Fauser, P., Nielsen, M., Winther, M., Plejdrup, M., Gyldenkærne, S., Mikkelsen, M.H., Albrektsen, R., Hoffmann, L., Thomsen, M., Hjelgaard, K. & Nielsen, O.-K. 2013. Verification of the Danish 1990, 2000 and 2010 emission inventory data. Aarhus University, DCE – Danish Centre for Environment and Energy, 85 pp. Scientific Report from DCE – Danish Centre for Environment and Energy No. 79. http://dce2.au.dk/pub/SR79.pdf
The verification report covers 1990, 2000 and 2010 emissions, reported in 2012, for 25 Danish key categories that have been identified from a Tier 1 analysis for total emitted amounts and trend assessment. Key categories comprise 14 energy, eight agriculture, two industry and one waste category. The 25 key categories cannot be directly derived from the Common Reporting Format (CRF) tables, therefore they are represented by 29 verification categories. See Table 2.1 and 2.2 for description of key categories and verification categories. Furthermore the seven priority, six additional and 15 supplementary Annex II indicators and results from the reference approach are covered.
Inter-country comparison is made for EU15 countries, Norway and Switzerland and for some verification steps also including Australia, Canada, Japan, the Russian Federation and the United States of America. Aggregated values for EU15 and EU27, respectively, are also included for some verification steps. The verification procedure comprises the following steps:
1) Inter-country comparison of 28 Annex II indicators covering energy and industry.
Verification criteria: Consistency in time trends, comparability between countries.
2) Inter-country comparison of implied emission factors (IEFs) for 29 verification categories.
Verification criteria: Consistency in time trends of Danish United Nations Framework Convention on Climate Change (UNFCCC) implied emission factors, comparability between countries.
3) National and inter-country comparison of activity data (AD) reported to the European Union (EU) and Eurostat (2013) for energy sector and agricultural sector, comparison of UNFCCC and United Nations (UN) (2013) activity data for industrial processes and comparison of UNFCCC and Organisation for Economic Co-operation and Development (OECD) (1997 and 2004) data for waste.
Verification criteria: Consistency in time trends of Danish EU and UNFCCC activity data, comparability with other activity data.
4) National verification with reference approach for energy sector.
Verification criteria: Comparability between national approach and reference approach.
In Table S.1 (in the report) the results from verification of the 28 Annex II indicators are summarised. In Table S.2 and S.3 (in the report) the results from verification of IEF and AD for the 29 verification categories, are summarised. For each indicator and verification category the verification criteria are stated.
For the 28 Annex II indicators and 29 verification categories there are three verification criteria; Consistency in time trends gives an indication of robustness and consistency in methodologies and data. Comparability between countries indicates accuracy and reliability in methods and data, and comparability with other (independent) data ensures accuracy in data.
Overall these criteria give lines of evidences that the inventory method and the associated data fulfil the demand for accuracy, reliability and transparency. However, specific conditions may prevail in activity data, e.g. variations in used fuel amount or industrial production, that give dips and jumps in calculated emissions, which challenges a direct time trend consistency check. In such cases it is important to investigate the reason for these anomalies and also an assessment of other (independent) data is important.
For Annex II indicators decrease is the predominant time trend for Denmark, i.e. for 15 indicators representing energy, industry, transport, households and services, cf. Table S.1. This suggests that the politically initiated change of applied fuels, the increasing power production based on wind and the increased energy efficiency in both production and consumption is reflected in the indicators. In general, the indicators for Denmark are not outliers. The inter-country comparison does not reveal consistently comparable countries. However, there is a tendency for the Danish indicators to be comparable with France, Greece, the Netherlands, Portugal, Spain, Sweden and the United Kingdom.
For 22 verification categories the IEFs show constant time series indicating consistent IEFs from 1990 to 2010, cf. Table S.2. This implies robustness in methodology and underlying data. Comparability of IEF between countries is found for energy, transport and industry (cement production). Most of the IEFs for the agricultural categories are comparable with other countries. A few categories, such as 4.A-sheep, 4.B-liquid, 4.B-other and 4.D3-leaching differ from other countries and the differences are identified and explained. In many countries the cattle and swine production are key sources and therefore due to the IPCC guidelines require use of national data, which leads to a larger variation of the IEF values. The Danish IEFs for cattle and swine are in line with other countries that have comparable agricultural conditions. IEF for solid waste disposal on land is not comparable between countries due to the fact that emissions arise as a result of decay of organic material in the deposited waste over time. This means that an IEF based on the emission in a given year and the amount of waste deposited in that year will not be representative since the emission only to a very small degree is dependent on the amount of waste landfilled in the given year.
Activity data for verification categories generally reveal no time trend in the period 1990 to 2010, cf. Table S.3.
The energy sector has undergone large changes since 1990 including a politically initiated change of fuels towards fuels with less CO2 emission, increased wind power production, liberalised electricity market and the construction of a natural gas grid. Electricity import/export cause fluctuations for fuel consumption in Danish power plants and thus fluctuations of the national CO2 emission. A comparison of activity data from IEA energy statistics supplied to Eurostat (2013) and CRF data reported to EU, performed by Umweltbundesamt Gmbh (UBA, 2013) for the energy sector, shows good agreement with deviations 0.1-4 %. Exceptions are; petroleum refining (14 %), where Denmark includes combined heat and power plants in 1A1b and Eurostat does not include auto-producers under refineries, and residual oil use in navigation (115 %), where additional fuel consumption for sailing between Denmark and Greenland/Faroe Islands is not accounted for in the official Danish fuel statistics. Further exceptions are residential use of liquid fuels (9 %) and use of liquid fuels in agriculture/forestry/fisheries (21 %). The differences for liquid fuels applied in residential plants and plants in agriculture/forestry/fisheries are caused by reallocation of some liquid fuels in the Danish emission inventory. The Danish transport model represents better disaggregation data and part of the liquid fuel consumption is reallocated in the Danish inventory. The total consumption of liquid fuels has been verified with good agreement with deviations below 2 %. The data source for the IEA data is the international reporting from the Danish Energy Agency. The Danish Energy Agency also delivers data for the Danish emission inventory and thus data are not independent. However, the aggregation and data transfer differ and the verification with the IEA data will reveal errors in the data aggregation. For off-shore flaring no independent data are available.
For the agriculture sector activity data from Eurostat (2013) are used for verification, which yield high consistency and thus low deviations of 1-5 % and 11 % for number of cattle and sheep, respectively. No international independent data survey is available for crop residues, atmospheric deposition and nitrogen leaching.
Activity data for solid waste disposal on land is verified with OECD Environmental Data (OECD, 1997 and 2004): Disposal of municipal waste on landfills with a deviation of 73 %, which reflects the fraction of Municipal Solid Waste (MSW) in percentage of the total deposited waste; MSW being defined as “Municipal waste is waste collected and treated by or for municipalities. It covers waste from households, including bulky waste, similar waste from commerce and trade, office buildings, institutions and small businesses, yard and garden waste, street sweepings, the contents of litter containers, and market cleansing waste. The definition excludes waste from municipal sewage networks and treatment, as well as waste from construction and demolition activities.
Cement production is verified with UN Statistical Yearbook: Cement production with a deviation of 10 %. The deviation in cement production may be explained by a difference in activity data where the applied activity data is “produced amount of clinker” whereas the activity in trade statistics probably is cement, and cement is milled clinker added, e.g. fly ash or other mineral compounds.
The sectoral approach for fuel combustion has been verified by the reference approach. The reference approach is based on data for fuel production, import, export and stock change whereas the sectoral approach is based on fuel consumption data. In 2010, the fuel consumption rates in the two approaches differ by 0.51 % and the CO2 emission differs by 0.62 %. In the period 1990 to 2011, both the fuel consumption and the CO2 emission differ by less than 2.0 %. The differences are below 1 % for all years except 1998 and 2009. According to IPCC Good Practice Guidance (IPCC, 2000) the difference should be within ±2 %.
In conclusion, the used verification procedure is appropriate for evaluating data consistency and accuracy. There are consistent time trends for Annex II indicators and for IEFs for verification categories identified based on the key category analysis. There is good agreement between reported and other activity data for verification categories for energy sectors and some agriculture sectors. Comparable countries can be identified for Annex II indicators and for verification categories comparability between countries is evident for energy and transport sectors.
It is a challenge to find suitable independent data, and in many cases the alternative datasets are to some extent based on the same raw data. However, these data can be used to some degree to assess the completeness and the correctness of the emission inventory. In situations when national data vary from EU mean values ± uncertainties it is often more correct to use national data instead of default values, as they represent specific national conditions.
The reasons for comparability and consistency are sometimes apparent, and in other cases identification of the underlying factors requires a more in-depth analysis. It is important to underline that a comparison between countries only considers consistency compared to how and what other countries report. It is not a verification of the scientific value of the inventory data themselves (Holtskog et al., 2000). When comparing Annex II indicators between countries it is important not to over-interpret the results; indicators are good for explaining emission trends but less so for establishing the reliability of the GHG inventory. Especially for the agricultural sector it is important to compare with countries that have comparable agricultural conditions. Comparability with countries with different conditions may show high deviations that do not necessarily indicate erroneous inventory data.
A quantitative verification of implied emission factors can furthermore be made when a measured or theoretical value of the carbon content in the respective fuel type (or other relevant parameter) is available. For the energy sector all countries are in principle comparable, and inter-country deviations arise from variations in fuel type applied in each of the fuel groups solid, liquid, gaseous or other fuels.
Verification in this approach is predominantly of qualitative nature. The terms “good agreement” and “poor agreement” are used for inter-country comparisons and time trends. Each source category has an inherent uncertainty with respect to absolute values of e.g. quantification of CO2 emissions and with respect to methodological approaches. Thus a “good agreement” may be a relative statement for source categories with greatly different uncertainties. For agreement between reported data and other (independent) data, the verification is quantitative and is reported as a percentage deviation. The evaluations of agreement are based on these deviations.
An important outcome of a verification procedure is to support identification of sectors and categories that require more attention and thus a prioritisation of resources that are required to obtain more accurate and reliable emission inventories in the future.
