Abstract

Rivers and streams are an important pathway in the global carbon cycle, releasing carbon dioxide (CO₂) and methane (CH₄) from their water surfaces to the atmosphere^1,2. Until now, CO₂ and CH₄ emitted from rivers were thought to be predominantly derived from recent (sub-decadal) biomass production and, thus, part of ecosystem respiration^3,4,5,6. Here we combine new and published measurements to create a global database of the radiocarbon content of river dissolved inorganic carbon (DIC), CO₂ and CH₄. Isotopic mass balance of our database suggests that 59 ± 17% of global river CO₂ emissions are derived from old carbon (millennial or older), the release of which is linked to river catchment lithology and biome. This previously unrecognized release of old, pre-industrial-aged carbon to the atmosphere from long-term soil, sediment and geologic carbon stores through lateral hydrological routing equates to 1.2 ± 0.3 Pg C year⁻¹, similar in magnitude to terrestrial net ecosystem exchange. A consequence of this flux is a greater than expected net loss of carbon from aged organic matter stores on land. This requires a reassessment of the fate of anthropogenic carbon in terrestrial systems and in global carbon cycle budgets and models.

The recent Nature study titled “Old carbon routed from land to the atmosphere by global river systems” is not only a rigorous piece of scientific work—it’s also a spectacular indictment of the so-called “settled science” of climate change. This 2025 paper is a flaming arrow into the heart of carbon cycle certainty, unearthing yet another inconvenient truth: over half of the CO2 emitted from rivers comes from carbon sources that are hundreds to thousands of years old—not from recent fossil fuel emissions or current biological activity.

Let that sink in. Climate models and carbon budgets, paraded as settled science by every bureaucrat, green politician, and eco-apocalyptic influencer on Earth, have been built on the foundational assumption that riverine CO2 is part of a contemporary, short-term biosphere loop. Turns out, they’ve been routing old ghosts through a new story.

According to the authors:

“The largest proportion (52 ± 16%) of river CO2 emissions is sourced from millennial-aged carbon…” and “7 ± 1%…from petrogenic carbon” .

That’s right. Over half of these emissions are from old carbon stores—carbon that, until now, was presumed stable, buried, and irrelevant to modern emission tallies. In other words, nature has its own deeply entrenched carbon leaks, and our modern instruments are just now getting around to noticing them.

The implications are vast and devastating—to the credibility of those who have weaponized science to promote radical climate policy. Here are a few of the most laughable consequences of this study for the “settled science” narrative:

1. The Carbon Budget Is a Fantasy

The entire idea of a “carbon budget” depends on the assumption that we can accurately track all natural and anthropogenic carbon sources and sinks. The paper’s authors explicitly state:

“This previously unrecognized release…equates to 1.2 ± 0.3 Pg C yr⁻¹, similar in magnitude to terrestrial net ecosystem exchange”.

Translation: We were missing a carbon leak as big as the net carbon uptake of all land-based ecosystems. That’s like losing a financial ledger entry equivalent to your annual revenue and still claiming your books balance.

2. Climate Models Can’t Model What They Didn’t Know Existed

This isn’t a rounding error. This is a previously invisible carbon flux at a planetary scale—entirely omitted from mainstream Earth system models. The authors even note:

“Current numerical models of river carbon transport and emission also fail to account for inputs from old carbon sources”.

For those of us who have long argued that climate models are glorified curve-fitting exercises based on selectively tuned assumptions, this study is pure vindication. It’s an outright admission that the models are not merely imperfect—they’re structurally blind to major natural processes.

3. Climate Science Is Still in Diapers

If 59% of riverine CO2 emissions come from millennial or older carbon pools, then just how settled can the science be? The authors describe this as a “planetary-scale release” of old carbon and conclude:

“We provide evidence for a previously unrecognized, planetary-scale release of old, pre-industrial-aged carbon from land to the atmosphere through rivers”.

Imagine building a trillion-dollar global policy framework on a dataset that left out half the equation. It would be funny if it weren’t tragic.

4. Anthropogenic Carbon Attribution Is Now a Shell Game

One of the central talking points of climate activists is that CO2 in the atmosphere is traceable and largely caused by human emissions. This study kicks that stool out from under them. After adjusting the models to include this new understanding, the study finds that only:

“41 ± 16% of river CO2 emissions…could contain recent anthropogenic-derived carbon”.

That means nearly 60% of river-based CO2 emissions are from carbon predating modern industrial activity. This calls into question the accuracy of anthropogenic attribution models—models which governments use to justify taxes, regulations, and top-down restructurings of energy and agriculture.

5. So Much for Predicting the Future

The authors admit they don’t know whether the increase in old carbon emissions is from natural variability or anthropogenic disturbance. In their own words:

“Whether or not anthropogenic perturbation has increased the leak of old carbon…remains a notable knowledge gap”.

Yet we’re told with absolute certainty that the Earth will warm by 1.5°C unless we ban gas stoves, eat bugs, and shut down reliable energy. This study exposes just how deeply uncertain and unresolved the feedbacks in the carbon cycle remain.

6. Rivers: Nature’s Carbon Cheaters

The new conceptual model developed in this paper (see Fig. 3b on page 13) is a quiet revolution. It admits that the traditional model of river emissions—where CO2 was thought to be recent and local—is deeply flawed. Instead, rivers act as carbon transport systems, redistributing ancient carbon from soils, rocks, and geologic layers into the atmosphere. That’s not just a different magnitude—it’s an entirely different mechanism.

7. Policy Has Left Science Behind

The study’s authors call for a reexamination of the terrestrial carbon sink and the role of rivers, noting:

“This fundamentally changes our inference of where anthropogenic carbon resides within the main Earth system carbon reservoirs”.

But don’t expect the IPCC, Net Zero campaigners, or ESG investors to acknowledge this. Their policy steamrollers are already in motion, powered by inertia and political leverage rather than scientific humility.

---

This study is a torpedo below the waterline of climate orthodoxy. It makes it painfully clear that we don’t understand the Earth’s carbon system nearly well enough to justify radical economic and societal upheaval. The confidence of climate alarmists—built on the brittle scaffolding of incomplete data and overconfident models—has once again been exposed for what it is: performative certainty.

To call climate science “settled” in the wake of this paper is not just intellectually lazy—it’s laughable. It’s the scientific equivalent of declaring victory halfway through a chess match while ignoring that your queen is missing and half your pawns are spies. The river CO2 study is not a minor correction. It’s a flashing red light that we’re still flying blind.

So the next time someone tells you the science is settled, ask them if they’ve heard of F¹⁴C. Then sit back and enjoy the silence.

From THE DAILY CALLER

Steve Milloy
Contributor

President Trump took two major steps this week to end the 14-year-old Democrat war against the coal industry and cheap electricity. Although greens have promised to sue, they are unlikely to succeed as the moves have pretty much been pre-approved by the Supreme Court.

First, EPA proposed to roll back all greenhouse gas emission standards for coal plants. The Obama EPA first issued climate emissions standards for coal plants in August 2015. These rules didn’t last long as they were stayed by the Supreme Court in February 2016.

Although President Trump proceeded to replace the Clean Power Plan with the much less expensive and more practical Affordable Clean Energy rule in June 2019, that effort was rejected by the Court of Appeals for the DC Circuit in January 2021. But that turned out to be a Pyrrhic victory for climate activists. (RELATED: STEVE MILLOY: Big Beautiful Bill Won’t Raise Electricity Prices)

In June 2022, the Supreme Court invalidated the Clean Power Plan in West Virginia v. EPA on the basis of a first-time used constitutional theory called the major questions doctrine. Under that doctrine, unless a regulatory agency can point to express authorization from Congress for a major regulatory program, the program is unconstitutional and cannot be implemented. The Clean Power Plan had no such authorization.

But the never-admit-defeat Biden EPA went back to the drawing board and issued a new rule that can essentially be thought of as a Clean Power Plan 2.0. It is this rule that the Trump EPA is now rolling back.

When the greens sue the Trump EPA, the agency will be able to point to West Virginia v. EPA and say that neither the Biden EPA nor the Trump EPA have been expressly authorized by Congress to regulate emissions from coal plants. This should be a winning argument.

The second rule to be rolled back is something called the Mercury Air Toxics Standard (MATS). As far as the war on coal is concerned, this is actually a much more important EPA rule as it was the one the Obama EPA used to wreck 50 percent of the US coal industry. Issued in 2012, the MATS rule was aimed at reducing mercury emissions from coal plants, something that sounded scarier than it really was.

When EPA did the benefit-cost analysis for the MATS rule, it could only come up with hypothetical benefits worth $6 million dollars, while the actual compliance costs were estimated to be on the order of $10 billion. In the 2015 SCOTUS ruling that rejected EPA’s benefit-cost analysis as unreasonable, Justice Antonin Scalia wrote, “One would not say that it is even rational, never mind ‘appropriate,’ to impose billions of dollars in economic costs in return for a few dollars in health or environmental benefits.”

Similarly to regulatory ping-pong of the Clean Power Plan, the first Trump EPA took action to defang MATS. The Biden EPA responded by defying SCOTUS and making the rule more stringent. Now the ball is back in the Trump EPA’s court and MATS is once again headed to the ashbin of regulatory history, hopefully for good. The rule’s economics have only gotten worse for its advocates and a challenge to the Trump EPA’s new action is unlikely to succeed.

While the good news is that these Trump EPA actions should finally put an end to the war on coal, the bad news is that severe damage to the industry and the cheap electricity it provided was done long ago.

The 2012 MATS rule was so draconian that utilities hurried to close coal plants and switch to gas plants. By the time SCOTUS got around to ruling against MATS in 2015, it was too late for the half of the coal industry that had been destroyed.  Obama EPA chief Gina McCarthy mocked the tardiness of SCOTUS, responding, to the Court’s decision as follows: “The majority of power plants have already decided and invested in a path to achieving compliance with those mercury and air toxic standards.” Even the West Virginia v. EPA decision came seven years after the Clean Power Plan was first issued.

Democrats wielded the government to illegally wreck the coal industry and to pointlessly raise electricity prices. The damage done is immense and will take the government-sized help to repair it. President Trump is taking the necessary steps to revive the coal industry, but there is a very long way to go.

Steve Milloy is a biostatistician and lawyer, publishes JunkScience.com and is on X @JunkScience.

The views and opinions expressed in this commentary are those of the author and do not reflect the official position of the Daily Caller News Foundation.

All content created by the Daily Caller News Foundation, an independent and nonpartisan newswire service, is available without charge to any legitimate news publisher that can provide a large audience. All republished articles must include our logo, our reporter’s byline and their DCNF affiliation. For any questions about our guidelines or partnering with us, please contact licensing@dailycallernewsfoundation.org.

In the summer of 1969, a young astrophysics graduate, J. Richard Gott III, was touring Europe and found himself gazing upon the Berlin Wall. Pondering just how long it would take before it would finally be pulled down, he turned to his touring companion and confidently proclaimed that it would last at least two and two thirds more years but no more than 24. In 1987, President Reagan said ‘Mr Gorbachev, tear down this wall!’, and within five years the wall was gone. That’s within 23 years of Gott making his 24 year prediction.

So was Gott a crack political analyst, or did he possess a crystal ball? Neither, in fact. He was simply employing a principle he had learned at college, i.e. that we have no reason to presuppose that we occupy a special place in the universe. This principle, known as the Copernican principle, can be applied in both space and time, and is not restricted to cosmological questions. Gott just reasoned that he shouldn’t assume he was living in any special epoch as far as the Berlin Wall was concerned. That is to say, he wasn’t likely to be living during the very early life of a long surviving edifice, nor at the very end of a shorter-lived one. The likelihood instead was that the wall’s future would be as long as its past (to be precise, the probabilities would take the form of a normal distribution centred upon Gott’s Copernican judgement).

In 1993 Gott submitted a paper to Nature describing his reasoning (which he referred to as the ‘delta t argument’) and, much to everyone’s horror, Nature accepted it. Experts of all persuasions dismissed it as facile numerology, unworthy of a prestigious magazine’s attention. The problem, however, is that the technique works, and has been successful in predicting everything from Broadway show runs to the future value of stock market investments. Indeed, the idea has been independently developed by others in a number of forms (all of them essentially variations on Bayesian reasoning). The techniques now go by the name Doomsday Argument, principally because they are used to predict how much longer we can expect the human race to survive.

The answer isn’t reassuring, particularly if you take into account that it isn’t the chronological time on Earth that should be used as the basis for the calculation, but the number of man-years that have been lived to date compared to how many remain before mankind’s demise. Given that the vast majority of humans that have lived since Neolithic times are still alive today, and given the projected birth rate, delta t reasoning, based upon man-years past and future, gives as few as 12 years to as many as 18,000 years remaining to us (at 95% confidence).

Granted, there is massive uncertainty. Even so, it is quite sobering to appreciate that sound statistical reasoning, teamed up with the Copernican principle, suggests that there is a one in twenty chance that the human race has only got another 12 years ahead of it. And keep in mind that none of this analysis is in any way informed by the specific threats facing mankind, such as nuclear conflict, dwindling resources or even climate change. It’s just an example of how to determine a species’ expected survival span using basic Bayesian statistics, liberally sprinkled with the principle of indifference.

Ah yes, I hear you say, but we are not just any old species, we are the human race, famed for its resourcefulness and durability. We will find a way, because we always do. There will always be a technological revolution around the corner that kicks the Copernican principle into the long grass.

Oh really?

Wait, I have a cunning plan

Well let’s put that argument to the test by examining the greatest technological revolution the human race is likely ever to experience, one that is not just around the corner but already very much upon us: the proliferation of Artificial Intelligence (AI). And, in deference to my readership’s primary interest, let us consider the role it may play in weaning mankind off fossil fuels — because you don’t have to believe in a mad rush to net zero to understand that we cannot rely upon them forever.

Depending upon who you talk to, the AI revolution is either going to be the best thing that has ever happened to the human race or the last thing. Either way, the only thing one can say for certain is that it is going to be massively transformative and utterly inevitable. Nation states see falling behind in AI as an existential threat; trillions upon trillions of dollars are being invested; AI is seen as vital in solving the challenges currently facing mankind; and its development is being driven by a scientific and technological community devoted to its development, if only because of the personal and corporate glory to be had. These are all reason enough to believe that AI isn’t going to fizzle out and it isn’t going to be tamed. You only have to look at the exponential rate of development recently experienced, and then factor in the self-reinforcement that autonomous, self-designing, general AI promises, and one has to concede that the human race’s AI future is not only inevitable, it is also inherently unpredictable. But I’m not here to talk about robot wars and singularities; let us just reflect upon the risks and benefits facing those who would wish to apply AI in solving the fossil fuel problem.

Not such lovely jubbly

If you want a quick summary of AI’s potential role, you only have to google how AI can be put to use in tackling climate change and an AI summary will pop up for you. So we have:

• Analysing vast amounts of data from energy systems to optimize generation, distribution, and consumption whilst helping to integrate renewable energy sources like solar and wind power more seamlessly into the grid.
• Providing more accurate weather forecasts to assist disaster preparedness and climate change adaptation.
• Detecting and monitoring greenhouse gas emissions, enabling faster response and mitigation, and tracking and analysing emissions across various sectors.
• Optimizing agricultural practices, helping farmers adapt to changing climate conditions and improve crop yields.
• Accelerating the development of carbon capture and storage solutions.
• Accelerating the development of new materials for renewable energy technologies, such as more efficient solar panels, battery storage solutions, etc.
• Developing new turbine designs that optimize energy generation across a range of wind speeds.
• Improving climate modelling leading to more reliable predictions.
• Looking into ways in which AI technology’s own carbon footprint can be minimised using modified algorithms and developing new and more efficient computer technologies.

This all sounds great, but it has to be kept in mind that none of the above is a silver bullet, and taken as a whole it still isn’t nearly enough. The challenge is far greater than the above list would seem to suggest, and it is not at all clear that AI is up to the job. As Mustafa Suleyman, CEO of Microsoft AI, explains:

Despite well-justified talk of clean energy transition, the distance still to travel is vast. Hydrocarbons’ energy density is incredibly hard to replicate for tasks like powering aeroplanes and containerships. While clean electricity generation is expanding fast, electricity accounts for only about 25 percent of global energy output. The other 75 percent is much trickier to transition. Since the start of the twenty-first century global energy use is up 45 percent, but the share coming from fossil fuels only fell from 87 to 84 percent – meaning fossil fuel use is greatly up despite all the moves into clean electricity as a power source.

Vaclav Smil, Distinguished Professor Emeritus in the Faculty of Environment at the University of Manitoba in Winnipeg, calls ammonia, cement, plastics and steel the four pillars of civilisation, and it is highly germane to point out that their production is extremely carbon-intensive and that each has no obvious successor. As Suleyman says:

Without these materials modern life stops, and without fossil fuels the materials stop.

And the problems keep stacking up. Electric vehicles may not emit carbon dioxide when being driven, but their production is hugely resource hungry, including a great many unsustainable materials. And it’s all very well to talk of the development of public transport and getting everyone to cycle to work, but how is that going to work for the remote rural communities?  More to the point, how on earth is AI going to solve what is ultimately a social problem? As Suleyman puts it:

To meet this global challenge, we will have to re-engineer our agricultural, manufacturing, transport, and energy systems from the ground up with new technologies that are carbon neutral or probably even carbon negative. These are not inconsiderable tasks. In practice it means rebuilding the entire infrastructure of modern society while hopefully offering quality-of-life improvements to billions.

But even that will not be enough. He concludes with the following words of warning:

A school of naïve techno-solutionism sees technology as the answer to all of the world’s problems. Alone, it’s not. How it is created, used, owned and managed all make a difference. No one should pretend that technology is a near magical answer to something as multifaceted and immense as climate change. But the idea that we can meet the century’s defining challenges without new technologies is completely fanciful.

All of this is before we start to count up the ways in which AI and the required technology revolution may destabilize society. Suleyman speaks of “hopefully offering quality-of-life improvements to billions” and yet a society in which human intelligence has become increasingly redundant doesn’t sound like utopia to many people. An AI that is up to the job of solving the transition to a carbon neutral society would be easily up to the job of facilitating our self-destruction through a myriad of ways. The bottom line is that even if AI can ultimately wean us off fossil fuels, let alone tackle climate change, it may only be AI that is around to ‘enjoy’ the benefits.

Doh!

So where does that leave us? Seemingly between a rock and a hard place. The Doomsday Argument hints at a bleak future based upon simple (some would say simplistic) logic. Fossil fuel depletion and climate change may not be the immediate existential threat that Greta thinks they are, but they are still challenges that may very well determine how the doomsday statistics pan out. That said, the same could be said of AI itself, particularly in the employment of a pointless and self-destructive rush to net zero.

The problem is that we can’t expect our technological ingenuity to bail us out, even if superintelligent AI steps up to the plate. Indeed, by the time AI has helped wean us off fossil fuels, it will probably be so all-invasive as to pose a threat to society in its own right – and I’m not just talking here about power-hungry data centres. So if you believe that net zero is essential by 2050, then consider yourself doomed. On the other hand, if you think we have a lot longer, and AI will ultimately bail us out, then you must also consider yourself doomed. In fact, with or without climate change, and with or without a complete depletion of fossil fuels, you should consider yourself doomed. Doomed, I tell you, doomed.

Further Reading:

For an account of the inevitability, benefits and risks of the coming AI revolution: ‘The Coming Wave: AI, Power and Our Future’, Mustafa Suleyman and Michael Bhaskar, ISBN 978-1-52992-383-4.

For an account of the history and employment of Doomsday Arguments: ‘How to Predict Everything: The Formula Transforming What we Know About Life and the Universe’, William Poundstone, ISBN 978-1-78607-756-1.

See also the Lindy Effect.