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Data Sources & Licensing

fair-shares bundles several datasets to enable allocations without external dependencies. This page documents the sources, licenses, and citation requirements.

Quick Reference

All bundled data permits redistribution. The licenses are permissive:

Data Type Source License Citation Required
Emissions PRIMAP-hist v2.6.1 CC-BY-4.0 Yes
Population UN/OWID 2025 CC-BY-4.0 Yes
GDP World Bank WDI 2025 CC-BY-4.0 Yes
GDP IMF WEO 2025 Terms of Use Yes
Gini UNU-WIDER WIID 2025 Academic use Yes
Regions regioniso3c (custom) MIT Optional
Scenarios IPCC AR6 (Gidden 2022) CC-BY-4.0 Yes
Carbon budgets Lamboll et al. 2023 See paper Yes

Emissions Data

PRIMAP-hist

Source: Gütschow, J., Busch, D., & Pflüger, M. (2025). The PRIMAP-hist national historical emissions time series (1750-2023) v2.6.1. Zenodo.

DOI: 10.5281/zenodo.15016289

License: CC-BY-4.0

Location: data/emissions/primap-202503/

What it provides: National greenhouse gas emissions by country (1750-2023), including CO2 from fossil fuels, land use, and other GHGs.

Population Data

UN/OWID

Source: United Nations World Population Prospects via Our World in Data (2025).

License: CC-BY-4.0

Location: data/population/un-owid-2025/

What it provides: National population time series (historical and projections).

Economic Data

World Bank WDI

Source: World Bank World Development Indicators (2025).

License: CC-BY-4.0

Location: data/gdp/wdi-2025/

What it provides: GDP per capita (PPP, constant 2021 USD).

PPP vs MER: a normative choice

The choice between PPP and MER GDP measures is not purely technical — it is a normative decision that can significantly affect allocation results [Pelz 2025b]. See From Principle to Code for further discussion.

IMF World Economic Outlook

Source: International Monetary Fund World Economic Outlook (2025).

License: IMF Terms of Use (permits academic use with citation)

Location: data/gdp/imf-2025/

What it provides: GDP projections and historical estimates.

Inequality Data

UNU-WIDER WIID

Source: UNU-WIDER World Income Inequality Database (2025).

License: Academic use permitted with citation.

Location: data/gini/unu-wider-2025/

What it provides: Gini coefficients for income inequality.

Regional Mappings

regioniso3c

Source: Custom mapping by Setu Pelz (2024).

GitHub: setupelz/regioniso3c

License: MIT

Location: data/regions/

What it provides: Consistent mapping between ISO3C country codes and model region definitions.

IAMC regional data

When working with IAMC-format files, the library uses the regions defined in your input file, not fixed mappings. The bundled regional mapping is only for converting country-level outputs to model regions.

Carbon Budget Provenance

The global remaining carbon budget (RCB) is a key input for budget-based allocations. Different sources, temperature targets, and probability levels produce substantially different budgets. The table below documents the primary sources used and referenced in fair-shares:

Source Budget Temperature Probability Notes
Lamboll et al. 2023 247 GtCO2 from 2023 1.5°C 50% Default RCB in fair-shares bundled data
IPCC AR6 Various Various Various Temperature–budget relationships in WG1 Chapter 5

Citation for default budget:

Lamboll, R. D., et al. (2023). Assessing the size and uncertainty of remaining carbon budgets. Nature Climate Change, 13, 1360–1367. doi:10.1038/s41558-023-01848-5

Budget choice is normatively significant

The choice of carbon budget (source, temperature target, probability level) corresponds to Entry Point 2 of the fair share quantification framework — the allocation quantity [Pelz 2025b]. Results are sensitive to this choice. Always document the budget source, temperature target, and probability level when reporting allocation results.

Scenario Data

IPCC AR6 Scenarios

Source: Gidden, M. J., et al. (2022). AR6 Scenarios Database hosted by IIASA.

DOI: 10.5281/zenodo.8411053

License: CC-BY-4.0

Location: data/scenarios/ipcc_ar6_gidden/

What it provides: IPCC AR6 WGIII emission pathways.

Attribution in Your Work

When publishing results generated with fair-shares, cite:

  1. fair-shares library (see CITATION.cff)
  2. Data sources used (listed above)

Example citation block:

BibTeX
@software{fair_shares,
  author = {Pelz, Setu},
  title = {fair-shares: Climate mitigation burden-sharing allocations},
  year = {2026},
  url = {https://github.com/setupelz/fair-shares}
}

@dataset{primap_hist,
  author = {Gütschow, Johannes and Busch, Daniel and Pflüger, Mika},
  title = {PRIMAP-hist v2.6.1},
  year = {2025},
  doi = {10.5281/zenodo.15016289}
}

Adding Your Own Data

See Adding Data Sources for instructions on integrating additional datasets.

See Also