The request usually arrives from your largest customer, phrased as a formality: emissions data for the parts you supply, per unit, by next quarter.
It isn't a formality. Their own reporting obligation is being pushed down the chain, and the shops that can answer keep the business while the ones that can't get a follow-up email with a deadline on it.
The good news is that a defensible first answer is arithmetic, not a consultancy engagement.
Estimating embedded emissions
Most of a machined part's footprint is the material, not the machining:
kgCO2e = billet_kg × material_factor
+ (cycle_hours × machine_kW × grid_factor)
+ freight_tonne_km × transport_factor
Published material factors vary by source, so cite whichever you use and stay consistent — the number's value is in comparison, not absolute precision. Typical ranges for aluminium:
| Route | kgCO2e per kg | Bracket at 0.68 kg billet |
|---|---|---|
| Primary (virgin) | 8–18 | ~5.8–12.2 |
| Recycled secondary | 0.5–2.0 | ~0.3–1.4 |
That single choice — virgin or recycled feedstock — moves the part's footprint by roughly an order of magnitude, and it dwarfs anything the machining step contributes:
machining = 0.075 hr × 15 kW × 0.35 kgCO2e/kWh ≈ 0.39 kgCO2e
Which is why "we upgraded to efficient lighting" is not an answer, and "our billet is 75% recycled content" is.
What it costs, when it costs anything
Where a carbon price applies to imported goods, the arithmetic is direct:
carbon_cost = kgCO2e × price_per_tonne / 1000
At €70/tonne, our bracket carries €0.41 on the primary route and €0.07 on recycled. Per part that's noise. At 40,000 parts a year it's €16,400 against €2,800 — and it lands entirely on whichever side of the border the rules put it.
Treat it as a sixth term in the landed cost equation rather than a separate sustainability exercise. It behaves exactly like freight: small per unit, decisive at volume, invisible if you only compare unit price.
The part people get wrong
Chasing precision before coverage. A supplier-specific figure for one part, with nothing for the other four hundred, answers no customer's question.
Collect a rough, consistently-derived number for everything first — material route, weight, origin — then improve the parts that turn out to matter. The distribution is always lopsided: a handful of heavy, virgin-material, long-freight parts carry most of the total.
How this gets solved
The reason this becomes a six-week project instead of a query is that the inputs live in different places: weight on a drawing, material route in a supplier's head, freight distance in a shipping folder, and none of it attached to the part.
The RFQ is the natural capture point. You are already asking suppliers a set of structured questions and storing their structured answers — adding material route and origin to that list costs one field and gets answered by the person who actually knows.
RFQTrace stores quotes as line items against your questions rather than as a lump sum in a PDF, so an attribute you start collecting today is queryable across every part you buy next year. That's the whole trick: not a carbon module, just refusing to throw the data away.