Process Modeling Cookbook: Electricity, Transport & Manufacturing
Practical recipes for modeling common LCA processes—regional electricity grids, transportation in complex supply chains, cement and concrete, and more.
Prerequisites:
Process Modeling Cookbook
"How do I model electricity consumption with regional grid mixes?" and "How do I account for transportation in complex supply chains?" are hands-on questions every practitioner faces. This cookbook provides practical recipes for common modeling challenges.
Recipe 1: Electricity with Regional Grid Mixes
The Challenge
Electricity impacts vary dramatically by region:
- Norway: ~20 g CO₂/kWh (hydro)
- France: ~60 g CO₂/kWh (nuclear)
- Germany: ~400 g CO₂/kWh (coal + renewables)
- Poland: ~700 g CO₂/kWh (coal)
Using the wrong grid mix can completely change your results.
Basic Recipe: Using Database Grid Mixes
Step 1: Identify the correct regional electricity process
In ecoinvent, electricity processes are named:
market for electricity, [voltage] | electricity, [voltage] | [location]
Voltage levels:
- High voltage: Transmission (large industry)
- Medium voltage: Distribution (manufacturing)
- Low voltage: End use (offices, homes)
Example selections:
| Need | ecoinvent Process |
|---|---|
| German factory electricity | market for electricity, medium voltage, DE |
| US consumer electricity | market for electricity, low voltage, US |
| Global average | market for electricity, medium voltage, GLO |
Step 2: Apply appropriate voltage transformation losses
If your data is in primary energy, convert:
Delivered electricity = Primary energy × Grid efficiency (~35-40%)
Most databases already account for this—check your process documentation.
Advanced Recipe: Custom Grid Mix
When needed:
- Your country isn't in the database
- You have site-specific renewable energy
- You want to model future grid scenarios
Step 1: Get generation mix data Sources:
- IEA Electricity Information
- Ember Climate (free)
- National grid operator
- Company energy bills (for site-specific)
Step 2: Create custom process in openLCA/SimaPro
Custom process: "Electricity, medium voltage, Country X"
Inputs (per 1 kWh at medium voltage):
- Electricity, coal, at power plant: 0.45 kWh × 1.08 (losses) = 0.486 kWh
- Electricity, natural gas, at power plant: 0.30 kWh × 1.08 = 0.324 kWh
- Electricity, hydro, at power plant: 0.15 kWh × 1.08 = 0.162 kWh
- Electricity, solar, at power plant: 0.05 kWh × 1.08 = 0.054 kWh
- Electricity, wind, at power plant: 0.05 kWh × 1.08 = 0.054 kWh
Output:
- Electricity, medium voltage, Country X: 1 kWh
Note: The 1.08 multiplier accounts for ~8% transmission/distribution losses. Adjust based on actual regional data.
Recipe Variations
Scenario: On-site renewable energy
Site electricity = (% grid × grid process) + (% solar × solar process)
Scenario: Hourly matching (advanced) For time-sensitive analysis:
- Use hourly grid carbon intensity data
- Match consumption to generation profiles
- Consider marginal vs. average emissions
Quick modeling tip: For most studies, using the correct country-level grid mix from ecoinvent is sufficient. Custom mixes add effort—only create them when regional differences are significant and you have good data.
Recipe 2: Transportation in Complex Supply Chains
The Challenge
Real supply chains have:
- Multiple transport modes
- Varying distances
- Different vehicle types
- Return trips (often empty)
Basic Recipe: Single-Mode Transport
Formula:
Transport impact = Mass × Distance × Emission factor
Transport (tkm) = tonnes × kilometers
Database processes:
| Mode | ecoinvent Example |
|---|---|
| Truck (small) | transport, freight, lorry 3.5-7.5t |
| Truck (large) | transport, freight, lorry 16-32t |
| Rail | transport, freight train |
| Ship (ocean) | transport, freight, sea, container ship |
| Air | transport, freight, aircraft |
Example calculation:
Ship 5,000 kg of goods from China to Germany:
Step 1: Sea freight (Shanghai to Hamburg)
- Distance: ~20,000 km
- Transport: 5 t × 20,000 km = 100,000 tkm
- Process: transport, freight, sea, container ship
Step 2: Truck delivery (Hamburg to Munich)
- Distance: ~800 km
- Transport: 5 t × 800 km = 4,000 tkm
- Process: transport, freight, lorry >32t
Advanced Recipe: Full Supply Chain Logistics
Step 1: Map the logistics chain
Supplier → Port → Sea → Port → Warehouse → Factory
▲ ▲ ▲ ▲ ▲ ▲
Truck Truck Ship Truck Truck Internal
(40km) (100km) (50km) (300km)
Step 2: Create transport sub-model
| Leg | Mode | Distance | Load (t) | tkm |
|---|---|---|---|---|
| Supplier to port | Truck 16-32t | 40 km | 5.0 | 200 |
| Port handling | - | - | - | (use port process) |
| Sea freight | Container ship | 20,000 km | 5.0 | 100,000 |
| Port to warehouse | Truck 16-32t | 50 km | 5.0 | 250 |
| Warehouse to factory | Truck 7.5-16t | 300 km | 5.0 | 1,500 |
| Total | 101,950 |
Step 3: Account for packaging and empty returns
Transport with packaging:
- Gross weight = Product (5t) + Packaging (0.5t) = 5.5t
- All tkm calculated on gross weight
Empty return (if applicable):
- Return trip at 20-50% load factor = partial impact
- Or use round-trip database processes
Recipe: Multi-Modal Decision Tool
| Distance | Typical Mode | Impact (kg CO₂/tkm) |
|---|---|---|
| <100 km | Van/small truck | 0.15-0.30 |
| 100-500 km | Truck | 0.05-0.10 |
| 500-2000 km | Truck or rail | Truck: 0.05, Rail: 0.02 |
| >2000 km land | Rail | 0.02-0.03 |
| Ocean (bulk) | Ship | 0.003-0.010 |
| Ocean (container) | Ship | 0.010-0.020 |
| Air | Aircraft | 0.50-1.00 |
Rule of thumb: Air freight ≈ 50× ocean freight per tkm.
Don't forget the "last mile." Local delivery from warehouse to retailer to consumer can dominate transport impacts for light products due to small-vehicle inefficiency.
Recipe 3: Cement and Concrete Manufacturing
The Challenge
Cement and concrete are critical for construction LCA but complex to model:
- Cement production has high process emissions (calcination)
- Concrete mixes vary widely
- Regional differences are significant
Basic Recipe: Using Database Cement
ecoinvent cement processes:
| Process Name | Use Case |
|---|---|
| cement, Portland | General purpose |
| cement, blast furnace slag | Lower-carbon alternative |
| cement, pite calcium aluminate | Specialty applications |
| concrete, normal | Ready-mix concrete |
Simple concrete modeling:
1 m³ concrete ≈ 300-400 kg cement + 1,800 kg aggregates + 150 L water
Advanced Recipe: Custom Concrete Mix
Step 1: Get mix design data
Example ready-mix concrete (C30/37):
- Portland cement: 350 kg
- Fine aggregate (sand): 700 kg
- Coarse aggregate (gravel): 1,100 kg
- Water: 175 kg
- Admixtures: 3 kg
Step 2: Build custom process
Custom process: "Concrete, C30/37, Site-specific"
Inputs (per 1 m³):
- cement, Portland, local: 350 kg
- gravel, crushed: 1,100 kg
- sand: 700 kg
- tap water: 175 kg
- concrete admixture: 3 kg
- electricity, medium voltage: 5 kWh (mixing)
Output:
- Concrete, C30/37: 2,328 kg (≈1 m³)
Step 3: Add transport if not included
Transport of materials to batching plant:
- Cement from plant (50 km): 350 kg × 50 km = 17.5 tkm
- Aggregates local (20 km): 1,800 kg × 20 km = 36 tkm
Recipe: Low-Carbon Cement Alternatives
Supplementary cementitious materials (SCMs):
| SCM | Replacement Rate | CO₂ Reduction |
|---|---|---|
| Fly ash (coal) | 15-30% | ~15-25% |
| Blast furnace slag | 30-70% | ~30-60% |
| Silica fume | 5-10% | ~5-10% |
| Calcined clay | 20-40% | ~20-35% |
Modeling SCM blends:
Blended cement (CEM II/B-S):
- 65% Portland clinker
- 30% blast furnace slag
- 5% gypsum
Use weighted average of component impacts
GaBi vs. openLCA note: GaBi has proprietary cement/concrete databases with regional specifics. openLCA uses ecoinvent's processes. Results may differ—check your database documentation for included processes.
Recipe 4: Manufacturing Processes
Generic Manufacturing Model
Template for any manufacturing process:
Manufacturing process template:
Inputs:
├── Materials
│ ├── Main material input: X kg
│ ├── Auxiliary materials: Y kg
│ └── Packaging materials: Z kg
├── Energy
│ ├── Electricity: A kWh
│ └── Thermal energy: B MJ
├── Water
│ └── Process water: C L
└── Transport
└── Input materials: D tkm
Outputs:
├── Products
│ └── Main product: 1 unit
├── Co-products
│ └── Byproduct: E kg
├── Emissions (direct)
│ ├── CO₂: F kg
│ └── VOCs: G kg
└── Waste
└── Production scrap: H kg
Recipe: Metal Fabrication
Example: Steel component manufacturing
Process: Steel bracket manufacturing (1 unit = 0.5 kg)
Inputs:
- Steel sheet, cold rolled: 0.6 kg (20% scrap rate)
- Electricity (cutting, forming): 0.3 kWh
- Lubricant: 0.005 kg
- Compressed air: 0.1 kWh electricity
Outputs:
- Steel bracket: 0.5 kg
- Steel scrap (to recycling): 0.1 kg
- Waste lubricant: 0.005 kg
Recipe: Plastic Injection Molding
Process: Injection molded part (1 unit = 0.1 kg)
Inputs:
- Polypropylene granules: 0.108 kg (8% process loss)
- Electricity (molding): 0.8 kWh
- Water (cooling): 5 L (closed loop, minimal loss)
Outputs:
- Molded part: 0.1 kg
- PP scrap (recycled internally): 0.008 kg
Recipe: Assembly Operations
For assembly (often overlooked):
Assembly process (1 unit)
Inputs:
- Components: From upstream processes
- Fasteners: X units (screws, rivets, etc.)
- Electricity: 0.1-1.0 kWh (tools, conveyors)
- Packaging: Y kg
- Compressed air: via electricity
Note: Assembly is often <5% of manufacturing impact.
Consider cut-off if not significant.
Recipe 5: End-of-Life Modeling
Waste Treatment Selection
| Waste Type | Common Treatment | Database Process |
|---|---|---|
| Mixed municipal waste | Landfill + incineration | treatment of municipal solid waste |
| Plastic (sorted) | Recycling or incineration | treatment of waste polyethylene |
| Metal (sorted) | Recycling | treatment of scrap steel |
| Construction waste | Recycling or landfill | treatment of waste concrete |
| Hazardous waste | Specialized treatment | treatment of hazardous waste |
Recipe: Multi-Path End-of-Life
Scenario: Product with mixed materials going to multiple fates
Product end-of-life breakdown:
- Total mass: 1 kg
├── Steel (0.5 kg): 80% recycled, 20% landfill
├── Plastic (0.3 kg): 50% recycled, 30% incinerated, 20% landfill
└── Electronics (0.2 kg): 60% WEEE recycling, 40% landfill
Waste treatment processes needed:
- treatment of scrap steel: 0.5 × 0.8 = 0.4 kg
- treatment of steel to landfill: 0.5 × 0.2 = 0.1 kg
- treatment of waste plastic, recycling: 0.3 × 0.5 = 0.15 kg
- treatment of waste plastic, incineration: 0.3 × 0.3 = 0.09 kg
- treatment of waste plastic, landfill: 0.3 × 0.2 = 0.06 kg
- treatment of WEEE: 0.2 × 0.6 = 0.12 kg
- treatment of electronics to landfill: 0.2 × 0.4 = 0.08 kg
Common Modeling Pitfalls
Pitfall 1: Wrong voltage level for electricity
Wrong: Using high voltage for office building Right: Low voltage for offices, medium voltage for factories
Pitfall 2: Forgetting transport
Wrong: Materials appear at factory gate by magic Right: Include transport for all purchased materials
Pitfall 3: Double-counting recycling
Wrong: Recycled input burden-free AND recycling credit at end-of-life Right: Choose one approach consistently
Pitfall 4: Ignoring packaging
Wrong: Only modeling the product itself Right: Include primary, secondary, and tertiary packaging
Pitfall 5: Using annual instead of per-unit data
Wrong: "Factory uses 1 GWh/year electricity" Right: "Product uses 0.5 kWh/unit" (calculate from production volume)
Key Takeaways
- Electricity grid mix significantly affects results—use correct regional data
- Transport modeling requires mode, distance, and vehicle type
- Cement/concrete has high process emissions—use specific mix designs when available
- Manufacturing processes follow a template: materials + energy + water → product + waste
- End-of-life requires fate percentages for each material stream
- Document everything—assumptions, sources, and calculations
Modeling Checklist
For each process in your model:
☐ Correct geographic process selected ☐ Appropriate voltage level for electricity ☐ Transport included for material inputs ☐ Direct emissions estimated or measured ☐ Waste/byproduct treatment included ☐ Data scaled to functional unit ☐ Mass balance verified (inputs ≈ outputs)
Next Steps
With modeling recipes in hand, the next lesson covers Result Validation & Troubleshooting—how to check your results make sense and diagnose common problems.