This is a Python conversion of an R-based Multi-Regional Input-Output (MRIO) model merged with FoodLife for the purpose of analyzing agricultural trade and its impact on cropland use and species habitats.

• main.py - Main execution script (equivalent to _Execute.R)

• processing/unzip_data.py - Utility for unzipping FAOSTAT data (equivalent to Unzip data.R)
• processing/calculate_trade_matrix.py - Calculates apparent consumption and trade links (equivalent to Calculating_Trade_Matrix.R)
• processing/animal_products_to_feed.py - Converts animal products into embedded feed items (equivalent to animal_products_to_feed.R)
• provenance/_provenance.py, provenance/_get_impacts_bd.py and provenance/_process_dat.py - Modified version of LIFE impact code

• requirements.txt - Python package dependencies
• README.md - This documentation file
• PipelineChangesLDN.md- List of significant changes made from original code

• Python 3.8 or higher
• pip (Python package manager)

1. Clone or download this repository
2. Navigate to the python directory
3. Install required packages:

   pip install -r requirements.txt

1. If downloading from Github LFS takes too long, download the FAOSTAT data files and place in the input_data directory

   • Production_Crops_Livestock_E_All_Data_(Normalized).zip
   • FoodBalanceSheetsHistoric_E_All_Data_(Normalized).zip
   • FoodBalanceSheets_E_All_Data_(Normalized).zip
   • Trade_DetailedTradeMatrix_E_All_Data_(Normalized).zip
   • CommodityBalances_(non-food)_(-2013_old_methodology)E_All_Data(Normalized).zip
   • SUA_Crops_Livestock_E_All_Data_(Normalized).zip
   • Inputs_LandUse_E_All_Data.zip

2. Configure settings in main.py

3. Run the main script:

   python main.py

You can modify the following options in main.py:

YEARS = list(range(1986, 2022))  # Limits: 1986-2022, default: 2013-2022

Choose from the following nutritional conversion methods:

conversion_opt = "dry_matter"

Available options:

• "dry_matter" (default)
• "Energy"
• "Protein"
• "Fiber_TD"
• "Zinc"
• "Iron"
• "Calcium"
• "Folate_Tot"
• "Riboflavin"
• "Choline_Tot"
• "Potassium"
• "Vit_E"
• "Vit_B12"
• "Vit_K"
• "Vit_A"

Choose whether to prefer import or export data:

prefer_import = "import"  # or "export"

Choose whether to use 2020 mapspam data:

USE_2020_DATA = True

Control which parts of the pipeline to run:

PIPELINE_COMPONENTS:list = [0]

Component options:

• 0 = Full pipeline (all components)
• 1 = Unzipping data only
• 2 = Error matrix calculation
• 3 = Trade matrix calculation
• 4 = Animal products to feed calculation
• 5 = Country-level impact calculations (as in LIFE)

Which countries to analyse in detail:

COUNTRIES = ["GBR"]

The pipeline expects the following data files in the input_data directory:

• CommodityBalances_(non-food)_(-2013_old_methodology)_E_All_Data_(Normalized).zip
• FoodBalanceSheets_E_All_Data_(Normalized).zip
• FoodBalanceSheetsHistoric_E_All_Data_(Normalized).zip
• Production_Crops_Livestock_E_All_Data_(Normalized).zip
• SUA_Crops_Livestock_E_All_Data_(Normalized).zip
• Trade_DetailedTradeMatrix_E_All_Data_(Normalized).zip
• Inputs_LandUse_E_All_Data.zip

• CB_code_FAO_code_for_conversion_factors.csv
• CB_items_split.csv
• CB_to_primary_items_map.csv
• commodity_crosswalk.csv
• composition_old_vs_new.csv
• content_factors_per_100g.xlsx
• country_opp_cost_v6.csv
• nocsDataExport_20251021-164754.xlsx
• Planet-Based Diets - Data and Viewer.xlsx
• primary_item_map_feed.csv
• Reporting_Dates.xls
• schwarzmueller_wwf.csv
• SUA_Crops_Livestock_E_ItemCodes.csv (also produced during unzip)
• tb_pasture_factors_2.csv
• weighing_factors.csv

For each processed year, the pipeline generates:

• results/{year}/.mrio/TradeMatrix_{conversion}_{year}.csv - Main trade links for apparent consumption
• results/{year}/.mrio/TradeMatrixFeed_{conversion}_{year}.csv - as above, broken down for feed
• results/{year}/.mrio/Pasture_calc.csv - Pasture efficiencies calculated for the relevant year
• and all additional files as in LIFE
  • kdf.csv has been renamed impacts_aggregate.csv
  • xdf.csv have been renamed impacts_full.csv
  • df_uk.csv is now df_{country_iso}.csv rather than uk for all countries
  • food_commodity_impacts.csv has been added with calculated per kg impacts