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Titel Improved modelling of atmospheric ammonia over Denmark using the coupled modelling system DAMOS
VerfasserIn C. Geels, H. V. Andersen, C. Ambelas Skjøth, J. H. Christensen, T. Ellermann, P. Løfstrøm, S. Gyldenkærne, J. Brandt, K. M. Hansen, L. M. Frohn, O. Hertel
Medientyp Artikel
Sprache Englisch
ISSN 1726-4170
Digitales Dokument URL
Erschienen In: Biogeosciences ; 9, no. 7 ; Nr. 9, no. 7 (2012-07-17), S.2625-2647
Datensatznummer 250007189
Publikation (Nr.) Volltext-Dokument vorhandencopernicus.org/bg-9-2625-2012.pdf
 
Zusammenfassung
A local-scale Gaussian dispersion-deposition model (OML-DEP) has been coupled to a regional chemistry-transport model (DEHM with a resolution of approximately 6 km × 6 km over Denmark) in the Danish Ammonia Modelling System, DAMOS. Thereby, it has been possible to model the distribution of ammonia concentrations and depositions on a spatial resolution down to 400 m × 400 m for selected areas in Denmark. DAMOS has been validated against measured concentrations from the dense measuring network covering Denmark. Here measured data from 21 sites are included and the validation period covers 2–5 years within the period 2005–2009. A standard time series analysis (using statistic parameters like correlation and bias) shows that the coupled model system captures the measured time series better than the regional- scale model alone. However, our study also shows that about 50% of the modelled concentration level at a given location originates from non-local emission sources. The local-scale model covers a domain of 16 km × 16 km, and of the locally released ammonia (NH3) within this domain, our simulations at five sites show that 14–27% of the locally (within 16 km × 16 km) emitted NH3 also deposits locally. These results underline the importance of including both high-resolution local-scale modelling of NH3 as well as the regional-scale component described by the regional model. The DAMOS system can be used as a tool in environmental management in relation to assessments of total nitrogen load of sensitive nature areas in intense agricultural regions. However, high spatio-temporal resolution in input parameters like NH3 emissions and land-use data is required.
 
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