Ole-Kenneth Nielsen

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

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.

Air Pollutant Trends over Denmark over the Last 37 Years as Simulated by the Integrated Model System THOR

Air pollutant levels over Denmark are simulated using the high resolution THOR model system for the years 1979–2015. The system employs the Danish Eulerian Hemispheric Model (DEHM), coupled to the Urban Background Model (UBM) that covers the whole of Denmark on a 1 km spatial resolution. This study evaluates the performance of the model system in simulating hourly, daily, monthly and yearly mean ozone (O3), nitrogen oxides (NOx) and particulate matter (PM10 and PM2.5) concentrations using surface measurements from eight Danish monitoring stations between 1990 and 2015. The spatial and temporal variability of air pollutants and emissions are also investigated to better understand the air pollution trends over Denmark during this 37 year period.

Particle emissions in Belarus and in the Nordic countries

The overall goal of the project is to stimulate decision-makers in Belarus to prioritize abatement measures aimed at black carbon in their efforts to reduce emissions of PM2.5, as encouraged in the ...

High-Resolution Modelling of Health Impacts and Related External Cost from Air Pollution Using the Integrated Model System EVA

EVA (Economic Valuation of Air pollution), a multi-scale and high-resolution integrated model system for assessing health impacts and related external costs from air pollution), has been further developed by implementing the air quality model, UBM, with a 1 km × 1 km resolution covering the whole of Denmark. The high-resolution model is coupled to the long-range chemistry-transport model DEHM (Danish Eulerian Hemispheric Model) in a configuration with four nested domains. By using this system, a high-resolution assessment of health impacts from air pollution and related external cost has been conducted for Denmark for the year 2012.

Verification of the Danish greenhouse gas key categories and annex II indicators

Danish emission values, implied emission factors (IEFs) and activity data (AD) for the national greenhouse gas inventory are assessed according to an updated verification procedure. Focus is on 28 Annex II indicators and 25 identified Key Categories, represented by 29 verification categories covering energy, agriculture, industry and waste. The data are based on the national greenhouse gas inventory for the years 1990 (base year), 2000 and 2010, as reported in 2012, and provided by the United Nations Framework Convention on Climate Change and the European Union. Inter-country comparison and time trend consistency check of Annex II indicators, covering energy and industry, is made for EU15 countries, excluding Italy and Luxembourg. Inter-country comparison and time trend consistency check of IEFs is made for EU15 countries, excluding Luxemburg and including Norway and Switzerland and for some verification steps also including Australia, Canada, Japan, Russian Federation, USA and aggregated values for EU15 and EU27. National and inter-country verification and time trend consistency check of AD are made with data for energy consumption [(Eurostat. (2013). European commission. Retrieved January 9, 2013], agricultural statistics [Eurostat. (2013). European commission. Retrieved January 9, 2013], industrial processes (UN. (2013). United Nations Statistical Yearbook 2010 – fifty fifth issue. New York: United Nations. Retrieved October 12, 2012, from http://unstats.un.org/unsd/syb/default.htm) and waste disposal (OECD. (1997, 2004). Environmental data, compendium 1997 and 2004. Paris: Organisation for Economic Co-operation and Development). Verification in this approach is a combination of qualitative and quantitative assessments and gives lines of evidence of the correctness of the emission inventory.