5.0	Time-Distance Considerations Relevant to "Transport" and Regions of Influence

5.A	Introduction

The issue of ozone and/or precursor transport as a requisite for or a major contributor to ozone episodes has been discussed in scientific meetings focused on air quality and in the literature, but no definite conclusions have been reached. For the most part, there is insufficient evidence to determine conclusively when and how often transport is important in episode situations. The evidence must come in two parts: (i) transport of ozone and/or precursors must be demonstrated and (ii) it must be shown that the transported ozone and/or precursors played a significant role in the development of an episode. The area which contributed ozone/precursors to the episode, "the area of influence," (AOI) should also be subjected to these criteria. The available evidence suggests that there are situations in which episodes would not have occurred without the effects of transport (Jeffries, Personal Communication, 1996; Dennis, Personal Communication, 1996), but the evidence also indicates that regional scale episodes occur, for the most part, in situations that minimize transport. This document briefly summarizes what we do know about the meteorology of ozone episodes to examine when and how transport may provide a major contribution to ozone episodes. With this background established, we examined the recent results of Zurbenko et al (1995), Rao and Zurbenko (1994), Rao, et al (1995), Flaum et al (1995), and Dennis (1996) to determine what new information might be available concerning the issue of ozone and/or precursor transport and the AOI. These papers are available in Appendix A.

5.B	Meteorology of Ozone Episodes

In a recent study of the time scales for ozone, it was found that high frequency variations were dominated by 3- to 10-day time scales which are consistent with that for synoptic weather systems (SWSs)(Vukovich, 1996). The day-to-day variations of ozone are significantly influenced by SWSs which is supported by the fact that high ozone is normally found in association with migratory high pressure systems (HPS) and low ozone, with frontal passage and migratory low pressure systems (LPSs) (Bach, 1975; Bach et al., 1977; Vukovich et al., 1977; Ludwig et al., 1977; Ripperton et al., 1977; Vukovich, 1979; King and Vukovich, 1982; Korsog and Wolff, 1991; NRC, 1992, EPA, 1996; Vukovich, 1994; Vukovich, 1995; Stasuik and Coffey, 1974; Buntz et al., 1974; Decker et al., 1976; Vukovich and Fishman, 1986; Wolff et al., 1977; Husar et al, 1976; Samson, 1980; Wight et al., 1978; Lyons et al., 1978; Mueller et al., 1980; Wolff and Lioy, 1980). Therefore, as SWSs pass through a region, they modulate the ozone concentration. Fundamentally, chemistry, meteorology, and emissions are the defining processes that govern the behavior of ozone in the atmospheric boundary layer, but the existing evidence suggests that ozone variations in the 3- to 10-day range in the eastern half of the United States are dominated by SWSs.

High ozone can and has occurred most everywhere east of the Mississippi River and depends on the path of the HPSs (Vukovich and Fishman, 1986). As the HPS approaches a region, ozone increases reaching a maximum on the backside of the HPS (i.e., on the westside of an eastward moving HPS) (Vukovich et al., 1977; Ludwig et al., 1977; Ripperton et al., 1977; Vukovich, 1979; King and Vukovich, 1982; Wolff et al., 1977; NRC, 1992). The size of the area over which above standard ozone concentrations (i.e., the time and space scale of above standard ozone) may be found, is controlled, to a large degree, by the speed and intensity of (and the dynamic process in) HPSs (Vukovich and Fishman, 1986; Vukovich et al., 1977). These scales are modified by the chemistry, emissions, and deposition; the processes not directly associated with HPSs that affect ozone. The region of above standard ozone is usually imbedded in the area of relatively high ozone, and the size of the area of high ozone and magnitude of the ozone concentrations in that area are smaller in faster, more intense migratory HPSs (Vukovich et al., 1977; Ripperton et al., 1977; Vukovich and Fishman, 1986). On the other hand, the size of the area and the magnitude of the ozone concentration are larger in slower, weaker HPSs.

The largest area for and magnitude of ozone in high ozone situations of regional dimensions are found in quasi-stationary, weakening, and dissipating HPSs. For example in the 1- 15 July 1988 episode in the eastern United States, a HPS occupied the region east of the Mississippi River during most of the period. The HPS was quasi-stationary, weakening (i.e., the central pressure was decreasing), and dissipating (i.e., the strength of the pressure gradient was decreasing). The region east of the Mississippi River was characterized by weak winds (i.e., wind speeds ≤ 3 m/s) and disorganized flow from the surface to at least the 7-km level in the atmosphere. The weak winds and disorganized flow occurred because there was no strong pressure gradient to support a wind field, let alone organized flow. In the period during this stagnation event, high ozone (i.e., ozone concentrations greater than 90 ppb) was found in areas that covered up to about 70% of the area east of the Mississippi River, and when above standard ozone developed, it covered up to about 30% of that area.

High ozone in HPSs and low ozone in LPSs often develop in very definite meteorological scenarios that are associated with these weather systems. High ozone is very often found in the region of a migratory or quasi-stationary HPS characterized by light winds, disorganized flow, relatively high temperatures and humidities, low precipitation, limited vertical mixing (i.e., capping inversion aloft), and subsidence. Exceptions to this scenario have been noted. For example, in the northeast corridor, high ozone has occurred when there were relatively strong winds and organized flow, which suggest the influence of transport. Low ozone is generally found when fronts associated with an LPS sweep through the region. At this time, the region is characterized by relatively low humidities and temperatures, strong organized boundary layer flow, and deep, strong convective activity. No single meteorological parameter (e.g., temperature, humidity, wind, or pressure) can act as a surrogate for these meteorological conditions and processes at synoptic time scales (Vukovich, 1995). For example, application of surface temperature for this purpose (e.g., Wackter and Bayly, 1988; EPA, 1996) has shown a general trend for ozone to increase with increasing temperature, but these data also show that for any given temperature, the range in the ozone concentration is as much 100 ppb (i.e., for a given temperature, the ozone concentration could be 50 ppb below the standard or 50 ppb above). Furthermore, it was shown (Vukovich, 1995) that, though the low ozone often coincided with the low humidities and temperatures found after frontal passage, peak temperatures and humidities generally occurred one or two days after the peak value of ozone was reached (or the region of highest temperatures and humidities was located upstream from the region of highest ozone), suggesting that there is no relationship between the meteorological processes causing the highest temperatures and humidities and those influencing the highest ozone.

5.C	Conditions For Transport

For long-distance transport of ozone and/or ozone precursors to occur as an identifiable species, two conditions must be satisfied: (i) the air mass being transported must maintain its integrity (i.e., the ozone/precursor air mass that is being transported must be in a quasi steady- state) and (ii) organized flow must develop and persist over a large area. The region in the atmosphere that can support both these conditions is the free troposphere (i.e., the region above the boundary layer). Ozone and/or its precursors are generally not in a steady state in the boundary layer so that long-distance transport in this region of the atmosphere is difficult to quantify; but transport can occur in the boundary layer in the form of a non-steady polluted air mass rather than strictly as ozone and/or its precursors. These are the conditions modeled by Dennis (1996), but even in this case organized flow must persist to provide transport over relatively large distances.

Most of the tropospherically-produced ozone is created in the boundary layer (Vukovich et al. 1985, Lui et al, 1987, Linn et al, 1988, Trainer et al, 1987). Mid-afternoon profiles of ozone obtained during episode situations (Vukovich et al, 1985; Huffman et al, 1977) have indicated that the highest ozone is found in the surface layer and that ozone decreases with height throughout the boundary layer, suggesting that the daytime mixing could transport ozone to the free troposphere. Some ozone can reach the free troposphere by a cloud venting processes in the presence of convective clouds (Vukovich and Ching, 1990; Ching et al, 1988; Gidel, 1983). When the nocturnal surface inversion was created in an area characterized by high ozone or episode conditions, high concentrations of ozone persisted above the top of the surface-based inversion layer, which generally has its top at about the 200-300-m level, presumably because the inversion limited the mixing and thus prevented the surface-based ozone destructive agents from penetrating above the inversion; whereas the ozone in the inversion layer was destroyed principally by NOx. The upper-level ozone will, therefore, maintain its integrity, especially the ozone at or above the top of the mid-day PBL, and can be transported a fair distance during the night provided there is organized flow. After sunrise and as the boundary layer developed, the profile data indicated that large increases in ozone occurred in the surface layer presumably due to ozone production and the mixing down of ozone from above when the inversion layer broke up. As the boundary layer developed, the ozone that was above the inversion layer became boundary layer ozone again, losing the quasi steady-state characteristic it maintained at night.

Strong organized flow is not normally a requisite condition for the development of high ozone, and it is usually associated with pre- and post-frontal conditions which is where low ozone is found. Sizable concentrations of ozone and/or its precursors can be absorbed into a strong organized flow, however, as a result of the motion of SWSs. SWSs move by dissipating in their present location and reforming in a new location. This dissipating/reforming process can provide a pressure pattern and associated processes (i.e., weak pressure gradients, subsidence, weak winds, and no organized flow) that support the accumulation of ozone and/or its precursors in a certain location on one day. Whereas on the next day, the dissipating/reforming process can produce strong pressure gradients, strong winds, and organized flow in that same location which will initiate the transport of that ozone and/or its precursor.

When a HPS moves to a new location, the background ozone and/or precursors in that location are, for the most part, transported ozone and/or precursors. If, then, the HPS provides conditions that lead to a regional ozone episode (i.e., the HPS is quasi-stationary, weakening, and dissipating), regional high ozone develops quickly, but an episode with regional dimensions generally does not because it needs time to build-up. For example, in the 1-15 July 1988 episode, the HPS moved into the eastern United States on 2 July. From about 2 July through 11 July, the region east of the Mississippi River was characterized by weak winds and disorganized flow from the surface to at least the 7-km level. These flow conditions nullified any further long-distance transport in or immediately above the boundary layer in that region for that period. High ozone (i.e., ozone concentrations greater than 90 ppb) with regional dimensions developed on 3 July and persisted through 11 July. Above standard ozone with regional dimensions, however, developed on 6 July, five days after the HPS moved into the region, and persisted through 11 July. Isolated episodes occurred in that region before 6 July, but it was not until 6 July that a regional-scale episode existed. The transported or background ozone and/or precursors undoubtedly played a role, and possibly even a significant role, in the development of the regional-scale high ozone condition on 3 July. However, it is unlikely that the transported ozone and/or precursors contributed directly to the regional-scale episode on 6 July, considering that four days of chemistry preceded the regional episode in which the transported ozone and/or precursors should have lost their identity; but it is possible that the transported background ozone and/or precursors could have initiated a sequence of events that over a period of days led to the regional episode.

5.D	Time Series Analysis

The research of Zurbenko et al (1995), Rao and Zurbenko (1994), Flaum et al (1995), and Rao et al (1995) has focused on the use of time series analysis of ozone data and on the application of time series analysis in the development of methods to determine the effects of control strategies for urban regions. (Nota Bene: the authors listed in the previous sentence will hereafter be referred to as "they"). They divided the time series of urban ozone (X) into three components: a trend term (L); a seasonal term (S); and a remainder which included the short-term variations and which they called white noise (W); i.e.,

X(t) = S(t) + L(t) + W(t).

The deterministic portions of the time series (i.e., Y and Y(t) = S(t) + L(t)) were separated from the short-term variations (i.e., W) using a Kolmogorov-Zurbenko filter, which is a low pass filter produced by repeated iterations of a moving average. The same filter was applied to a temperature time series for the same period where temperature was used as a surrogate for all meteorological conditions. A linear regression was applied to the log of the filtered ozone concentrations and the filtered temperatures (T); i.e.,

Y(t) = aT(t + a) + b + L(t),

where a and b are parameters from the regression analysis and L(t) are the residuals of the regression and presumably provide the contribution due to non- meteorological processes (e.g., the effect of emission changes). They noted that there was a phase lag (a) between the filtered time series of ozone and temperature. A better relationship in the regression analysis was obtained when the phase lag was accounted for. (Adding dewpoint to the regression analysis improved the relationship even further.) The resulting regression term was the seasonal term (S); i.e.,

S(t) = aT(t + a) + b

Their analyses of the L(t) term across the eastern United States indicated that there was, in general, downward trend the air quality in the northeast in the period 1983 through 1992.

This approach to examine the behavior of ozone is new and provides some very interesting results. The filtering procedure, the Kolmogorov-Zurbenko filter, is also new and, therefore, has not been evaluated. The results of the filtering provides a times series of the intra-annual variations of surface ozone. The processes that influence the intra-annual time series as they described it include the intra-annual variations of UV radiation, which affects the production process, and of temperature, which affects the rate constants in the ozone chemistry, and the interannual fluctuations of climate, which affects emissions and chemistry. They used surface temperature as a surrogate for all meteorological conditions and modeled the intra-annual variations of ozone as a function of the filtered surface temperature. The residual from the modeled intra-annual ozone was considered the non-meteorological contribution to the long-term ozone variations. This technique has been used by many investigators in the past (Cox and Chu, 1992; Feister and Balzer, 1991; Bloomfield et al, 1993; Bloomfield et al, 1996). There is, however, a weakness in this modeling approach. There exit no objective means to assure that the total variance due to the meteorology is captured by the model (i.e., L(t) contains no meteorological affects). The fact that they obtained better results (i.e., the model accounted for a larger fraction of the variance) when they included humidity in the model (Flaum et al, 1995) is an indication of this problem. There may be other terms (e.g., precipitation, cloud cover, solar radiation, wind speed, and/or a term that provides some measure of stagnation) that when combined with temperature and humidity will provide a model that will account for an even larger fraction of the variance.

There is also a problem with the interpretation of the W(t) term. They have indicated that this term, which is strictly a time dependent term, has the properties of white noise. It is the only term that includes the high frequency variations of ozone (in particular, the variations associated with SWSs). One definition of white noise is a response due to random processes. It is hard to believe that any process associated with the behavior of ozone is random, particularly one associated with SWSs. In a recent paper (Vukovich, 1996), perturbation theory was used to separate the ozone time series into four terms, three representing the long-term effects of meteorology, emissions, and chemistry on ozone and one, the synoptic perturbation, providing the short-term effects. Vukovich's synoptic perturbation is, from a theoretical point of view, similar to the term W(t), though the two terms were calculated using different filters. Power spectra of the synoptic perturbation indicated that it was dominated by time scales of 3 to 10 days which are time scales consistent with SWSs. Furthermore, the synoptic perturbation was a maximum in the summer when the ozone chemistry is a maximum and a minimum in the winter when the chemistry is a minimum. These results suggest that the synoptic perturbation (i.e., the short-term variations of ozone) operates in a well-behaved system, responding to the processes (i.e., meteorology, emissions, and chemistry) that are most effective and those happen to be at the 3- to 10-day time scales (i.e., the time scales of synoptic-scale forcing). There are no random responses in the synoptic perturbation. Based on these results, it is not clear what is meant by the statement that W(t) has the properties of white noise. In subsequent analyses, W(t) has been called "the short-term (synoptic-scale) variation" (Memo from S.T. Rao dated 10 May 1996 to the FACA Science Team). W(t) has also been used in correlation analysis (Rao et al, 1995), and if W(t) was truly white noise, the correlation between the W(t) term from the ozone time series at one station with that at another station would be zero. The fact that they obtained results different from zero indicates that W(t) is not dominated by white noise.

Their correlation analysis applying the W(t) terms for temperature and ozone from stations across the United States was used to determine the space scales for the synoptic-scale forcing and for ozone. Time scales were determined by combining the space scales with typical wind speeds. By application of the temperature data, they found space scales about of 1000 km (Figure 1) and time scales of 3 to 5 days for the synoptic forcing. The space scale is consistent with that normally attributed to SWSs, but the time scales for synoptic forcing have generally been considered to be 3 to 10 days. This discrepancy is most likely due to the application of wind speed to estimate the time scales. This aspect will be discussed in detail shortly. The space scale determined for the ozone was 350 km (Figure 2), about 35% of the synoptic-forcing space scale, and the time scales for ozone were 2 to 3 days. This time scale for ozone is inconsistent with the 3 to 10 day time scales for ozone (Vukovich, 1996) discussed previously. This discrepancy may also be due to the application of wind speed to estimate the time scales, but not entirely.

It has been shown in Sections 2.0 and 3.0 that SWSs are significant forcing functions affecting ozone, and this forcing function operates at time scales that should predominate in the term W(t). The typical temporal and spatial behavior of ozone associated with cold frontal passage through the HPS that follows frontal passage to the next cold frontal passage showed that ozone is a minimum at cold frontal passage (Vukovich et al., 1977; Vukovich, 1995). As the HPS approached, ozone increased reaching a maximum on the backside of the HPS (i.e., on the westside of an eastward moving HPS). As the next cold front approached, the ozone decreased rapidly to low values again. This is precisely the modulation of ozone that is found in terms like W(t) that account for the high frequency variations of ozone. The modulation produced by the SWSs is modified, among other things, by the local chemistry, but the effects of the SWSs predominate or there would not be any

consistency in the ozone variations (i.e., there would not necessarily be a reasonable correlation between neighboring stations).

For example, consider an urban station and a rural station which is upwind of and about 50 km from of the selected urban site. The precursor emissions and the pathways for the ozone chemistry at these two sites should be significantly different, and yet significant correlations have been found at two such sites which are as much as 100 km apart (Rao et al, 1995) because there are over-riding processes, the processes associated with SWSs, that control the behavior of ozone sufficiently to produce consistency in the ozone variations and high correlations between the sites. It is doubtful because of the differences in the emissions and chemistry at the two selected sites that similar responses could be produced at the two sites over a period of days without focusing processes. The correlation between these two sites is a measure of the consistency between the processes that govern the behavior of the ozone at the sites. The correlation is large because the scale of the SWSs is large compared to the separation scale between stations; but the correlation is not 1.0 because the response at each site is also a function of the emissions and chemistry, which are different at the two sites, and of the speed of movement and intensity of the SWSs all of which vary in time and space.

As previously indicated, SWSs move by dissipating in their present location and reforming in a new location. This process governs the speed of movement of the SWSs, and the time scales associated with SWSs are a function of those speeds. The speed at which these systems move range from 0 (quasi-stationary summertime systems) to about 15 m/s (fast moving winter storms), and have no relationship to typical wind speeds. Furthermore, since these time series include ozone variations in the winter as well as the summer ozone season, the time and space scale derived through correlation analysis will be the integral of the effects of high energy, large, fast-moving winter weather systems and of the lower energy, smaller, slower-moving summertime weather systems, the former having no bearing on episodes or the space scale for high ozone and episodes. It may be possible to obtain a more realistic estimate of that space scale by piecing together those portions of the ozone time series dealing with the ozone season for each year, probably just the June-July-August period for each year since that period has the highest frequency of episodes, and applying correlation analysis to the truncated time series.

Though the changes in the procedure suggested above will probably improve the ozone space- scale estimates, they should not change the overall results; i.e., ozone variations have regional space scales. However, the reader is cautioned that the correlation analysis provides the space scale over which there is consistency in the ozone variations and/or processes, produced, for the most part, by SWSs. The correlation analysis in no way determines that the consistency in the ozone variation, and therefore that space scale, was a result of transport because correlation analysis alone will not isolate any one of the processes affecting the variations of ozone.

5.E	Model Applications and Transport

Dennis (1996) used the Regional Acid Deposition Model (RADM) to develop estimates of the range of influence for emissions subregions (i.e., areas of approximately 160 x160 km) on the surrounding air quality concentrations and on acidic deposition. The range of influence is the reverse of the AOI so to speak; i.e., the range of influence is the effective transport distance from the source and the AOI is the effective transport distance to the receptor. Under the same meteorological conditions, the numerical values for the range of influence and the AOI should be about the same.

The estimated range of influence was developed using a mix of meteorological conditions, one representing average annual conditions and another average growing season conditions. Meteorological cases which were derived using the University of Pennsylvania-National Center for Atmospheric Research Mesoscale Model (MM4) for the period 1982-1985, were grouped by applying cluster analysis according to the character of the 850-mb flow. The cluster analysis provided 38 groups, 19 groups involving storminess (wet group) and 19 groups that were void of precipitation (dry group). Meteorological cases for the model runs were randomly selected from each group and the number cases selected from the wet group out numbered those from the dry group to optimize the meteorology for deposition. Thirty 3-day meteorological cases were selected and more than half of these represented weather systems found in the growing season (i.e., April through September which is consistent with the ozone season), but a large percentage of the growing season cases were storm cases involving intense cold frontal activity (i.e., the growing season cases were also biased toward higher energy weather systems) and included very intense springtime storms. Five days were actually modeled, but the output from the first two days was ignored to remove any sensitivity to the initial conditions. The annual average estimates were developed as a statistical aggregation of the 30 3-day cases or a subset of the thirty cases in the case of the growing season averages. This aggregation method was developed for the purposes of acidic deposition (Brook et al, 1994a and 1994b), and has worked equally well for annual ambient sulfate concentrations (Eder and LaDuc, 1996).

The emissions and air quality associated with a particular emissions subregion were "tagged" by reducing the emissions for each of the 30 aggregation cases, subtracting the hourly concentrations from the base case (i.e., the case without emissions reduction), converting the difference to an effective 100% reduction in emissions, and aggregating the converted difference into an annual average. Since the procedure assumes the system response is reasonably linear, the results were examined to determine if there were non-linear distortions. For sulfate, the results were tested using the tagged engineering model (McHenry at al, 1992), which accounts explicitly for the nonlinearity in the oxidant competition for SO2 oxidation, and the results from the two approaches were very similar. Reductions in NOx were used to produce changes in ambient ozone. Several NOx emissions reductions ranging between 25% and 100% were implemented and the differences converted to an effective 100% reduction. The results were very similar, implying that since the majority of the domain is NOx-limited, the nonlinearities were not seriously distorting the estimated changes in ozone. However for some large cities, titration effects were noted so that the range of influence was developed for Ox, where Ox = O3 + NO2.

The aggregate results for air pollutants are for surface concentrations, and these were normalized by dividing the ambient concentration in each cell by the total accumulated ambient concentration over the entire domain. The percentage of the total accumulation was determined by summing the relative concentration, starting from the cell with the highest relative concentration. Contours of the sum were drawn at intervals 25%, 50%, 75%, and 90% which according to Dennis' experience provided a good spatial characterization upon which to base spatial range of influence estimates. He indicated that these contours can be used to represent the distances that account for the highest quarter, half, three-quarters, and ninety percent of the ground-level pollutants, respectively. He further stated that the distance from the source to the 67.7% contour line is a good estimate of the range of influence for that source.

Figures 3 through 6 provide examples of the growing season range of influence for the emissions from sources located south of Pittsburgh, Pennsylvania and from the Atlanta, Georgia area for Ox and SO4-2. The range of influence for Ox (i.e., ozone) is very similar to the combined range of influence for HNO3 and PAN which were presented in the paper by Dennis (1996). The results for the Pittsburgh area (Figures 3 and 4) show the distorting influence of the prevailing winds combined with the Appalachian spine. In these cases, the range of influence stretches for about 600 to 800 km in the direction of the prevailing wind (i.e., northeast-southwest) and only 200 to 400 km in the cross wind direction. On the other hand, the results for the Atlanta area (Figures 5 and 6) show a more uniform range of influence.

The results of Dennis (1996) demonstrate a broad range of influence for ozone for the two source regions (i.e., an ellipse for Pittsburgh with a major axis of about 800 km and a minor axis of about 300 km, and a circle for the Atlanta area with a radius of about 300 km). These results are accomplished because the meteorology that was used in the simulation is biased toward cases that maximize deposition (e.g., convectively active, cold front conditions and convectively active LPSs), which are the kinds of weather systems in which low ozone is found. Some, but all too few, low energy HPSs, the kinds of weather systems in which high ozone and episodes are found, are included in the simulations, but since only 3-day simulations are used and effective stagnation events persist for 5 days or more, the effects of the HPSs are truncated and underestimated. The higher energy frontal systems and LPSs generally move faster and, therefore, reside in a region a shorter time, so that the truncation effect due to the 3-day simulations should not be as severe. As previously noted, cold front conditions and LPSs are characterized by strong winds and large regions of organized flow which promote long-distance transport and large ranges of influence; whereas HPSs are characterized by weak winds and disorganized flow which nullify transport and promote a very confined region of influence. Furthermore, the highest frequencies of episodes are found in the June-July-August period when storms are generally weaker than those found in the spring, and therefore the long-distance transport may not involve as large distances as that associated with springtime storms. The combination of the weaker summer storms and stagnation events associated with HPSs in the June- July-August period suggest that the region of influence in that period should be smaller, and maybe much smaller, than those dictated by Dennis' results.

It should also be noted that Dennis' results involve 30 3-day simulation (Nota Bene: these were actually 5-day simulations, but only the last three days were used) so that the transport was confined to the 3-day period. In the real world, transport does not cease after three days, suggesting that the range of influence may be underestimated by Dennis' procedures. Dennis (Personal Communication, 1996) argues that the 3-day period is sufficient for deposition because by the end of three days, the particle/sulfate mass left in the atmospheric boundary layer near the boundary of the range of influence is trivial. He does concede, however, that the 3-day transport period may not be sufficient for ozone. Though the outer boundaries of the range of influence may not change significantly if the transport period is increased for ozone, the 25% and/or the 50% contours may expand over a broader area and more significant concentrations of ozone and/or precursors may be provided over a larger area. This aspect is speculation and requires further research.

Dennis (1996) examined the transport and range of influence associated with changes in emissions for an isolated source area with no regard to whether the transported ozone and/or precursors could in any way influence the development of an episode, either locally or regionally. Transport has been noted to be very influential in the development of isolated episodes in Charlotte, North Carolina (Jeffries, Personal Communication, 1996) and Toronto, Ontario (Dennis, Personal Communication, 1996) in 1988. In the Charlotte North Carolina case, Jeffries and his collaborators showed through modeling efforts that when transport was excluded from the initial conditions, above standard ozone did not develop; i.e., the transported ozone was necessary to create the episode. An important point is that the transport of relatively high ozone (i.e., 70 to 100 ppb) was involved in both of these cases. What is the lower limit on the transported ozone and/or precursor concentration that is effective in the direct development of episodes? How frequent are episodes involving transport? The answer to these questions is not known. The lower limit on the transported ozone and/or precursor concentration that is effective in episode development is undoubtedly variable, dependent on the emission and meteorological conditions at the site of influence. Transport of ozone and/or precursors is a necessary condition for an episode in these cases. The amount of transported ozone and/or precursors required to affect episode development is the sufficient condition and is a factor together with the frequency data that should have a significant influence on the estimates of the range of influence and of the AOI.

5.F	Conclusions

The correlation analysis using time series data (Zurbenko et al, 1995; Rao and Zurbenko, 1994, Rao, et al, 1995; Flaum et al, 1995) provides information on the spatial dimensions over which the time variations (or the processes) for ozone are reasonably consistent. The process consistency is produced by SWSs which modulate the ozone as the systems move across the region, and therefore the correlation analysis provides the spatial scale over which the effects of SWSs remain reasonably consistent. The spatial scale for that consistency is a function of the speed of, the intensity of, and the dynamics and physics associated with the SWSs and the chemistry for ozone all of which vary in space and time. Transport plays a role in defining that space scale, but it is just one of the numerous processes involved. The correlation analysis alone does not isolate the role of transport in defining

the spatial scale for that consistency. Due to the central characteristics of the space scale associated with correlation analysis of time series data, this space scale has no relationship to the AOI for ozone.

Dennis (1996) estimated the range of influence of a source area (i.e., 160 x160 km area) using an air quality model, the RADM. Thirty 3-day meteorological cases were used in the annual simulations and these cases were biased, providing meteorological situations that maximize deposition. The meteorological cases for the growing season (i.e., April through September which is consistent with the ozone season) were used for the study of the range of influence for ozone, and more than half of 30 cases represented weather systems found in the growing season. A large percentage of the growing season cases, however, included meteorological situations that also maximize deposition, and these are meteorological situations in which low ozone is found. Only a few low energy HPSs, the kinds of weather systems in which high ozone and episodes are found, were included in the simulations. This suggests that the meteorology that was used provided an overestimate of the range of influence. On the other hand, since the results are an aggregate of 3-day simulations and a 3-day transport period for ozone may not the sufficient, this factor may have produced an underestimate of the range of influence. Fishman et al [1990] has shown using satellite data that in the summer, relatively high ozone develops in the troposphere across the Atlantic and Pacific Oceans at mid latitudes, suggesting very long-distance transport, requiring long time scales, of continental ozone and/or precursors. If transport of such long distance is possible, then it will be necessary to carry out the transport calculations using a model for more than three days.

Finally, Dennis' results were established with no regard to whether the transported ozone and/or precursors could in any way influence or significantly contribute to the development of an episode, either locally or regionally. Most of the meteorological cases used in the estimates of the range of influence for ozone involve frontal conditions and LPSs which provide strong winds and organized flow and long-distance transport, but are conditions that are characterized by low concentrations of ozone. The few cases in which high ozone could develop are generally characterized by little or no transport. Cases have been noted in which transport played a significant role in the development of an episode, but it is not clear how often such cases occur or if they are each special cases. Any calculation of the range of influence or AOI must be bounded by the condition of significance if the calculation is to be meaningful. The fact that the meteorology used by Dennis probably produced an overestimate of the range of influence for ozone, that the short 3-day transport period he used may have produced an underestimate of the range of influence, and that Dennis' results were established with no regard to whether the transported ozone and/or precursors could influence or contribute to the development of an episode suggest that further research is required to provide a more definitive AOI for ozone. In the following section, four research projects are outlined the results from which may provide a better understanding of transport and the AOI.

5.G	References

Bach, W. D., 1975: Investigation of ozone and ozone precursor concentration at non-urban locations	in the eastern United States, Phase II, meteorological analysis. Final report, Environmental Protection Agency by Research Triangle Institute, Research Triangle Park, NC. 145 pp.

Bach, W. D., J. E. Sickles, R. Denyzson, and W. E. Eaton, 1977: Chemical and meteorological	analysis of the mesoscale variability of ozone concentrations over a six-day period. Proceedings International Conference on Photochemical Oxidant Pollution and its Control. Contract No. EPA-600/3-77-001A, Environmental Protection Agency, Research Triangle Park, NC, 197-211.

Bloomfield, P., J.A. Royle, L.J. Steinberg, and Q. Yang, 1996: Accounting for meteorological effects	in measuring urban ozone levels and trends. Submitted to Atmos. Environ., 35 pps.

Bloomfield, P., J.A. Royle, and Q. Yang, 1993: Accounting for meteorological effects in measuring	urban ozone levels and trends. Tech. Rep. No. 1, Nat. Inst. of Stat. Sci., RTP, NC.

Buntz, S.M., W.S. Cleveland, T.E. Graedel, B. Kleiner, and J.L. Warner, 1974, Ozone concentrations	in New Jersey and New York: statistical association with related variables. Science, 186, 257-258.

Brook, J.R, J. Samson,and S. Sillman, 1994a: Aggregation of selected 3-day periods to estimate	annual and seasonal wet deposition totals for sulfate, nitrate, and acidity. Part I: A synoptic and chemical climatology for eastern North America. J. Appl. Meteorol., 34, 297-325.

Brook, J.R, J. Samson, and S. Sillman, 1994b: Aggregation of selected 3-day periods to estimate	annual and seasonal wet deposition totals for sulfate, nitrate, and acidity. Part II: Selection of events, deposition totals, and source-receptor relationships. J. Appl. Meteorol., 34, 326- 339.

Ching, J.K.S., S.T. Shipley, and E.V. Browell, 1988: Evidence of cloud venting of mixed layer ozone	and aerosols. Atmospheric Environment, 22, 225-242.

Cox, W.M. and S.H. Chu, 1992: Meteorologically adjusted trends in urban areas: a probability	approach. US EPA, Tech. Support Div., MD-14, RTP, NC.

Decker, C. E., L. A. Ripperton, J. J. B. Worth, F. M. Vukovich, W. D. Bach, J. B. Tommerdahl,	F. Smith and D. E. Wager, 1976: Formation and transport of oxidants along the Gulf Coast and in the northern United States. Report No. 450/3-76-033, Environmental Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, NC, 456 pp.

Dennis R.L., 1996: Using the regional acid deposition model to determine the nitrogen deposition	airshed of the Chesapeake Bay watershed. Draft of Chapter of SETC book, 30 pages

Eder, B.K. and S.K. LaDuc, 1996: Can selected RADM simulations be aggregated to estimate annual	concentrations of fine particle matter. Paper presented at "Measurements of Toxic and Related Air Pollutants" Air and Waste Management Association/EPA conference, RTP, NC, 7-9 May 1996.

Feister, U. and K. Balzer, 1991: Surface ozone and meteorological predictors on a subregional scale.	Atmos. Environ., 25A, 1781-1790.

Fishman, C. E. Watson, J. C. Larsen, and J. A. Logan, 1990: Distribution of tropospheric ozone	determined from satellite data. J. Geophys. Res., 95, D4, pp. 3599-3617.

Flaum, J.B., S.T. Rao, and I.G. Zurbenko, 1995: Moderating the influence of meteorology on	ambient ozone concentrations. J. Air and Waste Management (In Press).

Gidel, L.T., 1983: Cumulus cloud transport of transient traces. J. Geophys. Res., 88, 6587-6599.

Huffman, G. D, G. W. Herring, R. C. Bourke, T. P. Cook, and M. P. Sillars, 1977: Ozone	observations in and around a midwestern metropolitan area. Proceedings International Conference on Photochemical Oxidant Pollution and its Control. Contract No. 600/3-77- 001A, Environmental Protection Agency, Research Triangle Park, NC, pp. 341-353.

Husar R.B., D.E. Patterson, C.C. Paley, and N.G. Gillani, 1976, Ozone in hazy air masses. Proc. Int.	Conf. on Photochemical Oxidant Pollution and its Control, Raleigh, NC, EPA-600/3-77-001, 275-282.

King, W.J. and F.M. Vukovich, 1982: Some Dynamic Aspects of Extended Air Pollution Episodes.	Atmos. Environ., 16:5, 1171-1181.

Korsog, P.E. and G.T. Wolff, 1991: An examination of tropospheric ozone trends in the northeastern	United States (1973-1983) using a robust statistical method. Atmos. Environ., 25B, 47-57.

Linn, W.S., E.L. Avol, D.A. Shamoo, R.C. Peng, L.M. Valencia, E.E. Little, and J.D. Hachney,	1988: Repeated laboratory ozone exposures of volunteer Los Angeles residents: an apparent seasonal variation in response. Toxicol. Indust. Health, 4, 505-520.

Ludwig, F. L., W. B. Johnson, R. E. Ruff, and H. B. Singh, 1977: Important factors affecting rural	ozone concentration. Proceedings International Conference on Photochemical Oxidant Pollution and its Control. Contract No. 600/3-77-001A, Environmental Protection Agency, Research Triangle Park, NC, 425-439.

Lui, S.C., M. Trainer, F.C. Fehsenfeld, D.D. Parish, E.T. Williams, D.W. Fahey, G. Hubler, and P.C.	Murphy, 1987: Ozone production in the rural troposphere and implications for regional and global ozone distribution. J. Geophys. Res., 92, 4191-4207.

Lyons, W. A., J. C. Dooley, Jr., and K. T. Whitby, 1978: Satellite detection of long range pollution	transport and sulfate aerosol hazes. Atmos. Environ., 12, 621-631.

McHenry, J.N., F.S. Binkowski, R.L. Dennis, J.S. Chang, and D. Hopkins, 1992: The tagged species	engineering model (TSEM). Atmos. Environ., 26, 1427-1443.

Mueller, P. K., G. M. Hidy, K. Warren, T. F. Lavery, and R. L. Baskett, l980: The occurrence of	atmospheric aerosols in the northeastern United States. Annual New York Acad. Sci., 388, pp. 463-482.

National Research Council, 1992: Rethinking the ozone problem in urban and regional air pollution.	National Academy of Science Press, Washington, DC, 500 pp.

Rao, S.T. and I.G. Zurbenko, 1994: Detecting and tracking changes in ozone air quality. J. Air &	Waste Manage. Assoc., 44, 1089-1092.

Rao, S.T., E. Zalewsky, and I.G. Zurbenko, 1995: Determining temporal and spatial variations in	ozone air quality. J. Air & Waste Manage. Assoc., 45, 57-61.

Ripperton, L. A., J. J. B. Worth, F. M. Vukovich, and C. E. Decker, 1977: Research Triangle	Institute studies of high ozone concentration in non-urban areas. Proceedings International Conference on Photochemical Oxidant Pollution and its Control. Contract No. EPA-600/ 3-77-001A, Environmental Protection Agency, Research Triangle Park, NC, 413-425.

Samson, P. J. 1980: Trajectory analysis of summertime sulfate concentrations in the northeastern	United States. J. Appl. Meteorol., l9, pp. 1382-1394.

Stasuik, W.N. and D.E. Coffey, 1974: Rural and urban ozone relationships in New York state.	JAPCA, 24, 564-568.

Trainer M., E.T. Williams, D.D. Parish, M.P. Buhr, E.J. Allwine, H.H. Westberg, F.C. Fehsenfeld,	and S.C. Lui, 1987: Models and observations of the impact of natural hydrocarbons on rural ozone. Nature, 329, 705-707.

United States Environmental Protection Agency, 1996: Air quality criteria for ozone and related	photochemical oxidants, Vol. I. EPA Report No. EPA/600/AP-93/004a, ORD, Washington DC, 365 pp.

Vukovich, F.M, 1979 :A Note on Air Quality in High Pressure Systems. Atmospheric Environment,	13, 255-265.

Vukovich, F.M., 1994: Boundary layer ozone variations in the eastern United States and their	association with meteorological variations: long-term variations. J. Geophys. Res., 99, 16839-16850.

Vukovich, F.M., 1995: Regional-scale boundary layer ozone variations in the eastern United States	and their association with meteorological variations. Atmos. Environ., 29:17, 2259-2273.

Vukovich, F.M., 1996: Time scales of regional ozone variations in the regional, non-urban	environment. Accepted for publication in Atmos. Environ.

Vukovich, F. M., W. D. Bach, B. W. Crissman, and W. J. King, 1977: On the relationship between	high ozone in the rural boundary layer and high pressure systems. Atmos. Environ., 2, 967- 983.

Vukovich, F.M., and J.K.S. Ching 1990: A semi-empirical approach to estimate vertical transport	by nonprecipitating convective clouds on a regional scale. Atmos. Environ., 24:8, 2153- 22168.

Vukovich, F. M., J. Fishman, and E. V. Browell, 1985: The reservoir of ozone in the boundary layer	of the eastern United States and its potential impact on the global tropospheric ozone budget. J. Geophys. Res., 90:D3, 5687-5698.

Vukovich, F. M., and J. Fishman, 1986: The climatology of summertime O3 and SO2 (1977-1981).	Atmos. Environ., 20:12, 2423-2433.

Wackter, D.J. and P.V. Bayly, 1988: The effectiveness of emission controls on reducing ozone levels	in Connecticut from 1976 through 1987. The Scientific and Technical Issues Facing Post- 1987 Ozone Control Strategies, G.T. Wolff, J.L. Hanisch, and K. Schere (eds), Air & Waste Manage. Assoc., Pittsburgh, 398-415.

Wight, G. D., G. T. Wolff, P. J. Lioy, R. E. Meyers, and R. T. Cederwall, l978: Formation and	transport of ozone in the northeast quadrant of the United States in air quality meteorology and atmospheric ozone. American Society Testing Materials, Philadelphia, PA, pp. 445-457

Wolff, G. T., and P. J. Lioy, l980: Development of an ozone river associated with synoptic-scale	episodes in the eastern United States. Environ. Sci. Technol., 14, pp. 1257-1260.

Wolff, G. T., P. J. Lioy, G. D. Wight, R. E. Meyers, and R. T. Cederwall, 1977: An investigation	of long-range transport of ozone across the midwestern and eastern United States. Atmos. Environ., 11, pp. 797-802.

Zurbenko, I.G, S.T. Rao, and R.F. Henry, 1995: Mapping ozone in the eastern United States.	Environmental Manager, 1, 24-29.