Averaging the 3 DV to get the final future year 5 year weighted average DV:

(63.7 + 57.0 + 59.9)/3 = 60.2 = 60 ug/m3

In the above examples, emissions reductions from steel mills were modeled with a

dispersion model, which provided additional reductions to the future year 5 year weighted

average annual and 24-hour design values. Changes in design values derived from

photochemical modeling should be evaluated to determine the magnitude (on concentrations) of

emissions changes from the flagged steel mills. The change in concentration in the

photochemical model from emissions controls on the steel mills may need to be subtracted from

the final design value to ensure that there is no double counting of emission reductions.

Double Counting

The methodology discussed above may result in double counting of local emissions

sources and reductions. The change in emissions from local sources is counted once in the

photochemical modeling and again in the dispersion modeling. There are several ways to

account for this issue.

1) Run the photochemical model without the primary PM2.5 emissions from the flagged sources

in both the base case and future case(s).

2) Run the grid model with a source tagging approach. The flagged sources can be tagged so

that their contribution in the grid model can be explicitly tracked (Douglas, 2006) (Environ,

2006a), (Environ, 2006b).

3) Employ a methodology to combine the results of the grid and dispersion models so that

double counting is eliminated or minimized. Several techniques have been developed to do this

(Isakov,2007).

4) Assume that double counting is small enough to be ignored.

 

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