These curves are the smoothed, normalized, coarse, and fine centrifuge runs for each sample. The cell fume (solid line) is seen to have a number distribution that increases, nonlinearly, with decreasing particle size. The “after baghouse” sample (dashed line) is strikingly different. A maximum number of particles occur a t -0.4 p and then decrease very sharply with decreasing particle size. Interpretations of these size distribution comparisons are as follows: The very fine cell fume particulate in the “before baghouse” sample collected onto the surfaces of the much larger alumina particles in the dry scrubber. The alumina particles are evidently effective collectors of very fine particles as well as gaseous fluorides. Mass- size distributions were calculated from the number distributions. These results are shown graphically in Figure 14. The mass distribution of the cell fume is seen to be strongly bimodal. I t is interpreted that the small size mode is true cell fume and the larger size mode is mostly from alumina particles. These results suggest that it is not the finest of the fines, but the coarser of the fine particles, -1-10 1,that tend to penetrate the baghouse. Cumulative log-normal plots from the cascade impactor plates which were sampling concurrently showed the afterbaghouse sample to be log-normally distributed with a mass-median diameter of about 4 wm and 85% of the mass larger than 1 pm. The cell fume sample was bimodal not log-normal; it showed a mass-median diameter of -4 pm but only 63% of the mass was larger than 1 wm.
Acknowledgment Several people a t Kaiser’s Center for Technology provided significant input to the success of this project. In particular, J. A. Dickeson provided the engineering design work, A. J. Jensen the machine work, and J. Peaslee the electrical work. J. D. Balser and Rosa Chau did the SEM work. H. J. Seim and E. 0. Strahl critically reviewed the manuscript. Thanks is expressed for their considerable help.
Literature Cited (1) Miller, S., “Who’s Afraid of Small Particles?”, Enuiron. Sci. Technol., 7 (13), 1085 (1973). (2) Blacker, S. M., “Evaluation of the Andersen Stack Sampler for Particle Sizing”, American Industrial Hygiene Association Conference, San Francisco, Calif., May 1972. (3) Hochrainer, D., “ A New Centrifuge to Measure the Aerodynamic Diameter of Aerosol Particles in the Submicron Range”, Colloid Interface Sci., 36, (2) (June 1971). (4) Motor: Globe, Cat. No. 166A100-7, Avent Electronics, 10916 Washington Blvd., Culver City, Calif. Controller: Detection Sciences, Inc., System SY1010, 7731 Country Club Drive, Minneapolis, Minn. (5) Stober, W., Berner, A., Blashke, R., “The Aerodynamic Diameter of Amregates of Uniform SDheres”. J . Colloid Interface Sci., 29 (4j:71; (April 1969). (6) Stober, W., Flachsbart, H., “Size-Separating Precipitation of Aerosols in a Spinning Spiral Duct”, Enuiron. Sci. Technol., 3, 1280-96 (Dec. 1969).
Received for review M a y 5, 1975. Accepted October 3, 1975. Work partially supported by the California Air Resources Board.
Ozone Formation from NO, in “Clean Air” William L, Chameides” and Donald H. Stedman Space Physics Laboratory, Department of Atmospheric and Oceanic Science, University of Michigan, Ann Arbor, Mich. 481 09
We present a theoretical model to explain recent observations of ozone in excess of 80 ppb in relatively rural areas. The proposed mechanism involves the interaction of anthropogenic nitrogen oxides from urban areas with the natural photochemical methane oxidation chain. This mechanism can cause the production of large quantities of ozone in the urban pollution plume, leading to high ozoneair pollution events in rural areas downwind of the urban pollution source.
In recent years, several studies have been undertaken to determine the levels of atmospheric pollutants in nonurban environments (1-4). These studies have shown that rural areas are frequently subjected to ozone abundances in excess of the current air quality standard of 80 ppb; a level previously assumed to be limited to the urban environment and significantly in excess of the natural background level of 20-40 ppb ( 5 ) . While these rural air pollution events are characterized by high densities of ozone, the abundance of NO, (NO + NO21 is generally significantly lower than the level of NO, found in urban areas (2, 3 ) . Furthermore, dbring the night, ozone is observed to undergo a relatively small amount of destruction compared to the large nighttime loss of ozone in polluted urban areas. Also it has been shown that these 150
Environmental Science & Technology
events are not simply the result of direct transport of ozone rich air from a specific urban source (2). These results have led to the following theory of nonurban air pollution ( I , 2): An air mass obtains high concentrations of ozone precursors as it passes over an urban center. This air mass is then transported to the remote sampling site. During this transport, it is conjectured, ozone is synthesized and the precursors (which can act as destruction agents during the night) are consumed, thus leaving a large local abundance of ozone that exhibits little or no decay a t night. In fact, Johnston and Quitevis (6) have pointed out that the injection of large amounts of anthropogenic NO, into an air mass as it passes over an urban center could lead to high levels of ozone several hours later as a result of the interaction of NO, with the methane oxidation chain (7,8). In this work we present the results of a photochemical model designed to test the hypothesis of Johnston and Quitevis (6). The calculations demonstrate that many of the gross features of nonurban air pollution events can be explained by this theory.
Photochemistry As Johnston and Quitevis (6) have pointed out, our present knowledge of tropospheric photochemical processes suggests a mechanism for the production of large quantities of ozone from a mixture of urban air, containing large amounts of NO,, and ambient air, containing meth-
Figure 2.
Reactions of the odd nitrogen and odd oxygen gases.
FNO, represents the production of odd nitrogen at the ground
Figure 1. Methane oxidation of methane at the ground
chain. FCH4 represents the production
ane. The photochemical methane oxidation chain shown in Figure 1 is believed t o be the major source of tropospheric formaldehyde ( 9 ) , molecular hydrogen (IO), and carbon monoxide ( 1 1 ) . However, as Crutzen (7) pointed out, the methane oxidation chain also suggests a local source of tropospheric ozone. Note in Figure 1, that in traversing the methane oxidation chain as many as four hydroperoxyl radicals may be produced. As shown in Figure 2, these hydroperoxyl radicals react with nitric oxide (R22) HO2 + NO
NO2
-+
+ OH
producing nitrogen dioxide. About 90% of the nitrogen dioxide molecules are photodissociated (R30) NO2
+ hv
+
NO
+0
drocarbons, like methane, since radical losses to the walls become a significant interference. Nonmethane hydrocarbons are also present in the background troposphere, but their specific nature and concentrations are not well known. If these species contribute significantly to ozone formation arising from their oxidation by OH radicals, then they would increase our calculated rate of ozone formation from the oxidation of methane, but not our overall conclusion. In this work methane, a species whose tropospheric abundance is well known, is the only hydrocarbon included in the model. I t is useful to note that while ozone is being formed via the methane oxidation chain, NO2 may react with OH radicals (R23) NO2 + OH
M
HN03
converting NO, to "03, the most abundant form of tropospheric odd nitrogen, with a characteristic lifetime of about 10 h. Subsequently, heterogeneous reactions remove "03 from the troposphere and thereby constitute a sink of atmospheric odd nitrogen.
Basic Model yielding atomic oxygen, which immediately combines with molecular oxygen (R38) 0
+0 2+M
+
0 3
+M
to form ozone. The return reaction (R29) NO
+0 3
---*
NO2
+0 2
is effective only in setting up a photostationary state (12):
n(NO)n(03) k29 = J30n(NOa)
(1)
Chameides and Walker (8) have calculated, assuming a background concentration of NO,, that this process produces about 5 X IO6 ozone molecules cm-3s-1 a t the ground, which is an order of magnitude larger than the estimated source of ozone due to mixing from above. Thus the methane oxidation chain is probably a major source of ozone in the lower troposphere. In general, the production of ozone or destruction of NO is proportional t o the rate of reaction (R22). Thus it is that an air mass into which relatively large levels of NO, are injected will produce ozone a t a faster rate and therefore contain excess levels of ozone downwind. Note that methane has been shown to be unreactive in smog chambers; however, these experiments tend to be somewhat unreliable for the less reactive or longer lived hy-
T o determine quantitatively the probable ozone increase brought about by the mixing of NO,-rich urban air with ambient air, a time-dependent photochemical model was constructed. The model is similar to that of Chameides and Walker (13) where the details of the calculations are outlined. T h e model includes 22 different gaseous compounds and 52 chemical reactions, some of which are illustrated in Figures 1 and 2. Reaction rate coefficients for these reactions were, for the most part, taken from the recent review of Garvin and Hampson ( 1 4 ) . The model distinguishes between species with relatively long photochemical lifetimes and species with relatively short photochemical lifetimes. Those whose photochemical lifetimes are longer than 30 days (e.g., methane) are assumed to have constant densities that correspond t o their average mixing ratios. The short-lived species, on the other hand, have photochemical lifetimes shorter than 30 days and their local densities are assumed to be determined by photochemical processes, with transport being negligible. T o avoid the inherent stiffness of the photochemical system, very-short-lived species, whose photochemical lifetimes are of the order of 100 s or less, such as OH and HO2, are assumed to be in photochemical equilibrium. Note that since we are interested in variations on the time scale of the order of an hour, this is a good assumption. Finally, the densities of the moderately short-lived species, such as O3 which are not assumed to be in equilibrium, are obtained Volume 10, Number 2, February 1976 151
by integrating the remaining system of continuity equations using standard numerical techniques. The accuracy of the numerical technique is estimated to be about 10%. Consistent with this approach is our treatment of the NO-N02-03 system. As in Chameides and Walker (131, when the NO density is less than the O3 density, typically the case in ambient air, the NO, and 0 3 densities are obtained from integration of equations of the form
dn(Nox) = P(N0,) dt
- n(NO)D(NO) - n(NO2)D(NOz) (2)
and (3) where P is the production rate of the appropriate constituent and D is the destruction frequency of the appropriate constituent. [The exact formulation of P and D are given by Chameides and Walker (13).] The photostationary state, Equation 1, is used to determine the relative amounts of NO and NOz-i.e., (5) However, when the NO density is greater than the 0 3 density, often the case in urban air, 0 3 has a shorter lifetime than NO. In this case, Equation 1 is used to specify the ozone density-i.e.,
St. Louis plume 100 km downwind was less than a factor of two larger in size than the source. Furthermore, extrapolation of the theoretical model of Pasquil and Slade (16) indicates little dilution for a 30-km diameter source over a 300-km downwind travel. For each initial condition, the model simulated the variations in 0 3 and NO, as the day progressed and the air mass advected toward the rural site. Temperature, surface density, and relative humidity were taken from the July U S . Standard Atmosphere Supplements for latitude 30°N and 0 km altitude. T o simulate a diurnal cycle, instantaneous rates were used for summer solstice a t 30°N ( 1 7 ) . Figure 3 illustrates the time evolution of 03,NO, and NO2 in an air mass which passes over the urban center a t 0300, 0600, 0900, 1200 h. Note, particularly in the early morning calculations, the large production of excess ozone and the corresponding loss of NO, (which results in the production of HN03). Furthermore, the relatively low levels of NO, a t night lead to little or no nighttime loss of 0 3 . For comparison, Figure 4,A and B, illustrates the results obtained for different initial concentrations of NO, at 0600 h. These concentrations were obtained from the data of Stedman and Jackson (12) diluted with ambient air by a factor of 3:4 in Figure 4A and factor of 1:4 in Figure 4B. These results, similar to those of Chameides and Walker (13), illustrate the increased daytime production of ozone that results from an increase in the density of NO,.
J30n (NOz) n(03) = -~ n(NOlk.28 Since in this regime, the effect of producing an 0 3 molecule (by way of R22, for instance) is to transform an NO molecule into an NO2 molecule, the relative amounts of NO and NO:, are determined by integretion of the equation
for n ( N 0 ) > n(03) Calculations and Results Calculations were made t o simulate a hypothetical situation in which a remote sampling site is located about 250 km from a large urban center such as Detroit. We suppose that a t about 0200 h on a summer day the local meteorological conditions change so that the rural site is 10 h downwind of the urban center. Thus the rural site, which normally experiences relatively clean air conditions, begins t o be affected by the urban pollution plume a t about 1200 h and continues to do so for some unspecified period. The wind speed and sampling distance were arbitrarily chosen for illustrative purposes. T o simulate the event, successive calculations were made, initializing the model to conditions which approximate those of an air mass over an urban pollution source a t 0300, 0600, 0900, and 1200 h. The initial conditions were taken to be measured concentrations from downtown Detroit (12) diluted in ambient air by a factor of two. The air parcel was then considered to advect with no further mixing. This is a simplifying approximation which is reasonable on some types of days, in view of the scale involved, particularly since the NO, concentration decreases rapidly due to photochemistry. This assumption is supported by the observation of Breeding e t al. (15) that the width of the 152
Environmental Science & Technology
-I.*=
:: X Y
lhrs.
Calculated time variation of 03, NO, and NO2, in an air mass after passing over the urban pollution source Flgure 3.
Solid line is for Os,broken line is for NO,and dotted line is for NO2
1
0600
NOON
I800
0603
NOON
\I
I8W
TIME OF DAY l h s l
Figure 4. Calculated time variation of 0 3 . NO, and NOn in an air mass for different initial concentrations of NO and NO2 at 0600 hours Solid line is for Os,Broken line is for NO,and dotted line is for NO2
loot /POLLUTED 80
I-
4
I
i
i
TIME
1
O3
-I
OF DAY(hn.1
Figure 5. Calculated variations of O3 and NO, at the rural site 10 h downwind of the urban pollution source Solid line illustrates the effect of the advected pollution plume, and the broken line illustrates the calculated diurnal variation in ambient air
Figure 5 shows the resulting time variation of 0 3 and NO, a t the rural site, 10 h downwind of the urban center. Before 1200 h, recall that the rural site experiences relatively clean air conditions, t h u s the O3 density prior to 1200 h is given by the ambient ozone density, as calculated by the model with n(N0,) -1 ppb. Then after 1200 h the effects of the evolution of 0 3 in the urban pollution plume cause the 0 3 density a t the rural site to increase rapidly above the NAAQS of 80 ppb. Note that the O3 level continues to increase in the evening, as air with more concentrated 0 3 arrives a t the site. The general variation of 0 3 and NO, shown in Figure 4 is very similar to the observation of high ozone events a t rural sites by Johnston e t al. ( 5 ) . Based on these results, we conclude that the mechanisms described here can explain the general features of many nonurban air pollution events. I t is interesting to note that this mechanism can also explain the recent observations of moderate ozone enhancements downwind of electricity generating plant smoke stacks by Davis et al. ( 1 8 ) . They observed about 25 ppb excess NO, within the power plant plume a t 32 km downwind with a wind of about 20 km/h. According to our calculations, it is possible that the subsequent 20 ppb excess 0 3 observed in the plume at about 40 km downwind was due t o the interaction of the NO, emitted by the power plant with the natural photochemical processes of the methane oxidation chain. As discussed previously, the presence of nonmethane hydrocarbons would simply tend to further increase the rate of ozone formation.
Conclusion We have presented a time-dependent photochemical model which grossly reproduces the general features of rural air pollution events. We have shown that significant amounts of excess ozone may be produced through the interaction of anthropogenic NO, from urban centers with
the ambient methane oxidation chain. These results imply t h a t the high abundances of NO, commonly present in urban areas may ultimately cause air pollution levels of ozone in surrounding rural areas. The characteristic ozone depletion by NO, injection and subsequent reformation of excess ozone that we calculate is typical of smog chamber data. One important difference between the mechanism considered here and urban photochemical smog is that the highly reactive, heavier hydrocarbons do not play a role in the production of ozone in rural areas. This is likely since the reactive hydrocarbons produced in urban areas are rapidly removed by reactions with ozone and other oxidants. As a result, eye irritants such as PAN and PBAN are not produced during these rural events. This lack of a direct “human effect” may account for the fact that-, until recently, rural high oxidant events mostly passed unnoticed. I t is interesting to note that in our model the destruction of NO, results in a corresponding production of gaseous HN03. The rapid loss of NO, calculated in our model gives rise to H N 0 3 abundances large enough to lower significantly the pH of rain. While the results presented here are highly suggestive, more complete and detailed studies are necessary to fully identify the factors that control the frequency and severity of nonurban air pollution events. In particular, measured concentrations and mixing parameters will make possible a more accurate assessment of the role of the photooxidation of methane in rural air pollution events.
Literature Cited (1) Miller, P. R. McCutchan, M. H., Milligan, H. P., Atmos. Envi-
ron., 6,623-33 (1972). (2) Johnston, D. R., Bach, W. D., Jr., Decker, C. E., Hamilton, H. L., Jr., Matus, L. K., Ripperton, L. A., Royal, T. M., Worth J . J. B., RTI Project No. 41v-764, 106, Research Triangle Institute, North Carolina, 1973. (3) Johnston, D. R., Decker, C. E., Eaton, W. C., Hamilton, H. L., Jr., White, J . H., Whitehorne, D. H., EPA-450/3-74-034, ibid., 1974. (4) Coffey, P. E., Stasuik, W. N., Enuiron. Sci. Technol., 9, 59-62 (1975). (5) Hering, W. S., Borden, T . R., Doc. AFCRL 64-30 (1, 2), U.S. Air Force Cambridge Research Lab, Bedford, Mass., 1964. (6) Johnston, H. S., Quitevis, E., presented a t the Fifth International Congress of Radiation Research, Seattle, Wash., July 1974. (7) Crutzen, P. J., “Physics and Chemistry of the Upper Atmosphere,” B. McCormac and D. Reidel, Eds., Dordrecht, Netherlands, 1973. (8) Chameides, W., Walker, J . C. G., J . Geophys. Res., 78, 8751-60 (1973). (9) Levy, H., Science, 173, 141-3 (1971). (10) Wofsy, S. C., McConnell, J. C., McElroy, M. B., J . Geophys. Res.. 77,4477-93 (1972). (11) McConnell, J. C., McElroy, M. B., Wofsy S. C., Nature, 233, 187-8 (1971). (12) Stedman. D. H.. Jackson J. 0..I n t . J . Chem. Kinet.. in Dress. September 1975. ’ 113) Chameides. W.. Walker, 3. C. G., J . Geophys. Res., 81,413-20 (1976). (14) Garvin, D., Hampson, R. F., NBSIR 74-430, Nat. Bur. Stand., Washington, D.C., 101 pp, 1974. (15) Breeding, R. J., P. L. Haagenson, J . A. Anderson, J . P. Lodge, J . Appl. Met., 14, 204-16 (1975). (16) D. H. Slade, “Meteorology and Atomic Energy”, Atomic Energy Commission, 1971. (17) Stedman, D. H., Chameides, W., Jackson, J. O., Geophys. Res. Lett., 2.22-5 (1975). (18) Davis, D. D., Smith, G., Klauber, G., Science, 186, 733-6 (1974). Received for review March 20, 1975. Accepted October 13, 1975.
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