Adding spatially resolved CO2 removal by afforestation

CO2 sequestration potential is typically maxed out because the model is eager to achieve negative emissions to compensate for process emissions and, in some cases, to offset fossil oil emissions. It will be nice to have other carbon dioxide removal (CDR) strategies represented in PyPSA-Eur.

Afforestation = Establishment of forests in regions without prior significant tree cover

Conservative cost estimations from the literature are already in the technology-data repository: https://github.com/PyPSA/technology-data/pull/254

Potential removal in every region can be estimated based on CLC Category ”transitional woodland/shrub” (suitable for young plantations), NUTS3-specific biomass density ( doi:10.1038/s41597-023-02868-8 ) and assuming 30 years for forest growth.

We have estimated the total removal potential of afforestation in Europe as 83 MtCO2/a.

More details: https://arxiv.org/abs/2603.25663

The proposal is to add a store removing CO2 from the CO2 atmosphere bus with e_nom_max representing afforestation potential.

This is a description, and a PR will follow.

Start by reading the proposed CO2-atmosphere store and e_nom_max approach in the issue, then review the linked technology-data PR, CLC transitional woodland/shrub category, NUTS3 biomass-density paper, and arXiv details. Done means afforestation removal potential is represented spatially with the stated cost and growth assumptions and the model accounts for the proposed store.