Ideally, the modeled attainment test should reflect model results obtained for days in

each season having observed PM2.5 concentrations slightly below as well as above the design

value. This may seem strange at first. The underlying reasons are that PM2.5 consists of a

mixture of pollutants. Composition of the mixture could vary substantially from season to

season. Second, there could be a substantial amount of uncertainty associated with predictions

on any single day. Thus, our test is most likely to be reliable when relative response factors

reflect composite responses from many days. Therefore, we recommend modeling as many days

as feasible where observed PM2.5 is greater than 65 :g/m3. Alternatively, the test can focus on

the high end of the distribution of days in each quarter, (e.g. the top 25% of PM2.5 days)

assuming that many of the high days violate the NAAQS (or are representative of days that

violate the NAAQS). As with the annual NAAQS (and for the same reasons), the preferred

approach is to develop relative response factors which are season (i.e., quarter) specific.

We have noted that it is desirable to base our conclusions on a composite response of the

model(s) over many days. However, there is not likely to be many days with observed

concentrations greater than 65 :g/m3. If this results in a sample size of smaller than about 5 days

per quarter then the analysis should focus on the high end of the distribution of PM2.5 days in

each quarter (e.g. the top 25% of PM2.5 days51).

The 24-hour attainment test should be based on the same 5 year weighted average

methodology that was used for the annual standard, with some slight modifications. The 24-hour

design values are calculated from the 98th percentile value for each year. We recommend

applying the attainment test on an annual basis and then averaging the annual average results up

to 3 year averages and then averaging again to get a 5 year weighted average.

PM2.5 is a complex mixture of components that have significant seasonal variations. If the

observed 98th percentile value came from the 1st quarter, it is possible that an observed

concentration from a different quarter, which may have a slightly lower concentration, could

become the 98th percentile value in the future. It is important to demonstrate that the standard

will be met for all seasons. Therefore we recommend applying the test by quarter for each



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