The development of a rigorous uncertainty analysis entails a series of steps, including the development of a systematic strategy for completing the analysis and so that not just the results but also the process of preparing the analysis improves the quality of the inventory. These steps can be summarized as follows:

1.Develop strategy to estimate uncertainty across entire inventory

• Prioritize Key Source and Sink Categories
• Focus on investigations that may improve inventory methods and data

2. Select method to combine uncertainties (Tier 1 error propagation or Tier 2 Monte Carlo).

3. Parameterize emission and removal estimation models, which may be identical to estimation methods or simplifications of those methods

4. Collect uncertainty input information and data for the parameters developed above

• Statistical data on direct measurements, where available
• Statistical data on emission factors, activity data, and other parameters, where available
• Expert judgment (using elicitation protocols) for other information and to provide qualitative information

5. Combine uncertainties using method selected

6. Analyze results, prepare transparent documentation, and include detailed qualitative discussions

The IPCC Good Practice Guidance defines good practice in estimating and reporting uncertainties associated with both annual estimates and emissions/removals trends over time. Two tiers are provided for combining source category uncertainties into an uncertainty estimate for total national emissions and for emission trends.

Tier 1 uncertainty calculation and reporting, which relies on simple error propagation, is restricted to normal (i.e., Gaussian) probability distribution functions and does not account for correlation and dependency between categories that may occur because the same activity data or emission factors may be used for multiple estimates.

The Tier 2 method estimates uncertainty by using Monte Carlo analysis, which avoids all the limitations of the error propagation method (if implemented correctly and rigorously)

And for all cases and methods, it is critical that rigorous and detailed qualitative explanations are provided. It is this type of information that documents the data quality problems in the inventory estimates that leads to future improvements and the most transparency in the quality of the inventory submitted.

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 LULUCF Good Practice Guidance report here.