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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