Green banking groups argue that EPA's attempt to cancel their federal funding runs counter to last year's Supreme Court decision to curtail agency power.

The world’s most-populous country and third-largest carbon emitter will regulate "carbon intensity" to slow emissions increases as it grows.

Friends of the Earth Netherlands has expanded its climate targets, filing a lawsuit that charges ING is contributing to global warming.

The Senate will hold its first hearing this week on the upcoming highway bill.

The European Union's current targets stipulate that all cars sold in the region’s single market should be emissions-free by 2035.

Emissions fell by 1.8 percent last year to 366 million tons of carbon dioxide equivalent.

Peak measurement taken this month was about 30,000 square miles smaller than the lowest previous peak in 2017, a difference about the size of California.

The drone will deliver infrared images, among other things, and works in combination with a fire detection system that’s already being used in several countries.

It’s tricky to predict precisely what the impacts of climate change will be, given the many variables involved. To predict the impacts of a warmer world on plant life, some researchers look at urban “heat islands,” where, because of the effects of urban structures, temperatures consistently run a few degrees higher than those of the surrounding rural areas. This enables side-by-side comparisons of plant responses.

But a new study by researchers at MIT and Harvard University has found that, at least for forests, urban heat islands are a poor proxy for global warming, and this may have led researchers to underestimate the impacts of warming in some cases. The discrepancy, they found, has a lot to do with the limited genetic diversity of urban tree species.

The findings appear in the journal PNAS, in a paper by MIT postdoc Meghan Blumstein, professor of civil and environmental engineering David Des Marais, and four others.

“The appeal of these urban temperature gradients is, well, it’s already there,” says Des Marais. “We can’t look into the future, so why don’t we look across space, comparing rural and urban areas?” Because such data is easily obtainable, methods comparing the growth of plants in cities with similar plants outside them have been widely used, he says, and have been quite useful. Researchers did recognize some shortcomings to this approach, including significant differences in availability of some nutrients such as nitrogen. Still, “a lot of ecologists recognized that they weren’t perfect, but it was what we had,” he says.

Most of the research by Des Marais’ group is lab-based, under conditions tightly controlled for temperature, humidity, and carbon dioxide concentration. While there are a handful of experimental sites where conditions are modified out in the field, for example using heaters around one or a few trees, “those are super small-scale,” he says. “When you’re looking at these longer-term trends that are occurring over space that’s quite a bit larger than you could reasonably manipulate, an important question is, how do you control the variables?”

Temperature gradients have offered one approach to this problem, but Des Marais and his students have also been focusing on the genetics of the tree species involved, comparing those sampled in cities to the same species sampled in a natural forest nearby. And it turned out there were differences, even between trees that appeared similar.

“So, lo and behold, you think you’re only letting one variable change in your model, which is the temperature difference from an urban to a rural setting,” he says, “but in fact, it looks like there was also a genotypic diversity that was not being accounted for.”

The genetic differences meant that the plants being studied were not representative of those in the natural environment, and the researchers found that the difference was actually masking the impact of warming. The urban trees, they found, were less affected than their natural counterparts in terms of when the plants’ leaves grew and unfurled, or “leafed out,” in the spring.

The project began during the pandemic lockdown, when Blumstein was a graduate student. She had a grant to study red oak genotypes across New England, but was unable to travel because of lockdowns. So, she concentrated on trees that were within reach in Cambridge, Massachusetts. She then collaborated with people doing research at the Harvard Forest, a research forest in rural central Massachusetts. They collected three years of data from both locations, including the temperature profiles, the leafing-out timing, and the genetic profiles of the trees. Though the study was looking at red oaks specifically, the researchers say the findings are likely to apply to trees broadly.

At the time, researchers had just sequenced the oak tree genome, and that allowed Blumstein and her colleagues to look for subtle differences among the red oaks in the two locations. The differences they found showed that the urban trees were more resistant to the effects of warmer temperatures than were those in the natural environment.

“Initially, we saw these results and we were sort of like, oh, this is a bad thing,” Des Marais says. “Ecologists are getting this heat island effect wrong, which is true.” Fortunately, this can be easily corrected by factoring in genomic data. “It’s not that much more work, because sequencing genomes is so cheap and so straightforward. Now, if someone wants to look at an urban-rural gradient and make these kinds of predictions, well, that’s fine. You just have to add some information about the genomes.”

It's not surprising that this genetic variation exists, he says, since growers have learned by trial and error over the decades which varieties of trees tend to thrive in the difficult urban environment, with typically poor soil, poor drainage, and pollution. “As a result, there’s just not much genetic diversity in our trees within cities.”

The implications could be significant, Des Marais says. When the Intergovernmental Panel on Climate Change (IPCC) releases its regular reports on the status of the climate, “one of the tools the IPCC has to predict future responses to climate change with respect to temperature are these urban-to-rural gradients.” He hopes that these new findings will be incorporated into their next report, which is just being drafted. “If these results are generally true beyond red oaks, this suggests that the urban heat island approach to studying plant response to temperature is underpredicting how strong that response is.”

The research team included Sophie Webster, Robin Hopkins, and David Basler from Harvard University and Jie Yun from MIT. The work was supported by the National Science Foundation, the Bullard Fellowship at the Harvard Forest, and MIT.

As a college student in Serbia with a passion for math and physics, Ana Trišović found herself drawn to computer science and its practical, problem-solving approaches. It was then that she discovered MIT OpenCourseWare, part of MIT Open Learning, and decided to study a course on Data Analytics with Python in 2012 — something her school didn’t offer.

That experience was transformative, says Trišović, who is now a research scientist at the FutureTech lab within MIT’s Computer Science and Artificial Intelligence Laboratory.

“That course changed my life,” she says. “Throughout my career, I have considered myself a Python coder, and MIT OpenCourseWare made it possible. I was in my hometown on another continent, learning from MIT world-class resources. When I reflect on my path, it’s incredible.”

Over time, Trišović's path led her to explore a range of OpenCourseWare resources. She recalls that, as a non-native English speaker, some of the materials were challenging. But thanks to the variety of courses and learning opportunities available on OpenCourseWare, she was always able to find ones that suited her. She encourages anyone facing that same challenge to be persistent.

“If the first course doesn’t work for you, try another,” she says. “Being persistent and investing in yourself is the best thing a young person can do.”

In her home country of Serbia, Trišović earned undergraduate degrees in computer science and mechanical engineering before going on to Cambridge University and CERN, where she contributed to work on the Large Hadron Collider and completed her PhD in computer science in 2018. She has also done research at the University of Chicago and Harvard University.

“I like that computer science allows me to make an impact in a range of fields, but physics remains close to my heart, and I’m constantly inspired by it,” she says.

MIT FutureTech, an interdisciplinary research group, draws on computer science, economics, and management to identify computing trends that create risk and opportunities for sustainable economic growth. There, Trišović studies the democratization of AI, including the implications of open-source AI and how that will impact science. Her work at MIT is a chance to build on research she has been pursuing since she was in graduate school.

“My work focuses on computational social science. For many years, I’ve been looking at what's known as 'the science of science' — investigating issues like research reproducibility," Trišović explains. “Now, as AI becomes increasingly prevalent and introduces new challenges, I’m interested in examining a range of topics — from AI democratization to its effects on the scientific method and the broader landscape of science.”

Trišović is grateful that, way back in 2012, she made the decision to try something new and learn with an OpenCourseWare course.

“I instantly fell in love with Python the moment I took that course. I have such a soft spot for OpenCourseWare — it shaped my career,” she says. “Every day at MIT is inspiring. I work with people who are excited to talk about AI and other fascinating topics.”

In another rare squid/cybersecurity intersection, APT37 is also known as “Squid Werewolf.”

As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.

Earlier this week, the House Judiciary Committee passed H.R. 1526, a bill by Rep. Darrell Issa to prevent courts from issuing nationwide injunctions. This bill could receive a vote on the House floor as early as next week. Senator Josh Hawley recently introduced a similar bill in the Senate. Both bills would prohibit district courts from handing down injunctive relief orders that apply to parties that are not involved in the case. 

EFF opposes both bills. We see this legislation for what it is: a transparent attempt to limit courts' ability to act as an effective check on the Trump administration’s recent flood of illegal orders and actions – some of which EFF itself is challenging. Congress should firmly oppose any effort to prevent the judicial branch from fulfilling its constitutional duty.

Indeed, this is a remedy in search of a problem. There are already well-established tests for injunctive relief: Courts must consider multiple factors, including the strength of the case against the defendant, the potential harms of granting the injunction, what other relief is available, and the public interest.  As part of this analysis, courts can and do tailor the relief they grant to what they conclude is necessary to remedy the harm. Nationwide injunctions may be necessary to stop nationwide unlawful conduct. And if an injunction was improperly granted, its target can appeal to have it overturned. 

To be clear, EFF doesn’t agree with every grant of nationwide relief. Courts sometimes get it wrong, often because they misinterpret the law they are asked to apply. If Congress wants to fix that kind of problem, it should draft specific legislation to reform or clarify specific laws. It should not, and cannot, rewrite our Constitutional system of checks and balances just because it doesn’t like some of the outcomes.

The move is part of a wholesale review of 56 FEMA programs to ensure they meet President Donald Trump's immigration enforcement efforts.

This is a truly fascinating paper: “Trusted Machine Learning Models Unlock Private Inference for Problems Currently Infeasible with Cryptography.” The basic idea is that AIs can act as trusted third parties:

Abstract: We often interact with untrusted parties. Prioritization of privacy can limit the effectiveness of these interactions, as achieving certain goals necessitates sharing private data. Traditionally, addressing this challenge has involved either seeking trusted intermediaries or constructing cryptographic protocols that restrict how much data is revealed, such as multi-party computations or zero-knowledge proofs. While significant advances have been made in scaling cryptographic approaches, they remain limited in terms of the size and complexity of applications they can be used for. In this paper, we argue that capable machine learning models can fulfill the role of a trusted third party, thus enabling secure computations for applications that were previously infeasible. In particular, we describe Trusted Capable Model Environments (TCMEs) as an alternative approach for scaling secure computation, where capable machine learning model(s) interact under input/output constraints, with explicit information flow control and explicit statelessness. This approach aims to achieve a balance between privacy and computational efficiency, enabling private inference where classical cryptographic solutions are currently infeasible. We describe a number of use cases that are enabled by TCME, and show that even some simple classic cryptographic problems can already be solved with TCME. Finally, we outline current limitations and discuss the path forward in implementing them...

The planned 25 percent tariff on imported automobiles is a gut punch for most electric vehicle makers, whose supply chains are rooted in China.

The EV company’s popularity has wilted in Europe and among left-leaning consumers.

Climate experts whose research is funded by federal grants hide, whisper and wait for their jobs to disappear.

A federal judge rejected oil companies' efforts to move the lawsuit out of the state court where it was first filed.

The rule would have required companies to provide climate information to investors. Its demise was expected under the Trump administration.

A House bill to bar environmental, social and governance investing also emerged this week.