Comprehensive guide to our data collection, calculation methods, and scoring algorithms for accurate Scope 3 emissions measurement
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:
Access and export data within the DitchCarbon web app, via API in your preferred application or ERP.
Data is aggregated and structured into standardized formats, normalizing for units and various reporting styles to GHG Protocol Standards.
Data Category | Description | Sources |
---|---|---|
Emissions Disclosures | All GHG Protocol Scopes/Categories | Organization disclosures |
Assurance Levels | 3rd party auditor and assurance level received, by Scope, extracted from each disclosure. | Organization disclosures |
Organization Emission Factors | Global factors - 3 boundaries available. See Organization Emission Factor section for detail | Organization disclosures: emissions and revenue |
Reduction Targets | Disclosed directly by company, or validated by SBTi | Disclosing organization or SBTi |
Initiative Participation | Participation status: SBTi, CDP, Race to Net Zero, UN Global Compact, RE 100, Climate Action 100, Ecovadis (if publicly disclosed). | Initiative databases and disclosing organization. |
Reduction Actions | Actions taken by organization to reduce emissions | Organization disclosures |
DitchCarbon Score | Climate action score, 0 to 100. See DitchCarbon Score methodology for detail | DitchCarbon algorithm |
Score Benchmark | Compares Organization's score to others in its industry. See Score methodology for detail | DitchCarbon algorithm |
Peer Comparisons | Data from similar Organizations | Organization disclosures S&P global database |
Recommendations | Highest leverage reduction actions to take, based on Organization's profile, and relevant actions taken by similar organizations | DitchCarbon reduction action database, UN Climate Drive |
Industry Emission Factors | 6 years industry emission factors, used as fallbacks where organization emission factors unavailable | US EPA, Exiobase, Denstore, UK DEFRA |
For more information on fields see our Data Dictionary, or get in touch: enquiries@ditchcarbon.com
Users may provide a combination of inputs:
Ask if not listed above - others are provided
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.
Direct Match IDs enable immediate matching to corresponding entity in DitchCarbon's system
Fuzzy match attempted against records in DitchCarbon's database
Request resolves to the relevant Organization
Request moved to "waiting" status - user can provide more input data
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.
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:
Our automated extraction engine and human QA process handles common issues that users of primary emissions data encounter regularly:
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:
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.
Emission Factor | Minimum Data Requirements | Other Calculation Logic |
---|---|---|
Scope 1+2 / revenue | - Global Scope 1 and 2 available - Global consolidated annual revenue data available | If multiple Scope 2 values available, prefer: 1) market-based 2) unspecified "total" 3) location-based |
Scope 1+2+3 (upstream) / revenue | - Global Scope 1, 2, and all relevant upstream scope 3 categories disclosed - Global consolidated annual revenue data available | See above, and: If all relevant Scope 3 upstream categories are disclosed, then calculate All disclosed upstream scope 3 categories are included in calculation, not just "relevant" categories |
Scope 1-3 / revenue | - Global Scope 1, 2, and all relevant scope 3 categories disclosed - Global consolidated annual revenue data available | See above, and: If all relevant Scope 3 categories are disclosed, then calculate All disclosed scope 3 categories are included in calculation, not just "relevant" categories |
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.
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.
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.
Gross CO₂e emissions data points are extracted from Documents and mapped to fields based on the emissions boundaries of the GHG Protocol standard
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
Users may provide a combination of inputs:
Ask if not listed above - others are provided
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.
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:
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:
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.
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:
Factors Increasing Score | Weight | Source |
---|---|---|
Reduced absolute emissions: last year | High | Primary data – company disclosures |
Reduced emissions intensity (revenue adjusted): last year | High | Primary data – company disclosures |
Committed to SBTI: Net Zero | High | SBTI database |
Are in a very low or low emitting industry | High | Exiobase, DEFRA, EPA EEIO databases |
Reduced absolute emissions: previous 2 years | Medium | Primary data – company disclosures |
Reduced emissions intensity (revenue adjusted): previous 2 years | Medium | Primary data – company disclosures |
Disclosed Scope 1, 2, and 3 emissions: last year | Medium | Primary data – company disclosures |
Reported all industry-relevant Scope 3 categories: last year | Medium | CDP relevance criteria | company disclosures |
Committed to SBTIs: Near Term or Long Term | Medium | SBTI database |
Is a Climate Pledge signatory | Low | Climate Pledge database |
Committed to at least 1 UN Global Compact environmental initiative | Low | UNGC database |
Disclosed to CDP: last year | Low | Public disclosures |
Disclosed Scope 1, 2, and 3 emissions: previous 2 years | Low | Primary data – company disclosures |
Disclosed to CDP: previous 2 years | Low | Public disclosures |
Reported all industry-relevant Scope 3 categories: previous 2 years | Low | CDP relevance criteria | company disclosures |
Is headquartered in a very low or low emitting country | Low | National grid intensity disclosures |
Received assurance on last year's report | Low | Public disclosures |
We provide 2 benchmarks at the score level:
DitchCarbon provides over 200 industry emission factors for 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".
Each user input is mapped to an industry emission factor, regardless of if more granular data (such as organization specific spend-based emission factors) are available. When more granular data is not available, industry emission factors are used as a fallback for embodied emissions calculations.
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.
Source urls are always cited in our web app exports and API responses:
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.
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).
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
Source Type | Description | Example source url |
---|---|---|
SBTiRow | Structured targets extracted from SBTi | SBTi |
Document | Targets captured from annual reports or website announcements | IBM |
Industry | Global initiatives for cross-border (global native) sectors: maritime and aviation | IMO |
Region-Industry | Targets set by specific sectors in specific regions, eg "German automotive" | EU for select sectors |
Region | Net zero targets set by regions | Singapore regional plan |
Targets are structured as follows:
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.
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.
Each scenario can be configured across the following attributes:
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:
When no target is available given the user's configuration, embodied emissions will grow based on spend, revenue, and inflation inputs.
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):