οἶκος

ECOS — Environmental Cost of Service

A governed research walkthrough: each inference is routed to the lightest viable model tier, checked against a nested environmental budget, and receipted before release.

From Greek οἶκος (oikos) — "home." The shared root of ecology and economy. The management of the house. Indigenous Environmental Safe Procurement — the carbon footprint left behind by responsible governed AI. Governance from the same soil as the research it protects.

What is Indigenous Environmental Safe Procurement?

The obligation of any AI governance system to measure, disclose, and limit the environmental cost of every inference at the point of generation — accountable to the specific land, water, and atmosphere where the compute physically runs.

Indigenous locates the accountability. The compute has a physical address. The energy comes from a specific grid. The water comes from a specific source. The CO₂ lands on specific soil. The governance must answer to that soil.

Environmental names what is at stake. Not data. Not privacy. Not bias. The planet.

Safe makes the promise. The procurement of AI compute will not exceed what the land can absorb. The gate enforces the budget. The receipt proves it was honored.

Procurement places the intervention. Before the contract. Before the inference. Before the cost is incurred. Governance at the point of purchase — not after the damage.

CARE governs the data. Indigenous Environmental Safe Procurement governs the compute — and the land it touches.

OrganizationDeBacco Nexus — ATHENA Research Centre
ProgramMaritime Twin Transition Study
Grid regionGreece — 0.344 kg CO₂/kWh (EEA 2024)
MethodNEXUS-ECOS-2026.1
BUDGET ARMED
Methodology — derivation of all values on this page

Energy per token by model tier

GPU baselineNVIDIA A100 · 300W TDP
PUE1.2 (hyperscale average)
Haiku-class (~8B)0.18 J/token
300W ÷ 2,000 tok/s × 1.2
Sonnet-class (~70B)1.80 J/token
300W ÷ 200 tok/s × 1.2
Opus-class (~175B+)7.20 J/token
300W ÷ 50 tok/s × 1.2

Environmental conversion factors

Water intensity1.8 L/kWh → 0.0005 mL/J
Microsoft Environmental Sustainability Report 2023
CO₂ (Greek grid)0.344 kg/kWh → 9.56e-5 g/J
European Environment Agency 2024
Org budget basis200 researchers × annual load
50 wk × 5 sessions × 12 inf × ~694 J avg
Gate overheadHaiku 120 tok / Sonnet 180 tok
Fixed consensus + intent check per request

Published sources

[1] Patterson et al. (2022). "Carbon Footprint of ML Training." IEEE Computer.

[2] Luccioni et al. (2023). "Power Hungry Processing." ACM FAccT 2024.

[3] Li, Yang, Islam, Ren (2023). "Making AI Less Thirsty." arXiv:2304.03271.

[4] Microsoft (2023). Environmental Sustainability Report.

[5] European Environment Agency (2024). Greek grid: 0.344 kg CO₂/kWh.

[6] DeBacco (2026). "Governed Interoperability and Accountability." SSRN. Author page ↗


Reducing compute waste at the data center

Without governed tiering, every research query defaults to the heaviest available model — consuming 40× more energy per token than necessary. ECOS routes each request to the lightest tier that can handle it. The savings compound across the entire research ecosystem.

Ungoverned — every query hits Opus

Tier distribution100% Opus
Cost per token7.20 J/tok
1,000 queries × 600 tok avg4,320,000 J
Water (1.8 L/kWh)2,160 mL
CO₂ (Greek grid)413.2 g

Governed ECOS — lightest viable tier

Tier distribution60% Haiku · 25% Sonnet · 15% Opus
Weighted cost/tok1.64 J/tok
1,000 queries × 600 tok avg982,800 J
Water491.4 mL
CO₂94.0 g
77%Energy reductionper 1,000 governed queries
3.34 MJCompute preventednever reached the GPU
319 gCO₂ avoidedGreek grid · per 1,000 queries

Scaled to ATHENA: 200 researchers × 50 weeks × 60 queries/week = 600,000 queries/year. Ungoverned: 2.59 GJ · 720 kWh · 248 kg CO₂. Governed: 0.59 GJ · 164 kWh · 56 kg CO₂. Annual savings: 556 kWh and 191 kg CO₂ across a single research network. That is publishable data from a working instrument — not a projection.


ECOS Hierarchical Budget

01 · ECOS-Org — DeBacco Nexus Annual4.17 / 4.17 MJ
200 researchers × 50 wk × 5 sessions × 12 inf × ~694 J = 4.17 MJ
02 · ECOS-Program — Maritime Study52,083 / 52,083 J
5 researchers × 50 wk × 10 sessions × 15 inf × ~694 J = 52,083 J
03 · ECOS-Agent — Session 0x7f2a10,417 / 10,417 J
15 inferences × ~694 J weighted average = session ceiling
04 · ECOS-Tx — Current Inference—
Cascade rule: one permitted request deducts from organization, program, and agent simultaneously. If any level is empty, the gate withholds before target inference runs.

Model Tier Policy

Tier 1 — Haiku (Consensus gate)standby
0.18 J/tok · ~120 tokens · ~21.6 J fixed gate cost
Tier 2 — Sonnet (Intent classification)standby
1.80 J/tok · ~180 tokens · ~324 J fixed gate cost
Tier 3 — Opus (Target inference)standby
7.20 J/tok · runs only when both gates clear · 40× Haiku cost

Conservation principle: the heaviest model runs only when earned. When Haiku can resolve the request, Sonnet and Opus never wake up — their compute never reaches the data center GPU.

0.00Energy consumedJoules
0.0000Water usedmL
0.00000CO₂ emittedg (GR 0.344)
0.00Energy preventedJ (never consumed)

ECOS Carbon Passport Receipts

Inference 0 / 11

Budget is armed. Run the first governed research inference to begin the walkthrough.

οἶκος

ECOS — Environmental Cost of Service. The economy of compute governed by the ecology of the planet.

Every receipt is a carbon passport. Every withheld inference is energy the planet never had to absorb.

We don't offset. We prevent.

Environmental Fiduciary Duty ↗ · Live gate ↗ · SSRN ↗

Energy, water, and CO₂ figures are derived from published per-token measurements and Greek grid data (see Methodology). Budget logic, receipts, and hashes execute locally. © 2026 DeBacco Nexus LLC. Governedware™