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Atmospheric Transport and Dispersion of Air Pollutants Associated with Vehicular ~ . . Emissions PERRY ]. SAMSON University of Michigan Definitions of Transport and Dispersion / 78 Meteorological Parameters / 78 Scales of Motion / 81 Transport and Dispersion: Theory and Applications / 82 Near Field / 82 Urban-Scale Transport and Dispersion / 88 Regional-Scale Transport / 89 Summary 1 92 Summary of Research Recommendations / 93 Air Pollution, the Automobile, and Public Health. @) 1988 by the Health Effects Institute. National Academy Press, Washington, D.C. 77

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78 Atmospheric Transport and Dispersion of Air Pollutants Definitions of Transport and Dispersion The movement of pollutants in the atmo- sphere is caused by transport, dispersion, and deposition. Transport is movement caused by a time-averaged wind flow. Dis- persion results from local turbulence, that is, motions that last less than the time used to average the transport. Deposition pro . . cesses, 1nc. .uc sing precipitation, scavenging, and sedimentation, cause downward move- ment of pollutants in the atmosphere, which ultimately remove the pollutants to the ground surface. This chapter deals only with transport and dispersion. During the past decade, the complexities of transport and dispersion of airborne pol- lutants associated with vehicular emissions have been studied with elaborate field and modeling experiments. In the first part of this article, the terms used in the study of transport and dispersion of pollutants and the scales of motion (time and distance) over which vehicular emissions may affect air quality, precipitation quality, or both, are defined. Since pollutants can travel dis- tances from meters to hundreds of kilo- meters, the relative scales of motion involved in distinguishing transport phe- nomena from dispersion phenomena may vary from problem to problem. The second part of the chapter, Trans- port and Dispersion: Theory and Applica- tions, outlines the observational informa- tion on transport and dispersion, describes the theoretical tools that have been used to simulate the transport of vehicular emis- sions, identifies the limitations of these tools, and recommends specific areas for further research. Mathematical formula- tions of transport and dispersion are devel- oped only as needed to identify the param- eters of interest. Meteorological Parameters The concentration of pollutants associated with moving vehicles is determined by several factors: the emission rate of pollut- ants from the vehicle, mixing induced by vehicle motions wind speed and direction relative to the axis of the highway, inten sity of ambient atmospheric turbulence, reactions to or from other chemical species, and rate of removal to the ground surface (deposition). Concentrations associated with nonmoving vehicles as might be encoun- tered in traffic queues, parking structures, and street canyons are determined by emis- sion rates and the wind flows and turbulence produced by the interaction of the local wind with complex structures such as buildings and roadside sound barriers. Weather plays a role in most of these components, generally causing higher emission rates at lower tem- peratures (Chang and Norbeck 1983b), dilut- ing pollutants at higher wind speeds, mixing pollutants vertically during unstable thermal conditions, and influencing the rates of ho- mogeneous and heterogeneous chemical re- actions and the rate at which pollutants are scavenged from the atmosphere by moisture or dry deposited. Regardless of the distance over which a pollutant is transported, the change in its concentration can be described by the con- servation-of-mass equation. The temporal change of the concentration of a pollutant is expressed mathematically as OX ~ 6(ux), box), tax) at ax By Oz = Q+R+S (1) where X is the concentration in ,ug/m3; UJ V, and w are the east-west, north-south, and vertical components of the wind, respec- tively, in m/see; t is the time in seconds; Q is the emission rate in ,ug/m3/sec; R is the rate of increase or decrease in concentration due to chemical reaction, in ,ug/m3/sec; and S is the rate of removal by deposition, in ,ug/m3/sec The continuous calculation of X would be untenable and would not allow for ex- trapolation of the results to other sites. Instead, motions are divided into mean and turbulence components to simplify the cal- culation and allow generalized parameter- ization. The turbulence component (disper- sion) is defined as the deviation of the actual wind from a mean wind vector. The aver- aging time used to define the mean varies depending on the scales of motion associ- ated with the problem. For example, dis

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Perry]. Samson 79 persive components of wind motions con- sidered in the long-range transport of pol- lutants include motions that are also con- sidered to be mean components in the dispersion of pollutants within 100 m of a highway. The variables u, v, w, and X can each be described as the sum of a mean and a turbulent component as follows: u = u + u', v = v + v'; w = w + w', and X = X + X', where, for example, u is the instanta- neous measurement of the east-west com- ponent of the wind, u is the mean compo- nent, and u' is the deviation of u from the mean. Substituting these equations into equation 1 and assuming an incompress- ible, nondivergent atmosphere (reasonable assumptions for most scales of motion af- fecting vehicular emissions) produces (8X/~: +-u(6xl~x) + -v(6x/by) + -[~(U'X')/dxl-[~(V X )/8Y] -[~(w'x')/6z] + Q + R + S W(6xIeZ) = The first term in equation 2 describes the change of concentration with time, the second through fourth terms on the left side describe the changes due to mean motions (transport), and the first three terms on the right side describe the changes due to turbulence (dispersion). Many of the unsolved problems associated with the transport and dispersion of vehicular emis- sions arise from the need to characterize the turbulence components of this equation in some universal manner. The turbulence fluxes (ill, F7i7, ~7iT- defined as the mass of pollutant deposited per unit area per unit time due to turbu- lence) are difficult to measure directly. It is common therefore to assume that the tur- bulence flux is proportional to the gradient of the mean concentration w'x' =-Kz(6xl~z) (3) where the proportionality, K=, is called the vertical eddy diffusivity. Hence equation 2 becomes equation 4: ~ _ ~ _ ~ _ ~ (6X/6t) + U(6X/6X) + v(6x/dy) + w(6x/3z) (flax) [KX(6XI3X)] + (flay) [KY(6X/6Y)] + (6l~z)[Kt(6xl~z)] + Q + R + S = Furthermore, assuming that the eddy dif- fusivity values, Kx, Ky' and Kz' are invari- ant along their respective axes (Fickian dif- fusion, an assumption often made to simplify the calculation, but not necessarily physically'realistic), this expression can be simplified to the parabolic form (6x/3t) + U(6X/6X) + v(dx/by) + w(6x/6z) = KX(62XI6X2) + Ky (62x/6y2) + K (62xl~z2) + Q + R + S . (5) Generally, when the flow is parallel to the x-axis, the diffusion term KX(32XI6X2) is small compared to the transport term u(6xl~x) and is ignored. Likewise, for a continuous infinite line source (for exam- ple, a long, straight section of highway) oriented along the y-axis, both the KX and Ky terms are usually ignored. Although values of Kz have been deter- mined for relatively simple surface charac- teristics, values for complex surfaces are nonunique and difficult to establish. The problems associated with parameterizing dispersion over a variety of scales are pre- sented in the Scales of Motion section. Apart from natural transport and disper- sion processes, moving vehicles themselves cause considerable mixing that influences pollutant concentrations within about 100 m of a highway. The aerodynamic drag of a moving vehicle causes a turbulent wake in which pollutants initially mix. 'This mixing is influenced by the shape and speed of the vehicle, and its influence on concentra- tion is most pronounced when the wind is nearly parallel to the axis of the highway. [figure 1 shows a schematic representa- tion of the wake area behind a moving vehicle. Vehicular emissions that are transported beyond about 100 m from a highway are generally at levels well below any National Ambient Air Quality Standard (NAAQS). However, in some urban areas and under conditions of limited atmospheric ventila

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80 Atmospheric Transport and Dispersion of Air Pollutants Wind \ direction \ \ .~..~ !~ r hi wake Figure 1. Schematic representation of the transport of a turbulent wake away from a highway with an oblique wind angle. (Adapted with permission from Eskridge and Hunt 1979, and from the American Meteorological Society.) lion (that is, low wind speeds and topo- graphical barriers), potential problems still exist. For example, Los Angeles experi- ences periods of limited ventilation because of topographic constraints. Schultz and Warner (1982) have demonstrated the recir- culation of pollutants in the Los Angeles basin. Other researchers have shown that the recirculation of urban air can lead to high concentrations of primary pollutants (those emitted directly into the atmosphere) and secondary pollutants (those resulting from chemical reaction). Anchorage and Fair- banks, Alaska, although small compared to other U.S. cities, frequently have days on which the carbon monoxide (CO) concen- trations exceed the NAAQS. These days occur during the coldest winter months when air stagnates in the valleys (Zim- merman and McKenzie 1974; Bowling 1984; Femau and Samson 1985~. Also, there are potential problems in urban street canyons, where the complexities of wind flow can lead to high pollutant concentrations under cer- tain conditions. The introduction of metha- nol in fuel, for example, could lead to in creases in formaldehyde in urban street canyons. Although problems still exist, the inci- dence of elevated concentrations of primary pollutants in urban areas has been declin- ing. This is not true of secondary pollutants such as ozone (03~. High O3 concentra- tions occurring in and downwind of urban areas have been documented for many cit- ies in the United States and elsewhere (Spicer et al. 1982; Clark and Clarke 1984~. High O3 concentrations generally occur during the summer months under sunny, but not necessarily stagnant, atmospheric conditions. To diagnose the cause of high O3 concentrations in urban areas, better measurement of wind flow is needed. De- termining the transport of pollutants in urban areas is often difficult, if not impos- sible, due to the lack of relevant measure- ments of wind flow above the surface. Hy- drodynamic simulations of wind flow over urban areas have been performed but were constrained by a lack of relevant meteo- rological data for boundary and initial condi- tions. During the past 20 years, transport and dispersion of pollutants over long distances have been implicated in the degradation of air and precipitation quality in remote ar- eas. Concentrations of O3 in excess of 80 ppb were found in rural areas by Coffey and Stasiuk (1975) and Quickert et al. (1976), and the transport of O3 over long distances has been investigated by a num- ber of researchers (Husar et al. 1976; Lyons and Cole 1976; Chung 1977; Samson and Ragland 1977; Wolff et al. 1977; Spicer et al. 1979~. Pollutants other than O3 and its precur- sors are believed to be transported over long distances and to influence precipitation quality in nonurban areas. The direct con- tribution of vehicular emissions to acidic deposition is thought to be small given the magnitude and emissions of nitrogen ox- ides (NOX = NO + NO2) relative to other sources and the relatively lower mean height of emissions. However, if sulfur dioxide (SO2) emissions are decreased as part of an emissions control program for acidic deposition, NOX emissions may con

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Perry I. Samson 81 tribute a larger percentage of total acidic deposition. An assessment of the NOX contributions to the production of O3 and atmospheric acids requires an estimation of the amount of pollutants moved to the surface near the source by dry deposition. (Dry deposition is the removal of pollutants from the atmo- sphere in the absence of precipitation. See Atkinson, this volume.) The rate of dry deposition also affects the vertical distribu- tion of pollutants, and hence their residence time in the atmosphere, and is dependent upon the rate of pollutant mixing to a surface as well as the type and condition of the surface. The study of the rate of drv deposition of vehicle-related pollutants is of special interest since pollutants released near the surface should be deposited closer to the source area than those emitted from elevated sources. Presumably, a unit of pollutant emitted close to the surface is available to the surface in higher concentra- tion than is a similar amount emitted from a higher point and thus is more likely to be dry deposited in the near field. This implies that vehicular emissions of NOX would be less likely to travel long distances than NOX emitted from elevated sources. Scales of Motion Human exposure to vehicular-related pol- lutants is considered in terms of three scales of distance: near field (0.0~.2 km), urban (0.2-20 km), and regional (20-2,000 km). Direct exposure to primary vehicular emis- sions may occur inside vehicles as they idle, or from entrainment of air from other vehicles. Generally, vehicular emissions are produced by moving vehicles, but it is also possible for idling vehicles to contribute to high pollutant concentrations, for example, in a parking structure or lot, a street can- yon, or a highway queue at rush hour. Consequently, the dispersions associated both with moving vehicles (line sources) and with aggregates ot parked or queued vehicles (area sources) are considered. Ele- vated (nonsurface) emissions from sources such as smokestacks (point sources) are of little importance in the field of vehicular . . emissions except perhaps when comparing the relative human exposure resulting from surface versus nonsurface emissions on ur- ban and regional scales. The exposure of humans to vehicular emissions has been studied principally in the near-field environment (0-0.2 km) as will be shown. Exposures in this range are experienced by bicyclists, motorcyclists, pedestrians, people in nearby buildings, and vehicle passengers. This exposure has been fairly well documented for simple configurations in open countryside, but the exposure obtained in complex settings such as street canyons is poorly understood. Knowledge of concentrations on highways is also sketchy. In terms of human expo- sure, however, this information is critical. Air entering a vehicle or breathed by a cyclist is a direct sample of initially mixed emissions. Hence, understanding the initial . . . . . . mixing process 1S very important in est1- mating exposure. Exposures obtained on an urban scale (0. 2-20 km) due to the mixture of vehicular and nonvehicular emissions are also fairly well documented. Urban-area exposure to primary pollutants has generally declined due to improvements in emission control technology. However, some urban areas of high exposure still exist, as mentioned pre- viously, and these problems are generally exacerbated by a combination of adverse meteorological conditions and topographic constraints. Secondary pollutants formed from vehicular emissions, such as O3, can become fairly high in urban areas. Estimating the contribution of vehicular emissions to regional-scale (20-2,000 km) air quality problems is even more challeng- ing. The NOX and reactive hydrocarbon emissions of vehicles are thought to con- tribute to regional-scale O3 levels and the levels of other oxidizing compounds such as hydrogen peroxide (H2O2) and hydroxyl radical (OHM. These oxidizing agents are known to influence the rate of conversion of SO2 to sulfate (SO42-) and NOX to nitric acid (HNO3) and nitrate (NO3-~. Thus, while the direct influence of emitted NOX on acidic deposition is not thought to be large relative to other sources, the indirect

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82 influence of vehicular emissions on the pro- duction of acidic species is probable but poorly understood. Transport and Dispersion: Theory and Applications This section describes the theories of trans- port and dispersion of vehicular emissions for the various scales of motion outlined above and discusses their application to available observational data. Mathematical descriptions are presented only to the point necessary to identify areas of understanding and ignorance. Near Field Open Highway. Most automotive emis- sions presumably result from moving ve- hicles. The dispersion from a continuous line source (highways) assuming Fickian diffusion can be described using the Gaus scan equation X~ Y) Lutz Lx) U texpt-1/2~:~ + ~ 1/2:Z-~1~25: where q is the emission rate in g/m/sec; Mix) is the standard deviation of concen- tration expected in the vertical direction as a function of travel distance, x, downwind; H is the elevation of the source above the surrounding terrain; the z + H term on the right side of the equation describes the effect of surface reflection on the vertical distribution of the plume; and U is the mean wind speed near the highway. (The choice of a representative wind speed is not straightforward. Wind speed and direction can change substantially near the surface, especially near the highway where they are influenced by the motion of the vehicles.) Atmospheric Transport and Dispersion of Air Pollutants The theoretical description of transport and dispersion processes has been devel- oped for a continuously emitting line source by Calder (1973) and for an instantaneous emission from a line source by Shair (1974~. A variety of line-source models using this basic approach are available (Zimmerman and Thompson 1975; Benson, 1979~. Such models have been shown to reproduce con- centrations with some accuracy when winds are perpendicular to the highway with near neutral stability (that is, temperature de- creases with height at a rate of approximately 1 C/100 m). However, under conditions with winds nearly parallel to the axis of the highway, these models tend to overpredict concentrations of pollutants (Noll et al. 1978; Rao et al. 1979a; Sistla et al. 1979~. One reason for the observed overpredic- tion in these models has been the lack of description of the effect of mixing by vehi- cles themselves. Figure 2 shows the rela- tionship of the concentration of the tracer gas sulfur hexafluoride (SF6) versus vehicle speed for unstable, neutral, and stable at- mospheric conditions 2 m downwind of a roadway. This plot shows that concentra- tions generally decrease with increasing vehicle speed regardless of ambient atmo- spheric stability, suggesting that vehicle (6) 20 _ Q g 0 15 _ A: z LO ~ 10 o co 5 _ o o -. \/ \~ Stable 20 40 60 80 100 VEHICLE SPEED (km/hr) Figure 2. Concentration of SF6 tracer gas versus vehicle speed for unstable, neutral, and stable atmo- spheric conditions at 2 m downwind of a roadway. (Adapted with permission from Petersen et al. 1984.)

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Perry.~. Samson 83 induced turbulence dominates ambient tur- bulence. Green et al. (1979) also noted that the ground-level pollutant concentrations near a highway did not increase as rapidly with decreasing wind speed as predicted by most Gaussian line-source models. Fur- thermore, using a Gaussian model for a city in Czechoslovakia, Hesek (1981 p. 144) also found that "the diffusion . .. caused by moving cars must also be considered in the calculation. " Most modeling of pollutant transport and dispersion in the vicinity of highways has ignored the turbulence generated by the moving vehicles themselves. Since a theory to predict the wind velocity and turbulence in the wakes of vehicles did not exist, models either ignored the changes in veloc- ity and the mechanical mixing caused by the vehicles, or parameterized them in a simple manner, such as assigning a large eddy-diffusion coefficient to the roadway. Rao et al. (1979b), using data from a study of pollutant dispersion along the Long Island Expressway (Rao et al. 1978), found enhancement of turbulence energy in the range of 0.1-1.0 Hz downwind of the highway during moderate-to-heavy traffic a, 20.0 _ - * 15.0 Mu ~ 10.0 at o ~ s.o J > 0.0 A ~ / ? Aft/ |: == E I ~ I ~ 20 40 60 80 100 120 DISTANCE FROM THE MEDIAN CENTER, meters Figure 3. Measured values of - (x) as reported by Rao and Keenan (1980) compared with - (x) curves suggested by Briggs (1975) for open, flat country point sources under various ambient stability catego- ries, A-F (A represents least stable atmospheric con- ditions; F. most stable). l , , conditions. This corresponded to turbulent elements of a few meters in diameter, which is roughly the height of the automo- bile and truck traffic on the nearby high- way. Sedefian et al. (1981) found similar "traffic turbulence" enhancement in wind data collected during the General Motors (GM) dispersion experiment (Cadre et al. 1977~. The calculated values of Mix) downwind of the GM line source are plot- ted in figure 3 and compared with the suggested curves for open, flat country from Briggs (1975~. The lack of variation in oryx) values despite the changing ambient stability illustrates the dominance of traff~c- induced turbulence over ambient turbu- lence in the near field of a line source. To compensate for the poor predictions of simple Gaussian line-source models un- der certain conditions, a number of modi- fications to the basic Gaussian approach have been developed. Bullin and Maldo- nado (1977) developed a model that used an empirical equation near the highway and the Gaussian dispersion equation down- wind. Benson (1982) suggested that the initial mixing of pollutants by vehicles could be described mathematically by rede- fining c~z~x) values. Chock (1977b) and Rao and Keenan (1980) suggested improve- ments to the Gaussian line-source model through redefinition of oryx) to account for traff~c-induced mixing near the highway. The former suggestions were used to im- prove the predictive capability of the EPA HIWAY model (Petersen 1980~. These modifications improved the performance of the model, but they were tuned to vehicle speeds of about 80 km/hr and a vehicle distribution that was not necessarily typical of other traffic situations. Others have used numerical simulation of the conservation-of-mass equation to predict pollutant transport near highways. Malin (1972) reported on a two-dimen- sional numerical model that included the likely role of topography on the wind field. Danard (1972) allowed for horizontal vari- ation of vertical eddy diffusion (K=) over the highway. It was found that even nu- merical models incorporating variable eddy diffusivity (see, for example, Ragland and Peirce 1975) failed to improve significantly

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84 Atmospheric Transport and Dispersion of Air Pollutants Table 1. Suggested Values of Kxt and Kz' to Account for Tradic-Induced Turbulence as a Function of Wind Speed, U (m/sec) Distance broad Height Kit (m2-sec) K ' (m2 see) (m) (m) U> 2 1 2 1 < U ' 2 U ' 1 1.7 u 4.5 0 0 0.45 0 0 0.30 1.7 u 1.5 0.45 0.45 0.45 0.30 0.30 0.30 Median 4.5 0.45 0.45 0.45 0.30 0.30 0.30 Median 1.5 0.45 0.45 1.05 0.30 0.30 0.45 1.7 d 4.5 0.60 0.60 0.60 0.45 0.45 0.45 1.7 d 1.5 1.05 1.05 1.05 0.45 0.45 0.45 15 d 4.5 0 0.60 0.60 0 0.45 0.45 15 d 1.5 0 0.75 0.75 0 0.45 0.45 30 d 4.5 0 0 0.45 0 0 0.15 30 d 1.5 0 0 0.45 0 0 0.15 NOTE: u = upwind; d = downwind. SOURCE: Adapted with permission from Chock 1978a, and from the American Meteorological Society. upon the simulated concentrations using Gaussian line-source models. Fay (1975) and Lane (1976) made some earlier estimates of the dispersion of pollut- ants in automobile wakes, but recent work has had the advantage of new data on near-highway turbulence and tracer has concentrations. Eskridge and Hunt (1979) and Eskridge et al. (1979) developed a finite-difference model for calculating pol- lutant concentrations on and near a high- way that incorporates a vehicle wake the- ory. The wake theory was modified and predicted concentrations under these con- ditions. Eskridge and Rao (1986) used ver- tical and lateral profiles of tracer gas con- centrations obtained in the wake of a simulated moving vehicle (Eskridge and Thompson 1982) to determine the best turbulence scale lengths (a measure of the average size of turbulent elements). This information was used to improve upon the earlier concentration predictions, which in- cluded wake effects. Chock (1978a) developed a model for pollutant dispersion near roadways that approximated the influence of traffic by in- creasing the eddy diffusivity near the high- way. This approximation implied that tur- bulence generated by traffic did not interact strongly with ambient turbulence. For an automobile moving at 80 km/hr, Chock suggested the use of Kxt and Kz`' the down- wind and vertical eddy diffusivities due to traffic, respectively, as shown in table 1. Chock (1977a, 1978b) showed that under light wind conditions a measurable heat flux can be discerned from temperature and wind data collected at the GM dispersion experiment and at a field experiment con verified in wind tunnel experiments by Eskridge and Thompson (1982~. They cau- tion that their results were restricted to conditions where vehicle speed was much greater than wind speed. Eskridge et al. (1979) compared the predictions of a line- source model that included wake theory with observed SF6 tracer gas concentrations in a controlled field experiment conducted by the General Motors Research Labora- tory (Cadre et al. 1976; Chock 1977a). The results showed that predictions made using wake effect were closer to the observations than those of the EPA HIWAY model , l (Zimmerman and Thompson 1975~. Esk- ducted by SRI International (Dabberdt ridge et al. (1979) found that ignoring wake 1977~. The exhaust heat convection could turbulence led to overpredictions in con- play an important role in the dispersion of centration when the wind was nearly par allel to the axis of the highway. An increase in mechanical mixing led to a decrease in pollutants near highways under light wind conditions with heavy traffic by lifting the exhaust plume (plume rise).

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Perry T. Samson 85 The transport and dispersion processes described above were designed to predict concentrations of inert gaseous pollutants. Some modeling of the transport and disper- sion of particles from highways has also been recently attempted. Katen (1977) used the method of modified Gaussian solutions, developed through analogy with finite- differencing techniques, to simulate the transport, dispersion, and deposition of lead particles from a highway. Sheih (1980) devel- oped a finite-difference model to evaluate the importance of particulate coagulation during dispersion of emissions from a highway. In summary, there have been several recent advances in the description of trans- port and dispersion on the open highway. The advances have included the observa- tions that traffic enhances dispersion near highways, traff~c-wake-induced turbulence can dominate ambient turbulence, and a measurable plume may rise over highways having high traffic density under light wind . . cone Tons. These advances have stemmed from the availability of high-quality measurements of turbulence and tracer gases. New inves- tigations of vehicle wake turbulence and its effect on near-field pollutant concentrations hold considerable promise for improved description of transport and dispersion of pollutants near highways. But these new studies are constrained by the fact that the data, and hence the models, represent a somewhat biased subset of meteorological conditions and generally represent straight- line sources in open, flat terrain. Research on transport and dispersion from line sources has greatly benefited from field studies of tracer gas dispersion near straight highways. The recent incor- poration of vehicle-wake theory into line- source models offers more realistic descrip- tions of the vehicle-induced turbulence and its effect on near-field pollutant concentra- tions. Recommendation 1. Future research should continue to focus on the role of vehicular turbulence in the initial dispersion of pollutants. Since high-quality field data have been collected in the past decade, this research would be best served by the use of physical modeling facilities to simulate highway situations. This research should focus on air quality on the highway to which vehicle passengers and open-vehicle (bicycle, motorcycle, moped, and so on) passengers and pedestrians would be ex- posed. Recommendation 2. The importance ot plume buoyancy on near-highway and/ or street-canyon pollutant concentrations needs to be clarified. The amount of heat being generated on both the highway and vehicles should be quantified. The disper- sion of that heat should be modeled to identify the atmospheric conditions most likely to produce significant thermal plume rise. These calculations should be verified against wind tunnel simulations. Urban Street Canyons and Parking Struc- tures. The transport and dispersion of pollutants from urban street canyons, bus or truck terminals, and parking structures and lots is less well understood than the transport and dispersion of pollutants around open highways. Human exposure to pollutants emitted in these environments could be high in such congested areas. Simulating the transport of pollutants within a street canyon is very difficult and virtually impossible to extrapolate to other sites or times. Application of line- or point- source equations to vehicular emissions in complex situations is generally not war- ranted. The airflow in street canyons is neither steady nor homogeneous, and street segments do not approximate infinite line sources. Likewise, exhaust from parking structures is rarely vented through an iso- lated, elevated point source. Parking struc- ture emissions tend to be relatively close to the ground in areas of complex wind flow because of nearby structures. The initial rise (if any) of the nonbuoyant plume is difficult to estimate and often difficult to measure because of local air circulation var- iation (Hosker 1984~. Transport through open parking lots, such as are found at most truck stops, is also difficult to describe because of the inhomogeneities produced by the interaction of the wind with the configuration of trucks.

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86 Atmospheric Transport and Dispersion of Air Pollutants __ ~/ ...... ~: / ~5 in/ ~ ~...,~/ it/ if/: ~ Figure 4. Schematic representation of the complex- ity of airflow in a two-dimensional street canyon with wind perpendicular to the axis of the street. Simple models have been developed by Benesh (1978) and Messina et al. (1983) to simulate pollutant concentrations at urban intersections. These models incorporate modified Gaussian plume equations to try to reproduce concentration fields in com ncult to obtain representative values ot wind direction, wind speed, and stability. Moreover, the large concentration gradi- ents that could occur in a street canyon because of the complexity of airflow make extrapolation of results to estimates of "typical" human exposure difficult (Brice and Roesler 1966; Cortese and Spengler 1976; Petersen and Allen 1982~. Very few computer simulation models have been developed for street canyons because of the complexity of building ge- ometry and wind flow. A vortex of airflow is expected when the flow above building height is perpendicular to the axis of the canyon, as shown schematically in figure 4. Air moves down the windward side of the canyon, returning as it approaches the street in a direction opposite to the direc- tion of the airflow above the roof, and rises on the leeward side. For situations where the wind flow problem can be approxi mated two-dimensionally (such as in the midsection of a long uniform street can yon), some numerical approaches have been attempted. Johnson et al. (1973) de veloped an empirical model based on data from San Jose, California. The model pre dicted decreasing concentration away from the line source on the leeward side of the canyon but a linear decrease in concentra tion with height on the windward side. Sobottha and Leisen (1980) modified the approach of Johnson et al. (1973) to allow concentrations to increase away from the line source on the windward side. Chock (1983) suggested improvements to the Johnson model by allowing the leeward side concentration to be not only a function of the path lengths from the point closest to the line source along the flow trajectory to the receptor but also a function of the proximity of the trajectory to the source. Yamartino and Wiegand (1986) described the flow and turbulence fields within a street canyon using a simple Gaussian line l ~source model following the flow field with plex settings. The errors in simulated time-dependent coefficients. short-term concentrations can be large Georgiiet al. (1967)conducted one ofthe (Rao 1984~. This is not surprising since the first field experiments of street-canyon pol meteorological conditions at an intersec- lutant concentrations. They found that tion, and especially in a street canyon, are concentrations were higher on the leeward not homogeneous; consequently, it is dif- side of the canyon than the windward side ' ' ' ~because of the presence of a vortex. John son et al. (1973) and Leisen and Sobottha (1980) found that curbside concentrations decreased with height faster on the leeward side than on the windward side. Leisen and Sobottha also observed that the dispersion due to turbulent flows generated around buildings and by moving vehicular traffic was greater than the dispersion generated in the atmosphere through natural means. Nicholson (1975) developed a microme- teorological approach to the airflow in a two-dimensional street canyon. She com- pared her results to observed data from Frankfurt, West Germany, and Madison, Wisconsin. Additionally, Hotchkiss and Harlow (1973) attempted numerical simu- lations of street canyon flow. Although these studies were all able to reproduce the qualitative features of airflow in the street ~.

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Perry I. Samson 87 canyon, no attempt has been made to ex- trapolate these techniques to other situa- tions. The air quality associated with complex- area sources is not well represented by simple modeling techniques. The best, albeit lim- ited, method for assessing impact from such diffuse sources may be physical modeling. Skinner and Ludwig (1976) conducted exper- imental studies of CO dispersion from a highway model in an atmospheric-simula- tion wind tunnel. Their street canyon model induded scaled, moving "automobiles" that were able to emit various tracers for visual or ambient study. Kennedy and Kent (19773 used two lengths of nichrome wire to simu- late two lanes of traffic. The transport and dispersion of heat from the resistance wires were measured as a surrogate for automobile emissions. They found that the addition of two large buildings to their domain could significantly reduce ground-level concentra- tions. Hoydysh and Chin (1971) examined flow in street canyons using a tracer gas released in a street-level line source. They con- cluded that the flow is wake or convection dominated, depending on the crosswind component in the street. Hoydysh et al. (1974) concluded from their experiments that a high-density configuration of uni- form-size buildings generally increased con- centrations and caused pockets of high con- centration near building corners, whereas an intermittent high-rise configuration al- lowed pollutants to escape. Wedding et al. (1977) used a 85Kr-air mixture as a tracer in their wind tunnel to study the effects of building geometry on street-level tracer concentrations. They found that pollutant dilution in a street canyon was controlled by the mean airflow through the canyon rather than by turbulence diffusion. Kita- bayashi et al. (1977) used both neutral and stably stratified air in a wind tunnel to simulate a street canyon situation in To- kyo. The review of the exposure potential for indirect sources requires techniques for es . . . . . tlmatlng transport anc . c aspersion assocl ated with, for example, truck stops, shop ping center parking lots, and intersections. Generally this analysis requires estimates of the number of queued vehicles, idling traf- fic emission rates, and description of emis- sion density geometry. Transport and dis- persion are then estimated using Gaussian line-source approximations (Hanisch et al. 1978; Rao 1984~. Although there is poten- tial for short-term exposure in such situa- tions, there are few comprehensive data with which to evaluate the transport of these pollutants. For example, given the possibility that truck drivers, while sleep- ing in their cabs, could be exposed to long-term (overnight) exposures of pollut- ants from diesel exhaust, the study of trans- port and dispersion from idling vehicles must also be explored. In summary, studies of the transport and dispersion of pollutants from complex ur- ban situations suffer from a lack of reliable data and the uniqueness of each situation. Street canyons in particular pose special problems because of the complicated nature of the wind flows relative to specific geom- etries of buildings. Computer simulation of airflow in urban street canyons would re- quire elaborate descriptions of the equa- tions of motion and would be very expen- sive. Tracer studies can provide much useful information about a particular loca- tion but are very labor intensive and awk- ward to use in many situations. Physical modeling (such as wind tunnel simulations) can be adapted to the study area of interest and modified to represent particular atmo- spheric thermal structures. Although this approach is also quite expensive, it is a reasonable way to evaluate potential or existing pollution hot spots at urban inter- sections. Recommendation 3. Transport and dispersion of pollutants within street can- yons and parking structures is so variable that it is unlikely that generalizations will be useful. Nonetheless, better definition of the transport and dispersion of pollutants in such complex situations has a high priority. It is recommended that this problem be studied through use of tracers and that environmentally safe and easily measured tracers be developed. Ideally, the tracer sampling system would be portable and make use of remote sensing. Release of a

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88 Atmospheric Transport and Dispersion of Air Pollutants tracer that could be tracked through the canyon under a variety of conditions would generate new, useful information with which to evaluate the reasonableness of flow generalizations. A portable system could be used at several sites to assess site-to-site deviations from flow generali- zations. The sites for this program should include urban street canyons, parking struc- tures (including truck stops), and other com- plex environments, for example, where sound-reducing roadway barriers and cov- ered highway cuts influence air movement. ~ Recommendation 4. Hand in hand with the development of tracer technology, emphasis must be placed on improving wind tunnel facilities to meet the demands of inexpensively simulating many different complex settings with a variety of atmo- spheric conditions. Given the uniqueness of each urban setting, physical modeling may hold the best hope for identifying potential pollutant hot spots due to complex surface flows. The advantage of physical modeling is that it may be possible to identify phys- ical alterations to the setting that would decrease human exposure to the pollutants. Urban-Scale Transport and Dispersion Modeling of urban-scale (0.2-20 km) trans- port and dispersion of vehicle-related pol- lutants is limited by the lack of wind ob- servations other than hourly measurements at the surface and twice-daily measure- ments in the upper atmosphere. Generally, airflow over an urban area is poorly de- scribed by surface wind measurements, and upper air observations are made at stations roughly 400 km apart. The transport of pollutants over an urban area depends, in part, on regional-scale (2(~2,000 km) wind flows. Even when regional winds are strong, the flow at the surface is modified (usually slowed and turned) by contact with the surface. When the regional flow is light, the flow at the surface is generally altered by inhomoge- neous surface characteristics, both physical (for example, differential friction of forests versus fields) and thermal (differential heat- ing of water versus land). The inhomoge- neities in wind flow that have been of interest to urban-scale transport are those that occur above building height. Goodin et al. (1979) used a dense network of me- teorological measurements to describe ob- jectively the three-dimensional wind flow in the Los Angeles basin. Their estimates included a local terrain adjustment tech- nique (from Anderson 1971, 1973) and successive solutions of the divergence equa- tion to reduce anomalous divergence in the complete field. Transport of pollutants in urban areas has also been described with trajectory analysis. Lurmann (1979) used surface- based observations of wind direction and speed to calculate a transport path through the Los Angeles basin. Lack of observed winds above the surface can lead to signif- icant errors in the estimated path of the air. Liu and Seinfeld (1975) assessed the uncer- tainty imposed on urban-scale trajectory calculations by the effects of wind shear and horizontal dispersion. Chang and Norbeck (1983a) found that inclusion of wind shear corrections In trajectory estimations of source input significantly improved photo- chemical model predictions, since pollutant emission sources were not uniform. Numerous tracer and tetroon (constant- pressure balloon) experiments have shown that under some conditions the air parcel trajectories can vary significantly as a func- tion of height. Angell et al. (1975) observed three-dimensional air trajectories from te- troon flights in the Los Angeles basin. Drivas and Shair (1974) tracked tracer con- centrations across the Los Angeles basin to estimate pollutant transport and dispersion. Bornstein (1975) used a hydrodynamic mod- el to describe the expected wind field over the New York metropolitan area. Al- though their results were not applied to the urban air quality problem, they do repre- sent a reasonable alternative for data-sparse regions where objective analysis techniques are not adequate. Keen et al. (1979) diagnosed the three-di- mensional flow fields associated with lake breeze circulations in the Chicago area. They were able to demonstrate the poten- tial for return, via lake breeze circulation, of pollutants transported over the lake. Vertical circulations such as those associ- ated with a lake or sea breeze will generally

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Perry I. Samson 89 not be diagnosed by static spatial interpo lation techniques. The development of hy drodynamic models has aided the under standing of complex three-dimensional wind fields over urban areas. Many transport and dispersion models over urban areas ultimately rely on some estimate of the mixing height (the height to which the atmosphere is uniformly mixed). Holzworth (1964) defined the mixing; height as the intersection of two tempera ture profiles: the observed temperature profile and a profile constructed from the observed maximum surface temperature and adiabatic lapse rate (the theoretical rate at which temperature decreases with height in the absence of any heat input). The method has been tested extensively, using visual observations of clouds, analyses of data collected with acoustic sounders, and comparisons with temperature measure ments made through well-mixed layers. In many cases all methods give similar results, but other studies have shown that this method overestimates the overall mixing height by about 50 percent (Pendergast 1974; Schubert 1976~. The estimation of morning mixing heights, presumably important during the morning rush hour, has also been highly generalized. Holzworth (1967) assumed that the urban morning mixing height could be approximated from the intersec tion of the morning temperature profile and a profile constructed from the observed morning minimum temperature plus some constant value and the adiabatic lapse rate. Although useful for assessment of the gen eral air pollution potential for an urban area, this morning mixing height may be of limited value for diagnosing specific pollu . . tlon ep1soc es. The mixing height is considered useful for evaluating the pollutant potential of an area, but its use in problems related to vehicular emissions has been limited. Aron (1983) showed that variations in mixing height were inconsistent in explaining day to-day variations in 0~ and CC) in several . in. urban areas. 1 he concentrations ot (my were not consistently related to the morn ing mixing height, possibly because there was insufficient time for the pollutant to mix to the mixing height, and possiblywhich are emitted principally from elevated because of the unreliability of the method for calculating the morning mixing height. The concentrations of O3 were not related to the maximum mixing height, possibly because of the dominance of other factors such as solar intensity and upwind pollut- ant concentrations. In summary, diagnosing the airflow over an urban area remains a challenge. With only a couple of exceptions (for example, Los Angeles), most cities have inadequate networks of meteorological stations for di- agnosing wind flow. Although hydrody- namic models hold promise for interpret- ing transport, they still require adequate initial and boundary conditions for reliable calculations. The data needed to estimate mixing heights are also generally lacking for most cities. However, better mixing height data may still not yield a useful measure of dispersion potential for vehicu 1 tar emlsslons. Recommendation 5. As noted earlier, few measurements have been made of the transport and dispersion of air from an urban area. There are several important reasons why this is true and will probably remain true for some time: (a) the logistics of surface measurements of tracers can be very difficult in an urban setting; (b) the possibility of aircraft measurement can be severely limited by airspace restrictions; and (c) the measured concentrations can be influenced by local air circulations caused by the physical setting. This research could be significantly aided by the development of automated, remote-sensing, wind-pro- filing instruments. The technology for re- mote sensing of wind fields is currently being developed for measurement of winds above about 2 km from the earth's surface, but development of a sensor for lower levels is still in its infancy. Therefore it is recommended that research into the devel- opment of methods for sensing of near- surface winds remotely be conducted. Regional-Scale Transport Modeling of regional-scale pollutant trans- port (2~2, 000 km) has so far focused main- lv on the transport of sulfur oxides (SO i.

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9o Atmospheric Transport and Dispersion of Air Pollutants point sources (such as smokestacks) rather than vehicles. In this discussion the trans- port and dispersion of pollutants from ele- vated point sources is presented because debate continues on the relative residence time of pollutants released at the surface versus those released from an elevated stack. The relative contribution of elevated point-source emissions versus surface-based emissions could be simulated using a numer- ical or Gaussian solution to estimate ground concentrations from each type of source. The rate of dry deposition can be approximated by using the boundary condition -(w X )O = VdX (7) where the turbulent flux of pollutant to the surface, _ (~Ti7)o, is proportional to the mean surface concentration. The propor- tionality is called the deposition velocity and varies considerably depending on the type of pollutant (gas or particle), its sol- ubility, and the ambient atmospheric sta- bility, among other influences (Sehmel 1984). Observations of deposition velocities for NO, NO2, and hydrocarbons have shown considerable variability. Much of the vari- ability in deposition velocities may be re- lated to variability in meteorological con- ditions. The description of dry deposition has often been addressed in a manner sim- ilar to an electrical resistance series (Wesley and Hicks 1977; Fowler 1978). The depo- sition velocity (hi) is assumed to be in- versely proportional to the sum of three resistance terms V,~= (ta + rb + rS) (8) where ra is the aerodynamic resistance to pollutant transport through the lowest at- mospheric layer, rb is determined by the rate of molecular and diffusive transport processes over a surface, and rS is any additional resistance encountered at the sur- face itself. Various methods have been proposed for evaluating each of these resistance terms, but few data have been compiled with which to generalize deposition rates for vehicle-related pollutants over a variety of surfaces and meteorological conditions. For HNO3 the surface resistance is thought to be near zero (Huebert and Robert 1985), but other pollutants may have significant values of rS and those may vary signifi- cantly with surface type and conditions. Methods for estimating ra and rb are de- scribed by Hicks and Liss (1976). The diagnosis of regional-scale transport of vehicle-related pollutants also suffers from the lack of information about the three-dimensional wind fields in the lower troposphere. Horizontal wind measure- ments are conducted routinely by the Na- tional Weather Service (NWS) rawinsonde network, but these may not be adequate for diagnosing pollutant transport or for pa- rameterizing vertical mixing. These mea- surements have a spatial and temporal res- olution of about 400 km and 12 hr. respectively. The NWS rawinsonde net- work, although capable of resolving fea- tures with length scales of about 1,000 km, is too coarse to identify accelerations in the wind field associated with frontal passages and diurnal phenomena such as the low- level nocturnal jet a layer of high-speed winds occurring at night at an altitude of approximately 30(}700 m. It is most com- mon over the Great Plains and the Midwest (Bonner 1968) during the summer months and is characterized by generally southerly flow. It has been speculated (Lyons and Cole 1976; Smith et al. 1978) that this jet could transport pollutants rapidly north- ward during the night. Thus the use of current 12-hr upper-air data may produce . ~ . . . slgn1tlcant atlases In atmospheric transport calculations. Models that utilize the hydrodynamic equations of motion are capable of resolv- ing smaller-scale features (Anthes and War- ner 1978), but the computational expense of using these models is often prohibitive for long-term pollution studies. Smaller- scale wind fields may also be obtained by any number of objective analytical tech- niques (Goodin et al. 1979; Haagenson 1982). Objective analysis offers a less ex- pensive solution to the problem of inade- quate data resolution, but the errors in- volved in spatial and temporal interpolation may distort the "true" meteorological rep- resentation. Unfortunately, few high-reso

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Perry I. Samson 91 lution upper-air wind data are available to 107 _ test the reliability of interpolation tech niques. Kuo et al. (1985) quantified the effects of low-resolution meteorological data on trans- port calculations. They conducted several "observing system simulation experi- ments" in which trajectories were com- puted using meteorological information derived from a hydrodynamic model. The model output, considered to represent the "true" state of the atmosphere, was sys- tematically degraded to simulate the effects of low-resolution rawinsonde measure- ments. Isentropic trajectory calculations based on the degraded output suggest that, after 72 hr of travel, horizontal displace- ment errors greater than 400 km may re- sult. Vertical displacement errors were also shown to increase with decreasing data resolution. The results indicate that increas- ing the temporal resolution of rawinsonde measurements improves the accuracy of transport calculations to a greater extent than increasing the spatial resolution. The quantitative estimates of trajectory errors provided by Kuo et al. (1985) were based on the analysis of a single weather system. Long-term air pollution studies such as those required for the estimation of source-receptor relationships for acid pre- cipitation require analysis of a wide range of meteorological situations. Verification of these results over a larger sample of meteorological conditions is difficult due to the lack of high-resolution wind measure- ments. The Cross Appalachian Tracer Experi- ment (CAPTEX), conducted in the north- eastern United States and eastern Canada during September and October 1983, re- duces this deficiency (Ferber 1984~. The CAPTEX data base contains fine-scale me- teorological measurements (both spatial and temporal) and offers an excellent op- portunity for analyzing the errors in trans- port calculation resulting from spatial and temporal interpolation of low-resolution wind data. Kahl and Samson (1986) evalu- ated several spatial and temporal interpola- tion techniques against the high-resolution measurements available from CAPTEX. They concluded that an increase in spatial ~ 1o6 ID <~ 1 o5 z In G en 1 04 ~ _ / _ a/' MAX ' OCR for page 77
92 Atmospheric Transport and Dispersion of Air Pollutants (~x) and crosswind toys dispersion parame- ters derived from Taylor (1982) without (dashed line) and with (solid line) turbulence diffusion. This graph illustrates that the ef- fects of wind shear generally dominate the dispersion produced by ambient turbulence after a few hours of travel time. Calculations made by Draxler and Taylor (1982) suggest that the rate of horizontal dispersion of a "puff" of tracer over regional scales is roughly proportional to the wind speed. Draxler and Taylor also conclude that for a given wind speed the rate of growth of a pollutant puffis proportional to travel time, consistent with the empirical rate suggested by Heffter (1965~. In summary, the study of transport and dispersion of vehicle-related pollutants over regional scales suffers from many of the same uncertainties outlined for urban transport. Although the present observa- tional networks are thought to be inade- quate, there is still debate over how to most efficiently increase the resolution. The rates of dry deposition of vehicle-related pollut- ants are not well known and need to be quantified if the relative contributions of surface-based vehicular emissions and ele- vated emissions are to be estimated. Recommendation 6. In view of the possible need to develop efficient strategies for reducing tropospheric O3 and acidic deposition, the relative contribution of ur- ban, ground-level emissions versus ele- vated point-source emissions should be as- sessed. The first step should be a feasibility study using transport, dispersion, and dep- osition modeling. If this study suggests that the difference in potential impact is rela- tively large, then a second stage should consist of a dual tracer field experiment to track pollutants over a period of 12 to 24 hr. This experiment would demonstrate the sensitivity of transport to height of release and quantify ground-level concen- trations from the two source heights for use in estimating rates of dry deposition. Recommendation 7. Research on the transport of pollutants over regional scales should focus on defining the most efficient method for augmenting the current NWS rawinsonde measurement network. It is not now clear whether, on the scale of eastern North America, it would be more advantageous to measure the winds at the existing network sites at a higher frequency or to select additional sites for measure- ments at the standard frequency. With the development of remote-sensing technology for the measurement of winds, it is essential that the needs of the transport and disper- sion researchers be considered in the de- ployment of the newer equipment. Some recent research has begun to explore this issue, but more work is needed to optimize the information gained from system aug- mentation. This research should encompass numerical studies of hypothetical atmo- spheric situations and analysis of data from previous network augmentation programs. Summary The level of human exposure to vehicular pollutants depends upon the emission rate of the pollutant from the vehicle, the direc- tion of transport, the rate of dispersion, and the location of the population relative to the ensemble of sources. During the past dec- ade, the complexities of the transport and dispersion of air pollutants associated with vehicular emissions have been made more evident through elaborate field and model- ing experiments. The exposure of humans to vehicular exhaust is considered in terms of three scales of distance: near field (0.0-0.2 km), urban (0. 2-20 km), and regional (20-2, 000 km). The direct exposure of humans to vehicular emissions in the near-field envi- ronment has been the focus of most of the research. It is known that the concentra- tions of pollutants associated with moving vehicles are determined by several factors, including their emission rate from the ve- hicle, mixing induced by vehicle motion, wind speed and direction relative to axis of the highway, intensity of ambient atmo- spheric turbulence, reactions to or from other chemical species, and the rate of removal to the surface (deposition). l he concentrations of pollutants that would be expected in the absence of mov- ing vehicles are determined by emissions

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Perry I. Samson 93 rates and the complex wind flow and tur- bulence produced by the interaction of the local wind with complex structures (for example, buildings, sound barriers, other vehicles). Weather plays a role in most of these components, generally causing higher emission rates at lower temperatures, dilut- ing pollutants at higher wind speeds, mix- ing pollutants vertically during unstable thermal conditions, and influencing the rates of homogeneous and heterogeneous chemical reactions and the rate of scaveng- ing of pollutants from the atmosphere by . . . . . preap1tat1on anc c try c .epos1t1on. Apart from the natural transport and dis- persion processes, moving vehicles exhibit a considerable mixing potential that influences pollutant concentrations within about 100 m of a highway. The aerodynamic drag of a moving vehicle causes a turbulent wake in which pollutants initially mix. This mixing is influenced by the shape and speed of the vehicle. It is recommended that new studies of the effects of vehicular turbulence on pol- lutant concentrations be initiated. Simulating the transport of pollutants within street canyons and parking struc- tures is very difficult and virtually impos- sible to extrapolate to other sites or times. The flow of air in street canyons is neither steady nor homogeneous, and represent- ative wind flow measurements are difficult to obtain. It is suggested that additional effort be put into developing artificial tracer systems that can easily be deployed in a variety of complex situations. Exposures due to urban-scale transport and dispersion of direct emissions and their chemical products are less understood than are the near-field exposures. Urban area air pollution problems still exist, but the inci- dence of elevated concentrations of primary pollutants has been declining. Nonetheless, concentrations of O3 that exceed the Na- tional Ambient Air Quality Standards still exist and require special consideration. Iden- tifying transport and dispersion in urban ar- eas is often very difficult, if not impossible, because of the lack of relevant measurements of wind flow above the surface. Future re- search should focus on better methods for determining the flow fields over urban areas. The estimation of the contribution of vehicular emissions to regional-scale air . . . . . . anc . precipitation contamination IS even more challenging than that encountered on an urban scale. It is generally believed that pollutants transported over long distances influence precipitation quality in nonurban areas. An assessment of the vehicle-induced NOx contributions requires an estimation of the amount of dry deposition to the surface near the source. The rate of dry deposition of pollutants depends upon the rate of pollutant mixing to a surface, as well as the type and condition of the surface. Faster deposition will result in more depo . . . . . . . . . sltlon in the vicinity o t le emission anc ., consequently, fewer pollutants will be transported longer distances. Future studies should be aimed at understanding the rates of dry deposition of vehicle-related emis- sions and defining the transport and disper- sion of pollutants over long distances. Summary of Research Recommendations Given the state of knowledge outlined in this chapter, the following studies have the highest likelihood of yielding useful new data relevant to human exposure to vehicle-related emissions. Given limited re- sources, these topics should be considered in the following order. HIGH PRIORITY Recommendation 1 Determine, by physical modeling, the role of vehicular turbu Open-Highway fence in the initial dispersion of pollutants. This research should Exposure focus on defining the factors influencing concentration fluctuations near and over the highway.

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94 Atmospheric Transport and Dispersion of Air Pollutants Recommendlation 3 Define the transport and dispersion of pollutants in street can Transport and yons through the use of chemical tracers. Ensure that many sites be Dispersion in Street investigated with widely varying building configurations and the Canyons observations be conducted over sufficient time to include many different meteorological conditions. MODERATE PRIORITY Recommendation 2 Buoyant Plume Assess the importance of plume buoyancy on near-highway and street-canyon pollutant concentrations. Recommendation 4 Physical Modeling Develop physical models to simulate a variety of complex settings and atmospheric conditions. Recommendlation 6 Regional-Scale Transport and Dispersion Assess the relative contribution of urban, ground-level emissions versus elevated point-source emissions to overall regional-scale pollutant levels. A dual tracer release conducted over a range of atmospheric conditions would have a high likelihood for success. LOW PRIORITY Recommendation 5 Urban-Scale Transport Develop an automated, remote-sensing wind-profiling system for use in defining wind flow within an urban atmosphere. Recommendlation 7 Regional-Scale Transport Define the most efficient method for augmenting the existing NWS rawinsonde measurement network to satisfy the data needs of regional-scale air pollution transport models. References Anderson, G. E. 1971. Mesoscale influences on wind fields,J. Appl. Meteorol. 10:377-386. Anderson, G. E. 1973. A Mesoscale Windfield Anal- ysis of the Los Angeles Basin, EPA-650/4-73-001, U.S. Environmental Protection Agency, Washing- ton, D.C. 56 pp. Angell, J. K., Dickson, C. R., and Hoecker, W. H. 1975. Relative diffusion within the Los Angeles basin as estimated by tetroon triads, J. Appl. Meteo- rol. 14:149~1498. Anthes, R. A., and Warner, T. T. 1978. Development of hydrodynamic models suitable for air pollution and other mesometeorological studies, Mon. Weather Rev. 106:1045-1078. Aron, R. 1983. Mixing height an inconsistent indi Correspondence should be addressed to Perry J. Sam- son, Department of Atmospheric and Oceanic Sci- ence, University of Michigan, Ann Arbor, MI 48109- 2143. cator of potential air pollution concentrations, Atmos. Environ. 17:219~2197. Benesh, F. 1978. Carbon Monoxide Hot Spot Guide- lines, Vol. 5: User's Manual for Intersection-Mid- block Model, EPA-450/3-78-037, U. S. Environ- mental Protection Agency, Washington, D.C. Benson, P. E. 1979. CALINE~A Versatile Disper- sion Model for Predicting Air Pollutant Levels Near Highways and Arterial Streets, FHWA/CA/TL- 79/23, NTIS:PB 220842, November 1979, 129 pp. Benson, P. E. 1982. Modifications to the Gaussian vertical dispersion parameter, at=, near roadways, Atmos. Environ. 16:1399-1405. Bonner, W. D. 1968. Climatology of the low-level jet, Mon. Weather Rev. 96:83~850. Bornstein, R. D. 1975. The two-dimensional URB- MET urban boundary layer model, J. Appl. Meteo- rol. 14:1459-1477. Bowling, S. A. 1984. Meteorological Factors Respon- sible for High CO Levels in Alaskan Cities. U.S. Environmental Protection Agency, Environmental Research Laboratory, Corvallis, Ore. Brice, R. M., and Roesler, J. F. 1966. The exposure to

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Perry I. Samson carbon monoxide of occupants of vehicles moving in heavy traffic, J. Air Pollut. Contr. 16:597-604. Briggs, G. A. 1975. Plume rise predictions, In: Lec- tures on Air Pollution and Environmental Impact Anal- ysis (D. A. Haugen, ed.), pp. 59-111, American Meteorological Society, Boston, Mass. Bullin, J. A., and Maldonado, C. 1977. Modeling carbon monoxide dispersion from roadways, Envi- ron. Sci. Technol. 11:1071-1076. Cadle, S. H., Chock, D. P., Heuss, J. M., and Monson, P. R. 1976. Results of the General Motors Sulfate Dispersion Experiments, General Motors Res. Publ. GMT-2107, Warren, Mich. 140 pp. Cadle, S. H., Chock, D. P., Monson, P. R., and Heuss, J. M. 1977. General Motors sulfate disper- sion experiment: experimental procedures and re- sults, ]. Air Pollut. Contr. 27:33-38. Calder, K. L. 1973. On estimating air pollution con- centrations from a highway in an oblique wind, Atmos. Environ. 7:863-868. Chang, T. Y., and Norbeck, J. M. 1983a. 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