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Air Quality Modeling

To predict air quality impacts from a project that is still on the drawing board, and for which and Environmental Impact Assessment (EIA) is being conducted, Air Quality Modeling may be the only possible method to arrive at realistic estimates of possible impacts.

An air quality or dispersion model is a mathematical description of the meteorological transport and dispersion processes as well as chemical reactions and transformations and settling and wash-out, that translate the emissions from one or several sources into ambient concentrations or immissions of one or more pollutants.

 
Air Quality Modeling:
introductory lectures

Environmental standards important for Impact Assessment are formulated either in terms of

  • emission related limits including regulations on furnaces, engines and fuel quality;

  • air quality guidelines or thresholds for ambient concentrations (immissions).

Model come in many different styles, depending on the intended purpose but also the available data, but in principle they all are of a general form:

   C(x,y,z,t)  =  f(Q,M)

where C is the ambient concentration at the location (x,y,z) and time (t), which is a (more or less complex and dynamic) function of the emissions (Q) and the meteorology (M), Q and M being complex constructs themselves and in most cases of high dimensionality, spatially distributed and dynamic.

A typology of models

Models can be based on a a number of priciples and approaches, and can have quite different levels of complexity in the underlying theory and the set of assumptions they represent:

Dynamics:

  • steady-state models (the most commonly regulatory model based on the Gussian equation are of this type)

  • dynamic models treat the metoeorology and/or the emissisons as a function of time. This is essential where key meteorological parameters such as wind speed and direction can be changing faster than the system can reach steady state (e.g., in coastal locations), or where temporal emission patterns are important.

Spatial distribution

  • spatially lumped (box models), irrespective of the temporal dynamics and resolution or process complexity: box models are useful when the topography can be approximated by a box (like in a narrow valey under stagnant conditions.

  • spatially distributed: this can be interms of

    • one dimension: along the main wind axis)

    • two dimensional: downwind and crosswind, in a horizontal plane

    • multi-layer: two-diemensional models that describe several (coupled) vertical layers;

    • three dimensional (comparable resolution along all three axis, full coupling in all directions)

Source types:

  • point sources, the most common type representing industrial stacks; this includes a description of plume rise due to momentum and thermal buoancy;

  • are sources: usually understood as an agglomeration of numerous small point sources not treated individually; typical examples are residential heating, or industrial parks with numerous small stacks; area sources are also important in the modeling of particulates, where they contribute particles due to wind induced entrainment.

  • line sources: typical for the analysis of traffic generated pollutants;

  • volume sources: used, for example in the analysis of aircraft emissions that can be treated as a three dimensional volume of pollutnts generated primarily at start and landing (TOL cycles).


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