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Corporate Carbon Footprinting (CCF)

Updated Oct 24, 2026

Methods of Calculating Scope 3 Emissions

Scope 3 is calculated with spend-based, average-data, fuel-based, supplier-specific or hybrid methods. Compare accuracy, data needs and when to use each.

Summary

Scope 3 emissions are calculated by multiplying activity or spend data by an emission factor, or by using emissions data from suppliers. The GHG Protocol describes spend-based, average-data (activity-based), fuel- and distance-based, supplier-specific and hybrid methods. Most companies use spend-based data to screen, then move to supplier and activity data for their biggest hotspots.

What is the basic formula for Scope 3?

Most Scope 3 methods use one formula: activity data × emission factor = emissions. The difference between methods is what you use as activity data (money spent, kilograms bought, litres of fuel, or a supplier's own figures) and how specific the emission factor is.

The rules come from the GHG Protocol Technical Guidance for Calculating Scope 3 Emissions (2013), which sits alongside the Scope 3 Standard. New to Scope 3? Start with our main guide, what Scope 3 emissions are.

Which Scope 3 calculation methods are there?

There are five main approaches. The table compares them.

Method Activity data used Emission factor Accuracy Effort Best for
Spend-based Money spent on goods or services Average emissions per unit of spend (e.g. kgCO2e per US$) Low Low First screening of all categories; long-tail suppliers
Average-data (activity-based) Physical quantities, such as kg, litres or units bought Industry-average emissions per physical unit Medium Medium Key materials where you know quantities but not supplier data
Fuel- and distance-based Fuel used, or distance × weight moved Emissions per litre of fuel or per tonne-km Medium to high Medium Transport and distribution (categories 4 and 9), business travel
Supplier-specific A supplier's own product-level, cradle-to-gate emissions Supplied by the supplier High High Your largest suppliers and materials
Hybrid Supplier Scope 1 and 2 data plus activity data, with secondary data for gaps Mix of supplier and secondary factors Medium to high Medium to high Suppliers that can share some data but not a full product footprint

How does the spend-based method work?

The spend-based method multiplies what you spent on a product or service by an average emission factor per unit of spend. For example, spend on packaging is multiplied by a factor for the packaging sector.

Spend factors come from environmentally extended input-output (EEIO) models, which estimate emissions per unit of economic output for each sector. Examples include the US EPA's supply chain emission factors and the EXIOBASE database.

Pros: your finance system already has the data, and you can cover all categories quickly.

Cons: it is the least accurate method. It reflects sector averages and prices, not what you actually buy. If prices rise, your emissions appear to rise. If a supplier cuts its emissions, your figure does not change. Use it to screen, not to track reductions.

How does the average-data (activity-based) method work?

The average-data method multiplies the physical amount you buy, such as kilograms of sugar or tonnes of steel, by an industry-average emission factor for that material. The GHG Protocol calls this the average-data method. It is often called activity-based.

Pros: it is more accurate than spend because it follows physical flows, not prices. It also responds to real changes, such as buying less or switching materials.

Cons: you need quantity data, which is often held outside finance systems. The factors are still averages, so they don't show differences between suppliers, farms or regions.

How do the fuel-based and distance-based methods work?

These methods are used mainly for transport. The fuel-based method multiplies the fuel used by a carrier by the emission factor for that fuel. The distance-based method multiplies the weight moved by the distance travelled and a factor for the transport mode (tonne-km).

The GHG Protocol guidance suggests several ways to estimate fuel use when carriers don't report it:

  • Spend on fuel divided by the average fuel price.
  • Distance travelled and the vehicle's fuel efficiency.
  • Spend on transport services, the share of that cost that is fuel, and the average fuel price.

Pros: fuel data from carriers is quite accurate, and both methods show the effect of changing routes, modes or fuels.

Cons: carriers don't always share fuel data, and distance-based results rely on average load factors.

How does the supplier-specific method work?

The supplier-specific method uses product-level, cradle-to-gate emissions data provided by the supplier for the goods you buy. You multiply the quantity bought by the supplier's emissions per unit.

Pros: it is the most accurate method and the only one that reflects a supplier's own improvements. It shows clearly which suppliers drive your emissions.

Cons: many suppliers can't yet provide product footprints, and the quality of what they send varies. Collecting and checking this data across many suppliers takes time. Ask for the method and boundary used, so you can compare suppliers fairly.

How does the hybrid method work?

The hybrid method combines supplier data where you have it with secondary data for the gaps. According to the GHG Protocol guidance, it involves three steps:

  1. Collect Scope 1 and 2 data from suppliers, allocated to the goods or services you buy.
  2. Calculate upstream emissions from the supplier's own inputs, such as materials, fuel, electricity, transport and waste, using activity data and emission factors.
  3. Use secondary data to fill in upstream emissions where supplier data is missing.

Pros: it uses real supplier data without waiting for a full product footprint, so it is a practical middle step for many suppliers.

Cons: you still depend on suppliers to provide and allocate data, and you need a clear process to combine primary and secondary data.

What does a worked example look like?

Here is one purchase calculated two ways. All figures are made up to show the method and are not real emission factors.

Spend-based Average-data
Activity data US$1,000,000 spent on cardboard packaging 800 tonnes of cardboard bought
Emission factor (illustrative) 0.5 kgCO2e per US$ 900 kgCO2e per tonne
Calculation 1,000,000 × 0.5 800 × 900
Result 500 tCO2e 720 tCO2e

The two methods can give quite different answers for the same purchase. That is why you should disclose which method you used for each category, and why switching methods needs to be explained when you recalculate your baseline.

How do you choose the right method?

Use the most accurate method you can for the activities that matter most, and simpler methods for the rest. The Scope 3 Standard asks companies to focus effort on activities that are large, offer reduction opportunities, or are important to stakeholders.

A practical approach:

  1. Screen all 15 categories with spend-based data.
  2. Rank the results to find the categories, materials and suppliers that make up most of the total.
  3. Upgrade the hotspots to average-data, then hybrid or supplier-specific data.
  4. Use different methods within one category where it makes sense. In business travel, for example, flights and road travel can use different methods.
  5. Record data quality for each result and set a goal to raise the share of primary data each year.

Prioritising works. Princes, the food and drink group, found that its top five activities made up more than 60% of its emissions. That told the team where better data and supplier engagement would matter most. Read the Princes case study.

For why the data is often hard to get, see Scope 3 measurement challenges. For how Scope 3 fits with the wider carbon accounting picture, see methods of carbon accounting.

How Terrascope helps you calculate Scope 3

Terrascope lets you use more than one method in the same inventory and upgrade over time:

  • Screens all categories from spend and activity data, with AI matching each line to a suitable emission factor.
  • Combines spend-based, average-data and supplier-specific results in one model, with the method and data quality shown for each line.
  • Collects supplier data through Scope 3 supplier engagement tools, so you can move hotspots from averages to primary data.
  • Brings ERP and procurement data together with Terrascope data management.
  • Tracks method changes between years, so you can explain baseline recalculations.

Want to know which categories to upgrade first? Book a free value chain mapping workshop.

Frequently asked questions

What is the most accurate method for Scope 3?

The supplier-specific method, which uses product-level emissions data from your suppliers. It is also the most demanding, so most companies use it for their largest suppliers and simpler methods for the rest.

What is the difference between spend-based and activity-based?

Spend-based multiplies money spent by an emission factor per unit of spend. Activity-based (the GHG Protocol's average-data method) multiplies physical quantities, such as kilograms or litres, by an emission factor per unit. Activity-based is usually more accurate and reflects real changes in what you buy.

Can I use spend-based data for Scope 3 reporting?

Yes. The GHG Protocol allows it, and many companies use it for screening and for smaller suppliers. But it can't show supplier improvements, so it is weak for tracking reductions. Disclose where you used it.

Can I use different methods for different categories?

Yes. The GHG Protocol expects it. You can use different methods across categories and even for different activities within one category. Document the method used for each.

What is the hybrid method for Scope 3?

It combines supplier data, such as a supplier's allocated Scope 1 and 2 emissions, with activity data and secondary emission factors to fill the gaps. It is a practical step before suppliers can share full product footprints.

Talk to us about your Scope 3 methods

If you need to choose methods for a baseline, target or assurance, contact our team.

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