Berdowski JJM ,
Draaijers GPJ ,
Janssen LHJM ,
Hollander JCTh ,
Loon M van ,
Roemer MGM ,
Vermeulen AT ,
Vosbeek M ,
Visser H
160 p
in Dutch
2001
Toon Nederlands
English Abstract The agreed emission reductions in the Kyoto Protocol
require methods to establish the quality and accuracy of the inventory data
and to monitor compliance with the Protocol. The IPCC Expert Meeting in
November 1997 in the Netherlands concluded that an assessment of inventory
data quality was strongly supported by independent checks and additional
analysis of uncertainties in the emissions inventories. In this study,
carried out in the frame of the Dutch National Research Programme on Global
Air Pollution and Climate Change three connected validation procedures have
been applied for a methane emission inventory, namely (i) the comparison of
emission inventories, (ii) the comparison of modelled with observed methane
concentrations, and (iii) the comparison of bottom-up emission estimates
with inversely modelled emission estimates. There is a good overall
correspondence between the consistent bottom-up METDAT emission inventory
and the National Communication data. However, on a country level and on a
source category level large discrepancies could been found. The analysis of
concentration measurements gives a clear indication of the contribution from
the different areas. Time series analysis as such appeared not to be
suitable for verification purposes in this study. The technique of emission
verification by modelling methane concentrations with the bottom-up
estimated emission data as input for the model and comparing the results
with measured concentrations has been proven quite successful, at least on a
regional scale. The technique applied so far is however not able to
indicate whether the individual sources are estimated realistically as well.
At present, the technique of inverse modelling has not proven to be robust
enough to produce stable results of satisfactory accuracy on a regional
scale. At least, there is a lack of sufficient measurement data, e.g. from
neighbouring countries and a need for the improvement of background
concentration data (by global models).