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Opportunities of SEIS and SISE: Integrating Environmental Knowledge in Europe
Hradec, J. ; Pelikán, Emil ; Mirovský, O. ; Pillmann, W. ; Holoubek, I. ; Bandholz, T.
The European conference *Towards /e/Environment* was dedicated to information exchange among public administrations, EU institutions, environmental agencies, scientists and businesses involved in developing and using environmental informatics for the delivery of modern eEnvironment services in Europe. The conference was organised by the Masaryk University in cooperation with the Ministry of Environment of the Czech Republic, the European Commission, the European Environment Agency and the European Space Agency and further Czech institutions (CENIA, CSO, ICS AS, CHMI, CTU). The proceedings was printed in Masarykova universita in Brno (ISBN 978-80-210-4824-9).
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Konverze inventářů z databáze REZZO pro modelování znečištění ovzduší
Liczki, Jitka ; Resler, Jaroslav ; Krč, Pavel ; Eben, Kryštof
The Czech national emission and air pollution sources inventory (REZZO) is a large database covering anthropogenic emissions produced in the Czech Republic. REZZO can be used as emission inputs for advanced air quality models, e.g. CAMx, CMAQ after a conversion that enables SMOKE system. Since SMOKE is developed for US standards it needs some adaptations before using for REZZO. Converted REZZO emissions for point and area sources for a grid with 3km horizontal resolution are presented.
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Asimilace satelitních a přízemních dat do modelů kvality ovzduší
Resler, Jaroslav ; Eben, Kryštof ; Juruš, Pavel ; Krč, Pavel
Tropospheric columns of various species retrieved from satellite instruments bring a new quality into data assimilation systems for air quality models. In our experiments we assimilate tropospheric columns of NO2 retrieved from the instruments GOME2 and OMI together with ground-level observations of NO2. The 4DVar method has been used to optimize both initial conditions and suitable parameters of the emission model. A forecast experiment has been performed and the contribution of data assimilation to the one-day-ahead forecast has been studied.
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