The size and location of the modeling domain define the data

requirements for the modeling. In selecting a modeling domain,

consideration should be given to (1) typical wind patterns, (2) the

location of major area and point emission sources, (3) the location

of air quality monitors and important receptor locations, and

(4) the need to mitigate effects of uncertainty in upwind boundary

conditions. Generally, the domain should be set as large as

feasible in order to reduce the dependence of predictions on

uncertain boundary concentrations and to provide flexibility in

simulating different meteorological episodes. It is generally much

easier to subsequently reduce the size of a modeled area than it is

to subsequently increase it.

Once UAM input data for a sufficiently large domain have been

assimilated and processed, the size of the modeling domain can be

reduced for modeling purposes by specifying domain boundary values

in the UAM. Procedures for reducing the size of the domain are

described in Reference 2. This could save resources in simulating

modeling episodes in which light or poorly defined wind fields

result in a smaller domain being adequate. In contrast, expanding

domain dimensions would require reconstructing most of the UAM

input files.


It is recommended that the domain's downwind boundaries be

sufficiently far from the CMSA/MSA that is the principal focus

of the modeling study to ensure that emissions from the

CMSA/MSA occurring on the primary day for each selected

episode remain within the domain until 8:00 p.m. on that day.

The extent of the upwind boundaries will depend on the

proximity of large upwind source areas and the adequacy of

techniques7 used to characterize incoming precursor

concentrations. Large upwind emission source areas should be

included in the modeling domain to the extent practicable.

Also, if large uncertainty is anticipated for domain boundary

conditions, the upwind boundaries should be located at a

distance sufficient to minimize boundary effects on the model

predictions in the center of the domain. Sensitivity analyses

described in Section 4.3 assist in determining the effects of

boundary conditions on predicted values.


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