Food matters: Dietary shifts increase the feasibility of 1.5°C pathways in line with the Paris Agreement
Data files
Sep 14, 2023 version files 69.79 KB
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DietEnergy_data_figures.xlsx
67.81 KB
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README.md
1.98 KB
Sep 13, 2023 version files 69.84 KB
Abstract
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.
README: Food matters: Dietary shifts increase the feasibility of 1.5°C pathways in line with the Paris Agreement
This dataset contains results of a forward-looking modelling study conducted with the opensource Integrated Assessment Modelling (IAM) framework REMIND-MAgPIE (REMIND 3.2.0 and MAgPIE 4.6.7).
Data is provided 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.
Description of the data and file structure
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.
Fig1: Overview of scenario assumptions for dietary composition, per-capita food intake and food waste (kcal per capita per day)
Fig2a: Global mean temperature incrase (K)
Fig2b: Global GHG price (USD2020 per ton CO2eq)
Fig2c: Annual CH4 and N2O emissions (Gt CO2eq per year)
Fig2d: Annual CO2 emissions (Gt CO2 per year)
Fig2e: Cumulative net CO2 emissions (Gt CO2)
Fig2f: Cumulative carbon dioxide removal (Gt CO2)
Fig2g: Demand modern bioenergy (2nd gen.) (EJ per year)
Fig2h: Final energy price (Index 2020=100)
Fig2i: Forest and other natural land (change in Mha since 2020)
Fig2j: Landuse intensity indicator tau (index)
Fig2k: Nitrogen surplus on cropland (Mt N per year)
Fig2l: Per-capita food expenditure (USD2020 per capita per year)
Fig3a: GHG emissions from Agriculture, Forestry and Other Land Use (AFOLU) (Gt CO2eq per year)
Fig3b: GHG emissions from energy and industry (Gt CO2eq per year)
Fig4: Subcategories of GHG emissions from Agriculture, Forestry and Other Land Use (AFOLU) (Gt CO2eq per year)
Fig5: Carbon Dioxide Removal (CDR) (Gt CO2 per year)
Fig6: Land-use change of major land types (Change in Mha compared to 2020)
Sharing/Access information
Data was derived from the following sources:
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.
Usage notes
Microsoft Excel, LibreOffice Calc Spreadsheet, R-Studio