A use-chain model to deal with uncertainties : a focus on GHG emission inventories

The measurements necessary to estimate GHG emission inventories create uncertainty. Currently emission inventories are built on statistical data, parameters and some “other information.” Investigating the role of the latter has driven this analysis, since it has proven to be a key concept in understanding and reducing uncertainty. This article proposes a use-chain model to guide researchers in choosing the appropriate available method to deal with uncertainty. The model involves three main parts: data production, data analysis and data use. The findings suggest, first, that statistical techniques, although crucial, do not represent the only possible way to reduce uncertainty; and, second, that the appropriate way to deal with uncertainty depends on whether one is dealing with data production or data analysis or data use, each characterized by a different degree of specificity and by a different influence of the surrounding context.