Selecting days to derive RRF values. RRF values should be estimated by taking the

ratio of future predictions averaged over several days to current predictions averaged over the

same several days. It may often happen that a regional planning organization or a group of

States decides to model effects of a strategy for numerous Class I areas simultaneously. As we

note in Section 14, this may make it advisable to simulate (at least) a full year so that relative

response factor (RRF) values for each Class I area is based on a substantial number of observed

“best” and “worst” days. For the “worst” days in the chosen year, the RRF for a component of

PM should be estimated as the ratio of its arithmetic mean predicted value on the 20% worst

days with future emissions to that with baseline emissions. Thus, the RRF should reflect values

averaged over ~ 24 “worst” days in that year. The same procedure is followed to derive RRFs

over the ~24 “best” days in the year.

If it is not feasible to model an entire year, or if only a small number of Class I areas is to

be considered, a State should examine when worst visibility is observed to occur. Choose a

sample of days from each quarter in which an incident of “worst” visibility occurs and calculate

a RRF estimate for each component of PM. The appropriate RRF value would be applied to

monitored “worst visibility” days. There is not, as yet, a good basis for suggesting a minimum

number of days to choose for this purpose. However, information presented in Section 14.1.4

suggests that this number should be > ~10 days.

Since meteorological conditions and/or emissions may be markedly different on “best”

visibility vs. “worst” visibility days, we recommend calculation of a separate set of RRF values

 

 

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