Competing for land: mapping potentials and trade-offs of land-based carbon dioxideremoval under climate targets

Most national climate pledges and climate change mitigation scenarios assessed by the IPCC
assume substantial deployment of land-based carbon dioxide removal (CDR) to meet the
temperature goals of the Paris Agreement. This reliance implies a large land footprint: land-based
CDR in national pledges and IPCC AR6 pathways can require land areas up to around one
billion hectares, comparable in magnitude to today’s global cropland area. At these scales, land
competition becomes a binding constraint, with significant trade-offs for food security,
livelihoods, and biodiversity.
Integrated assessment models (IAMs) are widely used to evaluate the role of CDR in mitigation
pathways, yet they often represent land-system constraints in a crude fashion. Previous studies
typically rely on models with simplified biophysical processes and coarse spatial resolution,
obscuring sub-regional heterogeneity in land suitability and carbon dynamics. This limitation is
particularly salient given evidence from process-based ecosystem studies that CDR potentials
vary strongly across space. Additionally, most IAM studies assess only a narrow subset of CDR
options, potentially underestimating total removal potentials and overstating land competition.
The emphasis is typically placed on land-intensive approaches like afforestation/reforestation
(A/R) and bioenergy with carbon capture and storage (BECCS), while underrepresenting
approaches that can be co-deployed on agricultural lands, such as biochar and enhanced rock
weathering (ERW). Consequently, potential synergies between CDR and other land uses, for
example through crop yield improvements, remain insufficiently explored.
We address these gaps by extending the IMAGE integrated assessment framework with a newly
developed IMAGE-CDR module that directly couples the energy system model TIMER with the
land system model IMAGE-Land/LPJmL. IMAGE-CDR estimates the spatial and temporal
deployment of land-based CDR by allocating land across competing options subject to demand,
biophysical potential, land suitability, deployment-rate limits, and economic feasibility. The
module operates on a 5′×5′ global grid and represents fractional land allocation within each grid
cell. Competition between CDR options is resolved through grid-cell-level net present value
profitability ranking, while land scarcity and interactions with agriculture are captured through a
land-cost supply curve that increases the opportunity cost of land as competition intensifies.
IMAGE-CDR represents A/R, bioenergy crops (with optional carbon capture and storage to
enable BECCS), ERW, and biochar.
Using scenario analysis, we compare the spatial deployment of land-based CDR across three
mitigation pathways: (i) current policies, (ii) a stringent target with limited overshoot, and (iii) a
less stringent target with high overshoot. We quantify method-specific removal trajectories, land
footprints, and removal efficiency per unit of land, and identify regional hotspots of feasible
deployment. We further assess interactions with food production and biodiversity conservation
by mapping overlaps with cropland and conservation priority areas and quantifying impacts on
food security and biodiversity. Our results inform the design of land-based CDR strategies by
mapping feasible deployment and associated trade-offs across regions and mitigation pathways.