New Simulation Framework Reveals How Earth Fights Back Against Carbon Removal

Carbon dioxide removal has quietly become the linchpin of nearly every credible pathway to the Paris Agreement’s temperature goals. Delayed mitigation means that simply cutting emissions is no longer enough: the world must also pull carbon back out of the atmosphere at gigatonne scale to compensate for residual emissions that are too costly or technically impossible to eliminate. Yet a deceptively simple question has remained stubbornly hard to answer with precision: when we deploy a carbon removal technology, how much CO2 does it actually take out of the air, once the Earth system’s own reactions are accounted for? A new study published in the journal Earth System Dynamics by Jörg Schwinger of NORCE Climate and Environment in Bergen and an international team of co-authors now offers the most rigorous answer yet to that question, laying out a complete simulation framework that connects the economics of future societies to the biogeochemistry of the entire planet.

The core of the problem lies in a mismatch between two very different modeling worlds. Integrated assessment models, or IAMs, simulate the global economy, energy systems, agriculture, and land use, and they decide where and when carbon removal technologies should be deployed based on costs, resource demands, and policy assumptions. Earth system models, or ESMs, simulate the physics, chemistry, and biology of the atmosphere, ocean, and land surface in fully coupled detail. In the current state-of-the-art setup, used for the fifth and sixth phases of the Coupled Model Intercomparison Project and planned again for the seventh, the IAM simply hands the ESM a net emissions number in which the carbon removed by technologies like bioenergy with carbon capture and storage is folded in as a prescribed negative flux. The Earth system model never sees the bioenergy crops growing, never simulates the forests being planted, and never computes the ocean chemistry changes caused by dumping alkaline material into the sea. Everything the model does in response to that removal is therefore invisible.

Schwinger and colleagues argue that this prescribed approach must give way to what they call activity-driven simulation of carbon dioxide removal. Instead of prescribing a negative emission, the ESM explicitly represents the activity that draws down atmospheric CO2. For bioenergy with carbon capture and storage, that means growing the crops inside the model, harvesting the biomass, and routing a scenario-dependent fraction of the harvested carbon into geological storage. For ocean alkalinity enhancement, it means adding an alkaline agent such as slaked lime to the surface ocean and letting the model’s carbonate chemistry, circulation, and biology determine how much CO2 is actually sequestered, and how quickly. Only afforestation and reforestation have always been simulated this way, because the land-use patterns passed from IAMs to ESMs implicitly contain the forest transitions. Extending the same philosophy to other methods harnesses the full power of Earth system models: climate change effects on removal efficiency, from drought stress on bioenergy crops to ocean circulation changes, are computed rather than assumed.

But simulating the activity is only half the challenge. To measure what carbon removal actually achieves, scientists need a reference against which to compare, and this is where the study makes its most consequential conceptual contribution. The team defines two distinct metrics. The first is Process Carbon Removal, the gross amount of carbon a removal process takes up minus its own positive emissions, without any feedback effects. This is essentially what IAMs estimate, and it is the quantity relevant for carbon accounting, in the same way that emissions are priced per tonne regardless of how natural sinks respond. The second is Net Atmospheric Removal, the true difference in atmospheric carbon content between a world with the removal technology and a world without it, including every carbon-cycle and biogeophysical feedback the Earth system can muster. Crucially, the authors show that these two numbers can diverge substantially, because the planet’s carbon sinks respond to removal in ways that partially undo the benefit.

The reason for that divergence is the buffering nature of the carbon cycle. Today, terrestrial and oceanic sinks absorb more than half of every tonne of CO2 humanity emits. Models project that under declining emissions these sinks will take up less carbon, and under net-zero or net-negative emissions they can even flip into carbon sources, releasing CO2 back to the atmosphere as the reversed feedbacks operate in reverse. The practical consequence is stark: the net atmospheric reduction achieved by any carbon removal portfolio will always be less than the gross amount removed. How much less is a question the new framework is designed to answer quantitatively, scenario by scenario and model by model.

Constructing the necessary no-CDR baseline turns out to be anything but trivial. The authors distinguish two fundamentally different approaches. The first is an ex-post adjustment: take an existing IAM mitigation scenario and surgically remove the carbon removal, for instance by freezing the land-use transitions associated with afforestation or by omitting the alkalinity flux to the ocean. This preserves the original scenario’s geography and allows regional attribution of effects, but it produces a socio-economically inconsistent world, one where land earmarked for bioenergy simply sits idle rather than being reallocated to food production. The second is a counterfactual IAM scenario: re-run the economic model in a world where carbon removal was never an option, letting the energy system, land use, and emissions evolve consistently without it. This counterfactual world is socio-economically coherent but so different in its land-use and emissions geography that regional biogeophysical effects of the original removal deployment cannot be isolated. The two approaches are complementary, and the authors recommend that IAM teams begin producing counterfactual no-CDR baselines for selected scenarios, something that, to their knowledge, does not yet exist in the scenario literature.

To demonstrate the framework in action, the team turned to the Norwegian Earth System Model NorESM2-LM and a deep mitigation scenario generated by the REMIND-MAgPIE integrated assessment model, expanded to include ocean liming as a removal method. The scenario reaches an end-of-century carbon budget of 500 gigatonnes of CO2 from 2020, corresponding to 1.5 degrees Celsius of warming in 2100 after a substantial overshoot, with a peak cumulative budget exceeding 1000 gigatonnes around 2060 before massive upscaling of removals pulls it back down. In the Earth system model, ocean alkalinity enhancement was simulated activity-driven, with alkalinity deployed within exclusive economic zones excluding polar regions, while bioenergy removals remained prescribed. Three ensemble members were run for each of the required simulations.

The results are striking and, for anyone banking on ocean-based removal, sobering. For a deployment of 4.93 petamoles of alkalinity between 2050 and 2100, equivalent to 182.5 gigatonnes of calcium hydroxide, the model simulated a Process Carbon Removal of 28.2 petagrams of carbon by 2100. Carbon-cycle feedbacks from both land and ocean then clawed back 7.9 petagrams, roughly 28 percent, leaving a Net Atmospheric Removal of just 20.3 petagrams of carbon, equivalent to a 9.7 parts-per-million reduction in atmospheric CO2. The ocean and terrestrial biosphere contributed roughly equally to the feedback losses, at 4.8 and 3.1 petagrams respectively, though the authors caution that the land feedback in particular may vary greatly between models. Equally revealing was the comparison with the IAM’s own estimate: REMIND-MAgPIE, which assumes a constant efficiency of 0.57 moles of CO2 per mole of alkalinity and instantaneous uptake, overestimated the removal by about 7.4 petagrams, roughly 20 percent, partly because real ocean chemistry takes ten to fifteen years to fully equilibrate an alkalinity addition.

Perhaps the most humbling finding concerns the noise floor of the climate system itself. Even a tiny initial difference in carbon removal deployment acts as a perturbation that causes the scenario and baseline simulations to diverge chaotically, exactly as separate ensemble members with different initial conditions do. Within a few years of the alkalinity deployment beginning around 2040, the El Niño-Southern Oscillation states of the two simulations had become completely uncorrelated. The resulting internal variability in calculated removals and feedback fluxes remained comparable in magnitude to the global annual mean signal, and even decadal averages carried a noise level exceeding 0.25 petagrams of carbon per year. The implication is uncomfortable: detecting the small signals associated with carbon removal and its feedbacks in emission-driven simulations requires either sufficiently large initial-condition ensembles or averaging over long periods, and for some applications, such as quantifying regional biogeophysical effects, stylized modeling approaches may simply remain preferable.

The timing of this work could hardly be better. The upcoming seventh phase of the Coupled Model Intercomparison Project has adopted emission-driven scenario simulations as a priority, yet its ScenarioMIP protocol still foresees only prescribed carbon removal and no no-CDR baselines, limiting what those simulations can say about removal effectiveness. The authors argue that the next phase of the Carbon Dioxide Removal Model Intercomparison Project should adopt their framework, and they issue concrete recommendations to the modeling community: IAMs should provide gross positive and negative emissions separately for each removal method, deliver spatially explicit information on bioenergy with carbon capture in future land-use datasets, and flag the difference between passive forest regrowth and deliberate afforestation. As nations and companies commit billions to carbon removal portfolios whose real-world performance remains deeply uncertain, this framework offers something the field has lacked: a transparent, physically consistent way to separate what a removal technology promises from what the Earth system actually delivers.

Subject of Research: Earth system modeling of carbon dioxide removal efficiency and feedbacks in mitigation scenarios

Article Title: Assessing Earth system responses in mitigation scenarios with activity-driven simulation of carbon dioxide removal

Article References: Schwinger, J., Merfort, L., Bauer, N., Bernardello, R., Butenschön, M., Bourgeois, T., Gidden, M. J., Gupta, S., Lee, H., Mengis, N., Moustakis, Y., Muri, H., Nieradzik, L., Peano, D., Pongratz, J., Sauer, P., Tourigny, E., & Wårlind, D. (2026). Assessing Earth system responses in mitigation scenarios with activity-driven simulation of carbon dioxide removal. Earth System Dynamics, 17(5), 1341-1363. https://doi.org/10.5194/esd-17-1341-2026

Image Credits: AI Generated

DOI: 10.5194/esd-17-1341-2026

Keywords: carbon dioxide removal, Earth system models, integrated assessment models, ocean alkalinity enhancement, BECCS, afforestation, carbon cycle feedbacks, no-CDR baseline, CMIP7, net-zero emissions, NorESM2, climate mitigation scenarios