Which Emission Factor Database Should You Use for Scope 3? (EEIO vs LCI vs Sector Specific)

Choosing emission factors isn’t one size fits all. The right source depends on your data (spend vs activity vs product, your geography, and whether you need supplier specific insights for reductions. This guide compares EEIO, LCI, and sector methods, with pros/cons for the most used sources, including DitchCarbon for supplier specific factors.---## Quick glossary- EEIO (spend based): Average intensities per currency for economic sectors. Fast coverage; lower specificity.- LCI (process/product): Inventory datasets for materials, processes, and products. High specificity; more effort.- Sector methods: Category specific standards (e.g., freight, aviation) with activity factors and calculation rules.- Supplier specific: Factors mapped to your actual vendors/SKUs, enabling targeted reduction with procurement.---## Decision matrix| Your situation | Best starting point | Add for accuracy | What unlocks action || ------------------------------------------------------ | ----------------------------------------------------------- | ------------------------------------- | ------------------------------------------------------------------ || “We only have spend by vendor/category.” | EEIO (EPA USEEIO; UK DESNZ/Defra spend) | LCI for material hot spots | DitchCarbon to map spend to supplier specific factors || “We have activity data for freight/travel.” | Sector methods (GLEC, ICAO) | Country factors (Defra, ANZ) | DitchCarbon to engage logistics providers/suppliers || “We’re redesigning products or negotiating materials.” | LCI (ecoinvent, Sphera/GaBi, EF/PEF, ADEME) | Country factors (for utilities/waste) | DitchCarbon to connect product factors to real suppliers || “We need audit ready corporate coverage fast.” | National sets (Defra/DESNZ, ANZ) | GLEC for logistics | DitchCarbon to prioritize suppliers and track reductions |---## Quick comparison (top options)| Source | Type | Strength | Typical use | Watch outs || ------------------------- | -------------------------------------- | ------------------------------------------------------- | -------------------------------------------- | --------------------------------------- || DitchCarbon | Supplier specific platform | Vendor/SKU level Scope 3 factors; procurement workflows | Turning averages into supplier level actions | Needs integration + supplier data depth || UK DESNZ/Defra | Company factors (incl. spend/activity) | Broad, auditor familiar | Corporate coverage, UK + global | UK centric averages; not product LCI || US EPA WARM/USEEIO | Waste model + EEIO | Waste scenarios; spend based breadth | US coverage, screening | US centric; averages vs supplier data || ecoinvent | LCI | Product/process depth | Purchased goods/services; LCA | Paid license; complexity || GLEC (Smart Freight) | Sector method | Logistics standardization | Freight emissions | Methodology ≠ huge factor table || EU EF/PEF | LCI | EU aligned product footprints | EU suppliers/customers | Patchy category coverage || ADEME Base Carbone | Activity + LCI mix | Public, frequent updates | FR/EU corporate | French first docs/locality || ICAO | Sector method | Travel/air freight calc | Business travel/air cargo | Non CO₂ often added via policy uplift || Sphera/GaBi | LCI (commercial) | Industrial depth | Product Scope 3 | Cost; dataset transparency varies || ANZ (NZ MfE + AU NGA) | Company factors | Official regional coverage | NZ/Australia | Regional assumptions |---## What to use## by model type### EEIO leaders (fast coverage, lower specificity)- US EPA USEEIO, UK DESNZ/Defra spend categories, ANZ national sets Pros: Quick wins across Purchased Goods & Services and services categories. Cons: Averages can obscure supplier differences, use for screening, then refine.### LCI leaders (high specificity, more effort)- ecoinvent, Sphera/GaBi, EU EF/PEF, ADEME Base Carbone Pros: Product/material insight for design, sourcing, and negotiation. Cons: Requires tooling and expertise; licenses (commercial sets).### Sector methods (activity data first)- GLEC (freight), ICAO (aviation) Pros: Standardized methods; good for carrier/route comparisons. Cons: Works best with primary activity data (tonne km, fuel, load).### Supplier specific (actionable reductions)- DitchCarbon Pros: Converts spend/activity/product info into supplier specific factors; enables category and vendor prioritization, measurable reduction plans. Cons: Requires integration and supplier participation to deepen coverage.---## Pros & cons (profiles)### DitchCarbon (Supplier specific platform)Pros: Vendor/SKU level factors; procurement ready; integrates with ERPs/AP, sourcing, and data warehouses; supports supplier engagement and tracking.Cons: Commercial license; coverage depth grows with supplier data.Best for: Turning Scope 3 from averages into supplier action.### UK DESNZ/DefraPros: Broad categories; clear annual updates; auditor friendly.Cons: UK averages; not product LCI.Best for: Fast corporate coverage; UK/EU heavy companies.### US EPA WARM/USEEIOPros: Waste scenario modeling (WARM); spend based breadth (USEEIO).Cons: US centric; averages vs supplier.Best for: US reporters; screening + waste decisions.### ecoinventPros: Extensive product/process datasets; global coverage.Cons: License cost; learning curve.Best for: Purchased materials and product level Scope 3.### GLEC (Smart Freight Centre)Pros: ISO aligned method for multimodal freight; common language with carriers.Cons: Not a giant factor table; needs activity data.Best for: Logistics programs and carrier alignment.### EU EF/PEFPros: EU aligned product data; supports PEF customer asks.Cons: Coverage varies; access via LCA tools.Best for: EU supplier/customer requirements.### ADEME Base CarbonePros: Public, frequently updated; broad activity coverage.Cons: Localized assumptions, French first docs.Best for: France based reporting; EU contexts.### ICAOPros: Recognized for flight emissions; route/aircraft assumptions.Cons: Non CO₂ impacts often handled via policy uplift.Best for: Business travel and air freight estimates.### Sphera/GaBiPros: Industrial LCI depth; annual refresh; strong tooling ecosystem.Cons: Commercial; variable transparency.Best for: Complex product chains and supplier dialogues.### ANZ (NZ MfE + AU NGA)Pros: Official national factors; Scope 3 coverage for regional needs.Cons: Regional specificity.Best for: NZ/Australia entities and global firms with ANZ spend.---## How to implement (simple path)1. Screen: Use EEIO/national sets for full coverage.2. Standardize logistics: Apply GLEC; use activity data where possible.3. Deepen critical materials: Add ecoinvent/Sphera/GaBi/EF/PEF.4. Make it actionable: Layer DitchCarbon to convert averages into supplier specific factors and reduction roadmaps.---## FAQsCan I mix multiple sources?Yes: start broad (EEIO/national), add sector methods for logistics, add LCI for key materials, and use DitchCarbon for supplier specific action.What if my data is just invoices?Map spend to EEIO/national factors for coverage and use DitchCarbon to identify where supplier specific factors will move the needle.How often should I refresh factors?At least annually for national sets/LCIs; update supplier specific factors as vendors share new data or you change products/suppliers.---Next step: Explore how DitchCarbon turns your spend and supplier master data into prioritized Scope 3 reductions.