Worked example: a steel panel

This lesson runs every phase on one small product system. It’s the same panel you met in Why learn LCA?, costed both ways. In the Skills class you’ll get an AI assistant to reproduce this answer, and check that it did.

Hypothetical data

The process data below are invented for teaching. They are in a plausible range but represent no real product, supplier or database. The GWP factors are real IPCC AR6 values.

Goal and scope

• Goal: find the climate change hotspot in making a painted steel panel, to decide where the design team should look first. Internal use, no comparative assertion.
• Declared unit: 1 painted steel panel, at factory gate.
• Boundary: cradle-to-gate. Four processes: grid electricity, steel sheet production, paint production, panel assembly. Transport and packaging are excluded (a known limitation).
• Method: climate change, GWP₁₀₀, IPCC AR6.

The product system

 Electricity, grid ──► Steel sheet production ──►
        │                                        ╲
        ├─────────────► Paint production ────────► Panel assembly ──► 1 panel
        │                                        ╱
        └───────────────────────────────────────╯

Process	Makes	Needs	Direct emissions per unit made
Electricity, grid	1 kWh	none	0.35 kg CO₂, 0.0008 kg CH₄, 0.00001 kg N₂O
Steel sheet production	1 kg steel	0.6 kWh	1.7 kg CO₂, 0.002 kg CH₄
Paint production	1 kg paint	1.2 kWh	2.1 kg CO₂, 0.0001 kg N₂O
Panel assembly	1 panel	4 kg steel, 0.25 kg paint, 3 kWh	none

Inventory

1. Scale each process to one panel. Steel: 4 kg. Paint: 0.25 kg. Electricity is needed in three places:

   assembly         3.0 kWh
   steel    4 × 0.6 = 2.4 kWh
   paint 0.25 × 1.2 = 0.3 kWh
   total            5.7 kWh

2. Multiply each process’s emissions by its scale and sum.

   Flow	Electricity (×5.7)	Steel (×4)	Paint (×0.25)	Total
   CO₂, fossil	1.995	6.8	0.525	9.32 kg
   CH₄, fossil	0.00456	0.008	0	0.01256 kg
   N₂O	0.000057	0	0.000025	0.000082 kg

Impact assessment

CO₂   9.32     × 1    = 9.3200
CH₄   0.01256  × 29.8 = 0.3743
N₂O   0.000082 × 273  = 0.0224
                        ──────
                        9.7167 kg CO₂-eq per panel

Interpretation

Contribution analysis:

Process	kg CO₂-eq	Share
Steel sheet production	7.04	72%
Electricity, grid	2.15	22%
Paint production	0.53	5%
Panel assembly (direct)	0	0%

Note that assembly causes 3 of the 5.7 kWh, so it’s responsible for about 1.1 kg CO₂-eq through its electricity use even though its direct emissions are zero. How you present contributions (by process, or by life cycle stage including upstream) changes the story. Say which one you’re showing.

Sensitivity: if the grid factor dropped from 0.35 to 0.05 kg CO₂/kWh (for example a renewable electricity contract), the total falls to about 8.01 kg CO₂-eq, a 17.6% cut. Steel remains the hotspot either way.

Conclusion: steel is the hotspot and should be the design team’s first target (less steel, or lower-carbon steel). Limitations: hypothetical data, transport and packaging excluded, climate change only.

ExplainerHypothetical teaching numbers

Unit cost vs carbon cost

1. Scene 1 of 6

   One painted steel panel

   Start with the bill of materials.

   InputQuantity

   Steel4 kg

   Paint0.25 kg

   Electricity (assembly)3 kWh

   The same list you already use for costing.

   The bill of materials for one painted steel panel: 4 kg of steel, 0.25 kg of paint and 3 kWh of electricity for assembly. It is the same list a costing team already uses.

2. Scene 2 of 6

   Price every line

   quantity × price = cost

   InputQuantity€

   Steel4 kg€3.20

   Paint0.25 kg€2.00

   Electricity3 kWh€0.45

   Per panel€5.65

   Unit costing: multiply each quantity by its price. Steel costs €3.20, paint €2.00 and electricity €0.45, so one panel costs €5.65.

3. Scene 3 of 6

   Give every line an emission factor

   quantity × emission factor = carbon

   Input€kg CO₂-eq

   Steel€3.207.942

   Paint€2.000.645

   Electricity€0.451.130

   Per panel€5.659.717

   Life cycle assessment uses the same list and the same maths, with an emission factor in place of the price. Steel gives 7.942 kg CO₂-eq, paint 0.645 and electricity 1.130, so one panel carries 9.717 kg CO₂-eq.

4. Scene 4 of 6

   Already inside the number

   The steel price already includes the mill’s energy bill.

   The steel emission factor already includes the mill’s emissions.

   A sketch of a steel mill sending 4 kg of steel to the panel. You do not add the mill’s energy bill to the price of steel, because the price already includes it. In the same way, the steel emission factor already includes the mill’s emissions. That is what cradle-to-gate means.

5. Scene 5 of 6

   Same list, different hotspot

   Steel’s share

   of cost57%

   of carbon82%

   Paint’s share

   of cost35%

   of carbon7%

   Steel is 57% of the panel’s cost but 82% of its carbon. Paint is 35% of the cost but only 7% of the carbon. The cost view and the carbon view point at different priorities.

6. Scene 6 of 6

   Unit costing for the environment

   Σ quantity × price = cost per unit

   Σ quantity × emission factor = impact per unit

   Same bill of materials. Same maths.

   Check every number by hand in LCA 101, lesson 8.

   Summary: the sum of quantity times price gives cost per unit; the sum of quantity times emission factor gives impact per unit. If you can cost a product, you can learn to assess it. Lesson 7 of LCA 101 works through these numbers by hand.

Exercise

Change the panel to use 3.5 kg of steel and 0.3 kg of paint. Recalculate the total and the steel share by hand, then open the answer below.

Answer

Electricity: 3 + 3.5×0.6 + 0.3×1.2 = 5.46 kWh. CO₂: 5.46×0.35 + 3.5×1.7 + 0.3×2.1 = 1.911 + 5.95 + 0.63 = 8.491 kg. CH₄: 5.46×0.0008 + 3.5×0.002 = 0.011368 kg. N₂O: 5.46×0.00001 + 0.3×0.0001 = 0.0000846 kg. Total: 8.491 + 0.33877 + 0.02310 = 8.853 kg CO₂-eq. Steel: 5.95 + 0.007×29.8 = 6.159, a 70% share.

What you should now be able to do

• Scale every process in a small product system to one functional unit.
• Turn an inventory into a climate change result with GWP factors.
• Run a contribution analysis and name the hotspot.
• Explain how a sensitivity case changes (or doesn’t change) the conclusion.