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OCR for page 77
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
OCR for page 78
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
OCR for page 79
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
OCR for page 80
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
OCR for page 81
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
OCR for page 82
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.)
OCR for page 83
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
OCR for page 84
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).
OCR for page 85
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.
OCR for page 86
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
~.
OCR for page 87
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
OCR for page 88
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
OCR for page 89
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.
OCR for page 90
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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Representative terms from entire chapter:
street canyons
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
'
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
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.
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.
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