Uncertainties in the EDGAR emission inventory of greenhouse gases

The Emissions Database for Global Atmospheric Research (EDGAR) estimates the human-induced emission rates on Earth collaborating with atmospheric modelling activities as well as aiding policy in the design of mitigation strategies and in evaluating their effectiveness. In these applications, the uncertainty estimate is an essential component as it quantifies the accuracy and qualifies the level of confidence in the emission. This study complements the EDGAR's emissions inventory with estimation of the structural uncertainty stemming from its base components (activity data statistics (AD) and emission factors (EF)) by i) associating uncertainty to each AD and EF characterizing the emissions of the three main greenhouse gases (GHG) CO2, CH4 and N2O; ii) combining them, and iii) making assumptions for the cross-country uncertainty aggregation of source categories. It was deemed a natural choice to obtain the uncertainties in EFs and AD from the Intergovernmental Panel on Climate Change (IPCC) guidelines issued in 2006 (with a few exceptions), since the EF and AD sources and methodological aspects used by EDGAR have been built over the years based on the IPCC recommendations, which assured consistency in time and comparability across countries. While on one side the homogeneity of the method is one of the key strengths of EDGAR, on the other side it facilitates the propagation of uncertainties when similar emission sources are aggregated. For this reason, this study aims primarily at addressing the aggregation of uncertainties sectorial emissions across GHGs and countries. On global average we find that the anthropogenic emissions of the combined three main GHGs for the year 2015 are accurate within an interval of −15 % to +20 % (defining the 95 % confidence of a log-normal distribution). The most uncertain emissions are those related to N2O from agriculture, while CO2 emissions, although responsible for 74 % of total GHG emissions, accounts for and for approximately 11 % of global uncertainty share. Sensitivity to methodological choices is also discussed.