Example 1: Carbon and Region-Specific Steel
User:
“I’m looking for low-carbon steel reinforcement from Asia.”
Possible Match Data:
Product: Steel, rebar, imported (Asia weighted average of BF/BOF and EAF production [scrap input = 29.9%])
Origin: Asia
Carbon Intensity: Medium (inferred from BF/BOF + 29.9% scrap input)
LCIA: Volume dependent [LCIA/m3]
Next query:
“Do you have options with higher recycled content?”
Possible Match Data:
Product: Steel reinforcement, primary, bar (Pacific Steel)
Origin: New Zealand
Carbon Intensity: Lower (assumed higher EAF process, local sourcing)
Recycled Content: Higher (inferred)
LCIA: Volume dependent [LCIA/m3]
Note: Not from Asia — tradeoff between recycled content and origin
Next query:
“Okay, then filter to only options made in Asia, even if scrap input is lower.”
🔍 Possible Match Data:
Product: Steel, rebar, imported (Asia weighted average of BF/BOF and EAF production [scrap input = 29.9%])
Product: Steel reinforcement, primary, imported (generic)
Origin: Asia (weighted), Generic
LCIA: Volume dependent [LCIA/m3]
Example 2: Polyethylene Membranes with Thickness Constraints
User:
“Show me polyethylene membranes for building wraps.”
Possible Match Data:
1. Membrane, building wrap, polyethylene (PE) (0.5 mm thickness)
LCIA Basis: Area dependent, to derive volume [m3/m2]
2. Membrane, building wrap, polyethylene (PE) (0.25 mm thickness)
LCIA Basis: Area dependent, to derive volume [m3/m2]
Next query:
“Which one provides more material per m²?”
Possible Match Data:
→ 0.5 mm membrane: 0.0005 m³ per m²
→ 0.25 mm membrane: 0.00025 m³ per m²
Result: 0.5 mm membrane provides double the material per area
Next query:
“Which is more environmentally efficient per unit volume?”
Possible Match Data (inferred or from LCIA if available):
→ 0.25 mm membrane has lower impact per m³ (less raw material)
→ Efficiency tradeoff: Less insulation, but lower footprint