SILAM (System for Integrated Modeling of Atmospheric Composition) is a global-to-meso-scale atmospheric dispersion model developed by the Finnish Meteorological Institute (FMI). 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.
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