Urban ozone and its precursors Reliable measurements and robust statistics are prerequisites for more effective ozone control
David F ! Choek Jon M. Heus General Motors Research Laboratories , Warren, Mich. 48090 According to the Clean Air Act, Dec. 31, 1987, is the deadline for achieving the National Ambient Air Quality Standard (NAAQS) for ozone. As this date approaches, it is evident that many regions of the country will not attain this standard. On the hasis of EPA's estimates, at least 60 major metropolitan areas will be out of compliance by the deadline (I). Meanwhile, the agency is in the process of reviewing the air quality standard for ozone. Tropospheric ozone has both a natural and a man-made origin. In urban areas, man-made emissions are overwhelmingly dominant over natural ozone sources. Moreover, the ozone standard is violated most frequently in urban areas and in areas immediately downwind. This article addresses the ozone problems of urban areas, emphasizing three important issues. The first concerns the form and level of the NAAQS, which directly affects the achievability of the standard, as well as confidence in its attainment. The second issue encompasses the trend in ozone concentrations, which is a measure of the effectiveness of existing ozone control strategies. The third entails the control strategies whose failure may reflect a deficiency in the understanding of the ozone problem or in the implementation of the strategies themselves. 1146 Environ. SCi.TeChnOl.. Vol. 21. No. 12,IS87
W15936X18710921-11461.5010 @ IS87 American Chemical Sociew
The standard An NAAQS is defined as a concentration over a specified averaging time and an allowed fresuency of occurrence. Its stated objective is to protect pblic health and welfare. For it to be enforceable, compatible air quality models should be available for the purpose of designing control strate@es. The issue of the allowed frequency of occurretlce will be discussed here. The issue of protecting public h d t h and welfare, which governs the stringency of the NAAQS, is beyond the scope of this discussion. Model compatibility and application are addressed elsewhere (2). The current NAAQS for ozone specifies that the average number of days with daily maximum one-hour concentrations greater than 120 ppb should not be more than one per year. The averaging period generally is assumed to be three years. This form of air quality standard clearly emphasizes the upper extreme, values of air quality data. If the standard is exceeded, a control program must be implemented. In a typical state implementation plan, the
fourth highest daily maximum onehour owne concentration in three years in an urban area is chosen as the design value and is used as an input to an EPAapproved air quality model. This value, in turn, is used to determine the degree of emission control necessary to bring this fourth highest value down to the level (120 ppb) specified in the standard. Although this procedure appears straightforward, some questions arise: “How reliable is this fourth highest value in three years?”; “Is it subject to much uncertainty?”; and “Is it equivalent to the second highest value in one year?” To answer these questions, one must examine the statistical properties of extreme values. If air quality data can be assumed to be independent and identically distributed (iid), one can fit a statistical distribution to the data set and use it as a parent distribution to determine the statistical properties of extreme values of the data. On the other hand, the best distribution to fit the data often is ambiguous because the best candidate for the same data varies for different g d ness-of-fit tests (3). This ambiguity
makes these estimates unreliable because extreme-value estimates depend on the parent distribution (see box). Compounding the problem of estimating extreme values is the fact that air quality data are not iid, but are time series data that contain trends and serial correlations (autocorrelations). This is especially true for ozone, which has seasonal trends and daily maximum one-hour concentrationsthat are correlated from one day to the next (4-6). Taking into account the effectsof trends and autocorrelation, Chock (7)recently studied the statistical behavior of extreme values. The results indicate that a p i t i v e autocorrelation will lower the estimated means of the extreme values and increase their uncertainties; a nonconstant trend also will increase their uncertainties. Thus, for a 122-day ozone concentration series with an autocorrelation of 0.5-0.6 at a one-day time lag (time separation between two observations), the decrease in expected extreme values relative to the uncorrelated case typically is less than 2%. The increase in the estimated uncertainties of these ex-
Some properties of extreme-value distributions air quality data are indeyielded an expected maximum value and identically distributed of 510 ppb with a standard deviation ppose further that we have a of 90 ppb. By comparison, a twon of many such data sets, parameter Weibull distribution fitted with N observations. The distrito the same data yielded an exn describing the collection of pected maximum value of 360 ppb the data sets then is highfstvalue distnbudepends closely butmn that chare data sets. If the expressed as the function, has a ch as that of the buinthe istri-
tails of mast unctions the loca-
(3). For the seventh highest value, on the other hand, the two-param-
eter lognormal distribution gave an expected value of 340 ppb and a
standard deviation of 20 ppb, whereas the two-parameter Weibull distribution gave corresponding values of 300 ppb and to ppb, in closer agreement with the results from the lognormal distribution. For a parent distribution that has no upper-limit cutoff, the mth highest value distribution also depends on the number of observations, N, in each data set. The higher the value of N, the more likely a higher uppe extreme value will occur; hence the higher will be the expected upper e
ent distribution fits one with 365 days ’ expected extrem former data set w
one does not expect an identical parent distribution to fit both the yearly
Envifon. Sci. Technol..MI. 21, NO.12. i987 1147
treme values is much greater; it can be more than 25% higher than the increase in uncertainties in the uncorrelated case for the seventh highest value. Overall, the large uncertainties inherent in the extreme and nearextreme values of ozone data are further aggravated by the presence of trends and autocorrelation in the data. These uncertainties are enlarged further by the ambiguity in determining an appropriate distribution to describe the data (even if we insist on using the iid assumption). These factors make the choice of an extreme value for the air quality standard undesirable. Moreover, the fourth highest value in three years is not equivalent to the second highest value in one year (8).The former can be significantly higher than the latter, thereby making the implementation of the standard more stringent than would otherwise be necessary. For example, for a first-order Markov series (a series in which an event is influenced by the event immediately preceding it) of about 100 days per year, with an autocorrelation of 0.5-0.6 at a lag of one day, the fourth highest value in three years is about 10% higher than the second highest value in one year. As the rank m increases (m=1 for the maximum value) and becomes less extreme, however, it is expected that the [n(m-l)+l]th highest value in n years will better approximate the mth highest value in one year, assuming that the data from each year are from the same population. Even though the statistical form of the NAAQS is independent of the suingency of the standard, it plays an important role in the problem of compliance. If an extreme value is chosen for the NAAQS, as has been done, its large statistical uncertainty can cause a region to be unpredictably in and out of compliance. For control purposes, it is desirable to enhance the robusmess of the statistic, that is, to reduce the uncertainty inherent in the form of the standard. Moving away from the extreme values in the standard will help accomplish this. Using ambient ozone data collected between 1975 and 1981, Hayes et al. (9) showed that the standard deviations of the design values for a standard using the 95th percentile, and those for a standard using an expected exceedance of five days per year, were respectively 27 % and 39% less than the standard deviation of the design value for the current NAAQS. Clearly, to retain the stringency of the current standard, the concentration specified in a standard with a less extreme statistic would have to be revised downward. Wends in m n e concentrations Since the promulgation of the ozone NAAQS in 1971, an emission control 1148
Environ. Sci. Technol.,Vol. 21, No. 12. 1987
program for reducing ozone concentrations in the troposphere has been in place across the nation. The degree of its success must be measured by trends in owne concentration. Determining these trends is not a straightforward procedure. There are questions regarding the choice of the statistic for trend analysis, the effects of changes in measurement and calibration methods, and the intluence of meteorology on ozone concentration. l k n d s in ozone concentration in various parts of the country have been compiled by several government agencies (IO,11). One statistic often used is the second highest daily maximum onehour concentration in a year, which normally is used to determine whether a violation of the standard may have occurred at a site during a particular year. Because of the great uncertainty associated with this statistic, it may show a trend that is different from those of more robust statistics. Figure 1 shows an example of trends based on different statistics for m n e concentrations observed at San Bernardino, Calif., between June and September of each year. The trend for the second highest daily maximum one-hour concentrations (top curve) has more tluctuations than those for the 95th percentiles (middle curve) and for the means (bottom curve). Each curve can result in a different trend estimate, depending on the time interval involved. Walker (12) showed that the trends in annual maximum ozone in the California South Coast Air Basin were much more variable than the trends in average daily maximum ozone for May
through October. It is obvious that the trends of the extreme values can be different from those of the less extreme values. Because of the great uncertainties inherent in the extreme values, a long period of time @erhaps 10 or more years) is necessary to reduce the influence of the uncertainties on the trend line. Another commonly used statistic for trend analysis is the number of days of exceedance (the number of days on which the ozone standard is exceeded). The robustness of this statistic varies (12), becoming more robust as the number of days of exceedance increases; therefore, this statistic is less useful for defining the trend when an urban area is close to compliance. Because of the large amount of data available for certain regions, it is common practice to take concentration averages for all the sites within a region or area to determine the trend (lo). This practice may cause the loss of pertinent information on ozone trends within the region. For example, changes in ozone concentration 'depend on changes in reaction rates caused by changes in precursor emissions. Consequently, changes in precursor emissions can result in different trends within different parts of an area. In the California South Coast Air Basin, for example, monitoring sites near or upwind of the major precursor sources have shown an upward ozone concentration trend, whereas downwind monitoring sites have exhibited a downward trend between 1975 and 1984 (11, 12). Separate studies of trends from these sites thus reveal the need for closer scrutiny
of the emission trends of ozone precur- gust and are low during the winter months. This is true even for the southsors. Techniques for measuring ozone ern United States. Meteorological inhave evolved with time. Before the fluences on trends in m n e concentraearly 1970s. the standard technique was tion also have created confusion potassium iodide (KI) colorimetry. This concerning the trend itself. In the trend method is not ozone-specific. It is sen- of the nationwide composite averages sitive to species such as Na, which of the second highest daily maximum oxidizes iodide to iodine (hence the one-hour ozone concentrations remeasured quantity is called oxidants ported by EPA (Figure 2). a local peak rather than ozone), and to species such appeared in 1983. This peak alters the perception of an otherwise gradually as SO,, which reduces iodine to iodide. decreasing trend. EPA officials beThe ethylene chemiluminescence method was introduced during the mid- lieved that the peak was attributable 1970s. but it has not been universally partly to meteorological conditions in used. Since 1979 the accepted method 1983 that were conducive to m n e forfor measuring ozone has been the ultra- mation. The influence of meteorological conviolet (W) photometric method. Although these two methods are highly ditions on trends in m n e concentration specific to owne, the UV method is may lead to erroneous conclusions about the effectiveness of existing considerably more reliable. Accompanying the change in analyti- ozone control strategies. It would be cal methcds was a change in instrument desirable to remove the effect of calibration procedure. Because the weather from ozone concentration chemiluminescence method measures mnd data; however, our knowledge of the relative concentration of m n e , it is the relation between ozone concentracalibrated by either the KI method or tion and meteorology is far from perthe W method. The shift from the KI fect. One must therefore establish such calibration method to the UV method in a relation statistically. This relation can change from year to 1979 caused an artificial downward year because of changing amounts of shift in measured ozone of about 1896. B r e n t state agencies have applied emissions that modify the response of somewhat different calibration correc- m n e formation to identical meteorotion factors to their pre-1979 data. As a logical conditions. To circumvent this result, the national composite averages problem, one can freeze all of the releof mne concentrations prior to 1979 vant meteorological parameters at fixed are not reliable (Figure 2). The Califor- and realistic values and determine the nia Air Resources Board not only cor- corresponding ozone concentration for each year by interpolation using a starected the m n e data reported to EPA, but also made side-by-side measure- tistical relation constructed kparately ment comparisons behveen the KI and the chemiluminescence methods in 1974 and 1976, and between the KI and the UV methods in 1978 in the South Coast Air Basin. The resulting data revealed that when the ozone concentrations based on the chemiluminescence or W methods were relatively high, they could actually be higher than their oxidant counterparts measured by the KI method (13-15). These data also allow one to convert mne to oxidants, or vice versa, on a consistent basis (assuming relatively constant or small interfe.renm caused by species such as N@ and SQ over the years of interest), so that one can link the pre-1979 data with the more recent data for meaningful trend analysis. Unfortunately, the observations in California raise the question of whether a simple calibration correction factor is sufficient to assure the accuracy of the pre1979 mne data reported elsewhere. The formation and transport of ambient ozone depends on meteorological conditions. Ozone formation varies with the seasons because of its dependence on solar radiation. Ozone concentrations tend to peak in July and Au-
for each year (14).In so doing, one can establish the owne concentration trend with fixed meteorological factors and without the uncertainty associated with extrapolation. By choosing a meteor0 logical condition that is realistic and conducive to m n e formation, one can establish the concentration trend for days with high ozone-forming potential and exclude nonrobust extreme values. The south Coast Air Quality Management District in California uses this method (11). It has been assumed that the important meteorological m e t e r s to be accounted for are solar radiation, temperature, mixing height, and wind v 6 locity. Solar radiation is not measured routinely, but depndence on it may be reduced by considering only the highm n e seasolls of lune-September or May-Octhr. Ofthe remaining parameters, the upper level (950 mb and 850 mb, which are about 500 m and 1500 m, respectively, above mean sea level) temperatureshave been found to be the most important statistically in the South Coast Air Basm (14). The surface temperature is next in importance (14). Both surface and upper level temperatures are negatively correlated with mixing height and are expected to be positively correlated with solar radiation. The role of mixing height thus is obscured by temperature parameters. The effectof wind speed on ozone measured at a ked site is ambiguous because air p m l s arriving at the site ms through sources that are nonuniform in space and time.
Emiron. Sd.Techpol., W. 21, No. 12.1987 1140
With meteorological factors held Ozone Concentration trends from constant for conditions conducive to other urban areas have been reported three different ozone-forming poten- by regulatory agencies. They tend to be tials (high, medium, and low), the short term, without meteorological ozone trends for the basinwide daily consideration, and based on an exmaximum one-hour concentrations treme-value statistic. Therefore they over the South Coast Air Basin from are more susceptible to the impact of lune to September, 1971 to 1981, were year-to-year fluctuations. EPA listed determined (14, I s ) . For the case of five consecutive annual second highest high ozone-forming potential, a decline daily maximum one-hour concentraof about 15% occurred between 1971 tions, averaged over all the monitoring and 1981. More recently, Davidson et sites in 14 metropolitan areas (IO). The al. (11) established the ozone concen- data show that between 1981 and 1985, tration trend for the daily maximum ozone concentrations increased in Bosone-hour concentrations averaged over ton and decreased in Baltimore, Desix stations in the Basin from May to troit, Denver, New York, Philadelphia, October, 1975 to 1984. By holding the Phoenix, portland, and Seattle. They temperature at 850 mb constant at its remained unchanged in Atlanta, Chilong-term average value they found an cago, Houston, Los Angeles, and St. overall decrease in ozone of 7.1% dur- Louis. The slopes of the trends were small (less than 2%/yr relative to the ing the period. Itend studies using fixed meteoro- 1981 values), except for Boston (+8%/ logical conditions and robust statistics yr), Denver (-3%lyr), Detroit (-6%/ have not been conducted in other areas. yr), and Seattle (-3%/yr). If we assume, however, that 10 years is On a nationwide basis, the ozone long enough to average out the year-to- concentration trend has gone down only year variations in weather, then we slightly during the 1980s (Figure 2). should note the trend analysis of Walker On a local level, ozone concentration (12) using the statistic of average daily trends have more variations. In the maximum Mlehour concentration from South Coast Air Basin of California, May to October. This analysis indicates where Ozone air pollution is the most that for the Houston area and Texas in serious in the nation, the trend based on general, the ozone concentration trend fixed meteorological factors and a rowas up by 2.1-2.6% per year between bust statistic is slightly downward. 1973 and 1982. For California outside Nevertheless, it is expected that that the South Coast Air Basin, the trend area and many other urban areas will was slightly upward for the San Diego not reach attainment of the ozone standAir Basin (1.1 %/yr) and the San Fran- ard by the end of 1987. This pattern is cisco Bay Area (0.4%/yr), flat in the disturbing because it indicates that exCentral Valley, and down in the South isting control programs may not have Central Coast (- 1.3Wyr). been effective.
Ozone chemistry A brief description of ozone chemistry is provided in the box; a more detailed description can be found elsewhere (17-19). Because the oxidation of nonmethane organic compounds (NMOC) leads to ozone formation, a reduction in NMOC is expected to reduce ozone prcdwtion. The efficiency of ozone reduction, however, depends on the amounts of nitric oxide (NO) and nitrogen dioxide (NO*). (NO and NO, often are combined and denoted as NO,; 90% of NO, emissions are in the form of NO.) The ability of NO, to promote or inhibit ozone formation depends on the level of NMOC. When NMOC is abundant relative to NO, (say, 20 ppm C1 ppm, where ppm C is measured in terms of the total number of carbon atoms), there is a shortage of NO that can be oxidized by peroxy radicals. Therefore, the formation of Ozone is controlled primarily by the amount of NO, available, and much less by the amount of NMOC. Increasing the concentration of NO, eventually will lead to an increase in Ozone concentration, even though increasing NO, always will sup press ozone initially near the sources of NO, because of the rapid reaction of NO with ozone. On the other hand, when NMOC is less abundant relative to NO, (at an NMOC-NO, ratio of 5 ppm C/ppm, for example), the ready availability of NO for oxidation makes ozone formation highly dependent on the amount of NMOC. Also, NO initially will m v enge ozone at a rate faster than the ef-
I f i n of NO by HO,, the photolysis of ozone in the presence of water vapor, the photolysis of nitrous acid (HONO, formed by the reactions of NO, with water, NO with OH, and perhaps other unknown pathways), and that of hydrogen peroxide
The only known route of ozone formation in the lower troposphere is the photolysis of NOz. In the absence of other oxidizing species, however, ozone will oxidize NO to form NO2. resulting in no net gain in ozone. The three species quickly reach a p
state
NO2 (UV 0+02 +M 0 3 + M 0 3 + NO NO2 + 0 2 The photolysis and oxidation of re. active organic compounds provide a major pathway leading to the oxidation of NO without destroying ozone. The reactive organic compounds include aldehydes (RCHO, including formadehyde and higher aldehydes) and hydrocarbons (RH) such as ethene, internally and terminally banded hiaher alkenes. hiaher al-
--
1150 Envimn. Sci.Technol..W. 21, No. 12,1987
are omitted):
-
RH + OH R02 (alkylperoxy radical) RCHO + OH RC03 (acylperoxyradical) RCHO (UV radiation) HO, (hydroperoxyl radical) + R'O, H 0 2 + NO OH + NOz RC03 + NO
-
RO,
- + + NO2
GO2
R02+NOR'CHO + HO2 + NO2 The OH radicals are the chief oxi-
tion. tmportant among the removal reactions are: OH + NO2 HN03 RCO, + NO, RC0.NO
--
fective rate of NO oxidation via the channel involving NMOC and the OH radicals. Further, N@ also will remove OH more readily, thereby inhibiting the formation of peroxy radicals and the subsequent oxidation of NO. As a result, increasing NO, will lead to an initial decrease in m n e formation, and to a delay and possibly a decrease in the peak ozone concentration. The slower formation of pemxy radicals, however, may simply delay the availability of these radicals so that even though the peak ozone may be suppressed,the post peak ozone formation within the same parcel of air may be enhanced. Consequently, increasing NO, may cause ozone to cross over and exceed the level it would otherwise obtain during the post peak period. This behavior has been observed in a smog chamber with constant light intensity (20). In ambient air, the reduction in light intensity in the mid- or late afternoon may further slow down the formation of peroxy radicals, so that a cross-over point may not occw. This behavior has been observed in captive-air irradiation experiments conducted in Detroit. In these experiments, ambient urban air was captured in a series of Teflon bags and NO, NMOC, clean air, or some combination of these were added to some of the bags. The original NMOCNO, ratios were 4-6 (21). In these experiments, spiking the ambient air with NMOC increased m n e concentrations significantly. Reducing both NMOC and NO, also reduced ozone levels, but was less effective than either reducing NMOC alone or increasing NO, alone. From the foregoing, one infers that the NMOC-NO, ratio at the time of high emissions during the day undoubtedly is an important factor in influencing the subsequent formation of ozone. The roles of NO, at high and low NMOCNO, ratios are fairly explicit. At intermediate ratios, for example, between 8 and 15, it is plausible that reducing NMOC, NO,, or both, may reduce ozone. Photochemical models have been constructed to attempt to increase our understanding of the quantitative aspects of ozone chemistry. TWO major factors, however, impede this endeavor. First of all, because it is impossible to include all atmospheric species in a model, one uses a lumping or surrogate scheme to represent the different classes of organic compounds in the atmosphere. In more recently developed schemes to simulate the ambient atmosphere, there has been a tendency to increase the number of lumped and individual species (18. 19). Yet there is no clear consensus on how the lumping should be done. Secondly, photochemical models are
1
I
tuned to reproduce the results of laboratory smog chamber experiments. When the chamber-specific effects and reactions are removed from the modeling schemes, the predictions from different models agree only qualitatively (22, 23). As a result, no photochemical model for the formation of ozone has been universally accepted. Fortunately, the qualitative agreement among models allows their use as a guide to the development of control strategies. A popular use of photochemical models has been the generation of the Empirical Kinetic Modeling Approach (EKMA) isopleths of daily maximum ozone concentrations as a function of morning concentrations of NMOC and NO, (17). An example of these isopleths is shown in Figure 3. This a p proach entails detailed chemistry but little meteorology. The isopleths do not show the time variation of ozone, but they do show the effect of precursor control on the daily maximum ozone concentration. For example, Figure 3 shows that in the region with low NMOC-NO, ratios, reducing NO, would increase the daily maximum ozone concentration. Because of the unique shape of the isopleths, the regions with high and low NMOC-NO, ratios can be roughly partitioned by the NMOC-NO, ratio where an isopleth has the highest curvature. This ratio is abwt 8 in Figure 3, but it need not stay the same for all isopleths in the same plot. Therefore,
for a fixed NMOC-NO, ratio, the role of NO, may change as one ozone level is shifted to another. Also, the partitioning ratio may be different for different models and different assumptions about precursor emissions and free-radical sources. More detailed models containing both chemistry and meteorology have also been used to study the effects of NO, and NMOC controls in the California South Coast Air Basin (24-26) and elsewhere (27). Such models predict ozone formation as a function of time and space. They can be used to determine the degree of impact that different ozone control scenarios may have in a given area; however, they require detailed information on wind fields, atmospheric stability, emissions, and initial and boundary conditionsthat generally is not available.
Precursor trends One important item of information is lacking: The trends in NMOC and NO, emissions must be determined in order to identify the reasons for our plodding progress in reducing ozone levels. Estimates of nationwide emissions of volatile organic compounds and NOx are available (IO), but they are of little use for comparison with ozone trends in nonattainment areas. First of all, they are annual estimates instead of estimates for smog seasons; secondly, they are nationwide averages instead of estimates specific to nonattainment areas; Envimn. Sci.Technol..MI. 21. No. 12. 1987 1151
thirdly and most important, they are uncertain. Year-by-year emission inventories for specific urban areas generally are not available. The South Coast Air Basin of California is an exception, but even there, knowledge of speciated organic compound emissions is very limited. NMOC and NO, concentrations measured in the morning, before the hours of active photochemical reactions, are expected to be proportional to their emissions. Therefore, their trends should parallel the emission trends. Trijonis (28) found that in the Houston area, the observed 6-9 a.m. NMOC concentration during the smog season increased by 7-23% at different sites between 1974 and 1978, even though NMOC emissions were estimated to have decreased by 7% during the same period. The observed NO, increased by 16-48 % while the estimated emissions went up by 18%. In the California South Coast Air Basin, NMOC emissions were estimated to decrease by about 35% between 1975 and 1984 (29), but the observed daily maximum total hydrocarbons (HC, the daily maximum occurring in the morning) averaged over the Basin sites from June through August showed very little decline between 1975 and 1985. The calculated decline of 6% was not important at the 10% significance level. There was a more significant decline of 16% between 1978 and 1985 (significant at the 5% level) (30). For the same basin, the NO, emissions were estimated to increase slightly (less than 4%) from 1975 to 1979 and then decrease steadily by 20% between 1979 and 1984 (29). In contrast, the observed daily maximum NO,, measured in the morning and averaged over the basin sites from June through August, showed little decline between 1975 and 1985 (the calculated decline of 14% is not significant at the 10% level) (30). On the other hand, when the observed NO, data base was enlarged to cover the period from 1968 to 1985, NO, declined by 35% (significant at the 5 % level) (30). These discrepancies are troublesome and raise questions about the evaluation of the impact of control strategies based on emission estimates. A lack of reduction in ambient HC concentrations may be partly responsible for the slow improvement in ozone air quality, but we cannot be sure because information on either total or speciated NMOC concentrations is not available. This information is extremely critical for determining NMOC trends and NMOC-NO, ratios so that a sensible ozone control strategy may be devised. Corrections based on limited atmos pheric measurements have been used to 1152 Environ. Sci. Technol., Vol. 21, No. 12, 1987
convert total HC to NMOC (31). The ing rush hours in the Lincoln Xnnel in corrections must change with time be- 1982 (33), around 2.6 for the FTP cycause the composition of the emissions cle (average speed of 20 mph), and changes over time. For example, the about 6 for the New York City Cycle methane content of vehicular HC ex- (average speed of 7 mph). Conversion haust emissions, based on the Federal to ppm C/ppm was based on a methane Test Procedure (FTP) cycle, was 7-9% fraction of 20% by weight in the vehicby weight with the early catalyst sys- ular emissions and a hydrogen-to-cartems between 1975 and 1979, but it has bon ratio of 1.85 for NMOC. increased dramatically with advanced In essence, these ratios tend to be catalytic controls and has shown levels low. If mobile sources in cities such as of 24% by weight for 1982-model cars Washington, D.C., contribute 87% or 96% to the NMOC based on the (32). This increase is relative to other NMOC-acetylene ratio measured in the NMOCs in the vehicular emissions, Lincoln Xnnel, then it is reasonable to Overall emissions have decreased sub- expect a higher NO, level than what stantially. Because methane is the most was observed to be consistent with the difficult hydrocarbon to oxidize, how- typically low NMOC-NO, ratio from ever, its fraction in those emissions that vehicular emissions. If the observed remain has increased even though the ambient NMOC-NO, ratios are reliable total emissions have been reduced. and applicable city wide, the contribuMeasurements of NMOC have been tion of motor vehicles to NMOC in mamade occasionally, but they are uncer- jor cities may turn out to have been tain because they are expressed as the overestimated. This discrepancy again difference between two large measured highlights the necessity of reliable meanumbers (total HC-methane). Also, surements, rather than estimates, as a there have been few speciated ambient basis for identifying major NMOC HC measurements. Lonneman et al. sources. (33) have used chromatographic methods to measure speciated NMOC con- The need for reliable data Billions of dollars have been spent on centrations (primarily from motor vehicles) in the Lincoln 'knnel in New York the control of ozone precursors, yet City during morning rush hours in ozone concentrations have decreased 1970 and 1982. They found that the more slowly than expected in most urNMOC level declined by a factor of 3.9 ban areas during the 1980s. Ozone forbetween 1970 and 1982. In 1984 and mation is a nonlinear process and our 1985, Baugues (34) reported accurate understanding of it is far from commeasurements of nonspeciated NMOC plete. The critical NMOC-NO, ratio using the cryogenic preconcentration that separates the ozone inhibition redirect flame ionization detection gion from the ozone promotion region method (35) during summer morning has not been firmly established. Neverrush hours in 20 cities in Texas and the theless, there is a general consensus eastern United States. Although he that controlling NMOC emissions in found large variations in the NMOC- urban areas will reduce ozone, whereas NO, ratios (in ppm C/ppm) at each site, controlling NO, may or may not reduce a rough picture does emerge. Outside ozone, depending on the NMOC-NO, the Gulf states, large metropolitan areas ratio (37, 38). Unfortunately, we cansuch as Boston, Cincinnati, Philadel- not confidently test our knowledge of phia, and Washington, D.C., had typi- ozone chemistry in the real world becal ratios of 6-10, and smaller cities cause we lack sufficient information had typical ratios of 10-17. In the Gulf about ambient NMOC. Estimates of states, large cities had ratios of 11-14 NMOC emissions generally remain and smaller cities had ratios ranging mere estimates, with little or no corrobfrom 12 to 53. The measured ratios of oration from actual measurements. In NMOC-NO, were several times addition, the decline of NMOC emisgreater than the ratios based on emis- sions may have been overestimated. Options for emissions control are besion estimates (36), indicating that the NMOC emissions in urban areas may coming more limited and costly. Thus the first step toward an efficient and efhave been underestimated. Baugues (34)also attempted to deter- fective ozone control strategy is to demine the motor vehicle contributions to termine by actual measurements the the measured NMOC in different cities concentrations and composition of using the NMOC-acetylene ratio mea- NMOC in the ambient air as well as in sured in the Lincoln Tunnel in 1982 as a emissions from large and small (but scaling parameter. This approach raises prevalent) sources. Only with this ina few problems. For example, the acet- formation and an up-to-date ozone ylene fraction of vehicular NMOC model can we really compare observed emissions can vary by a factor of 10 or ozone levels with projected levels. This more (32). Moreover, typical NMOC- comparison may then reveal major defiNO, ratios for vehicular exhaust emis- ciencies in our knowledge that will resions were about 1.8 during the morn- quire further scientific investigation.
Acknowledgment T h e authors would like t o thank A. M. Dunker, M. A. Ferman, N. A. Kelly, and the ES&Treviewers for helpful discussions and suggestions. This article was reviewed for suitability as an ES&T feature by Jack Calvert, National Center for Atmospheric Research, Boulder, Colo. 80307; Marcia Dodge, EPA, Research Triangle P a r k , N . C . 2771 I; and Alan C. Lloyd, Environmental Research and Technology, Newbury Park, Calif. 91320.
Refemnces (1) EPA Note to Correspandence. R-124.
Aug. 27. 1987; Office of Public Affairs, EPA: Washineton. r) C 19x7 o~..., . (2) HeusS:J:~M.; Chock, D. F! Presented at Air Pollution Control Association Conference on Regulatory Approaches for Control of Air Pollutants, Atlanta. Ga.. Feb. 1987. (3) Chock. D. F!; Sluchak, P S . Armos. Environ. 1986,ZO. 989-93. (4) Chock. D. P Armos. Environ. 1982, 16. 2855-62. ( 5 ) Hirlzel. C. S.;Quon, J. E. Atmos. Em;ron. 1981. 15. 1025-34. (6) Chock. D. ;!F Terrell. T R.; Levitt. S . B. Armos. Environ. 1 9 5 , 9, 978-89. (7) Chock. D. !F Atmos. Environ. 1985. 19. 1713-24. (8) Chock, D. F! Armos. Environ. 1984, 18. 2461-70 .... . .. (9) Hayes. S. R.; Burton. C. S.; Ames, J. “Alternative Forms of the National Ambient Air Quality Standards for Ozone”; SYSAPP831163; Systems Applications, Inc.: San Rafael, Calif., 1984. (10) “National Air Quality and Emissions Trends Report, 1985”; EPA450/4-87-001. Officc of Air and Radiation. Office of Air Quality Planning and Standards. EPA: Research Triangle Park. N.C., 1987. (11) Davidson. A,; Hoggan, M.; Wong, P “Air Quality Trends in the South Coast Air Basin 1975-1984”; South Coast Air Quality Management District: El Monte. Calif.. 1985.
tion and Application of the Urban Air Shed Model in Philadelphia Air Quality Control Region“; EPA-45014-85-003; Office of Air Quality Planning and Standards. EPA: Research Triangle Park, N.C., 1985. (28) Trijonis. J. I n Proceedings ofthe EmpiriCUI Kinetic Modeling Approach (EKMA) Validot;on Workshop; Dimilriades. B.; Dodge. M.. Eds.; EPA-60019-83-014; Office of Research and Development. EPA: Research Triangle Park, N.C.. 1983; pp. 1-41. (29) 7he Eff~clsofOxides ofNirrogm on Coliforniu Air, @ d r y , TSD-85-01; Technical Support Diviston. California Air Resources Board: Sacramento, Calif., 1986. (30) Kuntasat. G.; Chang. T. Y. “Trends and Relationships of 0,.NO, and HC in the South Coast Air Basin of California”; J. Air Pollur. Control Asroe., in press. (31) Trijonis. J. “‘Analysisof Historical Ozone Trends in Los Angeles Sorted by the NMHC1 NO, Ratio (Final Report): California Air Resources Board Contract No. AI-056.32. California Air Resources Board: Sacramento. Calif.. 1983. (32) Sigsby. Jr.. J. E. et 81. Environ. Sci. Techno/. 1987, 21, 466-75. (33) Lonneman. W. A,; Sella, R. L.; Meeks, S . A. Environ. Sri. Techno/. 1986,20. 79096. (34) Baugues. K. “A Review of NMOC, NO. and NMOCINO, Ratios Measured in 1984 and 1985.’’ EPA-45014-86-015; Office of Air Quality Planning and Standards. EPA: Research Triangle Park. N.C.. 1986. (35) McElroy. E E etal. J. AirPoIIur. Control ASIOC. 1986.36, 710-14. (36) Ching. J.K.S. et at. Presented at the 80th Annual Meeting of the Air Pollution Control Associalinn. New York. N.Y.. June 1987. (37) Dodge. M. C. Presented at the North American Ozidant Symposium, Quebec City. Quebec. Canada, February 1987. (38) Meyer. E. L. “Review of Control Strategies for Ozone and Their Effects on Other Environmental Issues”; EPA-45014-85-01 I ; Office of Air Quality Planning and Standards, EPA: Research Triangle Park. N.C.. 1986.
D a v i d I! Chock (I) is a senior staff research scimti.sr in General Motors Re.worch Loboratories ’ Enaironmental Science Departmen!. He holdr a Ph.D. degree in chemical physicsfro,n the Universifyof Chicago. He hos worked on problems related to airpollurion, including atmospheric transport. mathematical modeling. numerical methods. ond statistical applications.
Jon M. Heuss (r) is a principal research
(27) Haney. J. L.; Braverman, T L. “Evalua-
engineer in General Motors Research Loboratories ’ Environmental Science Department. He is the manager in charge of the Pollutant Chemistry and Transport Section. He holds an M.S. degree in chemical engineeringfiom the Universiry of California at Berkeley. He has carried out or led research in air pollution, including the characterization of emissions and laboratory studies of rhe fate of emissions. He also has conducted j e l d and modeling studies. Envimn. Sci. Technol..Vol. 21. NO. 12. 1987 1153
