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A conversation with Ben Goldfarb about his road ecology book Crossings.

An alternative title for journalist Ben Goldfarb’s fantastic new book, Crossings, could have been Squashings. “Wait a minute,” I thought to myself about 25 pages in. “Have I been duped into reading a book about … roadkill?!”
The answer wasn’t precisely no, although Crossings is also about so much more (its subtitle: How Road Ecology Is Shaping the Future of Our Planet). From cliff swallows that have evolved to have shorter wings to better avoid zooming cars, to Oedipal cougars stranded in the highway-wrapped Santa Monica Mountains, to the trials of one surprisingly charismatic anteater named Evelyn, Crossings observes that “the repercussions of roads are so complex that it’s hard to pinpoint where they end.”
Goldfarb, though, attempts valiantly to untangle them, and the result is as funny, heartbreaking, enraging, and enlightening as anything I’ve read this year. “There may be nothing humans do that causes more misery to more wild animals than driving,” he writes, but planet-warming emissions are only the most prominent part of that story. Ahead of Crossings’ publication next Tuesday, Goldfarb and I discussed the promise (and drawbacks) of the EV transition and autonomous cars on road ecology; the short-sightedness of infrastructure budgets; and how bad people are at driving. Our conversation has been condensed and edited for clarity.
When you told people you were working on a book about road ecology, did they take it as an invitation to share their personal, unsolicited roadkill stories with you?
Absolutely, they did. I wouldn’t say it was unsolicited: I’m always — I don’t want to say I’m happy to hear roadkill stories — but I’m certainly interested in stories and there were lots of them. One of my favorite ones was a guy who told me that he’d recently hit a squirrel and he was so confused and upset and unhappy about it that he actually called 911. He didn’t know what else to do. And the 911 operator basically said, “Uh yeah, the squirrel is dead.” I mean, to me, that sort of gets at how viscerally upsetting and disturbing roadkill can be. It’s something we see constantly and ultimately take for granted in a lot of ways but committing it ourselves is, of course, a miserable feeling. I just hit an owl a few nights ago and I’m still losing sleep.
One of the things I was most astonished by while reading this book is how well-sourced it is — the texts and interviews you bring together are so broad and enriching. Do you have any idea how many books you read? Tell me a little about how you approached the research.
Oh, geez. Let’s see — two shelves of that bookshelf [behind me] are road ecology reference books. So, several dozen. I can’t claim that I read them all cover to cover, but certainly I drew a lot from other books. I think I ultimately had close to 300 sources in the book who were just invaluable founts of help and knowledge and information.
One of the challenges of writing about road ecology is it’s not necessarily a single discipline. It’s really an umbrella that covers many different disciplines. Roadkill science is its own sort of subset. The impact of forest service roads on contributing erosion to streams is a whole science unto itself. The impact of improperly built road culverts as fish passage barriers — I mean, there are 10,000 papers about that alone. So every chapter was sort of learning a new science unto itself.
You write that “among all the road’s ecological disasters … the most vexing may be noise pollution.” We do a lot of coverage of the future of driving here at Heatmap, and I suppose I was hoping to learn that electric vehicles and cutting-edge advances in automotive technology would help solve at least this problem. Can you tell me why you’re less optimistic?
EVs are much quieter; their engines are silent, which is helpful, especially in an urban context. They’ll ultimately reduce noise pollution and that’s profoundly important. We tend to overlook noise pollution because we’re so awash in it but it’s one of the great public health crises of our time. You read the literature about the health impacts of road noise and it’s horrifying — I mean, literally, it’s elevating our stress levels, it’s increasing our risk of heart attack and diabetes and stroke, it’s taking years off of our lives, mostly without our noticing it. So anything we can do to reduce noise is fundamentally positive. And EVs are part of that.
The drawback, the reason that EVs aren’t a panacea, is that engines aren’t the only thing that makes noise on a car. Above 35 mph, most of what you’re hearing is tire noise: the grinding of the tire itself against the pavement and the little air pockets in the tread popping — “pattern noise” is what that’s called. I wrote most of this book while living a half mile or so from I-90 in eastern Washington state and I could just hear, every time I stepped out of my house, that monotonous hiss of the interstate. That’s tire noise, not engine noise. And tires have gotten much quieter over time, which is good, and hopefully they’ll continue to get quieter, but just electrifying vehicles is not going to solve the problem of road noise even if it does help in urban settings.
Not to keep raining on the parade, but you also write that autonomous vehicles could be “the gravest challenge to road ecology since, well, roads.” How do driverless cars change the road ecology calculus?
I think the answer is, we don’t know yet. From a large animal avoidance perspective, I think they’re ultimately going to be really helpful. Yes, it’s fun right now to dunk on Tesla and Waymo and all of these autonomous vehicle companies whose products are still very buggy, but, you know — probably there are people who will read this and take exception with this idea, but I’m ultimately pretty optimistic that the AVs will solve most of those problems and become better drivers than human beings.
And that’s the thing that always gets lost when somebody posts a video of an AV doing something stupid — human drivers do stupid things constantly, right? We’re horrifically bad drivers. Tens of thousands of people die in the U.S. every year because of it. And one of the things that we’re really bad at is avoiding large animals. We don’t see that well at night, they jump out unexpectedly, and our reflexes are too slow to slam on the brakes. I think that AVs will be much, much better at avoiding those deer and elk and moose than we are because those are large animals and all of [the AV] sensors that are designed to avoid pedestrians will be triggered by those large animals.
But, of course, that doesn’t really help a rattlesnake or a prairie dog or any smaller creature. I, for one, go out of my way to avoid hitting those animals, and when my car is piloted by a robot, that’s not going to help; that robot will have no reason to avoid those small animals if engineers don’t design it to do so.
And the broader problem is that autonomy is likely to lead to a whole lot more vehicles on the road. When you can get in your car and it drives itself and you can spend that time watching movies or doing work or what have you, commuting becomes a lot less onerous. Every autonomous vehicle could have a kid in it who’s not able to drive currently. Most of the modeling suggests that there’s going to be a dramatic increase in vehicle miles traveled as a result of autonomous cars. And that’s going to be bad for wildlife, that’s going to make the barrier effect of roads even more severe and make it even harder for animals to migrate across highways.
And commuting traffic, human traffic, is really just the tip of the iceberg when it comes to autonomy. The autonomous delivery fleet, in some ways, is the bigger concern. A lot of the early AVs are going to be delivery vehicles; it’s going to be so easy to summon products to us. So it’s hard to imagine a scenario where AVs lead to less driving rather than more of it, unfortunately.
How did you navigate striking the right balance between the ideals of conservation and the realities of politics and economics in this book? I found myself getting so frustrated reading about the frogs trying to cross Highway 30 in Portland, Oregon, only to then learn that SP-139 in Brazil actually closes a section between 8 p.m. and 6 a.m., when animals are most active. I was like, “Why can’t we do that!”
We do have this very constrained idea of what is possible and that’s why I like drawing upon other countries. You mentioned that road in Brazil that is closed at night through a park; another great anecdote is that in India, they built a new highway through a tiger sanctuary and they just elevated the entire highway on pilings so that animals can come and go underneath the lifted freeway. Of course, that made the project vastly more expensive, but it’s ecologically the right thing to do and is much more radical than anything we’ve done in this country.
I was just talking about this the other day with somebody in the bird ecology world: how our sense of what we can afford is so skewed. I think that people hear the price tag of a wildlife crossing structure and they think, “Oh my gosh, $10 million just to help elk cross the highway, what an extravagant expenditure.” But that’s beyond nothing in the context of national, state, and federal transportation budgets. I mean, $10 million for a wildlife crossing, that’s not even a drop in the bucket. That’s like a molecule of H2O in the bucket. It costs a million dollars to pave a mile of highway, let alone add a bunch of lanes to it. So to me, the notion that we can’t make our infrastructure better for nature because it costs money is incredibly short-sighted and fails to consider how much money we’re spending on our roads already.
A great example of that was the Infrastructure Act, which contains $350 million for wildlife crossings — which is great and wonderful and a step in the right direction. But it also contains billions of dollars for highway expansions and repaving and bridge repairs. And one bird ecologist described that $350 million as “decimal dust,” you know, just nothing in the context of federal transportation. The politics of the possible can definitely be frustrating.
Not to mention, you have a statistic in Crossings that animal crashes cost America something like $8 billion per year.
And that was $8 billion in 2009. So for inflation and accounting for increased collisions over time — yeah, it’s an enormous number that we’re not doing a whole lot about.
Your book is full of so much humor and cautious optimism but when I was reading it, I would sometimes get overwhelmed just thinking about how many roads exist and how many more roads are going to exist and the awful ends so many living things meet because of them. How did you stay hopeful while immersed in these stories?
I think that the book comes off as humorous and optimistic because that’s just my natural register as a writer, but I’m not sure I actually always feel that way. There are times that I feel totally desperate about the future of conservation. One of the challenges of writing about this topic is that there’s no perfect solution, there’s no panacea. We could say “we need more mass transit,” and certainly we need to get people out of cars, but I live in rural Colorado: It’s hard to imagine a public transportation system that is going to meaningfully change driving rates in this kind of very rural, dispersed area that was built around the automobile.
Wildlife crossings are the same thing. They help a specific set of problems, which is roadkill and the curtailment of animal migration. But they don’t reduce road noise, they don’t prevent tire particles from spewing into the environment and killing salmon, they don’t do anything about road salts being applied in ridiculous quantities and destroying freshwater ecosystems. So, again, there is no panacea here and it can be really challenging to confront the scale and the number of different solutions needed to make our roads lie more lightly on the planet.
Is there anything else you would want readers to know about Crossings?
You mentioned EVs in the context of road noise and one of the things that I almost wish I had emphasized more in the book is that when people tend to think about the environmental impacts of transportation, they think about the carbon emissions, right? And the solutions tend to be things like the electrification of vehicle fleets and fuel standards. And certainly, those are good things. But the electrification of the fleet is going to do absolutely nothing for wild animals. In fact, just as AVs could lead to more driving, EVs can do the same thing when it becomes much cheaper to drive your car because you just have to plug it in — the whole Jevons paradox idea that a million EV scholars have written about.
I feel like part of the purpose of the book is to say, look, the carbon emissions from transportation are an enormous problem. But they’re only one of the many, many ecological problems that our car-centered transportation network causes. You can strip the carbon out of our transportation and still not make it benign for the environment.
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Citrine Informatics has been applying machine learning to materials discovery for years. Now more advanced models are giving the tech a big boost.
When ChatGPT launched three years ago, it became abundantly clear that the power of generative artificial intelligence had the capacity to extend far beyond clever chatbots. Companies raised huge amounts of funding based on the idea that this new, more powerful AI could solve fundamental problems in science and medicine — design new proteins, discover breakthrough drugs, or invent new battery chemistries.
Citrine Informatics, however, has largely kept its head down. The startup was founded long before the AI boom, back in 2013, with the intention of using simple old machine learning to speed up the development of more advanced, sustainable materials. These days Citrine is doing the same thing, but with neural networks and transformers, the architecture that undergirds the generative AI revolution.
“The technology transition we’re going through right now is pretty massive,” Greg Mulholland, Citrine’s founder and CEO, told me. “But the core underlying goal of the company is still the same: help scientists identify the experiments that will get them to their material outcome as fast as possible.”
Rather than developing its own novel materials, Citrine operates on a software-as-a-service model, selling its platform to companies including Rolls-Royce, EMD Electronics, and chemicals giant LyondellBassell. While a SaaS product may be less glamorous than independently discovering a breakthrough compound that enables something like a room-temperature superconductor or an ultra-high-density battery, Citrine’s approach has already surfaced commercially relevant materials across a variety of sectors, while the boldest promises of generative AI for science remain distant dreams.
“You can think of it as science versus engineering,” Mulholland told me. “A lot of science is being done. Citrine is definitely the best in kind of taking it to the engineering level and coming to a product outcome rather than a scientific discovery.” Citrine has helped to develop everything from bio-based lotion ingredients to replace petrochemical-derived ones, to plastic-free detergents, to more sustainable fire-resistant home insulation, to PFAS-free food packaging, to UV-resistant paints.
On Wednesday, the company unveiled two new platform capabilities that it says will take its approach to the next level. The first is essentially an advanced LLM-powered filing system that organizes and structures unwieldy materials and chemicals datasets from across a company. The second is an AI framework informed by an extensive repository of chemistry, physics, and materials knowledge. It can ingest a company’s existing data, and, even if the overall volume is small, use it to create a list of hundreds of potential new materials optimized for factors such as sustainability, durability, weight, manufacturability, or whatever other outcomes the company is targeting.
The platform is neither purely generative nor purely predictive. Instead, Mulholland explained, companies can choose to use Citrine’s tools “in a more generative mode” if they want to explore broadly and open up the field of possible materials discoveries, or in a more “optimized” mode that stays narrowly focused on the parameters they set. “What we find is you need a healthy blend of the two,” he told me.
The novel compounds the model spits out still need to be synthesized and tested by humans. “What I tell people is, any plane made of materials designed exclusively by Citrine and never tested is not a plane I’m getting on,” Mulholland told me. The goal isn’t to achieve perfection right out of the lab, but rather to optimize the experiments companies end up having to do. “We still need to prove materials in the real world, because the real world will complicate it.”
Indeed it will. For one thing, while AI is capable of churning out millions of hypothetical materials — as a tool developed by Google DeepMind did in 2023 — materials scientists have since shown that many are just variants of known compounds, while others are unstable, unable to be synthesized, or otherwise irrelevant under real world conditions.
Such failures likely stem, in part, from another common limitation of AI models trained solely on publicly available materials and chemicals data: Academic research tends to report only successful outcomes, omitting data on what didn’t work and which compounds weren’t viable. That can lead models to be overly optimistic about the magnitude and potential of possible materials solutions and generate unrealistic “discoveries” that may have already been tested and rejected.
Because Citrine’s platform is deployed within customer organizations, it can largely sidestep this problem by tuning its model on niche, proprietary datasets. These datasets are small when compared with the vast public repositories used to train Citrine’s base model, but the granular information they contain about prior experiments — both successes and failures — has proven critical to bringing new discoveries to market.
While the holy grail for materials science may be a model trained on all the world’s relevant data — public and private, positive and negative — at this point that’s just a fantasy, one of Citrine’s investors, Mark Cupta of Prelude Ventures, told me over email. “It’s hard to get buy-in from the entire material development world to make an open-source model that pulls in data from across the field.”
Citrine’s last raise, which Prelude co-led, came at the very beginning of 2023, as the AI wave was still gathering momentum. But Mulholland said there’s no rush to raise additional capital — in fact, he expects Citrine to turn a profit in the next year or so.
That milestone would strongly validate the company’s strategy, which banks on steady revenue from its subscription-based model to compensate for the fact that it doesn’t own the intellectual property for the materials it helps develop. While Mulholland told me that many players in this space are trying to “invent new materials and patent them and try to sell them like drugs,” Citrine is able to “invent things much more quickly, in a more realistic way than the pie in the sky, hoping for a Nobel Prize [approach].”
Citrine is also careful to assure that its model accounts for real world constraints such as regulations and production bottlenecks. Say a materials company is creating an aluminum alloy for an automaker, Mulholland explained — it might be critical to stay within certain elemental bounds. If the company were to add in novel elements, the automaker would likely want to put its new compound through a rigorous testing process, which would be annoying if it’s looking to get to market as quickly as possible. Better, perhaps, to tinker around the edges of what’s well understood.
In fact, Mulholland told me it’s often these marginal improvements that initially bring customers into the fold, convincing them that this whole AI-for-materials thing is more than just hype. “The first project is almost always like, make the adhesive a little bit stickier — because that’s a good way to prove to these skeptical scientists that AI is real and here to stay,” he said. “And then they use that as justification to invest further and further back in their product development pipeline, such that their whole product portfolio can be optimized by AI.”
Overall, the company says that its new framework can speed up materials development by 80%. So while Mulholland and Citrine overall may not be going for the Nobel in Chemistry, don’t doubt for a second that they’re trying to lead a fundamental shift in the way consumer products are designed.
“I’m as bullish as I can possibly be on AI in science,” Mulholland told me. “It is the most exciting time to be a scientist since Newton. But I think that the gap between scientific discovery and realized business is much larger than a lot of AI folks think.”
Plus more insights from Heatmap’s latest event Washington, D.C.
At Heatmap’s event, “Supercharging the Grid,” two members of the House of Representatives — a California Democrat and a Colorado Republican — talked about their shared political fight to loosen implementation of the National Environmental Policy Act to accelerate energy deployment.
Representatives Gabe Evans and Scott Peters spoke with Heatmap’s Robinson Meyer at the Washington, D.C., gathering about how permitting reform is faring in Congress.
“The game in the 1970s was to stop things, but if you’re a climate activist now, the game is to build things,” said Peters, who worked as an environmental lawyer for many years. “My proposal is, get out of the way of everything and we win. Renewables win. And NEPA is a big delay.”
NEPA requires that the federal government review the environmental implications of its actions before finalizing them, permitting decisions included. The 50-year-old environmental law has already undergone several rounds of reform, including efforts under both Presidents Biden and Trump to remove redundancies and reduce the size and scope of environmental analyses conducted under the law. But bottlenecks remain — completing the highest level of review under the law still takes four-and-a-half years, on average. Just before Thanksgiving, the House Committee on Natural Resources advanced the SPEED Act, which aims to ease that congestion by creating shortcuts for environmental reviews, limiting judicial review of the final assessments, and preventing current and future presidents from arbitrarily rescinding permits, subject to certain exceptions.
Evans framed the problem in terms of keeping up with countries like China on building energy infrastructure. “I’ve seen how other parts of the world produce energy, produce other things,” said Evans. “We build things cleaner and more responsibly here than really anywhere else on the planet.”
Both representatives agreed that the SPEED Act on its own wouldn’t solve all the United States’ energy issues. Peters hinted at other permitting legislation in the works.
“We want to take that SPEED Act on the NEPA reform and marry it with specific energy reforms, including transmission,” said Peters.
Next, Neil Chatterjee, a former Commissioner of the Federal Energy Regulatory Commission, explained to Rob another regulatory change that could affect the pace of energy infrastructure buildout: a directive from the Department of Energy to FERC to come up with better ways of connecting large new sources of electricity demand — i.e. data centers — to the grid.
“This issue is all about data centers and AI, but it goes beyond data centers and AI,” said Chatterjee. “It deals with all of the pressures that we are seeing in terms of demand from the grid from cloud computing and quantum computing, streaming services, crypto and Bitcoin mining, reshoring of manufacturing, vehicle electrification, building electrification, semiconductor manufacturing.”
Chatterjee argued that navigating load growth to support AI data centers should be a bipartisan issue. He expressed hope that AI could help bridge the partisan divide.
“We have become mired in this politics of, if you’re for fossil fuels, you are of the political right. If you’re for clean energy and climate solutions, you’re the political left,” he said. “I think AI is going to be the thing that busts us out of it.”
Updating and upgrading the grid to accommodate data centers has grown more urgent in the face of drastically rising electricity demand projections.
Marsden Hanna, Google’s head of energy and dust policy, told Heatmap’s Jillian Goodman that the company is eyeing transmission technology to connect its own data centers to the grid faster.
“We looked at advanced transition technologies, high performance conductors,” said Hanna. “We see that really as just an incredibly rapid, no-brainer opportunity.”
Advanced transmission technologies, otherwise known as ATTs, could help expand the existing grid’s capacity, freeing up space for some of the load growth that economy-wide electrification and data centers would require. Building new transmission lines, however, requires permits — the central issue that panelists kept returning to throughout the event.
Devin Hartman, director of energy and environmental policy at the R Street Institute, told Jillian that investors are nervous that already-approved permits could be revoked — something the solar industry has struggled with under the Trump administration.
“Half the battle now is not just getting the permits on time and getting projects to break ground,” said Hartman. “It’s also permitting permanence.”
This event was made possible by the American Council on Renewable Energy’s Macro Grid Initiative.
On gas turbine backorders, Europe’s not-so-green deal, and Iranian cloud seeding
Current conditions: Up to 10 inches of rain in the Cascades threatens mudslides, particularly in areas where wildfires denuded the landscape of the trees whose roots once held soil in place • South Africa has issued extreme fire warnings for Northern Cape, Western Cape, and Eastern Cape • Still roiling from last week’s failed attempt at a military coup, Benin’s capital of Cotonou is in the midst of a streak of days with temperatures over 90 degrees Fahrenheit and no end in sight.

Exxon Mobil Corp. plans to cut planned spending on low-carbon projects by a third, joining much of the rest of its industry in refocusing on fossil fuels. The nation’s largest oil producer said it would increase its earnings and cash flow by $5 billion by 2030. The company projected earnings to grow by 13% each year without any increase in capital spending. But the upstream division, which includes exploration and production, is expected to bring in $14 billion in earnings growth compared to 2024. The key projects The Wall Street Journal listed in the Permian Basin, Guyana and at liquified natural gas sites would total $4 billion in earnings growth alone over the next five years. The announcement came a day before the Department of the Interior auctioned off $279 million of leases across 80 million acres of federal waters in the Gulf of Mexico.
Speaking of oil and water, early Wednesday U.S. armed forces seized an oil tanker off the coast of Venezuela in what The New York Times called “a dramatic escalation in President Trump’s pressure campaign against Nicolás Maduro.” When asked what would become of the vessel's oil, Trump said at the White House, “Well, we keep it, I guess.”
The Federal Reserve slashed its key benchmark interest rate for the third time this year. The 0.25 percentage point cut was meant to calibrate the borrowing costs to stay within a range between 3.5% and 3.75%. The 9-3 vote by the central bank’s board of governors amounted to what Wall Street calls a hawkish cut, a move to prop up a cooling labor market while signaling strong concerns about future downward adjustments that’s considered so rare CNBC previously questioned whether it could be real. But it’s good news for clean energy. As Heatmap’s Matthew Zeitlin wrote after the September rate cut, lower borrowing costs “may provide some relief to renewables developers and investors, who are especially sensitive to financing costs.” But it likely isn’t enough to wipe out the effects of Trump’s tariffs and tax credit phaseouts.
GE Vernova plans to increase its capacity to manufacture gas turbines by 20 gigawatts once assembly line expansions are completed in the middle of next year. But in a presentation to investors this week, the company said it’s already sold out of new gas turbines all the way through 2028, and has less than 10 gigawatts of equipment left to sell for 2029. It’s no wonder supersonic jet startups, as I wrote about in yesterday’s newsletter, are now eyeing a near-term windfall by getting into the gas turbine business.
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The European Union will free more than 80% of the companies from environmental reporting rules under a deal struck this week. The agreement between EU institutions marks what Politico Europe called a “major legislative victory” for European Commission President Ursula von der Leyen, who has sought to make the bloc more economically self-sufficient by cutting red tape for business in her second term in office. The rollback is also a win for Trump, whose administration heavily criticized the EU’s green rules. It’s also a victory for the U.S. president’s far-right allies in Europe. The deal fractured the coalition that got the German politician reelected to the EU’s top job, forcing her center-right faction to team up with the far right to win enough votes for secure victory.
Ravaged by drought, Iran is carrying out cloud-seeding operations in a bid to increase rainfall amid what the Financial Times clocked as “the worst water crisis in six decades.” On Tuesday, Abbas Aliabadi, the energy minister, said the country had begun a fresh round of injecting crystals into clouds using planes, drones, and ground-based launchers. The country has even started developing drones specifically tailored to cloud seeding.
The effort comes just weeks after the Islamic Republic announced that it “no longer has a choice” but to move its capital city as ongoing strain on water supplies and land causes Tehran to sink by nearly one foot per year. As I wrote in this newsletter, Iranian President Masoud Pezeshkian called the situation a “catastrophe” and “a dark future.”
The end of suburban kids whiffing diesel exhaust in the back of stuffy, rumbling old yellow school buses is nigh. The battery-powered bus startup Highland Electric Fleets just raised $150 million in an equity round from Aiga Capital Partners to deploy its fleets of buses and trucks across the U.S., Axios reported. In a press release, the company said its vehicles would hit the streets by next year.