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Why Thursday’s opinion on the Clean Water Act was not entirely out of character for the justice
On Thursday, the Supreme Court sharply limited the Environmental Protection Agency’s ability to protect wetlands under the Clean Water Act. Writing for a five-justice majority, Justice Samuel Alito said that only wetlands with a “continuous surface connection” to a protected body of water were covered by the law. The decision will remove federal protections from millions of acres of swamp, bog, and marsh, allowing companies to dump pollutants into them without penalty or oversight.
The ruling is arguably a more severe rollback to the EPA’s power than last year’s West Virginia v. EPA, which partially curtailed the agency’s authority under the Clean Air Act. In that case, the Court prevented the EPA from regulating carbon pollution in one hypothetical way, but did not prevent it from attempting to regulate emissions at all. Now the Court is lifting wetland protections that have been in place for decades.
Four justices, including the Court’s three liberals, decried the decision. “By narrowing the Act’s coverage of wetlands,” one of them wrote, “the Court’s new test will leave some long-regulated adjacent wetlands no longer covered by the Clean Water Act, with significant repercussions for water quality and flood control throughout the United States.”
Yet the identity of the justice who wrote that sentence may come as a surprise: It was Justice Brett Kavanaugh, a conservative whom President Donald Trump appointed to the Court in 2018. In what was essentially a dissent, Kavanaugh called the Court’s ruling “atextual,” warning it will “create real-world consequences for the waters of the United States.” The case could prevent the government from protecting the Chesapeake Bay or Mississippi River, he said.
The ruling was Kavanaugh’s highest-profile disagreement in an environmental case. (Technically, his dissent was filed as concurrence because all nine justices ruled against the EPA on the limited facts of the case.) And it attracted some notice, given that Kavanaugh, along with Justice Neil Gorsuch and Chief Justice John Roberts, now provide the closest thing that the right-wing Court has to a swing vote. Environmentalists and progressives noted Kavanaugh’s dissent with surprise.
Yet it was not entirely out of character for the justice. Before he was nominated to the Supreme Court, Kavanaugh was seen as a skeptic, but not an enemy, of environmental regulation. Because he previously sat on the Court of Appeals for the District of Columbia, which often hears EPA cases, Kavanaugh had a deeper record on environmental law than most other jurists who join the court.
“He’s not like a Scalia — or, to some extent, an Alito — where you read their opinions and find there’s an antipathy, a hostility, to environmental law,” Richard Lazarus, a Harvard Law professor, told me in 2018 after Kavanaugh was first nominated. “He is a conservative judge and a stickler for the notion of separation of powers. If he’s going to find an agency has sweeping regulatory authority, with significant economic or social implications, he’s going to want to find that Congress really intended it.”
That appears to be what he did in Thursday’s case. He criticized the five-justice majority for “relitigating an issue that Congress settled in 1977,” arguing that lawmakers had always intended for the Clean Water Act to cover wetlands close to, but not directly connected to, protected lakes, streams, and rivers. The Court’s “overly narrow view of the Clean Water Act,” he warned, “will have concrete impact.”
Kavanaugh also sits apart from some of his conservative colleagues for affirming the science of climate change in broad terms. “The earth is warming. Humans are contributing,” he volunteered while hearing a major EPA climate case in 2016. “There is a moral imperative. There is a huge policy imperative,” he continued. “The pope’s involved.” He did not say — crucially — whether he believed that the EPA also had the legal authority to act, although he later ruled against the agency in a similar case.
Yet Justice Amy Coney Barrett, by comparison, has declined to affirm the existence of climate change. During Barrett’s confirmation hearing in 2020, Kamala Harris, then a senator and vice-presidential candidate, asked whether smoking causes cancer and COVID-19 is contagious. Yes, they were, Barrett affirmed, but asked what Harris was driving at.
Then Harris asked: “Do you believe that climate change is happening and threatening the air we breathe and the water that we drink?”
“Again, I wondered where you were going with that,” Barrett replied. “You asked me uncontroversial questions, like COVID-19 being infectious or if smoking causes cancer, and you’re trying to solicit to an opinion from me on a very contentious matter of public debate and I will not do that. I will not express a view on a matter of public policy, especially one that is politically controversial because it is inconsistent with the judicial rule, as I explained.”
Aside from the notable failure to affirm even the scientific existence of climate change, Barrett is incorrect. The open political question about climate change is what, if anything, to do about it — not whether it exists. In the next year, Barrett and her eight colleagues — including Kavanaugh — will get to participate in that debate when she rules on a series of major EPA climate proposals. I suppose we shall learn more about her views — and his — then.
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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.
Welcome to Decarbonize Your Life, Heatmap’s special report that aims to help you make decisions in your own life that are better for the climate, better for you, and better for the world we all live in. This is our attempt, in other words, to assist you in living something like a normal life while also making progress in the fight against climate change.
That means making smarter and more informed decisions about how climate change affects your life — and about how your life affects climate change. The point is not what you shouldn’t do (although there is some of that). It’s about what you should do to exert the most leverage on the global economic system and, hopefully, nudge things toward decarbonization just a little bit faster.
We certainly think we’ve hit upon a better way to think about climate action, but you don’t have to take our word for it. Keep reading here for more on how (and why) we think about decarbonizing your life — or just skip ahead to our recommendations, below.