Monte Carlo (Tier 2) uncertainty analysis of Danish Greenhouse gas emission inventory

Abstract

The methodology and results of Monte Carlo (Tier 2) uncertainty analysis of the Danish Greenhouse Gas (GHG) inventory for base year 1990 and most recent year 2008 are presented. The analysis covers 100% of the total net Danish GHG emissions and removals, excluding LULUCF. Methodological procedures such as random sampling of uncertain parameters and parameter correlation between years are explained. Uncertainties in activity data and emission factors are given for all sectors, Input data are assumed to have log-normal probability distributions, represented by median values and 95% confidence interval uncertainties. The total uncertainty levels for GHG emissions, expressed as 95% confidence intervals, are 4.1 and 5.3% for Tier 1 and Tier 2, respectively. Uncertainties in the trend are 2.4 and 6.9% for Tier 1 and Tier 2, respectively. The most influential sources from the Tier 2 analysis to the total uncertainty are CH4 from solid waste disposal on land (4.4%), N2O from leaching (3.0%), N2O from synthetic fertilizer (2.0%), and N2O and CH4 from manure management, each with 1.6%. Tier 1 and Tier 2 uncertainties in levels and trends are comparable to seven European countries that have performed a Tier 2 uncertainty analysis.