SOMA AI Emission Factors (SAEF) – AI Inference Emission and Resource Factors for Corporate GHG Inventories, dataset v3.1

SOMA AI Emission Factors (SAEF), version 3.1.0, is the machine-readable companion to Llopis-Garcia, G. (2026), Accounting for Purchased Artificial Intelligence Inference in Corporate Greenhouse Gas Inventories: A Token-Based Method (arXiv:2606.10660, accepted for publication in Sustainable Production and Consumption). It gives estimated kg CO2e and water factors per million tokens for commercial and self-hosted large language models, by model class and region, with a standard-library Python calculator, end-to-end checks and a data dictionary. Released under CC BY 4.0.

Changes from v3.0.0 (10.5281/zenodo.23371447). Corrections only; CHANGELOG.md gives before and after values and RELEASE_NOTES_v3.1.0.md the summary. (1) Azure canadaeast and Google Cloud northamerica-northeast1, which the providers place in Quebec, now take the Quebec provincial grid (0.0265 kg CO2e/kWh) instead of the Canadian national average (0.1744), as AWS ca-central-1 already did; their class B factor per million billed tokens falls from 0.0168 to 0.0063 kg. (2) The Central African Republic grid row, which Ember publishes as 0 g/kWh because its emissions round to 0.00 MtCO2, now takes a documented zero-intensity fallback of 0.0238 kg/kWh (100% hydro). (3) The README quick-start example now states the value the calculator returns, 0.0871 kg. No other row changes, and no number printed in arXiv:2606.10660 changes.

Changes in v3.0.0 from v2. (1) The boundary is a four-term lifecycle: electricity, embodied hardware, construction and training, each reported separately. (2) Factors are on an effective-token basis, with the prefix-cache share restated per benchmark run to a reference mix. (3) The three model classes are the means of their measured members (18 open-weight models on H100 and B200, ML.ENERGY Leaderboard v3). (4) Coverage is 210 countries and economies, 27 US eGRID subregions and 143 public cloud regions; water, with AWARE 2.0 scarcity, is given for 17 regions. (5) Monte Carlo propagation of the input ranges is added. (6) Region-range and grid-year-2024 sensitivities are added.

The raw third-party corpora (Azure traces, WildChat and Arena samples, OpenRouter rankings, Economic Index extracts) are excluded because they carry their own licences; they can be re-downloaded as described in THIRD_PARTY_DATA.md, which gives source, licence, attribution and script for each. The derived statistics are included. The folder v4_inputs/ is uploaded as v4_inputs.zip. See MANIFEST.md for every file. Licence CC BY 4.0.