Meteorology[1] is fundamental for the dispersion of pollutants because, the ground-level concentrations (GLC) of pollutants are primarily controlled by two meteorological elements:

• Wind direction and speed (for transport), and
• Turbulence and mixing height of the lower boundary layer (for dispersion).

Therefore, it is important that meteorology is carefully considered when modeling. The meteorological data requirements for steady-state Gaussian-plume models and advanced dispersion models vary considerably. Steady-state Gaussian-plume models require meteorology data from a single surface station. They assume that the single station data are applicable to the whole modeling domain up to the top of the boundary layer and that conditions do not vary with height.

Advanced dispersion models - including puff, particle and grid models - allow meteorological conditions to vary across the modeling domain and up through the atmosphere. This is a much more complex situation than for steady-state modeling and thus requires much more complex meteorological data.

In this section, we will be discussing the primary and derived meteorological variables used in the steady-state Gaussian-plume models. The wind speed, wind direction, temperature, temperature difference, humidity, precipitation, pressure, and solar radiation are considered primary in that they are generally measured directly. The derived variables are atmospheric stability, mixing height, and turbulence.