{
  "data_date": "2026-10-28",
  "methodology_version": "0.9.2",
  "scope_caveat": "This project estimates the CO₂ footprint of OpenRouter-visible LLM inference — a representative but partial slice of global AI usage. It is NOT a measurement of total global data-center emissions. All figures are estimates with uncertainty ranges, not measurements.",
  "scope_2": {
    "location_based": {
      "low": 5038653.193626482,
      "mid": 22701836.428312097,
      "high": 119635791.92002432
    },
    "market_based": {
      "low": 4321596.597771675,
      "mid": 20287173.607800532,
      "high": 110053343.20506187
    }
  },
  "esrs_e1": {
    "standard": "ESRS E1 Climate Change",
    "disclosure": "E1-6 Gross Scopes 1, 2, 3 and Total GHG emissions",
    "line_item": "Scope 2 purchased energy (location-based vs market-based) — estimated from OpenRouter-visible LLM inference traffic (proxy for Scope 3 Category 1 purchased services)",
    "location_based_kgco2e": {
      "low": 5038653.193626482,
      "mid": 22701836.428312097,
      "high": 119635791.92002432
    },
    "market_based_kgco2e": {
      "low": 4321596.597771675,
      "mid": 20287173.607800532,
      "high": 110053343.20506187
    },
    "modeled_traffic_fraction": 0.9390258357223126,
    "note": "Ranges carried end-to-end from totals; no collapse to point values. Dual reporting follows GHG Protocol Scope 2. Scale by modeled_traffic_fraction for full inventory. Full uncertainty and partial-coverage statement is in scope_caveat (non-removable)."
  },
  "source_citation": "Source: OpenRouter (openrouter.ai/rankings), as of 2026-10-28"
}