Choose a sufficient number of days to enable the monitored attainment test to be based on
multiple days at each monitoring site violating the NAAQS.
Figure 4.1 indicates that the relative response factor computed at any given site appears
to be affected by the minimum threshold value. Based on an analysis of modeled data, the
recommended minimum (baseline) threshold value is 85 ppb. The minimum threshold value
analysis (detailed in section 4.1) was also used to examine how the number of days contained in
the mean RRF calculation influences the mean RRF. It was found that, on average, a minimum
of 10 modeled days (in the mean RRF calculation) produces mean RRFs that are relatively
The analysis cited earlier in the guidance (Timin, 2005b) was used to help determine the
minimum number of days to use in a mean RRF calculation. The dataset consisted of 206
monitoring sites which had at least 10 days with predicted 8-hour daily baseline maximum ozone
concentrations > 85 ppb. In the analysis we assumed that a mean RRF calculated from a “large”
set of days is more stable than an RRF calculated from a small set of days. Using information on
the variability of the model response on individual days, we are able to measure the variability of
the mean RRF on any subset of days. The analysis used datasets of 25, 50, and 100 days95. The
standard deviation of the daily RRFs was used to create the datasets and measure the variability
of the RRFs.
Figure 14.1 shows an example of the variability of the mean RRF as a function of the
number of days in the mean RRF calculation. The example plot is for a monitoring site in
Harford County, MD. The mean RRF for a 50 day sample size is 0.90 (10% ozone reduction).
The standard deviation of the daily RRFs was 0.034 (3.4%)96. The plot shows the range of the
mean RRFs calculated using a sample size ranging from 3 to 25 days (a subset of the 50 days).
Each subset (3 days, 4 days, 5 days, etc.) was sampled 1000 times. As can be seen in the plot,
the range of mean RRFs varies widely for a small sample size (3 days) and is relatively stable for
a large sample size (25 days). As the number of days increases, the variability of the mean RRF
decreases. A similar conclusion was reached in a different study (Hogrefe, 2000) which found
that the RRF is more variable when based on a small number of days.
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