In decision-making processes on emission reduction, not only are emission data needed but also information on the uncertainty of these data. Here, structured expert elicitation was used an uncertainty analysis on NOx emissions from Dutch passenger cars in 1998.
Experts from several Dutch research institutes were elicited on individual car performance (emission factors) and volumetric (kilometres driven) variables could be obtained with the expert elicitation method. Total population uncertainty was calculated by propagation and aggregation of individual car uncertainty in a Monte Carlo simulation. The calculation process was explicitly geared to variables showing inherent variability (aleatory uncertainty) and variables that are uncertain because of a lack of knowledge (epistemic uncertainty).
The smallest 95% uncertainty interval for total population NOx emission was obtained for the TNO-CBS (Statistics Netherlands) expert (-12% to +15%), while the largest interval was obtained for the RIVM expert (-35% to +51%). The combination of experts (called decision-makers [DM]) showed intervals of -30% to +41% (DM before propagation) and -46% to +81% (DM after aggregation). The use of structured expert elicitation was very time consuming, and there is still a lot of discussion on combining expert data. Therefore, the need for structured expert elicitation should be firmly substantiated and focused on sensitive and controversial variables.