Say you read my last post and you agree cost is sorta the whole ballgame when it comes to carbon dioxide removal. The question is, ok, so what’s going to be the lowest-cost method?

The easy answer —we don’t know yet!— is both true and unhelpful. It’s true because the way you find out what something costs is by implementing it at scale and then optimizing that implementation: that’s where the big learning-by-doing economies come in, and that’s not something you can simulate ahead of time. It’s unhelpful because it doesn’t guide our decision-making at all.

We don’t know yet, that’s true, but we can make some educated guesses. To make those guesses, you have to understand where the cost drivers are for carbon dioxide removal. Basically, there are two: the cost of capturing carbon dioxide, and the cost of storing it safely away from the atmosphere.

These vary a lot by method. Many methods proposed use energy for the capture part — which figures: the reason we burn hydrocarbons in the first place is that they release energy as they produce carbon dioxide. If you want to run that reaction in reverse, obviously it’s going to require energy. And energy is expensive.

For many electrochemical methods — direct air capture, electrochemical ocean alkalinity enhancement, etc.— energy costs tend to dominate the cost picture. And because the core variables in this equation are hard-coded into the laws of thermodynamics, there are relatively high price floors involved unless energy becomes much cheaper (which, let’s hope it does!) Other methods, like enhanced rock weathering, rely more on chemistry for the capture — but to get that chemistry to work you have to mine and crush and spread huge quantities of minerals, and that has an energy cost of its own.

But once you’ve done the capture, you’re now left sitting on a large quantity of carbon dioxide that you have to store somehow. There are some clever ideas out there to store it in plain sight, locked inside building materials, for instance. But for many methods, storage is another expensive proposition: you have to build the industrial infrastructure to inject the carbon dioxide into depleted oil wells, say, or you have to literally bury it in a hole you’ve dug in the ground. Those things cost money.

If you’re going to seriously drive down the cost of carbon dioxide removal to the kind of $5-$25 per ton region where you’d need it to be to make implementation at scale feasible, you need some kind of workaround, some way to bring both the energy cost of capture and the cost of storage down to near-zero.

That sounds like a pipedream. But it isn’t. It is possible, if you leave the job to tiny marine plants.

Phytoplankton —microscopic plants in the ocean— daintily sidestep both of the cost drivers that make most carbon dioxide removal uneconomic. Capture relies on photosynthesis, which is solar powered and therefore literally free. And storage relies on particles sinking through the water column, which is just gravity, which last I checked, was also free.

With $0 to pay for capture and $0 to pay for storage, phytoplankton carbon solutions begin life with an insurmountable cost advantage over other capture methods. The actual costs end up being associated with the actual minerals you’d need to add nutrients to marine deserts, but because you’re mostly talking about modest quantities of cheap minerals like iron, those just don’t add up to very much: no more than $5 per ton, and potentially as little as a few pennies. That leaves the cost of deployment — the boats and crews and such — and the cost of scientific monitoring, reporting and verification of carbon transport. Where that ends up settling once you scale is really uncertain, but there’s no a priori reason why it can’t settle at $25 a ton, or potentially quite a bit less.

This is why I tend to think we should spend all our time developing Phytoplankton Carbon. It has a clear, credible path at delivering a sub-$25 ton of carbon dioxide removal that’s both ecologically sound and long-lasting. It can do this because it puts two big fat zeros in the Excel cell where most CDR methods have the bulk of their costs: capture energy and storage.

Maybe there’s some other technique that can match that. If there is, I haven’t heard of it.

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Say you’re the chief sustainability officer for United Airlines. Or Lafarge, the French cement giant. Or Nippon Steel. Or basically any big polluter in a sector where abating emissions is difficult.

You have a bunch of engineers working for you, and part of their job is calculating what it will take to abate your climate emissions. Because you’re in a hard-to-abate industry, the costs they’re going to report to you are going to be high — that’s sort of the definition of hard-to-abate. In aviation, the marginal cost of lowering emissions comes in around $300-$400 per ton of CO₂ — which is a lot because, well, Sustainable Aviation Fuel prices are sort of murder.

In cement, you’re looking at sort of the $80-$240 range per ton for CCS, depending on a whole lot of factors. In steel, you’re again looking at sort of $90-$200 per ton or so. These are the marginal costs of abating the next ton of CO₂ — the average costs of abating your entire carbon footprint would certainly be higher.

For simplicity’s sake, let’s say in your company, the engineers tell you the marginal cost of abating the next ton is $100. And let’s say your sustainability budget also happens to be $100.

Now, say you look at the offset market, and an entrant has figured out technology for a high quality, long-term ton of carbon dioxide removal that costs $50. What should you do?

Well, you could say your primary responsibility is for your company’s own emissions, so you’re going to abate those first. You could spend your $100 budget abating one ton of CO₂. Of course, that means you don’t pay that new CDR company $100 to draw down two tons of CO₂. The opportunity cost of your decision, then, is to leave one ton of CO₂ in the atmosphere that you could have taken out of it.

Is this reasonable environmental stewardship?

I don’t think it is. I think if you’re really focused on carbon dioxide concentrations in the atmosphere, the logical thing to do is to buy the offsets. Given your budget constraint, economic rationality demands that you focus your resources on the pathway that will have the greatest impact.

The logic of this seems, to me, fairly obvious. And yet when I tell people I’m working on low-cost carbon dioxide removal options, one of the objections I hear most often is “but isn’t that just giving polluters an excuse not to decarbonize?”

Now in the carbon removal world, the standard reply to that objection is “no of course we know we need to decarbonize. We’re not proposing an alternative to decarbonization, we’re proposing an addition to it.” Which, I think, sounds nice and makes you come across as environmentally conscious and respectable and solidly within-the-consensus.

But more and more, I find myself questioning that answer. Because it is economically illiterate.

The atmosphere, for its part, is entirely indifferent between a ton of carbon dioxide that’s been removed and one that was never emitted in the first place. It’s not that one has a bigger impact than the other. It’s the overall level of carbon dioxide in the atmosphere that causes warming: a ton is a ton is a ton.

If you accept that, you come to see that the insistence on prioritizing emissions reductions over carbon removal is entirely arbitrary: more an expression of a kind of free-floating hostility to industrial civilization than anything you can really defend on climate terms.

What the world needs now is a $10 ton of safe, long-term carbon dioxide removal. Once we have a truly low-cost, high-quality, scalable technology for taking carbon out of the atmosphere, some things that are now obscure will become crystal clear. If we had a $10 ton, then abating all 40 billion tons of carbon dioxide we’re now emitting each year would become a $400 billion a year proposition.

That’s a lot of money, yes, but it’s not actually that much money in the scheme of things.

Total current spending on climate mitigation and adaptation has been estimated at north of $1 trillion. Which means if we had a $10 ton of removals, we would be able to save $600 billion a year and actually reach Net Zero, rather than what we’re doing now, which is spending more than twice that much without actually solving the problem.

Look, I know there are powerful conventions preventing us from really developing this kind of reasoning. I understand it makes people uncomfortable. I get it that emissions reductions have been fetishized to such an extent that people see punishing polluters as a kind of inherent goal of climate policy.

But this has it backwards. United Airlines doesn’t pollute a lot because they’re bad people, they pollute a lot because you and I want to fly in airplanes. Lafarge doesn’t pollute a lot because they’re irredeamable fat cats, they pollute a lot because you and I demand infrastructure that can only be built with cement. Nippon Steel doesn’t pollute a lot because they’re indifferent to the environment, they pollute a lot because every day of the year you and I use things that can only be made with steel.

Emissions are there because you and I benefit from products and services that generate emissions.

My focus is on carbon dioxide concentrations in the atmosphere. If we recenter the climate debate on what actually matters to the climate, we’ll see clearly that there’s more than one way to bring those concentrations down. We’ll accept the obvious reality that our willingness to pay to abate climate change is limited, and that when your resources are limited rationality demands that you concentrate them on their most efficient uses.

Which is why developing a long-duration, low-cost method of capturing carbon dioxide from the atmosphere is where our focus should be as climate activist. The rest might make us feel good, but it won’t make a difference.

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Remember the climate crisis? Bet you don’t. For the average news consumer, climate has fallen dramatically in salience this year.

Which kind of figures: the world is on fire.

A deranged American president launched a war he can’t explain that now threatens a global economic calamity. The global order is no such thing, and AI is racing towards the realm of the truly weird much faster than people guessed even just a year ago. It’s…not an environment that’s conducive to fretting about climate, is it?

Not everybody’s thrown in the towel, of course. The Guardian still has a Climate Crisis vertical, and plenty of outlets do still try to keep up some climate reporting. Yet when the Washington Post fired fourteen climate reporters in February, the story barely registered. Everybody recognized that the vibe had well and truly shifted, and honestly with [gestures broadly] all that going on, worrying about climate feels like a bit of a specialist interest, doesn’t it?

Look, I’m a climate guy. I work on climate, I spend all day every day thinking about this stuff. So you might expect me to be distraught about its disappearance from the discourse. I’m not, though. Because I know the public’s basic response to the shitshow that is 2026 is, strictly speaking, quite rational.

For all the time and effort (and money) spent by the activist community to convince us that climate is an acute emergency, most people understand that the biggest risks associated with climate change are long term. Genuinely catastrophic outcomes are very much in the cards — and very much more likely to upend the lives of your great grandchildren than yours.

People discount the far future; they always will. Discounting the far future is fully rational. Doing so more aggressively when you’re in the middle of an acute crisis is also fully rational. Your high blood pressure may be a genuine, serious health problem, but if you’ve just been shot in the thigh you’d be insane to prioritize it right this minute.

That’s just the way the world works, and if we allow ourselves to think about it dispassionately, I don’t think any of us would seriously dispute that.

As a climate activist, I don’t think these realities are reasons for inaction, much less for despair. I try to accept them as a given: just the shape of the information space we operate in.

We don’t actually get to change it, and if we try —by launching, say, an ill-judged information campaign to convince people to write “climate crisis” instead of “climate change”— all we’ll do is raise the public’s skepticism. People know when they’re being hoodwinked.

The willingness to take a cold, hard look at these realities has come to be associated with the denialist right: people like Chris Wright who want to make it an excuse to do nothing. That’s not a defensible position either, I don’t think. Intuition screams at us that leaving an unlivable planet to the people of the 22nd century is wrong, even if you and I won’t be there to deal with the consequences

Instead, I try to think honestly about what we can do about a hugely consequential problem that most people quite rationally do not prioritize.

That people will not and should not prioritize climate has troubling consequences. For one, it means we’re not likely to see dramatic reductions in greenhouse gas emissions anytime soon. Yes, emissions may peak in the next ten years or so and start to abate slowly, but that’s very different from the kind of drastic, fast reductions needed to reach net zero quickly enough to keep warming to within 2 degrees of the pre-industrial baseline.

Such abrupt reductions would be just about imaginable if people really did see climate as a crisis in the same way they see the Strait of Hormuz crisis as a crisis. But they don’t, and they won’t, because it isn’t.

People will not support a drastic changes in their lifestyles, much less dramatic reduction in their standard of living, to prevent big harms in 80 years. Thinking we can persuade them to do that is a fool’s errand. It would be irrational and self-harming and they won’t do it, and the sooner we accept that, the sooner we can move into an honest conversation about what we can do.

This is why I spend all my time working on heterodox responses to climate change.

Albedo modification and marine Climate Dioxide Removal are the only responses to the climate crisis that align the public’s actual level of concern with a program of action we can really implement.

These heterodox responses allow us to meet people where they are — to tell them, honestly — “look, I get it: this is a concern for you, but it’s not the concern. You’re not going to turn your life upside down to respond to it, nor should you. Still, it’s madness to just ignore it, so let’s have an honest conversation about the things we can do without nuking your lifestyle, or your budget.”

Traditional environmentalists will see that as waving a white flag. It’s certainly not that. It’s a grown-up response to a problem that’s proven to be beyond the reach of juvenile antics.

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I tried to vibecode an app the other day.

It did not go well.

I’m not a coder, so I didn’t really know how to prompt the AI precisely enough to get it to do what I wanted. It spat out a thing that wasn’t really what I wanted, and because I’m not a coder, I didn’t know how to get it to change it into the thing I did want.

Some sort of app did come out the other end. It sucks.

The wrong lesson to take from that experience is “AI is bad at coding.” Software engineers all seem to find that AI is incredibly good at coding. It’s just that to get AI to code well, you sort of have to know how to code yourself. If you heard a software engineer say they think AI is terrible at coding, you’d probably think to yourself “this guy isn’t very good at coding.” And you’d probably be right.

It’s the same thing for writing.

I write with AI all the time. Every day, really.

It’s just that, I’m a writer. I’ve been doing it professionally for 25 years. When AI gives me a garbage output, I can spot where the garbagefulness resides right away. I know exactly what good writing is, so I know precisely how to prompt AI when it messes up.

People who complain AI is bad at writing are sort of telling on themselves. If you’re bad at writing, AI won’t help you much. It’ll clean up your sentences, sure: hunt for typos, give your garbage input some kind of superficial sheen. But it won’t make it good.

If you’re good at writing, AI is hugely liberating. My workflow now consists of a series of very intensive collaborations with Claude. I’ll work up a draft, upload it. Ask it to pick it apart. Consider the feedback, pick apart the good advice from the bad. Rewrite and upload again, ask him to suggest a better way of expressing this point or that, consider it, then tweak it and keep it or chuck it out fearlessly, because the robot never takes an edit personally. I’ll keep iterating, taking advantage of Claude’s true killer feature: indefatigableness. It can keep spotting typos on the 18th iteration, long after any human editor’s eyes would’ve gone dead. I’ll be insanely picky, because the robot doesn’t mind.

Then I’ll ask it to fact check, and to fix any mistakes. Then I’ll ask it to read it oppositionally, looking for weaknesses a critic might attack or imprecisions that might confuse someone. I’ll rewrite again, and check again. On my own this would take an unfeasibly long time, but the robot is fast, and it doesn’t get tired.

And I’ll ask it to help me identify the people I’d need to interview to really make sure it’s right, then I’ll put in a call to that person to check. I don’t expect the robot to replace reporting, I expect it to take the pain out of reporting.

What comes out at the end of this process is unambiguously better than what I could’ve written on my own in a comparable span of time. I might have been able to get to that same level on my own if I had 60 hours to throw at a piece, but I don’t. I have 3 or 4. The end product is fully mine: even if not every word on the page is one I wrote, every word on the page is one I closely scrutinized.

If you’re a writer, Claude can make you a better writer. If you’re not a writer, it can’t do magic. If you have a half-baked idea, prompt the AI sloppily once then copy and paste its first response into the Substack window, you’re debasing the discourse.

But you’re not proving AI is bad at writing. You’re proving you’re bad at writing.

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Your house looked something like this:

Your parents scrimped and saved to put you through school, and you were determined their sacrifice wasn’t going to be for nothing. You studied hard, and you did well. You finished high school, went on to technical training, learned things no one in your family had ever known, qualified for jobs much better than they could have had.

And you’ve done well. Well enough to help your aging parents now. Well enough to afford things they never could—meat when it’s not a holiday, trips to see them once or twice a year. You bought a window air conditioner on installments for those days when it gets really hot. Which come more and more often.

You have a good job now.

After years in a cramped apartment, you even qualified for a mortgage.

Your house looks something like this:

You’re nobody’s idea of rich. You’re one work accident away from losing it all. But you’re not poor in the way your parents were. You sleep on a foam mattress you got at a store, not on straw. Your kids don’t cry themselves to bed hungry. Things get tight at the end of the month, but you’re making it.

Maybe your job is in Lagos. Or Guayaquil, or Dhaka, or Chongqing. The farm where you grew up may have been in Nigeria, or Ecuador, or Bangladesh, or China. Probably China.

The thing is, you are not alone. There are billions of people like you, worldwide, who grew up very poor and now have a foothold in the global lower middle class.

Individually, each of you generates a fraction of the greenhouse gases the lifestyle of the average person in a rich country does. But there are many times more of you than there are people in rich countries. Which is why global emissions keep rising, even though emissions from rich countries keep falling.

People in rich countries aren’t ready to face what your rise means.

We aren’t ready to accept that for millions of people like you, being less poor and consuming more stuff are pretty much synonyms. We don’t want to face the reality that when your consumption goes from near zero to not a lot, emissions rise.

This is about much more than where you get your power. Sure, solar panels are cheaper than ever. But you’re not just buying electricity. You’re buying a scooter to get to work instead of taking the bus. You’re buying a refrigerator so food doesn’t spoil. You’re replacing your corrugated metal roof with concrete. You’re taking the bus to visit your parents instead of walking. You shudder when you remember a childhood of eating just one staple grain meal after meal, and you treasure the variety of foods you can now afford: vegetables, processed foods and, yes, meat.

Rising into the global lower middle class means using more of everything—concrete, steel, transportation, food.

Every step up from poverty is built on physical stuff. And making physical stuff, moving physical stuff, keeping physical stuff cold—that’s where the emissions are. The electricity to power your lights is almost incidental.

The solar panels on your roof don’t change the fact that you bought a roof. They don’t change the emissions from the concrete plant, the steel mill, the scooter factory, the truck that delivered your refrigerator, the industrial farming that produces your chicken.

We aren’t ready to face the reality that you-being-less-poor and you-emitting-more-carbon are sides of the sane coin—not because you’re buying dirty electricity, but because you’re finally able to buy things at all.

Of everything the first-world climate commentariat is in denial about—and there’s a lot—this is the big one: that rising global emissions have little to do with what happens in the rich countries. They keep soothing themselves with misleading headlines about half of the world’s CO2 emissions coming from just 36 fossil fuel firms, as though those firms were emitting for the sake of emitting, instead of serving the demand from people like you.

Deep down, though, they must know that the story of rising global emissions are the story of you getting less poor.

We’re desperate for this not to be true. We want a villain we can properly hate. We want Climate Justice to mean sticking it to capitalist pigs, not reckoning with the fact that emissions are rising because billions of the world’s poorest people have lives incomparably better than their parents did.

We want the baddie to be someone easy to hate.

You’re not. So we don’t think about you at all.

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Look at this bad boy.

It’s the Newton.

Apple launched it in 1993. Nerds and analysts ranted and raved about it. It could recognize your handwriting! It could keep your calendar and your contacts! To a lot of people at the time, this was the future. But this wasn’t the future.

Camera? Sharight. The Newton could not connect to the internet, because there was no internet to connect to. It was a complete failure commercially. The iPhone would come along fourteen years later, wipe the canvas clean, and establish a new paradigm.

Carbon dioxide removal is in its Newton era. We have a bunch of clunky technologies that aren’t it, and we spend a lot of time trying to perfect them. Because we see a shiny future off in the distance and we want to get closer to it.

Right now we’re looking at direct air capture systems that cost around $1,000 per ton, maybe headed toward $600, maybe eventually $100 if a series of engineering (and, hell, thermodynamic) miracles materialize in the coming decades. Enhanced rock weathering might get down to $200. Biochar, maybe $150 on a good day with generous carbon accounting. OAE hoping for sub $100 tons one day, if the stars align.

The technologies are real: they work, people are deploying them. But at those prices, the market that exists is tiny and artificial. It’s Microsoft making commitments for demonstration projects that look great on a Corporate Sustainability report. All of this is subsidy-dependent or driven by corporate climate pledges that amount to sophisticated PR. It’s not a real market.

For lots of carbon removal people, the working assumption is that the way you get to an iPhone is by making a Newton 10% better year after year.

That’s…not how this works.

Multi-gigaton carbon removal is not going to happen by making DAC fans 15% more efficient or scaling up biochar production or testing enhanced weathering on larger acreage. These are real improvements: brilliant engineers are working hard on them right now. But they’re refinements on existing approaches that have hard cost floors and fixed scalability ceilings.

The urge to optimize what exists is strong. But every minute we spend optimizing our Newton is a minute we’re not spending developing our iPhone.

The iPhone didn’t just win the existing cell phone market. It created an entirely new market by solving problems the previous generation of designers couldn’t solve.

Cheap carbon removal will do the same thing. At $1,000 per ton, the only buyers are true believers and regulatory compliance. At $100 per ton, you get serious corporate purchases and maybe some government programs. But at $10 per ton, removing a ton of carbon ends up being cheaper than abating emissions in many cases. Why spend the $50 it takes for electrified heavy trucking to prevent one ton of carbon dioxide if that same $50 can buy you five tons of removals?

To get to genuinely low-cost removals, we need to be a bit ruthless. Devoting more time and more money to elegant approaches that won’t scale isn’t going to do the climate a lick of good. Here, I’m with Ocean Visions: if your carbon removal method doesn’t have a clear path to multiple-gigatons-per-year scale, you need to rethink. Because high cost approaches amount to fancy corporate PR, not climate work.

The carbon removal sector that exists blinds us to the shape of the one that will exist.

To bring it into existence, we need to focus on approaches that aren’t refinements of existing methods but genuine reconceptualizations of the problem. That means focusing on the projects that sound weird or implausible or too ambitious. The ones that aren’t trying to make biochar 20% cheaper but are asking entirely different questions about how to interact with the carbon cycle.

If you read this substack, you know the general direction I expect those ideas to come from. But that’s not really what this is about. Because maybe I’m wrong: maybe the avenue that gets you to $10 a ton is not the one I’m thinking of at all.

My sense is that the people building the transformative solutions aren’t visible yet. They’re too early. Too weird. Too unproven. They’re in a lab probably, or on a ship, thinking ideas that strike people as way out there.

If that’s you, keep going. And reach out if you want to chat. And if you’re looking for someone doing this, try to find weird people saying weird counterintuitive things, or most likely working quietly and not saying anything at all.

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For an 84 year old, James Hansen has a remarkable knack for stirring the pot. The man who first brought Climate Change into the public imagination remains one of the planet’s most closely watched climate scientists. But rather than settling comfortably into the climate science mainstream he once embodied, he’s become an increasingly ardent critic: slamming mainstream science for dramatically underestimating the amount of warming Earth is likely to face.

His latest hobby horse? The El Niño cycle is all out of whack.

But first, here’s the lay of the land for this controversy: the Intergovernmental Panel on Climate Change — the IPCC, the body that synthesizes the global scientific consensus on climate — estimates that if you doubled the amount of CO₂ in the atmosphere, the planet would eventually warm by about 3°C. Jim Hansen says it’s at least 4°C.

What the earth’s actual “climate sensitivity” is matters enormously. If Hansen is right and the IPCC is wrong, we’re in for a much rougher climate ride than we’ve realized.

The debate is wonky, and can come across as irresolvable: one set of nerds has one set of numbers, another set has another set, the math behind each is baffling and you have no way to tell who’s right.

Except Hansen thinks he can prove he’s right not someday in the far future, but before the next summer Olympics. That’s why he’s put a specific, falsifiable prediction on the table: global temperatures, measured as a 12-month running mean, will bottom out at around 1.4°C above pre-industrial levels in early 2026 — during the current La Niña — and then rise to around 1.7°C by early 2027, as the next El Niño kicks in.

If that happens, he argues, it’s game over for the low-sensitivity models.

What’s an El Niño Got to Do With It?

Think of the tropical Pacific Ocean as a giant bathtub that sloshes back and forth. Normally, trade winds push warm surface water westward, toward Indonesia and Australia. Cold water wells up near South America to replace it. That’s La Niña — the cool phase.

But sometimes the winds weaken or reverse. Warm water sloshes back east. The cold upwelling stops. Heat that was stored in the ocean escapes into the atmosphere, and global temperatures spike. That’s El Niño.

El Niños don’t cause global warming — they temporarily reveal heat the ocean has been storing. It’s like opening the oven door: the kitchen gets hotter, but the heat was already there. What makes them useful for Hansen’s argument is that they act as a natural stress test. An El Niño forces the climate system to show its hand.

The thing is: we just had one. The 2023-24 El Niño ended barely two years ago. Normally, the ocean needs longer than that to recharge — to rebuild the pool of warm water in the western Pacific that fuels the next event. In the last 75 years, no strong El Niño has followed another one this quickly.

So if a substantial El Niño develops in 2026 anyway, that itself is a signal. It would suggest the ocean is accumulating heat faster than it used to.

The Aerosol Dimension

The standard story of global warming is straightforward: we emit greenhouse gases, they trap heat, the planet warms. But there’s a hidden variable that typically gets snipped out of the picture: aerosols.

When we burn fossil fuels, we don’t just produce CO₂. We also produce sulfur dioxide and soot and other particulate matter that drifts into the atmosphere and ends up cooling the planet by reflecting solar radiation back out to space. Aerosols also seed cloud formation, and clouds reflect sunlight too. For decades, this aerosol cooling has been partially masking the full warming effect of greenhouse gases: like we’ve been running the heating and the air conditioning at the same time.

Starting around 2015, aerosol emissions began to drop — fast. Mostly, this was good news: China launched an aggressive clean-air campaign that dramatically cut sulfur dioxide emissions and prevented many, many Chinese people from dying horrible deaths from respiratory illnesses caused by air pollution. But it also cut down on the reflective aerosol particles that were offsetting some of our global warming.

Then, in 2020, new international regulations forced the shipping industry to switch to cleaner fuels, cutting sulfate emissions from cargo ships. That, again, turned down the air conditioning.

Hansen argues that this reduction in aerosol cooling is a major reason global temperatures have surged in recent years. It’s not just that greenhouse gas forcing has increased — which it has, by about 20% between 2010 and 2015. It’s that the aerosol mask has been ripped away. And if you put those two things together — higher sensitivity and reduced aerosol cooling — you get a planet warming much faster than the standard models predict.

Why the IPCC Gets It Wrong (If Hansen Is Right)

Hansen charges the IPCC with relying heavily on Global Climate Models — massive computer simulations that try to capture the physics of the atmosphere and oceans. These models handle some things well. They simulate water vapor feedback accurately, for instance. But Hansen argues they systematically underestimate cloud feedback — the way warming changes cloud cover in ways that amplify further warming. Clouds are fiendishly hard to model. They form and dissipate at scales smaller than most climate models can resolve. They’re the source of most of the fat error bars around the IPCC’s climate sensitivity estimates. They know they don’t know how to model them. Hansen thinks if they modeled them right, they’d realize we’re in way deeper shit than we realize we are.

IPCC models produce a climate sensitivity centered around 3°C — not because the physics demands it, but because the models can’t fully capture the feedback loops that would push it higher. Hansen points to four independent lines of evidence — paleoclimate data, observed warming patterns, ocean heat content, and direct measurement of Earth’s energy imbalance — that all converge on a sensitivity of at least 4°C.

The IPCC, he says, has been giving too much weight to models and not enough to observations.

So what happens now?

As of early 2026, the tropical Pacific is in a La Niña phase — the cool side of the cycle. But climate models and recent wind patterns suggest a transition to El Niño later this year. Westerly wind anomalies over the past month have been weakening the trade winds, allowing warm water to slosh back eastward. If these wind patterns persist through the northern hemisphere spring, a substantial El Niño could develop by summer.

Hansen is characteristically blunt about what this means. If global temperatures bottom out around 1.4°C during this La Niña — a level higher than any El Niño peak in the decade before 2023 — that alone would be powerful evidence that global warming is accelerating sharply. He bolsters the case by noting that the 12-month running mean of tropical Pacific upper ocean heat has a correlation of more than 50% with running-mean global temperature, “leading global temperature by 9 months,” while the Nino3.4 index — the standard El Niño measure — has “slightly higher correlation, but a lead time of only 4 months.” (If your eyes just glazed over, welcome to the James Hansen reading experience.)

Hansen is saying the ocean data he’s tracking is already flashing warm. If temperatures then rise to 1.7°C during the next El Niño, it would be very difficult to explain without invoking high climate sensitivity and reduced aerosol cooling — because, as Hansen puts it, climate feedbacks “do not come into play in direct response to a climate forcing, but rather in response to the (delayed) temperature change caused by the forcing,” and it’s precisely those feedbacks that “distinguish high sensitivity from low sensitivity.” Translation: give it a year or two after an El Niño, and the temperature response will diverge sharply depending on whose models are right. It’s easy to get lost in the details, the point is that the La Niña trough we’re in now is already inconsistent with IPCC models, and the El Niño peak we’re about to experience will be even more so.

“This is the sort of bet,” Hansen writes, “that one prefers to lose.”

Please, God, let Hansen be wrong

Let’s be clear about what it means if Hansen is right.

It means 2°C of warming — the threshold the Paris Agreement was designed to prevent — arrives in the 2030s, not mid-century. It means the window for meaningful climate action is considerably narrower than most policymakers assume. It means the comfortable framing of “we have until 2050” — which already felt optimistic — is just flat-out wrong.

Jim Hansen has been sounding the climate alarm since his famous 1988 congressional testimony, and he’s had a better forecasting record than the mainstream consensus for nearly four decades. His contempt for colleagues who disagree with him can be grating — he accuses the climate establishment of responding to his papers in “juvenile, unscientific fashion,” which is not exactly how you build coalitions. But he has a track record that demands attention, even when — especially when — his conclusions are uncomfortable.

I hate it that his ideas are trapped inside prose that only specialists can parse. If you’ve ever tried to read one of his Substack posts, you know the experience: you start with genuine interest, hit a wall of acronyms and chart descriptions around paragraph four, and emerge twenty minutes later unsure what you just read but vaguely anxious.

What he’s saying, stripped of the jargon, is that we have less time than we think, the evidence is about to become undeniable, and the climate science establishment needs to get its shit together and face this. Whether you find that credible or alarmist, the next eighteen months of temperature data will bring a clarity this discussion is sorely in need of.

Because the thermometer doesn’t care about anyone’s writing style.

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For the better part of fifteen years, ocean fertilization has been stuck in a peculiar limbo—too promising to ignore, too controversial to fund, too uncertain to deploy. To phytoplankton obsessives like me, it’s been an intolerable state of affairs. Last week, though, brought the promise of a reprieve from this limbo, in the form of the thing we crave most: big time validation from the institutional mainstream.

Ocean Visions —the nonprofit that’s become the closest thing the marine Carbon Dioxide Removal world has to a central nervous system—just released its Phytoplankton Carbon Solutions Research Framework, a landmark 47-page blueprint for how to investigate whether boosting the ocean’s biological carbon pump could actually work as a climate-relevant mCDR strategy. And not in the hand-wavy, wouldn’t-it-be-nice way that ocean fertilization has been talked about since the 1990s, but in a rigorous, stage-gated, outcome-agnostic way that can bring big time donors on board.

This is a big deal.

Ocean Visions isn’t some scrappy startup with a pitch deck and a prayer. Founded in 2020 with backing from the Grantham Environmental Trust and ClimateWorks Foundation, it’s become the field-building hub for marine CDR, sitting at the center of a network of leading oceanographic institutions and universities. Their CEO, Brad Ack, and chief scientist, David Koweek, have been methodically assembling the infrastructure—roadmaps, databases, assessment frameworks—that a serious research field needs to actually function.

And the money behind this particular report? The Ocean Resilience and Climate Alliance, better known as ORCA—a $250 million philanthropic coalition whose funders read like a who’s-who of serious climate money. Bloomberg Philanthropies. The Sergey Brin Family Foundation. The Packard Foundation. The Moore Foundation. Builders Vision (that’s Lukas Walton, i.e., Walmart money). Oceankind. The Grantham Trust, which leads ORCA’s mCDR pillar specifically.

We’re way past the fringe here. This is the institutional climate philanthropy establishment saying: we think this question deserves a serious answer.

The report itself was guided by an international advisory board, workshopped with 67 experts at the Ocean Visions Biennial Summit in Vancouver, and put through a 30-day public comment period that drew feedback from 56 individuals. We’re far beyond vibes here.

Ocean Visions starts by introducing a useful umbrella term—”Phytoplankton Carbon Solutions,” or PCS— that goes beyond just traditional ocean iron fertilization in High Nutrient, Low Chlorophyll cold water ecosystems — what I think of as GOFOIF (Good Old Fashioned OIF.)

Phytoplankton Carbon Solutions includes a broader family of approaches that leverage the biological carbon pump for CDR. This includes new approaches like nitrogen-fixation in low-nutrient (subtropical) waters, macronutrient fertilization, artificial upwelling, and newer categories like export-based approaches that enhance how much organic carbon sinks down to the deep ocean.

GOFOIF is still the headliner, simply because it’s been trialed already so we have some solid idea of how it would work. Idealized models suggest it has multi-gigaton gigatons removal potential, and its leverage ratio is extraordinary: one unit of iron could theoretically remove hundreds to tens of thousands of units of carbon from the surface ocean.

But the report makes it clear that Ocean Visions is still reserving judgment on whether GOFOIF can actually work in practice. Their cost estimates for OIF range from less than $25 to more than $53,000 per ton of CO₂, which is not a cost estimate, more like a confession of ignorance. Kudos to Ocean Visions for refusing to pretend to have answers they don’t yet have. The challenge for the field now is to constrain that uncertainty.

The report’s most consequential contribution here may be the four-stage decision framework for how to move these ideas forward.

Stage 1 is Pathway Characterization: define the mechanics, quantify the uncertainties, identify the risks. Basically, does this idea even make sense? Stage 2, Pathway Refinement, is where you start doing real science — model improvements, natural analog studies, small-scale field trials up to 100 tons of iron over 1,000 km², and serious community engagement. Stage 3, Evidence for Scale Up, is where it gets expensive and where you find out if your models were lying to you: large-scale field trials with over 100 tons of iron across 1,000+ km², rigorous MRV validation, co-designed research with affected communities, and full regulatory compliance. Stage 4, Deployment Optimization, is our shangri-la: gigaton-scale operations, independent standards development, and the kind of broad international public support that, let’s be honest, no ocean intervention has ever come close to achieving.

Each gate requires clearing specific feasibility and desirability hurdles before more money flows. What they’re building is a funnel designed to kill bad ideas early and cheap, before they become bad ideas that are late and expensive — a concept that, come to think of it, would save us all a lot of grief if applied more broadly in climate policy.

They’re thinking in a structured way about what research to back and what research to step away, so they lay out specific criteria a PCS pathway should meet to advance to the next level of investment. To keep backing a thing, they want to make sure it has a clear pathway to:

1. Durability of at least 100 years.

2. Measurability on par with other CDR pathways.

3. Potential to reach a gigaton per year of CDR for multiple decades.

4. Cost trajectory toward $100 per ton or less.

5. Sufficient understanding of environmental and socio-economic risks to support informed decision-making.

6. Social and regulatory support from affected communities.

The flipside is that the approach builds in explicit offramps. If scalability potential drops below a gigaton per year, if there’s no feasible path to reduce uncertainty, if environmental risks prove insurmountable—you stop. This is exactly the kind of disciplined, outcome-agnostic structure the field has needed. Because the phytoplankton world needs advocates —a role I’m super happy to play— but it can’t be just about advocacy: the money people need a decision architecture, a structured way to tell if the light is green, yellow or red.

Currently, only GOFOIF qualifies for Stage 2 (Pathway Refinement), based on the knowledge built up through 15 field experiments between the 1990s and 2009. Everything else—LNLC iron fertilization, export innovations, macronutrient approaches—sits in Stage 1 (Pathway Characterization). No field trial has been conducted since 2009, when a rogue commercial operation in the Pacific poisoned the well for a generation of research.

Ocean Visions is definitely right that we need to reduce uncertainty in net CDR estimates and, especially, the biogeochemical models behind those estimates. This is my current main obsession: right now, models don’t agree on basic questions about fertilization’s carbon benefits, so we certainly can’t have that. The report does note we’d be much better off if we understood the nitty gritty of the biological carbon pump’s baseline behavior better. I know it sounds like motherhood and apple pie, but it matters.

The most exciting part is that Ocean Visions comes out emphatically in favor of doing field trials, but the report is clear-eyed about what they’re going to cost. Small-scale trials (less than 100 km², two months of observation) could run $3 to $25 million. A comprehensive program with multiple large-scale trials might come in at $250 million over ten years. For reference, the ExOIS consortium’s proposed northeast Pacific GOFOIF trial—currently the most advanced field trial concept—carries a price tag of $40 to $45 million for two trials over three years.

The pathway-specific priorities focus on sharpening the scalability picture for GOFOIF through realistic deployment scenarios (not idealized models), but also advancing the still-nascent science of subtropical nitrogen-fixation-based iron fertilization (building on the Tonga-Kermadec hydrothermal vent observations I’ve written about before), as well as funding early-stage innovation in export enhancement—clay flocculation, mineral ballasting, aluminum-based degradation resistance.

The implementation priorities are where the report earns its institutional credibility. Community co-design isn’t an afterthought—it’s baked into the stage-gate progression. Coastal community and fisheries capacity-building gets its own dedicated priority. And the report insists that PCS risks be contextualized against the alternative: doing nothing in a world where ocean primary production is already declining under climate stress.

It’s exciting to see people who command the respect of big-time funders thinking through these ideas in this way. This feels like the way you shift the whole concept from neat-in-theory to real-thing-we’re-going-to-do.

Still, though, if you’ve been tracking this space, you might ask: what does this add to the 2022 NASEM report or the ExOIS roadmap?

Three things, I’d say.

First, scope. By defining the PCS umbrella broadly enough to include export-based innovations alongside production-based fertilization, the framework opens up a richer design space for research. If the big problem with iron fertilization is that you can grow blooms but can’t reliably get the carbon to sink deep enough, then export enhancement can’t stay an afterthought.

Second, structure. The stage-gate approach provides something that previous roadmaps lacked: a clear, repeatable decision framework with explicit criteria for advancing, pausing, or killing a pathway. This is the kind of tool funders need to make defensible allocation decisions in a field full of uncertainty.

Third, realism about money. The report is designed for a world where PCS funding is scarce—starting with $1-5 million for initial sensitivity analyses and model improvements, scaling to $5-10 million for parallel pathway investigations and community engagement, building toward the $40+ million needed for large-scale field trials. If some random guy with a substack tells you that, that’s one thing. When the body set up by the biggest climate funders says it, it’s quite another.

That freeze is thawing. The NASEM report in 2022 gave scientific legitimacy back to the question. ORCA and the Grantham Trust put real money behind it. ExOIS started designing actual trials. Growing Oceans launched to study nitrogen-fixation pathways. And now Ocean Visions has produced the strategic architecture to coordinate the whole sector.

None of this means phytoplankton carbon is going to be a killer solution. The report levels with us about the possibility that it might just won’t work: uncertainties might prove irreducible, environmental risks might prove unacceptable, the math might simply not add up at scale. Those are legitimate outcomes of a well-designed research program: if we were sure it would work, there’d be no point to doing research.

But here’s the thing. We need 10 gigatons of CDR per year by 2050. We’re nowhere close. No other CDR approach combines scalability with affordability like phytoplankton does. The idea that we can afford not to rigorously investigate the ocean’s biological carbon pump—the planet’s largest natural carbon sequestration system—has always been more about politics than science.

The grownups are finally acting like it.

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The year is 2038.

You’re looking at a screen showing a patch of ocean 170 kilometers northeast of the Seychelles.

It’s the subtropical Indian Ocean gyre, some of the most nutrient-poor waters anywhere. Satellite data shows chlorophyll concentrations barely above detection limits — nothing’s growing there.

Your job is to operate a prescriptive ocean AI trained on reams of ocean data called Ocean Intelligence, OI to friend. The system has just identified a nearby patch with low iron, low fixed nitrogen, and fertilization assets close enough to be deployed in time. It flags the patch as the optimal deployment opportunity for carbon drawdown.

OI pulls together satellite observations, historical measurements from research cruises that have passed through this region to generate a set probabilistic projections about what happens if you intervene. It runs a full physics-based simulation of the next two weeks of ocean circulation in this exact patch, generating an ensemble of scenarios, each with a likelihood estimate. A mesoscale eddy is likely to develop, which could contain any bloom to a manageable area. Iron added now will hit a sweet spot—enough mixing to distribute nutrients, not so much that the bloom gets dispersed before carbon export begins.

The OI packages all of this into a recommendation. It specifies the intervention: three autonomous surface vehicles should deploy 12 tons of iron across 400 square kilometers in a specific geometric pattern.

It lays out the monitoring strategy: two underwater gliders positioned to track bloom development, a fixed mooring to measure CO₂ drawdown, satellite overpasses coordinated with profiling floats to measure particle flux. It estimates 200,000 tons of CO₂ sequestered with an uncertainty range of 150,000-280,000 tons. It flags potential risks: a 15% chance the eddy doesn’t develop as predicted, a 5% chance of unusual oxygen depletion based on similar historical cases.

But that’s just the oceanography. Next it has to deal with the bureaucracy.

This patch of ocean sits in the Seychelles’ Exclusive Economic Zone. You can’t just put iron in someone else’s waters because some computer says it’s a good idea. The OI generates an Environmental Impact Assessment formatted to the regulatory standards required by the Seychelles. It documents baseline conditions, projects ecological changes, quantifies likely impacts on fisheries and marine ecosystems. It shows that iron concentrations will remain below natural variability from dust deposition, that the intervention is time-limited and reversible, that monitoring will detect any adverse effects early. It compiles the whole package —data, methodology, risk assessment, monitoring protocols— and submits it to the Ministry of Fisheries. Then it waits for regulatory approval, just like any other marine research project.

But the OI is also about thinking economically. It pulls current carbon credit prices from compliance and voluntary markets, calculates the costs of deployment and monitoring, and builds a profit-and-loss model for this specific intervention. It estimates return on investment, but crucially, it doesn’t just show a single number. It shows the full distribution of possible outcomes—best case, worst case, most likely case—all couched in terms of quantified uncertainty.

Then it waits.

A team of oceanographers reviews the recommendation. They work for a non-profit run by scientists to operate the OI platform. They drill down into the physics model outputs, check the uncertainty bounds, examine the historical analogs the model used. For sure, they have questions: Why this specific iron dosage? What happens if the eddy arrives six hours early?

The Ocean Intelligence model is not itself a full physics-based ocean model, but it can always invoke one in high stakes situations. In this case, the OI runs several high-resolution physics-based simulations to answer the human team’s questions and presents its conclusions. After human review and regulatory approval, the oceanographers authorize the deployment.

The three wave gliders converge on the target coordinates and begin their runs, so monitoring begins immediately. Gliders descend and surface, transmitting data. The mooring records CO₂ changes. The OI checks them against satellite data monitoring chlorophyl and temperature and processes everything in near-real-time, continuously updating its predictions against observations.

Four days in, chlorophyll concentrations begin to rise. The bloom is developing exactly as predicted. But on day six, something unexpected happens: dissolved oxygen levels start dropping faster than the model had anticipated. The OI flags it immediately, runs diagnostics, determines it’s likely due to more intense bacterial respiration than the initial model suggested. It checks for harmful algal bloom species, for unusual changes in zooplankton communities, for any sign this is heading somewhere problematic.

The OI sends an alert to the oversight team, adding the regulators in the Seychelles in CC: “Oxygen anomaly detected, likely within normal bloom dynamics but 20% more intense than predicted. Recommend continued monitoring, no intervention suspension required.”

It runs the full physics-based model a dozen times to ensure its expectations are met. It shows its work—the results of the full physics-based model runs, its diagnostics, and comparison to historical blooms. The oceanographers and regulators concur. The operation continues. The OI adjusts itself in light of what it has learned from this experience.

By day fourteen, the bloom begins to dissipate. The profiling floats show particulate organic carbon sinking past 200 meters, past 500 meters. The OI then calculates final results: 220,000 tons of CO₂ sequestered for at least one century, verified by multiple independent field measurements, with a full counterfactual baseline, and backed also by several runs of the full physics model.

The OI packages everything into a verification report—raw data, model outputs, uncertainty quantification, counterfactual analysis—and hands it off to an independent verification team. They have their own physics-grounded AI, trained independently and using different methods to cross-check the results. The verification AI reviews the monitoring data, runs its own physics models, and confirms the carbon accounting. If the numbers match within acceptable uncertainty bounds, carbon credits get issued.

The credits hit the market, buyers pay up and apply them to the offsets to their own nationally mandated caps. Revenue flows back to fund the next deployment, with royalties also flowing to the treasury of the Seychelles. It’s their ocean, after all.

At each step, the OI learns from the experience: bacterial respiration parameters for this region need adjustment. The next recommendation will be more accurate.

That’s the vision, anyway. Whether it becomes reality depends on choices we make now.

To be clear, all the tech to build what I’ve just described exists today — it just hasn’t been integrated into a single tool. Using 2026 technology, building such tool would be complex but doable, if properly resourced. And AI technology is advancing enormously fast. Every year the barriers to building a tool like this will become less daunting. As the frontier pushes towards artificial general intelligence, tools like this that scan as futuristic today may come to seem almost humdrum.

I think when we look back, 25 years from now, we’ll wonder that anyone ever thought it would be possible to get on top of climate change without an AI-based prescriptive ocean model like this.

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If you saw the 2016 documentary AlphaGo, you remember Move 37. DeepMind’s fantastically sophisticated AI algorithm is playing against Lee Sedol, South Korea’s top Go player. The game looks “normal” until the machine does something that looks completely insane. You can hear the collective intake of breath from the professional commentators, the initial confusion after Move 37 —that can’t be right!— followed by slow, dawning recognition that something unprecedented is happening. Move 37 isn’t just bizarre, it’s superhuman. It turns the whole game. Lee Sedol eventually resigns.

Move 37 obsesses a certain breed of techie because it shows AI coming up with an idea no human being would even have considered. An idea so obviously “bad”, it merits no serious interest from a professional.

Go is hugely complex. On each turn, a player has hundreds of legal moves to choose from, and the opponent has hundreds of possible moves in reply. The decision trees that result are insane: just three moves out, there are hundreds of millions of possible board configurations. No one can hold that many possibilities in their mind at once, so human champions adapt by focusing their attention on just a handful of candidate moves that, after years of practice, they’ve learned to intuit as good. The vast bulk of possible moves, they discard without thinking about them.

This is how all human expertise works. To be an expert means to have a gut level feel for what’s likely to work. It means developing sophisticated pattern recognition that instantly eliminates the vast majority of possibilities, leaving a manageable handful open to consideration.

These pruning heuristics are what make human expertise possible.

But they also make certain solutions invisible.

AlphaGo beat Lee Sedol because it pruned the game tree differently. Not because it searched the entire thing — not even a computer can do that. Its neural networks, trained on millions of games and refined through self-play, had developed pattern recognition from different foundations. It hadn’t inherited human heuristics about shape and territory and influence. It learned directly from outcomes: positions that lead to winning.

When ocean biogeochemists think about marine Carbon Dioxide Removal, they face a pruning problem that makes Go look like child’s play.

Consider what’s actually involved in evaluating a potential ocean carbon removal intervention. Three-dimensional circulation patterns that vary seasonally and interannually. Biogeochemical cycles—carbon, nitrogen, phosphorus, iron, silica, others—each with their own dynamics and limitations. Microbial community responses. Temperature and pH effects on biological processes. Viruses. Potential downstream impacts on fisheries, on oxygen minimum zones, on atmospheric feedback loops.

The combinatorial space of possible interventions—location × timing × method × scale × duration × combination strategies—is utterly overwhelming.

Human ocean scientists have developed powerful pruning heuristics to navigate it. They focus on interventions they can measure exploiting mechanisms that fit their understanding of existing biogeochemical models on scales that match realistic funding constraints and available logistics. They mind their professional reputations, so they propose approaches that will seem “reasonable” to peer reviewers who’ve spent careers studying these systems.

These heuristics are earned. Built from decades of observations, failed experiments, hard-won theoretical understanding. They’re mostly correct. That’s why they persist, why they’re taught to graduate students, why they shape which proposals get funded.

“Mostly correct” means they also create systematic blind spots.

At Anthropocene, we support an approach to marine carbon dioxide removal that exploits a mechanism most research overlooks: extending the availability of bioavailable nitrogen in oligotrophic ocean systems by mimicking natural fertilization events. The specifics involve decision trees that make Go look like tic tac toe. How much of which nutrient do you consider, where exactly, in what form exactly, when exactly?

We have heuristics to answer these questions, sure, but they’re relatively blunt.

What would a Move 37 for nitrogen fixation for phytoplankton carbon look like? Impossible for humans to say. Maybe there’s some spatial patterns of intervention that exploits circulation in ways that seem geographically nonsensical until you see the global response. Maybe it’s a timing strategy that coordinate with seasonal dynamics in ways humans wouldn’t think to orchestrate, or some exotic cascade effect where small interventions in “unimportant” locations trigger disproportionate responses elsewhere, or some nutrient that bottlenecks a whole system that’s not on our radar. Who knows.

The best human Go player couldn’t have seen Move 37. The best human oceanographers probably can’t see the optimal approach to mCDR.

This is where physics-grounded AI becomes interesting.

I’m not talking about large language models that confabulate plausible-sounding nonsense, or pure machine learning approaches that need massive training datasets and can only interpolate within their training distribution.

I mean a world-model AI of the ocean. Imagine a neural networks training on synthetic data from GPU-accelerated ocean general circulation models with full biogeochemistry, constrained by conservation laws, grounded in thermodynamics. Training the neural network on physics model outputs could yield an emulator that runs orders of magnitude faster while still respecting thermodynamic constraints, making it possible to search intervention space at scale.

I’m increasingly convinced this is what mCDR research will look like in the next decade.

An Ocean AI system still wouldn’t be able to search every possibility: it still has to prune the decision-tree. But it eliminates possibilities for different reasons than human experts do.

The system would simulate millions of intervention scenarios, evaluating each against physical constraints—energy balance, nutrient budgets, circulation dynamics—without inheriting human preconceptions about what’s “worth trying.” It won’t know that certain approaches are “obviously wrong” by expert consensus. It would only know what the physics and the biogeochemistry allows.

The interventions that survive AI pruning but fail human pruning—that’s where Move 37 lives for marine carbon dioxide removal.

Building a GPU-accelerated ocean model with sufficient resolution and biogeochemical complexity is technically challenging but conceptually straightforward. The computational infrastructure exists, the physics is just a wall of Navier-Stokes equations—Newtonian physics in fluid dynamics terms. It’s a fully solvable engineering problem.

The hard part is what comes after.

When the model proposes an intervention that human experts have learned to prune away, then what do we do? Move 37 looked like a mistake to every professional Go player watching in real time. Several thought AlphaGo had just malfunctioned.

The ocean’s Move 37 will trigger the same response from marine scientists. At first.

This creates a bootstrapping problem. A physics-based AI system for ocean carbon removal needs to build credibility before anyone implements its most counterintuitive suggestions. It might start by proposing relatively conservative interventions—things that look plausible to human experts but that no one had specifically thought to try. Demonstrate that those work on the basis of physical measurements and you can gradually expand the envelope of what seems reasonable to test.

Of course, if the system only ever proposes things that feel safe to human intuition, we’ve wasted our time. We’d build it precisely because human pruning has blind spots. The credibility-building phase can’t become a permanent constraint. At some point, we need institutional capacity to take seriously—and actually test—interventions that violate expert heuristics but respect physics.

Thing is, this isn’t a problem that gets solved with better AI or more computational power. It’s institutional and cultural. We need funding mechanisms that can evaluate proposals outside the pre-pruned solution space. Peer review processes that can distinguish “this violates what we expect” from “this violates what we know.” Experimental designs that can test counterintuitive proposals from physics-based models while maintaining appropriate safeguards.

None of this means dismissing human expertise. Ocean scientists have built extraordinary understanding of these systems through patient observation and theory-building. That knowledge is what constrains the physics models, what validates their outputs, what identifies when simulations are producing artifacts rather than insights.

But expertise creates structure in how we search for solutions. And that structure has gaps.

Human-led incremental research is systematically exploring a pre-pruned solution space. That’s fine for building fundamental understanding of ocean systems—possibly optimal, even. It may not be good enough for finding gigaton-scale carbon removal solutions on climate-relevant timescales.

We’re at an inflection point where computational power has finally caught up to the complexity of the problem. GPU acceleration makes it possible to produce high-resolution synthetic training data from global ocean models at speeds that enable the resulting emulator to systematically explore the intervention space. The physics is well enough understood to constrain these models meaningfully, we’re not short of observational data to validate their behavior in unperturbed conditions.

What we don’t yet have is institutional infrastructure to take seriously what these models might reveal.

Physics-based AI for ocean carbon removal would serve multiple functions. High-precision verification and monitoring of interventions—tracking carbon flux changes, attributing them to specific actions, quantifying permanence and downstream effects. This capability alone would be hugely valuable, helping distinguish effective interventions from failed ones and building the empirical foundation for scaling what works.

But the real value proposition is discovery. Building a platform that can show us interventions we’ve learned not to see, by pruning possibility space according to physics rather than human intuition.

And then—this is the hard part—building the institutional capacity to actually try what that different pruning reveals.

The solutions we need for gigaton-scale carbon removal are almost surely sitting in the 95% of possibilities that expert pruning has learned to eliminate. Not because ocean scientists are wrong about what works. They’re probably mostly right.

Being “mostly” right means systematically missing the exceptions.

We’re still designing research programs for a world where human intuition is our only guide. That world ended with AlphaGo. The climate timeline doesn’t give us time to exhaustively search the 5% of intervention space that feels safe to human experts.

We need to search the other 95%—systematically, guided by thermodynamics rather than familiarity. The computational tools exist. The institutional capacity to trust them does not.

I wouldn’t be surprised if building that capacity turns out to be harder than building the models.

It’s also more urgent.

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Everybody knows oil is made of dinosaurs, right?

The idea is part of our cultural flotsam and jetsam, just a fact that enters your head and squats there. It’s a great image: there’s a reason oil companies, real and imagined, put it right there in their logos.

The truth, however, is less exciting.

Yes, the long hydrogen-and-carbon chains we get gasoline from really do come from long-dead organic matter. But almost none of it was charismatic megafauna. Mostly it’s plants: organisms that, millions of years ago, perfected the magic trick of soaking up energy from the sun and turning it into their own bodies. Most of that didn’t happen on land, most of it happened in the oceans.

In fact, the vast bulk of the old biomass that turned into oil was organisms you would need a microscope to notice: phytoplankton. Which just means “tiny marine plants.”

Most people live their whole lives never giving phytoplankton a second thought. When you start learning about them, you get obsessed. Microscopic plants were the dominant form of life on Earth for literally a billion years. They’re the reason the atmosphere has oxygen in it in the first place. For millions of years they drifted, soaked up solar energy, died, sank, and got buried. Over absurd geologic timescales, some portion of that biomass got cooked under heat and pressure into the hydrocarbons we now extract, refine, and burn.

Which means a tank of gasoline is condensed sunlight captured by ancient ocean life. The “carbon” in the “carbon emissions” everyone is worried about is just the long dead bodies of phytoplankton.

Maybe if people understood that their cars run on fossil phytoplankton, not dinosaurs, our climate conversation would make more sense. Because then they’d find it more intuitive that the trick to climate change is getting the carbon we’ve dumped into the atmosphere back to the state it spent the last several million years in: as dead organic matter in the ocean depths.

We can do this. Because the organisms that fossilized into oil have descendants still floating in today’s oceans. The phytoplankton of today aren’t identical to the ones that made the oil: they’ve had billions of years to evolve. But the basic gig is the same: use the energy from the sun to fix CO₂, build organic matter with it, die, then sink.

What we’re talking about is closing the loop: phytoplankton becomes gasoline. Gasoline becomes carbon dioxide. Carbon dioxide turns back into phytoplankton. Everyone goes home happy.

This, in fact, is what will eventually happen to if we give the ocean a few tens of thousands of years to do its thing. Trouble is, that’s not a pace that works for humans.

The problem is timing. The ocean carbon cycle isn’t one loop, it’s a loop with gears. Some parts spin fast: photosynthesis, respiration, seasonal blooms. Other parts move slow: deep circulation, sediment burial, rock weathering.

When humans burn fossil fuels, we’re taking carbon that nature locked up on the “millions-of-years” schedule and releasing it on the “Tuesday morning” schedule. Once you see the mismatch, you recognize the problem of climate change is “how do we match the speed of carbon removal to the speed of carbon release?”

Can we accelerate the part of the loop that pulls carbon back down? Can we work with nature so it does what it was going to do anyway, but quicker?

Because the biosphere already knows how to take CO₂ out of the air. It does that every day. We don’t need to genetically engineer some new organism to do this, nature did that work for us. We just have to feed them.

This isn’t science fiction. There are places where something like this appears to happen already. Near Tonga, undersea volcanic activity injects nutrients and trace metals into surface waters, stimulating phytoplankton growth—more photosynthesis, more biomass, more carbon drawn out of the surface system. Saharan dust does the same thing in the North Atlantic, a major reason it’s a better carbon sink than the other oceans. Even ash from forest fires can play this role.

Sometimes the ocean gets a boost. A fertilization event. A reminder that the biological pump isn’t fixed, it’s responsive. Turn the right knobs and the biology ramps up. So the question isn’t “can the ocean take up carbon?” We know it can. The question is: can we accelerate the rate safely and predictably, at scales that matter?

I think we can. Once you frame it appropriately, this seems like it’s obviously the best response to the climate crisis. Figuring out the how is what I spend all my time on.

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Last week in Davos, my Prime Minister, Mark Carney, signed the death certificate for the rules-based liberal international order. Climate people are greeting his rupture speech with a sickened knot in their stomach. For three decades, they built their entire response to climate change on the assumption that something like the post-1945 settlement was permanent.

That order is no more.

In an upsetting but necessary piece in The Atlantic, Robert Kagan warns that the resulting multipolar reality is “one that will make the Cold War look like child’s play and the post–Cold War world like paradise.” Without a hegemon keeping the peace, and with Russia and China on the prowl, every middle power gets forced back to prioritizing security. Re-arming is expensive. In a world where Germany has to spend 4% of GDP on defense and Poland and South Korea are quietly building nuclear weapons, who exactly is going to care about emissions? Energy security trumps emissions every single time. All that stuff about “ratcheting ambition” already reads like an artifact from a lost era.

In Climateworld, the temptation is strong to just pretend like none of this is really happening. Fingers firmly plunged in ears, “naaa-naaa-naaa”s bellowing, they’re still going to turn up at the next COP like the old world still exists. The entire UN Framework Convention is likely to go the way of the World Trade Organization: a zombie institution that’s still there on paper but doesn’t actually do anything of relevance.

Let me say something heretical: the zombification of COP may be just what the climate space needed. Because even when it “worked,” the UN climate beast didn’t work. And not just because everything the UN touches turns to ossified bureaucracy, but because the focus was wrong from the start.

The UN system thinks of the climate problem as chiefly about mitigating emissions and, secondly, about helping poorer countries out if emissions can’t be brought down fast enough. That whole way of thinking made sense back in 1992, when atmospheric CO₂ concentrations were at 350 parts per million and the whole dog-and-pony show got on the road. It’s been losing relevance ever since. Now that atmospheric CO₂ is 430 ppm and the rise is still accelerating, we should stop pretending. It seemed like a good idea. It failed. We need something better.

We spent 30 years waiting for everyone to agree to do something serious about climate change. Everyone didn’t agree. The UN Process delivered exactly what it was architecturally destined for: the most aggressive climate agreement Saudi Arabia will sign on to. Doubling and tripling and quadrupling down on that mechanism was never really a sensible strategy in the first place.

Still, there was a kind of isomorphism between the UN Framework’s architecture and the emissions-reductions-first view of climate change. Carbon emissions all end up “well mixed” into the same atmosphere, wherever they came from. If your strategy centers on curbing emissions, multilateral cooperation is absolutely needed.

But what if we flipped the script? What if we shifted focus to removing the carbon dioxide that’s already in the atmosphere?

Well, then we’d get a very different dynamic. The opposite dynamic, in fact. Because you don’t need global agreement to capture carbon dioxide at scale. With emissions mitigation, unless everybody does it, nobody benefits. With Carbon Dioxide Removal if anybody does it, everybody benefits.

It means shifting from a world where everybody is a veto player to a world where nobody is.

Really, all you need is one place willing to give climate-scale CDR a chance, and some jurisdiction willing to pony up the cash. If you can bring CDR costs down to the $10 per ton range, it wouldn’t even be that much cash—certainly much less than we’re spending now on a path that doesn’t work.

The question, really, is whether carbon dioxide removal can be brought to scale at that kind of price.

My sense is that people gave up on CDR far too early. Marine carbon dioxide removal in particular has obvious potential to get us there, if only because the ocean already holds nearly 100 times more carbon dioxide than people have ever put into the atmosphere. Much, much more research ought to be going into these responses.

When the multilateral route commanded a consensus, people resisted talk about climate-scale CDR simply because it seemed to detract from the universality the UN approach demanded. This came phrased as concerns about moral hazard: “you can’t take carbon dioxide out of the atmosphere, because that just gives polluters excuses to keep putting more in!”

Once we process the rupture in the multilateral order we’re living through, the intelligent calibration is to double down on much better CDR: much cheaper, much safer, much more scalable and, of course, ecologically benign.

This is what I spend most of my time working on: specific marine carbon dioxide removal mechanisms that could turn this conversation on its head. Scientists are working on this problem as we speak. If we reorient climate action around supporting their efforts, and if we’re willing to think outside the box, we might actually be able to address climate in a multipolar world. Not because it’s easier, but because we’re finally free to pursue what works instead of what everyone can agree to.

It’ll take a few years. But we can do this.

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Before everything that happened, the idea that a 29-year-old scholar of medieval politics from Bennington College was going to rewrite the rules of American government would’ve struck everyone as absurd.

After everything that happened, after the whole catastrophic series of events leading to the Third Term, a battered and bruised nation convened the Constitutional Convention of 2031. By then, with national prestige in tatters, people were ready for radical departures.

Tons of weird ideas were in the air — for a while, it seemed every Silicon Valley bro had a take. Liquid democracy via blockchain. AI-selected cabinets. Prediction market governance. But Silicon Valley was complicit in everything that happened; who would trust them?

Instead, a head of steam built behind the low-key professor in the goatee giving YouTube lectures on the Venetian constitution.

It’s easy to forget now, but in the 2020s nobody was talking about Venice. Before those videos went viral — you remember them, the ones with the oddly soothing voice-over and the MS Paint illustrations of doges in funny hats — people didn’t know about the convoluted process Venice had used to pick its leaders, much less thought they might modernize a thousand-year-old system into a blueprint to protect America from everything that happened ever happening again.

But viral they did go. Maybe because they promised a system that couldn’t be gamed, a system no ambitious striver could pervert into autocracy ever again.

The principles were simple enough: the Venetians picked their Doge (not that kind of Doge) in a way that purposefully mixed elements of chance with elements of choice. Much of the process was purely random, and so impossible to game. The rest of it involved deliberation, so you couldn’t end up with some random lunatic in power.

Without an all-out existential crisis, Americans would never have considered a departure this bold. After everything that happened, they did.

How Democratic Selection Works

The 2032 constitution did away with presidential elections altogether, replacing them with the Democratic Selection process kids learn about at school. The requirements for putting yourself forward as a presidential candidate are minimal: 10,000 signatures nationwide and a $25,000 filing fee (refundable if you advance to The Ranch).

All kinds of people try it. Professional politicians who spent decades climbing the ladder. Crackpots who think the government is run by lizard people. Bored billionaires who think wealth means they’re uniquely qualified. Serious outsiders with something to offer — the Air Force general, the climate scientist, the former governor of a state nobody thinks about.

In the last cycle, 183 candidates filed.

The announcement period is its own circus. Candidates drop slickly produced videos. Some go viral (”Candidate 47’s announcement was just her silently making a sandwich for three minutes and it got 20 million views”). Most don’t. The media tries to cover all 183 but they can’t — it’s too many, too chaotic, too democratic.

Reddit’s r/WhoAreThese183 becomes the de facto clearing house. Users create spreadsheets tracking everyone. “Candidate 92 claims to have invented the waffle iron. He did not invent the waffle iron. Also he’s bankrupt.” Within 48 hours of filing, every candidate has a dossier compiled by amateur sleuths. Some candidates flame out before selection even begins — the billionaire whose finances don’t add up, the politician whose voting record contradicts their platform. Democracy by crowdsourced oppo research.

Then selection starts.

Round Zero

More than 84 million Americans are registered for the selector pool. It’s quick, free, the only requirements are that you’re over 18, have no criminal record, and aren’t registered as a foreign lobbyist. Out of them, 1,000 will be picked to serve as Selectors.

Why do people register for the pool? For all kinds of reasons. Some take it seriously — civic duty, a chance to shape history. Some are curious. Some figure the odds they’ll be picked to serve as selectors are astronomical, so why not? Some who become selectors swear up and down they didn’t even remember they’d put themselves in the pool until the FBI showed up.

The drawing is broadcast live. Names scroll by like a memorial wall, except this is a beginning. The cameras find some of them: a dental hygienist in Tulsa gasps. A retired marine in San Diego nods stoically. A librarian in Vermont starts crying.

One thousand names.

“I’m in the 1,000” becomes an instant online identity. Subreddits teem with them. Twitter accounts appear with “Selector #472” in the bio. Some of them become minor celebrities immediately. Selector #203 does an AMA on Reddit that crashes the server. “What’s it like knowing you might pick the next president?” “I’m mostly worried about my cat, honestly. Who’s gonna feed Mittens?”

Then the FBI background checks begin. Ninety-three people are struck off — criminal records that slipped through initial screening, financial irregularities. One person is revealed to be registered as a foreign lobbyist (they swear it was for a trade association, not a government — doesn’t matter, they’re out). A few withdraw for personal reasons.

The remaining 907 selectors get to work.

The First Filter

The 907 receive access to a portal with every candidate’s file, platform statement, video introduction. One hundred and eighty-three candidates. It’s overwhelming. Nobody can seriously evaluate 183 people.

But that’s the point. Round One isn’t about finding the best candidate, it’s about getting rid of the worst ones.

The selectors have two weeks. The online discourse is fevered. “Candidate 74’s platform is just a link to a conspiracy theory YouTube channel. Why is this person allowed to run for president?” Technically anyone can run — that’s the beauty of it. The selectors filter them out.

Using approval voting — check a box for every candidate you find acceptable — the 907 narrow the field to 100.

The results are announced live. Candidate 118, whose entire platform was “Free Pizza Fridays,” gets 12 approvals and is gone. Candidate 77, the conspiracy theorist, gets 43 and is gone. The billionaire everyone assumed would buy his way through gets 287 approvals and stays. The climate scientist everyone wrote off as too wonky gets 651 and stays.

By the end of the night, the Final 100 emerge.

It’s a mixed bunch. Senators and governors who’ve been preparing for this their whole lives. The math teacher from Oregon whose platform statement went viral. The former general with the distinguished service record. The tech CEO who actually has a coherent vision. The activist who’s been organizing for twenty years.

There are some surprises too — the guy who runs a chain of hardware stores in the Midwest and wrote a 47-page policy document on infrastructure that made actual sense. The epidemiologist nobody had heard of whose pandemic preparedness plan got 739 approvals. The tribal leader from New Mexico whose environmental platform combined traditional knowledge with cutting-edge science.

The 83 eliminated candidates give statements. Some are gracious, some are furious, some admit they were never serious.

The Final 100 face the cameras. “We survived Round One,” one says. “It’s a marathon, though, not a sprint.”

They have no idea.

The Venetian Pivot

Next, the system does something very Venetian.

The 100 candidates are reduced to 50 by lottery — random number generation, audited by international observers, open-source code available for anyone to verify.

The drawing is broadcast live. Candidate names appear one by one. Some make it, some don’t. A senator with 30 years experience gets eliminated by chance. The hardware store owner survives. The epidemiologist is gone. The tribal leader stays.

It’s brutal. Candidates who’ve been preparing for years, who advanced through merit in Round One, get eliminated by random number generator.

On PBS, professors discuss sortition’s long and surprisingly respectable pedigree in political theory. They note that the idea of choosing leaders by lot goes back to ancient Athens, where most public offices were filled by random draw. Athenians thought elections were oligarchic because electorates would just pick the richest, most famous candidate, while sortition was truly democratic, allowing anyone to serve. The practice fell out of favor for centuries, but it never quite died. Modern jury duty is sortition — we trust random citizens with life-and-death decisions in criminal trials but somehow balk at trusting them with political ones. Political theorists have been arguing for sortition’s revival since at least the 1980s: Bernard Manin wrote about it, James Fishkin designed “deliberative polls” using randomly selected citizens, and by the 2010s sortition enthusiasts were running citizens’ assemblies in Ireland and France to tackle thorny issues like abortion and climate policy. Even hereditary monarchy, if you squint at it right, is a kind of sortition — the luck of birth determines who rules, which at least prevents the most ruthlessly ambitious from clawing their way to power. The major drawback of sortition is that pure luck sometimes lands you with a mad king, or a plainly unfit leader. But after everything that happened, Americans fully grasped that democracy had the same pitfall. The Venetian approach solves the problem by combining sortition with voting in successive rounds. At the Bennington Forum, scholars stress that in this mixed approach lottery isn’t the endpoint, it’s a randomizing function inserted at key moments to prevent gaming, to break coalitions, to remind everyone involved that this is bigger than any individual’s merit or ambition.

The betting markets, meanwhile, are losing their minds.

Out of the 907 initial Selectors, 37 Grand Selectors are chosen by lot. The rest are thanked for their service and dismissed.

The 37 are in shock. Some of them had barely thought about the next stage, and now they’re about to pick the president.

Within 24 hours, they’re on planes to Utah.

The Ranch

The Selection Ranch sits on 12,000 acres of Utah high desert, purpose-built for Presidential Selection at a cost of $2.3 billion. Worth it? America is about to find out.

The architecture is striking — modernist glass and timber, designed to be both transparent and functional. The Main Selection Hall has 40-foot ceilings and a circular arrangement of desks. The quarters are comfortable but not lavish. Common areas include a library, a gym, a prayer room, a garden.

And cameras. Hundreds of cameras, everywhere except bedrooms and bathrooms.

The 37 Grand Selectors arrive and are briefed on the rules:

Total communications blackout. Surrender your phone. No internet, no calls. Supervised video calls with family are allowed, but they’re monitored and cut off if they touch on anything related to the selection process. Medical care available on-site. Anyone who breaches security gets removed immediately.

The incumbent president, who chairs the proceedings, welcomes them. “You will be here for four weeks, and everyone you’ve ever met will be watching.”

The feeds go live at 6 AM Mountain Time. Within an hour, 30 million people are watching. By evening, it’s 65 million.

The first time Democratic Selection took place, r/TheRanch became one of the fastest-growing subreddits in history. Within 48 hours it has 8 million subscribers, with live threads during every session generating thousands of comments per minute. “Selector 19 reacting to Candidate 47’s budget plan” gets 15 million views in six hours.

The parasocial relationships are intense.

“I would die for Selector 12. She asked the most thoughtful question about healthcare I’ve ever heard.”

“Selector 8 is so quiet but when he speaks, EVERYONE listens. King behavior.”

“Did you see Selector 23 laugh at Selector 4’s joke? ROMANCE. I’m shipping it.”

Fan accounts appear. @Selector12Updates tweets play-by-play. Someone creates Selector Fantasy League — draft your favorites, score points based on whose questions get the most applause.

The betting markets go a little crazy. Predictit crashes twice in the first week trying to handle action on questions like “Which Selectors make the Final 25?” “Which candidates survive?” “Will there be a romance?” (Current odds: Yes, 3:1)

Week One at The Ranch: Selectors Select Themselves (37 → 25)

The 37 spend the first week getting to know each other. It’s awkward at first — a retired teacher from Maine, a software engineer from Seattle, a rancher from Wyoming, a social worker from Mississippi, a bartender from Brooklyn, a minister from Alabama.

They have nothing in common except random chance.

But they’re at The Ranch to do a job, so they talk, they deliberate, they argue. The cameras capture everything and America watches them become a community.

Selector 19, the quiet data analyst from Virginia, emerges as a natural leader — when she speaks, people listen. Selector 8, the rancher from Wyoming, provides folksy wisdom that cuts through bullshit. Selector 23, the Brooklyn bartender, is sharp and funny. Selector 4, the minister from Alabama, keeps everyone grounded.

And yes, there are tensions. Selector 31 talks too much. Selector 15 seems checked out. Selector 6 makes everything about themselves.

At the end of the week, they vote on each other using approval voting — who should stay?

You need a majority to advance. Twenty-five Selectors cross the threshold, twelve are eliminated.

The eliminations are broadcast live, with names appearing on a screen in the Main Hall. When Selector 6 doesn’t make it, there’s visible relief on some faces (caught on camera, becomes a meme). When Selector 15 is eliminated, they shrug — “I tried.” When Selector 31 is eliminated, they’re devastated.

The 12 eliminated Selectors pack their bags, say goodbyes, and leave. Exit interviews are conducted and broadcast after they’ve departed. Some are relieved, some are heartbroken.

The 25 who remain look at each other. Four weeks suddenly feels very long.

Chaos by Design

Just when the 25 think they understand the game, the system goes Venetian again.

Six Selectors are eliminated by pure chance — random lottery, live on camera.

The first name appears. Selector 12 — the one everyone loves, the thoughtful healthcare question asker — gets eliminated by random draw.

The reaction online is intense.

“THIS IS A CRIME AGAINST DEMOCRACY.”

“She was the best one and she’s ELIMINATED BY CHANCE?”

“This system is INSANE.”

But that’s the point. No one gets to imagine they’re there purely by merit. Chance humbles everyone. Being “the best one” is not the point.

When it’s over, 19 Selectors remain.

They’re shaken. They just watched six of their peers — some of them friends by now — get eliminated by lottery, and the reality sinks in: This could happen to any of us.

Selector 19, the natural leader, is still there. So is Selector 8, the rancher. So is Selector 23, the bartender. So is Selector 4, the minister.

But Selector 12 is gone. The internet mourns.

Meanwhile, on the other side of The Ranch...

The Candidates Self-Select

The 50 candidates arrive at The Ranch the same week the Selectors do. They’re kept in a separate wing with comfortable quarters but isolated from the Selectors.

They can see each other, though.

For one week, the 50 candidates meet, discuss, argue. The politicking is intense. Factions form. The senators cluster together. The outsiders band together. The former general tries to stay above the fray.

They vote to reduce themselves to 30 using approval voting, same as the Selectors.

The top 30 survive. It’s a brutal process — candidates who advanced through Round One, who survived the lottery, now get eliminated by their peers. But the 30 remaining candidates brace themselves because they know what’s coming: another lottery.

Eleven are eliminated by chance, nineteen candidates remain.

Among them: three senators, two governors, the former general, the climate scientist, the hardware store owner, the tribal leader, the tech CEO, a labor organizer, a neurosurgeon, a farmer, an economist, a teacher, a former diplomat, a civil rights lawyer, and a wildcard nobody saw coming — a 32-year-old mayor of a mid-sized city who wrote a platform so compelling that even the senators approved her.

These 19 have survived merit and chance. They’re energized.

And now they have to face the 19 Selectors.

The Reckoning

This is the heart of the system. Nineteen candidates, nineteen Selectors, one week of intensive deliberation.

Each day has a theme:

• Monday: Budget and Economy

• Tuesday: Foreign Policy

• Wednesday: Social Policy

• Thursday: Education and Science

• Friday: Defense and Security

The candidates make their cases, and it’s grueling.

The climate scientist presents a carbon removal plan so detailed that Selector 8, the rancher, admits, “I didn’t understand half of it, but I trust her.” The former general’s foreign policy vision is hawkish but coherent. The young mayor stumbles on defense but recovers. The hardware store owner’s infrastructure plan makes everyone nod.

But some candidates flame out. One senator dodges questions. A governor condescends. The tech CEO promises things that sound impossible.

The Selectors have figured out who among them is good at asking tough questions, and let them take the lead.

“Senator, you voted for the appropriations bill in 2028 but your platform opposes that spending. Explain.”

“Governor, your climate plan relies on technology that doesn’t exist. What’s your backup?”

“General, you talk about military strength, but what about diplomacy?”

The candidates can’t bullshit because the Selectors have done their homework.

America is glued to their screens. The livestream has 90 million concurrent viewers by Wednesday. r/TheRanch live threads crash Reddit servers twice. Podcasts recapping each day proliferate.

The memes are good.

“Selector 19 listening to Senator X’s budget proposal” (screenshot of pure skepticism)

“When the young mayor answered the foreign policy question and everyone went quiet because holy shit that was actually good.”

“Selector 23 (the bartender) calling out the tech CEO’s bullshit. Icon.”

At the end of the week, both groups vote.

The Selectors vote on the candidates: the top 10 advance, requires majority approval.

The candidates vote on the Selectors: the top 10 stay at The Ranch, same requirement.

The voting is broadcast live and the tension is real.

Ten candidates cross the approval threshold, nine are eliminated. Some gracious, some bitter. The climate scientist makes it. The young mayor makes it. The hardware store owner makes it. One senator makes it, two don’t. The tech CEO is gone.

Same for the Selectors. The 10 that remain watch their colleagues leave — tearful goodbyes, promises to stay in touch. Some of them have become genuine friends over two weeks.

The 10 remaining candidates watch from their wing. They’ve survived three rounds of filtering and two lotteries. They’re the real deal.

But the system isn’t done with them yet.

Churn by Design

Just when the 10 remaining Selectors think they know each other, just when coalitions have formed and friendships have deepened, the system pulls its final Venetian move.

Nine new Selectors are drawn by lottery from the original pool of 907.

They receive the summons. One is at work. One is on vacation. Another one is at a wedding. Within 24 hours, they’re on a plane to Utah.

They arrive at The Ranch, shell-shocked.

The existing 10 Selectors try to brief them, get them oriented, show them where the bathrooms are. But there’s awkwardness — the original 10 have been living together for two weeks, deliberating, bonding. The new ones are outsiders.

America watches the dynamic shift in real-time.

“The new Selectors are asking different questions. This changes everything.”

“Selector 34 (one of the new arrivals) just asked the hardware store owner about climate and he had NO answer. Where was that question two weeks ago?”

The betting markets scramble. All predictions are invalidated.

Online, people are losing it. “THE TWIST. THE ABSOLUTE MADNESS.”

The Final Deliberation

Nineteen Selectors. Ten candidates. One week.

The candidates do final presentations, in-person now, face-to-face with the Selectors in the Main Hall. No hiding behind video, no prepared remarks that can be edited.

It’s brutal.

The young mayor, who’s been impressing everyone, gets grilled on experience. “You’ve been mayor of a mid-sized city for just four years. Why should we trust you with the presidency?” She answers: “Because I’ve actually governed. Half these people have been in the Senate talking. I’ve been fixing potholes and balancing budgets.”

The climate scientist gets challenged on political feasibility. “Your plan is great on paper. How do you get it through Congress?” She stumbles, then recovers. “I’ll build coalitions. I’ll compromise where I can. But the science is non-negotiable.”

The hardware store owner surprises everyone with foreign policy knowledge. “I’ve been selling to contractors for 30 years. I understand supply chains, trade relationships, dependencies. The global economy isn’t that different from retail at scale.”

One of the new Selectors — Selector 34, a teacher from Colorado — asks questions that cut through noise and becomes a favorite overnight. Fan accounts appear. “Selector 34 for President.”

After one week, the 19 Selectors vote.

The top 7 candidates will advance.

The voting is broadcast live. Names appear on the screen in the Main Hall as they cross the threshold.

The climate scientist: 16 votes. Through.

The young mayor: 17 votes. Through.

The hardware store owner: 14 votes. Through.

By the time the seventh candidate crosses the majority threshold, three are eliminated. They came so far.

The Final Seven remain. All seven of them are fully qualified to lead the country. But sortition gets one more bite of this cherry.

One Last Lottery

Three of the remaining seven candidates are thrown out of the process at random.

The first name appears — one of the senators, a solid, qualified candidate, eliminated by chance.

The second name: The accountant, who’s been a dark horse favorite. Gone.

The third name: The civil rights lawyer. Eliminated. Half of America is furious: they loved him. The other half sighs with relief.

Four candidates remain:

• The climate scientist

• The young mayor

• The hardware store owner

• The former diplomat

These four survived merit, peer evaluation, supermajority voting, and multiple lotteries.

America has watched them for three weeks and we know them now. Their strengths, their weaknesses, their quirks. The climate scientist who gestures too much when she’s nervous. The young mayor who gets defensive when questioned about experience. The hardware store owner who tells dad jokes to break tension. The diplomat who speaks in measured, careful sentences.

They’re exhausted. But they’re also vetted. All four of them could be a fine president. None of them would’ve had a chance under the old system.

The People Vote

The very next day, voting begins.

There’s no campaign, no ads, no rallies, no polls. Because the candidates have been campaigning for weeks — to the Selectors, to each other, to the nation watching on TV.

The election uses ranked-choice voting. Voters are instructed to rank all four, or as many as you want. There’s no “lesser of two evils,” no strategic voting, just preference.

The 19 Selectors are released from The Ranch and return to families who’ve been watching them on TV for three weeks. The reunions are filmed (with permission). Selector 19 cries when she sees her kids. Selector 8 just hugs his wife for a long time. Selector 23 goes back to bartending and becomes the most famous bartender in America.

They vote like everyone else.

The same night, the results are in. The young mayor wins.

Thirty-two years old. Mayor of a mid-sized city. Survived six rounds of filtering, two lotteries, and ranked-choice voting by 140 million Americans.

She gives her acceptance speech from The Ranch, standing in the Main Hall where the Selectors deliberated.

“I didn’t get here alone,” she says. “Chance brought me here. The Selectors tested me. My fellow candidates pushed me. And you” — looking at the camera — “you chose me. I will not forget that.”

She’s inaugurated three months later to a single six-year term with extensive powers but no reelection.

At the end of her term, she’ll chair the next Presidential Selection process, then she’ll retire and design her Presidential Library.

The Culture of Democratic Selection

The Democratic Selection system is complicated, there’s no getting around that. It’s reality TV meets civic duty meets the most important decision a democracy can make.

But it works because it cannot be gamed. Randomness breaks every attempt to coordinate, to buy influence, to build dynasties. Dark money searches for leverage and finds none. You can be brilliant, charismatic, and rich — and still get eliminated by lottery. Humility is mandatory.

It also works because deliberation is real. The Selectors aren’t performing for constituents because they’re sequestered, filmed, accountable. They can’t be lobbied or threatened. They have time to think, to question, to evaluate, and they take it seriously because the nation is watching.

The spectacle creates engagement. Yes, people watch for the drama — the romance subplot between Selector 23 and Selector 19 (they got married two years later, by the way), the memes, the betting markets, the fantasy leagues.

But they’re also learning. They’re watching policy discussions, seeing candidates under pressure, getting invested in outcomes because they spent three weeks watching the process unfold.

Merit and chance get intertwined in a way that’s very Venetian. No candidate can fool themselves into thinking they won purely by genius. No Selector can imagine they chose purely by wisdom. Chance humbles everyone, but merit still matters — you have to survive peer evaluation, supermajority voting, expert questioning.

And the final choice is real. The general election isn’t “hold your nose and vote” — it’s ranked-choice among four vetted, tested, qualified candidates where you vote your conscience.

We lost the simplicity of traditional elections. We lost political dynasties (good riddance). We lost the professional political class’s stranglehold on power. We lost privacy for the Selectors — those 37, then 25, then 19 are watched constantly for three weeks.

We lost the illusion of control. You can register for the lottery, but chance decides. You can campaign, but lottery decides who evaluates you.

But we gained presidents who are vetted, tested, and humble. We gained a process that can’t be bought. We gained an engaged public that watches governance happen in real time.

We gained democracy as participatory spectator sport, which is weird but it works.

Venice Whispering Across Centuries

The Venetian Republic lasted 1,100 years — eleven centuries governing themselves through sortition and voting and supermajorities, through expansions and contractions, through a system so complex it seemed insane.

America’s 1787 constitution lasted 237 years before everything that happened, and then it broke.

The 2032 constitution isn’t elegant and it isn’t simple — it’s baroque, it’s complicated, it mixes chance with choice, randomness with deliberation, spectacle with substance. But it works.

When it was first mooted, back in the 2020s when Everything That Happened was just beginning to happen, the Venetian Option was dismissed as just too convoluted. By the 2030s, it had built a head of steam. Now, we couldn’t imagine America without it.

Every six years, tens of millions of Americans register for the lottery. Hundreds of candidates file. The nation gathers around screens to watch the drawing, the deliberations, the eliminations. Betting markets go wild. Fan accounts proliferate. Some random selector becomes a household name.

In the five years after the system was adopted, Colombia, Egypt and the Philippines adopted versions of Democratic Selection. Soon, it became the Go To institutional reform for countries where legacy Democracy seemed to be dying from the chaos it generated. When France, Germany and Italy adopted it, people began to talk about its spread throughout Europe as inevitable. Soon after Belarus became the first country to leap-frog legacy democracy, adopting Democratic Selection directly after the death of Lukashenko. Championing the system is now a central goal of American foreign policy.

The system cannot be gamed. No leader can fool themselves into thinking they earned the presidency on pure merit. Polarization can’t find a foothold when leaders are picked this way. By bringing chance and choice together, the system is armored against charismatic demagogues forever.

Venice lasted 1,100 years with this kind of madness.

Maybe we can too.

So far, it’s working.

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There is a specific kind of vertigo that comes from working in climate. It’s the feeling of staring at a mountain of data that is so vast, so contradictory, and so high-stakes that your brain tries to find an emergency exit. We crave a simple story to tell us where we’re going, but the story is splitting in three directions. Depending on who you talk to—and which data set they’re clutching—the trajectory we’re on is either pretty darn bad, not that bad, or truly horrible.

Pretty darn bad is the mainstream view. It’s the consensus among scientists who contribute to the Inter-governmental Panel on Climate Change. Pretty-darn-badders say that we’re on track to miss the Paris Agreement targets, reaching somewhere between 2.5 and 3.0 degrees of warming by 2100, which will mean the effective end of coral reefs as we know them, a doubling or even tripling of the frequency of extreme heat waves in many regions, and sea levels rising enough to threaten the homes of hundreds of millions of people in coastal cities. They note that this trajectory is nowhere near as bad as the 4 or even 5 degrees of warming that seemed plausible at the start of the century, and that for most of the people in the world this means challenging-but-survivable conditions. No bed of roses, but not armageddon, either.

But this mainstream view has challengers on both sides.

Some absolutely serious researchers argue our trajectory is really Not that bad. This view is advanced guys like Ted Nordhaus, Bjorn Lomborg, Roger Pielke Jr. and Chris Wright who find it pretty easy to poke holes in some of the more alarmist activist discourses out there.

Not-that-badders acknowledge climate change is real and that it is a problem, but they stress that actual climate harms have grown much less quickly than mainstream discourses suggest, because economic growth is extremely effective at enabling people and communities to adapt to a changing climate. Not-that-badders dwell on the 99% drop in annual deaths from climate-related disasters over the last century and the fact that we are currently spending a much smaller percentage of global GDP on weather-related damage than we used to. From this Ecomodernist point of view, climate change is well within the range of things human societies can and do protect themselves from effectively all the time. Late last year, the not-that-badders scored a major tactical victory when Bill Gates publicly joined their ranks.

Then there are critics who think our climate trajectory is Truly horrible. This is the smallest band, but it matters because its leading exponent, James Hansen, is among the world’s foremost climate scientists.

Truly-horriblers argue that standard climate models consistently underestimate the impact changing albedo has for temperature trajectories, which is why climate models can’t account for the acceleration in global warming we’ve seen these last few years. Sometimes called “climate accelerationists,” truly-horriblers point out that the loss of cloud condensation nuclei from maritime shipping pollution has led to unexpected spikes in sea-surface temperatures, and note that the massive acceleration in the Earth’s energy imbalance and the historical evidence that sea levels once rose several meters per century under similar conditions suggest we’re on track for a much more unstable climate than the mainstream expects. The credibility of the climate accelerationists suffer from association with some of the shrillest, most unhinged activist voices in the climate movement. Because they sound crazy, we tend to think they must be crazy. They’re not, though: they’ve got data to sling.

Hindsight is a trap

When you work in climate, people are constantly trying to pin you down to one of these groups. I find that frustrating, because all three make good points. All three are engaged in a good-faith effort to bring some clarity to an extraordinarily confusing mass of hard-to-interpret data. All three put forward views that are cogent and plausible.

I, for one, find myself shifting between their perspectives several times a day.

Come 2100, only one of these groups will have turned out to be right. In hindsight, the temptation will be to ascribe superior wisdom and insight to that group and condemn the other two as fools or knaves. Because Hindsight Bias is powerful. Once you know how a story turned out in the end, it seems obvious to you that that it ought to have been foreseeable from the start.

Hindsight Bias is a mirage, though. As of 2026, it’s genuinely impossible to say if the climate trajectory we’re on is pretty darn bad, not that bad, or truly horrible.

My guess is that the future will probably be weirder than any of these perspectives can capture. We may well live through a bizarre mash-up of all three. Maybe temperatures will shoot up as fast as the climate accelerationists are expecting, but we’ll turn out to be able to adapt to them relatively easily, as the ecomodernists expect.

Or maybe we’ll actually nail our emissions targets and keep warming to a ‘mainstream’ 2 degrees, but then we’ll find out global financial and political systems are way more brittle than we thought. Maybe a few mid-sized crop failures trigger a domino effect of state collapses and migration crises that look like a ‘truly horrible’ outcome despite ‘not that bad’ temperatures.

Alternatively, we could see a future where the planet warms significantly, but we ‘cheat’ the thermostat by figuring out how to manage solar radiation. We’d end up with a climate that is physically cool but ecologically and politically freaky, a world where the weather is ‘fine’ but ocean acidification is out of control, and where we’re one technical glitch (or a war) away from ‘termination shock’ and instant, catastrophic heating.

Getting bogged down on which of the three camps is ‘right’ misses the point.

The overwhelming reality we have to deal with is dominated by deep uncertainty: the fundamental unknowability of which trajectory we’re on, and the havoc that uncertainty plays with any attempt to nail down a reasonable policy response.

Faced with an amorphous threat we can’t necessarily nail down, can’t quantify exactly, consensus will remain elusive.

The mainstream, the ecomodernists and the accelerationists all make reasonable arguments on the basis of scientific data. The data is so vast and messy that you can use it to build almost any story you want. (This, to his credit, is something Pielke acknowledges often.)

For me, really getting into climate has been about appreciating just how deep the uncertainty goes, and how those uncertainties then go on to distort the climate debate.

Because we’re all human. We all come to this emotionally charged discussion with strong prior beliefs: ecological priors, economic priors, and also political priors. And those priors bleed through to our ideas of what a reasonable climate response might be. Of course they do!

We aren’t just looking at the data; we’re looking at it through the lens of who we are. If you’re a ‘market guy,’ you’re going to find Pielke’s adaptation data much more ‘reasonable’ than Hansen’s acceleration data. If you’re an anti-capitalist, the ‘truly horrible’ scenario feels like the vindication you’ve been waiting for all along. The temptation to think the storyline that jives with your identity must be right is massive.

Writing Charlatans, one thing that became very clear to me is that the tendency to interpret incomplete, confusing data in line with our priors is overwhelming. Social psychologists call it “motivated reasoning” — when we reason backwards, starting from the conclusion we want to reach to the arguments that will make it compatible with the data.

In the climate sphere, motivated reasoning is rampant. Because climate maxes out all the risk factors for motivated reasoning. We’re having complex debates about difficult-to-measure variables at unfamiliar scales all bearing directly on politically polarized questions. Hundreds of thousands of climate papers are published each year, yielding a mass of often contradictory information that you could use to sustain basically any conclusion.

Is it any wonder that when ideological conservatives make a good faith effort to try to evaluate this hugely confusing mass of material, they come to conclusions diametrically opposed to those ideological leftists reach?

Is there a better way?

For the last year, I’ve been puzzling through what a reasonable, defensible response to climate change looks like from a position that does not fall into the traps motivated reasoning sets for us.

How would we respond to climate change if we acknowledged, frankly, the uncertainties and the cognitive pitfalls that make this whole subject so tricky? How do you sidestep motivated reasoning and make decisions that make sense under deep uncertainty? And how do we do this in a world where climate money is drying up and where public appetite for costly responses is on the wane?

These aren’t easy questions.

A world where the mainstream and both its critics are all making reasonable points is a world that will tax our cognitive resources to their limits. It’s ok to be confused. It’s okay not to have the answers. Climate change is a challenge unlike any we’ve ever met before.

We need a place where we can acknowledge the vertigo. Where it’s okay to admit economic growth might be our best defense, even if you’re appalled at what we’ve done to the atmosphere. Where it’s safe to talk out what level of risk we’re really willing to bear if we decide the extra carbon belongs in the deep ocean, or that we’re better off sidestepping the entire mess by making the stratosphere more reflective.

I want One Percent Brighter to be a place where the camps are less fixed, less embattled, and less static. We shouldn’t have to decide if we’re in the ‘pretty darn bad,’ ‘not that bad,’ or ‘truly horrible’ camp just to have a seat at the table. This shit is complicated. And there’s no myth out there worse than the idea that it’s simple.

Flashback.

It’s December 6th, 2015. Just over ten years ago.

After a hard fought parliamentary election campaign, Venezuela’s opposition has won two-thirds of the seats in the National Assembly — enough, theoretically, to rewrite the constitution. It’s a massive win, and a huge blow against what is already a sharply authoritarian regime.

After these results are announced, I head out to report on the mood on the streets.

What I find is strange.

The streets are quiet.

Small groups of opposition die-hards gather in a few spots in the most anti-chavista bits of Caracas, my hometown. But there are no mass celebrations, no noisy horn-honking, no confetti, none of the outburst joy you’d have expected if people had really sensed the regime was done for.

Already back then Venezuelans knew better than to get too hopeful about a half-victory. They were happy to see an awful government humiliated, of course. But they were also weary. Because the same people were still in power. They still had the guns. They still ran the prisons. And the torture chambers. Nobody could quite bring themselves to believe something as prosaic an election would change all that.

It was no time to celebrate.

As it turned out, they were right. Over the months and years that followed, Maduro and his governing clique drained that win of all significance. They orchestrated far-fetched court decisions that drained the new National Assembly of all its power. Over the two years that followed, Venezuelans hit the streets in huge numbers to protest the powergrab. They were just met with more and more violence. As repression increased, people chose to abandon the country rather than to keep getting beaten, and jailed, and tortured.

Thinking back on that election night in 2015, it strikes me that the crowd was right. They weren’t celebrating, because there was nothing to celebrate. Not yet. They knew they were in a dictatorship just as much after that election as before.

That’s what kept running through my mind last night as I saw footage of Venezuelans celebrating in Madrid, in Miami, in Lima and in Mexico City…but not in Caracas. People back home understand that an important thing happened. A historic thing. A good thing. But they also know that on Sunday, Venezuela was just as much a dictatorship as it had been on Friday.

In the ways that matter most to people in Venezuela, nothing really changed. The guys with the guns are still the guys with the guns. The political prisoners are still locked up in their dank cells. Electronic communications are still being spied on just as actively as they were before. If anything, dissent is even more dangerous now than it was before Maduro was extracted. Because the regime feels more threatened, and if there’s one thing Venezuelans have learned in the last 10 years is that the more threatened the regime feels, the more viciously it gets.

Donald Trump, in his press conference, showed a shocking inability to understand any of this. He kept talking as though the removal of the president amounted to the collapse of the regime. That’s a fantasy that’s easy to sustain when you live in Washington, but far too dangerous to entertain if you’re in Caracas. Back home, people know very well that a single misjudged tweet can land them in a prison cell, or a torture chamber. That in a weird way, Venezuela is no freer now than it was on Friday.

All along, I’ve feared the Venezuelan job would be left half-done, leaving the country even more repressive than it was before: an all out police state. It’s obvious that Venezuelans’ well-being is precisely the last thing Donald Trump will consider when deciding next steps.

Chavismo without Chávez turned out to be far worse than with him. Chavismo without Maduro may be an even more brutal beast than it had been with him.

The streets were quiet in Caracas the day Maduro was taken away. There’s a message there we need to be tuned into. People aren’t celebrating. Because they can’t. They’re not free yet.

It’s been years since Venezuela faced any options that were not awful. That didn’t change this weekend. But in the menu of awful options ahead of us, leaving this chavista rump in charge of the country seems like the worst option.

Two mechanisms determine the planet’s temperature trajectory: the greenhouse effect and planetary albedo. We have a pretty good handle on the first, but the second remains a muddle, and a wildcard.

One very senior scientist in particular —Columbia University’s James E. Hansen— keeps warning us that mainstream science is getting albedo badly wrong. If he’s right, we’re in for a much bumpier climate ride than we realize.

Changes in albedo —the proportion of the sun’s energy that gets reflected back out into space, rather than absorbed by the earth— turn out to be tricky to model. The way clouds interact with aerosols, in particular, continues to stump scientists: it’s the biggest source of uncertainty in the IPCC’s estimates.

Hansen argues that some types of pollution make clouds much brighter, and albedo much stronger, with the unfortunate and paradoxical effect that cleaning it up accelerates global warming. If he’s right, we’re facing 4 or 5 degrees of warming, not 2 or 3. And that’s a much, much more unstable atmosphere.

It would be nice to be able to dismiss Hansen as some sort of crank, but he certainly isn’t that. Hansen is one of the world’s most highly regarded climate scientists. He’s the guy whose 1988 congressional testimony first brought concentrated attention to global warming as an issue of political significance.

Hansen’s views on climate sensitivity and cloud-aerosol interactions certainly are out of consensus, but that doesn’t mean they’re wrong. He expresses them with verve, in language accessible to everyone. You should read his latest note, it’s sobering.

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We’re so used to seeing the IPCC’s views questioned by skeptics that we’re weirdly ill-at-ease considering the alternative possibility: that the scientific mainstream is complacent about the risks we face. This leaves guys like Hansen in a peculiar predicament: criticizing the IPCC not for being alarmist, but for failing to sound the alarm loud enough.

Hansen argues that air pollution —mostly sulfur compounds from industry and especially from ocean-going shipping vessels— increased albedo by making clouds brighter. That boost to albedo masked some of the global warming we ought to have experienced due to rising greenhouse gas emissions. Rapid improvements in air quality over the last 20 years have withdrawn that veil, leading to accelerating warming.

It’s easy to see why this message has trouble breaking through to the public. Hansen is saying that air pollution, which is a bad thing, has some beneficial impacts, while policies against air pollution, which are a good thing, have some detrimental impacts.

We’ve been on the receiving end of decades of activism that paint pollution as everywhere and always bad, and cleaning up pollution as uncomplicatedly good. We’re now deeply committed to climate as a simple morality tale, where mother earth rewards virtuous behaviour with a clement climate, and punishes our transgressions with bad climate. That’s a comforting tale of an ethically ordered universe. Hansen’s warning upends all these neat correspondences. Of course that makes us squirm.

If James Hansen is right, we’re in big big trouble. Way bigger trouble than we realized. If James Hansen is right, the most serious climate impacts could start piling up within just a decade or two, not deep into the 22nd century as standard climate models suggest. If James Hansen is right, we need to get over our shit and understand we’ve been unwittingly managing solar radiation for half a century, and have only recently stopped doing it, leading to a kind of undiagnosed termination shock from the cessation of an unintended spell of geoengineering. If James Hansen is right, the case for dramatic interventions to curb the worst impacts of climate change is much stronger than we’d realized.

I, for one, am not qualified to opine on whether Hansen is right or wrong. He’s a serious enough, senior enough researcher that we should certainly act as though there’s a non-zero probability that he’s right. How far from zero? I don’t know. But I think p(hansen) should serve as a kind of climate counterpart to the popular p(doom) of the AI debate.

My p(hansen) right now is at about 20%: worse odds than you get playing Russian Roulette. If there really is a one-in-five chance we’re heading to a five degree hotter world, we should be doing much more than we are to address the eventuality. Because a five degree hotter world really would be a genuine calamity: it’s not just the rapidly rising sea levels and the prolonged and deadly heat waves, it’s that every climate tipping point in the book begins to look likely at five degrees, from AMOC collapse to a permafrost methane burst to rapid agroecological collapse across the tropical world. A nightmare.

A one-in-five chance that that’s the world we’re heading towards ought to chill you to the bone.

Unless your p(hansen) is at zero, you have to conclude our climate budgets are being disastrously misallocated. While we pour hundreds of billions of dollars into subsidies for solar cells and heat pumps, the basic science of Aerosol-Cloud Interactions continues to get nickel and dimed.

The International Maritime Organization continues to push to decarbonize bunker fuels, even though cloud condensation nuclei from shipping may be the thing that had been shielding us from disaster. And researchers looking into ways of restoring some of the albedo-enhancing effects of pollution in less destructive forms continue to be marginalized by a climate movement laser-focused on interventions that stopped making sense decades ago.

Unfortunately, no: I don’t know if James Hansen is right. But he might be right. And God help us if he is.

Climateworld is conflicted about China. On the one hand, the People’s Republic gets plaudits for its amazing achievement in renewables, especially solar. The wild growth in solar generation capacity in the last decade is a story of crushingly effective Chinese industrial policy: proof that when a big power really puts its mind to it, it can make stunning progress on green energy quickly.

The rub is that China’s solar renaissance happened at the same time as its greenhouse gas emissions exploded. Why? Because China went on a coal binge at the same time it spearheaded the renewables revolution.

The scale of China’s coal industry is staggering: around 1,000 coal power stations operating more than 3,200 generation units, with a nameplate capacity around 1.2 terawatts. China’s installed capacity from coal alone — 1.15 terawatts — is about the same size as the entire U.S. electrical system.

More than half of the coal consumed worldwide is now consumed in China, and they’re not slowing down. China is still building coal generation capacity at near-record rates. In 2024 alone, it started contruction on 94.5 gigawatts of coal plants, more than the total generation capacity of Vietnam or Poland. 2.5 million Chinese workers are directly employed in the coal industry, whole provinces depend on coal.

All of which helps explain why the undisputed world leader in renewable energy now emits more carbon dioxide than all the developed countries in the world put together. For that matter, China now emits more CO₂ than all the rest of the developing world combined, too:

China’s simultaneous embrace of the cleanest and dirtiest energy technologies looks like a contradiction, but only if you’re thinking ideologically. If you’re thinking like a grid planner, there is no contradiction. Because renewables work great…some of the time. If you’re in the business of planning a grid, the obvious question is what you’re going to do the rest of the time.

When Chinese grid planners looked at their geopolitical reality, it didn’t take them long to come to an answer. China doesn’t have much oil, but it has an almost limitless supply of coal. For a country that prizes energy independence for geopolitical reasons, depending on imported fuel sources was a non-starter. Building out solar-and-wind required building out coal at the same time.

The better question is why it feels to us as though China’s parallel solar-and-coal build out is contradictory.

The answer, I think, is that Western campaigners have spent decades constructing a narrative of renewables as a substitute for fossil fuels. They’ve been very successful. We’re so used to hearing solar and wind described as replacements for coal and oil that we don’t entertain the possibility the framing is nonsense.

In China, though, none of this is theory. They know solar and wind won’t work in the absence of coal and oil.

In the discourse, batteries are meant to step in to quell the cognitive dissonance this all provokes. It is true that battery prices have come down quickly over the last few decades. It’s now just about imaginable to install enough to cover your evening peak demand with your extra afternoon-solar generation. But these four-hour storage options are expensive, and costs soon become prohibitive if you need to cover eight or 12-hours worth of power.

Renewables boosters tend to talk as though continued falls in battery-storage prices are an immutable law of nature, a Moore’s Law-type regularity you can bank on. In the real world, lithium-ion batteries appear to be closing in on their fundamental physical limits: continued price reductions are in no way assured.

Which suggests China really is the future: the more we invest in weather-dependent renewables, the more we end up depending on fossil fuels. As renewable-penetration begins to climb beyond critical thresholds —the number depends a lot on your grid design and your geography, but it’s somewhere between 15% and 50%— the marginal cost of renewable generation becomes prohibitive.

The implication feels weird to us because our discourse is so divorced from the realities of running a real grid. To Chinese Communist Party planners, there’s no real mystery: the more wind and solar you install, the more coal you need to burn to keep the lights on when the sun doesn’t shine and the wind doesn’t blow.

There is, of course, an alternative to this paradigm: a zero-carbon energy source that works day and night, takes up almost no land, and at scale can be as cheap as coal.

If you want a carbon-free grid, its backbone will be nuclear.

The 1.5 degree target is dead. The focal point of target activism for much of the last decade died of anthropogenic causes this year, as global temperatures merrily zipped past what was meant to be an ultimate speed limit. Due to the convoluted way the UN keeps tracks of these things, the official death certificate won’t be issued for some time yet. But make no mistake about it: 1.5 has ceased to be, it’s kicked the bucket, shuffled off its mortal coil and joined the bleedin’ choir invisible.

It is an ex-target.

In stages-of-grief terms, most of climateworld is still in denial, but UN Secretary General Antonio Guterres has moved on to bargaining. In a recent speech to the UN Environment Program, he argued 1.5 is not dead, it’s resting: “scientists tell us that a temporary overshoot above 1.5 degrees is now inevitable…but this is no reason to surrender. It’s a reason to step up and speed up.”

Obviously, messaging around this is awkward. Any number of countries, states, municipalities and corporate boards publicly wedded themselves to the 1.5 goal over the last ten years, and walking away from all that was always bound to be tricky. Nobody wants to be stuck behind the podium announcing that the thing you ballyhooed as necessary just a few years ago is now impossible.

But if 1.5 degrees is an ex-target, what are we to replace it with?

Well, what do we want a target to do, anyway?

To my mind, the point of a target is to concentrate attention on the specific thing that will make the most difference. Targets exist to guide decisions. The point is to align climate action with the climate outcomes we want.

And the smart way to do that is to focus on costs.

Dollars and cents.

The one question that will make the biggest difference to our climate trajectory over the next seventy-five years is brutally simple: How much does it cost to take one ton of carbon dioxide out of the atmosphere?

Currently, we add about 40 billion tons of carbon dioxide to the atmosphere every year. Natural carbon sinks remove about 18 billion of those from the air. That leaves 22 billion tons of additional airborne carbon dioxide in the air each year.

When you get past the romantic nonsense, the real question is: how much are we willing to pay to bring that number down to zero?

Because there are thousands of ways of preventing emissions in the first place, and hundreds of ways of removing greenhouse gases from the air once they’re emitted.

But resources are limited.

Anytime you devote resources to less efficient ways of abating carbon dioxide, you’re leaving carbon dioxide in the air needlessly. If we were really focused on the climate first, we’d be much more cost conscious.

The $100/ton solutions often talked about as an aspirational target are still an order of magnitude too expensive to get us where we need to be. At $100 per ton, getting to net zero costs $2.2 trillion — more than twice the U.S. defense budget.

That’s a non-sense number: still an order of magnitude too high.

Instead, we should aim for a $10 ton of carbon dioxide removed from the atmosphere for at least a 100-years.

If we could do that, our climate problem would be pretty close to solved.

A $10/100-year ton would make net zero a $220 billion/year proposition. That sounds like a lot, but it really isn’t. We’re already spending five times that much on climate — more than a trillion dollars a year.

Of course, a $10/100-year ton feels out of reach. But that’s because carbon dioxide removal research has concentrated on approaches where costs are high and have no realistic prospect of falling.

The field is bifurcated between engineered approaches (i.e., big crazy machines) that cost $1,000+ a ton, or tree-planting projects that come in at $20-50 a ton, but only keep carbon out of the atmosphere for 20-40 years, and also compete for land with farmers.

In the middle you get a family of mineral-based techniques —enhanced rock weathering, ocean alkalinity enhancement— that are longer-lasting but more costly, coming in at around $50-$320 a ton.

That just means the tech we have is not up to the job.

Yet.

The usual objection to focusing on low-cost long-duration carbon dioxide removal invokes moral hazard. “If you create a get out of jail free card” people say “polluters are just going to keep polluting!”

This objection has it backwards. Our goal is not to punish people for insufficient green virtue; our goal is to bring down the concentration of atmospheric greenhouse gases. Developing high quality, low cost carbon removal technologies brings us much closer to that goal.

Take heavy-trucking, to take just one out of dozens of possible examples.

Electrifying big trucks requires big batteries, so decarbonizing heavy trucking is expensive. One study by Catalyst Climate suggests over the lifetime of a heavy truck, electrifying road haulage would stop a ton of carbon dioxide from being emitted at a cost of $50 per ton saved.

Say your decarbonization budget is $50. With that much money, you could take five times more carbon dioxide out of the atmosphere if you had a $10/100 year ton than by buying that fancy electric truck.

Imagine a world where we do have a $10/100 year ton of carbon removal. In that world, insisting on high-cost emissions reductions over low-cost carbon removals would mean up leaving a bunch of CO₂ in the atmosphere. Needlessly.

“Well, Quico would say that,” you’re thinking, “his job is all about developing low-cost 100-year CDR.” But that’s backwards too: I decided to work in this space because it’s the most important thing to do, not the other way around!

Today, the only family of approaches with a fighting chance to get to a $10/hundred-year ton rely on photosynthesis in the ocean. If we’re ever going to get the tech right, this is how we’re going to do it.

Some researchers think the way forward is macroalgae — kelp or sargassum are the ones most often mentioned. The people I work with tend to focus more on microalgae — the invisible kind of microscopic seaweed scientists call phytoplankton. Some researchers think phytoplankton carbon would work better in cold waters — the biggest research group in the field is targeting the Gulf of Alaska. The approach I’ve focused more on would happen in warmer waters in the Pacific. Who knows who’ll turn out to have been right?

The only way to find out who’s right is to try all these approaches in parallel: the kelp, the sargassum, the cold water phytoplankton, the warm water phytoplankton, all of it. If anything is going to yield a $10/100-year ton, it’s going to be in this space.

All hung up on the unburied corpse of the 1.5 degree target, Climateworld still hasn’t caught on that a $10/100-year ton of carbon removal is a live possibility.

When it does, the climate conversation is going to change. A lot.

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Some of y’all got miffed that my post panning Bill McKibben’s book was “anti-solar.”

It wasn’t. At least, I didn’t mean it to be.

Solar energy’s frikkin’ cool! You point a pane of glass (+fancy electronics) up at the sky and get electricity out of the deal! It’s as close to magic as energy technologies come.

The basic awesomeness of solar photovoltaics isn’t in question. The engineering advances that have made those magic glass panes now very cheap to manufacture are also real, and are also awesome.

That this amazing technology has limitations is also fully normal. It’s not the magic glass pane’s fault that the sun sets, it’s not a diss on the technology to note that its output varies a lot according to the weather, the season, the latitude, etc. That’s just physics. It’s not the solar array’s fault that people tend to demand more power in the evening than at noon. That’s just modern life.

My problem isn’t with solar technology at all. My problem is with the magical thinking about solar that’s run away with the climate movement’s brain. My problem is with the wild, irresponsible overselling of solar by people who’ve let confirmation bias run away with their critical faculties.

Guys like Bill McKibben seem unable to process the way overselling solar risks bringing it into disrepute. It’s their determination to sweep the problems of intermittency under the rug that’s pushing solar deployment into the danger zone.

Ignore the problems the grid faces when you try to ask solar more than it can do, and you end up with things like the Iberian blackout: mass disruption, serious economic losses and a reputational disaster brought about not really by solar but by the irresponsible decision to rely on it too much, without adequate safeguards.

“Sooner or later a false belief bumps up against solid reality,” Orwell told us, and he didn’t have it wrong. False beliefs about how much of our electricity intermittent solar energy can supply causes supply instability and price instability. The hype has real, tangible consequences: rising prices, deindustrialization, and ultimately political backlash.

None of that is the fault of the magic glass panes that make electricity for free. They’re the fault of the rigid ideologists who insist on believing those magic glass panes can supply more of our electricity than fundamental physics suggests they can supply.

The bigger risk to solar deployment now isn’t that fossil fuel interests block them — there’s no blocking a cheaper, higher performing competitor, at least not for long. The bigger risk is that guys like Bill McKibben convince policy-makers that solar can do things it can’t do, that we overbuild, end up with more expensive, worse power grids, and turn a whole generation of voters against the technology in the first place.

So let’s get it straight. I’m not anti-solar. Bill McKibben is.

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