in the season, but the fires this year were fed by a warm spring and drought-like condition, Kent Moore, an atmospheric-physics professor at the University of Toronto, told me. Because the fires took hold before the vegetation could “green up” for the spring, the conflagrations grew more rapidly than they normally would, he said.
The dry conditions also helped the fires ignite the soil itself. “Because the soil was so dry — because of the dry winter and the dry spring — the fire got into the ground,” he said. “The vegetation below ground started to burn, and those are much harder to put out.”
This is likely one of America’s worst days for air pollution in several decades, in terms of the number of people affected and the severity of the exposure, Marshall Burke, an economist and sustainability professor at Stanford, told me.
“It’s pretty off the chart,” Burke said. Wildfire smoke is affecting New York City much more acutely — and much earlier in the year — than it has at any time since 2006, when contemporary air-pollution data began to be kept.
It is difficult to attribute a single unprecedented event to climate change, and the climatology of wildfires in eastern North America is particularly challenging. (Climate change has more clearly worsened wildfires out West.) “This is probably an unlucky year for Canada, as far as wildfires go,” Moore, the atmospheric physicist, said.
But wildfires will become more likely across Canada as the climate changes, he said. And while climate change should broadly increase rainfall across Canada, it will also increase the likelihood of heat waves and more extreme spring and summer temperatures, which can make wildfires more likely.
“Nova Scotia has always had wildfires. It’s just they’ve had more wildfires this year than they have on average for the whole year,” he said. “There’s always going to be wildfires, but there’s going to be more of them.” As Canadian cities sprawl into previously uninhabited woodland areas, he added, the human impacts of wildfires will increase — even if the number and intensity of wildfires does not.
First, consult the air quality index at AirNow.gov. The AQI is a unit-less index of air quality running from zero to 500; any reading above 100 would rank as unusually polluted in the United States. On Wednesday afternoon, some air sensors in New York and New Jersey indicated that the AQI exceeded 400.
If it’s higher than 100, then the most vulnerable groups of people — including children, the elderly, anyone with a cardiopulmonary condition, and pregnant women — should limit strenuous activity outdoors. If higher than 150, then people should generally try to limit their outdoor activity; at levels above 200, the air is considered unhealthy and everyone should try to go outside as little as possible.
If you think you might be especially vulnerable, err on the side of caution. Recently, a body of new and large-scale studies have shown that air pollution is generally worse for the body and brain than previously thought.
Then, if you’re in an area with hazardous air pollution, consider how to limit your exposure to the air as much as possible. Keep your doors and windows closed. An air filter outfitted with a HEPA filter can improve the air in a home or apartment. It should generally be closer to the most sensitive people.
“Any pregnant moms — if my wife or anyone I knew was pregnant right now — I would be texting them to stay inside and sit by an air filter,” Burke told me. Exposure to severe air pollution during pregnancy has been shown to increase the risk of preterm birth, and it can reduce a child’s lifelong earnings, cognitive performance, and other indicators, he said.
A KN95 or N95 mask — the type of high-filtration mask used to prevent COVID infection — can also significantly limit your exposure to soot and ash. If you are in a sensitive group or are worried about air pollution’s health effects, you could consider wearing a mask inside if you have no other way to filter the air.
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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.
Subscribe to “Shift Key” and find this episode on Apple Podcasts, Spotify, Amazon, or wherever you get your podcasts.
You can also add the show’s RSS feed to your podcast app to follow us directly.
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.
As a global leader in PV and ESS solutions, Sungrow invests heavily in research and development, constantly pushing the boundaries of solar and battery inverter technology. Discover why Sungrow is the essential component of the clean energy transition by visiting sungrowpower.com.
Antenna Group helps you connect with customers, policymakers, investors, and strategic partners to influence markets and accelerate adoption. Visit antennagroup.com to learn more.
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.