4.4.1 - Why uncertainties?
Objectives and definitions of uncertainties.
Estimates and measurements inherently involve a margin of error; the vast majority of scientific methods therefore tend to associate values called uncertainties with the results of measurements or estimates.
These uncertainties allow deriving a 95% confidence interval, that is an interval [Value 1; Value 2] within which the true value of what is being measured or estimated has a 95% probability of lying.
The Bilan Carbone® method allows to determine uncertainties in a qualitative and quantitative manner.
Taking into account uncertainties related to activity data and emission factors and calculating their resultant effect on the estimated quantities of GHGs aims to help organisations identify priorities for improving the quality of these data, and thus to implement Process improvement action process improvement actions for collection and carbon accounting thereafter. Uncertainty values must also be taken into account when analysing results and developing the transition plan. The ultimate objective is to optimise the reliability of future inventories and to appropriately guide decision-making.
Quantitative uncertainties can be propagated across the different emission categories of the assessment or across the entire assessment to obtain a 95% confidence interval. It should be noted that the uncertainty propagated over the entire assessment is of limited relevance because it does not provide useful information for decision-making. A more detailed analysis of uncertainties, category by category and emission source by emission source, is far more relevant for the continuous improvement of the approach.
Do you have a comprehension question? Consult the FAQ. The method is living and therefore likely to evolve (clarifications, additions): find the change log here.
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