Most net-zero pathway models assume large amounts of land-based carbon dioxide removal. New forests. Bioenergy plantations. Soil restoration. The assumptions are baked into the models as givens.

A new study in Nature Climate Change asks the question those models often skip: where, specifically, does this land come from — and who lives there?

Ruben Prütz of the Potsdam Institute for Climate Impact Research and colleagues analyzed five widely used 1.5°C pathway models. They mapped the geographic distribution of where land-intensive CDR deployment is expected to occur across the modeled scenarios.

The findings are specific enough to be uncomfortable.

What the Models Assume

The 1.5°C models examined by Prütz et al. include REMIND-MAgPIE, IMAGE, MESSAGE, WITCH, and GCAM — the integrated assessment models that underpin the IPCC’s pathway analysis. These models are used by policymakers, central banks, and major investors to assess climate risk and transition scenarios.

They are, for the most part, agreed on one thing: reaching 1.5°C with moderate overshoot requires significant land-based CDR. The typical approaches modeled are:

Bioenergy with carbon capture and storage (BECCS): Grow energy crops, burn them for power, capture the CO₂ at the point of combustion, and store it geologically. The land required to grow sufficient biomass at scale runs to hundreds of millions of hectares in some models.

Afforestation and reforestation: Planting trees on previously unforested land. Land requirements vary widely by scenario but can reach 500 million hectares or more.

Soil carbon enhancement: Lower in land impact than BECCS or afforestation, but still spatially concentrated.

The models treat these land areas as available. The question Prütz et al. asked is: available to whom, and from whom?

The Geographic Concentration Problem

The study found that the models concentrate land-use demands in specific regions — and those regions are predominantly in the Global South.

Countries in sub-Saharan Africa, South and Southeast Asia, and Latin America appear frequently as the expected locations for large-scale land-based CDR under 1.5°C scenarios. These are often regions characterized by:

  • Existing food security pressures and high agricultural land competition
  • Complex land tenure systems, including informal customary rights
  • Governance gaps that make free, prior, and informed consent (FPIC) difficult to operationalize at scale
  • Lower political capacity to resist international pressure to accept land-use change

This is not a theoretical concern. Historical carbon offset projects — REDD+ forestry credits in particular — have generated well-documented cases of community displacement and land conflict in exactly these regions.

The models don’t include displacement. They include land availability. These are not the same thing.

Why This Matters for CDR Pathway Selection

This research does not argue against land-based CDR. Sustainable reforestation, improved land management, and soil carbon enhancement are legitimate and important pathways — when implemented with proper community engagement, benefit-sharing, and governance.

But the study’s spatial specificity reinforces something the CDR field has been slow to internalize: pathway selection has equity implications.

Enhanced weathering, ocean alkalinity enhancement, and direct air capture have much lower land footprints per tonne of CO₂ removed. They don’t require clearing existing vegetation, converting agricultural land, or negotiating complex tenure arrangements with rural communities. At scale, they face less political and social resistance — and they don’t carry the structural risk of replicating historical patterns of resource extraction from the Global South.

At CDI, our portfolio reflects this logic. We back pathways that are scientifically rigorous and, where possible, land-light. Not because land-based CDR is inherently problematic, but because the risk-adjusted case for land-light pathways looks stronger the more carefully you map the geographic and governance challenges of the alternative.

The Modeling Blind Spot

There is a broader methodological point worth flagging. The models that underpin IPCC scenarios are optimizing for physical outcomes — gigatonnes of CO₂ removed at least cost, subject to climate and energy system constraints. They are not well-equipped to model social and governance variables: community consent, legal uncertainty, political feasibility, or the time required to build the trust that large-scale land-use change requires.

This means the models systematically underestimate the real-world friction of land-based CDR deployment. That friction is not just an implementation detail — it affects whether the CDR happens at all.

The Prütz et al. study makes the geographic distribution of that friction visible. That’s a useful contribution, and one that policymakers designing CDR support frameworks should take seriously.

Source: Nature Climate Change, Prütz et al., via Mongabay.

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