Uncertainty information on the emission factors, activity data and other parameters used for the analysis must be collected to create probability density functions.

A probability density function describes the range and relative likelihood of possible values. Confidence limits give the range within which the underlying value of an uncertain quantity is thought to lie for a specified probability. This range is called the confidence interval. Click here to see probability density function graphs.

The IPCC Guidelines suggest the use of a 95% confidence interval, which is the interval that has a 95% probability of containing the unknown true value.

Actual statistical data should be used, where available, to empirically define the shape of the probability density functions. Where such empirical data are not available, expert judgment will be necessary.

As this uncertainty data are collected, the correlations between parameters (across source categories and across time) should also be considered.

The regular assessment of uncertainty also facilitates the creation of a continuous improvement process by the Party. In other words, it is the process of asking difficult questions and investigating data quality while collecting information for the probability distribution function inputs to the uncertainty analysis that has the potential to add real value to the inventory.

Such investigations should include communication with organizations (i.e., statistical agencies) supplying data to the inventory agency.

One effective way to facilitate the uncertainty analysis improving the Party’s overall inventory is to integrate the process of preparing the analysis with the Party’s QA/QC plan.

Click here for Chapter 6 “Quantifying Uncertainties in Practice” in the IPCC Good Practice Guidance. Additional guidance for uncertainty analysis for LULUCF can be found in Chapter 5.2 of the IPCC Good Practice Guidance for LULUCF report here.