Atmospheric Dispersion of Gaseous and Particulate Contaminants

Why dispersion modeling?

  • Assessing compliance of emissions with air quality guidelines, criteria, and standards

  • Planning new facilities

  • Determining appropriate stack heights

  • Managing existing emissions

  • Designing ambient air monitoring networks

  • Identifying the main contributors to existing air pollution problems

  • Evaluating policy and mitigation strategies (e.g. the effect of emission standards)

  • Forecasting pollution episodes

  • Assessing the risks of and planning for the management of rare events such as accidental hazardous substance releases

  • Estimating the influence of geophysical factors on dispersion (e.g. terrain elevation, presence of water bodies and land use)

Once a gas stream is exhausted into the atmosphere, it is transported downwind of the source. The contaminants can be removed from the atmosphere during transport by dry deposition, wet deposition, and by transformation to another material.

Dry deposition occurs when dispersed material diffuses, impacts, or intercepts some object on earth resulting in direct removal of the material from the atmosphere. Wet deposition occurs when the contaminant is captured in clouds (“wash out”) or precipitation that is falling through the atmosphere (“rain out”) and is then deposited to the earth.

Dispersion of contaminants in the atmosphere can be treated by numerous techniques. Box, Eulerian, Lagrangian, and semi-empirical semi-theoretical statistical techniques will be discussed.

Emphasis will be placed on the statistical technique, seeing that it is commonly used to model the dispersion of contaminants in the atmosphere.

Box Model

  • Simplest approach to predict the resulting concentration of a contaminant in the atmosphere that results from the emission of that contaminant into the atmosphere. This model is useful to discuss conceptually, but has limited applications due to the necessary assumptions used in the development of the model.

  • The model considers a contaminant that is emitted into the atmosphere with some source of strength (Q1) and flux (F1) into a box that has a certain length (L), width (W), and height (H). The wind has a constant speed as it passes through the box. The resulting downwind concentration of contaminant as predicted by the box model is defined as C2.

  • Useful to get an understanding of how source strength, wind speed, and vertical cross-sectional area of the box play roles in the resulting concentration of contaminant in the atmosphere.

  • Unfortunately, the model does not consider change in wind speed with height, concentration gradients within the source’s plume, chemical reactions, stability of the atmosphere, deposition of the contaminant, and topography. Therefore, we need more detailed models to adequately describe dispersion of contaminants in the atmosphere.

Lagrangian

  • Applying conservation equations with a Lagrangian frame of reference considers an air sample containing the contaminant relative to the moving fluid. The frame of reference would move with the sample as the sample is transported in the atmosphere.

  • The model could consider the physical properties of the sample and the sources, sinks, and chemical reactions that would influence the sample during the transport.

Eulerian

  • Applying conservation equations with an Eulerian frame of reference considers an air sample containing the contaminant relative to a fixed coordinate system. The frame of reference would be stationary while viewing the air mass as it passes through each grid within the spatial domain.

  • Once again, the model could consider the physical properties of the air mass and the sources, sinks, and chemical reactions that would influence the sample during transport.

Models using conservation equations with the Eulerian or Lagrangian frames of reference are useful to predict how contaminants are transported, and then removed from the atmosphere. Unfortunately, these models require large amounts of information to adequately execute the models and they can require large computing capabilities.

Gaussian

  • The semi-empirical, semi-theoretical statistical technique, also known as the Gaussian dispersion model is a much simpler and more readily available model when compared to the more general models using conservation equations.

  • Has also been approved by US state and federal environment to predict local air quality that would be affected by the operation of a source of air contaminant. The model is used to predict air quality conditions as needed for facilities to obtain certain permits to construct and operate a source or set of sources at the facility.

  • Developed by Sutton as part of the Chemical Defense Establishment (1918). Further theoretical considerations about atmospheric turbulence was then considered by Taylor. Hay and Pasquill (1957) developed Taylor’s results to refine the Gaussian dispersion model for transport of contaminants in the atmosphere.

  • Numerous field experiments were then performed to see how the contaminants were actually transported in the atmosphere and how well the experimental results agreed with the modeled results. Further improvements in the Gaussian dispersion model then occurred with respect to transport near the source of the contaminant.

  • Considerations of plume rise associated with the plume’s momentum and buoyancy at the outlet of the exhaust stack were considered by Briggs and others. More recently Gaussian dispersion models have been modified to consider topography and chemical reactions of the contaminants that would occur during atmospheric transport.

  • Application of the model to atmospheric dispersion of a contaminant from an elevated point source