Trust scores
The Trust score for projects comprises a base component and additional score modifiers. The base component stems from the Carbon Credit Quality Initiative (CCQI) framework, which assesses carbon credit quality through seven quality objectives. These objectives include robust determination of the GHG emission impact (additionality), avoiding double counting, addressing non-permanence, transition towards net zero emissions, strong institutional arrangements, environmental and social impacts, and host country ambition (not always included).
These objectives are rated on a scale from 1-5, either by CCQI or an independent carbon market experts. The overall score for each project is a weighted average of these scores, converted into a percentage scale (0-100) for convenience and comparison. Additional score modifiers are layered on top of the base component and include third-party ratings, Credit Completion Factor, and CCP eligibility probability.
Value scores
The Value score indicates the relationship between quality and price for each subtype within the voluntary carbon market. It shows how far above or below a project's price is from the expected value line through all projects of that subtype. For example, if a project in the afforestation/reforestation subtype has a quality score of 65 and an expected price of $12.00 but an actual price of $14.00, it sits above the value line, indicating it is expensive relative to its peers, and thus its value score will be low.
It's important to note that this means that Value scores only enable comparison amongst projects of the same (sub-)type, such as REDD+ or cookstoves.
Fit scores
The Fit score is calculated based on the guidelines set by the user. These guidelines can include a target price range, host country, registry, avoidance versus removal, type and subtype, methodology, and available vintages. After these factors have been defined, the platform calculates a fit score for every project in the database, indicating the degree to which each project aligns with the user's guidelines.
Guidelines can be changed at any time, which automatically triggers a re-calculation of the Fit scores.