Criterion A.9 - Awareness of result uncertainty

The Bilan Carbone® method states that the physical approach using activity data and emission factors has imperfect precision. Nevertheless, the primary objective of an uncertainty calculation is to raise users' awareness of the uncertainty inherent in greenhouse gas emission assessments (i.e., what degree of confidence can be placed in them?) while identifying priorities for improving data quality. However, this uncertainty in results (especially if it proves to be high) must not be a barrier to action.

This criterion evaluates the presence of elements raising awareness of this uncertainty (both on activity data and on emission factors). It also assesses whether the candidate tool, as part of a continuous improvement approach (cf. criterion B.10), seeks to encourage the user to reduce uncertainties, particularly for major emission categories. This can be achieved through improving activity data collection or by reducing emissions related to emission factors.

Criterion

Mandatory	Criterion A.9 - Raising Awareness of Results Uncertainty
Question	Does the candidate tool support users in understanding the principle of uncertainty, including uncertainties in emission factors and activity data? Does the candidate tool guide the user in reflecting on their main sources of uncertainty (activity data and emission factors)?
Answer	Yes, the tool supports users in understanding the principle of uncertainty and in reading the calculated uncertainty results Yes, the tool supports users in understanding the principle of uncertainty No
Implementation guidance	Check whether uncertainty is presented and whether elements raising awareness of data uncertainty and emission factor uncertainty are available in the guide(s) accompanying the candidate tool or directly within the candidate tool. Mention must be made of the uncertain nature of GHG results and of the need to reason primarily in terms of orders of magnitude when interpreting results. Verify whether, for major emission categories with high uncertainty, the candidate tool clearly identifies a need to reduce uncertainty.