In addition to ozone trend parameters, States with data from Photochemical Air

Monitoring Stations (PAMS) and/or reliable NOx measurements can consider trends in

precursor concentrations to see whether they appear to track emission control programs

which have been implemented. Use of PAMS data to estimate trends is described by Main

and Roberts (2000). Because precursor data may be subject to larger fluctuations than ozone

concentrations, we suggest using trend parameters like median or mean concentrations

observed during the summer (or ozone season) months. Since some of these data are not

likely to be measured continuously, mean values measured at a specific time of day (e.g., 6-9

am) may need to be used. The standard deviation in the chosen precursor trend parameter

may also be useful to compute to get a sense of how variable precursor concentrations are

during the course of each ozone season. Comparing this intra-annual variability with trends in

mean or median observations may provide a sense of the strength of the trend evidence

resulting from the precursor measurements.

Normalizing observed trends in ozone for meteorological differences. Generally, the trend

parameters we identify for ozone reflect the fact that the NAAQS focuses on extreme values.

Year to year fluctuations in meteorology may have a more pronounced effect on extremes

than on concentrations in the middle of a range of observations. Thus, in order to be able to

interpret observed changes in selected trend parameters, it is necessary to adjust the trend so

that it reflects differences in meteorology. Any credible procedure for adjusting air quality

trends for meteorological differences is acceptable. Several procedures for doing this are

reported in the literature.

Cox, et al. (1993) describe a method which has been used to adjust daily maximum ozone

concentrations for severity in meteorological conditions during any particular year. The

methodology develops a regression relationship between daily maximum ozone (dependent

variable) and several meteorological variables. This relationship defines each day’s ozone

forming potential. By going back over a long period of record (e.g., 40 years), severity of

meteorological conditions accompanying any given incident of high ozone can be characterized

in terms of climatological norms. This information can be used as a basis for adjusting the raw

observed air quality values. Use of the Cox, et al. methodology is illustrated in U.S. EPA

trend reports, as well as in U.S. EPA (1996).

Another method for adjusting observed trends is use of the Classification of Regression

Tree (CART) analysis procedure, as described in Dueul, et al. (1996). The widely-used

CART procedure identifies combinations of meteorological parameters which frequently

appear to coincide with high observed ozone concentrations. Noting differences in the

 

 

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

 

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