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How our Scope 3 calculation works
Most Scope 3 calculations start with supplier surveys and spreadsheets. They're slow, patchy, and hard to audit.
We take a different approach. We maintain a large dataset of company emissions disclosures, normalised to GHG Protocol standards. We match your suppliers to that dataset, fill gaps with industry data, and give you audit-ready numbers you can use straight away.
We'll walk you through the methodology using live data, emission factors with Q&A
No supplier surveys to get started
Automated Scope 3 solution, implemented in weeks.
Most customers see ROI in under 6 months.
Most customers see ROI in under 6 months.
Most customers see ROI in under 6 months.
The calculation, step by step
We build your Scope 3 footprint through six connected steps. Each step improves coverage, accuracy and consistency.
Company emissions data is collected from public disclosures and verified sources. It's standardised and mapped to GHG Protocol categories.
Where company data is missing, industry averages are used. Ensures full coverage across all suppliers.
Emissions are calculated using spend, sector and activity. Uses company disclosures where available, with revenue-based factors where not.
Company emissions data is collected from public disclosures and verified sources. It's standardised and mapped to GHG Protocol categories.
Companies are mapped into parent and subsidiary relationships. Emissions are assigned to the correct entity.
Where company data is missing, industry averages are used. Ensures full coverage across all suppliers.
Supplier records are matched to a single company profile. Handles duplicates, naming differences and IDs such as DUNS.
Emissions are calculated using spend, sector and activity. Uses company disclosures where available, with revenue-based factors where not.
Each record includes source data, version history and QA checks. Estimates are replaced as better data becomes available.
Explore the methodology
This is the detailed documentation behind our calculation methodology. It's actively maintained, versioned and updated as standards, data sources, and coverage evolve. Every change we make is documented for backwards compatibility.
How companies are identified, matched and structured
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How emissions are calculated using company data and industry factors
How organisations are scored and compared with their peers
How emissions are estimated using industry data
How future emissions are projected using targets and scenarios
Organization Data
DitchCarbon aggregates disclosed emissions data, reduction targets, and initiative participation, and generates insights from that data - with no surveys required.
Organization level records provide the complete picture of an organization from a climate action perspective. Use them to:
- Pull primary data into Scope 3 calculations
- Forecast future emissions
- Segment and benchmark Organizations
- Determine highest leverage actions to reduce emissions with Scope 3 counterparties
Access and export data within the DitchCarbon web app, via API in your preferred application or ERP.
Organization Record Payload
Data is aggregated and structured into standardized formats, normalizing for units and various reporting styles to GHG Protocol Standards.
Summary of data available in an Organization record:
Entity Resolution: Matching User Requests to DitchCarbon Organization Records
Users may provide a combination of inputs:
Direct Match IDs enable a direct match to the corresponding entity in DitchCarbon's system. When no Direct Match ID is provided, a fuzzy match to records in DitchCarbon's database is attempted.
If fuzzy match confidence is high enough, the request will resolve to the relevant Organization. If match confidence is not high enough, the user request is moved to "waiting" status, providing the user with the opportunity to provide more input data to resolve the request.
Organization Data Cascading Down Corporate Trees
DitchCarbon maps user inputs to corporate legal entity trees to ensure complete coverage of climate action across the corporation, while precisely reflecting lines of corporate control.
A user's request may successfully resolve to a subsidiary Organization and corresponding legal entity in DitchCarbon's database.
If the subsidiary Organization has disclosed emissions data, set reduction targets, or signed up to initiatives we track, those data points are provided in the Organization record payload.
If the subsidiary Organization does not have a given category of data, but a parent in its corporate tree does, that data cascades down from the parent Organization to the subsidiary Organization.
To enable auditability, user requests show the requested Organization's legal name, the parent Organization's legal name, and the relationship between the two entities (eg, L2 parent, ultimate parent)
Example:
If a user requests Beats Electronics, the subsidiary Organization (Beats Electronics, LLC) does not have emissions data, targets, or initiative participation, but its parent (Apple, Inc) does Apple Inc's Scope 1-3 upstream emission factor, targets, and initiative participation cascade to the Beats request, and the "ultimate parent" relationship between the two entities is displayed.
See example request, with subsidiary and parent Organization relationship type displayed:
Data Ingestion
Our automated extraction engine and human QA process handles common issues that users of primary emissions data encounter regularly:
- Differentiation between gross and net emissions disclosures in separate fields
- Normalization of reported units to kgCO₂e
- Mapping disclosed categories to GHG Protocol standard categories, flagging unusable data points
- Human checking of validation warnings triggered by anomalous data
Portability
All data is exportable in structured format via xls/csv.
Original source links are provided, and mirror urls of documents saved on DitchCarbon servers are also provided (to ensure auditability if documents are moved). See sample reduction target export:
Organization Specific Spend Based Emission Factors
DitchCarbon generates up to three different organization level emission factors per organization for each year. Emission factors are based on the organization's disclosed global consolidated revenue and global emissions data.
Emission factors are only generated if all minimum data requirements are met. If all minimum requirements are not met, the related emission factor fields will be left blank.
Emission factors are disclosed in kgCO₂e/USD.
Methodology for Determining Relevant Scope 3 Categories by Industry
Organization records have a primary Industry. Each Organization disclosure is checked against the relevant criteria for a company within its Industry.
For relevance criteria, CDP's Scope 3 Technical Note is used for 16 heavy emitting industries.
For industries that CDP does not cover, their meta-analysis methodology is borrowed to determine relevant categories. This was done by evaluating significant samples of the global emissions reports of publicly listed companies disclosing scope 3 category detail within our database. Only reports disclosed in 2022 or later were considered in the meta-analysis.
Revenue Data: Sourcing and Traceability
Annual revenue data is sourced from S&P Global, which provides revenue sourced from financial disclosures and converted into USD. This accounts for >99% of DitchCarbon's revenue data.
In cases where S&P Global revenue data is not available for large/listed companies, DitchCarbon may acquire revenue data disclosed directly on the organization's website. This accounts for <1% of DitchCarbon's revenue data.
In all cases, original source urls are retained and provided to users for audit purposes.
Organization Emissions Data: Sourcing, Traceability, and Entity Resolution
Emissions data is extracted from Documents disclosed by Organizations.
Documents may be discovered as annual reports disclosed online in PDF or other formats, data disclosed in html on Organization websites, or as reports submitted directly to DitchCarbon.
Original sources are retained, and a copy of each document is saved on DitchCarbon's servers. Users are provided the original source url and a mirror url generated from the DitchCarbon server copy, ensuring data audit trails can be maintained if reporting Organizations move their reports.
Reporting entity legal entity names are extracted from Documents, and matched to the DitchCarbon Organization with the same legal entity name.
Extracted Emissions Data Structure:
Gross CO₂e emissions data points are extracted from Documents and mapped to fields based on the emissions boundaries of the GHG Protocol standard
- Scope 1, with subcategories (eg mobile combustion)
- Scope 2 market based, location based, unspecified "total", and subcategories (eg purchased heat)
- Scope 1 and Scope 2 total (disclosed together)
- Scope 3 categories (15)
Proprietary libraries translate extracted emissions data point units into kgCO₂e and attempt to map to standard GHG Protocol standard emissions boundaries.
Emissions data from Documents are merged into Organization Yearly Performances. To account for companies restating their emissions, datapoints from Documents disclosed in more recent years overwrite data from Documents in less recent years.
For example, if an Organization has two documents - a 2024 annual report with 2022-2024 data, and a 2023 report containing 2021-2023 data - the 2022 and 2023 performances from the 2024 report will overwrite data from the 2023 report.
See Data Dictionary for more detail on specific fields
Entity Resolution: Matching User Requests to DitchCarbon Organization Records
Users may provide a combination of inputs:
Direct Match IDs are a direct match to the corresponding entity in DitchCarbon’s system. When no Direct Match ID is provided, a fuzzy match to records in DitchCarbon’s database is attempted.
If fuzzy match confidence is high enough, the request will resolve to the relevant Organization. If match confidence is not high enough, the user request is moved to “waiting” status, providing the user with the opportunity to provide more input data.
Emission Factor Cascading Down Corporate Trees
If user requests successfully resolve, they match to the Requested Organization record in DitchCarbon's database.
If the Requested Organization has an Organization Emission factor, it will be delivered. If the Requested Organization has not disclosed all Minimum Data Requirements to generate a Scope 1-3 upstream emission factor, but a parent entity has, the emission factor will cascade from the parent entity (ie the Matching Organization) to the Requested Organization.
Emission factors do not cascade up family trees, only down from parent to subsidiary entities.
To enable data auditability, each user request shows the Requested Organization legal name, the Matching Organization legal name, and the relationship between the two entities (eg, L2 parent)
For example:
If a user requests Beats Electronics, the Requested Organization (Beats Electronics, LLC) does not have emissions data or revenue, but its parent (Apple, Inc) does. As the Matching Organization, Apple Inc’s Scope 1-3 upstream emission factor will be used in relevant emissions calculations, and the “ultimate parent” relationship between the two entities will be displayed.
See example export file with cascaded Matching Organizations:
Data and Quality Assurance
As an emissions data aggregator (not an emissions data generator), DitchCarbon's role is to accurately represent Documents disclosed by Organizations, and enable users to evaluate that data.
To enable users to easily assess the quality of reports, DitchCarbon extracts assurance statements for each document, for Scopes 1, 2, and 3:
- Assurance level received (limited, reasonable, unspecified, or none)
- 3rd party assurer
- Extracted assurance statement text
- Additional assurance url, if provided
To ensure accurate capture of emissions data into our system, each Document follows an 18 step process leveraging machine learning and logging each state. Human and machine extraction are used depending on the characteristics of the Document.
A system of rules based validations triggers human QA review of potential extraction failures.
In some cases, these validation warnings catch obvious mistakes made by the disclosing entities (for example, incorrectly reported units), which are then flagged to users and the reporting entity.
DitchCarbon Score Methodology
The DitchCarbon Score enables professionals and non-sustainability experts alike to evaluate whether Organizations are taking action to reduce their emissions, and if they compare favorably with their peers.
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 generate your own internal score.
The Score leverages proprietary algorithms to analyze dozens of data points specific to an Organization and calculates their score between 0 and 100.
We believe that transparent criteria enables better decisions and drives improvement. This is why we disclose the factor categories and relative weights that the DitchCarbon Score takes into account:
Other factors that will be added to the Score algorithm soon:
- Other initiatives: Race to Zero, Climate Action 100, RE 100, Ecovadis (if publicly disclosed)
- CDP Score
- Comprehensiveness evaluation of net zero or near-term targets published
How to understand if a company's score is good, decent, or bad: use peer group benchmarks.
We provide 2 benchmarks at the score level:
1 Industry mean score: the average score globally for companies classified in the same industry
2 Percentile benchmark: a Score's percentile rank compared to its industry average.
Industry Average Emission Factors
DitchCarbon maintains a library of over 1,200 industries. These include around 200 top-level Exiobase sectors plus roughly 1,000 more granular NAICS-based industries, covering 43 countries and 5 global regions.
Each industry emission factor has an industry, a region, and a year, presented in kgCO₂e/USD. For example, "2022 US steel" or "2024 Egyptian business services". Because a factor is resolved for each industry, region, and year, the library produces many thousands of distinct emission factors.
Each user input is always mapped to an industry emission factor, so a result is available even with minimal information. Where more granular relevant data is available, such as product data, activity-based emission factors, or organization-specific spend-based emission factors, we prefer those. Industry averages are used as fallbacks when no more specific data is available. Both industry-average and any organization-specific factors are always calculated and stored, so you can switch between methods instantly without recalculation.
Independent verification
DitchCarbon's industry emission factor methodology has been independently reviewed by two third parties. UL Solutions verified our methodology, managed content, and control environment to a limited level of assurance under ISO 14064-3:2019, using the GHG Protocol Corporate Value Chain (Scope 3) Standard and CDP guidance as criteria. GT Technologies independently assessed the methodology as compliant with the GHG Protocol Scope 3 Standard, ISO 14064-1:2018, and IPCC guidelines, with sample recalculations falling within 1% of our reported values.
Sources and Traceability
Emission factors are generated from EEIO data published by environmental researchers and government agencies at the US EPA, Exiobase, and DenStore.
The specific source used depends on the user's requested Organization, and the Organization's industry and region inputs.
Where EPA supply-chain factors are used, both EPA v1.2 and v1.3 are available for users to toggle between for overlapping years, with EPA v1.3 used as the default.
Source urls are always cited in our web app exports and API responses:
Industry Emission Factor Selection
Industry emission factor selection requires both industry_name and region selection.
Users may provide unstructured inputs for either industry_name or region as inputs for each Organization requested.
If user inputs are provided, they are mapped to the appropriate classification and used. If the user does not provide either of these fields, data from DitchCarbon's matching Organization record are used as fallbacks.
Mapping user-provided industry_name to DitchCarbon industry:
- Matching is grounded in a curated library of >10,000 confirmed name-to-industry matches, built from standard classification systems (such as SIC and NAICS codes) and reviewed by our team. The large majority of inputs resolve directly against this human-validated library.
- For inputs not already in the library, an automated step proposes a candidate match by working down our industry hierarchy from broad sector to specific sub-industry, and assigns a confidence rating (high, medium, or low) to that proposal. Our human QA team reviews and confirms or overrides new proposed classifications.
- Each confirmed match is added back to the library, so our human-reviewed foundation grows over time and the same input resolves consistently thereafter.
Mapping user provided region to DitchCarbon region:
If the input region is one of 43 covered countries, this is used to select the appropriate industry_emission_factor
Example: Mexico has an industry emission factor for automotive manufacturing
If region is not one of 43 covered countries, fall back to the appropriate region from among 5 global regions
Example: Morocco is not covered, so falls back to “World Africa”
Transformations for inflation and grid intensity
EEIO datasets are updated irregularly. Where reported values for a given year are not available, we adjust the closest historical year's values for inflation and grid intensity to generate a future year value (always transforming forward in time, not backwards).
Grid intensity adjustments:
- All database industries are assessed with the method IPCC 2013 GWP 100a V1.03, impact category IPCC GWP 100a
- The contribution of the grid emissions to each industry's total footprint is calculated using data from the EU27 Input-Output Database
- The grid portion of the industry emission factor is adjusted for changes in grid intensity over time, as reported by national grids
Inflation adjustments:
- Adjusted for inflation using data from the US Bureau of Labor Statistics and the Bank of England
Forecasting Module
The forecasting module enables users to forecast their annual embodied emissions out to 2050 based on reduction targets their organizations have or have not set, and to what degree the user believes those targets will be achieved.
Users can configure multiple forecast scenarios, and plot these against their own Scope 3 targets to understand if they are on track to hit their own Scope 3 goals, and which organizations are driving potential gaps:
Forecasts are calculated at the "Project" level in DitchCarbon's web app. Underpinning each project forecast is individual organization forecasts, which are calculated using extracted reduction targets and user configurations
Reduction Target Sources
Targets are structured as follows:
- Scope: scope 1, scope 2, scope 3 (upstream), scope 3 (all), all scopes
- Type: absolute, intensity, net zero, or climate-neutral
- Start and target year
- Reduction target
Relevant organization targets are selected and applied for each forecast year, by emissions scope, to an Organization's overall forecast in priority level. SBTi validated targets have highest priority, with fallbacks down to Regional targets, if configured to apply in the given scenario.
A selected target's implied cumulative annual average reduction rate is calculated and applied for the relevant forecast years to its relevant emissions scopes.
Target cascading
If a requested organization has set its own targets, those will be used. If not, a parent entity's targets can cascade down the family tree from parent organizations to requested subsidiary organizations. Targets do not cascade upward.
Configuration
Each scenario can be configured across the following attributes:
Targets to use:
- Users may choose to only give credit for organization specific targets, or apply other targets as fallbacks where organization specific targets are not available
Target attainment rate:
- User may discount organization target attainment rate, by source type
- For example, if organization sets a target to scope 1+2 by 20%, and scope 3 by 10% by 2030, but user configures that they will only make 90% of that reduction progress by the target date
Spend growth rate:
- How much is user's spend growing with organizations
Revenue growth rate:
- How much is organization's revenue growing over time
Fixed assumptions:
- Inflation is assumed at 2% per year for organizations based in OECD headquartered organizations and 5% for non-OECD headquartered organizations
Forecast calculation
As with embodied emissions calculations in the DC platform, organization specific spend based emission factors are used if organizations have disclosed all relevant upstream categories for their sector, and if revenue data is available.
Organization emission factors can cascade from parent entities to requested child entities if the child entity has not disclosed enough information to generate its own emission factor.
If an organization specific spend based emission factor is not available, fallbacks to industry average emission factors are used.
Once an appropriate emission factor for the organization is selected, embodied emissions are calculated for future years as follows:
- Forecast future spend by applying spend growth configuration
- Generate an average annual reduction rate implied by the applied target and attainment rate configuration
- Forecast future emission factor by applying inflation assumption and generated average annual reduction rate
- Calculate forecasted embodied emissions by multiplying future organization emission factor and future user spend
When no target is available given the user's configuration, embodied emissions will grow based on spend, revenue, and inflation inputs.
Portability
Underlying structured target and forecast data is exportable via xls/csv, with original sources and mirror urls provided (in case document locations are moved after capture):
Frequently asked questions
Get answers to the questions procurement and sustainability teams ask most often.
