Next, determine which 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.

4.0 Summary

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.


n1201 - n1202 - n1203 - n1204 - n1205 - n1206 - n1207 - n1208 - n1209 - n1210 - n1211 - n1212 - n1213 - n1214 - n1215 - n1216 - n1217 - n1218 - n1219 - n1220 - n1221 - n1222 - n1223 - n1224 - n1225 - n1226 - n1227 - n1228 - n1229 - n1230 - n1231 - n1232 - n1233 - n1234 - n1235 - n1236 - n1237 - n1238 - n1239 - n1240 - n1241 - n1242 - n1243 - n1244 - n1245 - n1246 - n12247 - n1248 - n1249 - n1250


   Flag of Portugal 


 castellano: DISPER CUSTIC DESCAR RADIA    italiano:     


 français:    português:  





deutsch: DIS CUS  DES  RAD

castellano: DIS CUS DES  RAD   english: DIS CUS DES RAD  


 português: DIS CUS DES RAD   italiano:   DIS CUS  DES RAD


français:  DIS CUS DES RAD