necessary to capture spatially differing, complex non-linearities between ambient ozone and

precursor emissions. That is, it is difficult to tell whether or not a modeled exceedance obtained

on one or more days selected from a limited sample of days is consistent with meeting the

NAAQS. To do so would require modeling several years and, perhaps, many strategies. This

problem is reduced by using the monitored design value, as an inherent part of the modeled

attainment test.

3. PM2.5 consists of a diverse mix of primary and secondary components. This raises a

concern about a model’s potential inability to correctly predict values for each component which

are proportional to the observed mix of components. Failure to predict major measured

components of PM2.5 in the correct proportion increases the possibility of choosing ineffective

control strategies on the basis of incorrect model predictions. This possibility is reduced if the

model responses are instead applied to components of PM2.5 which are derived from


4. Model results and projections will continue to have associated uncertainty. The procedure

we recommend recognizes this by including modeling plus other analyses to determine whether

all available evidence supports a conclusion that a proposed emission reduction plan will suffice

to meet the NAAQS. For applications in which the modeled attainment test is not passed, a

weight of evidence analysis may be used to support a determination that attainment will be

achieved, despite the results of the modeled attainment test. The weight of evidence

determination includes several modeling results which are more difficult to relate to the form of

the 8-hour ozone and 24-hour PM2.5 NAAQS. These results address relative changes in the

frequency and intensity of high modeled ozone or PM2.5 concentrations on the sample of days

selected for modeling. If corroboratory analyses produce strong evidence that a control strategy


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