Next, determinewhich emissions trends to consider. This requires two questions to be
addressed: (1) do I consider VOC, NOx or emissions of both? and (2) what trend parameter
should I use to characterize the change in emissions? To address the first question, use
available urban scale modeling or ambient precursor data (Section 2.1) to identify the
precursor of principal concern in the local (i.e., nonattainment) area. Use results from past
regional modeling analyses to identify the precursor of principal concern in the larger,
regional area. If it is not clear from the available information which precursor is the
controlling one in the local area or the regional area, consider trends for both precursors in
the area(s) for which this is unclear.
To address the second question, we recommend using seasonal mean emissions estimates.
This, in effect normalizes year-to-year emissions for meteorological differences. Further,
uncertainties in estimating emissions factors and activity levels for specific days are likely to
be sufficiently large so as not to warrant this level of detail.
3.2.2 Some Concerns And Caveats
We have several concerns about the proportional extrapolation approach. Thus, for
various reasons, we recommend that States use results from photochemical grid models to
establish targets for comparison whenever feasible. First, the relationship between ozone
formation and precursor emissions can be a non-linear process under a number of
environmental conditions. Linear approximations work best if the current ozone (i.e., at midcourse
review time) is close to 124 ppb. If this difference is more than, say, 5 ppb, States
should consider developing an EKMA isopleth diagram to ensure that there is no intervening
ridge line between the current and desired air quality if a given precursor is reduced.
Presence of a ridge line indicates that reductions of one precursor may result in little or no
change in ozone while reductions in the other precursor may result in large changes in ozone.
Another analysis which might be performed to increase the weight of evidence produced by an
extrapolation methodology is to review correspondence between observed air quality trends
and estimated emissions trends to see whether something other than a linear curve provides a
better description of this correspondence. An extrapolation methodology which is analogous
to the one described herein (but reflecting a non-linear correspondence) could be applied.
Second, the extrapolation requires one to make previous assumptions about what kind of
emissions are important determinants of observed ozone, as well as where these emissions
are located. It is unlikely that these assumptions will be as reliable as those made with
models, as the models are better able to consider meteorological factors which influence the
importance of emission configurations on ozone concentrations.
States should first do an administrative review to determine whether the scheduled
number of measures called for in the SIP have been implemented and that
legal/administrative prerequisites are in place to implement the remaining measures identified
in the SIP revision. If these targets are not met, there is cause for concern that the SIP is not
on track toward attainment.
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