SILAM (System for Integrated Modeling of Atmospheric Composition) is a global-to-meso-scale

atmospheric dispersion model Atmospheric dispersion modeling is the mathematical simulation of how air pollutants disperse in the ambient atmosphere. It is performed with computer programs that include algorithms to solve the mathematical equations that govern the pollutant ...

developed by the

Finnish Meteorological Institute The Finnish Meteorological Institute (FMI; fi, Ilmatieteen laitos; sv, Meteorologiska institutet) is the government agency responsible for gathering and reporting weather data and forecasts in Finland. It is a part of the Ministry of Transport ...

(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. The FMI provides three datasets based on SILAM: a 4-day global air pollutant (SO₂, NO, NO₂, O₃, PM_2.5, 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.

References

Atmospheric dispersion modeling Air pollution {{science-software-stub