Food matters: Dietary shifts increase the feasibility of 1.5°C pathways in line with the Paris Agreement

A transition to healthy diets like the EAT-Lancet Planetary Health Diet could considerably reduce GHG emissions. However, the specific contributions of dietary shifts for the feasibility of 1.5°C pathways remain unclear. Here, we use the open-source Integrated Assessment Modeling (IAM) framework REMIND-MAgPIE to compare 1.5°C pathways with and without dietary shifts. We find that a flexitarian diet increases the feasibility of the Paris Agreement climate goals in different ways: The reduction of GHG emissions related to dietary shifts, especially methane from ruminant enteric fermentation, increases the 1.5°C-compatible carbon budget. Therefore, dietary shifts allow us to achieve the same climate outcome with less carbon dioxide removal (CDR) and less stringent CO2 emission reductions in the energy system, which reduces pressure on GHG prices, energy prices and food expenditures.

This dataset provides raw data for all figures shown in the paper. It includes data for three scenarios: SSP2-NDC, SSP2-1.5°C and SSP2-1.5°C-DietShift. All data is at global level and for the period 2020-2100. Raw data for each figure panel is provided on individual data sheets in a single .xlsx file. The structure of the data is identical on each sheet, organized in columns for model, scenario, region, variable, unit, year and value.

Methods
This dataset has been produced with the open-source Integrated Assessment Modeling (IAM) framework REMIND-MAgPIE.

The source code for MAgPIE 4.6.7 is openly available at https://github.com/magpiemodel and http://doi.org/10.5281/zenodo.7923602. The model documentation can be found at https://rse.pik-potsdam.de/doc/magpie/4.6.7/. Instructions for software installation and running the model are available at https://github.com/magpiemodel/magpie.

The source code for REMIND 3.2.0 is openly available at https://github.com/remindmodel and http://doi.org/10.5281/zenodo.7852740. The model documentation can be found at https://rse.pik-potsdam.de/doc/remind/3.2.0. Instructions for software installation, running the model and coupling to MAgPIE (tutorials subfolder) are available at https://github.com/remindmodel/remind.