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The variables needed for machine learning are different than a standard air quality model. It's actually a much shorter list because you don't have to numerically model atmospheric motion/chemistry/deposition. Most AQMs have a spatial domain that has horizontal and vertical depth. However, the machine learning forecasts I've seen are only for point ...


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From Seigneur C., Dennis R. (2011) (free access here, probably not in the final published form): Inputs to air quality models include the emission rates of primary air pollutants and precursors of secondary air pollutants, meteorology (three-dimensional fields of winds, turbulence, temperature, pressure, boundary layer height, relative humidity, clouds and ...


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