How we increase accuracy in scope 3 measurement

When calculating emissions: details matter

Increasingly corporations are required by law to report their emissions to regulators. In practice, this means they need to use credible calculation logic – most commonly by following the Greenhouse Gas Protocol standards – and provide auditable data sources to back up calculation results.

As one example, the EU’s CSRD regulation, which affects many corporations starting in 2024, requires companies to receive limited assurance for their emissions reports (source).

The pressure to produce audit-grade reports has only increased as corporations who reduce their reported emissions over time increasingly receive financial benefits.

Some examples of the financial impact of reducing emissions:

  1. Avoiding painful fines:
    1. The ECB has threatened daily fines up to 5% of annual revenue for banks who are not compliant with regulations to report emissions from their loan portfolios (source)
  2. Reducing the cost of carbon taxes:
    1. The EU’s cap and trade ETS scheme expanded in 2024, and now covers emissions from maritime shipping (source)
      1. This is already incentivizing large regulated enterprises to find lower carbon solutions to reduce their tax bill – for example, Nestle is now working with Maersk to reduce it’s shipping emissions using alternative fuels (source)
    2. The UK and California have similar cap-and-trade policies in place
  3. Retaining and winning enterprise buyers:
    1. Enterprises like Salesforce.com have committed to reducing their emissions by signing up to the Science Based Targets Initiative, and now require suppliers to contractually commit to doing the same. Such internal policies can have a cascading effect within entire supplier ecosystems (source)
Photo by Barney Yau on Unsplash

The Good News: Increasing accuracy enables reductions.

The GHG Protocol sets out three levels of data granularity, and provides guidance that companies use the most granular data that is available and accurate for their situation:

  1. Primary data at the product/service level reported by a supplier
  2. Primary data reported at the company-level
  3. Secondary average emission factors

Most carbon accounting software use EEIO emission factors compiled by environmental researchers out of the box. While this is an acceptable method by the GHG Protocol standard, and a reasonable starting point in a decarbonization journey, in practice many of these EFs are several years old and unhelpfully broad. This means they are less accurate and often overestimate emissions compared to more current and granular emissions data.

In addition to being less accurate, companies that use these emission factors to estimate their scope 3 emissions don’t get credit when their Scope 3 counterparties reduce their emissions. This means the only way to reduce your Scope 3 procurement emissions in the short term is to reduce your procurement spend – not exactly actionable advice!

On the other hand, if product or company-level emissions data is available, companies can increase their report accuracy while getting credit for reduction actions taken by their Scope 3 counterparties.

So Why Don’t All Companies Use Primary Data?

If using more granular primary data instead of average emission factors increases the accuracy of a report and can help reduce a company’s reported emissions, why doesn’t every company do it?

Companies increasingly publish primary emissions data, but these reports are complicated to acquire and use. This is because most managers don’t know how to translate unstandardized emissions reports into useful data and actions, and suppliers hate responding to surveys.

How DitchCarbon Simplifies the Scope 3 Challenge

We start by taking the pain out of acquiring company-reported carbon data, by aggregating data from many fragmented sources, and normalizing it to Greenhouse Gas Protocol standards.

We then provide tools that automate Scope 3 measurement and simplify carbon reduction decisions for both sustainability professionals and operational employees.

Depending on your use case and available input data, DitchCarbon can provide manufacturer-reported data and solutions at the product or company-level-level, as well as industry average EEIO emission factors when more granular data is not available, to complete coverage.

In practice, this means our products are:

  1. Auditable: with original data sources provided
  2. Accurate: aligned with the GHG Protocol
  3. Comprehensive: automatically delivering the broadest coverage while using the most granular primary data when available and appropriate for your use case

We handle common issues with Scope 3 data so you don’t have to, and our team is available to help you pick the best tool for your use case.

Feel free to ask questions via email or book a time to speak.

Our Methodologies

DitchCarbon’s Organization-level data gives you the full picture on an organization from an emissions perspective. Use it for pulling primary data into your Scope 3 calculations, benchmarking, and action planning to reduce emissions with Scope 3 counterparties.

Access and export data within your preferred application or ERP via API, or in the DitchCarbon web app.

Inputs accepted for entity resolution:

  1. Organization Name
  2. Industry
  3. Headquarter Country/Region
  4. Website domain
  5. Stock ticker

We provide organization-reported primary data when it’s been disclosed, and always provide average industry-level emission factors for use as fallbacks and comparisons:


Company disclosures are captured and normalized to the GHG Protocol standards leveraging:

  1. Artificial intelligence in the data extraction phase
  2. Machine validations of captured data against our previously validated database
  3. Human review of potential anomalies

Our data extraction engine automatically handles common issues that enterprises encounter when trying to use primary data that cause emissions reports to fail audits. Example issues we often correct:

Reported emissions figures not aligned with GHG Protocol reporting standards

Reductions from carbon offsets should be reported separately from total emissions numbers according to the GHG Protocol. In practice, companies sometimes report a Net Emissions figure as their Total Emissions without documenting the difference. DitchCarbon presents the cleaned GHG-aligned total in our web app, and provides it along with the original company-reported data via API or CSV export. This helps you avoid issues when using company-disclosed data.

Unclear units

Reported units are captured and normalized to kgCO2e. In cases where units are not clear due to poor reporting structure, units are inferred by comparing to benchmark industry emission factors in our existing dataset.

Incorrect category naming

Companies sometimes report emissions categories that are not aligned with the GHG Protocol, including combining Scope 3 categories together. DitchCarbon’s artificial intelligence automatically normalizes reported categories to GHG Protocol standard categories while filtering unusable data points.

Correcting emissions factors for proper use cases

We simplify Scope 3 measurement and benchmarking by providing 3 company-level emission factors and one industry-level emission factor out of the box, and guidance on the correct use case for each one. For example, using an emissions factor with upstream Scope 3 emissions included is appropriate for a procurement spend emissions calculator, but an asset manager evaluating automotive manufacturers should also consider downstream Scope 3 emissions to take vehicle efficiency into account.

Industry average spend-based emission factors are often used in the first step of the emissions reduction journey to quickly identify areas of focus, and later to fill in gaps where primary data is not available.

DitchCarbon provides 200 industry emission factors for 43 countries and 5 global regions.

Emission factors are generated from EEIO data published by environmental researchers and government agencies at DEFRA, the US EPA, and Exiobase. The specific source used depends on the emission factor requested, and sources are always cited in our web app and API responses.

Because these datasets are updated irregularly, they need to be adjusted for changes over time in inflation and grid intensity to be useful.

Country-level industry emission factors are:

  1. Adjusted for Inflation and exchange-rate using data from the Bank of England
  2. Adjusted for changes in grid intensity overtime. Government-reported national grid intensities are used, and each industry is adjusted based on the share of that industry’s emissions that are generated from the electrical grid, using data from the EU27 Input-Output Database

Regional average emission factors are:

  1. Provided where country-level emission factors are not available. These are calculated using a GDP-weighted average, using data from the World Bank
  2. Used in cases where Exiobase country-level data is anomalously high

For purchases of fuels and electricity, unit-based emissions factors are used to ensure accuracy and auditability.

For categories of electricity:

  1. Country-level emissions/kwh are used, and converted into spend-based emission factors using annual national average price/kwh data

For categories of fossil fuels, such as coal, kerosene, fuel oil, and natural gas:

  1. Spend-based emission factors are used to calculate Scope 3 emissions from extraction and distribution
  2. Unit-based emission factors are used to calculate Scope 1 emissions. These are converted into spend-based emission factors using annual national average price/unit data

The DitchCarbon Score enables professionals and non-sustainability experts to easily evaluate whether Organizations are taking action and if they compare favorably with their peers and benchmarks.

All data points used are provided in our Organization API response. Use our score out of the box to enable carbon-aware decisions within your operations, or leverage our data and methodology to improve your own score.

The Score leverages proprietary algorithms to analyze dozens of data points specific to a supplier and calculates their score between 0 and 100.

We believe that transparent decision-making criteria enables you to make better decisions, and helps your Scope 3 counterparties to improve.

This is why we disclose the factor categories and relative weights that the DitchCarbon Score takes into account. Organization scores improve when they have:

Apple Example:

Apple’s score for 2023 is 61. They are in a moderate emitting industry, and have made progress by disclosing all relevant emissions categories consistently, signing up to STBI near term targets, and reducing their emissions in 2022. The most impactful steps they can take to continue to improve are reducing emissions and emissions intensity consistently for the next few years, and setting an SBTI Net Zero target:

The Product API helps you determine emissions from product purchases using manufacturer-reported data where available. Access via DitchCarbon’s API inside your preferred application.

Leading procurement tech firms are using it within their guided buying applications to enable their enterprise customers’ buyers to understand the emissions of products before purchase, and generate auditable emissions data alongside purchase orders to streamline end-of-year carbon accounting.

In line with the GHG Protocol standard, the Product API provides data at three levels of granularity, automatically providing the most granular data available based on what manufacturers have disclosed:

  • Manufacturer-reported product-level data
  • Manufacturer-reported supplier-level calculation, using a spend based method
  • Category-average spend based calculation

For product-level disclosures, we provide both the original manufacturer-reported carbon footprint and a modified value that uses DitchCarbon’s model to consider aspects that have changed since the manufacturer’s declaration (e.g. grid intensity) to provide a more accurate estimate.

When category-average spend-based calculations are made, DitchCarbon uses EEIO data on the economic value of purchased goods and services and applies an emission factor per currency unit. Emission factors are adjusted from original sources for inflation and exchange rates where applicable.

DitchCarbon’s API provides the data method that was used for a calculation, along with the original source emissions disclosure, ensuring auditability.

The Expense API helps you estimate from activities, such as using fuel in your business, purchasing electricity from your local grid, or business travel nights spent at a hotel.

Leading Environmental, Health, and Safety SaaS platforms use the Expense API to help their users estimate their emissions based on fuel usage and electricity consumption.

We start with EEIO estimates provided by economic researchers and government agencies.

Released by, amongst others the US EPA and the UK’s Defra, these are among the most commonly used emission factors by carbon accounting tools.

Given these emission factors are not updated annually, we’ve updated them based on changing national grid carbon intensities and currency inflation rates. We calculate at a region, country and state level, providing greater granularity for grid emissions where possible.

Organization level data

  • Company name
  • HQ country
  • Website
  • Industry
  • Stock Ticker
  • Spend (if using web app)
  • Organization-level emission factor
  • DitchCarbon score
  • Current and historical disclosures 
  • SBTI, CDP, and UNGC status
  • Reduction Action Co-Pilot
  • Peer comparisons
  • Industry benchmark 
  • Sources for all data points

Product Level Data

  • Product name
  • Product manufacturer
  • Location of use
  • Quantity
  • Price (used as fallback)
  • Product carbon footprint (if disclosed)
  • Breakdown of stages of use
  • Method of calculation used
  • Organization-level spend or category-level spend (if not disclosed)
  • Sources of all data points

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DitchCarbon are great partners; Our customers are excited about getting the data they need to drive more sustainable decision making.
- Ryan @SAP Ariba

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