The 15 Scope 3 Categories Explained
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Upstream (categories 1-8)
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To get started, your team uploads ERP and invoice data to Bardo's secure dataroom. Bardo handles the enrichment step, including cleaning up messy data from multiple sources, then structuring and mapping it for calculation workflows.
To get started, your team uploads ERP and invoice data to Bardo's secure dataroom. Bardo handles the enrichment step, including cleaning up messy data from multiple sources, then structuring and mapping it for calculation workflows.
.svg){kind=small}
To get started, your team uploads ERP and invoice data to Bardo's secure dataroom. Bardo handles the enrichment step, including cleaning up messy data from multiple sources, then structuring and mapping it for calculation workflows.
.svg){kind=small}
To get started, your team uploads ERP and invoice data to Bardo's secure dataroom. Bardo handles the enrichment step, including cleaning up messy data from multiple sources, then structuring and mapping it for calculation workflows.
.svg){kind=small}
To get started, your team uploads ERP and invoice data to Bardo's secure dataroom. Bardo handles the enrichment step, including cleaning up messy data from multiple sources, then structuring and mapping it for calculation workflows.
.svg){kind=small}
To get started, your team uploads ERP and invoice data to Bardo's secure dataroom. Bardo handles the enrichment step, including cleaning up messy data from multiple sources, then structuring and mapping it for calculation workflows.
.svg){kind=small}
To get started, your team uploads ERP and invoice data to Bardo's secure dataroom. Bardo handles the enrichment step, including cleaning up messy data from multiple sources, then structuring and mapping it for calculation workflows.
.svg){kind=small}
To get started, your team uploads ERP and invoice data to Bardo's secure dataroom. Bardo handles the enrichment step, including cleaning up messy data from multiple sources, then structuring and mapping it for calculation workflows.
Downstream (categories 9-15)
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To get started, your team uploads ERP and invoice data to Bardo's secure dataroom. Bardo handles the enrichment step, including cleaning up messy data from multiple sources, then structuring and mapping it for calculation workflows.
.svg){kind=small}
To get started, your team uploads ERP and invoice data to Bardo's secure dataroom. Bardo handles the enrichment step, including cleaning up messy data from multiple sources, then structuring and mapping it for calculation workflows.
.svg){kind=small}
To get started, your team uploads ERP and invoice data to Bardo's secure dataroom. Bardo handles the enrichment step, including cleaning up messy data from multiple sources, then structuring and mapping it for calculation workflows.
.svg){kind=small}
To get started, your team uploads ERP and invoice data to Bardo's secure dataroom. Bardo handles the enrichment step, including cleaning up messy data from multiple sources, then structuring and mapping it for calculation workflows.
.svg){kind=small}
To get started, your team uploads ERP and invoice data to Bardo's secure dataroom. Bardo handles the enrichment step, including cleaning up messy data from multiple sources, then structuring and mapping it for calculation workflows.
.svg){kind=small}
To get started, your team uploads ERP and invoice data to Bardo's secure dataroom. Bardo handles the enrichment step, including cleaning up messy data from multiple sources, then structuring and mapping it for calculation workflows.
.svg){kind=small}
To get started, your team uploads ERP and invoice data to Bardo's secure dataroom. Bardo handles the enrichment step, including cleaning up messy data from multiple sources, then structuring and mapping it for calculation workflows.
Where most of your footprint lives
For services-oriented companies, investment firms, and multi-entity groups, Category 1 (Purchased Goods & Services) is where the bulk of emissions concentrate. Most of what your company buys gets counted here: from office supplies and IT equipment to consulting fees and raw materials.
This is also the category where measurement method matters most. A spend-based approach assigns the same emission factor to every dollar spent in a category. An activity-based approach identifies the actual product and matches it to specific lifecycle data.
Spend-based vs activity-based: why the method matters
The GHG Protocol allows multiple calculation approaches for Scope 3. The choice of method directly affects the quality and usefulness of your data.
The problem
The accuracy gap in Category 1
When a company buys 100 MacBook Airs at €1,199 each, a spend-based estimate assigns the generic "Office machinery and computers" emission factor to the total spend, lumping ultralight laptops with servers and industrial PCs. The result: 340 kg CO2e per unit. An activity-based approach identifies the exact model (MacBook Air M5, 13") and uses Apple's published LCA data: 119 kg CO2e per unit. The spend-based method inflates the result by nearly 3x.
The difference compounds. Across a procurement portfolio of thousands of suppliers and millions in spend, spend-based estimates consistently inflate totals, misallocate emissions across categories, and hide the real hotspots.
Read more: How product carbon footprints work at the transaction levelSpend-based vs activity-based: why the method matters
The GHG Protocol allows multiple calculation approaches for Scope 3. The choice of method directly affects the quality and usefulness of your data.
Spend-based
Activity-based
What CSRD expects from your Scope 3 data
Under CSRD and ESRS E1, companies must report Scope 3 emissions that can withstand external assurance. The current requirement is limited assurance, but even that demands traceable, documented calculations, something spend-based estimates struggle to survive.
In practice, this means:
- A traceable path from invoice → what was bought → reported emission
- Documented emission factors with source, method, and quality rating
- Consistent scope boundaries and category definitions year over year
Spend-based estimates end at a category-level average with no connection to actual purchases. Under these requirements, that is increasingly difficult to defend. The direction of regulation is clear: more granularity, more traceability, more accountability.
Try for yourself
See what we'd find in your data.
Talk to our team
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