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Scope 3 emission factors

Scope 3 emission factors for reliable carbon footprinting

Our emission factor dataset helps you to calculate the most reliable, system-complete carbon footprint using your spend data. Easy to use, with inflation-adjustment already taken care of, basic and purchase prices to take account of taxes and shipping, and a full transparent methodology to give you the confidence that you can answer any question about every number you report.

The SWC MRIO is unique in the market because it delivers the following benefits to you:

  • Purchasers' prices as well as basic prices - really important if you want to avoid overestimating your footprint, as it can show more realistic, lower emissions per unit of spend.
     

  • Country of demand as well as country of supply - this provides a more granular understanding and improves the realism of your footprint, accounting for differences between where something is purchased and where it is made.
     

  • Scopes 1, 2, and 3 breakdown - allows you to swap in company-specific data, essential for capturing reductions in your reporting as your supply chain reduces emissions.
     

  • Time series - you get a time series going back over seven years, giving you the freedom to check progress on past reports, if any methodological changes have occurred. 
     

  • System complete – as input-output models are top-down, they are inherently system complete compared to LCA’s, which will always suffer from truncation error. Truncation errors vary for different products; it's typically around 26% for paper, but up to 45% for computer equipment. See the different typical truncation errors in different sectors here.
     

  • Country coverage – 79 countries covered (non-estimated) to give you a reflection of your unique supply chain, not averages of UK purchases.
     

  • Sector coverage granularity – 102 sectors, representing a reasonable reflection of available data.
     

  • Radiative forcing for avaiation - this can add significant emissions to some sectors.
     

  • Standards compliant - Scope 3 emissions data in line with leading global standards, including GHG Protocol, SBTi, CDP, and ISO 14064.

Other MRIO databases might have some of these elements, but few (if any) contain all of these essential qualities, which together give you the very best estimate of your company’s carbon footprint.

Start with quality data, and you're set up to reach the best carbon targets available to you.

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Our guide to carbon accounting

How to use spend-based, activity-based and Product Carbon Footprints in your carbon footprint.

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Why should I measure my Scope 3 emissions?

The benefits to your business of reliable Scope 3 reporting and how to lower supply chain emissions.

SWC MRIO v3.0

Choose your dataset

One key benefit of the SWC MRIO is being able to ask the team any queries about any of the emissions factors, and they can talk us through their methodology in detail, unlike other 'black box' datasets.


Jane Hersey, Group Sustainability Reporting Manager, Savills.

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Support with your spend-based carbon footprinting


These documents give best-practice guidelines on using the SWC MRIO, how to use it to hybridise product carbon footprints (PCFs) so you can use them comparably in the same carbon footprint, and our full methodology.
 

Small World support days


Any SWC MRIO licence gives you a personal tuition and consultancy package worth up to £2,500 included in the fee. This upskills your carbon team, ensures your organisation is following best-practice carbon accounting and gives you answers for any queries about your carbon data by stakeholders, clients or auditors. 

Answers for auditors

Our specialists can be available to answer any queries from auditors or other stakeholders that you disclose your carbon accounts to, allowing you to provide evidence and explanations for every calculation in your emissions data.
 

We're happy to offer support days as an optional extra to anyone using our SWC MRIO Free.

 

Things we can help you with include:

  • Advice on how to gather your spend data and match it to the sectors in the model.

  • Specific use cases for your organisation and your supply chain.

  • Advice on individual spend data, when best to use supply basis, and when to use demand basis.

  • Examining your data to decide when to use basic prices and when to use purchasers' prices.

  • Allocating the most appropriate proxy for countries not in the model.

  • Bespoke inflation updates for an individual country.

  • Addressing any queries from auditors or other stakeholders.


 

What's new in SWC MRIO v3.0?

 

  • Updated underlying datasets for 2018, 2019, 2020, 2021 and 2022.

  • Inflation-adjusted data for 2023 and 2024.

  • Now covers 79 countries, up from 75 - new primary data for the United Arab Emirates, Angola, São Tomé and Príncipe, and the Democratic Republic of the Congo.

  • Increased OECD sector breakdown from 45 to 50. 

Improvements in methodology


Increased sector granularity: OECD data now has 50 sectors, up from 45. Of particular significance are the splits into mining and metals, with iron and steel now separate from other ferrous metals; agriculture now separated from forestry; and shipbuilding being separated from transportation. However, UK ONS data now combines metal products and weapons. Our sector total of 102 gives the greatest degree of granularity balanced with the realistic limitations of the available data. Our methodology shows how we upscale to 102 sectors. We recommend asking for a similar methodology if you are comparing other models with a greater number of sectors. 


Maritime shipping emissions: For some countries, our models showed shipping emissions quite a bit higher than those self-reported by the industry. Since v1 of the SWC MRIO, the OECD has also published a maritime model with higher emission levels, supporting our findings. Many countries do not adequately account for ships that sail under another country's flag, even when the ship is owned by them. This often leads to under-reporting for shipping emissions. Our new model contains improved and realistic shipping emissions backed by the OECD’s estimates.

Emissions from oil and gas leaks: Finding data on fugitive emissions, specifically leaks and discharges in the fossil fuel industry, is understandably difficult. Even when totals are known, it is still difficult to assign these to the appropriate industries as emissions can occur anywhere during extraction, processing, and transport. We've employed higher-quality data from the UK and used this to inform improved estimates of fugitive emissions in other countries.

Fluorinated gases: These gases are only used in a few specific industries and account for a small share of emissions but compared to CO₂ they have a very high GWP (global warming potential). Here we have again made use of high-quality data from the UK in order to inform a more refined mapping of these gases to the appropriate industries, thus improving our emissions factors.

Radiative forcing factor for aviation: The UK's DESNZ (Department for Energy Security and Net Zero) has reduced the recommended radiative forcing factor for the non-CO₂ effects of high-altitude flying since our first model, so we've updated our aviation emissions factors accordingly.

Our datasets are used by

Sage
National Trust
Cogo
Ecologi
Pawprint
Compare Your Footprint
Go Climate Positive
Recorra
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Download the free SWC MRIO v3.0

Fill in the form below to download the free SWC MRIO v3.0 dataset for 2023:

Ask for a SWC MRIO Custom
or SWC MRIO Pro licence

SWC MRIO Custom

SWC MRIO Pro

Tell us a few details about your organisation and we'll get in touch to arrange a call with our MRIO specialists to talk about the data you need and agree your licence details.

Choose your licence

Thanks for requesting a licence, we'll aim to reply in less than a week.

FAQs about the SWC MRIO

What data does the SWC MRIO use?

What’s the difference between CD and CS figures?

What format is the data in?

Which years does the data cover and when is the next update?

Which 79 countries does the model contain?

Do 102 sectors give enough granularity?

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