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Tier 2 — Parametric

What it is

The default tier and the one most production traffic returns. A parametric model calibrated against ecoinvent v3.10 and ADEME Base Empreinte 2024, computed via BoaviztAPI 0.7.x with model size, hardware, datacentre PUE, live grid intensity, and embodied amortisation as inputs.

Inputs

Input Source Update cadence
Model parameter count and architecture Internal model registry Per-release
Hardware specification (GPU, host CPU, DRAM) Per-region inventory (Scaleway, atNorth, OVH) Per-quarter
Datacentre PUE Provider disclosure Annual
Live grid carbon intensity ENTSO-E + regional ISO/TSO (see grid sources) Sub-hourly
Embodied carbon amortisation EcoLogits 2025 update + ecoinvent v3.10 Per-release
Batch size estimate Trailing-quarter telemetry Per-quarter

Calculation

Roughly:

energy_per_query = (
    parametric_gpu_energy(model_size, hardware, batch)
  + host_energy_share(model_size, hardware, batch)
  + idle_share(provisioned_concurrency)
) * pue

co2e_per_query = energy_per_query * grid_intensity_at_request_time
              + embodied_amortisation_per_query

water_per_query = energy_per_query * water_intensity_for_region

Each line carries a probability distribution rather than a point. The outputs are computed by Monte Carlo log-normal propagation (10,000 trials per query for tier-2; results cached and reused for repeated parameter sets within a calibration window).

Boundary

  • Narrow: accelerator only. This is what some vendors quote in marketing.
  • Comprehensive: accelerator + host CPU/DRAM + provisioned idle + datacentre PUE. This is what an assurance partner accepts and what we report by default.

The narrow ratio is typically 0.40 to 0.45 of the comprehensive number; the comprehensive boundary is the realistic operational footprint per request.

Output

{
  "tier": "parametric",
  "tier_id": "02",
  "co2e": {
    "median_g": 1.07,
    "ci90": {"low": 0.71, "high": 1.58},
    "boundary": "comprehensive"
  },
  "water": {"median_ml": 41, "ci90": {"low": 32, "high": 50}},
  "energy": {"wh": 0.231, "narrow_wh": 0.092, "comprehensive_wh": 0.231},
  "pedigree": [2, 2, 1, 1, 2]
}

Pedigree expectations

Tier 2 receipts typically score [2, 2, 1, 1, 2]:

  • Reliability (2): verified data partly based on assumptions
  • Completeness (2): representative data from > 50% of relevant sites
  • Temporal (1): less than 3 years old
  • Geographic (1): data from area under study
  • Technological (2): data from processes and materials under study, but with somewhat different technology

The pedigree improves substantially over tier 1 in the temporal and geographic axes because we have live grid intensity at calculation time and a per-region inventory.

Calibration

The 90% interval reported at tier 2 is conformal-prediction calibrated against tier-3 measurements from the prior quarter. This guarantees marginal coverage on the calibration distribution: the truth has historically fallen inside the interval at least 90% of the time on the calibration workload.

The calibration is re-fit quarterly. Re-calibration events are noted in the methodology changelog.

Where this is implemented

methodology/tier2/parametric.py

Citations

  • Boavizta. BoaviztAPI 0.7.x. github.com/boavizta/boaviztapi.
  • ecoinvent association. ecoinvent v3.10. Zürich, 2024.
  • ADEME. Base Empreinte 2024. base-empreinte.ademe.fr.
  • Lloyd & Ries (2007). Characterizing, Propagating, and Analyzing Uncertainty in Life-Cycle Assessment. J. Industrial Ecology 11(1).