Scope 1, 2 and 3 greenhouse gas emissions calculated to GHG Protocol standard and structured for IFRS S2 and ESRS E1 disclosure. Every figure carries its calculation method, emission factor source, and data quality tier — because a compliance number without provenance isn't disclosable.
IFRS S2 and ESRS E1 require assessing every category and disclosing the materiality process, not just the convenient ones. The engine assesses all 15 and flags what's unassessed.
Each calculation records its method, factor source, version and publication year — the exact disclosure IFRS S2 paragraph 29 requires, captured automatically rather than reconstructed later.
Re-running a prior period returns the emission factors that applied then, not today's revision — so historical disclosures reproduce exactly instead of silently restating.
The GHG Protocol ranks Scope 3 data from most to least accurate. Most tools give you a single number. ValQ Carbon shows which tier each figure sits in — because auditors ask, and because it tells you exactly where to improve next.
| TIER | METHOD | WHAT IT USES | WHEN IT'S RIGHT |
|---|---|---|---|
| Highest | Supplier-specific | Primary data reported by the supplier | Material categories, audit-ready reporting |
| High | Hybrid | Primary where available, secondary elsewhere | Large suppliers known, long tail estimated |
| Medium | Activity-based | Physical quantities × published factors | Energy, fuel, travel, freight — unaffected by price movement |
| Screening | Spend-based | Financial spend × EEIO factor per dollar | First inventory, hotspot identification, long-tail categories |
ValQ Carbon doesn't invent emission factors. It uses the same government and standards-body datasets auditors expect to see cited — versioned, attributed, and updatable as each source publishes revisions.
US supply-chain factors across 1,016 commodities by NAICS code, kg CO₂e per USD, using IPCC AR6 GWP values.
The National Greenhouse and Energy Reporting factor set — the regulatory standard for Australian operations.
UK DEFRA conversion factors, ADEME Base Carbone, and Ember grid-intensity data for international coverage.
Published sets have real coverage gaps — US-based factors applied to Australian spend embed the wrong grid mix and price level, long-tail service categories are coarsely aggregated, and most downstream Scope 3 categories have almost no published spend coverage at all. ValQ derives factors for those gaps using recognised carbon-accounting techniques, each fully documented with its own uncertainty bounds.
| DERIVATION METHOD | USED WHEN | UNCERTAINTY |
|---|---|---|
| Regional adjustment | Adapting a published factor across economies (grid intensity + price level) | ±15% |
| Physical intensity scaling | Converting between units via a known physical relationship | ±20% |
| Peer-set regression | Several published factors bracket the activity | ±25%+ |
| Proxy mapping | No published factor exists; mapped to closest analogue | ±30% |
| Value-chain extrapolation | Downstream categories (9–14) with no published coverage | ±35% |
Derived factors are always marked as ValQ-derived in output and disclosure, never presented as published. Each carries its method, the published inputs it was built from, the reasoning, and honest error bounds — because that documentation is exactly what an assurance provider will ask for.
Unlimited inventories, all 15 Scope 3 categories, IFRS S2-structured export, and factor updates as each source publishes. Built for the accountants, advisers and finance teams who have to sign off on the number.
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