How we get to our numbers, and what they do not claim.
The figures in our calculator and CO₂ dashboard are ex-ante estimates. They are produced with explicit attribution and deadweight assumptions and a stated time horizon. They are directional, meant to show order of magnitude, and they are not audited.
Ex-ante
forward-looking, not a measured result
~ 70%
share of the effect we credit to the match
~ 20%
what we assume would have happened anyway
Four adjustments, from mass to claim.
The same simple chain produces every estimate. We would rather make each assumption visible than bury it inside a single impressive number.
Handprint (t CO₂e) = tonnes re-matched × emission factor × attribution (~ 0.70) × (1 − deadweight ~ 0.20)
Time horizon: impact is counted once, at the point a single exchange settles, as a one-time displacement. We do not annualise it or project it forward over a material's lifetime.
Start from tonnes re-matched
We begin with the mass of material moved by a completed exchange, in tonnes. Nothing is counted until an exchange has actually settled.
Apply an emission factor
Each material has an avoided-emission factor: the emissions saved by using one tonne of re-matched material instead of one tonne of virgin equivalent. Factors come from public sources and are versioned.
Adjust for attribution (~ 70%)
We do not claim the whole effect. The exchange depended on the seller, the buyer, and logistics too, so we credit roughly 70% of the avoided emissions to the match the platform made.
Subtract deadweight (~ 20%)
Some material would have found a second life anyway. We assume roughly 20% deadweight and remove it, so we only count the additional effect the platform caused.
Attribution and deadweight are stated assumptions, not measured constants. They are deliberately conservative and will be refined as we gather exchange-level data.
Two different things, kept separate.
People often blur these two, which is how greenwashing happens. We keep them apart on purpose.
Footprint
Our own emissions: the harm we cause by running the company. Hosting, travel, the small team. The goal here is to reduce it.
This is about doing less damage. It is the ordinary work of keeping our own house in order, and it is not what the dashboard celebrates.
Handprint
The positive effect we enable for others: the emissions avoided when a buyer uses re-matched material instead of virgin, because our platform made the match.
This is the number our calculator and dashboard show. To keep it honest, what was labelled CO₂ avoided is the handprint: the good we help others do, estimated with the assumptions above.
A company can have a handprint far larger than its footprint, and that is the whole point of an enabling platform. But the two must never be netted against each other or presented as one figure. We report the handprint as an estimate of good enabled, never as an offset against our own emissions.
Public sources, and only those.
Every input traces back to a public source. We do not use private or unverifiable factors, and each emission factor is stored with its source and version so a reviewer can check it.
- Circularity Gap Report, Denmark
National circularity rate and virgin material consumption per capita.
- Eurostat / EEA, circular material use rate
European circular material use rate, used for context, not for crediting.
- Danmarks Statistik, material and waste accounts
Danish material flow and waste composition data.
- Recognised life-cycle inventory databases
Avoided-emission factors per material, virgin versus secondary, drawn from established public LCA datasets and government factor sets. Each factor is recorded with its source and version.
- Per-material illustrative factors
The calculator currently uses simplified per-material factors (for example, steel, wood, brick, mixed) as directional placeholders pending final sourced and versioned values.
Directional today, auditable as we grow.
Treat every figure as a careful estimate of order of magnitude, not a certified result. As exchange volume grows we will tighten the factors, version the methodology, and open the per-exchange data to review.