The Carbon Credit Quality Initiative developed its own methodology to assess the quality of carbon credit types. The methodology has undergone targeted stakeholder consultation and has been refined over time, based on the lessons learned from its application.
What makes a high-quality carbon credit is not a simple question. CCQI uses seven quality objectives that should be considered when assessing the quality of carbon credits. Each quality objective comprises several criteria and sub-criteria that assess specific quality features.
Assessing the quality of carbon credits is methodologically challenging and often requires difficult judgments. The approaches presented in the methodology are our judgment of what quality features matter and how these could be practically assessed and weighed.
To date, more than 10,000 mitigation projects are registered under carbon crediting programs. Assessing each individual project would provide the best picture of carbon credit quality—but this would require considerable resources. For this reason, CCQI focuses on scoring different types of carbon credits.
A type of carbon credit represents a specific combination of components: the project activity (e.g., landfill gas utilization), the carbon crediting program under which the carbon credits are issued (e.g., the Verified Carbon Standard), the quantification methodology that has been applied (e.g., the Clean Development Mechanism methodology ACM0001) and the country where the project is located (e.g., Brazil). Each of these components are used to define, and then score, types of carbon credits.
For each criterion or sub-criterion, our assessment methodology identifies which of these factors are most significant for carbon credit quality, and then evaluates the criterion or sub-criterion at these levels. For example, the "robustness of the quantification of emission reductions" is mainly assessed by evaluating the detailed provisions of the quantification methodologies applied, whereas the robustness of third-party auditing is assessed by evaluating the carbon crediting program's rules on third-party auditing.
This approach allows our assessments to cover a large share of carbon credits available on the market. It does not, however, necessarily account for the unique conditions of each individual project. For example, the sustainable development benefits of an afforestation activity will strongly depend on how the activity is designed.
For these reasons, our scores represent the likelihood or confidence that the quality objectives or criteria are met. The carbon credit quality of individual projects could vary considerably from our scores. Our scores should therefore be considered as a starting point for further due diligence.
While this initiative only publishes scores for types of carbon credits, the methodology can also be applied to individual projects. This requires, however, considerable carbon crediting expertise. To help users apply the methodology and derive their own scores, CCQI provides an Excel tool. Moreover, other agencies, such as Calyx Global, Sylvera, or BeZero, offer gradings of individual projects against subscription fees.
Our assessment methodology uses a scale of 1 to 5 to indicate the confidence or likelihood that types of carbon credits meet each quality objective, criterion or sub-criterion, with 5 representing the highest score. The scores have the following meaning:
|Very high confidence or likelihood that the assessment subject meets the criterion or quality objective.|
|High confidence or likelihood that the assessment subject meets the criterion or quality objective.|
|Moderate confidence or likelihood that the assessment subject meets the criterion or quality objective.|
|Low confidence or likelihood that the assessment subject meets the criterion or quality objective.|
|Very low confidence or likelihood that the assessment subject meets the criterion or quality objective.|
The results from each evaluation are combined into scores for each of the seven quality objectives. The final results for the seven quality objectives are not further aggregated but displayed separately. This aims to provide a nuanced picture of the different quality features of carbon credits and allows buyers to determine which quality objectives are most important to them.
The methodology draws upon innovative approaches to combine scores, such as "inverse weighing". This aims to ensure that a good performance on one criterion cannot make up for a bad performance in another criterion.