Two models were selected for consideration for an interim

approach, the Acid Rain Mountain Mesoscale Model (ARM3) (Morris

et al., 1988) and the MESOPUFF-II model (Scire et al., 1984b).

The MESOPUFF-II model was considered by the EPA for inclusion

in its list of refined models in the Guideline, but was

subsequently suggested for inclusion only in Appendix B of the

Guideline, the section reserved for models which could be

considered for regulatory use, but not generically preferred.

The NPS has been evaluating the ARM3 for use in its program of

evaluating the impacts of air pollution in the national parks.

As part of this evaluation, they chose to compare some of the

ARM3 results against MESOPUFF-II because of MESOPUFF-II's

availability and its consideration by the EPA. These two

models both contain features considered desirable in a model

for use in long range transport to Class I areas, particularly

the ability to consider the chemical transformation of SO and 2

NO to SO and NO and the removal of chemical species through X 4 3

= 

deposition. In addition, the ARM3 contains algorithms for

considering the effects of terrain on dispersion and on the

transport flow. Furthermore, both of these models have been

compared against other, similar models and have performed

somewhat better than those other models relative to measured

tracer data (Carhart et al., 1989; Moore et al., 1990).

The IWAQM recognizes that there are certain risks involved

with recommending an interim long range modeling approach.

From a regulatory perspective, it is generally desirable to use

an interim model which will yield somewhat higher impact

calculations than a more refined, preferred approach. In the

case of steady-state air quality models for example, this can

be relatively easily ensured because of the independence of the

concentration calculations from one hour to the next. In the

case of the Lagrangian long range transport models under

consideration here, the concentration calculations for a given

hour will be explicitly dependent on the spatially and

 

 

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