SILAM
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SILAM (System for Integrated Modeling of Atmospheric Composition) is a global-to-meso-scale atmospheric dispersion model developed by the Finnish Meteorological Institute (FMI).
Model
[edit]It provides information on atmospheric composition, air quality, and wildfire smoke (PM2.5) and is also able to solve the inverse dispersion problem. It can take data from a variety of sources, including natural ones such as sea salt, blown dust, and pollen.[1]
The FMI provides three datasets based on SILAM: a 4-day global air pollutant (SO2, NO, NO2, O3, PM2.5, and PM10) forecast based on TNO-MACC (global emission) and IS4FIRES (wildfire), a 5-day global wildfire smoke forecast based on IS4FIRES, and a 5-day pollen forecast for Europe.[2]
References
[edit]- ^ Sofiev, M.; Siljamo, P.; Valkama, I.; Ilvonen, M.; Kukkonen, J. (February 2006). "A dispersion modelling system SILAM and its evaluation against ETEX data". Atmospheric Environment. 40 (4): 674–685. Bibcode:2006AtmEn..40..674S. doi:10.1016/j.atmosenv.2005.09.069.
- ^ "System for Integrated modeLling of Atmospheric coMposition". silam.fmi.fi.