Draft
Do Not Quote or Cite
External Review Draft No. 2
February 1981
Air Quality Criteria
for Particulate Matter
and Sulfur Oxides —
Chapter 6: Atmospheric Transport,
Transformation, and Deposition
[Chapter 6 Was Inadvertently Omitted from the Volume III Printing
NOTICE
This document is a preliminary draft. It has not been formally released by EPA and should not at this stage be
construed to represent Agency policy. It is being circulated for comment on its technical accuracy and
policy implications.
Environmental Criteria and Assessment Office
Office of Health and Environmental Assessment
Office of Research and Development
U.S. Environmental Protection Agency
Research Triangle Park, N.C. 27711
-------
NOTE TO READER
The Environmental Protection Agency is revising the existing criteria
documents for participate matter and sulfur oxides (PM/SOX) under Sections 108
and 109 of the Clean Air Act, 42 U.S.C. §§ 7408, 7409. The first external
review draft of a revised combined PM/SO criteria document was made available
for public comment in April 1980.
The Environmental Criteria and Assessment Office (ECAO) filled more than
4,000 public requests for copies of the first external review draft. Because
all those who received copies of the first draft from ECAO will be sent copies
of the second external review draft, there is no need to resubmit a request.
To facilitate public review, the second external review draft will be
released in five volumes on a staggered schedule as the volumes are completed.
Volume I (containing Chapter 1), Volume II (containing Chapters 2, 3, 4, and 5),
Volume III (containing Chapters 6, 7, and 8), Volume IV (containing Chapters 9
and 10), and Volume V (containing Chapters 11, 12, 13, and 14) will be released
during January-February, 1981. As noted earlier, they will be released as
volumes are completed, not in numerical order by volume.
The first external review draft was announced in the Federal Register of
April 11, 1980 (45 FR 24913). ECAO received and reviewed 89 comments from the
public, many of which were quite extensive. The Clean Air Scientific Advisory
Committee (CASAC) of the Science Advisory Board also provided advice and
comments on the first external review draft at a public meeting of August 20-22,
1980 (45 FR 51644, August 4, 1980).
As with the first external review draft, the second external review draft
will be submitted to CASAC for its advice and comments. ECAO is also soliciting
written comments from the public on the second external review draft and
requests that an original and three copies of all comments be submitted to:
Project Officer for PM/SOX, Environmental Criteria and Assessment Office, MD-52,
U.S. Environmental Protection Agency, Research Triangle Park, N. C. 27711. To
facilitate ECAO's consideration of comments on this lengthy and complex docu-
ment, commentators with extensive comments should index the major points which
they intend ECAO to address, by providing a list of the major points and a
cross-reference to the pages in the document. Comments should be submitted
during the forthcoming comment period, which will be announced in the Federal
Register once all volumes of the second external review draft are available.
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6. ATMOSPHERIC TRANSPORT, TRANSFORMATION, AND DEPOSITION
6.1 INTRODUCTION
Preceding chapters of this criteria document discussed the physical and chemical properi-
ties of sulfur oxides and particulate matter (Chapter 2); their sources and emissions (Chapter
4) and measurements of their ambient levels in urban and rural environments. (Chapter 5).
These chapters in part, addressed material which is relevant to portions of the subject matter
to follow. Whenever possible reference to detailed resource material in previous chapters
is made so long as clarity of presentation is preserved.
The purpose of this chapter is to review our present knowledge of the physical and
chemical processes contributory to the transport, transformation and deposition of particulate
matter and sulfur oxides in the atmosphere and to discuss the theoretical approaches for
integrating these processes with source emission contributions through the use of mathematical
models. Such integrating approaches provide a vehicle for improved understanding and concept-
ualization of the complex processes operative in polluted atmospheres, and through these
source receptor relationships provide a means to a sound, creditable scientific basis for
determining the nature and extent of emission control required to meet specified ambient air
quality levels.
The concentration of a pollutant species at some fixed point in time and space after
being emitted from a source at a given distance away is dependent upon four fundamental
factors. These factors are as follows: 1) emission—the rate of pollutant emitted and the
configuration of its source; 2) transformation—the chemical and physical reaction processes
which convert one pollutant species to another; 3) transport and diffusion—the movement and
dilution of a pollutant species through time and space as a result of various meteorological
variables; and 4) deposition—the removal of a pollutant species through their interaction
with land and water surfaces (dry deposition) and through interaction with precipitation or
cloud condensation nuclei (wet deposition).
The principal pathway processes of airborne pollutants are schematically illustrated in
Figure 6-1. Ideally each of these processes should be treated explicitly in the air quality
simulation model, but this is typically not the case. In this chapter three of the factors,
transformation, transport and diffusion, and deposition are discussed in detail as they
constitute major theoretical components of the air quality simulation model. Emissions, which
can be viewed more as a model input, are discussed only in the context of their relevancy to
air quality simulation modeling in the final section.
It should be noted, that the modeling approaches discussed within this chapter consider
explicit treatments of the dynamic physical and chemical processes operative in the atmosphere
to simulate the relationship between pollutant emission and ambient air quality. More implic-
it statistical-empirical approaches, which deduce source contribution through analysis of
6-1
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FREETROPOSPHERIC
EXCHANGE
VERTICAL
DIFFUSION
AEROSOL
CONDENSATION
COAGULATION
CHEMICAL REACTIONS
ABSORPTION IN
CLOUD ELEMENTS
SEDIMENTATION
AS AEROSOL
DRY DEPOSITION ON
THE GROUND
cnMD?cc ANTHROPOGENIC ^
bUUHLtb cnnorcc <«,>
,'//'/ ',/,»",'""/'/
il i i '/// III It I 11 11 Hi I
ii i
ABSORPTION IN
PRECIPITATION
WASHOUT IN PRECIPITATION
Figure 6-1. Pathway processes of airborne pollutants.
Source: Adapted from Drake and Barrager(1979).
6-2
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empirical information only, are not within the purview of this chapter. One specific techni-
que, chemical factor analysis, has shown considerable promise in developing source-receptor
relationships for particulate matter and is discussed in Chapter 5.
6.2 CHEMICAL TRANSFORMATION PROCESSES
A detailed discussion of the chemistry of S02 and that of other gases reacting to form
particulate matter in the atmosphere has been presented in Chapter 2. Section 6.2.1 provides
a brief summary of the results on the atmospheric chemical transformation processes of S02
and particulate matter presented in Chapter 2. Section 6.2.2 reviews the status of field
measurements on the rate of SOj oxidation in industrial and urban plumes; and their contri-
bution to elucidating the transformation pathway processes of S02 oxidation.
6.2.1 Chemical Transformation of S02 and Particulate Matter
Present understanding of the homogeneous gas phase reactions of S02 indicates that the
rate of S02 oxidation in the atmosphere is dominated by free radical reaction processes.
The free radical species identified as important contributors to the S02 oxidation process
are hydroxyl (HO), hydroperoxy (H02), methylperoxy (CH302) and other organic peroxy species
(R02, R'02, etc.). The concentration of these radicals in the atmosphere are dependent on
many factors, the more important of which are the concentration of volatile organic compounds
and nitrogen oxides (NO and N02) in the atmosphere, temperature and solar intensity. Theo-
retical estimates have shown that maximum S02 oxidation rates of 4.0% h~l are possible in
polluted atmospheres. But, recent experimental rate constant determinations for the H02 and
CH302 reactions with S02 indicate that these processes may not be as important as previously
thought and that the maximum possible homogeneous S02 oxidation rate under optimum atmospher-
ic conditions may only be of the order of 1.5% h~l. This rate is a result of S02 reaction
with hydroxyl radical only.
Present knowledge of heterogeneous pathways to S02 oxidation in the atmosphere indic-
ates that the liquid phase catalyzed oxidation of S02 by Mn ion and carbon are potentially
important processes. Theoretical estimates of atmospheric S02 oxidation rates via these
processes are of the order of 10% h~l. Unfortunately, a great deal of uncertainty surrounds
the actual availability of these catalyzing substances in ambient fine particulate matter.
The quantitative determination of rates of S02 oxidation via these processes has never been
demonstrated under actual atmospheric conditions.
Organic and nitrate particulate matter forming processes are presently thought to be
dominated by homogeneous gas phase reactions. In the case of atmospheric nitrates, a particu-
larly significant production pathway is through reaction between hydroxyl free radical and
nitrogen dioxide resulting in nitric acid (HON03) formation. The fate of nitric acid in the
atmosphere is not well understood, though a portion of gaseous nitric acid is known to enter
into an equilibrium with ammonia (NH3) to form particulate ammonium nitrate (NH4N03). Info-
rmation on the production rates and mechanistic details of organic particulate matter is
6-3
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very limited. The product information which is available indicates that oxidation reactions,
involving the interaction of ozone, nitrogen oxides and hydroxyl free radicals with higher
molecular weight organics represents a major pathway to organic particulate matter production.
6.2.2 Field Measurements on the Rate of S02 Oxidation
The majority of S02 oxidation studies in the atmosphere have been only carried out in
recent years and of those, most have involved power plant plumes. One reason for the late
start in this research area has been the lack of adequate measurement technology for particu-
late sulfur, but recent developments Huntzicker et al. (1978), Cobourn et al. (1978) seem to
have alleviated this problem. A summary of S02 oxidation rates based on field measurements
in power plant, smelter and urban plume studies carried out from 1975 to the present is given
in Table 6-1. The rates of S02 oxidation in industrial plant plumes consistently range from
0 to 10%/h, with urban plumes showing only a slightly greater maximum rate of 13%/h. The
pre-1975 studies', Gartrell et al. (1963), Dennis et al. (1969), Weber (1970) and Stephens and
McCalden (1971), which observed conversion rates an order magnitude larger than more recent
observations, must be considered suspect due to possible artifact formations in the sulfate
analysis technique and limitations in the analytical methods in general.
Newman (1980) recently reviewed the majority of the power plant and smelter plume studies
presented in Table 6-1 and arrived at the following conclusions.
1) The diurnal average oxidation rate of sulfur dioxide to sulfate is probably less than
1% per hour.
2) Little or no oxidation of sulfur dioxide occurs from early evening through to early
morning.
3) Maximum oxidation rates of sulfur dioxide to sulfur of 3% per hour can occur under
midday conditions.
4) The contribution of homogeneous and heteorogeneous mechanisms to sulfur dioxide
oxidation in plumes cannot be elucidated from the present studies.
It should be noted that the reported S02 oxidation rates are estimates based on analyses
of measured physical and chemical parameters and in many instances have incorporated within
them certain simplifying assumptions which are not totally substantiated. Typical uncertain-
ties in reported values are 50%, but may be greater if inappropriate assumptions have been
used. Even with these uncertainties in mind, the overall consistency in the observed range
of S02 oxidation rates is gratifying.
6.3 PHYSICAL REMOVAL PROCESSES
The removal of particulate matter and gases from the atmosphere occurs predominantly via
two physical processes. These are dry deposition, the removal of chemical species from the
atmosphere at the air surface interface, and precipitation scavenging, the removal of chemical
species from the atmosphere by interaction with various types of precipitation such as rain,
snow, etc. These processes prove to have both a positive and negative impact with respect to
6-4
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TABLE 6-1. FIELD MEASUREMENTS ON THE RATES OF S02 OXIDATION IN PLUMES*
Plume Type
Location
S02 Oxidation
Rate (%h-l)
Method
Reference
Keystone
(Pennsylvania)
Labadie
(Missouri)
Four Corners
(New Mexico)
Labadie and
Portage des Sioux
(Missouri)
Muscle Shoals
(Alabama)
Kyger Creek
(Ohio)
Labadie
(Missouri)
Four Corners
(New Mexico)
Labadie
(Missouri)
Cumberland
(Tennessee)
Great Canadian
Oil Sands
(Alberta, Canada)
Keystone
(Pennsylvania)
Centralia
(Washington)
Four Corners
(New Mexico)
Four Corners
(New Mexico)
0-10
0.41-4.9
0.27-0.84
0-5
0-3
2-8
0-4
0-7
0-3
0-5
0-6
0.15-0.5
32S/34S ratio, change with
oxidation
Total change in particle
volume
Sub-micron sulfate and
- change of ratio with time
Newman et al. (1975)
Cantrell and Whitby (1978)
Ursenbach et al. (1977)
Particulate sulfur to total
sulfur ratio
Particulate sulfur to total
sulfur ratio
CCN production (CCN to S02
ratios)
Particulate sulfur to total
sulfur ratio
Particulate sulfur to total
sulfur ratio
Particulate sulfur to total
Particulate sulfur to
total sulfur ratio
Total change in particle
vo 1 ume
CCN production (CNN to S02
ratios)
Forrest and Newman (1977)
Gillani et al. (1978)
Pueschel and Van Valin (1978)
Husar et al (1978)
Meagher et al. (1978)
Lusis et al. (1978)
Dittenhoefer and dePena (1978)
Hobbs et al. (1979)
Mamane and Pueschel (1980)
6-5
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TABLE 6-1 (Continued).
Plume Type
SO? Oxidation
Method
Reference
Leland-Olds
(North Dakota)
Sherburne County
Minnesota
Big Brown
(Texas)
0-5.7 Total change in particle
volume
Hegg and Hobbs (1980)
Smelter
INCO Nickel 0-7
(Copper Cliff
Canada)
INCO Nickel 1.2-5.2
(Copper Cliff,
Canada)
Mt Isa Mines
(MTISA, Australia) 0.25*
Urban
Particulate sulfur to total
sulfur rates
Particulate sulfur to total
sulfur rates
Particulate sulfur to
lead ratio
Lusis and Wiebe (1976)
Forrest and Newman (1977)
Roberts and Williams (1979)
Los Angeles
Cal ifornia
St
St
. Louis
Missouri
. Louis
Missouri
1.2-13 Particulate sulfur to
total sulfur ratio
7-12.5 Particulate sulfur to
total sulfur ratio
3.6-4.2 Particulate sulfur to
total sulfur ratio
Roberts and Friedlander (1975)
Alkezweeny and Powell (1977)
Chang (1979)
*Adapted in part from Hegg and Hobbs (1980)
fdiurnal average rate
6-6
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environmental air pollution issues. On the one hand, they constitute the major mechanisms by
which the polluted atmosphere cleanses itself, lowering ambient air concentrations of pollutant
species and thereby reducing health related risks, but on the other hand the deposited pollu-
tant materials may introduce increased risks to our terrestrial and aquatic ecosystems.
Since wet and dry removal processes significantly affect the lifetime of SO? and particu-
late matter in the atmosphere and thereby affect the distance traveled and concentration of
these species, understanding these processes is essential if proper assessment of their envi-
ronmental significance is to result. The removal of pollutant species by dew fall has not
been studied and remains for future research to determine if this process is an important
removal mechanisms for atmospheric contaminants.
In the sections to follow, discussion on dry deposition and precipitation scavenging are
presented with emphasis on experimental data bases and theoretical treatment.
6.3.1 Dry Deposition
Extensive surveys in the area of particle and gas dry deposition have been performed over
the years, several recent examples are reviews by Sehmel (1980), McMahon and Denison (1979),
Chamberlain (1980) and Garland (1978). The dry deposition of sulfur dioxide and particulate
matter, as with other atmospheric species is governed by three major components: meteorologi-
cal variables, properties of the depositing pollutant and surface variables. These components
are influenced by specific parameters which interact in complex ways that in many instances are
not completely understood.
The most important meteorological processes affecting dry deposition are transport related
phenomena. These transport processes are governed by the wind and temperature profiles, by
eddy diffusion and by sedimentation across the boundary layer to the canopy. They are strongly
influenced by two meteorological parameters, the friction velocity, u* and the aerodynamic
surface roughness, z0. Both of these parameters are used to describe the wind speed profile
above a given surface under given conditions of atmospheric stability. Typically these two
variables are determined empirically by fitting wind speed data as a function of height. The
strong diurnal dependence of dry deposition is linked to the formation of a stable layer of air
at the earth's surface at night (nocturnal inversion) which affectively inhibits the vertical
transport of pollutant species to the canopy surface. The formation of the nocturnal inversion
and its affect on other atmospheric processes is discussed in the section on transport and
diffusion.
Important properties influencing the dry deposition of a pollutant are its solubility in
water and for particulate matter, specifically, its size distribution density, morphology and
composition. Important properties of the surface include: 1) the moisture content of the
surface which in conjunction with the solubility of the pollutant species will govern the
overall sticking efficiency of the deposited material; and 2) the physiological state of the
6-7
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vegetation surface, most importantly the the opening and closing of stomata pores, where the
rate of pollutant uptake is thought to be strongly governed.
Chamberlain and Chadwick (1953) introduced a convenient way to express the rate of dry
deposition of both gases and particles in the form of a velocity term. Dry deposition veloc-
ity, defined as the downward flux F of the species, divided by its ambient concentration x at
some specified height (typically 1-2 meters above the surface), is the standard form in which
all measured deposition rates are reported. Dry deposition velocities are typically reported
in units of cm s~l. p
vd = —
x
Dry deposition velocity is positive by convention and therefore requires a minus sign on
F, the downward flux which is defined as negative.
Measurement techniques for the dry deposition of pollutant species have been recently
reviewed and critiqued by Hicks et al. (1980). In this work measurement methods were sorted
into three major categories: 1) estimates of accumulation, 2) flux monitoring, and 3) flux
parameterization.
Though none of the experimental techniques developed to date has proven to be a panacea in
dry deposition measurements, a consensus of opinion on the overall accuracy of the methods and
their suitability for specific applications has generally been reached. Based on Hicks et al.
(1980) the three categories are described briefly with general comments on their limitation.
Estimates of accumulation maybe considered using atmospheric radioactivity or mass
balance methods. Radioactive techniques compare ambient concentration of selected radioactive
species with concentrations in water bodies vegetation, etc. to evaluate the rate of input of
the material into the ecosystem over long term periods. The technique is typically limited to
small particle uptake of long lived species and has difficulty distinquishing between dry and
wet removal and resolving short term variations. Mass balance studies attempt to measure the
various inflow and outflow processes in the ecosystem, with the exception of the dry deposi-
tion, which is then determined through a budget calculation. The major limitation of the
method is that the dry deposition is inferred by indirect measurements which in themselves are
difficult to measure accurately.
Flux monitoring considers the direct measurements of total deposition over a well defined
surface for set periods of time. Several types of deposition surfaces have been used with this
general category including: open pots, flat filters, flat plates and shallow pans, fiber
filters and sticky films. Overall, the methods are limited due to their lack of standardiza-
tion, unrepresentativeness of natural surfaces and potential for contamination by locally
resuspended particles.
Flux parameterization includes a variety of methods, one of which, eddy correlation has
shown significant promise as a measurement standard for the dry deposition of gases. The
6-8
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technique requires the simultaneous measurement of the concentration of pollutant species and
the vertical component of the wind velocity at a sufficiently fast enough rate to determine the
turbulent flux of the pollutant concentration. A significant limitation of the technique is
the lack of adequate fast-response instrumentation for many of the pollutant species of inter-
est. In addition, particle flux due to gravitational settling is not detected and can produce
invalid results if significant particle resuspension is occurring. Also considered under the
flux parameterization category are laboratory methods including chamber and wind tunnel stud-
ies. In these controlled experimental studies, plants, leaves, or simulated canopy surfaces,
etc. are exposed to known amounts of pollutant concentration. Measurements in the change in
concentration, which can be accomplished by a variety of methods, is then used to determine
pollutant uptake.
6.3.1.1 Sulfur Dioxide Dry Deposition—The dry deposition of SO? to grass, crops, forests,
soil and building surfaces has been reviewed in recent years by Sehmel (1980), McMahon and
Denison (1979) Chamberlain (1980) and Garland (1978). Compilations of dry deposition labora-
tory and field measurements of SOj have been presented in McMahon and Denison (1979). A
review of these results indicates measured dry deposition velocities ranging from 0.04 to 3.7
cm-sec"l, but with the majority residing in the range 0.3 to 1.6 cm-sec'l. The apparently
wide range of dry deposition values is not particularly disconcerting when the variety of
surfaces, meteorological conditions, and experimental methods is taken into consideration.
A summary of the average dry deposition velocity by surface type is presented in Table
6-2.
TABLE 6-2. AVERAGE DRY DEPOSITION VELOCITY OF S02 BY SURFACE TYPE
Laboratory Measurement, Field Measurement,
Surface vg(cm sec'l) vg(cm sec'1)
Alfalfa
Grass
Wheat
Forest
Sandy Soil
Clayey Soil
Soil
Land
Water (Fresh)
Ocean
Snow
1.2 (2)
-
-
-
0.6 (2)
0.8 (2)
-
-
-
-
—
1.6 ( 2)
1.1 (14)
0.4 ( 3)
1-4 ( 5)
-
1.2 ( 4)
1-2 ( 4)
1.1 ( 6)
0.5 ( 2)
0.3 ( 2)
Note: Values in parenthesis indicate the number of separate studies used to obtain the
average deposition velocity.
6-9
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In reviewing predominantly the same set of data Garland (1978) concluded that the mean
deposition velocities for S02 over surfaces ranging from water and soil through short grass
to forest were very similar and suggested a value of about 0.8 cm s~l to be quite applicable
to large areas of Europe.
Sheih et al. (1979) in a more detailed effort to estimate dry deposition velocities of
sulfur dioxide and particulate sulfate over the eastern half of the United States, southern
Ontario and nearby oceanic regions, computed deposition velocities as a function of land use
characteristics, surface roughness scale lengths and surface resistances to pollutant uptake.
Gridded dry deposition velocities maps of sulfur dioxide and sulfate corresponding to half
degree increments of longitude and latitude were computed for a range of atmospheric stabili-
ties. The results indicate that deposition velocity distributions for sulfur dioxide are
rather nonuniform for the less stable atmospheric conditions. For very unstable, Pasquill
category A, atmospheric conditions dry deposition velocities over the eastern U.S. ranged from
0.4 to 0.9 cm s~l (excluding water surfaces) for sulfur dioxide, with a mean area wide dry
deposition velocity of approximately 0.6 'cm s~l. Under the same conditions sulfates ranged
from 0.7 to 0.9 cm s-1 with a mean value of approximately 0.8 cm s~l. Sheih et al. (1979)
note that under near calm conditions at night, stability classification schemes do not adequ-
ately represent the nocturnal inversion formed at the surface and recommend that a dry deposi-
tion velocity of 0.07 cm s'1 be assumed for both sulfur dioxide and sulfate particles.
6.3.1.2 Particle Dry Deposition—The dry deposition of particulate matter is considerably less
understood from the viewpoint of measurements for pollutant species of interest. In the
reviews by Sehmel (1980) and McMahon and Denison (1979), deposition velocities for particle
species are compiled for both artificial and natural surfaces. Unfortunately, with the excep-
tion of lead particles from automotive exhaust, virtually no data existed for the other impor-
tant particulate pollutants, such as sulfates, nitrates, and carbon containing particles. An
additional problem arises in the interpretation of the relationship between deposition measure-
ments on fallout collectors to that of dry deposition rates on natural surfaces. Fallout
collectors which were used in a significant portion of the measurements reported, typically do
not have the characteristics of the surfaces they are attempting to simulate.
Tables 6-3 and 6-4 from McMahon and Denison (1979) present a compilation of literature
values for the deposition velocities of particles measured under laboratory and field condi-
tions. The data cover a range of surface variables, particle sizes and composition, and
meteorological conditions. A review of the data indicate:
— Deposition in nature varies considerably via processes which are not totally understood.
-- The minimum deposition velocity for a particle is in a size range of 0.1 to 1.0 urn dia-
meter.
-- Deposition velocities are often reported for particle diameters and size distributions
that do not reflect typical atmospheric particulate matter characteristics.
6-10
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TABLE 6-3. LABORATORY MEASUREMENTS OF DEPOSITION VELOCITIES OF PARTICLES
Author
(date)
Chamberlain (1967)
M oiler and Schumann
(I97UI
Chjmberljin and
Chjjuick (1972)
CUighl 197.1)
Schmcl (197.1)
Schmcl and Suiter 119741
Bclot and Gauihier
11975)
Klcppcr and Craig (1975)
Craig a nl. (1976)
Wedding ,-i al. 11976)
Little and Widen (1977)
Litile (1977)
Reference
i, height
(cms"') (ml
0.0.1
0.03
01
O.S
,.r D:>
i . •= 0.06H.
r,-o.i2u.
0.005 "I
r 0-
2 J
2xlO'J-IO 0.01
5x|0~'-29 0.01
r. r. «'
r. ;. f
0.00.15
0.01
0.11
0.02
0.5
0.04
0.3
0.9
O.I
0.3
1.5
0.3
0.8
Paniculate
diameter
(; Short grass
Nettle
Beech
White Poplar
Nettle
Beech
White Poplar
Nettle
Beech
While Poplar
Comment
D «= ilillusion coefficient
2« I0': > D? 2« I0'5tm:»''
Drvllni-liirtes wind-tunnel
We'lJanJ held data
r, lo copper also mejMJrrd.
i, found to be a funi'iion of
wind speed.
Sec Fig. 1
Sec Fip 1
u — wind speed
d — panicle diameter
Wind-tunnel
Dcno>itiun rate on pubesceni
lca\e\ of sunflower was nearly
7 limes that of the non-
purvsicni leaves of tulip
poplar.
These data are for whole
shoots for wind speeds of
2.5ms"1. Data for other wind
speeds and separate plant
surfaces are gi\en in reference.
6-11
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TABLE 6-4. FIUD MEASUREMENTS OF DEPOSITION VELOCITIES OF WKTICLES
Authur
(date)
Chamberlain (1953)
EnUson (1959)
Small (I960)
Neubergcr >i ul. (1967)
While and Turner (1970)
Esmen and Com (1971)
Reference Paniculate
i, heifht diameter
icms*1) (ml (iim) Surface
11 0.3-09
II 0.3-0.9
0.5 0.3 09
0.7
1.6
05
(0.2 3.4)
,6 1
16 > Grass
,6 J
Ocean
Land
Land
Rag-weed Coniferous
e forest
S.f,
4.7
3.0
7.1
0.8
Na •} ^
K 1 Miied 1
Ca f deciduous f
Mg woodland
P J J
r Filler paper.
Comment
u - 9.2 m/s
u - 3.2 m/s
u - I.I m/s
Chloride over Scandinavia
Radioactive particles over
Non»ay
80°. rag-weed pollen removed
from air by forest
>l Probable overesiimaiion of
aerosol income, hence rr
2. Standard deviation varied
between 65 and 95". of
mean i§.
i.-O.SD 0.1-10 •{ Milliporc filler
Chamberlain and
ChadwicL (1972)
Pierson el ul 11973)
Caw« (1974)
Han jnd Parent (1974)
Clough (1975)
Abrahjimcn rf ul.
(19761
DovljnJ and Elijv-en
(19761
Frii.thcn and EJmonds
Prjhm ft ul. (1976)
Kie> anj ToonLel (1977)
Wesley ,-i ul. ( 1977)
r. - 0.06,,. jo.,
0.1-0.6
1.3
0.22
(045)
0.50
(0.50)
I.I
0.56
(0.45)
0.30
(1.0)
0.29
0.62
3.4
7.3
II
61
100 :
0.74
I.I
0.75 1
117
soi
*• Class slide
J > Cereal crops
Land
Al -N
As
Cd
Cr
Cu
Fe
Mr,
Ni
Pb
Ti
\
Zn J
'*' V?' Douglas fir
°' ' and junipers
P. NO, ' ^
Crass
Grass
• 30 Grass
Dry moss
Wet moss
• 4 Grass
1 Grass
Dry moss
Spruce and
pines
0.16 \ atmospheric "\ _
068 /aerosol / Snow
007
0.46
3 Douglas lir
atmospheric Atlantic
»cro
0.5
to! ocean
06 5 005 0 1 Bare soil
and grass
Dmlncludes mind-tunnel and
Wet/field data.
t, estimated for 23 trace
elements based on several
years of data
Entracted from Gatz (1975).
Values in parentheses were
estimated by Cau from a
relationship between particle
silt and rr
*
Deposition
beneath trees ^
open terrain
Dry u. - 37 cm s " '
Dry u, " 87 cms" '
Wet ii. - 87 cms'1
Dry w. • 37 cms"1
Dry u. — 37 cm s " '
Deposition
bencjth trees ^
open terrain
Lead
SO;" : upper bound value
soj-
90».: HASL wet -dry collector
• < 2m.'1; Edd) correl
method.
6-12
-------
The large experimental uncertainties associated with particle dry deposition velocity
measurement has stimulated the development and application of theoretical models for simulating
the dry deposition process and predicting dry deposition velocities given specific meteorologi-
cal data, Sehmel (1980), SI inn (1978, 1977), and Davidson and Friedlander (1978). The models
describe only the physical processes of bringing the particle to the depositing surface.
No consideration has been given to particle shapes other than spherical, to particle composi-
tion, or to surface properties with regard to particle retention. Particle size, an important
property in the aerodynamic flow of particles to surfaces, is considered. The typical model
result, shows predicted deposition velocities to increase as surface roughness and/or friction
velocity increases and to be nearly independent of atmospheric stability. The deposition
velocity for particles passes through a minimum in the 0.1 to 1 pm diameter particle range.
Figure 6-2 (Sehmel 1980) presents predicted deposition velocities at 1 meter from the
surface, for u* = 30 cm s'l and particle densities of 1,4, and 11.5g cm3, (g/cm^ = yg/m^).
In Table 6-5 the range of predicted deposition velocities at a height of 10 meters is
presented for two particle size regions and for a range of aerodynamic surface roughness
lengths, mean wind speeds, and calculated friction velocities. These results are based on data
presented in Sehmel (1980) and should be fairly representative of the majority of meteorologi-
cal and surface conditions encountered in the environment.
6.3.2 Precipitation Scavenging
As with dry deposition, precipitation scavenging or wet removal results from a series of
complex physical and chemical interactions involving properties of the scavenging media and the
species removed. Research in the area has continued for over the past thirty years, focusing
on the removal of radioactive debris from the atmosphere introduced by nuclear weapons testing
Bowen, (1960), Engelmann, (1968) and Volchok, et al. (1971), and in conjunction with material
balance or budget studies on the removal of various elemental species from the atmosphere,
Robinson and Robbins (1970), Rasmussen et al. (1975) and Junge (1972, 1974).
The fundamentals of the theory of precipitation scavenging have been researched and
reviewed over the years, by Engelmann (1968), Postma (1970), Hales (1972), Slinn, et al. (1978)
and Slinn (1981). Though our understanding of the details of the complex processes operative
in precipitation scavenging is less than complete, significant progress has been made in
elucidating the general scavenging pathways and developing appropriate parameterizations for
their quantitative treatment. As pointed out by Slinn (1981) and others, the removal of trace
constituents from the atmosphere by precipitation scavenging is dependent on four basic fac-
tors: 1) the position of the trace constituent relative to the scavenging media; 2) the
physical form of the scavenging media; 3) the chemical and physical properties of the trace
constitutent; and 4) the specific physical/chemical process that is operative. These basic
factors are schematically illustrated in Figure 6-3.
6-13
-------
•^ .,1
MIIICU DIAMHtl. urn
Figure 6-2. Predicted deposition velocities at 1 m for
densities of 1, 4. and 11.5 g cm 3.
30 cm s'1 and particle
6-14
-------
i
*—i
in
DEPENDENCEJJF J'RE^PjTATIp^SCAVENGIKG (WASHOUT) ON:
(1) POSITION ! (2) PRECIPITATION | (3) POLLUTANTS | (4) PROCESSES
I
NUCLEATION
SCAVENGING
IN-CLOUD
SCA VENG I NG
aow -CLOUD
SCAVENGING Vl
SCAVENGING
(SNOWOUT)
I SCAVENGING
I (RAINOUT)
I
I
"•"> PARTICLE
SNOWOUT
GAS
RAINOUT
eg.
INtRTIAL
DIFFUSICNAL,
etc.,
PARTICLE
SNOWOUT '"'
:n*
EQUILIBRIUM
REVERSIBLE,
etc.
GAS RAINOUT
Figure 6-3. Basic factors influencing precipitation scavenging.
-------
TABLE 6-5. PREDICTED PARTICLE DEPOSITION VELOCITIES1"
Deposition Velocity Rangett
ZQ
cm
0.1
10
0.1
10
u/u*
m-sec/cm-sec
2.3/10
1.2/10
11.5/50
5.8/50
Particle
0.1 to lu
cm s"l
1.5X10-2 - 5.0X10-2
9.0X10-2 - 1.5X10-1
2.0X10-2 - 5.5X10-2
1.0X10"1 - 2.0X10'1
Diameter
lu to lu
cm s"l
5.0X10-2 - 4
1.5X10-1 - 4
5.5X10-2 - 4
2.0X10'1 - 4
fBased on model predictions in Sehmel (1980)
"^particle density of 11.5 mg/m^
A convenient practice in the field of precipitation scavenging has been to distinguish
between below-cloud and in-cloud scavenging processes. Unfortunately, the commonly used
terminology used in describing these processes, rainout for in-cloud and washout for below
cloud, has lead to considerable confusion. The elucidation of the contribution of these
processes to the total scavenging in a precipitation event is extremely difficult. Washout,
being more amenable to experimental study, has received the most attention from the scientific
community. Also in many experimental studies, distinction of the two processes has been
ignored and only the total precipitation scavenging has been considered. The theoretical
approaches to be discussed in the section to follow are for washout processes only, while
empirical parameterization discussed consider total gas and particle scavenging.
The parameterization of the precipitation scavenging process has generally taken the form
of a loss rate per unit volume and has evolved from various assumptions applied to the continu-
ity equation, SI inn (1977). Parameterizations for the removal of gases by rain and the removal
of particles by rain and by snow are considered in the following sections. The formalism and
technical rigor used in their development, can be found elsewhere, Hales (1972, 1978) SI inn
(1977), and is beyond the scope of this work.
6.3.2.1 SO? Wet Removal--The removal of sulfur dioxide from the atmosphere by rain is governed
by basic physical processes that describe the absorption and desorption of the S02 molecules
from the hydrometeor, Hales (1972, 1978), and by a series of chemical reactions, Postma (1970),
Hill and Adamowicz (1977), Barrie (1978), which account for the liquid phase oxidation of
S02- From a purely physical process viewpoint, the rate of scavenging of a gas by rain is a
function of the size spectrum of the raindroplets, the fall path of the raindroplet to the
ground, the rainfall rate, and the solubility of the gas. General expressions have been
6-16
-------
developed, Hales (1978) and Slinn et al. (1978), for computing the scavenging of S0£ and
other gases given simplifing assumptions regarding the characterization of the precipitation
and solubility of the gas. As pointed out in Chapter 2, the liquid phase oxidation of SO? is
very complex and not adequately understood at present. Several recent studies, Hill and
Adamowicz (1977), Barrie (1978), Garland (1978), Gravenhorst, et al . (1978) have considered the
S02 - bisulfite oxidation process, Scott and Hobbs (1967) in predicting wet removal rates of
S02 under various atmospheric conditions. The solution phase chemistry for SO?, based on
the mechanism of Scott and Hobbs (1967) as used in the S02 washout model by Barrie (1978) is
discussed here as an illustrative example.
Sulfur dioxide exists in solution as physically dissolved SC>2 (S02-H20), which follows a
linear Henry's Law relationship with gas phase S02, bisulphite (HSC>3'), and sulfite (503").
The equilibria describing the process are as follows:
(S02)g + (H20)i * (S02-H20)£
[S02-H20]t
KH = - (i)
[S02]g
* H\ + HS03-J,
[H+]1[HS03-])l
(2)
HS03-t *H\
[H+]1[S03=]£
K2 = - (3)
The K's are equilibrium constants, with KH being the Henry's Law constant for S02, and
the square brackets represent chemical activities which are effectively concentrations for the
dilute conditions present. It has been established Beilke and Lamb (1975) that the dissocia-
tion of S02-H20 and HS03" are very rapid, thereby introducing a non-linear relationship between
gas phase S02 and total dissolved SC>2 which is strongly dependent on pH (see Figure 6-4
Barrie, 1978) and only weakly dependent on temperature. The effect of temperature is a shift
in equilibria to the left for increasing temperatures, resulting in a slight shifting to the
right of the curves in Figure 6-4. Within the pH range of precipitation, pH 3 to 6, over 90%
of the dissolved S02 exists as bisulfite, with less than 10% existing as sulfite. This
result indicates that equilibrium equation (7) can be neglected, without significantly effect-
ing the washout calculation. Barrie assumed that S02 oxidation in the raindrops could be
neglected due to the limited time for reaction (0-5 min) and the low pH's encountered, Beilke
et al.
6-17
-------
O 1 o
'•"
o
_l
u.
O
0.5
£ o
SO, • HjO
10
PH
Figure 6-4. Abundance of dissolved SO2 species as a function
of pH (25°C).
6-18
-------
(1975). In cases where S02 is the dominant species contributing to the acidity of the rain
droplet, an expression relating the gas phase SOj concentration to the bisulfite ion concen-
tration in equilibrium with the gas is as follows:
[HS03-]peq =
Incorporating this expression with a physical model for gas transfer to the droplet,
Barrie (1978) modeled the washout of SC>2 from a plume under varying meteorological and SC>2
concentration conditions. He concluded that the fractional plume washout rate (%/mm rain) is
inversely proportional to the plume concentration and thickness. For heavy rain (25 mm/h)
washout from a 1000 ppb(v) S02 plume of 20 m thickness occurs at a rate of 56% hr'l, while
under drizzle conditions (0.5 mm/h) for a 300 pph(v) S02 plume of 50 m thickness the rate was
2% h~l. Barrie assumed that the pH of the raindrop was governed by the dissolution of the
S02- In a more definitive model of S02 washout, Hill and Adamowicz (1977) included esti-
mates for S02 oxidation within rain droplets and for the pH dependence of the precipitation.
They indicated that pH can be quite variable (over six orders of magnitude) at S02 ambient
levels of 10 ppb and less. As S02 levels increase, the variability in background pH decreases.
The S02 oxidation rate of 3.6% h~l used in the calculations is based on the catalytic oxidation
studies of Brimblecombe and Spedding (1974). In a typical calculation of the rate of S02
washout, Hill and Adamowicz assumed various ambient S02 concentrations to be well mixed
through a layer 1 kilometer in depth and a rainfall rate of 1 mm/h with a predominant drop
radius of 0.5 mm and pH of 7. Calculated washout rates of S02 under these conditions were
2.6%/h and .8%/h for ambient S02 levels of 10 ppb and 100 ppb, respectively.
A convenient empirical expression for the wet removal of gases takes the form of an
exponential decay process, where the time constant for decay (scavenging coefficient for the
gas), determined in field and laboratory studies, is a function of the rainfall intensity. The
expression takes the form
xt = xPt (5)
where xt and x0 are the atmospheric concentrations of the gas at time t and zero, respective-
ly, and A is the scavenging coefficient for the gas. Estimates of the scavenging coeffic-
ients for sulfur dioxide have been determined by Chamberlain (1953), Beilke (1970), Hales et
al . (1971), Dana et al. (1975) and others. calculated scavenging rates of 502 usi"9 these
coefficients can range typically from 2% h"1 to 22% h~l.
6.3.2.2 Particle Wet Removal—The study of precipitation scavenging of particles has predomi-
nantly focused on theoretical studies, Semonin and Beadle, (1977), Slinn (1977), Grover et al.
(1977), Wang et al. (1978), but with considerable emphasis in experimentel work taking hold in
6-19
-------
recent years (Dana and Hales, 1976 ; Radke et al., 1980 ; Gatz, 1977). The wet removal of
sulfate participate matter in the ambient environment has been of particular interest, (Scott,
1978 ; Hales, 1978 ; Dana, 1980) due to the acidic tendency of these particles and the
increased concern in the phenomenon termed "acid rain". Chapter 7 of this criteria document
discusses acid precipitation and its associated scientific issues and is not a specific topic
for consideration in this section.
Important parameters affecting the particle scavenging rate by precipitation, as with
gases, are the size spectrum of the rain droplets, the fall path of the rain droplet to the
ground, and the rainfall rate, but also include in addition, the size distribution and composi-
tion off the particulate matter. As with gases, general expressions have been developed (Slinn,
1977) for computing the scavenging of particles given certain simplif ing. assumptions.
A practical operational approach in predicting the wet removal of particles as mentioned
previously for gaseous has been through the measurement of empirical scavenging coefficients.
A comprehensive list of field measurements of wet scavenging coefficients of particle has
been compiled by McMahon and Denison (1979) and presented in Table 6-6. A cautionary note is
in order. The scavenging coefficients are dependent on the rain fall rate, the mean rain drop
radius, and the particle size. When these factors are taken into consideration, the scavenging
coefficients reported in Table 6-6 show reasonable consistency as demonstrated by Figure 6-5
taken from McMahon and Denison (1979).
Recent airborne measurements by Radke et al. (1980) on precipitation scavenging of aerosol
particles greater than 0.01 pm diameter in aged air masses, coal fired power plant plumes, a
Kraft paper mill, and a plume from a volcanic eruption were quite encouraging in supporting
theoretical estimates of wet removal for aerosol particles greater than 1.0 urn. Marked differ-
ences were observed in the submicron particle region, where measured scavenging efficien-
cies for submicron aerosol particles were typically an order of magnitude greater than theore-
tical predictions; and the scavenging gap, that portion of the aerosol particle size range
where scavenging collection efficiencies are at a minimum, was observed to be much narrower
than predicted by theory. Radke et al. (1980) offer some explanations for the discrepancies
including deliquescent growth and nucleation scavenging of the submicron particles in convec-
tive clouds. Considering the varied aerosol particle sources and. precipitation studied the
measurements showed marked continuity, (see Figure 6-6), Radke et al. (1980).
6.4 TRANSPORT AND DIFFUSION
Pollutant substances emitted into the atmosphere are transported and diffused as a result
of a series of complex physical interactions which describe the mean motion of air and its
fluctuating components. Transport and diffusion have associated with them spatial and temporal
scales. The selection of the spatial or temporal domain of interest directly influences what
specific physical phenomena will predominantly affect the transport and diffusion process.
6-20
-------
TABLE 6-6. FIELD MEASUREMENTS OF SCAVENGING COEFFICIENTS OF PARTICLtS
Author
Idaiel
Kalkstcin ri al. (1959)
Georgii (1963)
Banerji and Chatterjet (1964)
Makhon'ko (1964)
Shirvaikar n al. (1960)
Makhon'ko and Dmitrieva
(1966)
Makhon'ko (1967)
Wolf and Dane (1969)
Bakulin el al. (1970)
Burtscv ti al. (1970)
Dana (1970)
Perkins el al. (1970)
Peterson and Crawford (1970)
Esmen (1972)
Rodhe and Grandell (1972)
Acres- ESC (1974)
Gracdel and Franey (1975)
Hicks (1976)
Gruedel and Franey (1977)
A-',
1 x ID"'
2 x |Q-»
4 x 10"' -\
22 x 10'» >
4 x 10-' J
0.4 x 10"'
2 x 10-' \
«1 x 10"' /
7 x 10-'
20 x 10-'
7 x 10-'
0.5 x 10" 'J
3 x 10-'
is x io-'y°»
20 x 10-»J°»
13 x 10'»J
300 x 10"'
16 x ID'' J"
0.4 x 10-'
0.7 x 10-'
A^-25-SOA,.,.
50 x I0'»
19 IO'5
18 ID''
28 10'»
43 10-'
65 ID''
92 10-'
Particubic
size
(/iml
SO.. NH.
Cl, NO,
Dissolved
inorganic
contamineni
Radon
Fission products
Atmospheric dust
Fission products
Atmospheric dust
0.5
=0.2
=0.2
7.5.3
Atmospheric aerosol
5
Atmospheric aerosol
Atmospheric aerosol
0.4-1
<1
0.3-05
0.5-07
0.7-0.9
0.9-1.5
1.5-3
Commeni
Rainou,"lMalhon.k ,%7
Washout/
> Rainout
Washout
Rainout Makhon'ko (1967)
Rainoul
Washout
Rainout Makhon'ko (1967).
Rainoul
Rainoul plus washout
Snow: Knution and
Slockham (1977)
11 'Pb; washout from
thunderstorm
Washout
Rainout
Uranin and rhodamine
particles respectively
Rainout
Based on Engclmann's
data (1965)
Includes rainoul
Suggest A proportional
to rainfall intensity
Includes rainout
Set Slinn (1976)
Rainout
Condensation nuclei
Snow
Radkerf al. (1977)
Set Fig. 8
6-21
-------
2 ,oo
< 1
E
Radke * rf (1977)
Bunu» «l * (18701
Hkki (1»76>
Dan> (1B70)
Pateraon A
CrMfonl (IKS)
0.01 0.1 1 10
EQUIVALENT PARTICLE DIAMETER (pm)
Figure 6-5. Relationship between rain scavenging
rates and particle size.
6-22
-------
100
DATE SOURCE OF AEROSOL
MAY 13.1974 PT TOWNSCND PAPER MILL.WA
MAR 25.1976 "NATURAL.NEAR CENTRAUA.WA
MAY io. are CENTRALIA TOWER PLANT. WA
(•) 400 » AND (B) 265i
SCAVENGING TIME
10
DRY AEROSOL RARTICLE DIAMETER
(a)
IOU
^
05
£&>
0> 50
UJ ffi
§0
ss
P
»
PATE SOURCE OF AEROSOL
JUL. 1.1976 NATURAL* (o) 3 km MSL
AND (b) 2.5km MSL AT
JUN 29.1977 FOUR CORNERS POWER
•.
•.
(o)X \\ ///-
- .--"'^ ''' \\ I jf
"' \ M
\ '• i
\ §
\ .
\ §
\ -
V
. .... ...1 . . .1 , ,
o-f 10-' K>°
PARTICLES
MILES CITY.MT.
PLANT. NM.
X* /''
f" ,>'
i
10'
DRY AEROSOL PARTICLE DIAMETER Urn)
(b)
Figure 6-6. Percentages of aerosol particles of various
sizes removed by precipitation scavenging.
6-23
-------
The study of air pollution transport and diffusion is typically treated on the basis of
the extent of the horizontal scale. Therefore, high level pollutant concentrations which occur
in the vicinity of a major emission source are dominated by physical processes that are opera-
tive on a local horizontal scale of the order of 1 to 5 kilometers, or approximately one hour
of transport. Since the majority of criteria pollutants are emitted directly into the atmo-
sphere by major sources, a predominance of interest with respect to air pollution regulation
has resided on this scale. But, as air pollution issues are raised with regard to pollutants
of a more ubiquitous nature, having appreciable long life-time and in some cases forming
through secondary reaction processes, the horizontal scale of interest expands considerably.
Sulfur dioxide and particulate matter span a horizontal scale ranging from local to global. A
brief review of the physical processes contributing to transport and diffusion is presented in
section 6.4.1, while section 6.4.2 considers pollutant residence times and their long distance
transport.
6.4.1 The Planetary Boundary Layer
The primary vehicle for the transport of pollutants within the atmosphere is the mean wind
within approximately the first 1000 meters above the earth's surface. The mean wind is deter-
mined primarily by the interaction of three forces governed by thermodynamic and mechanical
processes. These are: the force due to the horizontal pressure gradient produced by differ-
ential solar heating of the earth's surface; the Coriolis force due to the earth's rotation;
and the friction force due to the texture of the earth's surface. The planetary boundary layer
is defined as that portion of the atmosphere within which surface frictional effects have a
substantial impact on the mean wind. Typically, this layer is hundreds of meters in depth and
varies diurnally.
Diffusion in the planetary boundary layer, which governs the spreading of pollutants
perpendicular to the transport flow, is regulated by turbulence. Turbulence, which is compris-
ed of a complex spectrum of fluctuating motion superimposed on the mean wind, is .generated
through the interaction of directional and speed differences (Shear) in large scale atmospheric
motions and perturbations introduced in the mean flow by the roughness of the earth's surface,
as well as by heating of this surface by the sun.
The theory of the mean vertical structure of the planetary boundary is fairly well under-
stood, Haugen (1973) and its characterization is possible through the measurement of basic
meteorological parameters. The description of the turbulent properties within the mean motion,
which govern diffusion, has proven to be more elusive. Detailed theoretical approaches to
turbulence encounter solution problems resulting from having more unknown parameters than
equations. The introduction of higher order closure techniques, which apply assumptions that
permit new unknowns to be expressed in terms of others in such a way as to allow solution of
the equation set, have limited practical application due to their intensive computer and data
requirements. As a consequence the practical treatment of atmospheric diffusion to air pollu-
6-24
-------
tion related processes is based on highly parameterized theories which depend strongly on
basic experimental data sets.
Practical approaches to the treatment of atmospheric diffusion have been derived from
three principal sources: statistical theory, similarity theory and gradient transport or
K-theory (Pasquill, 1974). A brief description of these approaches and their utility to air
pollution related problems is presented below. More definitive discussions on the theories can
be found in the annotated references.
Statistical theory considers the time history of the motion of a single fluid "particle",
relative to a fixed co-ordinate axis (Taylor, 1921), and of groups or clusters of such parti-
cles relative to their centroid (Batchelor, 1953). The theory provides the basis for the
development of the Gaussian diffusion formulation and provides an effective means to correlate
empirical dispersion data. As a result, diffusion equations for various emission source
types have been developed (Gifford, 1968, 1975 ; Turner, 1970 ; Pasquill, 1974, 1975). A practi-
cal limitation of this approach is that it makes the fundamental assumption of turbulence
homogeneity, whereas boundary-layer turbulence is inhomogeneous, especially in the vertical.
The similarity theory of diffusion relates the mean position and other properties of
diffusing clouds and plumes to the characteristic parameters of the surface layer, by dimen-
sional reasoning. Results (Monin and Yaglom, 1971) are reasonably complete for the surface
layer. But extension to the entire boundary layer introduces further parameters, which limit
their practical use.
The gradient-transport, or K-theory of diffusion is historically the oldest; it originated
with Pick (1855) and Boussinesq (1877). Atmospheric applications have been most successful at
large scales, including global diffusion. At boundary-layer scales the behavior of K is quite
complicated. Useful results can be obtained (Pasquill, 1974 ; Yaglom, 1975 -, or Csanady,
1973), but the mathematics required tends to be fairly elaborate. The essential problem is to
account for the strong space-time scale-dependence of eddy-diffusivity, which was first demon-
strated by Richardson (1926). Berlyand (1974) has based a comprehensive system of air pollu-
tion analysis entirely on a form of K-theory.
The parameterization of atmospheric diffusion was shown by Obukhov (1941) to follow a form
of Richardson's law of diffusion where the total amount of turbulent energy dissipation and the
pollutant spreading is proportional to the diffusion time to the 3/2 power. Data on the
instantaneous values of the spreading of plumes and puffs (i.e., on relative diffusion) shows
that this law describes diffusion up to t on the order of an hour (Gifford, 1976a). On the
other hand the time-average spreading of plumes was shown by Taylor (1921) to obey the asymp-
totic laws o « t for small t-values and a <* tl/2 in the limit of large t-values. Diffusion
depends both on travel time from source to receptor, and on the sampling time, that is, the
time over which the concentration is averaged at the receptor point. The situation is made
more complicated by the fact that cross-wind diffusion behaves markedly different from vertical
6-25
-------
diffusion in the boundary layer because of the inhibiting effect on vertical turbulence fluctu-
ations imposed by the presence of the ground, and because of the strong damping effect of
stability on vertical turbulent motions.
A number of attempts have been made to express horizontal and vertical boundary layer
diffusion for flat uniform terrain, as measured by the lengths oy and oz, to more or less
easily measured quantities that characterize boundary layer thermal and mechanical turbulence
properties. Extensive surveys of the literature on the subject, have been undertaken by
Gifford (1976b) and Weber (1976). The former stressed the common logic underlying various and
sometimes seemingly conflicting schemes, as well as the need to evaluate many exceptional cases
that arise in practical applications.
Based on these analyses and those of Pasquill (1975, 1976), the diffusion parameterization
originally suggested by Pasquill (1961) is valid for sources located at or fairly near the
surface, for uniform underlying terrain, and for receptors up to several kilometers distance.
Extension to greater distances, varying surface roughness, and other generalizations have been
discussed Smith (1972) as well as relations to surface-layer turbulence parameters, Golder
(1972) and Draxler (1976). The difficulties that have arisen in applying this methodology to
practical air pollution problems have centered around, cases for which the turbulence is
produced or modified by factors which extend beyond the purely thermal and mechanical compo-
nents that control the local boundary layer turbulence.
6.4.2 Horizontal Transport and Pollutant Residence Times
The horizontal distance over which a pollutant is transported is strongly influenced by
its overall lifetime or residence time in the atmosphere, the characteristics of the mean wind,
and the time of day and height at which the pollutant is emitted into the atmosphere.
Residence times for pollutants, are governed by the extent of wet and dry removal and
chemical transformation the pollutant species undergoes in the atmosphere. Depicted in Figure
6-7 are estimated residence times for typical pollutants and their associated characteristic
horizontal meteorological scale. Average wind speeds of 5 m/sec were assumed in approximating
the distance scale. Residence time estimates are based on Junge (1972, 1974).
Transport scales for pollutants such as SO? which have appreciable dry deposition veloc-
ities, will be sensitive to the relative height at which the pollutant is emitted. Pollutant
distributions also will be sensitive to the stability of the atmosphere which will govern the
extent of vertical mixing to the surfaces.
Industrial facilities emitting large quantities of S02 have tried to take advantage of
these natural meteorological phenomena to reduce ambient levels of SO? in the vicinity of
their stacks. By building taller effluent stacks, emitting facilities succeed in injecting
SC>2 at higher levels in the atmosphere, allowing the pollutant more time to disperse and
transport before reaching ground level, thereby affectively reducing ground level concentra-
6-26
-------
RESIDENCE
TIME.hr
103
m^ -^
10° -«
10'1 -
HORIZONTAL
LENGTH
SCALE
200 km
<" 20 km
2 km
CLIMATOLOGICAL
SCALE
PCB's
SYNOPTIC AND
PLANETARY
SCALE
0.1— 1.0 ^m
PARTICLES
MESO
SCALE
so2
r
MICRO-SCALE
2
a; 50 pm
PARTICLES
Figure 6-7. Estimated residence times for select pollutant species and their associated hori-
zontal transport scale.
6-27
-------
tions of S02 as a result. A great deal of controversy arose regarding this approach and as
to whether it was circumventing the intent of the Clean Air Act. As a result of the Clean Air
Act Amendments of 1977 the Environmental Protection Agency requires that the degree of emission
limitation necessary for control of any air pollutant can not be achieved through the construc-
tion of stacks higher than would be considered appropriate using good engineering practice
design standards. An interesting corollary of the tall stack issue is the potential for such
sources to enhance the production of particulate sulfate. As a result of SC>2 being emitted
at higher levels in the atmosphere the probability of its removal by dry deposition is lowered,
extending its lifetime in the atmosphere and subsequently enhancing its probability to trans-
form through chemical reaction to particulate sulfate.
Of particular importance to horizontal transport is the strength and time of formation of
the nocturnal inversion, a stable layer of air formed at the surface due to the differential
cooling of the earth's surface relative to the air at night. The depth of this stable layer
can vary from approximately 50 m to 500 m depending on meteorological conditions. At the onset
of the nocturnal inversion all pollutants present in the well mixed layer from that day's
emission are cut off from the surface by this stable layer of air. No major mechanisms for
transport through this layer exist; so dry deposition processes virtually stop, leaving the
pollutant reservoir aloft free to transport long distances with negligible losses. In addi-
tion, horizontal mean winds are typically enhanced in layers aloft due to the reduction in
frictional drag at the earth's surface as a result of the presence of the stable nocturnal
layer. Associated with this overall process is a phenomenon of the particular importance to
nighttime transport, the nocturnal jet. Blackadar (1957) described the mechanism for the
formation of the nocturnal jet as due to decoupling of winds previously restrained by friction-
al forces at the surface, and now free to accelerate in response to existing pressure gradi-
ents; as a result some overshooting in wind speed occurs as the flow attempts to establish a
new balance with inertial forces. Bonner (1968) examined two years of upper level wind data
from the National Weather Services rawinsonde network to determine the frequency and geographi-
cal distribution of the low-level jet. Recently, high-resolution measurements of wind profiles
collected over central Illinois, Sisterson And Frenzen (1978), showed that nocturnal, low-level
wind maxima occur more frequently than indicated in the analysis performed by Bonner. In
these studies, low-level wind maxima were observed on 24 out of a total of 30 nights for which
meteorological field experiments were conducted in the summers of 1975 and 1976. Typical
average wind speed profiles observed under the decoupled conditions showed wind speeds of the
order of 1-2 m s~* near the surface increasing to maximum values of 8 m s~* at 100-200 meters
above the surface.
It is quite apparent that the nocturnal jet and nighttime flows in general are significant
factors in the transport of pollutants over long distances.
6-28
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Definitive studies on the long range transport of atmospheric tracers have been primarily
associated with radioactive debris, Islitzer and Slade (1968), and in many instances at height
levels not of particular interest for air pollution related work. Some analyses of ambient
data have been performed to provide qualitative indications of the long range aspects of
certain pollutant species, Altshuller (1976), Lyons and Husar (1976), Rodhe et al. (1972),
Brosset and Akerstrom (1972), but very few quantitative studies exists. The major reason being
lack of appropriate experimental data. Recent monitoring and field study programs designed to
address the long range transport air pollution phenomenon, should alleviate this problem
somewhat, Perhac (1978), MacCracken (1978), Schiermeier et al. (1979).
6.5 AIR QUALITY SIMULATION MODELING
The principal role of the air quality simulation model is to describe quantitatively the
relationship between emissions distribution and ambient air quality in time and space. Air
quality simulation models provide a vehicle for improved understanding of the physical and
chemical processes operative in polluted atmospheres, and a means to sound, creditably based
scientific decisions on the nature and extent of emission control required to meet specified
ambient air quality.
The development of the air quality simulation model (AQSM) has its origins as far back as
the early 1930's when Sutton (1932) introduced his basic theory on diffusion in the atmosphere,
which established the foundation for the Gaussian equations used in describing the dispersion
of effulents in the atmosphere. The evolution of AQSM's has continued since then, treating
increasingly complex air pollution problems and utilizing advanced theoretical approaches
in describing the details of the physical and chemical processes operative in the atmosphere.
The use of mathematical models for air quality impact analysis associated with S02 and total
suspended particulate matter, both criteria pollutants, has been a standard practice over the
years, though discretionary, prior to the passage of the Clean Air Act Amendment in 1977. With
the passage of the 1977 amendments, the Environmental Protection Agency is now required to
take certain regulatory steps related to the use of air quality simulation models. The work
horse of operational air quality simulation modeling has been the single and multiple source
Gaussian plume models. The predominant use of these models has been the prediction of ground
level concentrations in the immediate vicinity to several kilometers downwind of the effluent
source. Many reviews on dispersion modeling are available, see for example, Gifford (1968),
Strom (1976) and Turner (1979). Section 6.5.1 provides a brief discussion on the status of the
Gaussian modeling techniques, while Section 6.5.2 discuss the scientific basis and status of
air quality simulation modeling over long distance scales and their impact on furthering our
understanding of the physical and chemical processes affecting the fate of SOj and particu-
late matter in the air environment. In Section 6.5.3, a discussion of model evaluation and
data bases is provided.
6-29
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6.5.1 Gaussian Plume Modeling Techniques
The Gaussian diffusion formulation used in a variety of air quality simulation modeling
approaches is a result of the Gaussian or normal distribution function being a fundamental
solution to the Fickian diffusion equation, which strictly speaking applies only in the limit
of large diffusion time and for homogeneous, stationary conditions.
The Gaussian diffusion formulation for a continuous point source emitting pollutants at
height h and calculated receptor concentrations at ground level is given by
Q y2 h2
x(x,y) = - exp [ -( - - + - )] (1)
2
-------
of horizontal wind fluctuations-; bulk Richardson number as determined from temperature, 10 m
wind speed and 2 and 10 m temperature differences; height of surface boundary layer under
unstable conditions; and the top of the inversion under stable atmospheric conditions. Addi-
tional improvements will be gained as existing theories and experimental data bases are drawn
together in a unified scheme for estimating dispersion parameters as a function of stability,
effluent release height and surface roughness.
A variety of operational Gaussian air quality dispersion models, used for the majority of
SO? and total suspended particulate matter regulatory applications, are available through
EPA's UNAMAP, User's Network for Applied Modeling of Air Pollution. A brief description of
these models can be found in Turner (1979).
Finally, an additional important aspect to dispersion modeling calculations is the predic-
tion of the effective height of the effluent release, so called "plume rise", which strongly
affects the predicted ground level concentration of pollutants. Significant research into the
processes affecting plume rise and its prediction has been underway for over the past twenty
years. Recently, Briggs (1975) reviewed the physics of plume rise and its prediction and
presented basic formulations for calculating the height to which plumes rise as a function of
atmospheric stability and several standard stack parameters. He indicates that the greatest
need for further investigation, concerns plume rise limited by ambient turbulence under convec-
tive atmospheric conditions.
6.5.2 Long Range Air Pollution Modeling
The growing interest in the long range transport of air pollutants in recent years has
resulted in several extensive reviews on the subject, Bass (1980), Eliassen (1980), Pack et al.
(1978), Smith and Hunt (1978). Long range is defined here as horizontal scales of the order of
1000 km resulting in transport times of the order of several days. Typical model spatial
resolutions on this scale range from 20 to 100 km. As concluded by Bass (1980), the majority
of long range transport models are Lagrangian based. The Lagrangian approach represents an
emitting source element by a series of discrete pollutant parcels which are advected and
diffused by a time and space dependent wind field. In principle, the individual pollutant
parcels can treat time-dependent chemical transformation, dry deposition and precipitation
scavenging processes. Fixed space-time averages of pollutants are generated by superimposing
all elements that pass a specified point over the averaging time of interest. The Lagrangian
models, although all cut from the same basic theoretical fabric, have developed various nuances
in their evolution.
In reviewing the models, very little consensus of opinion surfaces with regard to standard
treatments for: 1) wind field analysis; 2) choice of wind height level for trajectory; 3)
mixing height variations; and 4) dry and wet removal and chemical transformation rates. Even
the basic generation of discrete air parcels is viewed from four different approaches: puff
super-position, segmented plume, square puff, and statistical. Three of the approaches which
6-31
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are readily depicted, Figure 6-8 Bass (1980), are contrasted to the idealized continuous plume
they are attempting to represent.
Eulerian or grid-based approaches have been less prevalent in long-range transport air
pollution modeling. This may to some extent result from problems associated with the numerical
integration of the advection equation which give rise to pseudo-diffusion effects. But a more
likely reason is the increased complexity and enhanced data base and computational requirements
of the Eulerian models.
Table 6-7 provides a representative sampling of long-range transport models discussed in
the available literature and presents for each referenced model: a brief description of the
modeling approach, including characteristic averaging times; approaches to dry and wet removal
and chemical transformati )n; and pollutant species modeled.
A review of the mod .'Is presented in Table 6-7 indicates that sulfur dioxide and sulfates
have been the species of major interest. This stems from the fact that many of the models were
developed with the specific intent of addressing the acid rain phenomenon. These sulfur
species have been identified as major contributing factors in the acidification of precipita-
tion. Though none of the models as presently configured consider primary emitted particulate
matter, their inclusion would be reasonably straightforward given the availability of appropri-
ate emission inventories. The far more difficult tasks of considering the gas to particulate
matter forming processes of nitrates and organic species, aerosol dynamic processes and size
distributions remain for future research to resolve. Until these basic processes as well as
gas-liquid phase transfer and solution phase chemistry of rain droplets are adequately treated
within the models, significant skepticism as to the scientific creditability and utility of the
models will remain.
In a similar manner, regional visibility impairment, which results from the physical
interaction of sunlight with light absorbing gases and particulate matter and light scattering
aerosols, requires the consideration of many of the process indicated above. Though several
empirical analysis techniques have been developed recently which provide a qualitative under-
standing of the scope and general meteorological characteristics of the visibility impairment
problem, no adequate quantitative relationships presently are available for emission control
strategy assessments.
Although verification studies of long range transport models are limited, it has been
recognized for some time that errors in observed wind direction, Pack et al. (1978) and the
specification of wind fields in general, Sykes and Hatton (1976), Smith and Hunt (1978), and
Draxler (1979) can result in drastic errors in spatial predictions over long range travel
distances.
A significant contribution to uncertainties in transport prediction resides in the sparse
temporal and spatial resolve of upper level wind information. The National Weather Service
fi-32
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CONTINUOUS
PLUME
SEGMENTED
PLUME
MODEL
CTt
I
CO
CO
PUFF
SUPERPOSITION
MODEL
'SQUARE PUFF*
MODEL
Figure 6-8. Trajectory modeling approaches.
-------
TABLE 6-7. SUMMARY OF SELECT LONG RANGE TRANSPORT AIR POLLUTION MODELS
.
Model
bsaz
AKL-AIAP1 purr trajectory
HWIW-1,-22 purr trajectory
r.NAI1AI'-1
Mf.SDPMrr' pufr trajectory
IIESIII'LIIME* olume senment
trajectory
1 ,AS1HAP5 statistical
[pj trajectory
AII!51IX purr trajectory/
vert ical • Tinite
dirrerence
MISU Clill/' qrid
Uescr ipt ion
Avcraqinn 1 ime
daily to yearly
daily to yearly
dai ly to yearly
daily to yearly
monthly lo yearly
dai ly to yearly
daily to monthly
Heiiinvnl I'roi.'ess
rirst order wet
and dry removal
first order wet 5(1
and dry removal
I'irst order Sll
dry removal
first order 5
dry removal
diurnal and seasonal
dependent dry removal
Tirst order wel removal
rirst order wet
and dry removal
first order wet
and dry removal
Chemical I'rucess Pollulanl Species
none Inert Substances
2 first order decay 502 and 50^
2 firr.l order decay 502 and SO:
1*2 first order decay 5(12 and SO:
diurnal and seasonal 502 anf^ ^n
dependent 5112
firsl order dacay
502 first order decay 502 ""^ 50;
typically S02 first 502 and SOj
order decay
Reference
Merrier et al. (1975)
Merrier (11HM)
.Inhnson Rt al . ( 197H)
Manciiso et al. ( 1979)
Hliumralknr ( 19(1(1)
lienkley and Mass ( 1979a)
Renkley and Mass ( 1979h)
Shannon (197'')
Shieh (1977)
Meyers et^ al. (1979)
Morris et al. (1979)
1 see also model hy Start and Wendell (1974).
2 r.ne alr.o models hy Eliasen (197B), Nnrdo (1976)
arid lliasen and Saltbones (1975).
5 r,ei! alr.o models hy Draxler (1977, 1979).
4 see alr.n models hy McNaiinhton (19HII). Hales el al . (1977)
I'enderriar.l (1979) and llciuni (19HO).
^ r.ee alno models hy llolin and I'nssnn (1975),
Fislii-r (1975, 197H) and Scrivrn and F ir.linr (1975).
fl uee alr.n models hy tui and Durran (1977), Hao pi al . (1976),
l.avery el al . (-191111) and Carmicliael and Peters (1979).
-------
rawinsonde network provides vertical wind speed and direction, temperature, and moisture
profiles every 12 hours at seventy sites across the continental U.S. This provides upper-level
winds at a horizontal resolution of the order 400 kilometers, considerably less resolved
than the 20 to 80 kilometer grid spacing required in air quality simulation modeling techni-
ques. Increased temporal resolution in upper level winds should also diminish tranport predic-
tion uncertainties.
6.5.3 Model Evaluation and Data Bases
The evaluation/verification of long range transport models through comparisons of model
predictions with observation has been almost nonexistent. The major deterent has been insuffic-
ient or in many cases, inappropriate monitoring data for the spatial scales of interest. Long
range transport models predict ambient pollutant concentrations that are representative of
horizontal spatial averages of the order of 10-3 square kilometers. Standard monitoring
networks, established for local high level concentration measurements within the vicinity of
the emission sources do not provide representative data for long range models. Some routine
monitoring data for S0£ and S04 from the EPA Storage and Retrieval of Aerometric Data (SAROAD)
system has had some utility in model testing (Bhumralkar, 1980) but in general has proven less
than adequate. The SURE air quality network (Perhac, 1978) which operated over the period
August 1977 to October 1978, has provided to date the most extensive S02 and $04 data base
for long range transport model evaluation. But even these data collected over this limited
period are only sufficient during the intensive study periods, August 1977, October 1977,
mid-January to mid-February 1978, April 1978, July 1978 and October 1978, when an extend-
ed 54 site monitoring network was activated. During the SURE study period, data also exist
from the MAP3S precipitation chemistry network (MacCracken, 1978) which had at least four
sites operational during the program. No dry deposition data are available for the study
period. Since the data have only recently become available, they have had limited use, but
future long-range transport model evaluations are certain to consider their use.
Another limitation in model evaluation studies is the quality of the emission inventory.
Until recently a national gridded emission inventory did not even exist. Clark (1980) prepared
on annual gridded emissions inventory for the United States and Southern Canada east of the
Rocky Mountains utilizing data compiled by the U.S. Environmental Protection Agency and the
Ontario Ministry of the Environment and Environment Canada. In preparing the gridded inven-
tory, he found significant errors in many of the U.S. point source records which had to be
corrected. Models, like chains, are only as strong as their weakest link. Certainly emission
inventories must be viewed as candidates in this role.
As mentioned at the outset, long-range transport model evaluations are extremely limited,
but two recent studies should be noted.
Mancuso et al. (1979) evaluated a trajectory puff model using monthly averages from the
OECD monitoring program. They generated two sets of evaluation results. The first considered
6-35
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model predictions versus observations using parameters originally specified for the model.
This resulted in root mean square (RMS) differences of 12.9 and 4.8 ug/m3 for $03 and $04,
respectively. In the second evaluation, half of the data was used to optimize model parameters
through a regression analysis technique and then the remaining half of the data was used to
evaluate the model. This resulted in RMS differences of 7.7 and 2.9 yg/m3 for S02 and $04 and
correlation coefficients of 0.72 both for S02 and $04, a marked improvement in the model's
performance. None of the optimized parameters assumed values which were physically unrealistic.
Lavery et al. (1980) evaluated a grid model using data from the SURE monitoring network and
based on 24-hour averaged concentrations. Four days were selected for parameter "adjust-
ments" and "fine tuning" and additional three days were used for the model evaluation. RMS
differences for SO? ranged from 6.9 to 23.4 \i g/m3 for the three days, with a mean value of
14.1 yg/m3. RMS differences for S04 ranged from 5.2 to 14.4 yg/m3 with a mean value of
9.3 ug/m3. Mean correlation coefficients for S02 and $04 for the three days tested were
0.31 and 0.53, respectively.
Overall, the results from both models are encouraging. Evaluation of a trajectory puff
model for the U.S., Bhumralkar (1980), using the SURE data base is also showing promising
results.
6.5.4 Atmospheric Budgets
Atmospheric budgets have proven a convenient technique for evaluating on a quantitative
basis the overall source and sink contributions of specified pollutant species within a select-
ed region of interest. The budget is formulated by estimating the various input and output
processes associated with the region, as anthropogenic and natural emissions, pollutant concen-
tration inflow and outflow, and wet and dry removal. Budget analyses provide a general
indication over the long-term of the significant factors contributing to the pollutant burden
in a given region. Sulfur budgets have been of greatest interest both in Europe, Rodhe (1972,
1978), Garland (1978) and in North America, Galloway and Whelpdale (1980), primarily due to
sulfur's association with the acid precipitation phenomenon. Conclusions drawn from the
eastern North American sulfur budget by Galloway and Whelpdale (1980) were that man-made
emissions exceed natural ones by a factor of 10; wet and dry deposition over the region are
approximately equivalent; and at least one-quarter of the emissions leaves the region via the
atmosphere to the east. As with western Europe the North American budget showed that man's
activities dominates the regional atmospheric sulfur cycle.
6.6 SUMMARY
The processes governing the transport and diffusion, chemical transformation and wet and
dry removal of sulfur dioxide and particulate matter in the atmosphere are extremely complex
and not completely understood. The oxidation rates of S02 observed in industrial plumes and
urban atmospheres range from 0-15% h'l and would seem to be only partially accounted for
through homogeneous gas phase reactions. Liquid phase catalytic oxidation reactions involving
Mn and carbon are possible contributing sources to the observed oxidation rates, but further
6-36
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research is required to quantify these processes under typical atmospheric conditions.
The dry deposition of S02 is fairly well understood as a result of extensive measure-
ments over various canopies. Particle dry deposition has focused more on the physical aspects
of the deposition process, that is the aerodynamic and has very little supportive measurement
data on particles with compositions typical of those found in the polluted atmosphere.
Our understanding of the wet removal of S02 has progressed considerably in recent years,
including the consideration of solution phase chemistry within rain droplets. While particle
removal, as with gases, is extremely dependent on the physical characterization of the precipi-
tation events which may in many instances be the determining factor in accurate wet removal
prediction.
The characterization of the dynamics of the planetary boundary layer is essential to an
adequate understanding of pollutant transport and diffusion over all spatial scales. Though
considerable advances have been made in this area, our ability to predict mean transport and
diffusion over long distance scales is less than adequate. This in part is due, no doubt, to
the sparse spatial and temporal resolution of the upper air wind observation network used
to generate the transport winds.
Present generation long range transport air pollution models consider simple parameteriza-
tion for chemical transformation and wet and dry removal, and varying degrees of sophistication
in the treatment of transport and diffusion. None of the models adequately treat the dynamics
of the planetary boundary. Evaluations of long range transport models, though limited because
of lack of data bases, have shown that with further research and development these models
should prove to be adequate tools in addressing air pollution issues associated with the
movement of pollutant emission over long distance scales.
6-37
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*
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