-------
The dependence of these rates on cloud liquid water content are examined
later. Employing these concentrations at a temperature of 278 K and pH
of 5.0, yields characteristic oxidation times for S(IV) of: 0.93 hr
(Mn), 0.19 hr (Fe), and 0.01 hr (Mn + Fe) . The corresponding conversion
rates are ~ 100 percent hr-1 (Mn), 500 percent hr"1 (Fe), and ~
5 x 103 percent hr~l (Mn + Fe) . These values certainly suggest that
the catalyzed reaction will be considerably important, at least in urban
air. However, a word of caution is required.
It is not clear that the Mn rate or the mixed catalyst rate Barrie
and Georgii measured can be extrapolated to the atmospheric case.
Barrie and Georgii observed negligible oxidation with 10"6 mol a~l
of Mn as a catalyst. No clear evidence shows that the mixed catalyst
effect occurs at concentrations below 10~5 mol £-1. Furthermore,
these estimates have yielded rates that produce substantial ^$04 in
solution relative to initial concentrations of SO/j. One would
therefore expect the solution pH to drop substantially. Given the
inverse square dependence on FT concentration of the SOs2" concen-
tration in solution, the rate expressions for the catalyzed (and the
uncatalyzed as well) reactions suggest they may be self limiting in
hydrometeors. Hence, the rates calculated above from the characteristic
times, based on initial pH's, will be upper limits to the time-average
rates. Finally, the mixed catalyst rate is so fast that it will be
almost certainly limited by mass transport, even in raindrops of modest
size, as suggested by Freiberg and Schwartz (1981).
4.3.5.3 Homogeneous Non-aerobic Oxidation of SO?'H?0 to
H?so4--SQ2 absorbed into atmospheric hydrometeors can be oxidized
by oxidants other than 0. Indeed, recent work on H2$04 production
in clouds and rain has tended to emphasize the oxidation rates by 03
and H202 (Penkett et al. 1979, Durham et al . 1981). Recently,
interest has also revived in the classic reaction involving SOa^"
oxidation by N(III) in solution (Martin et al. 1981, Chang et al . 1981).
Of these three oxidants, 03 has been the most widely studied, and will
therefore be examined first.
The relevance of 03 to SO^2- formation in hydrometeors was
first examined by Penkett (197?), who studied S032' oxidation by
03 in a stopped- flow reactor at a solution pH of 4.65 and a
temperature of 283 K, values representative of the atmosphere. However,
the reactant concentrations employed were far higher than those
encountered in the atmosphere. More recently, several other studies
have been conducted on the 03 reaction with reactant concentrations
closer to those in the atmosphere. These studies are summarized in
Table 4-15. The study by Penkett et al. (1979) contains a number of
errors in the derived rate expression. It is therefore preferable to
show the rate expression derived by Dasgupta (1980a) from the data of
Penkett et al. However, the rate for atmospheric conditions (last
column in Table 4-15) is that directly measured by Penkett et al.
4-48
-------
TABLE 4-15. LABORATORY STUDIES OF S(IV) OXIDATION BY 03 IN AQUEOUS SOLUTION
Rate expression
Experimental
PH
Molar ratio of
reactants
Reaction rate3
(1n mol J.'1 s"1)
at 278 K, 1 ppb S02
40 ppb 63, and a
pH of 5.0
Penkett (1972)
Barrle (1975)
k![03][HS03-]
ki = 3.3 x 105 a mol'1 s'1
at 283 K
4.65
4.0
0.03 - 0.5
10-6-5 x ID'5
1.5 x 10-9
5 x 10-llb
EHckson et al .
(1977)
Larson et al .
(1978)
Penkett et al.
(1979) as
modified by
Oasgupta
(1980a)
k2[03][HS03-] + k3
[03][S032-]
k2 = 3.1 x 105 «. moT1 s'1
k3 = 2.2 x 109 a mol'1 s'1
at 298 K
k4[03][HS03-] [H+]-0-1
k4 = 4.4 x 10* j>0.9 mo1-0.9 s-l
at 298 K
k2[03][HS03-] + K3
C03][S032-]
k2 = 3.73 x 105 4 moT1 s"1
k3 = 3.12 x 108 i. moT1 s-1
at 298 K
-1.3 - 4.02 5-50 2 x 10'7
4.0-6.2 6 x 10-4 5 x 10'10
-2 x ID'3
1-5 0.1 - 0.4 6.6 x 10-9
aShows derived rates for atmospheric conditions.
bThe measured rate at pH = 4 and 283 K was converted to that at pH = 5 and 273 K by assuming that the
rate 1s proportional to [HS03-]> and changes negligibly with temperatures over 5 K.
-------
Examination of rates shown in Table 4-15 suggests nearly as much
uncertainty about the 63 oxidation rate as for uncatalyzed aerobic
oxidation. Rates tend to increase as the ratio of 63 to S(IV) in
solution increases, suggesting that oxidation rates measured in the
laboratory were limited by mass transport of (h. However, 03
concentrations in solution were measured directly in experiments of
Penkett et al., thus precluding any limitations due to mass transport.
In any case, the mole ratios of 03 to S(IV) used in the studies with
the higher derived rates are far above atmospheric values (~ 10~4).
Because the rates derived for atmospheric conditions from measurements
of Penkett (1972) and Larson et al. (1978) differ only by a factor of 3,
despite extrapolations over several orders of magnitude in reactant
concentrations, the higher of the two rates (Penkett 1972) has been
selected to estimate the importance of this reaction in ^$04
production in hydrometeors. While the relatively conservative nature
(compared to the upper end of the range in rates given in Table 4-15)
of this estimate should be considered, Hegg and Hobbs's (1981b)
observations discussed in Section 4.3.5.1 cast doubt on the applica-
bility to the atmosphere of the higher rates shown in Table 4-15.
Table 4-15 shows that the characteristic time for S(IV) oxidation
is ~ 1 hr for the Penkett rate, and the conversion rate is ~ 100
percent hr-1, which should be significant in the atmosphere.6
It has been proposed (Penkett et al. 1979) that the 03 reaction
mechanism is a free-radical chain, similar to that of the 0? oxidation
reaction. If so, like the aerobic oxidation, it should be both
catalyzed and inhibited'by certain trace metals and organics in solution
(Hegg and Hobbs 1978). Interestingly, Barrie and Georgii (1976)
reported a substantial enhancement in sulfite oxidation rate by 03
when Mn ions were present at roughly 10-5 moi £-1. However, no
data or discussion of this result was given, and only recently has a
study of the catalyzed 03 reaction appeared in the literature. This
study, by Harrison et al. (1982), found that Mn and Fe on the order of
10-3 jnol £-1 enhance the oxidation rate, though over a relatively
narrow pH range centered at ~4.4. The maximum enhancement is roughly
a factor of 2 for Fe and about 5 for Mn. Given the large uncertainty in
the uncatalyzed 03 rate, and that at a pH of 5.0 the Mn and Fe
enhancements were negligible for Fe and about a factor of 3 for Mn at
the high concentration of 10~5 mol £-!, this rate will be
considered indistinguishable from the uncatalyzed rate already
discussed.
6The characteristic or e-1 folding time is given by
1 _ d S(IV)"1
(S(IV) eft ; in the atmospheric pH range of ~ 3 to 6, HS04-
1 _ d S(
-S(IV) and this becomes: [HS03-J ~3t
4-50
-------
Oxidation by H202 has only recently been considered important
for acid production in hydrometeors. While early laboratory work on
this reaction was done by Mader (1958), the first study relevant to the
atmosphere was reported by Hoffmann and Edwards (1975). Penkett et
al.'s (1979) study essentially repeated the study of Hoffmann and
Edwards, with explicit extrapolation to atmospheric conditions. Martin
and Damschen (1981) have attempted to integrate all extant measurements
on the reaction within the framework of the nucleophilic displacement
mechanism, first advocated by Hoffmann and Edwards. While this approach
has the advantage of producing both a simple and widely applicable rate
expression, it is not yet clear whether all the objections Dasgupta
(1980a,b) raised to the Hoffmann and Edwards mechanism have been met.
However, from the point of view of this document, details of the
mechanism are unimportant as long as a rate expression is available that
can plausibly be applied to the atmosphere. In this regard, the
relatively simple rate expression derived by Martin and Damschen is
adequate and appealing. It is:
= k [H202] [S02.H20] [4-94]
dt
with k = 8.3 x 105 a mol'1 s"1 at 298 K and an activation energy
of ~ 28 kJ mol'1 (Martin et al . 1981).
This expression is independent of pH for a constant S02 partial
pressure. However, as the pH of the solution increases, less and less
S(IV) in solution will be in the form of S02«H20. Thus, the
effective S(IV) oxidation rate decreases rapidly with increasing pH.
Before the above rate expression is employed, the H202
concentration to be used must be determined. Many recent calculations
of the importance of the H202 oxidation reaction have employed
gas-phase H2Q2 concentrations of 1 ppb or greater (based on actual
measurements) and a value of the H202 Henry's law constant, based on
H20o vapor pressure data (Scatchard et al. 1952) taken under
conditions far removed from atmospheric. While the rather careful
extrapolations on such data appear plausible, they cannot be applied
directly to atmospheric conditions. For example, Martin and Damschen
calculate a value for the Henry's law constant of 6.07 x 10$ mol
r1 at 273 K. At 273 K, 1 x 10-9 atin H2Q2 is equivalent to
4.46 x 10-8 mol nr3 of H202. For a cloud water content of 0.5 g
m-3, and assuming all of the H202 goes into solution, the
resultant concentration would be only 8.9 x 10~5 mol £-1, close to
an order of magnitude less than the concentration predicted by the
Henry's law constant. Hence, as was the case for several of the strong
acids, the H202 concentration in solution cannot be based on Henry's
law equilibrium. Furthermore, H202 is reactive in solution with a
variety of organic and inorganic species (Ardon 1965) that could rapidly
deplete it without producing acid. Kok (1980) found concentrations of
H202 in precipitation considerably lower than those predicted for
Henry's law equilbrium. Because of this uncertainty in the value of the
4-51
-------
concentration in hydrometeors derived from gas-phase measure-
ments, values derived from direct measurements of this species in rain
and cloud water (Kok 1980, pers. comrn.) will be employed. The value
selected Is 0.5 ppn or ~ 1.5 x 10~5 mol A-l. Employing this
value in the Martin and Damschen rate expression for atmospheric
conditions results in a characteristic time with respect to S(IV)
oxidation of 0.14 hr at a pH of 5.0, which yields a highly significant
conversion rate of 700 percent hr'1- Indeed, this rate is high enough
that limitations due to mass transport are likely to be important for
larger hydrometeors.
The last oxidant considered in this section is N(III) (i.e., either
N02~ or HN02 in solution). The reaction(s) between N(III) and
S{IV) species in solution has been known for many years because it was
integral to the old lead-chamber process for producing ^$04
(Duecker and West 1959, Schroeter 1966) and remains considerably
important in flue-gas scrubbing technology (Takeuchi et al. 1977).
Because NOJs and S02 commonly coexist in polluted air, several
recent studies have attempted to evaluate the possibility of a
significant aqueous reaction between these two species (Nash 1979, Chang
et al. 1981). Oblath et al. (1981) and Martin et al. (1981) have
presented explicit rate expressions they use to evaluate the reaction's
significance in the atmosphere. The Oblath et al. study contains
considerably more information on the conversion mechanism. Furthermore,
it was conducted in the pH range of 4.5 to 7.0, whereas Martin et al.'s
was conducted at pH's less than 3.0. On the other hand, the sulfite and
nitrite concentrations employed by Martin et al. were closer to
atmospheric levels than were those used by Oblath et al. Also, Martin
et al.'s rate expression is relatively simple and easily applied to
atmospheric conditions. In any case, the two rates agree within a
factor of 3 at pH's near atmospheric. Therefore, Martin et al.'s
expression will be employed as a significance test. This expression is:
HP ^n ~\
* = kl[H+]l/2 {[HN02] + [N02]}{[S02.H20] + [HS03] } [4-95]
dt
with ki = 142 £3/2 moT3/2 s"1 at 298 K. No activation energy
was determined by Martin et al. (nor by Oblath et al. for atmospheric
conditions); it will be assumed to be negligible. Employing this rate
expression with the appropriate values of N(III) from Section 4.3.2
yields a characteristic time with respect to oxidation of S(IV) of 70 hr
for urban conditions. This reaction's importance to the H2S04
production in hydrometeors is therefore negligible.
Finally, we note that, based on their interpretation of the data of
Takeuchi et al. (1977), Schwartz and White (1982) have suggested that
aqueous N02 may oxidize S(IV) at a significant rate under somewhat
polluted conditions. However, more work must be carried out on this
reaction before its atmospheric significance can be assessed.
4-52
-------
In closing this section, it should be noted that aerobic oxidation
of sulfite is subject to inhibition by numerous atmospheric constituents
(Hegg and Hobbs 1978). Presumably, the same will be true of the 03
reaction, if it is in fact produced by a free-radical chain mechanism.
Furthermore, both 63 and ^02 are highly reactive in water and can
suffer either catalytically or photochemically induced decay. The rates
discussed do not account for such inhibition or decay. Therefore, in
some cases these rates may overestimate those in the atmosphere.
4.3.5.4 Heterogeneous Production of H2S04 in Solution—Few
heterogeneous reactions in solution Tiave been proposed for H
production. The only such reaction that has been studied extensively is
the oxidation of S(IV) on graphitic carbon suspended in solution
(Brodzinsky et al . 1980, Chang et al . 1981). Before this reaction is
discussed in detail, heterogeneous reactions involving metal oxides are
discussed briefly, prompted by the fact that many trace metal catalysts
commonly invoked for homogeneous oxidation of S032~ occur in
relatively insoluble form in the atmosphere. Heterogeneous oxidation
processes involving trace metals could therefore be of some importance.
Certainly, gas-solid heterogeneous reactions involving trace metals are
treated extensively in the literature on atmospheric S042~
production (Urone et al . 1968). However, in solution, only one such
reaction appears to have been examined: the study by Bassett and Parker
(1951) of the oxidation of S032" to H2S04 by various oxides of
Mn. While not a quantitative rate study, this work suggests that
substantial H2S04 can be produced by this reaction relative to
aerobic oxidation, at least for high concentrations of metal oxides.
Recent modeling studies of the heterogeneous carbon- sulfite
reaction have concluded that this reaction may play an important role in
sulfate production in water films on atmospheric particles (Middleton et
al. 1980, Chang et al. 1981). Both studies emphasize that the reaction
would require quite low pH solutions and a long reaction time to be
competitive with other sulfate production mechanisms. The rate
expression of Brodzinsky et al. (1980) is employed to evaluate the
significance of this reaction for H2S04 production in atmospheric
hydrometeors:
= k [Cx] C02] ' g [S(IV) ] _ [4-96]
_
dt (i + &[s(iv)] + a[s(iv)]2)
where k = 1.69 x 10~5 mol -03 £°'69 g"1 s'1, a = 1.50 x 1012 £2 mol~2,
3= 3.06 x 10° x, ml"1, [Cx] = grams of carbon per liter, and [0?] and
LS(IV)] are in molar concentrations. The activation energy of the reaction
is given as 48 kJ mol~l.
It should be noted that the graphitic carbon used to derive
Equation 4-96 was Nuchar C-190, a commercial product with a well -
characterized elemental composition and BET surface area (550 m2
g"1). However, soot generated in various combustion processes (i.e.,
combustion of acetylene, natural gas, and oil) was also employed. Chang
et al . (1981) report an average Arrhenius factor five times larger for
4-53
-------
these soots than for Nuchar-90. This higher value will be employed in
these calculations. Another novelty concerning Equation 4-96 is that it
is nonlinear in [S(IV)] and therefore has characteristic times that are
functions of the concentration of S(IV). Finally, use of Equation 4-96
requires an estimate of the graphitic carbon concentration in
hydrometeors. A recent direct measurement of elemental carbon in
rainwater collected in Seattle that was 2.4 x 10-4 g £-1 (Ogren
1980) has been employed. All of the elemental carbon is assumed to act
as an efficient catalyst.
Assuming a temperature of 278 K, a cloud water pH of 5.0, and an
urban S(IV) concentration in solution of 7.9 x 10~5 mo! a~^t the
rate expression of Brodzinsky et al. yields a characteristic time for
S(IV) oxidation of ~ 103 hr. Therefore, this reaction should be of
little importance in H2S04 production in precipitation, although it
might be important in Togs of low liquid water content in urban areas.
4.3.5.5 The Relative Importance of the Various H?S04 Production
Mechanisms--!n sharp contrast to HC1 and HNOg production in
hydrometeors, numerous reactions are capable of producing significant
levels of H2S04 in solution. It is therefore important to assess
the relative magnitudes of these reactions under differing atmospheric
conditions. To do this, two relatively extreme cases that can produce
precipitation are considered.
Much has been made of production of acid in mists and fogs, which
is of some importance from the standpoint of $0^2- production in the
atmosphere. However, it is of little consequence to acidic deposition
because even a modestly precipitating cloud will deposit far more acid
on the ground than will a fog. As an example of a "polluted" case, a
low-lying stratus cloud in urban air with a liquid water content of ~
0.1 g nr* (about the lowest liquid water content that can produce
precipitation in a warm cloud) is considered. HoS04 production by
0? (catalyzed and uncatalyzed), by 03, and by HgO^ oxidation of
SlIV) in solution is considered. Values of the various parameters to be
employed are given in Table 4-16. The value for the partial pressure of
03 is based on numerous measurements in urban air, the concentration
of H202 is derived from Kok's (1980) measurements, and the cloud water
pH range is based on measurements reviewed by Falconer and Falconer
(1979). The mechanisms considered have different pH dependencies, so
the production rates over the pH range of polluted clouds must be
considered.
Figure 4-4 plots the production rates for the various oxidants.
The ^2 reaction dominates HpS04 production in polluted clouds,
with the possible exception of the upper end of the pH range (where the
rather speculative mixed-catalyst rate becomes comparable to that of
H202).
We next consider a more typical mid-level cloud (at the ~ 800-mb
pressure level) with a more substantial liquid water content of ~ 1 g
nr3, situated in a moderately industrial region. The parameter values
4-54
-------
TABLE 4-16. VALUES OF PARAMETERS USED TO ESTIMATE
H2S04 PRODUCTION IN A POLLUTED CLOUD
Parameter Value
Partial pressure of H2S04 1 ppb
Partial pressure of S02 50 ppb
Temperature 288 K
Cloud liquid water content 0.1 g m-3
pH of cloud water 3.5 - 4.5
Partial pressure of 03 100 ppb
Concentration of H202 4.7 x 10-5 mol
Concentration of Mn 10-6 mo-| £-1
Concentration of Fe 10-6 mo] $,-1
4-55
-------
-1 -1
PRODUCTION RATE OF H2$04 (Mole Is)
f
tn
O>
cu ro
3 CO
IQ O
o
-a CL
o c
— ' O
c+ O
n> 3
D-
O CD
S--K °
I" 2 -"
-s oo
S g
o
X
Q.
O>
3
C/l
o
ro
r+
3-
ro
-------
used in this case are listed in Table 4-17. The pH range is again
derived from Falconer and Falconer (1979) and the HoC^ concentrations
from rainwater measurements by Kok (1980). The metal concentrations were
estimated by employing typical (rather than peak) metal concentrations
in clear air, divided by the cloud liquid water content given in Table
4-17, using the same percent solubilities as previously employed. The
resultant low metal concentrations preclude consideration of catalytic
oxidation by Mn or Mn plus Fe. Because some experimental support exists
for Fe-catalyzed oxidation at these levels (Brimblecombe and Spedding
1974), it is considered here.
Figure 4-5 plots the rates for the oxidants considered. While the
H202 reaction again appears to be the single most important reaction
over much of the pH range, the most striking result revealed by Figure
4-5 is that all of the oxidants can contribute significantly to
H2$04 production above a pH of ~ 5.2. Of course, this result is
quite sensitive to the concentration of Ho02 employed; further data
on this important parameter would be highly desirable. Nevertheless, it
is important to note that, on the basis of available field data and rate
studies, no one oxidant dominates H2S04 production in all
atmospheric situations.
Figures 4-4 and 4-5 show the time scale for acid produced in
solution to reach the concentration produced by direct absorption of
gases into cloud drops. This important point was approached in the
derivation of the S(IY) conversion rates necessary to produce
significant acid in solution. However, Figures 4-4 and 4-5 allow a more
precise estimate.
The maximum concentration of directly absorbed h^SOA in an
urban polluted cloud should be ~ 4.2 x 10-4 moi a-l (based on
the H2$OA and cloud water concentrations in Table 4-16, 1 ppb and
0.1 g m-3} respectively). For a mid-level cloud, the maximum
H2$04 concentration should be 4.4 x 10~6 mol £-1 (based on the
values for H^SO* and cloudwater in Table 4-17: 0.1 ppb and 1 g
nr3, respectively). These concentrations would be reached by the
Ho02 reaction alone in ~ 3 min for both urban and mid-level clouds
if the H202 were undepleted. With depletion, the time dependence of
H2S04 production is more complex, which is shown in Figures 4-6 and
4-7 for the urban and mid-level clouds. For an urban cloud (Figure
4-6), H2S04 production is dominated by H202 oxidation until the
H202 is completely depleted after about 2 min. Thereafter,
H2SO~4 production is maintained by catalyzed aerobic oxidation at a
much slower rate (solution pH is assumed to be 4.0). Indeed, it would
take roughly 41 min for the ^$04 produced in solution to reach the
concentration of the ^804 directly absorbed. In a mid-level cloud
(Figure 4-7), the ^2 concentration, even with depletion, is
sufficient to produce concentrations of H2S04 equal to those
produced by direct absorption in about 4.5 min. However, if the
solution pH is assumed to be in the upper half of the range listed in
Table 4-17, oxidation by 02 and 03 produces sufficient additional
H2S04 to reduce this time to ~ 1 min. These results suggest that
4-57
-------
TABLE 4-17. VALUES OF PARAMETERS USED TO ESTIMATE
H2S04 PRODUCTION IN A MID-LEVEL CLOUD
Parameter Value
Partial pressure of ^$04 0.1 ppb
Partial pressure of S02 5 ppb
Temperature 278 K
Cloud liquid water content 1 g m~3
pH of cloud water 4.5 - 6.0
Partial pressure of 03 40 ppb
Concentration of H202 5.9 x 10-6 moi
Concentration of Mn 2 x 10~9 mol j
Concentration of Fe 3.3 x 10~8 mol
4-58
-------
-1 -1
PRODUCTION RATE OF H2$04 (Mole 1 s )
-p.
cn
03
CD
en
-s re
o> ro
3 on
ia o
o -a
-h -s
o
3 Q-
o. o
I r+
fD O
< 3
a>
Qi
O r+
— i (V
O
C
Q- -+i
(/) O
• -s
o>
o
E
1/5
O
X
Q.
3
<-h
(Si
O
05
-S
r+
(T)
•o
O
MD
O
I
DO
CX5
cn
C/)
o 01
i— •
c ro
cn
cn
•
CT>
cn
•
00
-------
-1
CONCENTRATION OF H2$04 (Mole 1 )
to
c
-^
cr>
o 3
c n>
CL
o.
• — - fD
o -a
— i fD
O 3
C Q-
CL fD
S O
Q> 05
r+
fD O
-a
ni
M o
33 3
• Q. 3
o
3
cu
3
-s
cr
a>
-a
o
-------
1
CONCENTRATION OF H2$04 (Mole 1 )
-------
not only the rate, but also the pH dependence of the HpSCk
production in solution, will depend on the H202 concentration and
the pH, because these two parameters determine how much of the.H2S04
produced in solution is due to the non-pH-dependent H202 reaction
and how much to the other highly pH-dependent reactions.
One final point is suggested by Figures 4-6 and 4-7. The rates
shown in these figures produce substantial quantities of acid in a
relatively short time. Furthermore, a major component of this
production is a pH-independent reaction (^0? oxidation) that will
not be self-limiting in the usual sense of the term. If absorbed
concentrations of H2$04, HN03, and HC1 are considered as well,
within a few minutes of cloud formation, cloud water pH's in urban air
might be expected to reach a value of 2.0 or even lower. Because such
low pH's are not observed and because the anion levels predicted by
direct absorption and the rates shown in Figures 4-5 and 4-6 are similar
to those observed in urban precipitation (Larson et al. 1975,
Liljestrand and Morgan 1981), acid neutralization must play a role.
4.3.6 Neutralization Reactions
4.3.6.1 Neutralization by NH3--Probab1y the most important single
neutralization process in the atmosphere is the absorption-hydration of
NH3 by acid aerosols and hydrometeors and, in the case of
hydrometeors, the subsequent dissociation reaction:
iq = [NH4OH]
[NH4OH] = [NH4+] + [OH"] [4-97]
The preeminence of this neutralization process arises because HN3
is the only basic gas of widespread, substantial occurrence in the
atmosphere. The hydration and dissociation reactions are generally
assumed to be fast compared to acid production reactions in solution
(Scott and Hobbs 1967, Beilke and Gravenhorst 1978). Therefore, the
concentration of NH^ (and consequently OH~) is given by the
equilibrium expressions for NH3 absorption and dissociation in
solution.
This appears to be the case even for the fastest of the reactions
shown in Figures 4-3 and 4-4. For example, the H202 reaction in
urban air produces ~ 2.3 x 10-6 mo! s,"1 s'1 of ^$04, or
9.6 x 10"1° mol s~l in a 10 ym radius droplet. If a background
concentration of NH^ of 1 ppb (Levine et al. 1980) is assumed, the
rate of NH3 scavenging due to collisions with a 10 ym droplet will
be 8.25 x 10-15 mol s-le
Recent work by Huntzicker et al. (1980) suggests that the reaction
coefficient for the collisions will be close to unity for acidic
droplets 10 ym in radius. In this case, the collision frequency
becomes the rate of NH3 delivery to the droplet. The NH3 is
4-62
-------
hydrated virtually instantly in solution, and the product ammonium
hydroxide (NH40H) dissociates with a rate constant of kd = 6 x 10
s-1 (Eigen 1967). Thus, after ~ ICT6 s, the rate of OH~
production equals the collision frequency and NH3 neutralization will
not be transport limited. It is therefore possible to estimate the
NHA+ concentration (and the associated OH~ concentration) in
solution from equilibrium considerations, even for these fast reactions.
When the equilibria are employed for an NH3 solution, NHAOH
dissociation and water dissociation, the concentration of NH^ in
solution is given by:
[NH4+] = Ha pa Ka [H+] [4-98]
Kw
where Pa is the partial pressure of NH3, Ha the Henry's Law
constant for NH3, and Ka and Kw the equilibrium constants for
NfyOH and H20 dissociation, respectively.
Recent measurements of ambient NH3 concentrations range from 0.5
to 25 ppb (McClenny and Bennett 1980, Levine et al . 1980). While the
values for Ka and Kw are well known, recent work by Hales and Drewes
(1979) has suggested that the commonly accepted value for Ha of 55 mol
a~L atnr1 at 298 K is too high by about a factor of ~ 5 for
atmospheric hydrometeors (due to interaction between dissolved NH3 and
C02 at atmospheric concentrations). When this is taken into account,
the NH4+ concentration at 278 K is given by:
[NH4+] - 3.3 x 1011 Pa [H+3. [4-99]
is yields a range of NH4+ concentrations from 1.65 x 10~4 to 0.8
l r1. Thus, 1.65 x 10'4 to 0.8 equivalent of acid could be
Thi
mol
neutralized by NH3 alone. However, a word of caution is in order.
While concentrations of NH4+ found in cloud water lie toward the
lower end of this range (Petrenchuk and Drozdova 1966, Sadasivan 1980,
Hegg and Hobbs 1981a) , most rainwater samples have substantially lower
NH4+ concentrations than are predicted by the above calculations
(Lau and Charlson 1977). While this discrepancy is well known, it
remains unresolved.
4.3.6.2 Neutralization by Particle-Acid Reactions—Reactions between
strong acids produced in hydrometeors and particles incorporated into
these hydrometeors by scavenging (either nucleation or below cloud
scavenging) are well known. But these generally have been considered
from the standpoint of initially alkaline droplets produced from, say,
sea salt nucleation acidified by absorption or production of strong
acids (Robbins et al . 1959, Eriksson 1960, Hitchcock et al . 1980). The
initial "alkaline" salt for such a reaction is predominantly NaCl .
However, the widespread occurrence of Ca2+ in rainwater and the
fact that calcite (CaCOs) and dolomite (CaCOs'MgCOs) are often
4-63
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substantial components of the atmospheric aerosol have led to the
assertion (Winkler 1976) that these minerals will act to neutralize
H2S04 in hydrometeors via the substitution reaction:
CaC03 + H2S04 = CaS04 + H2C03. [4-100]
The relative weakness of carbonic acid ensures that this reaction
produces a net decrease in acidity. Certainly, CaS04 has been
measured in significant quantities in urban atmospheres (Sumi et al.
1959, Kasina 1980), and Ca2+ and Mg2+ are known to be important
components of the ionic precipitation in the United States (Chapter
A-8). Therefore, observational support exists for this idea. Indeed,
Sequeira (1981) recently found that excess Ca in precipitation (in
excess of that attributable to sea salt and thus of soil origin)
correlates much better with excess sulfate than does NH3, and that Ca
and Mg concentrations in precipitation are often more than sufficient to
offset observed SOd2" loadings. Sequeira also suggests a role for
calcium oxide (CaO) derived from fly ash as well as for CaC03 and
MgC03. The interesting point about these three minerals is their low
solubility in water (e.g., compared to sea salt) and their increasing
solubility with increased acidity. They may, threfore, act as
hydrometeor buffers in the atmosphere, much like N03- The absolute
amount of Ca and Mg available for such buffering is highly variable,
with Ca ranging from lO"'' to 10~4 mol £-1 and Mg fairly
uniformly a factor of 5 to 10 lower in both rainwater and cloud water
(Petrenchuk and Orozdova 1966, Hendry and Brezonik 1980, Sadasivan
1980, Liljestrand and Morgan 1981). Clearly, Ca, at least, can
substantially contribute to acid neutralization in hydrometeors.
4.3.7 Summary
The three acids that dominate the acidity of precipitation are
H2$04, HN03, and HC1, in decreasing order of importance. The
methodology employed to assess the importance of their formation within
clouds and rain has been to compare the solution concentrations of these
acids produced by direct absorption of their respective acidic vapors
from the gas phase with those generated by plausible solution reactions
over the lifetime of the cloud and raindrops. If an aqueous-phase
reaction produced solution concentrations comparable to those resulting
from absorption, the reaction was considered significant. In cases
where several reactions were found capable of producing significant
concentrations of a particular acid, their relative importance has been
evaluated. Finally, because the potential acidity of precipitation far
exceeds that commonly observed, plausible aqueous-phase neutralization
reactions have been examined.
4.4 TRANSFORMATION MODELS (N. V. Gillani)
4.4.1 Introduction
Secondary products of chemical transformations of SOX and NOX
emissions are generally more acidic than their precursors. In the
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context of acidification of lakes, vegetation and soil, however, the
chemical form in which the deposition arrives at the surface is of
little significance, because precursor depositions are rapidly converted
to the secondary forms following deposition. The real significance of
atmospheric transformations in this case lies in the fact that the rate
of the deposition process itself depends strongly on its chemical form.
Thus, for example, sulfate particles are believed to have a considerably
longer average atmospheric residence than S02, and hence a larger
range of impact. Nitric acid, on the other hand, is likely to be
removed from the atmosphere more efficiently and rapidly than its
precursors. Consequently, it is necessary for transport deposition
models to distinguish between primary and secondary pollutants, and to
facilitate atmospheric chemical transformations through appropriate
modules.
The chemical transformation module is an integral part of the
overall transport-transformation-removal model. The framework within
which the larger model is formulated and solved may be Lagrangian
(trajectory), or Eulerian (grid), or some hybrid scheme (details in
Chapter A-9). Lagrangian or trajectory models simulate the changing
concentration field within a given polluted air parcel (e.g., a puff or
plume release) as a result of the combined effects of dilution,
chemistry, and depositions. Typically, the concentration field as well
as meteorological variables are assumed to be homogeneous within the air
parcel. Recent attempts have also been made to obtain simulations with
finer spatial resolutions within the air parcel. Lagrangian models are
tailored for simulations of pollutant kinetics at the plume scale.
Regional Lagrangrian simulations are commonly based on simple linear
suppositions of individually-calculated concentrations of multiple
plumes. Individual plumes may be referred to point sources or area
sources. For the modeling of nonlinear processes in multiple
interacting plumes over regional scales, Eulerian grid models are more
appropriate. They are based on the solution of coupled transport-
transformation-removal mass balance equations of individual species over
specified two- or three-dimensional spatial grids. Typical grid sizes
vary from 50 to 100 km to a side. Within each grid cell, pollutant
concentrations, as well as meteorological variables, are assumed to be
uniformly distributed. In a pure grid model, emissions within a grid
cell are considered in an aggregate sense, and are instantaneously
homogenized over the entire cell volume. The error of this
approximation is particularly severe in two-dimensional grid models
which lack vertical resolution. The effects of sub-grid scale processes
are sometimes included in terms of bulk parameterizations. Alternately,
a hybrid scheme may be used in which individual plumes may be modeled in
a Lagrangian sense and detail until they acquire the spatial dimensions
of the Eulerian grid size, and subsequent simulation is within the
Eulerian framework. The output from a grid model is an evolving series
of snapshots of the deposition field over the entire modeled region.
This is clearly very desirable in regional modeling. Grid models,
however, require far more extensive input information, computations and
computational resources than trajectory models, and are generally quite
expensive to implement. The chemical transformation module does not
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depend, per se, on the framework of the larger model formulation.
However, its validity does depend on the spatial-temporal resolution of
the simulation, and on the facility for accommodating nonlinear pro-
cesses and plume interacti-ons with its chemically different environment.
The remainder of this section is focused on the transformation module.
An objective of this section is to review and assess briefly our
present ability to predict the rates of chemical transformations of
primary emissions of SOX and NOX to secondary acidic products
(sulfates and nitrates) during atmospheric transport. Such predictions
are based on transformation models, which are mathematical formulations
relating secondary pollutant formation rates to concentrations of the
precursor gases (S02, NO), and to any other chemical and meteorolog-
ical factors considered to contribute to the transformation processes.
The principal approaches in formulating such models are discussed for S
and N compounds, for power plant and urban plumes, and for each of the
major conversion mechanisms believed to be important. Specific
formulations of practical interest are reviewed briefly along with their
applications, and major outstanding problem areas are identified. An
overall assessment is presented of our present standing in terms of the
desired goals of transformation modeling. Emphasis is placed on
formulations believed to be suitable for inclusion as transformation
modules in current long-range transport-transformation models aimed at
simulating regional-scale acidic depositions.
The atmospheric transformation processes are very complex,
involving multiple parallel pathways (mechanisms) of physical diffusion
and homogeneous and heterogeneous chemical reactions of a wide variety
of reactants and catalysts. The reactants may be of primary or
background origin or intermediate or secondary products of concurrent
reactions. A variety of meteorological factors--UV radiation,
temperature, relative humidity, clouds, fogs, atmospheric turbulence,
and others—also have important influence on atmospheric transformation
processes. Many of these factors are interdependent; e.g., UV
radiation, temperature, clouds, and turbulent mixing are closely related
to insolation. Furthermore, a given factor may simultaneously have
opposite effects on different chemical reactions; e.g., the effect of
plume dispersion should be to "quench" reactions between coemitted
species (Schwartz and Newman 1978), but also to promote reactions of
primary emissions with background species (Wilson 1978, Gillani and
Wilson 1980). Given the complex array of reactants and their reactions
influenced in a complicated manner by interdependent environmental
factors, one must recognize that no single and simple mathematical
expression can describe adequately the transformation processes of a
given pollutant. Realistic transformation models should be capable of
distinguishing among the different conversion mechanisms and, for each
mechanism, should reasonably reflect the dependence of the conversion
rate on current plume, background, and environmental conditions.
Historically, the science of transformation modeling is young. As
recently as 1977, the state of the art was such that in a widely
acclaimed regional monitoring and modeling program, the conversion rate
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of S02 to S042~ was represented by a single constant number over a
regional scale, regardless of time of day, season, or prevailing
meteorological conditions (OECD 1977). Even today, such practice is not
uncommon in regional models, perhaps with some justification. Since
1977, however, significant progress has been made in developing
transformation modules appropriate for regional models, particularly for
the gas-phase mechanism of S conversions. Applicable models for the
liquid-phase mechanism are still rare and primitive. Current
transformation models for N compounds are generally complex, requiring
extensive computational resources even for mesoscale applications.
Their validations are limited.
4.4.2 Approaches to Transformation Modeling
Basically two approaches to transformation modeling exist—a
fundamental approach and an empirical approach.
4.4.2.1 The Fundamental Approach--The fundamental approach consists of
the so-called "explicit mechanisms method" and its simplified counter-
parts. In theory, the explicit mechanisms method involves considering
of all significant reactants and their elementary reactions involved in
each mechanism of sulfate or nitrate formation. Concentration changes
by all chemical reactions are calculated simultaneously for all species
at short-term intervals (typically a few seconds). Reactants include
not only the precursors (e.g., S02, and NO), their principal oxidizing
agents (e.g., OH, H02, and R02 in the gas-phase mechanism, and 02»
03 and H202 in the liquid-phase mechanism), and the secondary
products of concern (e.g., ^$04 and HMO^) but also catalysts and
significant intermediate species involved in the mechanisms. Of par-
ticular significance are the multitude of reactive HC species and their
derivatives involved in gas-phase chain reactions that contribute to
photochemical smog formation, as well as to sulfate and nitrate forma-
tion. In a spatially homogeneous system (well-mixed plume) consisting
of n species, a total of 2n first-order, nonlinear, ordinary differen-
tial equations must be solved simultaneously at each time step to
evaluate the changing species concentrations in the plume and in the
background with which the plume interacts. Plume-background inter-
actions must be facilitated in the model. If spatial inhomogeneities
are important and need to be resolved, the system of equations becomes
substantially larger. Also, because a wide range of reaction-time
scales are generally involved, computations for the equations' solutions
at each time step are quite involved, time-consuming, and expensive.
Implemention of the explicit mechanisms method has many associated
problems. The list of possible reactants is long, and sometimes there
is even disagreement about what the products are in given individual
reactions. Values of many elementary reaction rate constants have
either not been measured or are not quite reliable. Model input
requirements also include specification of initial concentrations of all
species in the plume and in the background. While primary emissions
from major point sources are reasonably well characterized, area source
emissions are not. This is particularly true for the hydrocarbons.
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Also, the spatial-temporal resolution of the current area source emis-
sions inventories is generally inadequate to verify model performance
based on the available mesoscale field data of power plant and urban
plume transport and transformations. Atmospheric measurements are
either rare or nonexistent for many short-lived species, some of crucial
importance (e.g., OH, H02, R02, and ^0?). Detailed HC and
aldehyde measurements in the atmosphere'are not common. Input specifi-
cations and model validations are thus only partial and very
approximate.
Perhaps the best example of an attempt to simulate smog chemistry
by explicit mechanisms is the work of Demerjian et al. (1974), which
incorporated more than 200 species, the great majority of them arising
from the explicit use of specific reactive HC and corresponding organic
intermediates and sinks. Despite this model's comprehensiveness, the
authors warn that it may be an oversimplification of the real atmos-
phere, which undoubtedly contains hundreds of organic compounds. Such
complex chemical modeling is currently impractical for application in
regional models. Simplifications and further approximations are
necessary. The key is to achieve a reasonable condensation of the vast
number of HC and aldehydes, and their reactions, while adequate repre-
sentation is maintained. Such condensation is attempted either by
"lumping" groups of species by some common criterion and then treating
each group as a single species in the model, or by substituting a single
surrogate species either for all HC (e.g., propylene by Graedel et al.
1976, "nonmethane HC" by Miller et al. 1978) or for a particular lumped
group of HC (e.g., xylene for aromatics, by Hov et al. 1977). Two
principal methods of "lumping" have been developed: the HSD method
(Hecht et al. 1974), and the carbon bond mechanism (CBM) method (Whitten
et al. 1980). In the HSD method, organic species of like reactivities
are grouped into four main classes: paraffins, aromatics, olefins, and
aldehydes. Many models use a modification of this in which the
following six lumped classes are used after Falls and Seinfeld (1978)
and Falls et al. (1979): ethylene, higher molecular weight olefins,
paraffins, aromatics, formaldehyde, and higher molecular weight
aldehydes. In the CBM method, similarly bonded C atoms are lumped into
four or more classes. In principle, the CBM is closer to the explicit
mechanism and is also easier to use in conjunction with measured data
than is the HSD mechanism. Such formulations have been further con-
densed in specific simulations by reducing the number of species modeled
through the use of surrogate reactions and rate coefficients which
effectively include the role of the omitted species (Levine and Shwartz
1982).
Validation of simulations performed by detailed chemical models
has, to date, been generally based on matching calculated concentrations
of certain key aspects of photochemical smog formation (e.g., HC loss,
and OH or 03 formation) with those measured in controlled smog chamber
studies in the laboratory. The roles of such meteorological variables
as sunlight, temperature, and relative humidity are simulated directly
in the experiments and included in the calculations through the
dependence of elementary reaction rates on them. The role of other
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meteorological variables such as turbulence and inhomogeneous mixing
generally is not simulated in laboratory experiments. This is probably
a serious limitation.
In the real polluted atmosphere, the deficiency of certain key
reactive ingredients in a primary emission may well be overcome through
entrainment of such ingredients from the background air. The formation
of ozone and sulfates in HC-poor power plant emissions in the eastern
United States during summer afternoons is thus almost as rapid as in
HC-rich urban emissions (Gillani and Wilson 1980). Appropriate back-
ground characterization and treatment of plume-background interaction
can be of critical importance in realistic modeling of transformation
processes.
An important positive feature of detailed chemical models is that
nonlinear chemical couplings between species, including the coupling
between sulfur and nitrogen chemistry, is explicitly retained. In this
sense, the same model can, in principle, perform simulations of SOX
and NOX transformatins, as well as of urban or power plant plume
chemical evolution. With appropriate spatial-temporal resolution, the
effect of plume-plume and plume-background interactions can also be
performed.
One of the major undesirable features of the detailed chemical
approach is the necessity of performing extensive computations.
However, considerable differences exist in amounts of computation
necessary depending on choice of numerical method and degree of chemical
approximations involved. The number of species in the chemical schemes
commonly used varies between 10 and 100. The amount of computations
increases nonlinearly and rapidly with increasing number of species.
For any given chemical scheme of smog simulation, the main numerical
problem arises from the fact that the various chemical reactions occur
at speeds which vary by several orders of magnitude. This wide range of
time scales involved in this problem makes the corresponding set of
differential equations quite "stiff." Standard techniques for
integrating sets of differential equations (e.g., the Runge-Kutta
Method) cannot provide stable solutions of such stiff systems at
realistic cost. Special techniques such as those developed by Gear
(1971) provide much more efficient numerical integrations by performing
automatic time and error control, and are capable of providing accurate
numerical solutions, albeit at considerable cost and requiring the use
of large high-speed computers. The Gear technique has been used widely
in simulations of photochemical smog. Other attempts to reduce
computations have resorted to the use of quasi-steady-state assumptions
for certain very reactive species. Such assumptions are not always
justified and have been shown to lead to large inaccuracies not only
under polluted conditions but also in relatively clean background
conditions (Farrow and Edelson 1974, Dimitriades et al. 1976, Jeffries
and Saeger 1976, Hesstvedt et al. 1978). Judiciously invoked
steady-state approximations (QSSA), based on continuous monitoring of
pollutant time scales during on-going simulations, can permit locally
analytical solutions (Hesstvedt et al. 1978) and even locally linearized
4-69
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analytical solutions (Hov 1983a). Such numerical techiques can provide
solutions comparable in accuracy to the Gear solutions at a fraction of
the cost, and can be implemented on smaller computers.
Examples of specific detailed chemical model calculations for
atmospheric applications are considered in Section 4.4.4.1.
4.4.2.2 The Empirical Approach—Given the substantial uncertainties and
gaps in the input information needed for detailed chemical models, and
given the discrepancies in reported transformation rates of SOX and
NOX, the use of detailed kinetic models continues to be questioned,
and simpler empirical rate expressions are often favored. A great deal
of experimental research on chemical transformations has been directed
at obtaining estimates of the conversion rates of S02 to sulfates, and
of NO to N02 to nitrates in the laboratory and in the field. In
recent years, some success has been achieved in relating field estimates
of the conversion rates to specific conversion mechanisms and to
specific, measured influencing factors. A large number of
source-related and environmental factors have been implicated as
influencing transformations. They include the time and height of source
release, the nature and amounts of the acid precursors, other coemitted
species, the reactivity of the airmass in which emissions are
transported, as well as such meteorological factors as sunlight,
temperature, absolute humidity, clouds and fogs, and atmospheric
stability.
In the empirical approach, an attempt is made to identify the
rate-controlling factors for each mechanism and to formulate and
validate an overall rate expression for measured sulfate or nitrate
formation by each mechanism directly in terms of these factors, which
are also measured. In other words, the effect of the multiple
elementary reactions is parameterized in terms of pertinent, measurable
chemical and meteorological factors. Such parameterizations of the
conversion rate are simple rate expressions, which can be inserted
directly into regional models as the transformation module. They entail
very few computations and require inputs that are, for the most part,
relatively readily available even on a regional scale. In spite of
their simplicity, they often yield quite reliable estimates of actual
atmospheric formations of such final products as sulfates. This is
particularly true when their formulation is based directly on field data
and their application is based on measured input data. Their principal
disadvantage is that they lack generality, being applicable mainly under
environmental conditions reasonably close to those for which they have
been successfully validated. In specific applications for which
relevant parameterizations are available, their simplicity and
reliability make them immensely valuable.
The reactions governing S02 oxidation have the general form:
S02 + Ox + (M) ->• products •> S042', [4-101]
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where Ox represents the principal oxidizing agents; i.e., OH and
possibly H02 and R02 for gas-phase oxidation (Calvert et al. 1978),
and H20?, 03, and 02 for liquid-phase oxidation (Penkett et al.
1979); (M) represents the catalysts, if and when any are involved. With
the possible exception of catalyzed reactions (Freiberg 1974), the rate
of sulfate formation, rs, may be expressed as:
rs = _1_ (S042-) = ks • (S02), [4-102]
3t
where the fractional conversion rate, ks, depends on Ox»
oxidizing species. Parameterization of ks which is the goal of
empirical transformation models, is thus a representation of the
weighted contributions of factors which effectively determine the Ox
concentrations. It may be broken down by mechanisms into:
ks = ksG + kSL + kSHET> [4-103]
where components on the right hand side represent, respectively, the
fractional conversion rates by gas-phase, liquid-phase, and
heterogeneous aerosol surface reaction mechanisms. No parameterizations
have been attempted for the heterogeneous mechanism, partly because
reliable and particular atmospheric data are lacking and partly because
the mechanism generally is not considered important on the regional
scale. Specific parameterizations of S conversions are most developed
for k§G, and efforts to parameterize kSL have just begun. These
are discussed in the next section.
Similarly, the formation of the two principle secondary nitrates
(HN03 and PAN) are largely governed by the reactions
N02 + OH + HNOs [4-104a]
and N02 + RC002 + PAN. [4-104b]
Hence, their formation rates may be expressed as:
""HNOs = kHN03 • (N02) [4-105a]
rPAN = kPAN • (N02), [4-105b]
where the fractional conversion rates, k(j (N = HN03» PAN), depend on
the concentrations of OH and RCOO?, respectively. The parameterizations
of k|»j would represent the weighted contributions of the factors which
effectively determine these free radical concentrations. Empirical
parameterizations of k^ based on field data have not been formulated
or tested. Sensitivity of kN to the HC - NOX mix has been studied
in smog chamber experiments. Some of the most recent specific results
and their implications will be discussed in a later section.
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4.4.3 The Question of Linearity
A much debated matter, and one of considerable practical importance
in terms of regional modeling and control strategy, is the question of
linearity of relationships between rs and SOg, and r*N and NOX.
If the transformation chemistry is nonlinear, certain common modeling
practices based on the assumption of linearity must be viewed with
caution. For example, regional models typically have a spatial
resolution over grids of 50 to 100 km to a side. The assumption of
uniform species concentrations within a grid cell which includes
concentrated emissions sources may give erroneous transformation
estimates unless some appropriate parameterization of sub-grid scale
processes is included. Distinctions in the chemical mix of different
source emissions are also presumably important in the case of nonlinear
chemistry. Linear superpositions of species concentrations, calculated
for individual plumes assumed to be isolated, will also give erroneous
estimates of nonlinear secondary formations in regions with multiple
plume interactions. The validity of the linearity assumption is also
crucial to the success of attempts to control secondary pollutants by a
strategy of linear rollback of precursor emissions.
The lack of consensus on the question of linearity, particularly
with respect to sulfur chemistry, is probably due to different
interpretations of the definition of the term linear relationship. By
definition, the relationship between rs and S02 is linear if it can
be stated in the form of Equation 4-102, and if ks is independent of
S02. Clearly, ks is variable through its dependence on species such
as the OH free radical which are responsible ultimately for the
oxidation of S02. Therefore, the critical question is whether these
oxidizing agents are themselves dependent on S02« There is no doubt
that in a fresh plume with high concentration of S02, OH level is
significantly controlled by S02 itself, and the oxidation of S02 is
a nonlinear process. Such conditions, however, are short-lived.
Subsequently, if there are no further fresh injections of S02 into
this plume, the formation of OH will be governed by the NOX-HC
chemistry in the plume and by entrainment from the background of OH
itself and of other reactive species contributing to OH formation. The
direct dependence of plume NOX-HC chemistry on local S02 concentra-
tion is very weak in this stage of plume transport. Consequently, one
commonly finds in the published literature explicit or implicit
statements about linear sulfur chemistry under such conditions. If the
mathematical definition of linearity is to be interpreted strictly, such
statements are correct within the context of the transport of a particu-
lar plume release. In the broader context of modeling of longer-term
averages or continuous emissions, possibly varying with time, and with
inevitable plume-plume and plume-background interactions, an indirect
form of nonlinearity does exist because of the correlation between SO?
emissions and the co-emissions of NOX and HC. A broader definition of
linearity which requires ks to be independent not only of S02 but
also of co-emitted species is implicit in the works of Cahir et al. 1982
and Hidy 1982.
4-72
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The significance of the role of the co-emitted species 1s illus-
trated in the following practical example. Suppose we wish to answer
the following question: "Will a 50 percent reduction of S02 emission
from source A for region A) result in a corresponding 50 percent
decrease in downwind sulfate formation?" There is no unique answer to
this question. First, the manner in which the emission reduction is
achieved is important. If source A is a coal-fired power plant, and the
reduction in S02 emission is achieved by a 50 percent reduction in the
amount of fuel burned, there may also be an accompanying reduction in
NOX emissions in turn, will cause k« to be different. The answer to
the question, therefore, is "no", the cause of this apparent or ef-
fective nonlinearity is the indirect dependence of ks on S02 through
the correlation between co-emitted SO? and NOX. The 50 percent
reduction in S02 emission could also have been achieved by the use of
fuel of 50 percent lower sulfur content or by scrubbing S02 from the
combustion products prior to stack emission. To the extent that these
latter procedures may not have changed NOX emissions, k$ will remain
unchanged except during initial transport and the downwind sulfate
formation would be expected to decrease by about 50 percent, all other
conditions being the same. The answer to the question is therefore
"yes".
A second factor which will profoundly influence downwind sulfate
formation is the composition of the air which the plume encounters
during mesoscale and long range transport. There is field evidence to
suggest that the role of co-emitted species may be substantially
enhanced, or overwhelmed, by the role of the background air which the
plume entrains by mixing processes. Like the co-emitted species, a
polluted background can also serve as the source of the oxidizing
agents. Figure 4-8 shows an example of the side-by-side transport of
two St. Louis plumes of very different emission composition, yet
comparable secondary formations. The Labadie power plant emission is
characterized by a very low HC/NOX ratio. The urban plume of St.
Louis, including the emissions from a large petroleum refinery complex,
by contrast is much richer in reactive HC emissions. The secondary
formation of ozone In large plumes on summer days is closely related to
the formation of sulfates (White et al. 1976, Gillani and Wilson 1980).
The formation of ozone and sulfates in power plant plumes at rates
comparable to those in urban plumes is due to the entrapment of
polluted background air. During long-range transport, the role of the
background air may well predominate as a source of reactive species
which oxidize S02« In laboratory measurements with no role of a
variable background, a first order dependence of sulfate formation on
SO? concentrations has been observed for gas-phase reactions (Miller
1978) as well as liquid-phase reactions (Penkett et al. 1979).
Mesoscale field measurements are also generally consistent with
pseudo-first-order dependence between rs and S02, except during
early transport.
Based on theoretical considerations, the relationship between rN
and NOX is expected to be nonlinear, since kw depends on OH. for
example, which depends directly on the NOX chemistry. Results of
4-73
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recent smog chamber experiments suggest, however, that the nonlinearity
of rjy| may also be short-lived relative to the time scale of long-range
transport (Spicer 1983). Pseudo-first-order parameterizations of r^
may be justifiable, but kjg may also need to reflect the make-up of the
air which an emission encounters during transport.
4.4.4 Some Specific Models and Their Applications
4.4.4.1 Detailed Chemical Simulations—Detailed chemical modules based
on the explicit mechanisms approach have been used within Eulerian as
well as Lagrangian formulations, and in model applications at the plume
scale as well as the regional scale. Such transformation modules differ
principally in terms of their representations of the hydrocarbons, and
in the methods used for the numerical solution of the set of nonlinear
differential equations describing the species concentration changes by
chemical reactions. The following discussion outlines some specific
representative models, and is not intended as an extensive review of
chemical models.
The LIRAQ model (McCracken et al. 1978, Duewer et al. 1978) is an
example of a two-dimensional grid model (single well-mixed vertical
layer). The transformation module attempts to simulate photochemical
smog formation based on the HSD scheme (Hecht et al. 1974), and the
numerical solution is based on the Gear technique. The SAI Airshed
Model (Reynolds et al. 1979) is a three-dimensional grid model which
permits initial isolation of elevated point sources from surface
sources. It uses the carbon bond mechanism of photochemical smog
simulation (Whitten and Hogo 1977), and numerical solution is by a
finite difference technique (SHASTA) developed by Boris and Book (1973).
An ambitious three-dimensional regional grid model currently under
development at EPA (Lamb 1981) presently uses the chemical scheme of
Demerjian and Schere (1979) which uses four hydrocarbon classes of
different reactivities. In some regional models (e.g., McRae et al.
1979), point source plumes are simulated in a Lagrangian sense within
the framework of an Eulerian grid network until they attain the
dimensions of the grid cell. Therefore, the simulation is continued in
the Eulerian frame.
On a global basis, the troposphere is presumed to be clean and the
organic species most relevant to smog formation are carbon and monoxide
(CO) and methane (CH/j). Recently, a two-dimensional global model was
employed by Fishman and Crutzen (1978) to predict the global distribu-
tion of OH, H02, and CH302 radical concentrations. Predicted OH
concentrations were reasonably comparable with recent, measured
atmospheric concentrations (Sheppard et al. 1978). Altshuller (1979)
used this model for OH to investigate the variability of the sulfate
formation rate by the homogeneous gas-phase mechanism with respect to
latitude and altitude. His results showed that in the clean enviroment,
OH is the principal oxidizing agent, and that, at higher latitudes,
e.g., in the northeastern United States, Canada, and northern Europe,
large seasonal differences in sulfate formation by this mechanism
4-75
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are to be expected. Very little sulfate formation is likely in winter
by gas-phase mechanisms.
The regional model of Carmichael and Peters (1979) is based on the
chemistry of a clean background in which the only organic species are CO
and C02- They invoke the pseudo-steady-state assumption for the
oxidizing species OH, H02, ^03, and 03, and use their iterative
solution for these species in first order expressions for the oxidation
of S02 to estimate the sulfate formation rate.
Most plume simulations are based on trajectory-type models.
Calculations made for polluted industrial regions and urban areas have
simulated certain observed phenomena related particularly to 03
behavior (Graedel et al. 1978) but at the same time have yielded
conflicting results concerning important control strategies. Results by
Graedel et al. (1978) suggest OH levels to be directly proportional to
N02 levels, implying that reduction of NOX emissions would help
control nitrate and sulfate production. Miller (1978) showed rather
that NOX emissions tend to delay S02 oxidation and that the ratio
(NMHC/NOX) of initial concentrations of nonmethane HC's and N0x's
dominates the S02 oxidation rate. Miller's conclusions were verified
experimentally. Actually, as suggested by Miller (1978), precursor
effects may significantly differ in the first several hours of daytime
plume transport from their effects during subsequent regional transport.
Detailed chemical calculations also have been applied to simulate
sulfate and nitrate formation in urban plumes (Isaksen et al. 1978,
Miller and Alkezweeny 1980, Bazzell and Peters 1981) and in power plant
plumes (Miller et al. 1978, Bottenheim and Strausz 1979, Levine 1980,
Hov and Isaksen 1981, Stewart and Liu 1981). In these caculations,
proper simulations of the changing background air and of plume-
background interactions were necessary for at least qualitative
agreement with field observations. Levine (1980) neglected plume-
background interactions and, as a result, his conclusion that power
plant plume dilution inhibits sulfate formation is contrary to field
observations in moderately polluted regions (Gillani and Wilson 1980).
Hov and Isaksen (1981), on the other hand, treated crosswind spatial
inhomogeneities in sulfate formation resulting from plume-background
interaction and succeeded in simulating, at least qualitatively, many
features of the crosswind plume data of Gillani and Wilson. Stewart and
Liu (1981) similarly provided cross-wind resolution and plume-background
interactions with their reactive plume model which was based on the
carbon-bond mechanism for the simulation of chemical kinetics.
Recently, Hov (1983b) performed a plume simulation in which vertical
stratification of the concentration field was considered. In general,
plume simulations have indicated that 03 and aerosol formation are
greater when the background is polluted, that OH is the dominant
oxidizing species, and that OH and peroxy radical (H02» R02)
concentrations, which play an important role in 03 formation, peak at
midafternoon in polluted regions.
4-76
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In all of the above simulations, only the homogeneous gas-phase
chemistry was included. Rodhe et al. (1979) added reactions of S02
and N02 with H?02 in the presence of "clpuds" to a highly lumped
gas-phase chemistry model. ^Og generation was calculated based on
the gas-phase reactions. The authors recognized qualitatively that the
effective rate constants for cloud reactions must include not only the
effect of the liquid-phase transformations occurring in cloud droplets
and in precipitating clouds, but also exchange rates of the reacting
species between the droplets and the surrounding air, and the frequency
and occurrence of clouds and precipitation. They then proceeded to
choose rate constant values such that overall gas- and liquid-phase
oxidation rates of S02 became comparable and the liquid-phase
oxidation of N02 became relatively insignificant compared to its
gas-phase counterpart. This procedure for the liquid-phase mechanism
represents a highly parameterized approach, with parameter values
assumed rather subjectively. Their calculations were applied regionally
to the European industrial environment under summertime conditions. The
relative contributions of gas-phase and liquid-phase mechanisms to
sulfate and nitrate formation, of course, reflected their assumptions.
Overall, HN03 formation proceeded rapidly, principally by the
gas-phase mechanism, peaking at 13 percent hr-1 after 15 hr.
H2SC>4 formation rate during 90 hr of simulation ranged between 0.1
and 1 percent hr-1 by the gas-phase mechanism and between 0 and 1.8
percent hr'1 by the liquid-phase mechanism.
4.4.4.2 Parameterized Models—For many years, no consensus could be
reached concerning the relative importance of the many chemical and
meteorological factors implicated as influencing gas-to-particle S
conversion. Most transport-transformation models used constant pseudo-
first-order rates for the oxidation of S02. Documentation of sunlight
as a dominant environmental factor governing sulfate formation in power
plant plumes (Gillani et al. 1978) has since been verified and widely
accepted and used. In particular, in a recent review of field data on
sulfate formation in power plant plumes during all seasons in the United
States, Canada, and Australia, Wilson (1981) observed that the
outstanding common pattern in this broad data base was the diurnality of
the sulfate formation directly related to solar radiation. Such a role
of sunlight is also consistent with the observed distinct summer peak in
regional S042- distribution in the eastern United States (Husar and
Patterson 1980), even though corresponding S02 emissions are
distributed fairly uniformly over all seasons (DOE 1979).
A sunlight-dependent model of the form ks « RT, the total
incoming solar radiation flux at ground level, was used by Gillani
(1978) in a diagnostic mesoscale plume model and by Husar et al. (1978)
in a multiday plume S budget study. A similar parameterization has been
used by Shannon (1981) and by others. Gillani found that such a model
based only on sunlight could not simulate the observed day-to-day
variation in sulfate formation. Evidently, factors other than sunlight
must be included. Also, the manner in which sunlight influences the
conversion process must be more carefully considered. As Wilson (1981)
noted, observed correlations of the conversion rate with sunlight, or
4-77
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with air temperature (Eatough et al. 1981), do not imply the direct role
of these factors in the underlying mechanisms. These two factors are
highly correlated, as are both to turbulent mixing, convective cloud
formation, and a number of other factors, which alone can exert
rate-controlling influences on specific conversion mechanisms.
Accordingly, formulation of meaningful parameter!'zations must be based
on mechanistic considerations.
Gillani et al. (1981) recently advanced a parameterization of the
gas-to-particle S conversion by the gas-phase mechanism based on plume
data collected during the summer in the Midwest (Missouri and
Tennessee). The motivation for their gas-phase parameterization was
derived from their earlier identification of a recurrent pattern of 03
and aerosol generation in power plant plumes, which evidently involved
participation of reactive species entrained from the background (Gillani
and Wilson 1980). Gillani et al. argued that accelerated photochemical
generation of the radical species OH, H02 and ROg that oxidize
gas-phase S02 would be facilitated by reactions involving NOX
emissions and entrained reactive HC and free radical species.
Consequently, the quality of the background air and the extent of plume
dilution by its entrainment were judged to be important contributing
factors, in addition to sunlight which powers the photochemical
reactions. Given the lack of detailed data of the oxidizing species,
the authors resorted to using 03 as a surrogate for, or an indicator
of, airmass reactivity. Vertical plume spread, Azn, was chosen as a
measure of the extent of plume dilution. The resulting gas-phase
parameterization is:
kSG-(.03 +_ .ODRy • (Az)p • (03)0, [4-106]
where k$G is in percent hr"l, Rj is in kW m~2, (Az)n is in meters, and
background ozone, (03)0, is in ppm. The coefficient 0.03 _+ 0.01 was
chosen on the basis of the best fit between the calculated (Equation
4-106) and measured values of ksg« The measured values were for dry
(relative humidity < 75 percent), cloudles conditions when gas-phase
reactions may safely be assumed to predominate. The parameterization
was validated successfully by data collected in the plumes of three
large central power generating stations in Missouri and Tennessee during
two different summers. The empirical coefficient (0.03) thus pertains
to such large power plant plumes in which the initial NOX/S02 ratio
is about 1:3.
The above parameterization is believed to provide good estimates of
the gas-phase sulfate formation rate under the moderately polluted
conditions characteristic of the eastern United States in summer and
appears to be valid even under more polluted conditions during
stagnation episodes. Its validity in winter, even in this region,
remains to be tested. Its performance in clean regions such as the
Southwest, and in extremely polluted areas such as Los Angeles, CA, on a
smoggy day is also unproven. Furthermore, the parameterization has no
validity for urban plumes and possibly also plumes from small power
plants owing to substantially different composition of the emissions.
4-78
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In spite of these restrictions, the parameterization is of practical
significance. Its input requirements are minimal and can be satisfied
presently over a regional scale in the eastern United States. Its
explicit inclusion of plume-background interactions and air mass
conditions probably gives it some validity even during long-range
transport when the role of the background is expected to be dominant.
Application of the parameterization based on 1976 St. Louis, MO, data of
the input variables yields the diurnal and seasonal pattern of kS£
as shown in Figure 4-9. The magnitudes and temporal variations snown
are plausible and consistent with available field data, as well as with
expectations based on detailed chemical calculations (Calvert et al.
1978, Altshuller 1979). The results predict that in the Midwest,
gas-phase mechanisms may be expected to convert about 10 to 20 percent
of the S02 in a power plant plume to S042' during an average
summer day, while corresponding conversion in winter may be about an
order of magnitude smaller. By comparison, measured values of S02 to
S042- conversion by all mechanisms range between 15 and 35 percent
for summer conditions in the same region (Gillani and Wilson 1983a). It
may be inferred, therefore, that liquid-phase mechanisms may convert
about 5 to 15 percent of the S02 to S042~ per day during summer in
the Midwest.
Gillani and Wilson (,1983b) have recently also made a first attempt
to formulate a parameterization of liquid-phase S042~ formation
resulting from plume-cloud interactions. The formulation explicitly
recognizes that the overall conversion rate, ksi . depends not only
on the chemical reaction rate within cloud droplets, KS. , but also
on the physical extent of plume-cloud interactions. Because clouds are
discrete entities in space and time, and plume-cloud interactions are
somewhat random events, the authors choose to describe plume-cloud
interactions in probabilistic terms. The overall formulation has the
general form
kSL = P • KSL [4-107]
where P represents a measure of the probability and extent of plume-
cloud interactions. All three quantities in the equation are time
dependent. The dependence of P on local plume and cloud dimensions has
been derived explicitly (details given in original reference), and its
values are determined during an actual power plant plume model run based
on current, calculated plume dimensions and local cloud data from
surface weather observations of the National Weather Service network of
stations, as well as on local lidar and aircraft measurements. P
represents a measure of the fraction of a given plume volume which is in
contact with the liquid phase.
The authors did not attempt to parameterize K$. . It depends
on such variables as liquid water concentration; droplet pH, and
concentrations of dissolved S, oxidizing agents (^03, 03, and
03), and catalysts (Fe and Mn). No data were available for such cloud
chemical composition. The authors did, however, obtain an average
daytime estimate for K$, under typical summertime fair-weather
4-79
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convective cloud conditions in the Kentucky-Tennessee area. The
inferred value of K$. (summer daytime average conversion rate within
clouds) was 12 percent hr"1. This value compares with values of 0 to
104 percent hr"1 estimated by Hegg et al . (1980), based on ambient
S02 and SO^- measurements in wave cloud situations and with
predicted values ranging from 10 to 20 percent hr"1 in large storm
cloud systems in the summer based on an indirect mass balance technique
(Scott 1981). Also, the value of P averaged over 24 hr is expected to
be significantly less than 0.1 during summer as well as winter. In
other words, the average bulk plume conversion rate by liquid-phase
mechanisms is likely to be less than the local droplet-phase conversion
rate by more than an order of magnitude. All of these estimates involve
several assumptions and approximations and must be used with caution.
Values of K$. at night and in winter are believed to be
substantially smaller as a result of lower concentrations of the
photochemically generated oxidizing species, 03 and
Based on the above parameterizations and St. Louis, MO, data, it is
estimated that the 24-hr average, overall sulfate formation rates in
July are likely to be 0.8 +_ 0.3 percent hr'1 by gas-phase reactions
and at least 0.4 +_ 0.2 percent hr'1 by liquid-phase reactions. Winter
rates by gas-phase reactions are estimated to be an order of magnitude
smaller than in summer and by liquid-phase reactions are estimated to be
comparable during the two seasons.
A variety of empirical data suggest that liquid-phase conversions
in wetted aerosols may be significant at relative humidity between 75
and 100 percent (Dittenhoefer and de Pena 1980, McMurry et al. 1981).
Winchester (1983) has formulated the following empirical parameteriza-
tion of ks which highlights the role of absolute humidity and
temperature:
ks - (PH20)3'°8 (P^O.sat)1'213.
where P^o denotes the partial pressure of water vapor, and
PHpO.sat denotes the saturation vapor pressure of water vapor (a
measure of temperature) .
No comparable parameterizations of NOX transformations have
been formulated. Summertime plume measurements suggest that N03~
formation is primarily in the form of HN03 vapor (Forrest et al. 1979,
1981; Hegg and Hobbs 1979b; Richards et al . 1981) and that oxidation of
N02 to HN03 may proceed about three times faster than does oxidation
of SO? to H2S04 (Forrest et al . 1981, Richards et al. 1981).
Gas-phase mechanisms of HN03 formation are believed to predominate in
the summer.
Whitby recently used a simple model assuming the total accumulation
mode aerosol formation rate to be directly proportional to UV radiation
intensity, to simulate observations of aerosol formation in the St.
Louis, MO, urban plume of 18 July 1975. He estimated that about 1000
tons of secondary fine aerosol may be produced in the St. Louis plume in
4-81
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one simmer irradiation day (Whitby 1980). For the same plume transport,
Isaksen et al. (1978) used a detailed chemical model to simulate the
measured data of 03 and S042- formation presented by White et al.
(1976) and estimated peak HgSC^ and HMOs formation rates of 5 and
20 percent hr-1, respectively, to occur in the early afternoon.
Alkezweeny and Powell (1977) also measured the St. Louis plume and
estimated afternoon $042- formation rates to be 10 to 14 percent
hr-1. Miller and Alhezweeny (1980) measured S042- formation rates
in the Milwaukee urban plume, particularly related to the quality of the
background air mass, to range from 1 to 11 percent hr-1.
Spicer (1977a) estimated the N02-to-Products transformation rate
in the Los Angeles urban plume as 10 + 5% hr-1. jn more recent
measurements downwind of Los Angeles TSpicer et al. 1979), the observed
lower limit of NOX conversion rates ranged from 1 to 16% hr-1, with
typical rates in the 5 to 10 percent hr-1 range. Spicer (1980)
estimated NOX transformation/removal rate for the Phoenix urban plume
to be less than 5 percent hr-1, while data for Boston showed rates in
the 14 to 24 percent hr-1 range. Transformation products of NOX
transformations include not only inorganic nitrate (e.g., HN03), but
also organic species (e.g., PAN). Spicer attributes the low conversion
rate in Phoenix at least partly to thermal decomposition of PAN and its
analogs at the high ambient temperatures of the desert area.
Recently, Middleton et al. (1980) performed a model study of
relative amounts of sulfate production in wetted aerosols in a polluted
environment by two different mechanisms: condensation of S02 gas-phase
oxidation products, and catalytic and noncatalytic S02 oxidation in
the liquid phase. The microphysical vapor transfer to the aerosols and
the chemical conversion within the aerosols were treated as coupled
kinetic processes. Concentrations of the oxidizing species (e.g., OH,
and H202) and of the catalysts (e.g., Fe, Mn, and soot) were assumed
known, and representative values for day and night and summer and winter
were used. The study concluded that in the daytime, photochemical
reactions and liquid-phase oxidation by ^02 are likely to
predominate, with particle acidity playing a minor role. At night,
sulfate production rates are low, being principally by catalytic and
noncatalytic liquid-phase mechanisms involving 03 and 02- The
daytime ^02 reaction rate was enhanced by the lower winter
temperatures.
4.4.5 Summary
Transformation models can, at best, be only as good as our
understanding of the transformation processes. Significant gaps in this
understanding remain, particularly with respect to the physical and
chemical kinetics of the liquid-phase processes. The validity and
extrapolation of laboratory results to real atmospheric conditions are
often questionable. Field measurements, in general, are insufficient,
particularly for wet conditions. For example, simultaneous physical and
chemical measurements pertaining to plume-cloud interactions are almost
nonexistent.
4-82
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Detailed chemical models are not yet practical for application in
regional models to predict acidic product formation and deposition.
Many individual pieces of information--microphysical pathways and
chemical reactions--must be put together correctly and we are still
struggling to assemble an adequate information base about the individual
pieces. To complicate matters, important couplings exist between the
different major mechanisms of sul fate and nitrate formation (e.g.,
^2®? formed by gas-phase photochemistry is of paramount importance
in liquid phase chemistry), and significant interdependences exist among
the major influencing environmental factors. Detailed chemical models
already can simulate qualitatively many field observations, but the
validity of quantitative predictions based on these models is
questionable. Furthermore, their application requires substantial
computational resources.
It appears that, for the foreseeable future, empirical parameteri-
zations will serve as transformation modules in regional models.
Preliminary parameter! zations have been developed only for $04
formation in power plant plumes, and will undoubtedly continue to be
improved. No practical parameter!' zations exist yet for N03~
formation or for urban plumes. Adherence to mechanistic considerations
is recommended in formulating the parameter!' zations. More, and more
reliable, measurements of such important variables as the atmospheric
concentrations of OH, H202, NHs, HC's, SQ^~ and NOs" and
of cloud dimensions and cloud chemical composition are needed direly.
and HN03 formation apparently peaks during daytime and
in summer. Gas-phase mechanisms are considered contribute a larger
share, on the average, to these secondary formations under warm, sunny
conditions. Typically, on a summer day (24 hr) in the eastern United
States, about 25 + 10 percent of the airborne S02 in power plant
plumes is likely To be converted to S042~. Nighttime conversion is
a small part (about 5 percent or less). S transformations may be
somewhat higher than these in the southeastern United States. HN03
formation rate in power plant plumes is about three times as fast as the
$04^" formation rate by gas-phase mechanisms. Aerosol N03~
formation rate is apparently very small, at least in the summer. Both
S042" and NOs" formation are faster in urban plumes.
The time has arrived to abandon the use of constant conversion
rates in regional models, at least for different seasons. In short-term
models, diurnal variabilities can also be resolved. We may not be able
to apportion secondary formations to different formation mechanisms
confidently, but we are at least reasonably comfortable with overall
conversion rates for average seasonal and diurnal conditions, at least
for S compounds in the summer. More atmospheric measurements are needed
of SOX transformations in the other seasons and of NOX transforma-
tions in all seasons.
4.5 CONCLUSIONS
The discussion of homogeneous gas-phase reactions has led to the
following conclusions:
4-83
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Organic acids produced during gas-phase oxidation of hydrocarbons
are expected to make only minor or insignificant contributions to
precipitation acidity because of their relatively small dissoci-
ation constants. More information is needed for assessment
(Section 4.2.1).
Acids (HX) produced from gas-phase reactions of halocarbons are
also expected to make insignificant contributions to regional dis-
position problems; their effects on global precipitation chemistry
is more plausible but uncertain. Direct anthropogenic emissions of
HX are potentially important (Section 4.2.1; Chapter A-2).
Oxidation of reduced forms of sulfur in the atmosphere generally
leads to sulfur dioxide (S02) formation (Section 4.2.1).
SOo oxidation in air is dominated by reaction with hydroxyl (HO)
radicals, and although the reactions of the HOS02 adduct and
other possible intermediates are unknown, the final product is
sulfuric acid aerosol (Section 4.2.1).
The average lifetime of S02 with respect to this reaction is
approximately 3-4 days (Section 4.2.2).
Of the remaining free-radical processes for S02 oxidation, only
the reaction by peroxy'alkyl radicals appears to have possible
atmospheric significance; additional information is needed for
assessment (Section 4.2.1).
Gas-phase oxidation of nitrogen dixoide (N02) leads to a variety
of products; nitric acid, dinitrogen pertoxide (^05) and
peroxyacetyl nitrate (PAN) are in greatest abundance. Nitrogen
trioxide and nitrous acid play active roles in photochemical cycles
but make smaller direct contributions to acid deposition. Further
research on the fate of PAN and N20s is direly needed (Section
4.2.1).
The average lifetime of N02 with respect to reaction with
hydroxyl radicals is approximately one-half day and the product is
nitric acid vapor (Section 4.2.2).
Field data tend to confirm overall transformation rates for
nitrogen and sulfur oxides, as established in laboratory
experiments, but fail to give conclusive evidence about dominant
reaction pathways and meteorological effects. Gas-phase trans-
formation rates in power plant plumes are usually smaller than in
urban plumes because of imperfect mixing an an abundance of nitric
oxide which suppresses the concentration of hydroxyl radicals
(Section 4.2.3).
The concentrations of hydroxyl radicals in the atmosphere are
governed by a tightly coupled reaction cycle involving HC-CO-NOX
-03, but not S02, and the HO concentrations are not
satisfactorily defined except, perhaps, on a global scale. In
4-84
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polluted air, the ration of hydrocarbons (HC) to nitrogen oxides
(NOX) is expected to be dominant variable for the HO radical
concentration. The cause-effect relationships governing the free
radical composition of the atmosphere need further clarification
(Section 4.2.1) .
0 Overall, the kinetics and mechanistic details of gas-phase che-
mistry affectign acidic species are understood, albiet some
important gaps remain. Adequate models of gas-phase chemistry can
be formulated but their application to real atmospheric situations
remains a problem (Sections 4.2.1, 4.2.2, and 4.2.3).
The review of the current understanding of the production of
acidity within hydrometeors has led to the following conclusions:
0 The production of both HN03 and HC1 within hydrometeors is
negligible compared with direct absorption of these species from
the gas phase. Here, the concentration of these species in
precipitation will be influenced strongly by homogeneous gas-phase
chemistry (Sections 4.3.3 and 4.3.4).
° Production of H2S04 in solution within hydrometeors, by any of
several different mechanisms, can rival or even suppress direct
absorption of H2S04 by hydrometeors (Section 4.3.5).
° Of _the Carious production mechanisms for H2S04 in solution,
oxidation by H202 and by catalyzed and uncatalyzed aerobic
oxidation appear to be most important (Section 4.3.5).
0 While oxidation by H202 appears to be the single most important
reaction producing H2S04, the extent of its contribution to the
acidity of hydrometeors will depend directly on the H202
available in solution, a parameter not well characterized at this
time (Section 4.3.5).
0 The amount of acid absorbed and produced in hydrometeors is such
that the pH's of precipitation particles should be much lower than
observed (Section 4.3.5).
0 Neutralization of hydrometeor acidity by NHs absorption and by
reaction with scavenged parti cul ate CaC03, MgCOa and CaO may be
of considerable importance (Section 4.3.6).
Considerable progress has been made in transformation modeling in
recent years. Significant gaps remain, however, in our ability to
predict transformation rates of SOX and NOX under atmospheric
conditions. The following observations summarize the current status of
the principal aspects of transformation modeling:
° It is now possible to simulate the principal features of the smog
chamber chemistry of the SOX-NOX-HC system rather accurately by
detailed modeling of the chemical kinetics based on lumped
4-85
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representations of the hydrocarbons, even though details of the
chemical mechanisms are not fully understood (Section 4.4.4).
Detailed chemical models of plume transformations under atmospheric
conditions have successfully simulated many qualitative features of
field observations, including some details of crosswind profiles
influenced by plume-background interactions. These simulations are
mainly restricted to gas-phase chemistry (Section 4.4.4).
The principal current limitations in detailed chemical modeling are
probably related to inadequate characterization of the emission
field and of the ambient polluted regional background. Improved
and more detailed inventories of the emissions of SOX, NOX, and
HC from major sources including the urban area sources, and reli-
able measurements of reactive species (e.g., OH, R02, H202)
in the ambient atmosphere are needed before reliable conclusions
concerning regional-scale transformation processes can be made.
The relative importance of co-emissions vs background entrainment
as sources of oxidizing agents (OH, R02, ^Oo, etc.) is not
understood at the present time (Section 4.4.4).
Current detailed chemical models generally do not include
liquid-phase chemistry. Quantitative descriptions of the
liquid-phase environment (e.g., cloud dynamics, plume-cloud
interaction, etc.) are not adequately incorporated into
transformation models. Cloud and fog chemistry measurements are
sparse and much needed. Coupled modeling of gas- and liquid-phase
chemistry is necessary, particularly under summer conditions.
First steps in this direction have been taken (Sections 4.4.2 and
4.4.4).
For the near future, it appears that transformation modules based
on empirical parameterizations will continue to predominate in
operational regional models. All models, to varying degrees use
prameterizations based on laboratory and field data. Currently,
regional models mostly employ pseudo-first-order or constant first
order bulk conversion rates. The basis for refining these esti-
mates to reflect at least the gross diurnal and seasonal
variations, and even the role of a changing background, exists.
Increasingly, new models are incorporating such empirical expres-
sions, which are constantly being improved. The state-of-the-art
of such prameterizations will be further advanced as more data are
obtained and analyzed, particularly for NOX precursors and
products, for urban plumes, and for other than summer conditions.
Detailed chemical models also serve to improve our understanding
and basis for the formulation of empirical parameterizations which
reflect the underlying physical-chemical processes rather than
merely expressing statistical correlations. At this time, the
major sources of uncertainty in determining atmospheric residence
times of pollutants are probably associated with transport and
deposition processes rather than with transformation processes
(Sections 4.4.2 through 4.4.4).
4-86
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THE ACIDIC DEPOSITION PHENOMENON AND ITS EFFECTS
A-5. ATMOSPHERIC CONCENTRATIONS AND DISTRIBUTIONS
OF CHEMICAL SUBSTANCES
(A. P. Altshuller)
5.1 INTRODUCTION
Air quality measurements of those substances that may contribute
directly or indirectly to acidic deposition processes are discussed in
this chapter. Substances such as sulfur dioxide and nitrogen dioxide
may contribute to acidic deposition in two ways: (1) They can undergo
dry and wet deposition to soil and subsequently undergo reactions to
acidic species in soils; (2) They can undergo atmospheric chemical
transformations to particle sulfate and gaseous and particle forms of
nitrate which, in turn, can undergo deposition to soils, lakes, and
streams. These substances may be acidic in their original forms as are
NH4HS04, H2S04, and HN03, or they may undergo reactions in
soil that result in release of hydrogen ions. Ammonia is an important
nitrogen species that can neutralize airborne acidic substances, but in
soils in the form of ammonium ion it can react to form hydrogen ions.
A number of other elements are of interest as airborne substances.
Alkaline earth metals such as calcium can react as calcium ions to
neutralize acidic substances. Iron and manganese ions are of
significance to the extent that they can be demonstrated to participate
in catalytic reactions in aqueous droplets to enhance the conversion of
sulfur dioxide to sulfate (Chapter A-4, Section 4.3.5). Other airborne
metallic elements may, upon deposition, have possible adverse biological
effects in soils, lakes, and streams. Aluminum and manganese ions have
been identified as possible causes of toxic effects in soils (Chapter
E-2, Section 2.3.3.3.2). Aluminum ions are of particular concern in
causing adverse effects in lakes and streams (Chapter E-4, Section
4.6.2). Zinc, manganese, cadmium, lead, and nickel also can have toxic
effects in lakes and streams at sufficiently high concentrations
(Chapter E-5, Section 5.6.4.2), and indirect health effects have been
associated with lead, aluminum, and mercury (Chapter E-6).
Ozone and hydrogen peroxide participate in oxidation of sulfur
dioxide to sulfate in aqueous droplets (Chapter A-4, Section 4.3.5.3).
The ambient air concentrations of both of these oxidants will be
considered, although substantial difficulties have been encountered in
the measurement of hydrogen peroxide.
The effect of light scattering by submicron aerosols such as
sulfates and nitrates is significant in the areas of eastern North
America impacted by acidic deposition. Particle sulfate appears to be
5-1
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particularly important in its adverse effects on visibility when
suspended in air and a significant contributor to acidic deposition to
soils, lakes, and streams. Therefore, a discussion of visibility
degradation effects of these aerosol species is included in this
chapter.
Measurements of airborne substances that may contribute to acidic
deposition are of particular interest in rural areas. However, in the
past, most measurements of airborne substances were made in urban areas.
Cities were the major sources of pollutants of concern until after World
War II. They still contribute substantially to the total burden of
airborne sulfur and nitrogen compounds. Urban plumes also are
significant because, through dry and wet deposition processes, they
contribute directly to the loading into soils, lake, and streams
substantially downwind of cities (Chapter A-3, Section 3.4.2).
5.2 SULFUR COMPOUNDS
5.2.1 Historical Distribution Patterns
Substantial changes in the geographical and seasonal distributions
of sulfur oxides and in the stack heights of emission sources of sulfur
oxides have occurred over time. Many of these changes occurred before
air quality monitoring networks were established.
Wood was the predominant fuel used in the United States until the
late 19th century (Schurr et al. 1960) when coal use began to increase.
The coals burned, unlike wood, contained substantial amounts of sulfur,
emitted to the atmosphere as sulfur oxides. Before and during World War
II, the major uses of coal included residential/ commercial heating,
production of coke, and the operation of railroad locomotives (Schurr et
al. 1960). Most of these sources of sulfur oxide emissions, except for
locomotives, were in the cities. In addition, small coal-fired power
plants were often located in cities. Thus, most sulfur oxides were
emitted from sources near the surface. These near-surface, emissions
plumes would have impacted on the adjacent countryside resulting in high
sulfur oxide concentrations in and near urban centers.
Coal usage declined immediately after World War II in the United
States. By the late 1940's and 1950's, the use of coal in
residential/commercial heating and railroad locomotives dropped off
rapidly as coal was replaced by oil and gas. In cities, coal for
residential/commercial heating was replaced by gas, which reduced sulfur
oxide emissions substantially, and by fuel oil containing high sulfur
contents, which did not reduce sulfur oxide emissions appreciably.
Increases in sulfur oxide emissions were seen in the 1960's from
industrial sources and the rapid growth of electric utility sources.
However, emissions from industrial sources decreased in the 1970's
(Chapter A-2, Figure 2-6). In the late I9601s and early 1970's,
regulations were promulgated to limit the sulfur content of fuels, thus
reducing emissions from fuel oils. These regulations were applicable in
particular to cities in the northeastern United States.
5-2
-------
The spread of cities Into suburban areas after World War II
resulted in more diffuse sources of urban plumes, although emission
sources in surburban areas usually used low-sulfur fuels. Coal-fired
electrical utility capacity in the midwestern and southeastern United
States increased rapidly. These power plants were constructed outside
of cities and with increasingly tall stacks. By the 1970's, numerous
large power plants with stacks of varying heights were distributed
throughout nonurban areas of the United States. These complex and
varied emissions sources contributed to the loadings of sulfur oxides in
rural areas on a seasonal and annual basis.
Where local contributions are negligible, the impact of urban plumes
on remote areas is unclear, although long-range transport is more likely
in winter (Chapter A-3, Section 3.4.2) because of unique atmospheric
conditions. The plumes from sulfur oxide emission sources with tall
stacks can be isolated from the surface for varying diurnal periods
depending on the hour of release and season of the year (Chapter A-3,
Figures 3-19, 3-20, 3-21, and 3-22). During these diurnal periods,
these sources contribute to the total sulfur loading of the lower
troposphere, but not to the sulfur oxides measured at ground level.
Therefore, ground-level monitoring alone is inadequate to evaluate the
total sulfur loading of the atmosphere available to participate in
subsequent wet and dry deposition. Chapter A-8 presents further
discussion of deposition monitoring.
5.2.2 Sulfur Dioxide
5.2.2.1 Urban Measurements—Most of the sulfur content of fuels is
emitted to the atmosphere in the form of sulfur dioxide (503). Sulfur
dioxide was monitored in various large cities in earlier years, but no
nationwide monitoring network existed until the I960's.
Jacobs (1959a) reported ambient air concentrations of S02 in
Manhattan and several other sites in the New York, NY, area for 1954-56,
with higher concentrations in winter than in summer. The diurnal
profiles showed midmorning and late afternoon peaks or early morning
peaks in $03 concentrations. Jacobs reported hourly S02
concentrations as high as 2500 to 3000 pg m~3 during some winter and
fall air stagnation episodes. On an annual average basis, S02
concentrations at the Manhattan monitoring site averaged 420, 520, and
500 pg m~3 in 1954, 1955, and 1956, respectively. Methods of
sampling and chemical analysis were reported also (Jacobs 1959b).
A National Air Sampling Network (NASN) was initiated in the United
States in the 1950's, but sulfur dioxide was not measured until the
early 1960's. In comparison with the S02 concentrations reported by
Jacobs (1959a), the NASN measurements in Manhattan in 1964 and 1965
averaged 450 and 370 pg nr3, respectively (Dept. of Health,
Education and Welfare 1966). These results appear to indicate
relatively little change in concentration from the 1950's to the
mid-19601s. This is not unexpected because fuel sulfur content was not
restricted during this time.
5-3
-------
In the 1963-72 period the decreasing order of annual average
concentrations was (1) East Coast, (2) Midwest (east of Mississippi),
(3) Southeast, (4) West Coast, and (5) Midwest (west of the Mississippi
River), and (6) western states. Many urban sites west of the
Mississippi River had $02 concentrations averaging only 10 to 20
percent of the concentrations at sites on the East Coast (Altshuller
1973).
Trends in the annual average, seasonal, and episodic concentration
levels of $02 with time have been evaluated by geographical region and
in specific urban areas (Altshuller 1980). Between 1963-65 and 1971-73,
S02 concentrations (3-year quarterly averages) at urban sites
decreased by about 80 percent in the northeastern United States (Figures
5-1 to 5-4) and by 30 to 50 percent in the midwestern United States
(Altshuller 1980). The declining S02 concentration levels in cities
appear to relate better to reductions in local sources of sulfur oxide
emissions than to regional-scale utility emissions.
S02 concentrations in the northeastern United States, in the
earliest period (1963-65) for which measurements are available, by
quarter of the year, were in the order: fourth quarter > second quarter
> third quarter (Figures 5-1 to 5-3). In 1971-73, the same order
prevailed (Altshuller 1980.).
Trends in S02 concentrations in urban areas in the 1970's are
available on an annual average basis for the United States and
geographical regions within the United States (U.S. EPA 1977a, 1978b).
Based on 1,233 U.S. sampling sites, the composite average of urban S02
concentrations decreased by 15 percent between 1972 and 1977 from the
1972 level of 23 yg nr3 (U.S. EPA 1978b). The 90th percentile
concentrations of S02 decreased by 23 percent between 1972 and 1977
from a 1972 level of 52 yg nr3. There were no significant changes
in either the 90th percentile concentrations or in the composite average
concentrations during the last few years of the 1970's.
By the latter part of the 1970's, ambient air concentrations of
S02 had been reduced to relatively low levels. In 1976 the composite
annual average (and 90th percentile) concentrations were: United
States--20 yg nr3 (40 yg nr3), New England--25 yg m'3 (40
yg nr3); Great Lakes--28 yg nr3 (50 yg nr3) (U.S. EPA 1977a,
1978). These concentrations were well below the S02 concentrations
experienced in the 1960's or the early 1970's. During the last few
years, S02 concentration levels appear to have stabilized.
5.2.2.2 Nonurban Measurements—Measurements for S02 concentrations at
nonurban sites in the United States are more limited than those at urban
sites. In addition, the concentrations measured often are near the
limits of detectability. Measurements of six nonurban sites in the
United States over a period of years for which results are available in
the NASN data bank are listed in Table 5-1.
5-4
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ANNUAL SULFUR DIOXIDE EMISSIONS FROM COAL- AND OIL-FIRED POWER PLANTS
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-------
TABLE 5-1. SULFUR DIOXIDE CONCENTRATIONS AT NONURBAN SITES
IN THE EASTERN UNITED STATES (in yg nr3)
(ADAPTED FROM NASN DATA BANK)
Site
First
quarter
Second
quarter
Third
quarter
Fourth
quarter
Annual
average
Acadia National Park, MA
1968
1969
1970
1971
1972
1973
Coos County, NH
1970
1971
1972
1973
Calvert County,
1970
1971
1972
1973
8
12
15
19
6
9
ND
12
7
13
MD
ND
20
5
12
Shenandoah National
1968
1969
1970
1971
1972
1973
20
16
16
15
10
18
7
9
7
11
6
ND
ND
10
6
ND
ND
15
6
9
Park, VA
5
7
6
8
5
8
5 9 10
889
8 15 11
7 9 13
6 7 7
ND ND
12 8 -
799
499
ND ND
10 18
8 9 13
6 § 7
ND 8 -
6 11 10
9 11 11
11 8 11
7 10 11
5 19 9
6 7 9
5-9
-------
TABLE 5-1. CONTINUED
Site
First
quarter
Second
quarter
Third
quarter
Fourth
quarter
Annual
average
Jefferson County, NY
1970
1971
1972
1973
ND
8
3
8
ND
5
5
19
16
6
5
ND
ND
7
9
25
7
6
Monroe County, IN
1967
1968
1969
1970
1971
1972
1973
19
13
19
13
11
15
30
5
7
10
8
8
10
11
6
7
8
16
7
7
10
33
12
18
10
14
15
10
11
10
14
12
11
11
15
ND = not detectable.
5-10
-------
The annual average concentrations range near 10 yg m-3. First-
and fourth-quarter concentrations often exceeded second-quarter
concentrations, and concentrations during the third quarter of the year
were almost always the lowest .values at each site. No clear trends in
nonurban S02 concentrations with time are evident on an annual average
or quarterly basis (Figures 5-1 to 5-3). Although average S02
concentrations at nonurban sites were much lower than at urban sites
during the 1960's, the difference between urban and nonurban S02
concentrations narrowed substantially in the 1970's.
Mueller et al. (1980) reported measurements from the Sul fate
Regional Experiment (SURE) obtained from a 54-station nonurban network
operated in August and October 1977 and mid-January, February, April,
July, and October 1978. The S02 concentrations measured in New
England and the Southeast were almost always below 26 yg m-3, except
during January-February 1978. Monthly average isopleths for S02 of
between 26 and 52 yg m-3 included varying portions of several
midwestern and mid-Atlantic States from month to month during the study.
Monthly average S02 concentrations of about 80 yg m-3 were shown
for small areas in August 1977 and January-February 1978. The highest
S02 concentrations tended to be in portions of the Ohio River Valley
and western Pennsylvania. These concentrations of S02 at SURE sites
were substantial compared to those reported at urban sites in the late
1970's. However, other measurements in western Pennsylvania in July and
August 1977 resulted in average S02 concentrations of 18 yg nr3
(Pierson et al. 1980a), which are substantially lower than those
reported by Mueller et al. (1980).
S02 measurements at rural sites in Union Co., KY, Franklin Co.,
IN, and Ashland Co., OH, were reported between May 1980 and August 1981.
Monthly average S02 concentrations ranged from as low as 8 to 10
yg m-3 during summer months to as high as 30 to 40 yg m-3 during
the winter months (Shaw and Paur 1982).
A number of Canadian monitoring networks were established during
the 1970's (Whelpdale and Barrie 1982). While precipitation
measurements have received the greater emphasis in these networks, air
quality measurements for sulfur dioxide are available from the Air and
Precipitation Monitoring Network (APN) (Barrie et al. 1980, 1983;
Whelpdale and Barrie 1982). Six monitoring sites east of Manitoba are
in operation at rural locations. Sulfur dioxide is collected on a
24-hour integrated basis on a chemically impregnated filter. A
low-volume sampler operates at a flow rate of about 20 a min-1 at an
elevation of 10 meters. The geometric means of 24-hour average S02
concentrations on a yg m-3 basis for the period November 1978 to
December 1979 are: Long Point, Ontario, 11; Chalk River, Ontario, 5.5;
ELA-Kenora, Ontario, 0.86; Kejimkujik, Nova Scotia, 0.86 (Barrie et al.
1983). Large concentration fluctuations are observed at these sites,
which are attributed to the alternating presence of clear background air
and air polluted by large S02 sources in the Lower Great Lakes area
(Barrie et al. 1980).
5-11
-------
Within Europe, annual mean S02 concentrations range from about 20
yg m-3 in rural areas of the United Kingdom, the Netherlands, and
the Federal Republic of Germany to concentrations of 2 yg m-3 or
lower in the remote areas of northern and western Europe (Ottar 1978).
This range of S02 concentrations over rural areas in Europe is close
to the range of concentrations discussed above for rural areas of North
America.
Georgii (1978) has reviewed aircraft measurements of S02 over the
European Continent. The average concentration of SO? decreased from
about 5 yg m-3 at 2 to 3 km altitude down to 1 yg nr3 at 5 km
altitude. From other aircraft flights, Georgii and Meixner (1980)
obtained a mean concentration of 1.3 yg m-3 above 6 km over Europe.
5.2.2.3 Concentration Measurements at Remote Locations—Meszaros (1978)
reviewed remote measurements of S02 concentrations.Several
investigations had been reported of $03 concentrations as a function
of latitude over the Atlantic Ocean. Concentrations of SO? ranging
from 0.1 to 0.2 yg m-3 were observed at latitudes above 60bN and
below 10°N in the northern hemisphere as well as in the southern
hemisphere. Between latitudes of 10°N and 60°N over the Atlantic Ocean
S02 concentrations increase to 1 yg m-3 at 25°N and at 55°N
latitude and peak at about 3 yg m-3 at 40°N latitude. These large
increases in S02 concentrations at midlatitude were attributed to
continental emission sources. Other investigations resulted in
concentrations of S02 averaging 0.3 yq nr3 over the Pacific Ocean
and 0.2 yg m-3 over the Indian Ocean (Meszaros 1978).
Measurements of S02 concentrations were obtained in aircraft
flights over remote areas as part of the 1978 Global Atmospheric
Measurements Experiment of Tropospheric Aerosols and Gases (GAMETAG) by
Maroulis et al. (1980). The areas sampled were between 57°S and 70°N
and included the central and southern Pacific Ocean and the western
section of the United States and Canada. The average S02
concentrations reported in pptv were as follows: northern hemisphere,
boundary layer, 89; free troposphere, 122; southern hemisphere, boundary
layer, 57; free troposphere, 90. The S02 concentrations in pptv over
marine and continental environments were as follows: marine boundary
layer, 54; free troposphere, 85; continental boundary layer, 112; free
trophosphere, 160. The boundary layer S02 concentrations were in the
0.1 to 0.3 yg m-3 range in reasonable agreement with other remote
measurements (Meszaros 1978). Bonsang et al. (1980) reported S02
concentrations ranging from 0.03 yg m-3 over the tropical Indian
Ocean to 0.3 yg nr3 over the Peruvian upwelling. A relationship was
identified between the atmospheric S02 concentrations and the
biological activity in sea surface waters (Bonsang et al. 1980).
The SO? concentrations measured at many remote sites are factors
of 10 to 100 less than those measured at rural sites in eastern North
America (Section 5.2.2.2). However, the S02 plume from eastern North
America appears to cause large increases in the S02 concentrations
measured at midlatitudes well into the Atlantic Ocean (Meszaros 1978).
5-12
-------
A similar impact of large plumes from strong source areas has been
observed at several rural Canadian sites (Barrie et al. 1983).
5.2.3 Sulfate
5.2.3.1 Urban Concentration Measurements—In 1963 the National Air
Sampling Network collected partlculate matter on high-volume (h1-vol)
samplers and began analyzing for sulfur as water-soluble sulfate at
urban sites in the United States.
The potential for a positive sulfate artifact resulting from
collection and conversion of S02 on glass-fiber filters was discussed
by Lee and Wagman (1966). Subsequent laboratory studies have shown that
the magnitude of such an artifact depends on S02 concentration, the
air volume per unit area of filter surface, temperature, and other
parameters (Coutant 1977, Mesorole et al. 1976). The conversion of
S02 to sulfate on clean glass-fiber filter surfaces was sensitive to
temperature but showed little dependency on humidity. A substantially
smaller artifact was obtained on surfaces coated with ambient air
particulates than on uncoated filter surfaces. Coutant (1977) estimated
sulfate loading errors from the use of untreated glass-fiber filters
under usual flow conditions in hi-vol samplers to be in the range of 0.3
to 3.0 yg m-3.
The results reported from field observations have varied widely
from small or negligible to large artifact effects (Appel et al. 1977,
Pierson et al. 1976, Stevens et al. 1978). However, differences in
sampling techniques and analytical procedures used complicated
comparisons. It will be assumed that sulfate artifacts are not large
enough to influence substantially the trends in sulfate concentrations
observed. If the sulfate artifacts were substantial, part of the
decreases in ambient air sulfate concentrations would have to be
attributed to the concurrent reductions in sulfur dioxide, Conversely,
increases also occurred in ambient air sulfate concentrations. These
increases were even larger than indicated, if they occurred at the same
time a positive sulfate artifact was decreasing.
At most urban sites in the western United States in the 1960's,
sulfate concentrations were below 10 yg m-3; at three-quarters of
the urban sites in the eastern United States concentrations were above
10 yg m~3 (Altshuller 1973). The general order of decreasing
sulfate concentrations by geographic region in the 1960's and 1970*s
was: (1) East Coast, (2) Midwest (east of Mississippi), (3) Southeast,
(4) West Coast, (5) Midwest (west of Mississippi), and (6) western
states. Average sulfates for urban sites in the western United States
ranged from 30 to 50 percent of the concentration of sulfate at urban
sites on the East Coast.
The excess in urban sulfate concentrations over the regional
background of sulfate is a measure of the contributions by local primary
sources and atmospheric transformations within the urban area
(Altshuller 1976, 1980). Although regional background levels of S02
5-13
-------
were small compared to urban concentration levels, regional background
levels of sulfate have been substantial In the eastern United States
compared to urban concentration levels (Altshuller 1976, 1980). These
regional background levels of sulfate are formed from atmospheric
transformations of sulfur dioxide to sulfate (see Chapter A-4).
Control of local sulfur oxide emissions by reductions in fuel
sulfur content resulted in a substantial reduction in ambient air
sulfate concentrations, particularly in the first and fourth quarters of
the year (Altshuller 1980). The largest decreases occurred in urban
areas in the northeastern United States, but smaller decreases also
occurred in urban areas in the Midwest and Southeast. In contrast,
during the third quarter of the year, ambient air sulfate concentrations
increased in the 1960's and 1970's, and then decreased somewhat at some
sites. Increasing sulfute concentrations during the third quarter
occurred well into the 1970's at some sites in the Ohio River Valley
region and at sites in the South.
The urban excess, the difference between the average urban and the
average regional (nonurban) sulfate concentration in a region, decreased
substantially between 1965-67 and 1976-78 in the North, Midwest, and
Southeast during the first and fourth quarters of the year (Altshuller
1980). Smaller decreases in the urban excess occurred in the second and
third quarter in the Northeast and Midwest, but increases occurred in
the southeastern urban areas.
The increase in third-quarter sulfate concentrations at urban sites
in the late 1960's into the 1970's occurred on the average in the
northeast, southeast, and midwestern regions, indicating geographic-
scale processes at work. The increases occurred consistently at sites
in the Ohio Valley area and adjacent areas in the Southeast. Regional-
scale sulfate episodes or potential episodes increased in frequency
during the same period. Most of these episodes occurred in the June-
through-August period of each year (Altshuller 1980). Therefore, the
higher sulfate concentrations in the summer months at urban sites are
likely to be associated with large regional-scale processes {Altshuller
1980, Hidy et al. 1978, Mueller et al. 1980).
In the late 1970's, the average urban sulfate concentrations by
quarter of the year in the northeastern, southeastern, and midwestern
United States had the order: third quarter > second quarter > first
quarter > fourth quarter (Altshuller 1980). The first- and
fourth-quarter average urban sulfate concentrations in the Northeast and
Southeast were below 10 yg nr3; the third-quarter average urban
sulfate concentrations in the Southeast and Midwest were at 15 ug
m-3. The urban excess, the difference between the average urban and
average nonurban sulfate concentrations, had decreased by the late
1970's compared to earlier years, except in the Southeast. Regional
trends at urban sites in the United States also have been discussed by
Frank and Possiel (1976). Plots of the regional distribution of
sul fates were developed.
5-14
-------
5.2.3.2 Urban Composition Measurements--The composition of the sulfate
in urban areas has been the subject of a number of investigations. In
several investigations of aerosol composition within urban areas,
including Philadelphia, PA, Chicago, IL, Charleston, WV, and Secaucus,
NJ, the sulfate appeared to be in the form of ammonium sulfate
[(NH4)2$04] (Wagman et al. 1967, Lee and Patterson 1969, Patterson
and Wagman 1977, Lewis and Macias 1980). However, no special
precautions were taken to preserve sample acidity.
Tanner et al. (1979) using a coulometric modification of the Gran
titration, reported aerosol samples in New York City to be slightly on
the acidic side of (NH/^SCty in winter (February 1977), but to
have the more acidic average composition of letoricite,
(NH4)3H(S04)2» in the summer (August 1976). These investigators
also found sulfate to be highly correlated with ammonium in both summer
and winter aerosols. Lioy et al. (1980) during a high sulfate episode
in the east on August 3 to 9, 1977, observed high acidities at nonurban
sites, as did Pierson et al. (1980a). However, in New York City the
aerosol appeared to be nearly neutral suggesting higher ammonia fluxes
in and near New York City.
Coburn et al. (1978) measured the acidity of sulfate aerosols in
St. Louis, MO, by an in situ thermal analysis technique during a 16-day
period in late April to early May 1977. Although the acidity reached a
one-to-one ratio of [NH4+] to [H+] on one morning, for the most
part the sulfate aerosol tended to be in the form of ^4)2804.
In earlier measurements in the Los Angeles area during 1972 and
1973, sufficient ammonium ion appeared to be present to neutralize the
sulfate to (NH4)2$04 except near strong local sources of sulfur
oxides (Appel et al. 1978). However, the authors did point out that the
techniques used could not distinguish between neutralization of acidic
constituents before and after collection. In subsequent measurements in
July 1979 at Lennox near strong sulfur sources, significant levels of
H2$04 and particulate acidity were obtained (Appel et al. 1982).
Sulfuric acid constituted 10 to 20 percent of the total sulfate.
It would appear that the sulfate aerosol in urban areas tends
toward the composition of ^4)2804, but that its composition is
variable with more of a tendency toward acidic species in the summer.
5.2.3.3 Nonurban Concentration Measurements--Althsuller (1973) pointed
out large differences in the range and average concentrations for sites
in the eastern compared to the western United States based on
measurements of sulfate concentrations at nonurban sites in 1965-68.
Relatively little overlap occurred in frequency ranges, with the sulfate
concentrations at eastern sites averaging 8.1 yg m-3, and those at
western sites averaging 2.6 yg nr3. At 10 percent of western sites,
annual average concentrations were as low as 0.5 to 1.0 yg m-3.
The eastern and western sites appeared to represent separate and
distinct populations as far as sulfate concentrations were concerned
(Altshuller 1973). A continental background of less than 1 yg m~3
5-15
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was Indicated by the minimum sulfate concentration levels at eastern and
western nonurban sites. A more detailed stratification of results on
sulfate concentrations at nonurban sites in the United States indicates
the order of decreasing sulfate concentrations in the 1965-72 period to
be: (1) East Coast and Midwest (east of Mississippi River), (2)
Southeast, (3) Southwest, (4) Midwest (west of Mississippi River) and
West Coast, and (5) Mountain States.
Between 1963-65 and 1976-78, sulfate concentrations at nonurban
sites varied only slightly in the first, second, and fourth quarters of
the year (Figures 5-1 to 5-3) (Altshuller 1980). The first- and
fourth-quarter trends showed both small increases and decreases in
sulfate concentration at the nonurban sites in the Northeast, Southeast,
and Midwest (Altshuller 1980). The second-quarter trends either were
positive or showed no change in these three regions.
At the nonurban sites in the northeastern and midwestern United
States, the third-quarter sulfate concentrations increased during the
1960's, peaked in the early 1970's, and subsequently decreased, just as
at the urban sites in these regions (Altshuller 1980). This upward
trend occurred most consistently for nonurban sites in the Ohio Valley
area.
Although urban sites showed decreases in sulfate concentration
during the winter quarters, presumably owing to local-scale reductions
of sulfur oxide emissions (Altshuller 1980), no substantial changes were
experienced at nonurban sites distant from such local influences.
Conversely, since third-quarter trends were presumably influenced
strongly by larger regional processes, both urban and nonurban sites in
the same region and even across regions should show similar behavior.
The second quarter showed intermediate behavior. Despite the large
upward trends in sulfur emissions fr$m power plants during the 1960's
and 1970's (Figure 5-4), very small increases were measured at nonurban
sites in the Midwest or East. The only substantial upward trends were
in the third quarter of the year at nonurban sites. The trend downward
after the early 1970's at the midwestern nonurban sites during the third
quarter of the year appears consistent with the downward trend between
1970 and 1978 of sulfur emissions in most midwestern states (Chapter
A-2, Table 2-14).
A plot of the regional distributions of nonurban sulfate concen-
trations averaged from months in 1977 and 1978 are shown in Figure 5-5
(Hilst et al. 1981). Sulfate concentrations were the highest in the
Ohio Valley area followed by other parts of the Midwest, mid-Atlantic
states and Southeast. During summer months in 1977 and 1978, Mueller et
al. (1980) observed a broader regional distribution of sulfates than
observed during the entire study period, with high sulfate concentra-
tions extending all the way from the Ohio River Valley to the Atlantic
Seaboard.
In the late 1970's the average nonurban sulfate concentrations in
the eastern and midwestern United States had the same ordering by
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1-HOUR
S02 (ppb)
24-HOUR
2" hig I"'3
Figure 5-5. Sulfur dioxide (arithmetic mean) and sulfate (geometric
mean) concentrations. Data obtained during 5 months
between August 1977 and July 1978. Adapted from
Hilst et al. (1981)-
5-17
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quarter of the year as at urban sites: third quarter > second quarter >
first quarter > fourth quarter (Altshuller 1980). Based on sulfate
measurements made from May 1980 to August 1981 at three rural sites in
the Midwest, Shaw and Paur (1982) reported monthly average
concentrations ranging from as low as 3 yg m-3 in some winter months
up to 12 to 15 yg m-3 in the summer months. The seasonal variations
in sulfate concentrations were just the opposite of those of sulfur
dioxide. As a result, the percentage of particle sulfur of total sulfur
measured ranged from 5 to 10 percent in the winter months to more than
40 percent in the summer months.
Diurnal sulfate concentrations were measured at two rural sites,
one in Kentucky and the other in Virginia, during the summer of 1976
(Wolff et al. 1979). Two types of diurnal patterns for sulfate
concentrations were observed. On one group of days, the sulfate
concentrations peaked in midafternoon at about the same time the ozone
concentrations peaked. Downward mixing of sulfate from the layer aloft,
as the noctural inversion layer broke up, was suggested as being
responsible for a substantial fraction of the sulfate in these afternoon
peaks. The second diurnal pattern involved sulfate concentration
peaking between 2000 and 0400 hours at night. This type of diurnal
behavior appeared to be most pronounced on clear nights when ground fog
developed. A few days fell into neither of these two patterns. These
latter days were characterized by very low sulfate concentrations, < 5
yg m-3, and occurred after passage of a cold front.
The sulfate concentrations measured at rural monitoring sites
outside of St. Louis, MO, were 80 and 90 percent of the sulfate
concentrations at urban sites within St. Louis during the years 1975
through 1977 (Altshuller 1982). These results also are consistent with
a strong regional influence on sulfate concentration distributions.
Vertical profile measurements were obtained from aircraft flights
over southeastern Ohio in early August 1977 and January 1978 (Mueller et
al. 1980). Measurements were made in the layer between 0.3 and 1.5 km
and at a higher layer between 1.5 and 3 km above mean sea level. On the
average, the sulfate concentrations in the lower layer were similar to
those obtained at ground sites. The sulfate concentrations in the upper
layer were smaller than in the lower layer. In August 1977, the
aircraft measurements indicated that the sulfate concentrations in the
lower layer were about twice as high in the afternoon hours as in the
morning hours. In a winter period, the sulfate concentrations varied
little between the morning and afternoon hours in the lower layer aloft.
The sulfate concentrations in the lower layer in the winter were about
one-third of those in the afternoon in the summer.
Twenty-four-hour average sulfate concentrations were measured in
the Canadian APN concurrently with SO? concentrations (Barrie et al.
1980, 1983; Whelpdale and Barrie 1982). Atmospheric particulate matter
was collected on a Whatman 40 particulate filter, which preceded the
chemically impregnated filter used to collect sulfur dioxide. Sulfate
was determined by means of ion chromatography. The geometric means of
5-18
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the 24-hr average sul fate concentrations on a yg m-3 basis for the
period November 1978 to December 1979 are: Long Point, Ontario, 1.0;
Chalk River, Ontario, 1.9; ELA-Kenora, Ontario, 1.0; Kejimkujik, Nova
Scotia, 1.8 (Barrie et al. 1983). Sulfate concentrations do not
decrease as rapidly as do S02 concentrations with distance from major
source regions. Sulfate concentrations, just as S02 concentrations,
show large fluctuations attributed to the alternate presence of clean
air and polluted air from large source regions (Barrle et al. 1980).
Concentrations of sulfate as a function of percentage cumulative
frequency are plotted In Figure 5-6 (Barrle et al. 1983). Results from
Canadian sites from the period November 1978 to December 1979 are
compared with those obtained in the eastern United States during
1974-75. Except for the highest sulfate concentrations experienced at
Canadian sites in lower Ontario, the sulfate concentrations at Canadian
sites fall well below those at sites in the United States. This is
particularly so for the Canadian sites more remote from large source
regions.
5.2.3.4 Nonurban Composition Measurements—Charl son et al. (1974)
reported evidence obtained from a semi quantitative humidographic
technique of acidic sulfate species frequently present at a rural site
outside of St. Louis during September 1973. The acidic composition was
variable (Char!son et al. 1974, 1978a). The sul fate aerosols were
acidic more frequently at the rural site than at the urban site. There
was no dependence on wind direction nor on synoptic conditions,
consistent with regional sources of the sul fate aerosol (Charlson et al.
1974).
Samples were obtained at 125 m above ground level on a
meteorological tower at Brookhaven National Laboratory from May through
November 1975 (Tanner et al. 1977). The ratio of [H+] to [NH4+]
in ng m-3 varied from 0 to 1.6:1. In 9 of the 11 samples taken
[NH4+] was substantially in excess of [H+], particularly for the
three samples collected in October and November, which were
predominantly in the form of (NH/i^SOA. Use of a diffusion
battery sampling technique indicated that particles below the optical
range were more acidic than the particles that effectively scatter
light. It also was observed that air mass passage over water from
source areas resulted in more acidic particles in the suboptical range
than for air mass passage over land.
Aerosol measurements were made at a rural site at Glasgow, IL,
during a 9-day period late in July 1975 (Tanner and Marlow 1977).
During the earlier portion of the sampling period with little or no
strong acidity measurable, the air mass backward trajectories indicated
reasonably direct transit from urban and/or power plant sources.
Stagnation conditions occurred on July 29-30, with movement of the air
mass from St. Louis past the vicinity of large power plant sources.
Significant strong acidity was measurable in the aerosols reaching the
Glasgow, IL, site during this period.
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100
50
m 10
i
e
oo
LU
-------
Measurements of sulfate aerosol composition were made in Research
Triangle Park, NC, during 4 days in July 1977 (Stevens et al. 1978).
Care was taken to preserve the acidity of the samples with use of a
diffusion denuder to remove ammonia during collection and with
preservation of the samples over nitrogen before analysis. The amount
of strong acidity measured was highly variable among the 16 samples. In
about half the samples, the strong acidity was zero or near zero. In
three of the samples, the ratio of [H+] to [NH4+] in neq m"3 was
near 1:1. The highest ratio of [H+] to [NH4+] occurred
concurrently with the highest sulfate concentration.
Measurements of aerosol composition were carried out at a site in
Tennessee at 646 m altitude in the Great Smoky Mountains National Park
in the latter part of September 1978 (Stevens et al. 1980). Each of the
12 aerosol samples collected and analyzed for strong acidity were
acidic. The average acidity was close to that of NH4HS04. The
higher ratios of [H+] to [NH4+] occurred with the higher sulfate
concentrations. Because no denuder was used to remove ammonia, some
neutralization could have occurred. Therefore, it is possible that the
samples were even more acidic than indicated by the measurements.
Weiss et al. (1982) at the Shenandoah Valley site obtained
(NH4+)/(s042~) molar ratios ranging from 0.5 to 2.0 with strong
diurnal variations. The particles were most acidic in mid-afternoon and
least acidic between 0600 and 0900 hours.
Sulfate composition measurements were made on samples collected at
853 m on top of a tower on the summit of Allegheny Mountain in
southeastern Pennsylvania between July 24 and August 11, 1977 (Pierson
et al. 1980a). On the average, the [H+] was slightly in excess of
[NH4+], corresponding to a composition near that of NH4HS04.
The concentrations of the other cations were so low that [H+] and
[NH4+] were the predominant cations associated with [S042"], and
the sum of [H+] and [NH4+] was essentially stoichiometric with
[SO*2-]. For sulfate concentrations above 15 yg m~3 the [H+]
to [SOd ] mole ratio was between 1:1 and 2:1 and approached 2:1 for
several samples. Therefore, appreciable amounts of ^$04 must have
been present at the high sulfate concentration levels.
Lioy et al. (1980) reviewed in detail the high sulfate episode
during August 3-9, 1977. The occurrence of a strong acid distribution
on a regional scale was identified by these workers, based on
measurements at High Point, NJ, Brookhaven, NY, and Allegheny Mountain
(Pierson et al. 1980a).
Evidence of strong acidity comes from samples collected at various
rural sites in the northeastern and midwestern United States between May
and September, 1977. In several investigations, the tendency was for
the higher ratios of [H+] to [NH4+] to occur concurrently with the
higher sulfate concentrations (Stevens et al. 1978, 1980; Pierson et al.
1980a).
5-21
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The only samples collected at Brookhaven National Laboratory in
October and November 1975 were of low acidity (Tanner et al. 1977). In
samples collected on the Swedish Coast, Brosset (1978) also obtained low
[H+]-to-[NH4+] ratios for winter samples. During "white" winter
episodes, the [H+]-to-[NH4+] ratios rarely exceeded 1:1 and
frequently were well below 1:1. The species observed by X-ray
diffraction included (NH4)2S04, (NfahHtSO/ib, and
NH4HS04 (Brosset 1978).
In general, there appears to be substantially more evidence for
strong acidic species at rural sites than at urban sites, and the
highest acidities were those measured at mountain sites.
5.2.3.5 Concentration and Composition Measurements at Remote
Locations--Meszaros (1978) reviewed available sulfate measurements at
remote locations. He estimated an average sulfate concentration of 1.3
yg nr3 over the Atlantic Ocean. The sulfate concentration as a
function of latitude have two maxima. One of these occurs near 40°N
latitude where SC^ also has a maximum concentration and the other
occurs south of the equator. Around 40°N the sulfate concentration is
2 yg nr3, but decreases below 1 yg m'3 above 50°N. He estimated
sulfate concentrations of about 0.3 yg m"3 over clean areas in the
Northern Hemisphere.
Gravenhorst (1978) obtained an average sulfate concentration of
excess sulfate (excluding the contribution of sea salt) of 0.9 yg
nT3 ± 0.5 yg m'3. The excess sulfate tended to be acidic.
Measurements of sulfate were made at a remote sampling site in the
Faroe Islands during February 1975 (Prahm et al. 1976). During a period
when air masses were crossing the site after traveling only over the
North Atlantic, excess sulfate averaged 0.14 yg m~3. During another
period when air masses had passed over the British Isles upwind, the
excess sulfate averaged 1.07 yg m~3.
An excess of submicron sulfur particles also was measured at a site
in Bermuda (Meinert and Winchester 1977). The excess sulfur was
attributed to long-range transport from the North American Continent.
Aerosol samples were collected from aircraft flying in the central
and southern Pacific Ocean and remote areas of North America during
GAMETAG by Huebert and Lazrus (1980a). The ranges of sulfate
concentrations in different environments in yg nr3 were:
continental boundary layer, < 0.25 to 0.5; marine boundary layer, 0.36
to 3.6; free troposhere, < 0.06 to 0.35.
As indicated by the results of Meinert and Winchester (1977),
Meszaros (1978), and by Prahm et al. (1976), remote sites can presumably
be fumigated by continental sources well upwind.
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5.2.4 Particle Size Characteristics of Particulate Sulfur Compounds
5.2.4.1 Urban Measurements—Particle size distributions have been
reported in a number of urban locations for sulfur as sulfate 1n
collected particulate matter. Similar results do not appear to be
available for sulfur in any other valence state. Stevens et al. (1978)
attempted to analyze for sulfite in samples from South Charleston, WV,
Research Triangle Park, NC, Philadelphia, PA, and New York, NY. The
sulfite content of the samples did not exceed the minimum detection
limit of 8 ng nr-3. By comparison with the fine particle sulfur
concentration, this results in less than 0.1 percent of the extractable
sulfur as sulfite or 2 percent of the total fine particle (< 3.5 pro)
sulfur as sulfite.
A five-stage impactor with stage mass median diameters (MMD's) of
1.9, 3.6, and 7.2 ym with a backup filter was used at two sites in
Pittsburgh, PA, in 1963-64 to separate particulate matter into size
fractions (Corn and Demaio 1965). Sulfate was measured by a
turbidimetric method. A substantial amount of the sulfate was reported
to be in larger particles with MMD's between 1.9 and 3.6 ym.
Size distribution of sulfate in particulate matter was determined
by Roesler et al. (1965) at sites in Chicago, IL, and Cincinnati, OH. A
six-stage Andersen cascade impactor was used for particle size
distributions. Sulfate was measured by a turbidimetric method. The
MMD's obtained at the sites in Cincinnati and Chicago were 0.4 ym and
0.3 ym, with nearly 90 percent of the sulfate below 3.5 ym.
Wagman et al. (1967) obtained sulfate size distributions at sites
in Chicago, IL, Cincinnati, OH, and Philadelphia, PA, during 1965. Lee
and Patterson (1969) reported ammonium size distributions during the
same time periods at these sites. A six-stage Andersen cascade impactor
was used for size separations. Sulfate was analyzed by the
turbidimetric method, and ammonium was determined by the Nessler method
with alkaline potassium mercuric iodide. The average MMD's for sulfate
and ammonium were similar, with an overall range from 0.35 to 0.66 ym.
The higher MMD in Philadelphia was attributed in part to dust generated
from road construction near the site. Eighty percent of the sulfate was
below 2 ym at all of the sites.
Sulfate particle size increased with humidity at all sites (Wagman
et al. 1967). Substantial scatter occurred with MMD ranging from below
0.2 ym at lower humidities to 0.6 to 0.8 ym at higher humidities at
three midwestern sites. At the site in Philadelphia, PA, the MMD
exceeded 1 ym at higher humidities. Correlation of MMD's with
absolute humidities was poor.
Ludwig and Robinson (1968) obtained particle size distribution of
samples collected in the Los Angeles and San Francisco Bay areas of
California in 1964-65. A Goetz aerosol spectrometer was used. The
analytical procedure involved high-temperature reduction of the sulfur
in the sample to hydrogen sulfide in a microcombustion furnace and
5-23
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iodimetric nricrocoulometric tltration for the hydrogen sulflde. Average
MMD's were computed from measurements at several sites 1n Los Angeles
and the San Francisco Bay area. Except at the Lennox, CA, site, the
MMD's ranged from 0.2 to 0.4 ym. The Lennox site is directly downwind
of a number of emission sources, including an oil refinery and a sewage
treatment plant, and is 2 miles from the ocean, which may account for
the higher MMD at this site.
Ludwig and Robinson reported that at these West Coast sites, samples
collected during periods of higher relative humidity (RH) had the higher
MMD's for sulfur-containing particles. The weighted average MMD varied
from 0.1 ym in the 12.5 to 27.5 percent RH class to 1.1 ym in the
72.5 to 87.5 percent RH class.
Ludwig and Robinson also observed diurnal decreases in the sulfate
size distribution by time of day as follows: forenoon > afternoon >
early morning > evening. Wagman et al. (1967) did not observe
consistent diurnal changes in sulfate size distribution from site to
site. In fact, only the Chicago, IL, site showed significant changes in
sulfate size distribution with sulfate size decreasing by time of day as
follows: morning > midday > evening. Therefore, in Chicago and at the
West Coast sites, sulfate particles tended to be smaller during the
evening hours. Both groups of investigators reported no relation
between diurnal variations in sulfate size and humidity changes, but no
explanation in terms of atmospheric processes was suggested.
Particle size distributions for sulfate and other species were
obtained in Riverside, CA, during the first half of November 1968
(Lundgren 1970). Samples were collected on a four-stage Lundgren
impactor. The average MMD for sulfate was about 0.3 ym with the range
of MMD's for the 10 samples collected varying from 0.1 to 0.6 ym. On
the average, about 90 percent of the sulfate in the collected particles
was below 1.7 ym. Particle size distributions of sulfate also were
reported by Appel et al. (1978) for the Los Angeles, CA, Basin area as
0.3 to 0.4 ym for most samples.
Patterson and Wagman (1977) obtained particle size distribution of
collected samples for a number of species including sulfate and ammonium
in Secaucus, NJ, near New York, NY, between September 29 and October 10,
1970. Seven-stage Andersen cascade impactors were used at 28 a
min-1, with either Gelman type A glass-fiber or Millipore* backup
filters. Sulfate was analyzed by the methods used previously (Wagman et
al. 1967, Lee and Patterson 1969). The air masses traveling across the
site were classified into four visual range classes. For sulfate and
ammonium, the MMD's, by visual range class, were:
Visual range (mi) Sulfate (ym) Ammonium (ym)
> 26 0.60 0.26
13 to 26 0.39 0.34
8 to 13 0.46 0.38
< 8 0.40 0.36
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The MMD's for sulfate and ammonium were reasonably similar except for
the background case of > 26 miles. For this condition, much more of the
mass of the sulfate was in the range 0.54 to 0.95 ym than was the case
for ammonium. Almost all of the sulfate and ammonium in the collected
particles was below 1.5 ym.
Tanner et al . (1979) measured sulfate in August 1976 and February
1977 in New York, NY, using a diffusion battery along with hi-vol
sampling. The diffusion battery was used to classify particles by size
below 0.25 ym before filter sampling and analysis. During the summer
month, about 50 percent of the sulfur-containing aerosols were below
0.25 ym; during the winter month only 25 percent were below 0.25 ym.
Stevens et al . (1978) concluded from measurements for sulfur along
with other metals in New York, NY, Philadelphia, PA, Charleston, WV, St.
Louis, MO, Portland, OR, and Glendora, CA, that sulfate in the fraction
below 3.5 ym had to be associated predominantly with ammonium and
hydrogen ions in urban areas. If all of the metals were assumed to be
in the form of sul fates, only 10 to 32 percent of the sulfate would be
accounted for as metal sul fates at these urban sites. Because it is
likely that most of the metals would be in the form of oxides, halides,
or carbonates rather than sul fates, these estimates would form upper
1 imits.
Separation of particles into two fractions with a fine fraction
consisting of particles below 3.5 ym involves use of a virtual
impactor or dichotomous sampler (Stevens et al . 1978). The percentages
of sulfur found in the size range below 3.5 ym at various sites were:
New York, NY— 93%; Philadelphia, PA— 85%; Charleston, WV— 92%; St.
Louis, MO— 79%; Portland, OR—83%; Glendora, CA— 87%. Sampling was done
in the winter months of 1975 and 1977. In additional measurements
reported from a site in Charleston, WV, 91 percent of the sulfur
measured during a period in the summer of 1976 was in the fine particle
size range (Lewis and Macias 1980).
Altshuller (1982) analyzed data on particulate sulfur measured with
dichotomous samplers at urban sites in St. Louis, MO. From 80 to 90
percent of sulfur measured was fine particle sulfur with no substantial
seasonal pattern between the third quarter of 1975 and the fourth
quarter of 1976.
5.2.4.2 Nonurban Size Measurements— Junge (1954, 1963) reported on the
particle size of sulfate aerosols at Round Hill, MA, 50 miles south of
Boston, and at a site south of Miami, FL. He found most of the
particles containing sulfate to be in the 0.08 to 0.8 ym range rather
than in the 0.8 to 8 ym range. Junge (1963) found the average
composition of the particles between 0.08 and 0.8 ym to correspond to
a mixture of (NH4)2S04 and (NH4)HS04-
Charlson et al . (1974) found strong acidity in particles at Tyson
Hollow, MO, 35 km WSW of the Arch in St. Louis, using an integrating
5-25
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nephelometer with humidity control (humldograph). Because the
nephelometer would respond to particles predominantly in the optical
range, 0.1 to 1 m, the technique associates acidity with
subm1cron-s1ze acid sulfate particles. In subsequent work in the St.
Louis area, well over 90 percent of sulfur 1n particles measured at
rural sites near St. Louis were found to be in the fine particle
size range with little, 1f any, seasonal variation (Altshuller
1982).
Measurements of particle size distribution of sulfates were made
with a diffusion battery technique at Glasgow, IL, 104 km NNW of the
Arch In St. Louis, from July 22-30, 1975 (Tanner and Marlow 1977).
About 50 percent of the sulfate containing particles were below 0.25
ym In size. The higher acidities were associated with the submicron
particles.
In the previously mentioned sulfate measurements in the Great
Smoky Mountains National Park, strong acidity was associated with the
fine particle size fraction (Stevens et al. 1980). It was estimated
that ammonium b1sulfate constituted 61 percent of the fine particle
mass.
Pierson et al. (1980a) used an Andersen eight-stage cascade
impactor to obtain particle size distributions for sulfate and hydrogen
ions at a tower on Allegheny Mountain in southwestern Pennsylvania. The
particle size distribution curves for sulfate and hydrogen ion were
almost identical, with an average MMD of 0.8 ym. About 90 percent of
the sulfate and hydrogen ion content was below 3 ym. The
[H+]-to-[S042-] ratios were somewhat higher for particles between
0.7 and 1.1 ym than for those below 0.7 ym, or between 1 and 2 ym.
Acidity was measured in even larger particles but the [H+] to
[SOA^-] ratio was lower than for particles below 2 ym (Pierson et
al. 1980a).
Aircraft outfitted with particle sizing equipment were flown across
portions of Arizona, Utah, Colorado, and New Mexico on October 5 and 9,
1977 (Madas et al. 1980). The MMD for sulfur In the collected
particles was not reported, but can be approximated as below 0.5 ym.
Sulfur particles below 1 ym constituted 92 percent of the sulfur
content.
5.2.4.3 Measurements at Remote Locations—Gravenhorst (1978) found the
excess sulfate in marine aerosols to be present In submicron-size
particles. The sulfate associated with sea salt was present In
supermicron particles. Meinert and Winchester (1977) also found the
excess sulfate to be present 1n submlcron-size particles in samples
collected in Bermuda. Similarly, the excess sulfate in samples
collected off the West African coast was in submicron-size particles and
the larger particles appeared to contain the sulfate associated with sea
salt (Bonsang et al. 1980).
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5.3 NITROGEN COMPOUNDS
5.3.1 Introduction
The nitrogen oxides and their atmospheric reaction products
constitute a more complex group of chemical species than do sulfur
dioxide and particulate sulfates. Unlike sulfates, nitrate composition
frequently is dominated by volatile species, nitrous acid, nitric acid,
and organic nitrates, particularly peroxyacetyl nitrates. Nitrous
oxide, although present in significant trace concentrations in the
atmosphere, does not react within the troposphere.
Nitric oxide, the predominant nitrogen oxide in emissions can be
converted rapidly to nitrogen dioxide by reactions with oxy radicals and
ozone in the atmosphere. Subsequent atmospheric reactions result in the
formation of nitric acid. Nitric acid and ammonia are in equilibrium
with ammonium nitrate. Ammonium nitrate formation is favored by lower
temperatures and sufficiently high levels of ammonia. Mixed nitrate-
sulfate aerosol systans also play a significant role in determining the
nitric acid concentration as does relative humidity. Nitrous acid can
form at night but is rapidly photolyzed in daylight. A wide variety of
volatile organic nitrates can be synthesized in the laboratory; however,
many are short-lived in the atmosphere or, if present, occur at parts-
per-trill ion concentrations. The exceptions are the peroxyacetyl
nitrates (PAN), which are present at significant concentration levels
relative to the other nitrogen oxides and their acids. Because the
peroxyacetyl nitrates and their precursors are in reversible
equilibrium, nitrogen dioxide can be regenerated and nitric acid may be
formed as these species undergo atmospheric transport.
As a consequence of the atmospheric reactions discussed above,
several species containing nitrogen can contribute directly or
indirectly to acidic deposition.
5.3.2 Nitrogen Oxides
5.3.2.1 Historical Distribution Patterns and Current Concentrations
of Nitrogen Oxides--Nitric oxide is the most commonly emitted oxide of
nitrogen. Less than 10 percent of nitrogen oxides are emitted as
nitrogen dioxide (NO;?)- Exceptions are found in emissions from some
types of diesel and jet turbine engines and tail gas from nitric acid
plants, which can contain from 30 to 50 percent nitrogen dioxide.
Because nitric oxide (NO) converts rapidly to NOg in the atmosphere,
N02 is the predominant form of nitrogen found outside cities.
Historical trends for NO and N02 are not available from nonurban
sites but are available from a limited number of urban sites. Because
of these limitations, it is not useful to separate historical trends
from current measurement results.
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5.3.2.2 Measurements Techniques-Nitrogen Ox1des--Most of the nitrogen
oxide measurements made during the 1970' s involved use of chemi 1 umi -
nescent analyzers. While the chemi luminescent technique can be used to
analyze nitric oxide directly and specifically, analysis of nitrogen
dioxide or nitrogen oxides (NO + N02) requires a converter to reduce
nitrogen dioxide to nitric oxide. However, it has been found that such
converters also will reduce other nitrogen compounds to nitric oxide.
Winer et al . (1974) reported that commercial chemi luminescent analyzers
equipped with either molybdenum or with carbon converters quantitatively
reduced peroxyacetyl nitrate to nitric oxide. Nitric acid also was
observed to cause a response in chemi luminescent analyzers, but the
response to nitric acid was not determined quantitatively.
Spicer and coworkers discussed the use of various converters or
scrubbers (Spicer 1977, Spicer et al . 1976b, Spicer and Miller 1976).
Nearly quantitative, but somewhat variable chemi luminescent responses to
nitric acid have been obtained (Spicer and Miller 1976, Spicer et al .
1976b). The reduction of nitric acid to nitric oxide by a stainless
steel converter was shown to increase rapidly from below 10 percent to
over 90 percent between 400 C and 550 C. However, the use of the lower
temperature also reduces the efficiency of conversion of nitrogen
dioxide to nitric oxide by stainless steel converters, so lowering the
temperature would not be a satisfactory approach (Spicer et al . 1976b) .
Although carbon converters will reduce nitrogen dioxide to nitric oxide
efficiently at lower temperatures than stainless steel, the nitric acid
reduction also continues to occur efficiently down to 140 C. Nylon
filters or scrubbers remove nitric acid but not peroxyacetyl nitrate and
provide a basis for analyzing nitric acid differentially (Spicer et al .
1976b). Use of ferrous sulfate as a scrubber was found to remove nitric
acid with high efficiency, but it also removed a variable fraction of
peroxyacetyl nitrate (Spicer et al . 1976b) . Use of such scrubbers with
chemi luminescent instruments permits the analysis not only of nitrogen
oxides but also of other nitrogen compounds (Kelly and Stedman 1979b,
Spicer et al . 1976b, Spicer 1979).
5.3.2.3 Urban Concentration Measurements--The Air Quality Criteria for
Oxides of Nitrogen (U.S. EPA 1982) contains detailed compilations of
ambient air concentrations of nitrogen dioxide in U.S. urban areas.
Pertinent data from the criteria document are summarized in the
following discussion. Average NO and N02 concentrations at Continuous
Air Monitoring Program (CAMP) sites were comparable, while peak
concentrations of NO tended to exceed peak concentrations of N02-
Trends in NO? concentrations at the six CAMP sites in Chicago,
IL, Cincinnati, OH, Denver, CO, Philadelphia, PA, St. Louis, MO, and
Washington, "DC, and at other sites in Los Angeles, CA, Azusa, CA,
Newark, NJ, and Portland, OR, have been tabulated and statistically
analyzed.
The annual mean concentrations of NOa at the sites ranged from 50
to 150 yg m~3 with the higher concentrations occurring at the sites
5-28
-------
in downtown Los Angeles and in Chicago. The maximum 1-hr N02
concentrations at these sites ranged from 200 to 1500 yg m-3. Peak
1-hr concentrations above 750 pg m-3 were frequently measured in
downtown Los Angeles and Azusa, CA, but infrequently, if at all, at
other sites. Both upward and downward trends with time were measured at
these sites.
At 31 urban sites during 1976, the maximum 1-hr concentrations
ranged from 216 to 815 yg m-3. The annual mean concentrations at
two-thirds of these sites ranged from 50 to 100 yg m-3.
Seasonal behavior in N02 concentrations varied at urban sites,
with a summer peak occurring at a site in Chicago, IL, winter peaks at
sites in Denver, CO, and Lennox, CA, but no significant seasonal trends
at other sites in California.
The diurnal patterns of N02 concentrations are available by
quarter of the year at eight sites (Trijonis 1978). Except for the two
sites in the western part of the Los Angeles Basin, the diurnal patterns
show two peaks—one in the morning hours, the other late in the
afternoon or during the evening hours. At the two sites in Los Angeles,
only a single peak late in the morning hours was observed. These peaks
varied in size from site to site and with the quarter of the year.
5.3.2.4 Nonurban Concentration Measurements--Measurements made of
nitric oxide and nitrogen dioxide at suburban and at rural locations in
the United States are tabulated in Table 5-2. Mean and maximum
concentrations of nitrogen oxides are listed. At eastern nonurban
locations the mean concentrations of nitric oxide ranges from 1 to
10 yg m~3 while the mean concentrations of nitric oxide at western
rural locations were at or below 1 yg m-3. Maximum concentrations
of nitric oxide at a number of sites exceeded mean concentrations by
factors of 10 to 30. At eastern nonurban locations the mean
concentrations of nitrogen dioxide ranges were from 2 to 27 yg m-3,
but most of the mean values ranged from 4 to 14 yg m-3. At two
western rural sites the mean concentrations of nitrogen dioxide were at
or below 3 yg m-3. Maximum concentrations of nitrogen dioxide at
most sites listed in Table 5-2 exceed mean concentrations by factors of
5 to 10. Although mean concentrations of nitrogen dioxide at a site
exceed mean concentrations of nitric oxide, maximum concentrations of
nitric oxide at a number of sites equal or exceed maximum concentrations
of nitrogen dioxide. This latter effect suggests that occasional
fumigations by strong local sources of nitric oxide can occur at many
rural locations.
The range of mean nitrogen dioxide concentrations of 4 to 14 yg
m-3 given above compares with the 50 to 100 yg m-3 range obtained
for many urban sites (Section 5.3.2.3). Additional measurements related
to the gradient of nitrogen dioxide concentrations between urban and
rural sites are available from the RAPS/RAMS monitoring results in the
5-29
-------
TABLE 5-2. MEASUREMENTS OF CONCENTRATIONS OF NITROGEN OXIDES AT SUBURBAN AND RURAL SITES
GO
o
Site (Type)
Montague, MA (R)
Ipswhich, MA (R)
Scranton, PA (S)
DuBois, PA (R)
Bradford, PA (R)
McHenry, MD (R)
Indian River
DE (S)
Lewisburg, WV (R)
Shenandoah, VA (R)
Research Triangle
Park, NC (S)
Period of
measurement
(method)
Aug. -Dec. 1977
(chemilumin.)
Dec. 54-Jan. 55
(colorimetric)
Aug. -Dec. 1977
(chemilumin.)
June-Aug. 1974
(chemilumin.)
July-Sept. 1975
(chemilumin.)
June-Aug. 1974
(chemilumin.)
Aug. -Dec. 1977
(chemilumin.)
Aug. -Dec. 1977
(chemilumin.)
July-Aug. 1980
(chemilumin.)
Nov. 65-Jan. 66
Sept. 66-Jan. 67
Ni trie
yg in-
Mean
3
ND
3
ND
2.4
ND
3
1
1
2.3
NA
oxide,
Max.
78
ND
70
ND
34
ND
114
33
NA
NA
NA
Nitrogen
yg
Mean
7
2.6
11
19
5.1
11
5
4
4
10.6
14.3
dioxide,
nr3
Max.
73
3.8
64
70
68
60
48
28
NA
NA
NA
Reference
Martinez and Singh
1979
Junge 1956
Martinez and Singh
1979
Research Triangle
Institute 1975
Decker et al . 1976
Research Triangle
Institute 1975
Martinez and Singh
1979
Martinez and Singh
1979
Ferman et al. 1981
Ripperton et al.
1970
(colorimetric)
-------
TABLE 5-2. CONTINUED
en
i
co
Site (Type)
Research Triangle
Park, NC (S)
Green Knob.NC (R)
Appalachian Mt.
Florida, southeast
coast
DiRidder, LA (R)
Wilmington, OH (S)
McConnelsville, OH
(R)
Wooster, OH (S)
New Carlisle, OH (R)
Ashland, Co., OH (R)
Period of
measurement
(method)
Aug. -Dec. 1977
(chemilumin.)
Sept. 1965
(colorimetric)
July-Aug. 1954
(colorimeteric)
June-Oct. 1975
(chemilumin.)
June-Aug. 1974
(chemilumin.)
June-Aug. 1974
(chemilumin.)
June-Aug. 1974
(chemilumin.)
July-Aug. 1974
(chemilumin.)
May-Dec. 1980
Nitric
yg in-
Mean
10
2.7
ND
1.9
ND
ND
ND
6.0
4.3
oxide,
Max.
249
NA
ND
17
ND
ND
ND
64
NA
Nitrogen
Mean
13
6.4
1.8
4.9
13
12
13
27
15.6
dioxide,
m~3
Max.
145
NA
3.7
43
90
70
90
NA
NA
Reference
Martinez and Singh
1979
Ripperton et al.
1970
Junge 1956
Decker et al. 1976
Research Triangle
Institute 1975
Research Triangle
Institute 1975
Research Triangle
Institute 1975
Spicer et al. 1976<
Shaw et al . 1981
(chemilumin.)
-------
TABLE 5-2. CONTINUED
CO
ro
Si
Franklin
(R)
Union Co
Giles Co
Creston,
Wolf Poi
Pierre,
site 40
Pierre
Jetmore,
te (Type)
Co., IN
., KY (R)
., TN (R)
IA (R)
nt, MT (R)
SD (R),
km WNW of
KA (R)
Period of
measurement
(method)
May-Dec. 1980
(chemilumin.)
May-Dec. 1980
(chemilumin.)
Aug. -Dec. 1977
(chemilumin.)
June-Sept. 1975
(chemilumin.)
June-Sept. 1975
(chervil umln.)
July-Sept. 1978
(chemilumin.)
April-May 1978
(chemilunrfn.)
Nitric
Mean
3
2
5
4
< 1
< 0
1
.0
.5
.7
.0
.25
.2
Oxide,
Max
NA
NA
96
28
NA
NA
NA
Ni trogen
yg
Mean
14
12
11
4
1
2
7
.3
.3
.3
.5
.3
.5
Dioxide,
nr3
Max
NA
NA
55
25
NA
NA
NA
Reference
Shaw et al . 1981
Martinez and
1979
Martinez and
1979
Decker et al.
Decker et al .
Kelly et al.
Martinez and
1979
Singh
Singh
1976
1976
1982
Singh
R = Rural.
S = Surburban.
ND = Not determined.
NA = Not available.
-------
St. Louis area (U.S. EPA 1982). During an air pollution episode in St.
Louis during October 1 and 2, 1976, nitrogen dioxide as well as other
compounds including ozone were elevated in concentration. The diurnal
patterns and concentrations of nitrogen dioxide at rural compared to
urban sites were substantially different. The diurnal patterns at urban
sites included two peaks in nitrogen dioxide, one in the late morning
hours and the other during the evening hours. At suburban sites only an
evening peak in nitrogen dioxide occurred, while at rural sites no peak
in nitrogen dioxide concentration was observed. The evening peaks in
nitrogen dioxide concentration within the city ranged from 250 to 500
yg nr3, while the concurrent concentrations of nitrogen dioxide at
the outermost rural sites, 40 km from the center of the city, ranged
from 20 to 40 yg nr3. Similarly the 24-hr average concentrations of
nitrogen dioxide ranged from 200 to 265 yg nr3 at urban sites but
averaged only 20 yg nr3 at rural sites. These results demonstrate
the rapid decrease in nitrogen dioxide concentrations that can occur
from urban sites to adjacent rural sites.
The cumulative frequency distributions of hourly nitrogen dioxide
concentrations reported in two studies (Decker et al. 1976, Research
Triangle Institute 1975) are reproduced in part in Table 5-3. Except at
the sites evaluated as suburban (Table 5-2), nitrogen dioxide
concentrations exceeding 40 yg nr3 occur very infrequently at
nonurban sites. Even at those sites considered to be in suburban
locations, nitrogen dioxide cocentrations were infrequently above 60
yg nr3. The highest nitrogen dioxide concentrations at nonurban
locations infrequently fall within the range of mean nitrogen dioxide
concentrations at urban sites.
The distinction between suburban and rural sites was made on the
basis of three factors: (1) geographical location, (2) frequency of
elevated concentrations of nitric oxide, and (3) the ratio of nitric
oxide to nitrogen oxides (NO + N02). The third of these factors was
discussed in some detail by Martinez and Singh (1979). They found this
ratio tended to be lower at rural than at urban or suburban sites. At
the four SURE sites they considered rural, the ratios of NO to NOX
ranged from 0.11 to 0.33 and averaged 0.23. At the five SURE sites they
considered suburban, the ratios of NO to NOX ranged from 0.21 to 0.43
and averaged 0.33.
Some of the relationships discussed above may be somewhat biased by
the tendency in a number of the studies involving nonurban sites to
limit the measurements to the warmer months of the year. Nitrogen
dioxide concentrations during the winter months have been reported to
exceed those during the summer months by 50 to 100 percent (Shaw et al.
1981). Nevertheless, the measurements available do indicate a rapid
decrease in nitrogen oxide concentrations from urban to suburban to
rural locations in the eastern United States.
5.3.2.5 Measurements of Concentrations at Remote Locations—The results
of measurements for nitrogen oxides from a number of studies carried out
5-33
-------
TABLE 5-3. CUMULATIVE FREQUENCY DISTRIBUTION OF HOURLY CONCENTRATIONS OF
NITROGEN DIOXIDE AT RURAL AND SUBURBAN LOCATIONS
Site/reference
DuBois,PA
Research Triangle
Institute 1975
Bradford, PA
Decker et al. 1976
McHenry, MD
Research Triangle
Institute 1975
en
do Wooster, OH
4:1 Research Triangle
Institute 1975
Measurement
period
June-Aug. 1974
July-Sept. 1975
June-Aug. 1974
June-Aug. 1974
Percent of hourly average concentrations
greater than stated
20 yg m~3 40 yg nr3
13.2 1.0
2.1 0.1
6.9 0.2
23.8 6.9
concentrations
60 yg m~3 80 yg m"3
0.2 0.0
0.0 0.0
0.1 0.0
1.9 0.3
McConnelsville, OH
Research Triangle
Institute 1975
Wilmington, OH
Research Triangle
Institute 1975
Creston, IA
Decker et al. 1976
Wolf Point, MT
Decker et al. 1976
De Ritter, LA
June-Aug. 1974
June-Aug. 1974
July-Sept. 1975
July-Sept. 1975
July-Sept. 1975
5.6
14.9
0.5
2.6
0.1
1.1
0.0
0.5
0.2
0.4
4.8
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.0
-------
at remote locations are tabulated in Table 5-4. The distinction between
remote and rural locations is somewhat arbitary. In this discussion
locations at which concentrations of nitrogen dioxide of less than 1
yg m~3 were frequently measured are considered to be remote.
However, substantially higher concentrations of nitrogen oxides were
observed at a number of these locations on those occasions that polluted
air masses crossed over the measuring sites.
At Niwot Ridge in the Rocky Mountains 20 miles west of Boulder, CO,
Kelly et al. (1980) reported average concentrations of 0.4 to 0.5 yg
nr3 in clean air, while Bellinger et al. (1982) reported nitrogen
oxide concentrations in a number of clear air masses passing this site
below 0.1 yg nr3. in contrast, Kelly et al. (1980) observed
nitrogen oxide concentrations up to 40 g m~3 when polluted air
arrived from the east. At Adrigole on the coast of Ireland, Cox (1977)
measured nitrogen dioxide concentrations below 1 yg m~3 in maritime
air but also reported measuring maximum hourly concentrations of
nitrogen dioxide of 10 yg m~3 and a maximum daily average value of
about 3 yg nr3. similarly at Loop Head the concentrations of
nitrogen dioxide measured in maritime air by Platt and Perner (1980)
were below 0.3 ug m"3, in other air masses they measured nitrogen
dioxide concentrations from 4 to 5 yg m~3. Therefore, although the
sites listed in Table 5-4 are listed as remote, it was not uncommon for
air masses containing nitrogen oxide concentrations overlapping those at
rural locations to pass across these sites.
In aircraft flights up to 5 to 6 km over West Germany, Drummond and
Volz (1982) measured nitrogen dioxide concentrations in the 0.1 to 1
yg m"3 range. Kley et al. (1981) measured nitrogen oxide
concentrations at 7 km over the vicinity of Wheatland, WY, as low as
0.1 yg m-3. During the 1977 and 1978 GAMETAG flights, nitric oxide
concentrations equal to or below 0.1 yg m~3 were measured in
maritime and in continental air at 6 km.
The measurements at the surface and aloft at remote locations
result in very low concentrations of nitrogen oxides in clean air
masses. The background concentrations at the surface and aloft at
remote locations can be 10 to 100 times lower than at rural locations in
eastern North America (Tables 5-2 and 5-3). The higher concentrations
measured at remote locations are attributed by the various investigators
to polluted air masses from populated areas. Therefore, natural sources
of nitrogen oxides do not appear likely to contribute significantly to
the nitrogen oxide concentration levels in eastern North America.
5.3.3 Nitric Acid
5.3.3.1 Urban Concentration Measurements--Mitrie acid (HN03)
measurements have been limited to short studies within urban areas.
Continuous coulometry (Spicer et al. 1976b, Spicer 1977) with a
detection limit of about 2 ppb and Fourier transform infrared
spectroscopy (FTIR) with a detection limit of 6 ppb (Tuazon et al.
5-35
-------
TABLE 5-4. CONCENTRATIONS OF NITROGEN OXIDtS MEASURED AT REMOTE LOCATIONS
co
CTi
Sites
Colorado, USA
Niwot Ridge
Colorado, USA
Niwot Ridge
Colorada, USA
Fritz Park
Island of Hawaii
Mauna Kea
La ramie, WY
Ireland, Adrigole
Co. Cork
Ireland, Loop
Head
Ireland, Loop Head
Measurement
period
(method)
Jan. and April
1979 (chemilumin.)
Dec. 1980 to Jan.
1981 (chemilumin.)
Fall 1974; Summer
Spring 1975-76
(absorption
spectroscopy) Dec.
1977 (chemilumin.)
Nov. 1954
(colorimetric)
Summer 1975
(chemilumin.)
Aug. -Sept. 1974
(chemilumin.)
April 1979 (Diff.
opt. abs. uv)
June 1979
(chemilumin.)
NO
0.02-
0.06
NA
NA
NA
ND
0.01-0.
<_ 0.2
ND
< 0.01
Concentratic
in yg nr>
N02
NA
NA
< 0.2
NA
2
06 NA
0.8
0.3
0.16
)ns
N0xa
0.4-0.5
< 0.1
NA
0.2-0.5
ND
0.2-0.8
NA
ND
NA
Remarks Reference
Kelly et al . 1980
Bol linger et al.
1982
Noxon 1978
Kley et al . 1981
Junge 1956
Drummond 1976
Maritime Cox 1977
air
Maritime Platt and Perner
air 1980
Maritime Helas and Warneck
air 1981
-------
TABLE 5-4. CONTINUED
Sites
Concentrations
Measurement
period
(method)
1n yg n
3
NO
N02 N0xa
Remarks
Reference
tn
i
CO
Tropical Areas
1965-1966
(colorlmetrlc)
0.1-0.6 0.4-0.8
0.3-0.5 0.6-0.9
0.3-0.8 0.6-0.1
0.3-0.8 0.6-0.9
Under
canopy of
forest
Above
canopy of
forest
Rlverbank
Seashore
and
maritime
Lodge and Pate
1966, Lodge et al
1974
*NOX = NO + N02.
-------
1978, 1980, 1981a,b; Hanst et al. 1982) were used to obtain the ambient
air measurements for HN03 listed in Table 5-5. An intercomparison
study was conducted on the 10 different techniques for measuring nitric
acid on Claremont, CA, during an 8-day period in August and September
1979 (Forest et al. 1982; Spicer et al. 1982a). The methods compared
included chemiluminescence, infrared, diffusion denuder, and filtration
techniques. The nitric acid concentrations ranged from 1.85 to 37.05
yg m~3 or 0.7 to 14.4 ppb based on the median values of the 10
methods (Spicer et al. 1982a).
The average HN03 concentrations in the Los Angeles Basin area
ranged from 7 to 40 yg nr3 (Table 5-5). The Riverside site where
the highest ammonia concentrations were measured had the lower HN03
concentrations. This follows from the equilibrium between nitric acid
and ammonia, with ammonium nitrate aerosol being shifted toward aerosol
formation in the presence of high ammonia concentrations.
NH4N03 t NH3 + HN03-
The maximum HN03 concentrations reported at several midwestern
sites are higher than those at Los Angeles area sites. These maximum
concentrations also are unusually high in comparison with the NOX,
ozone and peroxyacetyl nitrate concentrations measured concurrently.
Therefore, these values are suspect.
The averages of 24-hr HN03 concentrations are small compared with
the corresponding NOX concentrations. The NOX concentrations
averaged over the study period were: St. Louis, MO, 111 yg m~3;
West Covina, CA, 343 yg m~3 and Dayton, OH, 134 yg m~3 (Spicer
et al. 1976a, Spicer 1977).
The diurnal patterns at the Los Angeles area sites for HN03
concentration are similar to that of the ozone with peaking in the
afternoon hours (Spicer 1977; Tuazon et al. 1981a,b; Hanst et al. 1982).
Nitric acid decreases appreciably in concentration during the night. In
Dayton, OH, and in St. Louis, MO, the diurnal profiles of nitric acid
showed both morning and afternoon peaks, unlike ozone and PAN, which
peaked only in the afternoon hours (Spicer et al. 1976b, Spicer 1977).
However, the nitric acid concentrations frequently were near the limits
of detectability.
5.3.3.2 Npnurban Concentration Measurements--Measurements of nitric
acid at suburban and rural sites are listed in Table 5-6. Some of the
earliest measurements of nitric acid in ambient air were made at two
sites outside of Dayton, OH--Huber Heights, a surburban location, and
New Carlisle, OH, a small town (Spicer et al. 1976a). Analyses were
made by continuous coulometry. The average concentrations of nitric
acid were in the 2.6 to 5.2 yg m~3 range. The maximum concentration
of 116.1 yg nr3 reported at New Carlisle appears to be too high.
5-38
-------
TABLE 5-5. CONCENTRATIONS OF NITRIC ACID, PEROXYACETYL NITRATE
NITRATE AND AMMONIA AT URBAN SITES IN THE UNITED SJATES
Concentrations, ug
Site
West Los Angeles, CA
(Cal. State Univ.)
West Covina, CA
Claremont, CA
en (Harvey Mudd College)
GO
<£> Claremont, CA
(Harvey Mudd College)
Riverside, CA
(UC Riverside)
Riverside, CA
(UC Riverside)
St. Louis, MO
Dayton, OH
Period of
year
June 1980
Aug-Sept. 1973
Oct. 1978
Aug-Sept. 1979
Oct. 1976
July-Oct.
July-Aug 1973
July-Aug 1974
HN03
Avg
18.1
7.7
41.3
20.6
5.2-12.93
12.9-18. la
7.7
15.5
Max
30.0
103.2
126.4
56.8
20.6
51.6
206. 4b
139. 3b
Avg
35
10
25
20
45
30
10
ND
PAN
Max
80
95
185
55
90
90
95
ND
m-3
NH3
Avg
2.1
2.1
5.6
0.7-2.83
14.0
14.7
2.8
ND
Max
5.6
9.1
21.0
8.4
42.0
92.4
11.2
ND
References
Hanst et al. 1982
Spicer 1977
Tuazon et al .
1981b
Tuazon et al .
1981a
Tuazon et al .
1978
Tuazon et al.
1980, 1981a
Spicer 1977
Spicer et al.
1976a
ND = Not determined.
aMany individual values were below detectability limits (OL); lower concentrations listed based on
assuming values below DL equaled zero; upper concentration values listed based on assuming values below
DL equaled following concentrations: HN03, 12.9 g nr3; PAN, 10 g nr3; NH3, 2.1 g nr3.
bThese values appear unusally high when compared with NOx. PAN and 03 concentrations reported as
present during same time periods.
-------
TABLE 5-6. MEASUREMENTS OF CONCENTRATIONS OF NITRIC ACID, PEROXYACETYL
NITRATE AND AMMONIA AT SURBURBAN AND RURAL LOCATIONS
Concentrations, yg m~3
Site
Beverly Airport,
MA (S)
Van HI Seville, NJ
(R)
en Luray, VA (R)
0 Research Triangle
Park, NC (S)
Huber Hts. , OH (S)
New Carlisle, OH (R)
Croton, OH (R)
Warren, MI (S)
Period
of
measurement
July-Aug.
July-Aug.
July-Aug.
June-July
July-Aug.
July-Aug.
1978
1979
1979
1980
1974
1974
August, 1980
Sept.-Oct
Jan. -Feb.
May- June
. 1979
1980
1980
HNOa
Avg
2.6
< 2.1
1.0
2.1
2.1
5.2
1.8
0.8
1.3
2.4
Max
1 5
11
2
2
38
116
9
< 2
~ 5.2
~15.5
.2
.6
.1
.4
.7
.1 .
.8
.6
PAN
Avg
9.0
2.5
ND
ND
< 5
ND
ND
ND
ND
ND
Max
110
32.5
ND
ND
50
ND
ND
ND
ND
ND
Avg
ND
ND
1.3
0.4
< 0.7
ND
0.4
0.8
0.6
0.9
NH3
Max
ND
ND
2.9
0.6
11.9
ND
0.6
-2.8
< 1.4
-5.6
References
Spicer et al
1982c
•
Spicer and
Sverdrup 1981
Cadle et al .
McClenny et
1982
Spicer et al
1976b
Spicer et al
1976b
McClenny et
1982
Cadle et al .
1982
al.
•
•
al.
1982
-------
TABLE 5-6. CONTINUED
en
i
Site
Abbeville, LA (R)
Commerce City, CO
(S)
Thurber Ranch, AZ
(35 mi. SE Tucson)
Pittsburg, CA (S)
Concentrations, ng -3
Period of HN03 PAN NHa
measurement Avg Max Avg Max Avg Max References
June-Aug. 1979 1.8 NA ND ND 2.1 NA Cadle et al
Nov. -Dec. 1978 2.1 NA ND ND 1.3 2.9 Cadle et al
July-Aug. 1981 1.6 5.2 ND ND 0.8 1.5 Farmer and
1982
February 1979 2.1 4.1 ND ND 0.4 0.8 Appel et al
. 1982
. 1982
Dawson
. 1980
ND = Not determined.
NA = Not available.
-------
Nitric acid measurements were obtained at Pittsburg, a small town
in northern California (Appel et al. 1980). Tandem filter technique was
used with a Teflon prefilter for collection of particulate nitrate and
use of either a nylon or Nad-impregnated filter to collect HMOs-
Positive interference problems are known to occur because of loss of the
nitrate from the particulate collected on the prefilter owing to
volatilization onto the filter used to collect HN03. The range of
nitric acid concentrations was from 0.7 to 3.9 yg m~3 (Table 5-6).
Nitric acid was measured by Spicer et al. (1982c) at Beverly
Airport, MA (Table 5-6). The nitric acid concentrations usually were
below the limit of detection of 2 ppb (5.2 yg m-3) of the
chemiluminescent technique used. An integrated filter technique also
was used for nitric acid involving the use of a Teflon prefilter and a
nylon backup filter.
In this same study (Spicer et al. 1982c), aircraft flights were
made following the urban plume of Boston, MA, over the Atlantic Ocean.
On one flight it was possible to measure the nitric acid formed not only
in the urban plume, 10.3 yg nr3, but also in the Salem power plant
plume, 15.5 yg m-3. The plumes were over the Atlantic Ocean north
of Cape Cod.
Measurements of nitric acid concentrations were made during July
and August 1979 at Van Hi Seville, NJ, in the New Jersey pine barrens
(Spicer and Sverdrup 1981). Nitric acid was measured by the
chemiluminescence technique, and inorganic nitrate (HN03 and
N03~) was determined by use of the Teflon filter prefilter and
nylon backup filter collection method. These authors suggested that the
potential for loss of nitrate off the Teflon filter onto the nylon
filter, resulting in a positive interference problem, made it desirable
to consider the filter method as acceptable only for measuring the
concentrations of total inorganic nitrate. On the average, the total
inorganic nitrate during the study was 5 yg m-3 and the estimate of
nitric acid concentration was less than 0.8 ppb or 2 yg m~3 (Table
5-6). The average diurnal profile for nitric acid peaked at 1500 hours.
The ozone and PAN concentrations peaked at about the same time in the
afternoon.
McClenny et al. (1982) reported measurements of nitric acid in the
Research Triangle Park, NC, and a rural area near Croton, OH (Table
5-6). Analyses were made by the tungstic acid integrative sampling
method, which has a sensitivity of 0.07 ppb (0.2 yg m-3). Nitric
acid is effectively adsorbed on a tungstic acid surface, subsequently
desorbed into carrier gas, and passed on to a NOX chemiluminescent
analyzer. Maximum concentrations of nitric acid and of ozone occurred
near midday at both sites, with lower nighttime concentrations for both
but not as large a decrease for nitric acid.
Measurements of nitric acid by filter techniques at several
suburban and rural sites (Table 5-6) were reported by Cadle et al.
(1982). At the Abbeville, LA, and the Commerce City, CO, sites, nitric
5-42
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acid concentrations were obtained by difference between the inorganic
nitrate collected on a microquartz filter and particulate nitrate
collected on a Teflon filter. However, subsequent tests indicate that
the nitric acid may have been overestimated. The second method involved
removal of nitrate on a Teflon filter followed by removal of nitric acid
on a nylon filter. The positive interference problem possible with this
second technique has already been discussed.
The average diurnal profile for nitric acid from measurements at
Abbeville, LA, show a single late morning peak for nitric acid and an
afternoon peak for ozone. Nitric acid concentrations were found to
increase from fall to winter to spring in 1979-80 at the Warren, MI,
site (Cadle et al. 1982).
Both Appel et al. (1980) and Cadle et al. (1982) concluded that the
concentrations of nitric acid and ammonia at their measuring sites were
too low to result in the formation of ammonium nitrate in particulate
matter.
Kelly and Stedman (1979b) measured nitric acid by a
chemiluminescent technique at a rural site about 15 miles east of
Boulder, CO. The nitric acid concentrations during February 1978
usually were in the 1.3 to 12.9 yg nr3 range with many of the
concentrations of nitric acid in the 2.6 to 5.2 pg nr^ range.
A collection method involving condensation of water vapor onto a
cooled surface was used by Farmer and Dawson (1982) to collect nitric
acid (Table 5-6). During part of the sampling period in early August
1981, sulfur dioxide and nitric acid concentrations were well
correlated. The authors associated this behavior with transport and
chemical transformations occurring within smelter plumes fumigating the
site.
The average nitric acid concentrations at most of the suburban and
rural sites were at or below 2.6 yg m~3 with the concentrations
frequently occurring in the 0.7 to 2.1 yg nr3 range (Table 5-6).
These concentrations of nitric acid are about a factor of 10 lower than
the nitric acid concentrations measured at urban sites (Table 5-5). The
nitric acid concentrations at suburban and rural sites also are about a
factor of 5 to 10 lower than the nitrogen dioxide concentrations at
surburban and rural sites (Table 5-2).
5.3.3.3 Concentration Measurements at Remote Locations—Measurements of
nitric acid also are available at a number of remote or relatively
remote locations (Huebert and Lazrus 1978, 1980a,b; Huebert 1980; Kelly
et al. 1980). Kelly and coworkers measured nitric acid concentrations
at a relatively remote site, Niwot Ridge, in the Rocky Mountains 20
miles west of Boulder, CO, between December 1978 and August 1979. A
high sensitivity chemiluminescent instrument was used with nitric acid
measured by thermal decomposition to nitrogen dioxide followed by
FeS04 reduction of the nitrogen dioxide. Some interference by PAN was
observed in tests with this technique for measuring nitric acid. In
5-43
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clear air masses the nitric acid concentrations often were below the
detection limit but, when measurable, were in the 0.13 to 0.26 yg
m-3 range. When polluted air reached the site, the nitric acid
concentrations frequently were 0.5 yg m-3 or more and values over
2.6 were measured occasionally.
Huebert (1980) and Huebert and Lazrus (1978, 1980a,b) measured
nitric acid on samples collected from aircraft or shipboard over remote
areas of the Pacific Ocean and western North America. Samples were
collected using the same sort of tandem filter technique discussed
earlier. Samples were collected from aircraft as part of project
GAMETAG. Surface concentrations of nitric acid in the equatorial
Pacific region averaged 0.1 yg m-3 (Huebert 1980). The
concentrations of nitric acid measured in the boundary layer ranged from
less than 0.03 to 2.22 yg m-3, with a median range of 0.15 to 0.21
yg m-3 (Huebert and Lazrus 1980a). The free troposphere nitric acid
concentrations ranged from less than 0.08 to 1.39 yg m-3 with a
median of 0.31 yg m-3. The nitric acid concentrations in the
boundary layer in remote areas are a factor of 5 to 10 lower than at
rural locations in eastern North America.
5.3.4 Peroxyacetyl Nitrates
Peroxyacetyl nitrates can be determined by electron capture gas
chromatography down to the 0.1 ppb concentration level and below. This
method can be used in urban, rural, or remote locations. Long path FTIR
spectroscopy has been used to measure peroxyacetyl nitrate at locations
within the Los Angeles Basin area.
5.3.4.1 Urban Concentration Measurements--Peroxyacetyl nitrate
concentrations have been tabulated when obtained concurrently with
nitric acid and ammonia concentrations in Table 5-5. Many other
measurements of peroxyacetyl nitrate have been made in urban areas.
Additional average peroxyacetyl nitrate measurements made in the
Los Angeles Basin area are shown in Table 5-7. The highest peroxyacetyl
nitrate concentrations have been reported from the sites in the western
part of the Los Angeles Basin area. In the eastern part of the Los
Angeles Basin area, average peroxyacetyl nitrate concentrations usually
have been measured in the 5 to 25 yg m-3 range.
Maximum peroxyacetyl nitrate concentrations occur late in the
morning or early afternoon in downtown Los Angeles (Mayrsohn and Brooks
1965) and progressively later in the afternoon passing from west to east
across the Los Angeles Basin area from downtown Los Angeles to Pasadena
(Hanst et al. 1975) to West Covina (Spicer 1977) to Claremont (Tuazon et
al. 1981a,b) to Riverside (Pitts and Grosjeans 1979). Pitts and
Grosjeans (1979) also reported seasonal variations in peroxyacetyl
nitrate diurnal peak concentrations. Two peaks were observed at the
site in Riverside, CA. The earlier peak was associated with formation
of peroxyacetyl nitrate from local emissions while the later peak was
associated with formation of peroxyacetyl nitrate from emissions in air
5-44
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TABLE 5-7. AVERAGE PEROXYACETYL NITRATE MEASUREMENTS
FROM THE LOS ANGELES BASIN AREA
Site
Los Angeles
Pasadena
Claremont
Riverside
Year
1961
1965
1976
1979
1973
1980
1967-68
1975-76
1977
1980
1980
Concentration
yg m~3
100
155
40
25
150
65
19
18
8
6
24.5
Reference
Renzetti and Bryan 1961
Mayrsohn and Brooks 1965
Lonneman et al . 1976
Singh et al. 1981
Hanst et al . 1975
Grosjean 1981
Taylor 1969
Pitts and Grosjean 1979
Singh et al . 1979
Singh et al. 1982
Temple and Taylor 1983
5-45
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TABLE 5-8. PEROXYACETYL NITRATE MEASUREMENTS FROM SEVERAL URBAN
AND SUBURBAN AREAS IN THE UNITED STATES
Site
Hoboken, NJ
St. Louis, MO
Houston, TX
(Lange)
Houston, TX
(West Hollow)
(Aldine)
(Crawford)
(Fuqua)
(Jack Rabbit)
New Brunswick, NJ
San Jose, CA
Oakland, CA
Phoenix, AZ
Denver, CO
Houston, TX
Chicago, IL
Pittsburgh, PA
Staten Island, NY
Year
1970
1973
1976
1977
1978
1978-80
1978
1979
1979
1980
1980
1981
1981
1981
Concentration
yg nr3 Reference
18.5
31.5
2.0
3.0
4.5
3.0
3.0
4.0
2.5
4.5
2.0
4.0
2.0
2.0
2.0
1.5
3.5
Lonneman et al. 1976
Lonneman et al. 1976
Westberg et al. 1978a
HAOS 1979
Martinez et al. 1982
Brennen 1980
Singh et al. 1979
Singh et al. 1981
Singh et al . 1981
Singh et al. 1982
Singh et al. 1982
Singh et al . 1982
Singh et al . 1982
Singh et al. 1982
5-47
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rural and remote locations are given in Table 5-9. Additional
measurements of peroxyacetyl nitrate concentrations are listed in Table
5-6. The average concentrations of peroxyacetyl nitrate are in the
range of 0.5 to 5 yg m~3 overlapping the range of average PAN
concentrations at urban and suburban sites. The concentrations of PAN
at the remote sites, Reese River, NY, Badger Pass, CA, and Point Arena,
CA, are about 0.5 yg m~3.
Lonneman et al. (1976) observed two diurnal patterns of PAN
concentrations at the site near Wilmington, OH. One pattern involved
afternoon and evening elevation in PAN and in ozone concentrations. The
other pattern involved a flat diurnal profile for the PAN
concentrations, but an elevation in ozone concentrations. An afternoon
peaking of the PAN concentrations also was observed at the Sheldon
Wildlife Preserve, TX (Westberg et al. 1978b). At night, measureable
concentrations of PAN were obtained at both of these rural sites.
The concentrations of peroxyacetyl nitrate at rural sites were in
about the same concentration range as measured for nitric acid at rural
sites (Tables 5-6 and 5-9). The concentrations of PAN at remote
locations of about 0.5 yg m~3 were about the same as those reported
for nitric acid by Huebert and Lazrus (1980a) at remote locations.
5.3.5 Ammonia
Unlike nitric acid and peroxyacetyl nitrate, which are formed
through atmospheric reactions involving precursor hydrocarbons and
nitrogen oxides, ammonia is emitted directly into the atmosphere from
near-surface sources (Chapter A-2, Sections 2.2.2.7 to 2.2.2.10).
Consistent with ammonia being emitted from ground-level sources, ammonia
concentrations have been found to decrease with altitude (Georgii and
Muller 1974, Hoell et al. 1983). Ammonia has a significant role in
neutralization of acid sulfate and nitric acid in the atmosphere
(Brosset 1978). In addition ammonia, when it undergoes deposition, can
participate significantly in chemical reactions in soil.
Various techniques have been used to sample and analyze ammonia.
Long path FTIR spectroscopy was used at several sites in the Los Angeles
Basin area (Tuazon et al. 1978, 1980, 1981a,b; Hanst et al. 1982). Dual
catalyst chemiluminescent instrumentation was used in Los Angeles, St.
Louis, and the Dayton area (Spicer et al. 1976a, Spicer 1977). This
procedure depended on the fact that ammonia is oxidized to nitric oxide
by high temperature but not low temperature catalysts while nitrogen
dioxide is reduced by both high and low temperature converters. A
tandem filter technique involving a Teflon prefilter and two
oxalic-acid-impregnated fiberglass filters has been used at several
locations (Cadle et al. 1982). Both positive and negative interferences
can occur. A similar tandem filter technique with a glass fiber
prefilter was employed by Appel et al. (1980). Another method involved
use of oxalic-acid-coated glass tube diffusion denuders. Another
technique involved collection on Chromosorb T beads and desorption
either into an opto-acoustic detector or a chemiluminescent analyzer
5-48
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TABLE 5-9. PEROXYACETYL NITRATE MEASUREMENTS AT RURAL AND REMOTE SITES IN THE UNITED STATES
tn
Site
Wilmington, OH
H'jntington Lake,
IN
East Central
Missouri
Sheldon Wildlife
Preserve, TX
Jetmore, KA
Reese River, NV
Rodger Pass, CA
Mill Valley, CA
Point Arena, CA
Nature of
site
Rural-continental
Rural -continental
Rural-continental
Rural -continental
Rural-continental
Remote-high
altitude
Remote-high
altitude
Rural -marl time
Remote-maritime
Period of
measurement
August 1974
April 1981
February 1981
October 1978
June 1978
May 1977
May 1977
January 1977
Aug. - Sept. 1973
Concentration, vg n~3
PAN PPN
Avg Max Avg Max
NA
2.5
3.5
4.0
1.25
0.55
0.65
1.50
0.40
20.5
NA
NA
15.0
2.5
1.3
1.10
4.15
1.40
ND
ND
ND
ND
ND
0.22
0.28
0.22
ND
ND
ND
ND
ND
ND
0.50
0.50
0.60
ND
Reference
Lonneman et
1976
Splcer et al
Splcer et al
Westberg et
1978a
Singh et al.
Singh et al.
Singh et al.
Singh et al.
Singh et al .
al.
. 1983
. 1983
al.
1979
1979
1979
1979
1979
ND = Not determined.
NA = Not available.
-------
(McClenny and Bennett 1980). Harvard et al. (1982) also used the
acoustic detector. The tungstic acid technique was used by McClenny et
al. (1982) to measure ammonia. Gaseous ammonia and nitric acid are
separated from particulate species as a result of their more rapid
diffusion to the walls of a tungstic-acid-coated Vycor tube. The
ammonia is desorbed into a carrier gas and readsorbed on a second
tungsten-oxide-coated tube which passes nitric acid now in the form of
nitrogen dioxide. The ammonia is desorbed into a chemiluminescent
analyzer as nitrogen dioxide.
5.3.5.1 Urban Concentration Measurements—The concentrations of ammonia
measured at a number of urban locations are given in Table 5-5. The
highest concentrations of ammonia in ambient air have been measured at
Riverside, CA (Tuazon et al. 1978, 1980, 1981a). These high
concentrations were attributed to ammonia emissions from feed lots
upwind of the site in Riverside. Nitric acid was observed to decrease
in concentration with increases in ammonia concentration at Riverside
(Tuazon et al. 1978, 1980) owing to the ammonium nitrate equilibrium
relationship. The ammonia concentrations at sites in Claremont, West
Covina, and Los Angeles were substantially lower than in the Riverside
area (Spicer 1977, Tuazon et al. 1981a,b). Such a gradient in
concentrations of ammonia is consistent with strong localized sources of
ammonia rather than more uniform basin-wide emissions of ammonia. The
ammonia concentrations measured in St. Louis (Spicer 1977) were not
substantially different from those measured at locations in the Los
Angeles Basin area other than the Riverside area. Concentrations of
ammonia remain high at night in Los Angeles and St. Louis (Spicer 1977)
consistent with surface emissions of ammonia into the shallower mixing
layers occurring during the nighttime hours.
5.3.5.2 Nonurban Concentration Measurements—Earlier measurements of
ammonia concentrations at nonurban locations were in the range from
less than 0.07 yg m-3 to several factors of ten times greater
(Breeding et al. 1973, 1976; Lodge et al. 1974). Other measurements of
ammonia that were obtained concurrently with nitric acid concentration
measurements are given in Table 5-6. Average concentrations range from
0.35 to 2.1 yg m-3 and maximum concentrations reported ranged up to
11.9 yg m-3. However, this latter concentration value observed at
Huber Heights, OH, is unusually high compared to the maximum
concentration values at other suburban and rural locations.
Several additional studies have been reported at nonurban sites.
Ammonia was measured at several sites on Cedar Island off the coast of
North Carolina in August 1978 (McClenny and Bennett 1980). The ammonia
concentrations ranged from 2.1 to 2.4 yg m-3. The highest
concentrations were measured immediately above marsh grass. A few
measurements also were made at Research Triangle Park, NC, and these
ammonia concentrations were in the 2.8 to 4.2 yg m-3 range.
Measurements of ammonia also were made nearby in southeastern Virginia
at a site bordering the Great Dismal Swamp (Harward et al. 1982). The
ammonia concentrations obtained in August and September 1979 ranged from
5-50
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1.0 to 2.8 yg m-3 and averaged 1.9 yg m-3. Measurements were
made for comparison at Hampton, VA. The average ammonia concentration
was lower in air masses arriving over water than over land. The ammonia
concentration also was lower during periods of rain.
At Hampton, VA, the ammonia concentrations decreased from the 1.4
to 2.1 yg m-3 range in late summer to less than 0.14 yg m-3 in
the early winter (Harward et al. 1982). A decrease in ammonia
concentrations also was observed at Warren, MI, from 0.9 yg m-3 in
the spring to 0.6 yg nr3 in the winter (Cadle et al. 1982).
Although such seasonal changes have been associated with changes in soil
emissions and fertilizer volatilization, higher temperatures also could
be explained by a shift in the ammonium nitrate equilibrium resulting in
higher ambient air ammonia concentrations (Cadle et al. 1982).
5.3.6 Particulate Nitrate
Serious difficulties have been experienced in obtaining accurate
ambient air measurements of particulate nitrates. During recent years
substantial positive and negative artifacts have been identified as
occurring during the sampling of nitrates from air. The artifacts arise
as follows:
(1) Positive artifacts derived from
(a) adsorption of nitric acid by filter medium,
(b) adsorption of nitrogen dioxide by filter medium,
(c) loss of nitric acid onto the collected particulate
matter on a filter as a result of chemical reactions
with, or adsorption by, the particulate matter.
(2) Negative artifacts derived from
(a) reactions of particulate nitrate in the collected matter
with strong acids in the particulate matter, resulting
in release of nitric acid;
(b) volatization of ammonium nitrate from the filter to form
gaseous nitric acid and ammonia.
As a result of the artifact problems given above the earlier
nitrate measurements reported in the literature are likely to be
questionable, if not erroneous.
Most of the early measurements of particulate nitrate involved
analysis for nitrates on samples collected on glass fiber filters in
high volume (HIVOL) samplers (National Academy of Sciences 1977, U.S.
EPA 1982).
A number of investigators have observed in measuring particulate
nitrate in source emissions (Pierson et al. 1974) and in ambient air
studies (Witz and MacPhee 1977; Stevens et al. 1978; Spicer and
Schumacher 1977, 1979; Appel et al. 1979, 1981a; Witz and Wendt 1981;
Shaw et al. 1982; Witz et al. 1982) that much higher particulate nitrate
5-51
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concentrations were measured on glass fiber filters than on Teflon,
quartz, and some other filter types. Nitric acid was demonstrated to be
adsorbed on glass fiber filters in laboratory studies (Okita et al.
1976, Spicer and Schumacher 1977, 1978, 1979, Appel et al. 1979).
Nitrogen dioxide also has been shown in laboratory studies to be
adsorbed on glass fiber filters (Spicer and Schumacher 1977, 1978, 1979;
Rohlach et al. 1979). Appel et al. (1979) reported a positive artifact
from nitrogen dioxide at high ozone concentrations. However, adsorption
of nitric acid rather than nitrogen dioxide appears to be the dominant
source of the positive interference (Appel et al. 1979, 1981a).
Substantial positive nitrate artifacts have been measured on a
number of other filter types including Teflon-impregnated fiber filters
(Pierson et al. 1980b), silicone resin coated glass fiber filters (Appel
et al. 1979), cellulose filters (Appel et al. 1979), cellulose acetate
filters (Spicer and Schumacher 1978, 1979, Appel et al. 1979), and nylon
filters (Okita et al. 1976, Spicer 1977, Spicer and Schumacher 1978,
1979). Smaller but measurable positive artifacts have been reported on
some types of quartz filters including Gelman microquartz (Appel et al.
1978, Spicer and Schumacher 1977, 1979) and Pall flex Tissuquartz (Spicer
and Schumacher 1977, Forest et al. 1980).
Negligible positive artifacts have been obtained on Fluoropore
(Teflon) filters (Stevens et al. 1978, Appel et al. 1979, 1980, 1981a,b;
Pierson et al. 1980b) on polycarbonate filters (Spicer and Schumacher
1977), and on ADL quartz filters (Spicer and Schumacher 1978, 1979).
However, atmospheric particulate matter on Teflon filters can retain
nitric acid (Appel et al. 1980).
Harker et al. (1977) observed that an inverse relationship occurred
between ambient air sulfate and nitrate concentrations in samples
collected at West Covina, CA. A group of controlled photochemical
experiments were designed to investigate this behavior. When sulfuric
acid was generated and collected concurrently with nitrates on Gelman
Spectro Grade A glass fiber filters, the nitrate concentration was lower
than in the absence of sulfuric acid. The researchers concluded that
the sulfuric acid reacted with and caused the release of nitrate
probably as nitric acid from the surface of the aerosol particles
(Harker et al. 1977). The possibility of a negative artifact effect on
Fluoropore filters as a result of reaction with sulfuric acid and as a
result of volatization of ammonium nitrate was discussed by Appel et al.
(1979).
Pierson et al. (1980a,b) observed losses of nitrate off of
Fluoropore filters, an effect associated with the high sulfuric acid
concentrations measured at the Allegheny Mountain site. Appel et al.
(1981b) also found that particulate nitrate collected on Teflon filters
at Lennox, CA decreased with increasing amounts of ambient air sulfuric
acid. About half the nitrate was lost at ambient air sulfuric acid
concentrations of 10 vg m"3. About 50 percent of the nitrate
collected could be lost from Teflon filters at higher ambient
temperatures, 29 to 35 C, and about 30 percent RH (Appel et al. 1981a).
5-52
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No losses of nitrate appeared to occur from samples collected during the
night and morning hours. In samples collected at Research Triangle
Park, NC, large losses of particulate nitrate, up to 90 percent off
Teflon filters, occurred particularly during the day (Shaw et al. 1982).
Laboratory experiments were carried out by Appel et al. (1981b) to
investigate the losses of nitrate off Teflon filters loaded with
submicron (<_ 0.2 ym) ammonium nitrate particles. With equal loadings
of ammonium nitrate and sulfuric acid on the Teflon filters, over 90
percent of the nitrate was lost off the filters after exposure to a
clean air stream at 90 percent RH for six hours. Volatization of
nitrate under the same conditions in the absence of sulfuric acid
resulted in 30 to 50 percent losses of ammonium nitrate. Losses of
about 90 percent of the nitrate occurred when the filters were exposed
to 17 to 23 ppb of hydrochloric acid. Forest et al. (1980) observed
losses of preloaded nitrate from Pall flex Tissuquartz exposed sulfuric
acid. Particulate nitrates other than ammonium nitrate can be present
in the atmosphere but they, unlike ammonium nitrate, do not volatize
readily.
The artifact problems discussed above appear to have been dealt
with satisfactorily by use of diffusion-denuder tubes. These tubes are
used to remove gaseous species and to pass aerosols (Stevens et al.
1978). This technique was proposed for use with nitrate species by Shaw
et al. (1979) and demonstrated by Appel et al. (1981a) and by Shaw et
al. (1982). Ambient air measurements using this approach are of
particular importance (Appel et al. 1981a, Forest et al. 1982, Shaw et
al. 1982, Spicer et al. 1982a, Tanner 1982).
5.3.6.1 Urban Concentration Measurements—As discussed above, much
higher ambient air nitrate concentrations have been measured on glass
fiber filters than on Teflon and other inert filters. The magnitude of
the actual net positive artifact on ambient air samples cannot be
estimated. Therefore, the substantial body of ambient air nitrate
concentrations obtained on glass fiber filters will not be considered
(National Academy of Sciences 1977, U.S. EPA 1982). The same problem
probably applies to the measurements on cellulose filters used to
collect samples in the Los Angeles Basin during 1972 and 1973 (Appel et
al. 1978). Appel et al. (1981a), using Gelman A glass fiber filters in
low volume sampling over 2 to 8 hour periods, obtained reasonable
agreement for many of the samples between the nitrate values on glass
fiber filters and a total inorganic nitrate (nitrate particulate plus
nitric acid) sampling system. However, Shaw et al. (1982) did not
observe glass fiber filters to collect nitric acid with reproducible
efficiency at the subambient pressure in their sampling assembly. While
Appel et al. (1981a) concluded that glass fiber filters give an
approximation of total inorganic nitrate, Shaw et al. (1982) did not
consider glass fiber filters to be satisfactory collectors of total
inorganic nitrate. Neither group used the 24-hr high volume sampling
procedure. While it is clear that 24-hr average HIVOL samples are
totally inadequate for measurement of particulate nitrate, it is not
5-53
409-261 0-83-14
-------
clear to what extent such sampling might have provided an adequate
measurement of total inorganic nitrate.
Because of the large losses of nitrate off Teflon and quartz
filters, the ambient air measurements made with these filters are also
in question (Spicer 1977, Spicer and Schumacher 1977, Appel et al. 1979,
Spicer et al. 1979). Although the measurements can be considered lower
limit estimates, the losses of nitrate are so large as to make such
estimates of little value.
Nitrate measurements also are available from particle-size
distribution studies made using cascade impactors (Lee and Patterson
1969, Lundren 1970, Moskowitz 1977, Patterson and Wagman 1977, Appel et
al. 1978). However, these cascade impactors and the backup filters used
with them have the potential for similar types of artifact problems
discussed above. Therefore, it is not possible to know whether such
nitrate measurements are of value either.
The remaining nitrate measurements are those made recently using
gas diffusion denuders to remove nitric acid. Appel et al. (1981a)
collected inorganic nitrate on a Teflon prefilter followed by a nylon or
NaCl/W41 backup filter. Particulate nitrate was collected with the same
tandem filter system after removing the nitric acid with the diffusion
denuder. This arrangement allows nitric acid to be determined by
difference. Diurnal nitrate concentration profiles obtained with this
system were plotted for the period between July 23 and July 27, 1979 at
Claremont, CA (Harvey Mudd College). The particulate nitrate peaked in
concentration during the late morning hours. Particle nitrate
concentrations exceeded nitric acid concentrations between 2200 and 1200
hours. The average particle nitrate concentration during this period
was 25 yg m~3. The average particle nitrate concentration
moderately exceeded the average nitric acid concentration.
Forest et al. (1982), as part of an intercomparison study (Spicer
et al. 1982a) at Harvey Mudd College in Claremont, CA, measured nitrates
by using the gas diffusion denuder technique. Two assemblies, each with
a Fluoropore prefilter followed by two pairs of NaCl impregnated
filters, were used, with one assembly at the exit of a diffusion
denuder. Measurements of nitrates were made with this system between
August 27 and September 3, 1979. The particulate nitrate concentrations
tended to peak in the morning hours. The particulate nitrate
concentrations exceeded the nitric acid concentrations in the evening
and morning hours. This diurnal pattern was the same as observed at
this site earlier in the summer by Appel et al. (1981a). The average
particulate nitrate concentration was 13.4 yg m-3. This
concentration moderately exceeded the average nitric acid concentration.
Lower nitrate concentrations were obtained in August and September than
were measured in July (Appel et al. 1981a). The peak ozone
concentrations also were somewhat lower during this period (Spicer et
al. 1982b) than in the period in July (Appel et al. 1981a). The results
indicate that the later period was one of lesser photochemical activity.
5-54
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5.3.6.2 Nonurban Concentration Measurements—Discussion earlier in this
section notes that the nitrate cocentrations obtained at nonurban sites
using glass fiber filters HIVOL sampling are considered too unreliable
to use. The Teflon impregnated HIVOL filters employed by Mueller et al.
(1980) have similar problems associated with them (Pierson et al.
1980b). Even with a positive artifact associated with their nitrate
measurements, Mueller et al. (1980) usually measured less than 1 yg
m~3 of nitrate at rural sites, and during the spring and summer months
the nitrate concentration reported were at or below 0.5 yg m~3.
Pierson et al. (1980b) sampled with Fluoropore Teflon and quartz filters
at Allegheny Mountain; on Fluoropore filters an average nitrate
concentration obtained was 0.5 yg m~3, but the negative artifacts
likely to occur with these filters also may make these measurements
unreliable.
Shaw et al. (1982) made measurements of nitrates, using a diffusion
denuder at a site within the Research Triangle Park, NC during 16 days
in June, July, and August 1980. The assembly used contained a cyclone
to remove coarse particles. The cyclones were shown to pass nitric acid
efficiently. The cyclone was followed by a manifold to which were
connected tandem Teflon and Nylon filter holders, one of which had a
diffusion denuder between it and the manifold. The particulate nitrate
concentrations measured exceeded the nitric acid concentrations in the
late evening and early morning hours, as was observed at Claremont, CA
(Appel et al. 1981a, Forest et al. 1982). During the late morning,
afternoon, and early evening hours, the particulate nitrate
concentrations were substantially lower than the nitric acid
concentrations. Averaging the entire study period, the particulate
nitrate concentration was 1.0 yg m~3 and the particulate nitrate was
37 percent of the total inorganic nitrate. The average particulate
nitrate concentration at this nonurban site was 4 percent (Appel et al.
1981a) and 7 percent (Forest et al. 1982) of the average particulate
nitrate concentrations measured in Claremont, CA.
Tanner (1982) used the same diffusion denuder assembly arrangement
as Forest et al. (1982) at a site within Brookhaven National Laboratory
on Long Island, NY. Measurements of nitrates were made several hours
each day on November 7,8, and 9, 1979. The average particulate nitrate
concentration was 1.7 yg nr3 and constituted about one-third of the
total inorganic nitrate measured. As at the Research Triangle Park, NC
site, the particulate nitrate concentration at this site was only a
small fraction of the particulate nitrate concentrations measured at
Claremont, CA (Appel et al. 1981a, Forest et al. 1982).
5.3.6.3 Concentration Measurements at Remote Locations—Huebert (1980)
and Huebert and Lazrus (1978, 198UD) used a tamden niter assembly
consisting of a Teflon prefilter followed by a base-impregnated
cellulose filter to collect nitrates. As already discussed, these
filters have positive and negative artifacts. In combination such types
of filters are adequate for measuring total inorganic nitrate but are
questionable for the accurate measurement of particulate nitrate and
nitric acid individually (Appel et al. 1981a, Spricer and Sverdrup 1981,
Forest et al. 1982). Teflon filters alone were used to collect
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participate nitrate at remote locations (Huebert and Lazrus 1980a), but
these filters have the negative artifact problems already discussed.
Based on such measurements at remote locations, the authors concluded
that particulate nitrate concentrations exceed nitric acid
concentrations in the marine boundary layer (Huebert 1980), but
particulate nitrate concentrations are much lower than nitric acid
concentrations in the free troposhere (Huebert and Lazrus 1978, 1980b).
5.3.7 Particle Size Characteristics of Particulate Nitrogen Compounds
The available literature on measurement of particle size character-
istics of particulate nitrogen compounds is based on studies done
between 1966 and 1976. Therefore, the investigators could not have been
aware of the positive and particularly the negative artifact problems
with particulate nitrate sampling discussed earlier in this section.
The last stage of the cascade impactors used consists of cellulose
acetate or glass fiber filters. Because of losses of nitric acid on
such filters substantial overestimates of the amount of nitrate on the
last stage are likely. This would result in the mass median diameters
computed being too small. However, losses of nitric acid and
particulate may occur on the upper stages of the impactors. The
Lundgren impactor has substantial wall losses (Lundgren 1967, 1970).
The impactor stages usually were constructed of stainless steel. Shaw
et al. (1982) found at least 88 percent of nitric acid in air passed
through a stainless steel cyclone. This may be an indication that
nitric acid is unlikely to be lost to other stainless steel surfaces,
but no studies have been made.
The situation is complicated by the use of films and coatings over
the original stainless steel surfaces. Appel et al. (1978) used
polyethylene strips coated with a sticky hydrocarbon resin, while
Moskowitz (1977) used a thin film of vaseline on stainless steel strips.
No measurements have been made on losses of nitric acid or of nitrogen
dioxide to such surfaces. If losses did occur on the upper stages of
the impactors only, the mass median diameters computed would be too
large. It is impossible to estimate the extent to which artifact
problems may shift the apparent size distributions in these impactors.
Nevertheless, some qualitative results of these impactor studies appear
reasonable, and these will be discussed.
The larger mass median diameters given in Table 5-10 were computed
from measurements at locations near the ocean likely to be influenced by
air masses moving off the ocean. As can be seen from the mass median
diameters of particulate nitrate from the work of Appel et al. (1978),
the diameters tended to decrease from sites near the ocean, Dominguez
Hills, CA to those well inland, Rubidoux, CA. At Dominguez, CA and to a
lesser extent at West Covina, CA farther inland a substantial coarse
mode fraction of particles greater than 2 ym were measured.
Moskowitz (1977) observed the same sort of pattern of particle size
distributions of particulate nitrate in the South Coast air basin. The
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TABLE 5-10. MASS MEDIAN DIAMETERS REPORTED FOR NITRATE FROM PARTICLE
SIZING WITH CASCADE IMPACTORS
Site
Measurement
period
Reference
Mass median
diameter in ym
for nitrate
Cincinnati, OH
(CAMP Site)
Fairfax, OH
Riverside, CA
U. Cal. Campus
Secaucus, NJ
3/14-23/66
Lee and Patterson (1969) 0.23 (est)
Dominquez Hills,
CA
West Covina, CA
Pomona, CA
Rubidoux, CA
3/25-4/21/66 Lee and Patterson (1969) 0.59
11/1-15/68 Lundgren (1970) 0.8
9/29-10/10/66
Background
Level A
Level B
Level C
10/4-5/73
10/10-11/73
7/23-24/73
7/26/73
8/16-17/73
9/5-6/73
9/18-19/73
Patterson and Wagman
(1977)
Appel et al. (1978)
Appel et al. (1978)
Appel et al. (1978)
Appel et al. (1978)
0.20
2.6
0.38
0.37
1.64
0.72
1.13
0.62
0.68
0.33
0.34
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particle size distribution of nitrate indicated two modes. One mode was
located between 0.05 and 1 ym, while the other mode was between 2 and
8 ym (8 ym was an arbitrary upper cutoff). At Hermosa Beach, CA at
the coast the concentration of submicron nitrate was small with most of
the nitrate in the 2 to 8 ym range. At Pasadena, CA the size
distribution of particulate nitrate was bimodal with significant amounts
of nitrate in both size ranges. At Chino, CA, well inland, a large part
of the particulate nitrate was in the submicron range. Coarse mode
nitrate was still present. Chino is a cattle-feeding area with high
ammonia concentrations available to react with nitric acid to form
submicron ammonium nitrate.
Several studies provide results bearing on the chemical composition
of the nitrates in the fine and coarse modes. Grosjean and Friedlander
(1975) claimed that ammonium nitrate accounted for 95 percent of the
measured nitrate, based on infrared spectra of extracts from samples
collected on water washed Gelman type A glass fiber filters in Pasadena,
CA during 1973. O'Brien et al. (1975) usually observed the presence of
ammonium nitrate based on infrared spectra and paper chromatograms of
samples collected on prewashed Gelman type A glass fiber filters at
several locations in California. At Santa Barbara, CA a sample
collected within a mile of the ocean contained 16 percent nitrate, but
no ammonium ion was detected. The authors suggested that the nitrate
was sodium nitrate formed from the reaction of nitrogen dioxide with
sodium chloride. Lundgren (1970) in the samples collected at Riverside,
CA identified by x-ray diffraction very hygroscopic, crystalline-like
particles making up a large part of the 0.5 to 1.5 ym size range as
ammonium nitrate.
High-resolution mass spectrometric measurements were applied to
samples collected during a smog episode at West Covina, CA (Cronn et al.
1977). Ammonium nitrate and sodium nitrate were identified as present
in the size range below 3.5 ym. The ammonium nitrate concentration
substantially exceeded the sodium nitrate concentrations measured.
Kadowaki (1977) size classified particle nitrate using an Andersen
sampler with a type A Gelman glass fiber backup filter in Nogoya, Japan.
The size distributions of nitrate was bimodal. The submicron nitrate
was shown to be ammonium nitrate and the coarse particles sodium nitrate
based on analysis by paper chromatography. Increases in coarse mode
nitrate were observed when sea salt aerosols were transported to the
sampling location.
5.4 OZONE
Ambient air concentrations of ozone are of interest with regard to
acidic deposition for several reasons. Ozone can contribute to adverse
effects to field crops, forest trees, and other forms of vegetation
(Chapter E-3, Section 3.3.1). Ozone in combination with sulfur dioxide
can cause damage to vegetation. Ozone also may interact with acidic
deposition to cause damage to vegetation. However, the results of the
several studies completed to date are preliminary and inconclusive.
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Transformations of sulfur dioxide to sulfate in aqueous droplets in
clouds, fogs, and acid mists may be contributed to significantly by
reactions with ozone. Therefore, ozone concentrations both at ground
level and aloft, cloud heights, are of interest.
This presentation will not include a discussion of ozone
concentration measurements within cities. The literature on ozone
measurements within cities is too extensive to consider in detail here.
A discussion of ambient air ozone concentration levels within cities can
be found in the Air Quality Criteria for Ozone (U.S. EPA 1978a).
Most of the ozone measurements made from the early 1970's to the
present at ground level and from aircraft have used chemiluminescent
ozone analyzers. Investigators using these instruments at rural sites
and in aircraft believe the method to be reliable, specific, and precise
(Research Triangle Institute 1975, Decker et al. 1976).
Ozone is formed in the atmosphere from the reaction of oxygen
molecules with atomic oxygen. The atomic oxygen is formed from the
photolysis of nitrogen dioxide. Ozone reacts very rapidly with nitric
oxide. Maintaining the production of ozone in the atmosphere requires
the presence of radical species produced from the reactions of nitrogen
oxides in sunlight with organic vapors (U.S. EPA 1978a). Peroxyacyl
nitrates and nitric acid also are formed in the atmosphere by the
reaction of radical species formed in these reactions with nitrogen
dioxide. Hydroxyl radicals, OH, are particularly important in their
reactions with organic vapors to form other radicals, with nitrogen
dioxide to form nitric acid, and with sulfur dioxide to form sulfates.
Therefore, homogeneous photochemical reactions are important to the
formation of a number of the chemical species discussed in this
document.
Ozone is formed in the stratosphere and can be transported into the
troposphere by tropospheric extrusion events. Aircraft measurements
provide evidence for the transport of ozone from stratospheric
extrusions to within a few kilometers of the surface (Viezee and Singh
1982). Direct evidence for transport from the stratosphere, free
troposphere, and through the planetary boundary layer to rural locations
near sea level is lacking (Viezee and Singh 1982). The air packets from
the stratosphere have been observed to level out horizontally at a few
kilometers above the surface. Ozone previously transported to these
altitudes eventually will be transported to the surface by vertical
movements, depending on the lifetime of ozone under these circumstances.
A number of reports in the literature note stratospheric ozone
contributing to ozone concentration levels at or near the surface
(Viezee and Singh 1982). If stratospheric ozone extrusions are an
important source of ozone at rural locations, a spring maximum and a
fall minimum in ozone concentrations would be expected.
Another source of ozone at the surface could be the reactions of
biogenic hydrocarbons. Because background nitrogen oxide concentrations
are so low (Section 5.3.2.5), biogenic hydrocarbons, if present at
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significant ambient air concentrations, to react would have to mix with
anthropogenic nitrogen oxides. However, the ambient air concentrations
of biogenic hydrocarbons in urban and rural locations outside of forest
canopies are too low to generate significant concentrations of ozone
(Alt shul! er 1983).
Ozone formed in homogeneous photochemical reactions in the
atmosphere from anthropogenic precursors can be present at elevated
concentration levels at rural locatins as a result of one or more of the
following processes: (1) local synthesis (2) fumigation by a specific
urban or industrial plume (3) a high pressure system near the rural
location. Ozone concentrations generated from these processes are
higher in the warmer than in the cooler months of the year. If
homogeneous photochemical reactions of anthropogenic precursors are the
more significant source, the higher ozone concentrations would be
expected to occur in the late spring, summer months, and early fall.
5.4.1 Concentration Measurements Within the Planetary Boundary Layer
TPEET
Average ozone concentrations in rural areas have been reported as
low as 20 to 40 yg m-3, at night and during the early morning hours
(Martinez and Singh 1979, Research Triangle Institute 1975, Decker et
al. 1976, Evans et al. 1982). Maximum ozone concentrations often are
found downwind of the core areas of large cities. Maximum annual
one-hour ozone concentrations in the ranges of 800 to 1300 yg m~3
have been observed during most years between 1964 and 1978 at several
locations in the South Coast Air Basin (Trijonis and Mortimer 1982,
Hoggan et al. 1982). Well out into the eastern part of the South Coast
Air Basin at San Bernardino and Redlands maximum annual one-hour ozone
concentrations of 300 to 400 ppb have been measured (Trijonis and
Mortimer 1982, Hoggan et al. 1982).
A number of studies on urban plumes of large cities in the United
States have been reported. The effects of these plumes on elevated
ozone concentrations have been shown to extend out to distances as far
as several hundred kilometers downwind. Measurements have been made on
the flow of the New York metropolitan area plume into southern New
England (Cleveland et al. 1976, 1977, Si pie et al. 1977, Spicer et al.
1979) the Boston plume into the Atlantic Ocean (Spicer et al. 1982c),
the Philadelphia-Camden plume (Cleveland and Kleiner 1975), the Chicago
metropolitan area plume (Swinford 1980, Sexton and Westberg 1980), the
St. Louis plume (White et al. 1976, 1977; Hester et al. 1977, Spicer et
al. 1982b) and the Houston plume (Westberg et al. 1978a,b).
The concentrations of ozone measured within these urban plumes
typically ranged up to between 300 to 500 yg m-3. in the case of a
city the size of St. Louis, MO an urban plume 30 to 50 km wide was
observed downwind (White et al. 1977). The ozone concentrations within
the St. Louis plume were about twice the concentrations in the
background in adjacent rural areas. A definable plume containing excess
ozone concentrations over rural background also has been demonstrated to
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occur shorter distances downwind of small cities such as Springfield, IL
(Spicer et al. 1982b).
Impacts of urban plumes from large or medium-si zed cities within
several hundred kilometers on elevated ozone concentration levels at
specific nonurban sites have been reported. Examples of such
observations include those made at Research Triangle Park, NC, Duncan
Falls, OH and Giles Co, TN (Martinez and Singh 1979); at Kisatchie
National Park, LA and Mark Twain National Park, MO (Evans et al. 1982)
and at a rural site outside of Glasgow, IL (Rasmussen et al. 1977). the
peak ozone concentrations reported during such episodes at these
nonurban sites ranged from 140 to 260 pg nr3.
Davis et al. (1974) reported measurement of excess ozone
concentrations within power plant plumes. Measurements of ozone in four
power plant plumes in the States of Washington, New Mexico and Texas by
Hegg et al. (1977) did not show any excess of ozone in the plumes over
that in surrounding air out to distance of 90 km. Other measurements of
power plant plumes in the States of New Mexico and Texas by Tesche et
al. (1977) revealed ozone depletion within the plumes in the vicinity of
the stack and a gradual increase in ozone concentrations to background
levels far downwind. Gillani et al. (1978) observed a significant ozone
excess in the Labadie power plant plume 190 km and 9 hours downwind
during July 9, 1976. The ozone concentration within the plume at this
distance downwind was 220 yg nr3, about 100 yg nr3 above the
rural background. Before 5 hours downwind an ozone deficit was
observed. During another day in July 1976 a transition from an ozone
deficit to an ozone excess was observed after only 2 hours. On both
days the first indication of ozone production was observed around 1400
hours. There appears to be less likelihood of observing excess ozone in
power plant plumes in the western than in the eastern United States.
This result may be associated with the availability of more hydrocarbon
in rural air in the eastern United States to diffuse in and react with
excess nitrogen oxide in the plume. Observations of the direct effect
of power plant plumes on ground level ozone concentrations at rural
locations are lacking.
Several studies have been made of the effects of high pressure
systems on ozone concentrations over the midwestern and eastern United
States (Research Triangle Institute 1975, Decker et al. 1976, Husar et
al. 1977, Vukovich et al. 1977, Wolff et al. 1977). The distribution of
ozone concentrations relative to a moving high pressure system have been
represented for several rural locations in Pennsylvania, at Creston in
southwestern Iowa, and Wolf Point in northeastern Montana (Decker et al.
1976, Vukovich et al. 1977). A relative minimum in the maximum diurnal
ozone concentration occurs somewhere in the region between the initial
frontal passage and the high pressure center. The highest ozone
concentrations diurnally occur after the high pressure center passes the
site or on the back side of the high pressure system. The exception was
at Wolf Point, MO, where no substantial variation in the ozone
concentrations was seen as the high pressure system passed through that
location. Meteorological analysis indicated no reason why the average
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downward transport by general subsidence or by enhanced vertical mixing
should Increase the ozone concentration In the backside of the high
pressure system. The aircraft measurements showed no Indication on the
average that the vertical gradient of ozone through the troposphere is
greater in the eastern than in the western United States. Therefore,
the elevated ozone concentrations measured from Iowa eastward could not
be attributed to downward transport of ozone. It was concluded that the
most appropriate explanation was the availability of sufficient amounts
of precursors reacting to form ozone within the high pressure systems.
The backside of the high pressure systems is the region where air
parcels have the highest residence times for precursors to react to form
ozone.
The peak ozone concentrations during the movement of the high
pressure system were betwen 200 and 500 yg m-3 at the Pennsylvania
sites, 150 yg m-3 at Creston, IA and less than 100 yg m-3 at
Wolf Point, MO. Such high pressure systems were influencing the sites
much of the time in the July to September period. For example, at one
or another of the rural sites where measurements were being made in
1973, 1974, and 1975, a high pressure center or ridge was within 450
miles of the site between 80 and 90 percent of the time (Decker et al.
1976, Vukovich et al. 1977).
A study of factors responsible for higher ozone concentrations also
was made over the Gulf Coast area (Decker et al. 1976). Elevated ozone
concentrations of 160 yg m-3 or more were frequently measured in
plumes downwind of cities, major refineries, and petrochemical
installations. Ozone concentrations over the Gulf of Mexico usually
were lower than over land except when the air parcels had previously
passed over continental sources of pollution.
Diurnal profiles of ozone concentrations averaged over study
periods or quarter of year are available from several studies (Research
Triangle Institute 1975, Decker et al. 1976, Vukovich et al. 1977,
Martinez and Singh 1979, Evans et al 1982) at the rural sites discussed
and additional sites. The average profiles are very similar, with ozone
concentrations rising in the morning hours, peaking in the afternoon,
and falling after establishment of the noctural inversion in the evening
hours through the night to 0600 or 0700 hours. From a 1974 study made
between June 14 and August 31 (Research Triangle Institute 1975) the
average 0900 to 1600 ozone concentrations of interest in crop yield
studies can be computed for the rural sites as follows: Wilmington, OH,
125 yq m-3; McConnelsville, OH, 117 yg m-3; Wooster, OH, 119
yg m-3, McHenry, MD, 116 yg m"3; DuBois, PA, 132 yg nr3.
In some of the studies discussed above, either sulfate measurements
or visibility measurements as a surrogate for fine particles are
available (Decker et al. 1976, Husar et al 1977). The sulfate
concentrations (in yg m-3) and the sulfate as a percentage of total
suspended particulate from west to east were as follows: Wolf Point,
MO, 1.8, 6.2; Creston, IA, 7.2, 9.2; Bradford, PA, 9.9, 29.0. These
measurements show the same directional characteristics from west to east
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as do the ozone concentrations. Husar et al. (1977) analyzed an episode
during late June 1976, finding that the geographical location of high
ozone concentrations roughly corresponded to areas of low visibility and
high sulfate concentrations. The air quality measurements at St. Louis
during June through August of 1975 showed that ozone concentrations
above 160 yg m-3 roughly coincided with light extinction
coefficients above 5. Therefore, a similar behavior occurs for ozone
and for light scattering aerosols such as sulfate.
5.4.2 Concentration Measurements at Higher Altitudes
Ozone measurements at several higher altitude mountainous sites
have been compiled by Singh et al. (1978). Hourly ozone concentrations
are as high as 140 to 160 yg nr3 during the spring months, and as
low as 40 to 60 yg m-3 during the fall months. While the seasonal
patterns tend to be consistent, the absolute concentrations differ from
year to year. Relatively high summer ozone concentrations have been
observed at some sites (Singh et al. 1978). Viezee and Singh (1982)
have assembled results from recent aircraft observations. Observations
between the altitudes of 1.5 and 4.5 km indicate ozone concentrations
during May in the 110 to 150 yg m-3 range and during October in the
70 to 90 yg fir3 range. A summary of aircraft observations of ozone
concentrations during stratospheric air extrusions results in a power
curve from which the ozone concentration obtained is 140 yg nr3 at 3
km, 210 yg m-3 at 5 km and 330 yg m-3 at 7 km. Based on these
aircraft measurements compared to the elevated ozone concentrations
attributed to stratospheric ozone at sites between sea level and 3 km,
Viezee and Singh (1982) believe that reports of ozone concentrations
above 200 yg m-3 near the surface attributed to stratospheric air
extrusions are unlikely and should be reexamined.
5.5 HYDROGEN PEROXIDE
The oxidation of sulfur dioxide in aqueous droplets by hydrogen
peroxide may be the most important of the mechanisms for conversion of
sulfur dioxide to sulfuric acid (Chapter A-4). Therefore, the
measurements of hydrogen peroxide concentrations are of considerable
interest.
Several chemical methods for measuring of hydrogen peroxide in
ambient air and in rainwater are in use. Both the reaction of titanium
sulfate and 8-quinolinol with hydrogen peroxide (Cohen and Purcell 1967)
and the reaction of titanium (IV) tetrachloride with hydrogen peroxide
(Pilz and Johann 1974) have been used in colorimetric procedures for
measuring hydrogen peroxide in air. The chemiluminescent oxidation of
luminol by hydrogen peroxide in the presence of Cu(II) catalyst is the
basis of a sensitive automated system for continuous monitoring of
hydrogen peroxide in the atmosphere (Kok et al. 1978b). Addition of a
known amount of scopoletin to a buffered sample containing hydrogen
peroxide followed by addition of horseradish peroxidase to catalyze the
oxidation by scopoletin results in fluorescence decay (Zika et al.
1982). The amount of hydrogen peroxide is determined by difference in
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the fluorescence before and after addition of the horseradish
peroxidase.
The long path Fourier transfer infrared technique has not proved
applicable to measuring hydrogen peroxide because of its high
detectability limit of about 56 yg nr3 (Tuazon et al. 1981a).
Recent studies (Heikes et al. 1982, Zika and Saltzman 1982)
indicate that hydrogen peroxide can be produced from other species
within aqueous solutions. These results suggest that methods involving
collection in aqueous solutions may not provide useful measurements of
ambient air hydrogen peroxide concentrations. Both groups found
hydrogen peroxide to be generated within the aqueous collecting
solutions when ozone in oxygen-nitrogen mixtures is passed through
aqueous solutions in bubblers or impingers. Heikes et al. (1982) also
observed that sulfur dioxide vapor acts as a negative interferent by
depleting hydrogen peroxide in its aqueous collection or formation.
5.5.1 Urban Concentration Measurements
Ambient concentrations of hydrogen peroxide up to 56 yg m-3 in
Hoboken, NJ and 251 yg nr3 in Riverside, CA were measured in 1970 by
Bufalini et al. (1972) using Cohen and Purcell's (1967) method.
Subsequent measurements of hydrogen peroxide in 1977 at sites in
Claremont, CA and Riverside, CA gave hydrogen peroxide concentrations
typically ranging from 14 to 70 yg nr3 with a maximum concentration
near 140 yg nr3 (Kok et al. 1978a). Three chemical methods (Cohen
and Purcell 1967, Pilz and Johann 1974, Kok et al. 1978b) were used in
intercomparisons. The hydrogen peroxide concentrations measured by the
three methods differed by as much as a factor of two to three.
Substantial ozone concentrations were present in the atmosphere during
most of the time hydrogen peroxide was being measured.
Subsequent measurements of hydrogen peroxide were made in 1979 and
1980 in the Los Angeles Basin area at sites within Los Angeles, CA,
Claremont, CA and Palo Verde, CA (Kok 1982). In Los Angeles at Cal.
State University, the hydrogen peroxide concentrations on June 18 and
19, 1980 ranged between about 0.7 and 3.5 yg nr3. The hydrogen
peroxide concentrations were 1 to 2 percent of the maximum ozone
concentrations. At Claremont, CA hydrogen peroxide measurements were
reported during a number of days in June to September 1979 and in
September 1980. In June and July 1979 the hydrogen peroxide
concentrations were much higher than reported in August 1979 and
September 1979 and 1980. Peak concentrations exceeded 14 pg nr3 in
June and July, while in August and September the hydrogen peroxide
concentrations were only a few ppb. At Point San Vincente, located in
the Palo Verde peninsula, on September 11 and 12, 1980 the hydrogen
peroxide concentrations peaked at 8 to 11 yg nr3. The maximum
hydrogen peroxide concentrations compared to the maximum ozone
concentrations show no distinct relationship (Kok 1982).
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Heikes et al. (1982) obtained about equal amounts of hydrogen
peroxide in each of three impingers in series sampling ambient air over
a series of days in February and March 1981 at Boulder, CO. If the
ambient air hydrogen peroxide was collected efficiently in the first
impinger, the ambient air hydrogen peroxide concentrations ranged from
0.4 to 3.1 yg m~3. The about equivalent amounts of hydrogen
peroxide measured in the second and third impingers indicate substantial
amounts of hydrogen peroxide were generated in solution.
5.5.2 Nonurban Concentration Measurements
Measurements of hydrogen peroxide concentrations were obtained by
the luminol chemiluminescence technique at a rural site east of Boulder,
CO in February 1978 (Kelly and Stedman 1979a). The hydrogen peroxide
concentrations ranged from 0.4 to 4 pg nr3 during this period.
Hydrogen peroxide was measured in water condensate by the luminol
chemiluminescence technique at rural sites near Tucson, AZ (Farmer and
Dawson 1982). In more remote areas around Tucson the hydrogen peroxide
concentration were about 1.4 yg nr3, while at a Thurber Ranch site
the hydrogen peroxide ranged up to 6 yg nr3. The hydrogen peroxide
concentration was observed to drop off drastically when high sulfur
dioxide concentrations were measured. With a correction for the
interference by sulfur dioxide, the authors estimated that the hydrogen
peroxide reached 10 yg nr3.
5.5.3 Concentration Measurements in Rainwater
Because the key interest in hydrogen peroxide is with respect to
its behavior in solution, available measurements of hydrogen peroxide in
rainwater will be discussed.
Hydrogen peroxide in rainwater collected in Claremont, CA during
1978 and 1979 was analyzed by luminol chemiluminescence (Kok 1980). The
hydrogen peroxide content of the rainwater over long sampling intervals
dropped off substantially during precipitation events. The highest
hydrogen peroxide concentration obtained was 1590 yg jr1, but
hydrogen peroxide concentrations also frequently were below 100 yg
i~ • The lower concentrations could be accounted for by the
absorption of less than 0.14 yg m~3 of hydrogen peroxide from
ambient air into the cloud water.
Measurements of hydrogen peroxide in rainwater also were made in
Claremont, CA during 1980 and 1981 (Kok 1982). Hydrogen peroxide
concentrations were found to be extremely variable in rainwater samples
during the course of a storm. The results were interpreted as
suggesting that hydrogen peroxide is incorporated into the rain at cloud
levels. Most of the hydrogen peroxide concentrations in the rainwater
samples were at or below 500 yg £-1.
Hydrogen peroxide was measured in rainwater samples collected in
Miami, FL and the Bahama Islands (Zika et al. 1982). The concentration
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of hydrogen peroxide in rainwater, expressed as yg £-1, ranged
from 3.06 to 25.5 x 102 in Miami, FL samples and was 6.8 x 102 in a
sample collected in the Bahama Islands. The variations of hydrogen
peroxide concentrations during the precipitation events were different
from the changes in sulfate and nitrate concentrations. The authors
believed that the results for hydrogen peroxide were consistent with a
substantial part of the hydrogen peroxide being present as a result of
its being generated within the cloudwater rather than being present as a
result of rainout and washout of gaseous hydrogen peroxide.
5.6 CHLORINE COMPOUNDS
5.6.1 Introduction
Chlorine can exist in a number of gaseous and particulate forms in
the atmosphere. The gases can include hydrogen chloride, chlorine gas,
and carbon-containing vapors such as phosgene and halocarbons. The
particulate forms include sodium chloride, usually as sea salt particles
from the bursting of bubbles at the sea surface (Junge 1963). Ammonium
chloride also has been reported (Cronn et al. 1977).
The most likely form for gaseous chloride is hydrogen chloride.
Chlorine gas reacts rapidly with hydrogen-containing organic molecules
to abstract hydrogen and form hydrogen chloride (Hanst 1981). Phosgene
(C^CO) has been measured in the ppt range in the ambient atmosphere
(Singh et al. 1977b). Numerous chlorocarbons have been measured in the
ppt to ppb range in urban atmospheres (Singh et al. 1982) and in the ppt
range at rural and remote sites (Singh et al. 1977a,b). Most
chlorocarbons have long residence times in the atmosphere (Singh et al.
1981). Their inert chemical structure tends to limit their rates of dry
deposition and wet scavenging to very low values. The shorter-lived
chlorinated olefins react in the laboratory to form chlorine-containing
products such as hydrogen chloride, phosgene, chlorinated acetyl
chlorides, and chlorinated peroxyacetyl nitrates (Gay et al. 1976). The
chlorinated acetyl chlorides and chlorinated peroxyacetyl nitrates have
not been detected in the ambient atmosphere.
A number of the same type of artifact problems may exist for
particulate chlorine measurements as for particulate nitrate
measurements because of the volatility of hydrogen chloride. However,
such studies of sampling of chlorides on filters are not available.
5.6.2 Hydrogen Chloride
Junge (1963) reported early measurements of gaseous chlorine-
containing compounds that probably were hydrogen chloride. His
measurements at three sites gave the following average concentrations in
ug m'3: Florida--!.6, Ipswich, MA--4.4, and Hawaii—I.9. Gaseous
chlorine compounds were measured by the same technique by Duce et al.
(1965) on the island of Hawaii. The concentrations of gaseous chlorine
compounds ranged from less than 0.3 yg m~3 to 218 yg m"3
although the gaseous chlorine concentrations were at or below 10 yg
5-66
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m-3 in most samples. The halide ion analysis does not permit
identification of the original chemical species collected.
Although hydrogen chloride has been measured by infrared techniques
in a number of studies in the stratosphere, limited effort has gone into
its measurement in the troposphere. Farmer et al. (1976) reported both
tropospheric and stratospheric measurements at the ground and from
aircraft. The tropospheric mixing ratio at ground level was 10~y
corresponding to 1.5 yg m-3, with the mixing ratio decreasing to
10-10 in the upper troposphere. At ground level, the tropospheric
levels were essentially the same inland in the Mohave Desert, CA, as
near the coast (Farmer et al. 1976). Hydrogen chloride was not detected
by the FTIR system with a 1 km pathlength in measurements at Riverside
and Claremont, CA (Tuazon et al. 1981b). The established detection
limit was about 12 yg m-3.
5.6.3 Particulate Chloride
Junge (1963) measured comparable amounts of particulate chloride to
gaseous chlorine-containing compounds. His measurements gave the
following average concentrations in yg m-3: Florida--1.5 and
Hawaii—5. Duce et al. (1965) measured particulate chloride on a
four-stage cascade impactor. The total chloride concentrations ranged
from 0.5 to 137 yg m-5. Three of the nine samples had total
chloride concentrations of 39, 95 and 137 yg m-3; the remainder had
concentrations below 10 yg m~3.
Particulate chloride concentration distribution was measured at
about 30 sites in the Houston-Galveston, TX, area on 2 days in June and
2 days in September 1975 (Laird and Miksad 1978). The natural
background of chloride varied from 0.2 to 6.6 yg m-3 with wind speed
and direction. The higher background concentrations corresponded to the
stronger inland penetration of fresh maritime air from the Gulf of
Mexico. Significant incremental concentrations of 5 to 10 yg m'-3
above background were observed, particularly in the industrialized
Pasadena-Houston Ship Channel area.
At urban and nonurban locations somewhat inland, atmospheric
chloride concentrations typically average 1 yg m-3 and less
(Gartrell and Friedlander 1975, Flocchini et al. 1976, Paciga and Jervis
1976, Crecelius et al. 1980, Dzubay 1980).
5.6.4 Particle Size Characteristics of Particulate Chlorine Compounds
Junge (1963) discussed the particle size characteristics of
chloride particles. The chloride particles associated with maritime air
are found in the 1 to 10 ym range. Measurements at a rural coastal
site 50 miles south of Boston, MA (Round Hill), support these
conclusions. In contrast, chloride particles below 1 ym were
associated with processes occurring over land.
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Gladney et al. (1974) reported measurements of chloride on cascade
impactors at several sites in the Boston, MA, area. The shapes of the
site distribution curves for a number of samples indicated that the
chloride present was predominantly marine aerosol and that there also
was a strong correlation between sodium and chloride for these samples.
The concentrations of both chloride and sodium were usually low, and the
size distributions flatter, when the winds were from inland.
The size distribution of chloride particles at Secaucus, NJ, have
been reported for varying visibility conditions (Patterson and Wagman
1977). The MMD increased from the background condition of best
visibility of 0.17 ym to 1.1 ym under the poorest visibility
conditions experienced. The size distributions for chloride appeared to
be trimodal. Particles below 0.5 ym were associated with lead
aerosols from automobile exhaust, the particles near 1 ym with the
contribution from sea salt, and the largest particles with dredging
operations.
The particle size distributions of chloride particles were reported
at several sites in Toronto, Canada, by Paciga and Jervis (1976). The
chloride had a mass median diameter of 0.6 pm during the summer at
this inland site. The sources of chlorides were associated with lead
aerosols from automobiles and emissions from a power plant and an
incinerator. Winter samples showed a 10-fold increase in chloride
concentration, and an increase in the MMD of chloride to about 9 urn.
These increases were attributed to salting of roadways.
Hardy et al. (1976) reported chloride size distributions at three
sites in the Miami, FL, area. Two of the sites were 2 km from the
seacoast and the third 15 km inland. The cascade impactor stages
collecting particles above 2 ym contained most of the mass. There was
a low concentration of chloride on the stages collecting particles
between 0.25 and 1 ym, but the concentration increased again on the
filter used to collect particles below 0.25 ym. The small-particle
chloride was attributed to chlorine associated with lead aerosols
emitted from gasoline powered vehicles. The large particles were
associated with particles emitted from the sea surface.
Particle size distributions of chloride were measured at sites in
Philadelphia, PA, Cincinnati, OH (Fairfax), and Chicago, IL, in the
summer and fall by Lee and Patterson (1969). The MMD's obtained were
all near 0.85 ym. Lee and Patterson concluded that the chlorides at
these sites were primarily influenced by industrial and vehicle
emissions rather than sea salt aerosols.
5.7 METALLIC ELEMENTS
The various interests and possible concerns related to metallic
elements have been discussed briefly in the introduction. Alkaline
earth elements such as calcium and magnesium can help neutralize acidic
materials either during precipitation events or as a result of dry
deposition. Manganese and iron are possibly of consequence in the
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chemical transformations of sulfur dioxide to sul f ate (Chapter A-4,
Section 4.3.5). Aluminum, manganese, nickel, zinc, lead and mercury are
discussed elsewhere in this document (Effects Chapters) in relationship
to possible adverse effects in soil, lakes and streams, and indirect
effects on health.
5.7.1 Concentration Measurements and Particle Sizes in Urban Areas
An extensive literature on the air quality measurements of metallic
elements in urban areas is available. It is not appropriate to discuss
this literature in great detail. Concentrations of most of the elements
of interest here have been reported by Stevens et al. (1978) for six
urban areas. These measurements along with particulate sulfur
concentrations are given in Table 5-11 as examples of reasonably
representative urban concentration levels of these elements. This study
is useful in also providing the percentages of these elements in
particles below and above 3.5 ym at these urban sites. Sulfur is the
most abundant element, followed by calcium, aluminum, iron and lead.
Lead concentration measurements have been extensively reviewed in
the Air Quality Criteria for Lead (U.S. EPA 1977b). In urban
communities the percentage of monitoring sites falling within selected
annual average lead concentration intervals during 1966 to 1974 were as
follows: less than 500 ng m~3, 8; 500 to 999 ng rrr3, 38; 1000 to
1999 ng m-3 45; 2000 to 3999 ng m-3, 8; 4000 to 5300 ng m-3, 1.
The lead concentrations at over 80 percent of these monitoring sites
were in the 500 to 1999 ng m-3 range. The average concentrations of
lead at the urban sites given in Table 5-11 also fall within this
concentration range.
The National Academy of Sciences (1975) review on nickel contains a
compilation of measurements of ambient air nickel concentrations from
the National Air Surveillance Networks. The overall average ambient air
concentrations of nickel at urban sites was 21 ng m~3. Nickel, as
vanadium, is associated with the type of fuel oils used in cities within
the northeastern United States. In such areas the average nickel
concentrations often are in the 100 to 300 ng m-3 during the first and
fourth quarters. The nickel concentration listed at a site in New York
City in Table 5-11 is at the lower end of this range.
The percentages of fine (less than 3.5 ym) compared to coarse
particles (greater than 3.5 ym) in Table 5-11 indicate that sulfur,
nickel, zinc and lead are most often associated with fine particles.
Calcium, aluminum, and iron are usually found in coarse particles.
Sulfur and lead show the least variability in size distribution. As
discussed earlier (Section 5.2.4), most of the particle sulfur is
present in submicron particles. Lead also is associated mostly with
submicron particles in urban areas (Robinson and Ludwig 1967, Lee et al.
1968, Lundgren 1970, Gillette and Winchester 1972, Martens et al. 1973,
Patterson and Wagman 1977). Patterson and Wagman (1977) found 70
percent of the zinc measured in background air and 80 to 90 percent of
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TABLE 5-11. CONCENTRATIONS AND PERCENTAGES OF ELEMENTS PRESENT AS FINE
PARTICLES IN PARTICIPATE MATTER AT SITES IN THE UNITED STATES
Site
Period of measurement
New York City, NYa
February 1977
Philadelphia, PAa
Feb. -March 1977
Charleston, W VAa
April -Aug. 1976
and January 1977
St. Louis, M0a
en December 1975
0 Portland, ORa
February 1977
Glendora, CAa
March 1977
Smokey Mt. , PAd
July-Aug. 1977
Parameter
Cone, ng m~3
% Fineb
Cone, ng nr3
% Fine
Cone, ng m~3
% Fine
Cone, ng m~3
% Fine
Cone, ng nr3
% Fine
Cone, ng m~3
% Fine
Cone, ng nr3
% Fine
S
5936
93
3550
87
4119
92
3526
79
1679
83
1852
87
3948
95
Concentrations and
Ca Al Mn
1509
24
1104
15
924
10
2130
6
832
8
541
18
338
5
969
13
690
7
1372
19
_.C
— c
1385
15
>331
NA
215
9
99
56
31
55
19
37
73
55
48
56
11
45
NO
NA
percentages, ng
Fe Ni
1340
29
904
24
788
21
1338
25
1123
17
484
26
146
19
75
76
37
81
1
67
25
60
52
81
17
82
2
50
m-3
Zn
458
81
186
80
50
60
221
67
91
67
61
74
<12
Z?5
Pb
1227
86
1115
85
757
82
1076
77
1040
83
706
87
114
85
aStevens et al. 1978.
Percentage of mass of element present as particles less than 3.5 m.
cConcentrations reported not consistent with other Al measurements at site.
dStevens et al. 1980.
NA = not available.
ND = not determined.
-------
the zinc measured in more polluted air on particles below 1.5 ym with
most of the zinc associated with particles between 0.5 and 1.5 urn.
Those elements present in coarse particles would be expected to be
subject to rapid deposition near their areas of emission. Fine
particles have small dry deposition velocities (Chapter A-7, Section
7.4.2). However, atmospheric dispersion should tend to rapidly decrease
the ambient air concentrations of both coarse and fine particles
associated with primary emissions from urban sources.
Mercury occurs as a vapor in the atmosphere but also can be
associated with particles. Mercury concentrations have been measured in
ambient air in several urban areas. In Washington, DC a mercury vapor
concentration of 3.2 ng nr3 was measured during February 1972 (Foote
1972). Dams et al. (1970) reported mercury concentrations of 4.8 ng
m-3 on particulate matter collected in East Chicago, IN. In Los
Altos, CA in the San Francisco Bay area mercury vapor concentrations
varied from 1 to 25 ng m-3 in winter and from 1.5 to 2 ng m-3 up to
50 ng m-3 in summer (Williston 1968). This area has Franciscan
sediments high in mercury, 100 to 200 ppb, and two mercury mines exist
within 25 miles of Los Altos. The lowest concentrations were observed
with strong westerlies bringing clear marine air ashore after rainy
weather (Williston 1968).
5.7.2 Concentration Measurements and Particle Sizes in Nonurban Areas
The concentrations of the metallic elements of interest and sulfur
in particles are given at a number of rural and remote sites within the
United States and Canada in Table 5-12. Sulfur in particles collected
at the two sites in the eastern United States is in large excess to the
other elements. Calcium, aluminum, and iron usually are the next most
abundant elements. The three elements at the Smokey Mountains, TN site,
as at the urban sites, are found to a large extent in the coarse
particles (Tables 5-12). All of the elements listed except for sulfur
and aluminum occur at substantially lower concentrations at the rural
and remote sites than at the urban sites (Tables 5-11 and 5-12). Lead
concentrations at the three rural continental sites are a factor of 10
to 20 below those at the urban sites. At the Quillayute, WA site lead
concentrations in Pacific maritime air are a factor of 300 to 600 fold
lower than at the urban sites. Nickel concentrations at the rural and
remote sites show similar behavior compared to nickel at urban sites.
However, zinc does not show reductions in concentrations as large at
rural compared to urban sites as do lead and nickel.
Additional measurements of sulfur, zinc, and lead have been
reported for the period October 1979 to May 1980 from the 40 site
Western Fine Particle (WFP) Network, including the States of Arizona,
New Mexico, Utah, Colorado, Wyoming, Montana, North Dakota, and South
Dakota (Flocchini et al. 1981). Sulfur concentrations rarely exceeded
100 ng~3 and frequently were below 500 ng nr3 on the average at
these sites. Lead concentrations were in the 30 to 80 ng m-3 range,
but on the average were below 50 ng nr3 at almost all of the sites.
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TABLE 5-12. CONCENTRATIONS OF ELEMENTS IN PARTICIPATE MATTER AT NONURBAN SITES
IN THE UNITED STATES AND IN CANADA
ro
Site
Period of measurement
Alleghany Mountain, PA
July-August 1977
Smokey Mountains, TN
September 1978
Chadron, NB 1973
Col strip, MT
May-September 1975
Quillayute, WA
April -November 1974a
December-May 1975a
Twin Georges, NW Terr.,
Canada
S
4690
3948
ND
550
ND
ND
ND
Ca
330
338
ND
390
ND
ND
ND
Al
70
215
535
930
ND
ND
66
Mn
9
ND
6
9
0.7
0.8
1.5
ng nT3
Fe
320
146
ND
410
25.3
13.1
71
Ni Zn Cd Pb
ND 20 3 90
2 <12 ND 114
ND 16 0.6 45
0.6 6.5 ND 14
0.1 4.2 ND 1.9
0.1 11.3 ND 1.8
ND 3.8 ND ND
References
Pierson et al.
1980b
Stevens et al .
1980
Struempler 1975
Crecelius et al.
1980
Ludwick et al .
1977
Dams and Dejonge
1976
aonly those days included with trajectories having marine histories for at least three days before arriving
at the Quillayute, WA site.
ND = not determined.
-------
The overall mean concentration of coarse particles was 8000 ng nr3
with 60 percent associated with soil elements and their associated
oxides. The percentage of iron in fine particles (less than 2.5
was given for the sites in the study area. The percentage of iron in
fine particles ranged from 10 to 35 percent with the range at most sites
between 15 and 25 percent. These percentages are in good agreement with
those for fine particle iron at the urban sites and at the Smokey
Mountains site (Table 5-11).
Dams and Dejonge (1976) measured aerosol composition from August
1973 and April 1975 at Jungfraujoch (3752 m above sea level) in
Switzerland and also tabulated unpublished results by K. A. Rahn
obtained at Lakelv in marine air at North Cape, Norway during the winter
of 1971-72. The concentrations in ng nr3 of the elements considered
above were as follows: Jungfrau, Al, 51; Mn, 1.5; Fe, 36; Zn, 9.9; Pb,
4.4; Lakelv, Al, 43; Mn, 2.5; Fe, 51; Zn, 8.9; Pb, 5.6. These
concentrations are not much different than at Twin Georges in the
Northwest Territory, Canada.
A number of the rural and remote sites discussed are in mountainous
and marine locations. It is reasonable that the concentrations of most
elements would be low. In particular, sources of soil derived elements
would be limited near such sites. In areas with significant numbers of
unpaved roads, agricultural activities, and other sources of windblown
soils the concentrations of soil derived elements should be
substantially higher. The much higher concentrations of aluminum at
Chadron, NB and Colstrip, MT (Table 5-12) than at mountainous and marine
sites are consistent with this expectation.
Ambient air concentrations of mercury vapor at nonurban sites have
been summarized as a function of soil conditions (U.S. Geological Survey
1970). Over areas without mercury containing minerals, ambient air
concentrations of mercury vapor were in the 3 to 9 ng nr3. Over areas
containing mercury minerals, ambient air concentrations of mercury vapor
were in the 7 to 53 ng nr3, while in the vicinity of known mercury
mines the mercury vapor concentrations reached the 24 to 108 ng m~3
range. Mercury concentrations were found to peak at midday and to
decrease rapidly with altitude (U.S. Geological Survey 1970).
At nonurban locations on the beach in the San Francisco Bay area
mercury vapor concentrations of 3.1 ng nr3 have been reported (Foote
1972). Williston (1968) collected samples at 10,000 foot altitudes 20
miles offshore of the San Francisco Bay area and obtained concentrations
of mercury vapor of 0.6 to 0.7 ng m~3. At a rural site, Niles, MI, a
mercury concentration of 1.9 ng m-3 was measured in partial!ate matter
(Dams et al. 1970). Ambient air mercury vapor concentrations of 25 ng
nr3 were reported in samples collected in Research Triangle Park, NC
(Long et al. 1973).
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5.8 RELATIONSHIP OF LIGHT EXTINCTION AND VISUAL RANGE MEASUREMENTS TO
AEROSOL COMPOSITION
Visual range measurements can be influenced by a rubber of natural
and manmade factors. Visual range can be reduced substantially on an
episodic basis by rain, fog, snow, and by wind blown dust and sand.
Rayleigh scattering by air molecules contributes to light extinction and
limited visual range, but the contribution is small except in remote
areas. Nitrogen dioxide is the only other gas in the atmosphere with
the potential to contribute significantly to light extinction, but its
concentration in the atmosphere usually is too low for it to contribute
substantially in practice. Particles in the size range between about
0.1 and 2 ym are effective light scattering components of the
atmosphere while elemental carbon particles are effective absorbers of
light (Charlson et al. 1978b). Most of the emphasis in this section
will be on the relationships between aerosol composition and visual
range and light extinction.
Sul fates and nitrates as suspended aerosol components of the
atmosphere contribute to visibility reduction through light scattering.
These aerosols also contribute to acidic deposition and its effects. To
the extent that visual range and light extinction are accounted for to a
substantial extent by sulfates and nitrate concentrations in the
atmosphere, these visibility measurements can serve as surrogates for
concentration measurements in geographical areas where measurements are
not available. Because aerosol concentrations are related to deposition
rates, the visibility measurements also can be related to deposition or
the potential for deposition.
5.8.1 Fine Particle Concentration and Light Scattering Coefficients--A
number of investigators have demonstrated a proportionality between fine
particle concentration and light scattering coefficient. Sulfates and
nitrates, in some locations, are major components of the fine particle
concentration.
Waggoner and Weiss (1980) obtained a ratio of fine particle
concentration to the light scattering coefficient, bsc, of 0.36 g
m-2 (corrected for temperature) from measurements at five urban and
rural locations in the western United States. In Denver, CO Groblicki
et al. (1981) obtained a ratio of fine particle concentration to bsp
of 0.29 g m-2. in Houston, TX Dzubay et al. (1982) obtained a very
high correlation coefficient of 0.987 between fine particle
concentration and bsp and a ratio of 0.28 g m-2. The ratios
obtained in Denver and in Houston are in reasonable agreement with the
results obtained by Waggoner and Weiss (1980).
At a site in the Shenandoah Valley, VA Weiss et al. (1982) obtained
a correlation coefficient of 0.94 for the measurements of fine particle
concentration as related to bsp and a ratio of 0.24 g nr2. A
cyclone was used to eliminate particles above 1 vm from measurement as
fine particles. Ferman et al. (1981) made measurements at the same site
during the same period. These workers obtained a correlation
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coefficient of 0.91 for the measurements of fine particle concentration
as related to b§p and a ratio of 0.14 g nr2. However, a substanti-
ally higher particulate size cutoff was used by Ferman et al. than by
Wei ss et al.
Although there is variability in the ratio of fine particle
concentration to bsp from site to site, consistently high correlation
coefficients are obtained at individual sites. The variability in ratio
is related to the corresponding variability in the ambient air aerosol
composition (White and Roberts 1977, Ferman et al. 1981).
5.8.2 Light Extinction or Light Scattering Budgets at Urban Locations
At several locations in the South Coast Air Basin concurrent
measurements of light scattering and of aerosol composition were
available from the 1973 Aerosol Characterization Experiment (ACHEX).
HIVOL sampler measurements, not fine particle measurements, were made.
White and Roberts (1977) analyzed these results to obtain relationships
between light scattering and aerosol composition. Sulfate, nitrate and
organic aerosols all made a substantial contribution to the overall
aerosol concentrations at these locations. The average percentage
contribution of aerosol classes to the light scattering (based on all
emission sources) was as follows: sul fate, 47; nitrate, 39; organics,
14. Except at high humidities, the contribution, on a unit mass basis,
of sul fate was higher than that of nitrate. A lack of dependence on
humidity of the contribution of sulfate to light scattering was found.
In contrast Cass (1976), from similar measurements in the South Coast
Air Basin, did find a dependence on humidity of both the contributions
of sulfates and nitrates to light scattering. The sum of species other
than sulfates, nitrates, and organics was found to have about one-third
the effectiveness of sulfate on a unit mass basis in contributing to
light scattering (White and Roberts 1977).
In Riverside, CA the average percentage contributions of aerosol
classes to the light scattering coefficient were found to be 70 to 75
percent for sulfate and 20 to 25 percent for nitrate on a unit mass
basis (Pitts and Grosjean 1979). No statistical association could be
found in this study between light scattering with organic carbon or any
other aerosol species measured.
In November and December 1978 at a location in Denver concurrent
measurements were made of both light scattering and absorption of
nitrogen dioxide, and of ammonium, sul fate, nitrate, organic carbon,
elemental carbon and other species in the fine particle fraction
(Groblicki et al. 1981). Of the chemical species measured the
percentage contributions to the light extinction were as follows:
sulfate as ammonium sul fate, 20; nitrate as ammonium nitrate, 17;
organic carbon, 12; elemental carbon, 38 (scattering, 6.5, absorption,
31.2); remainder of fine particle mass, 6.6; nitrogen dioxide, 5.7.
Elemental carbon was found to be the most effective species on a unit
mass basis in contributing to light extinction. Both sulfate and
nitrate were found to have their contributions to light scattering
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dependent on relative humidity. Sulfate was a more effective scatterer
on a unit mass basis than nitrate or organic carbon. The sum of other
fine particle species showed a much lower effectiveness on a unit mass
than the other species specifically considered above.
During September 1980 in Houston, TX concurrent measurements were
made of light scattering and light extinction, of nitrogen dioxide, and
of sulfate, nitrate, carbon containing compounds and many other species.
(Dzubay et al. 1982). The percentage contributions of the chemical
species measured to light extinction were as follows: sulfate and
associated cations, 32, nitrate, 0.5; carbon, 17 to 24 (scattering, 11,
absorption, 6 to 13); other aerosol components, 4; water, 16; nitrogen
dioxide, 5; Rayleigh (air), 6. The crustal elements constituted 29
percent of the total mass concentration of particulates, but only 2.9
percent of the fine particle mass. As a consequence, the crustal
elements only contributed 2.6 percent of the light extinction. No
functional relationships of sulfate and nitrate including humidity were
used. Instead, the contribution of water to light extinction was
computed separately. If the contribution of water is associated
predominately with sulfates, the sulfates and associated species would
account for about one-half of the light extinction.
The contribution of light extinction associated with nitrates was
much smaller in Houston than in Los Angeles and Denver (White and
Roberts 1977, Groblicki et al. 1981, Dzuabay et al. 1982). Nitrates
were determined in both Houston and Denver studies on Teflon filters, so
a negative nitrate artifact would be expected in both sets of
measurements. Therefore, at least on a relative basis, the nitrate
concentrations in Denver should have been much higher than in Houston.
The difference in season during which sampling was done may in part
explain the differences in nitrate concentration obtained. In the
measurements used by White and Roberts (1977) glass fiber filters were
used, so overestimates of nitrate concentration are to be expected.
Pitts and Grosjean (1979) made measurements with tandem filters and
concluded that there was only a moderate, 11 percent on average, nitrate
artifact correction.
All of the studies at urban locations discussed above involved
concurrent air quality and instrumental light scattering absorption or
extinction measurements. Several other studies have used visibility
measurements combined with HIVOL sampling results obtained at sites
within the same urban area (Trijonis and Yuan 1978a,b; Leaderer et al.
1979). Aside from the usual limitations in regression models
themselves, these studies are subject to a number of other possible
sources of error. These sources of error include some related to
airport visibility measurements (1) inadequate sets of markers (2)
changes in markers (3) changing environment in vicinity of airports.
The differences in the locations where the visibility and the air
quality measurements are taken can also result in differences also in
aerosol concentration and composition at these locations. The lack of
compositional measurements on some significant species can result in
overestimations of the contributions of measured species. Such
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overestimations can occur when there are good correlatons between
measured and unmeasured species. The use of glass fiber filters in the
HIVOL samplers means that positive nitrate artifacts are likely, as
discussed earlier in this chapter.
Despite the limitations discussed above, the airport studies do
provide results at a number of urban locations at which more acceptable
studies are not available. The estimated contributions of the chemical
species measured to light extinction budgets has been tabulated and
discussed elsewhere (U.S. EPA 1979) and will be only briefly discussed
here. On the average, for the midwestern and northeastern locations
used (Trijonis and Yuan 1978b, Leaderer et al. 1979) the average
percentages and ranges of percentage contributions of chemical species
measured to the light extinction were as follows: sulfates 56, 27 to
81; nitrates, 2, 0 to 14; remainder of TSP, 8, 0 to 44; unaccounted for,
34, 19 to 73. At southwestern sites (Trijonis and Yuan 1978a) the
nitrates were reported to make a larger contribution to light extinction
than at the midwestern and northeastern locations considered.
5.8.3 Light Extinction or Light Scattering Budgets at Nonurban
Locations
At Allegheny Mountain, PA concurrent light scattering and air
quality measurements were made during the latter part of July and early
August 1977 (Pierson et al. 1980a,b). The authors comment that the
multiple regression analyses showed bsp to be remarkably insensitive
to any aerosol constituent but sulfate or its associated cations.
Sulfate alone accounted for 94+7 percent of the variability in bsp.
An even better correlation was Tound for bsp with the product of
sulfate and humidity than with sulfate alone. With respect to visual
range the authors concluded that "sulfate may be a good index of
visibility (and vice versa) if humidity is taken into account."
In the Shenandoah Valley/Blue Ridge Mountain area of Virginia
several groups of investigators made measurements during July to August
of 1980 (Ferman et al. 1981, Stevens et al. 1982, Weiss et al. 1982).
Ferman et al. (1981) obtained light scattering and light absorption
measurements, nitrogen dioxide concentrations, and aerosol composition
measurements. The aerosol composition of the fine particle mass was
reported. Based on these results, the observed light extinction on a
percentage basis could be accounted for as follows: sulfate (including
water), 78; carbon-containing compounds, 15.5 (scattering, 13,
absorption, 2.5); nitrogen dioxide, 0.3; Rayleigh (air), 5. For the
periods in the upper decile of bsp values the sulfate (and water)
accounted for 4 percent of the light extinction. Weiss et al. (1982),
from their measurements at the same site, also concluded that all of the
water at 70 percent RH was associated with sulfate and ammonium. The
sulfate with associated cations and water accounted on average for 70
percent of the light scattering. This result is in reasonable agreement
with the 78 percent obtained by Ferman et al. (1981). Stevens et al.
(1982) measured aerosol composition, but not light extinction. However,
it is of interest to compare their composition results for the fine
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particle mass with those obtained by Ferman et al. (1981). The
percentage of the fine particle mass contributed by the various chemical
species (do not add up to 100 percent) from the Ferman et al. study and
the Stevens et al. study, respectively were as follows: sulfate as
ammonium bisulfate, 55.4, 60.8; elemental carbon, 5.4, 5.7; organic
carbon (measured carbon x 1.2), 23.6, 4.1; nitrate as ammonium nitrate,
0.6, ND; Pb-Br-Cl, 0.2, 0.3; crustal (estimated from Si), 7.3, 1.1. The
higher percentage for sulfates and the lower percentage for organic
carbon in the Stevens et al. (1982) study would result in an even larger
contribution of sulfates to light extinction than found by Ferman et al.
(1981).
At another location in the eastern mountains of the United States,
Great Smoky Mountains, TN, aerosol composition, but no light extinction
measurements, were made (Stevens et al. 1980). The percentage of the
fine particle mass contributed by the various chemical species (do not
add up to 100 percent) were as follows: sulfate as ammonium bisulfate,
56; elemental carbon, 5; organic carbon (measured carbon x 1.2), 11;
Pb-Br-Cl, 0.5; crustal, 0.5. The percentages of sulfates and elemental
carbon at the Great Smoky Mountains site were nearly the same as at the
Shenandoah Valley site. In contrast, the organic carbon and the crustal
elements made up a substantially lower percentage of the fine particle
mass at the Great Smoky Mountain site (Stevens et al. 1980) than
reported by Ferman et al. (1981) at the Shenandoah Valley site.
In the midwestern United States at rural sites in Missouri and in
the Ozark Mountains, Weiss et al. (1977) concluded that essentially all
of the aerosol light scattering was due to sulfates. Measurements of
sulfate as ammonium sulfate at rural sites in the vicinity of St. Louis
indicate that 45 to 50 percent of the fine particle mass was ammonium
sulfate in the first and fourth quarters of the year and over 70 percent
of the fine particle mass was ammonium sulfate in the fourth quarter of
the year (Altshuller 1982). As in nonurban sites in the eastern United
States, the sulfates in the midwest are the major contributors to the
fine particle mass.
In the southwestern United States at nonurban locations concurrent
measurements of light extinction and of aerosol composition have been
made (Macias et al. 1980). From samples obtained in flights over the
Southwest the average percentge contributions of chemical species to
light scattering were as follows: sulfate as ammonium sulfate, 16;
silicon dioxide, 16: other fine mode particles, 8; coarse mode
particles, 4; Rayleigh (air), 44. In measurements at a nonurban site,
Zilnez Mesa, AZ measurements of light extinction and aerosol composition
were made (Macias et al. 1981). The average percent contributions to
light extinction were as follows: sulfate as ammonium sulfate, 18;
organic carbon, 33; elemental carbon, 12; nitrate, 2; other fine
particles, 20; coarse particles, 15. In individual measurements
Rayleigh scattering contributed from 16 to 54 percent. The light
extinction budgets at these western nonurban sites are clearly
substantially different than at eastern nonurban sites. Sulfates at
these western nonurban sites make a much smaller contribution to the
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light extinction than at eastern sites. Carbon-containing particles,
other fine mode species, coarse mode species, and Rayleigh scattering
are relatively more important at western than eastern nonurban sites.
However, the light extinction is smaller and the visual range much
greater at the western nonurban sites because the absolute amounts of
aerosol species are so much smaller.
The contributions of sulfates compared to other chemical species to
light extinction at rural sites in the midwestern and eastern United
States appear more important than in western urban areas (White and
Roberts 1977, Pitts and Grosjean 1979, Groblicki et al. 1981) and
western nonurban locations (Macias et al. 1980, 1981). At eastern rural
sites visibility should be a good index or surrogate for sul fates
(Pierson et al. 1980a, Ferman et al. 1981, Weiss et al. 1982). It is
less evident that visibility in the western United States can be used as
a surrogate for sulfates or for sulfates and nitrates.
5.8.4 Trends in Visibility as Related to Sulfate Concentrations
Several investigations have indicated that the patterns of
historical visibility at airport sites and sulfate trends in the eastern
United States are consistent with each other (Trijonis and Yuan 1978b,
Husar et al. 1979, Altshuller 1980, Sloane 1982a,b). The improvements
in visibility in the first and fourth quarters of the year appear
consistent with the decreases in sulfate concentrations. Similarly, the
deterioration of visibility during the 1960's into the 1970's was
consistent with the increase in sulfate concentrations. Further
deterioration in visibility during the 3rd quarter of the year did not
occur later in the 1970's, again consistent with the trends in sulfate
concentrations (Altshuller 1980, Sloane 1982b).
5.9 CONCLUSIONS
The following statements summarize the discussion in this chapter
on the atmospheric concentrations and distributions of chemical
substances. Table 5-13 summarizes measurements of sulfur, nitrogen, and
chlorine compounds in rural areas.
0 Sulfur dioxide concentrations have been high in urban areas in the
eastern United States, but decreased substantially during the
1960's into the 1970's. The decreases in sulfur dioxide appear to
be associated with local reductions in the sulfur content of fossil
fuels (Section 5.2.2.1).
0 In rural areas sulfur dioxide concentrations are appreciably lower
than in urban areas. The differences in concentrations between
urban and rural areas were not as great by the late 1970's as in
earlier years. This change primarily is the result of the
decreases in urban sulfur dioxide concentrations (Section 5.2.2.2).
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TABLE 5-13. CONCENTRATIONS OF SULFUR, NITROGEN, AND CHLORINE
COMPOUNDS AT RURAL SITES IN THE UNITED STATES IN THE 1970'S
Range of
Average concentrations, yg m-3
Compound
Sulfur dioxide
Sulfur aerosols
Nitrogen dioxide
Nitrate aerosols
Nitric acid
Peroxyacyl nitrates
Ammonia
Hydrogen chloride
Chloride aerosols
Maritime
Inland
East
10-20a
5-15a
10-20&
1C
0.3-1.3
0.5-1C
0.5-2<*
1-10C
1-10C
<_ 1C
West
NA
l-3a
12C
NA
1 lc
0.1-0.3C
0.5-2C
1-10°
1-10C
1 lc
aAnnual average.
bSummer months: August to December averages.
cLimited number of measurements.
NA= Not available.
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Sulfate concentrations decreased in eastern cities during the
1960's into the 1970's except during the third quarter of the
year (Section 5.2.3.1).
In rural areas in the eastern United States sulfate concentrations
have not decreased appreciably throughout the year and sulfates
have increased in concentration during the summer months (Section
5.2.3.3).
Sulfate concentrations within rural areas in the eastern United
States by the 1970's were almost as high as in adjacent urban
areas (Section 5.2.3.3).
Sulfate aerosols can contribute one-third to one-half the sulfur
budget (sulfur dioxide plus sulfate) in rural areas within the
eastern United States during the summer, but contribute relatively
little to the sulfur budget in the winter months (Section 5.2.3.3).
Sulfate aerosols are substantially higher in rural areas in the
eastern United States than in the western United States (Section
5.2.3.3).
Sulfate aerosols occur predominately in the fine particle size
range with much of the mass of sulfate aerosols concentrated
between 0.1 and 1 ym. Particles in this size range deposit more
slowly than does sulfur dioxide, so they can be transported
substantial distances (Section 5.2.4).
Sulfate aerosols tend to be more acidic in summer months than in
winter months and more acidic in rural areas than in urban areas
(Sections 5.2.3.2 and 5.2.3.4).
Much of the sulfate aerosol has been shown to be in the form of
strong acid species in the eastern mountains of the United States
during summer months (Section 5.2.3.4).
Sulfur dioxide and sulfate concentrations in remote areas are
between a factor of 10 and 100 lower than the concentrations in
rural areas in the eastern United States (Sections 5.2.2.2, 5.2.2.3
and 5.2.3).
Nitrogen oxides reach about the same concentration range as sulfur
dioxide in cities. Their concentrations have become more
significant relative to sulfur dioxide with the decrease in sulfur
dioxide emissions (Section 5.3.2.3).
Nitrogen oxides are substantially lower in concentration in rural
areas than in urban areas (Sections 5.3.2.3 and 5.3.2.4).
Nitrogen dioxide concentrations are substantially lower in rural
areas within the eastern United States than in the western United
States (Section 5.3.2.4).
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At remote locations the concentrations of nitrogen oxides can be 10
to 100 times lower than in rural areas of the eastern United
States (Section 5.3.2.5).
The average concentrations of nitric acid or of peroxyacetyl
nitrates are about a factor of ten lower than the average
concentrations of nitrogen dioxide in both urban and rural areas
(Sections 5.3.3.1 and 5.3.3.2).
The average concentrations of nitric acid are in the same
concentration range as the average concentrations of peroxyacetyl
nitrates in rural areas (Section 5.3.3.2).
The concentrations of nitric acid in the boundary layer in remote
areas are a factor of 5 to 10 lower than in rural areas in the
eastern United States (Section 5.3.3.3).
The equilibrium between ammonia, nitric acid, and ammonium nitrate
can be important in determining the ambient air concentrations of
these chemical substances (Section 5.3.5).
Several positive and negative nitrate artifacts on filters have
been identified and investigated. Such artifacts make most of the
measurements on single or tandem filter systems for particulate
nitrate unreliable (Section 5.3.6).
Measurements of particulate nitrate made using diffusion denuders
appear to be reliable. At both urban sites in Los Angeles and
rural sites in the eastern United States such measurements indicate
that particulate nitrate concentrations can exceed nitric acid
concentrations in the late evening and in the early morning hours.
Conversely, nitric acid concentrations are higher than particulate
nitrate concentrations in the late morning and afternoon hours
(Sections 5.3.6.1 and 5.3.6.2).
Particle size distributions of particulate nitrates are influenced
by the same nitrate artifact problems. It does appear that the
particle sizes of nitrates decrease in going from coastal locations
inland in California. The reason is related to the greater
abundance of submicron sodium nitrate aerosols in maritime air
reacted with nitrogen dioxide, compared to the submicron ammonium
nitrate aerosols found inland (Section 5.3.7).
The concentrations of sulfate aerosols appear to be several times
greater than the concentrations of nitric acid and particulate
nitrate at rural sites in the eastern United States (Sections
5.2.3.3, 5.3.3.2 and 5.3.7).
Ozone concentration levels in rural areas can result from one or
more of the following processes: (1) local synthesis, (2)
fumigation by urban or industrial plumes, (3) high pressure systems
near rural sites, and (4) stratospheric extrusions reaching ground
level (Section 5.4).
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Rural locations within urban plumes may experience ozone
concentrations in the range of 300 to 500 yg m"3. Within high
pressure systems, ozone concentrations at rural locations can range
from 150 to 250 yg nr3 (Section 5.4.1).
At remote elevated sites, hourly ozone concentrations are as high
as 140 to 160 yg nr3 during the spring months and as low as 40
to 60 yg m~3 in the fall months. Occasional observations of
ozone concentrations in excess of 200 yg nr3 attributed to
stratospheric air extrusions at remote sites appear too high
compared to aircraft measurements of ozone through the
troposphere (Section 5.4.2).
Ambient air measurements of hydrogen peroxide are in doubt because
of recent demonstrations of in situ generation of hydrogen peroxide
in aqueous solutions (Section 5.5).
Hydrogen peroxide concentrations measured in rainwater usually
correspond to those resulting from the absorption of less than 1
yg nr3 of hydrogen peroxide from the ambient atmosphere
(Section 5.5.3).
The variations in hydrogen peroxide concentrations measured in
rainwater during precipitation events are consistent with a
substantial part of the hydrogen peroxide being generated within
the cloudwater rather than being present as a result of rainout and
washout of gaseous hydrogen peroxide (Section 5.5.3).
The concentrations of particulate chloride compounds can be
important near the ocean, but not inland. At inland sites
particulate chlorides tend to be submicron in size and have been
associated with automotive lead aerosol emissions and with
emissions from combustion sources (Section 5.6.4).
The concentrations of metallic elements in most urban areas occur
at 1 to 2 yg m"3 and below. The bulk of the calcium, aluminum,
and iron occurs in coarse particles, while most of the lead and
zinc occurs in fine particles. The substantial differences in size
distribution should result in those elements found in coarse
particles usually being of local origin, while the elements in fine
particles are capable of being transported substantial distances
(Section 5.7.1).
Although lead aerosols are largely submicron in size, lead
concentrations drop off rapidly from urban to rural to remote
sites. At continental rural sites lead concentrations are a factor
of 10 to 20 below concentrations at urban locations. At remote
sites the lead concentrations are several hundred times lower than
at urban sites (Section 5.7.2).
High correlations exist between fine particle mass and light
scattering coefficients (Section 5.8.1).
5-83
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At eastern rural sites sulfate accounts for a large part of the
fine particle mass and the light extinction (Section 5.8.3).
At western locations nitrate and carbon-containing particles make a
substantial contribution to fine particle mass and to light
extinction (Section 5.8.2).
At rural sites in the eastern United States visibility measurements
should be a good index or surrogate for particulate sulfate
concentrations (Section 5.8.3).
5-84
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THE ACIDIC DEPOSITION PHENOMENON AND ITS EFFECTS
A-6. PRECIPITATION SCAVENGING PROCESSES
(J. M. Hales)
6.1 INTRODUCTION
The complex process of precipitation scavenging can be subdivided
into a number of distinct steps, which occur interactively within a com-
posite storm system. These are itemized as follows:
0 intermixing of pollutant and condensed water within
the same airspace,
° attachment of pollutant to the condensed water
elements,
0 chemical reaction of pollutant within the aqueous
phase,
0 delivery of pollutant-laden water elements to the
surface via the process.
Each of these steps can be associated with a corresponding
processing time that depends upon the pollutant, synoptic circumstances,
and storm type. In the simplest sense, the scavenging process occurs as
a forward progression through these steps; reverse processes are common,
however, and a pollution element may experience several cycles through
segments of this process before its ultimate wet deposition to the
Earth's surface. This chapter examines the several steps as they relate
to the problem of wet deposition of acidic substances.
Pollutant condensed-water intermixing, the process that introduces
pollutant to the immediate vicinity of cloud and precipitation systems,
can involve considerable time lags between a pollutant's emission and
its subsequent processing by the storm. Usually it is not cloudy or
raining in the vicinity of a pollutant's release point, and often
several days may occur before a storm is encountered. During this
period the pollutant may become involved in a variety of processes
(e.g., dry deposition, chemical reaction) that may alter its
concentration and physical state, and consequently alter its scavenging
characteristics once a storm is encountered. Thus, while the
storm-pollutant intermixing process is not considered totally within the
realm of wet removal, it is a highly important determinant of scavenging
time and distance scales and the resulting chemical composition of
precipitation.
The actual physical attachment of pollutant to condensed water
elements (ice, cloud droplets, rain) greatly depends upon both the
6-1
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physical and chemical states of the pollutant. For aerosol particles,
any or all of the following collection mechanisms may be active:
o nucleation of cloud droplets on the pollutant particles
o electrical attachment
° diffusiophoretic and thermophoretic attachment
o Brownian motion
° inertia! attachment
All mechanisms in the above list depend upon particle size, and usually
several mechanisms operate simultaneously to provide a composite capture
process in given situations.
Diffusional and convective transport are the primary attachment
mechanisms for gaseous pollutants. Gas scavenging differs from aerosol
scavenging in the important respect that gases may desorb from, as well
as absorb, in cloud particles and hydrometors. Thus relative rates of
absorption and desorption often determine to a large extent the net
efficiency of attachment, and for this reason gas solubility emerges as
an important factor in the scavenging process.
This chapter deals only briefly with the aqueous-phase reaction
step, owing to the fact that it is treated elsewhere within this
document (Chapter A-4). It should be stressed, however, that although
reaction is not necessary for scavenging to occur, it often emerges as
an important rate-limiting step. This importance stems primarily from
chemical conversion's capability, in some circumstances, to devolatilize
absorbed gaseous pollutants and thus inhibit their tendency for
desorption noted earlier. The conversion of dissolved S02 to sulfate
is an important example.
The final stage of the composite scavenging process is the actual
wet delivery of pollutant to the ground. This step is linked closely to
rain formation and precipitation processes and thus depends strongly
upon the variety of cloud-physics phenomena commonly associated with
water extraction. These include autoconversion of cloud elements to
form precipitation, accretion and condensation processes, and a host of
ice-formation phenomena. The kinetics of such processes often cast a
significant rate influencing influence on the overall scavenging
process.
Area! deposition by storm systems strongly depends on
climatological features of the storms themselves. Although a detailed
treatise on North American storm climatology is well beyond the scope of
this work, some limited insight in this regard may be gained by a
partial classification of storm types and a climatological analysis of
storm tracks.
6-2
-------
Much of what is known presently with regard to precipitation
scavenging has been learned as a consequence of field studies.
Pertinent field experiments are summarized in tabular form in
Section 6.4.
Mathematical models of precipitation scavenging tend to reflect the
stepwise sequence suggested above. Based upon conservation equations
for pollutant material, these models are similar in many respects to
typical air pollutant models, but differ in the sense that they must
account for gas-liquid exchange and wet delivery. A profusion of
different wet removal models is currently available and is presented in
tabular form in Section 6.5.
6.2 STEPS IN THE SCAVENGING SEQUENCE
6.2.1 Introduction
Precipitation scavenging is defined generally as the composite
process by which airborne pollutant gases and particles attach to
precipitation elements and thus deposit to the Earth's surface. This
definition pertains to removal from the gaseous medium of the atmosphere
combined with deposition to the ground. An alternative definition,
employed often throughout the open literature, pertains to the simple
attachment of airborne pollutants to liquid water elements, without
regard to whether the material is subsequently conveyed to the Earth's
surface. Which of these definitions is used is unimportant so long as
the precise definition is understood. The definition of "scavenging"
adopted here will be used consistently throughout this text. When
specific reference to the alternative situation is made, the terms
"attachment" and "capture" will be employed essentially
interchangeably.
This scavenging process typically contains many parallel and
consecutive steps, so as an introduction to this section it is
appropriate to provide a brief overview of these intermeshing pathways.
In a very general sense there are four major events in which a pollutant
moleculei may participate, prior to its wet removal from the
atmosphere; depicted pictorially in Figure 6-1, these are:
1-2. The pollutant and the condensed atmospheric water (cloud,
rain, snow, ...) must intermix within the same airspace.
^•Initial portions of this chapter will treat precipitation scavenging
in a general sense, with limited reference to specific types of
atmospheric material. The reader should continue to note, however,
that the "natural or pollutant molecules" of primary concern in the
present context are species associated with acid-base formation,
such as SOg, HN03, NH3, sulfate, chloride, metallic cations,
and so forth.
6-3
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MIXING
1
UNREACTED POLLUTANT
REACTED POLLUTANT
CONDENSED WATER
PRECIPITATION
Figure 6-1. Steps in the scavenging sequence: Pictorial representation.
6-4
-------
2-3. The pollutant must attach to the condensed-water elements.
3-4. The pollutant may react physically and/or chemically within
the aqueous phase.
3-5. The pollutant-laden water elements must be delivered to the
or(4-5.) Earth's surface via the precipitation process.
The interaction diagram of Figure 6-2 gives a somewhat more
detailed portrayal of these four major events. Here the individual
steps are represented as transitions of the pollutant between various
states in the atmosphere, and one can note that a multitude of reverse
processes are also possible; thus a particular pollutant molecule may
experience numerous cycles through this complex of pathways prior to
deposition. Indeed, Figure 6-2 indicates that this cycling process may
continue even after "ultimate" deposition. By pollutant off-gassing and
other resuspension processes, the deposited material can be re-emitted
to the atmosphere, with the possibility of participating in yet another
series of cycles throughout the scavenging sequence.
Another important feature of Figure 6-2 is that, while physio-
chemical reaction within the aqueous-phase is potentially an important
step in the scavenging process, it is not essentialI. This contrasts to
the remaining forward steps that must take place if scavenging is to
occur. Despite its nonessential nature, this step is often of utmost
importance in influencing scavenging rates, owing to its role in
modifying reverse processes in the sequence. An example of this effect,
already discussed in Chapter A-4, is the devolatilization of dissolved
sulfur dioxide via wet oxidation to sulfate. This effectively
eliminates gaseous desorption from the condensed water and thus has a
strong tendency to enhance the overall scavenging rate as a result.
From Figure 6-2 one can note also that precipitation scavenging of
pollutant materials from the atmosphere is intimately linked with the
precipitation scavenging of water. If one were to replace the word
"pollutant" with "water vapor" in each of the steps, Figure 6-2 (with
the exception of box 4) would provide a general description of the
natural precipitation process. In view of this intimate relationship,
it is not surprising that pollutant wet-removal behavior tends to mimic
that of precipitation. Pollutant-scavenging efficiencies of storms, for
example, are often similar to water-extraction efficiencies. This
relationship is useful in practically estimating scavenging rates and
will reappear continually in the ensuing discussion of wet-removal
behavior.
Figure 6-2 is interesting also because of its indication that, if
some particular step in the diagram occurs particularly slowly compared
to the others, then this step will dominate behavior of the overall
process. This is similar to the "rate-controlling step" concept in
chemical kinetics, and has been applied rather extensively in practical
scavenging calculations (SI inn 1974a). Finally, it is important to note
6-5
-------
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Figure 6-2. Scavenging sequence: Interaction diagram.
6-6
-------
that Figure 6-2 presents a framework for developing and evaluating
mathematical models of scavenging behavior. Successful scavenging
models must emulate these steps effectively and tend to reflect the
structure of Figure 6-2 as a result. This point will be recalled later
when scavenging models are examined specifically. The following
subsections will address qualitative aspects of the scavenging sequence
in the order of their forward progress to ultimate deposition.
6.2.2 Intermixing of Pollutant and Condensed Water (Step 1-2)
Upon first consideration, one often is inclined to dismiss
pollutant-condensed-water intermixing as an unimportant or at least
trivial step in the overall scavenging sequence. It is neither. In a
statistical sense it usually is neither cloudy nor precipitating in the
immediate locality of a freshly-released pollutant molecule; typically
this molecule must exist in the clear atmosphere for several hours, or
even days, before it encounters condensed water with which it may
co-mingle. This in itself establishes step 1-2 as a potentially
important rate-influencing event. Moreover, this extended dry period
typically presents the pollutant with significant opportunities to react
and/or deposit via dry processes; thus the chemical makeup of
precipitation is influenced profoundly by this preceding chain of
events.
Significant insights to the behavior of step 1-2 can be gained via
past analyses of storm formation (Godske et al. 1957) and the
atmospheric water cycle (Newell et al. 1972). Several statistical
analyses of precipitation occurrence (Rodhe and Grandel 1 1972, 1981;
Gibbs and SI inn 1973; Junge 1974; Baker et al. 1979) have been applied
as general interpretive descriptors of this step. These will not be
examined in detail here; rather we shall concentrate upon the mechanisms
by which step 1-2 can occur, from a more pictorial viewpoint.
Two types of mixing processes exist whereby pollutant and condensed
water can come to occupy common airspace; these are
1) Relative movement of the initially unmixed pollutant and
condensed water, in a manner such that they merge into a
common general volume; and
2) In situ phase change of water vapor, thus producing condensed
water in the immediate vicinity of pollutant molecules.
The relative importance of Type-1 and Type-2 mixing processes will
depend to some extent on the pollutant. J/f a particular pollutant is
easily scavengable and j_f precipitation is occurring at the pollutant's
release location, then Type-1 processes are likely to contribute
significantly. If these two conditions are not met, the pollutant will
usually mix intimately with makeup water vapor for some future cloud,
and Type-2 processes will predominate. Based upon in-cloud vs below-
cloud scavenging estimates (SI inn 1983) it is not unreasonable to
6-7
-------
estimate that, as a global average, roughly 90 percent of all
precipitation scavenging occurs as the consequence of a Type-2 process.
As Figure 6-2 indicates, reverse processes can serve to reseparate
pollutant and condensed water. Evaporation, for example, can reinject
pollutant from cloudy to clear air, and relative motion such as
precipitation "fall-through" can remove hydrometeors from contact with
elevated plumes. Cloud formation--reevaporation cycles are particularly
significant in this respect. Junge (1963), for example, estimates that
a single cloud condensation nucleus is likely to experience on the order
of ten or more evaporation-condensation cycles before it is ultimately
delivered to the Earth's surface with precipitation. The rate-
influencing effect of such cycling on precipitation scavenging is
obvious. Additional types of cycles will be described below in
conjunction with succeeding steps of the scavenging sequence.
6.2.3 Attachment of Pollutant to Condensed Water Elements (Step 2-3)
The microphysics of the pollutant-attachment process have been the
subject of extensive research, and numerous reviews of this area have
been prepared (Junge 1963, Davles 1966, Dingle and Lee 1973, Pruppacher
and Klett 1978, Hales 1983, Slinn 1983, Slinn and Hales 1983). This
process (Figure 6-1) is complicated somewhat in the sense that,
depending upon the particular attachment mechanism, Step 2-3 may occur
either simultaneously or consecutively with Step 1-2.
Simultaneous comixing and attachment occur in the case of
cloud-particle nucleation. This is a phase-transformation (Type-2)
process wherein water molecules, thermodynamically inclined to condense
from the vapor phase, migrate to some suitable surface for this purpose.
Pollutant aerosol particles provide such surfaces within the air parcel,
and the consequence 1s a cloud of droplets (or ice crystals)2 contain-
ing attached pollutant material.
Different types of aerosol particles possess different capabilities
to nucleate cloud elements and grow by the condensation process. As a
consequence, typically competition for water molecules exists among the
aerosol and associated cloud particles. Some will capture water with
high efficiency and grow substantially in size. Others will acquire
2At this point it is important to note that aerosols can participate
in several types of phase transitions in cloud systems. These include
vapor-liquid, vapor-solid, and liquid-solid transitions, in addition to
a subset of Interactions between numerous solid phases. Particles
active as ice-formation nuclei are generally much less abundant than
those active as droplet (or "cloud-condensation") nuclei. As will be
demonstrated later, the relative abundance of ice nuclei can have a
profound effect upon precipitation-formation processes and related
scavenging phenomena.
6-8
-------
only small amounts of water, and still others remain essentially as
"dry" elements. In addition, some particles may nucleate ice crystals,
while others will be active only for the formation of liquid water. The
nucleating capability of a particular aerosol particle is determined by
its size, its morphological characteristics, and its chemical composi-
tion. Various aspects of this subject are discussed at length in
standard cloud-physics textbooks (Mason 1971, Pruppacher and Klett 1978)
and in the periodical literature (Fitzgerald 1974).
An additional important aspect of the cloud-droplet nucleation and
growth process is the fact that once initiated, cloud-droplet growth
does not proceed instantaneously to some sort of thermodynamic
equilibrium. Because of diffusional constraints on delivering water
molecules from the surrounding atmosphere, the growth in droplet
diameter slows appreciably as droplet size increases (SIinn 1983).
Superimposition of this lag on the continually fluctuating environment
of a typical cloud results in a dynamic and complex physical system.
Finally, the competitive nature of the cloud-nucleation process
results in significant impacts by the pollutant on the basic character
of the cloud itself. If the local aerosol were populated solely by a
relatively small number of large, hygroscopic particles, for example,
one would expect any corresponding cloud to be composed chiefly of small
populations of large droplets. If on the other hand the local aerosol
were composed of large numbers of small, nonhygroscopic particles, the
corresponding cloud should contain larger numbers of smaller droplets.
This is precisely what is observed in practice. Unpolluted marine
atmospheres, for example, contain large sea-salt particles as a primary
component of their aerosol burden. Warm marine clouds are noted for
their wide drop spectra containing large drop sizes and their
corresponding capability to form precipitation easily. Continental
clouds, on the other hand, are typically composed of larger populations
of smaller droplets. Figure 6-3, prepared on the basis of results
published by Squires and Twomey (1960), provides a good example of this
point. Here, measured convective-cloud droplet spectra are compared
for two different cloud systems. The continental air-mass cloud
exhibits a distinct tendency toward smaller drop sizes and larger
populations, as compared to its maritime counterpart. It is interesting
also in this context to note Junge's (1963) estimates with regard to
relative amounts of aerosol participating in the nucleation process.
Junge suggests that while 50 to 80 percent of the mass of continental
aerosols can be expected to participate as cloud nuclei, as much as 90
to 100 percent of maritime aerosols can become actively involved.
As a concluding note in the context of nucleating capability and
water competition, it should be pointed out that acid-forming particles,
by their very nature, are chemically competitive for water vapor and
thus tend to participate actively as cloud-condensation nuclei. This
attribute tends to enhance their propensity to become scavenged early in
storm systems and has a significant effect on the nature of the acid
precipitation formation process.
6-9
-------
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There are numerous mechanisms by which pollutants can attach to
cloud and precipitation elements after the elements already exist, thus
In a manner consecutive with Step 1-2. These mechanisms are Itemized In
the following paragraphs. They are typically active for both aerosols
and gases, although the relative Importances and magnitudes vary widely
with the state of the scavenged substance.
Diffuslonal attachment, as Its name Implies, results from
dlffusional migration of the pollutant though the air to the water
surface. This process may be effective both In the case of suspended
cloud elements and falling hydrometeors. It depends chiefly upon the
magnitude of the pollutant's molecular (or Brownian) dlffuslvlty;
because dlffuslvlty Is Inversely related to particle size, this
mechanism becomes less Important as pollutant elements become large.
Dlffuslonal attachment Is of utmost Importance for scavenging of gases
and very small aerosol particles. For all practical purposes, It can be
Ignored for aerosol particle sizes above a few tenths of a micron.
In concordance with Pick's law (Bird et al. 1960), diffusional
transport to a water surface also depends upon the pollutant's
concentration gradient in the vicinity of this surface. Thus if the
cloud or precipitation element can accommodate the influx of pollutant
readily, it will effectively depopulate the adjacent air, thus making a
steep concentration gradient and encouraging further diffusion. If for
some reason (e.g., particle "bounce off" or approach to solute
saturation) the element cannot accommodate the pollutant supply, then
further diffusion will be discouraged. If the cloud or precipitation
element, through some sort of outgassing mechanism, supplies pollutant
to the local air, then the concentration gradient will be reversed and
diffusion will carry the pollutant away from the element.
Mixing processes inside cloud or precipitation elements play an
important role in determining the accommodation of gaseous species. If
mixing is slow, for example, it is likely that the element's outer layer
will saturate with pollutant and thus inhibit further attachment
processes. This is quite often a limiting factor in cases involving gas
scavenging by ice crystals. Internal mixing occurs as a consequence of
diffusion and fluid circulation and has been analyzed by Pruppacher and
his coworkers (Pruppacher and Klett 1978).
In general, diffusional attachment processes are sufficiently well
understood to allow their mathematical description with reasonable
accuracy, and numerous references are available as guides for this
purpose (Pruppacher and Klett 1978, Hales 1983, Slinn 1983).
Inertia! attachment processes directly depend upon the size of the
scavenged particle, and thus are unimportant for gaseous pollutants. In
a somewhat general sense this class of processes depends upon motions of
pollution particles and scavenging elements relative to the surrounding
air, which arise because both have finite volume and mass. The most
important example of inertia! attachment is the impactlon of aerosols on
falling hydrometeors. Here the hydrometeor (because of its mass and
6-11
-------
volume) falls by gravity, sweeping out a volume of space. Some of the
aerosol particles (because of their mass) cannot move sufficiently
rapidly with the flow field to avoid the hydrometeor and, thus, are
impacted. In principle, impaction could occur even if the aerosol
particles were point masses with zero volume. Assigning a volume to a
particle further increases its chance of collision, simply on the basis
of geometric effects. The inclusion of aerosol volume in this context
has been generally referred to in the past literature as interception.
The effectiveness of impaction and interception depends upon both
aerosol-particle and hydrometeor size; mathematical formulae exist which
can be used conveniently to estimate the magnitudes of these processes
(e.g., Hales 1983, SI inn 1983). These effects generally become
unimportant for aerosols less than a few microns in size. In this
context, it is interesting to note that a two-stage capture mechanism
can exist, in which a small aerosol first grows via nucleation to form a
larger droplet, which then can be captured by inertia! attachment in a
secondary process. This two-stage process has been postulated as an
important mechanism in below-cloud scavenging (Radke et al. 1978, Slinn
1983). It is also an essential factor in the in-cloud generation of
precipitation and is generally referred to as accretion.
A second example of inertia! attachment is turbulent collision. In
this case the particles and scavenging elements subjected to a turbulent
field collide because of dissimilar dynamic responses to velocity
fluctuations in the local air. This capture mechanism is thought to be
of secondary importance and has received comparatively little attention
in the literature although past theoretical treatments of turbulent
coagulation processes (e.g., Saffman and Turner 1955, Levich 1962, Fuchs
1964) indicate that it may be significant for specific dropsize-particle
size ranges.
While the mechanisms of diffusional and inertia! attachment are
efficient for capturing very fine and very coarse particles,
respectively, a region of low efficiency should exist approximately in
the 0.1 to 5.0 micron range where neither mechanism is effective. This
effect is shown schematically for a given drop in Figure 6-4. Because
its importance to scavenging was first recognized by Greenfield (1957),
it has become known generally as the "Greenfield gap." Depending upon
circumstances, several additional attachment mechanisms (including the
two-stage nucleation-impaction mechanism mentioned earlier) can serve to
"fill" the Greenfield gap. Some of the more important of these are
itemized in the following paragraphs.
Diffusiophoretic attachment to a scavenging element can occur
whenever the element grows via the condensation of water vapor. In
effect, the flux of condensing water vapor "sweeps" the surrounding
aerosol particles to the element's surface. In a competitive
cloud-element system where some droplets grow while others evaporate,
diffusiophoresis can be a rather important secondary attachment
6-12
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mechanism. This is particularly true when the cloud contains mixtures
of ice and liquid. Under such conditions, the ice crystals have a
pronounced tendency, owing to their lower equilibrium vapor pressure, to
gain water at the expense of the droplets. Known as the Bergeron-
Findeisen effect, this process is important in precipitation formation
as well as in diffusiophoretic enhancement.
Thermophoretic attachment results from a temperature gradient in
the direction of the capturing element. Here the element acts
essentially as a miniature thermal precipitator. Warmer gas molecules
on the outward side of the aerosol particle impart a proportionately
larger amount of momentum, resulting in a driving force toward the
capturing element.3
Thermophoresis depends directly upon the temperature gradient in
the vicinity of the capturing element. In cloud and precipitation
systems local temperature gradients are caused most often by
evaporation/condensation effects; thus, thermophoresis is usually
strongly associated with diffusiophoresis,4 and in fact these two
processes often tend to counteract each other.
Phoretic processes are unimportant in the case of gaseous
pollutants, owing to the overwhelming contributions of molecular
diffusion. At present, the theory of diffusiophoretic/thermophoretic
particle attachment is at a state where reasonably quantitative
assessments can be made for simple systems such as isolated droplets
(SI inn and Hales 1971, Pruppacher and Klett 1978, See Figure 6-4).
Rough estimates are possible for more complex and interactive
cloud/precipitation systems, but much remains to be done to make our
knowledge of this area satisfactory.
Electrical attachment of aerosol particles to cloud and precipita-
tion elements has been the subject of continuing study over the past
three decades. Understanding of this process is currently at a state
where relationships between aerosols and isolated droplets can be
quantified with reasonable accuracy (Wang and Pruppacher 1977). In
general, electrical charging of cloud and/or precipitation elements must
be moderately high for electrical effects to become competitive with
other capture phenomena, although such charging is certainly possible in
the atmosphere—particularly in convective-storm situations.
Understanding of electrical deposition in clouds of interacting drops is
still relatively unsatisfactory.
30ne should note that the precise mechanisms of thermal transport
differ radically, depending upon particle size (cf., Cadle 1965).
^As noted by Slinn and Hales (1971), inappropriate treatment of this
relationship has caused erroneous conclusions to be drawn in some of
the past literature. The reader should be cognizant of this if more
detailed pursuit is intended.
6-14
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While the mechanisms of attachment processes have been presented
here on an individual basis, they tend in actuality to proceed in a
simultaneous and competitive manner. Insofar as atmospheric cleansing
is concerned, this is a fortunate circumstance, because some mechanisms
tend to operate in physical situations where others are ineffective.
Figure 6-4 gives an excellent illustration of this point. Theoretical
attachment efficiencies appropriate to a 0.31 mm radius raindrop are
presented in it for various electrical and relative-humidity conditions,
demonstrating the capability of phoretic and electrical mechanisms to
"bridge" the Greenfield gap. This simultaneous and competitive
interaction of mechanisms serves to complicate profoundly the mathe-
matics of the scavenging process, and lends an additional degree of
difficulty to the problem of scavenging calculations. This complicity
will continue to emerge throughout this chapter, especially during the
discussion of scavenging models.
6.2.4 Aqueous-Phase Reactions (Step 3-4)
Aqueous-phase conversion phenomena have been discussed in some
detail in Chapter A-4 and will not be examined further here except to
note their general importance within the framework of the overall
scavenging sequence. As noted previously in the context of Figure 6-2,
aqueous-phase reactions are not essential to the scavenging process.
Depending upon the pollutant material, however, these reactions often
can have the effect of stabilizing the captured material within the
condensed phase and, thus, enhancing the scavenging efficiency
appreciably. Much needs to be learned before this important topic is
satisfactorily understood.
6.2.5 Deposition of Pollutant with Precipitation (Step 4-5)
Although a variety of mechanisms exist (e.g., impaction of fog on
vegetation), the predominant means for depositing pollutant-laden
condensed water to the Earth's surface is simply gravitational
sedimentation. Sedimentation rates depend upon hydrometeor fall
velocities, which depend in turn upon hydrometeor size. Thus, the
processes by which the pollutant-laden cloud droplets grow to
precipitation elements emerge as major determining factors of the final
stage of the scavenging sequence.
Once attached to condensed water, a pollutant molecule has several
alternative pathways for action (Figure 6-2). If the captured pollutant
possesses some degree of volatility it may desorb back into the gas
phase. Reverse chemical reactions may occur. Evaporation of the
condensed water may, in effect, "free" the pollutant to the surrounding
gaseous atmosphere. This multitude of pathways results in an active
competition for pollutant. If the precipitation stage of the scavenging
sequence is to be effective, it must interact successfully within this
competitive framework.
6-15
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Besides competing actively for pollutants, the above interactions
produce a vigorous competition for water. This parallel relationship
between pollutant scavenging and water scavenging, apparent in some of
the preceding discussion regarding attachment processes, can be drawn
even more emphatically when we consider precipitation processes. The
following paragraphs provide a brief overview of some of the more
important mechanisms in this regard.
Once initial nucleation has occurred, cloud particles may grow
further by condensation of additional water vapor. Net condensation
will occur to the surface of a cloud element whenever water vapor
molecules can find a more favorable thermodynamic state in association
with it. Because clouds contain varieties of makeup elements having
different thermodynamic characteristics, competition for water vapor
usually exists. Such interactions are discussed at length in standard
textbooks (Mason 1971, Pruppacher and Klett 1978). SI inn (1983) has
developed a conceptual scavenging model in which condensational growth
is an important rate-limiting step.
Thermodynamic affinity for water-vapor molecules depends upon the
cloud-element's size, its pollutant burden, and its physical structure.
These latter two factors often influence precipitation characteristics
profoundly. In particular, the favored thermodynamic state of a water
molecule in association with an ice crystal (as compared with a
supercooled water droplet) results in rapid competitive growth of ice
particles in mixed-phase clouds. This Bergeron-Findeisen process has
been mentioned already in the context of diffusiophoretic and
thermophoretic transport. Growth of large cloud elements via this
process is the primary reason that ice-containing clouds tend to be so
strongly effective as generators of precipitation water.
A further mechanism by which suspended cloud droplets can grow to
form precipitation elements is coagulation. This process occurs via the
collision of two or more cloud elements to form a new element containing
the total mass (and pollutant burden)5 of its predecessors.
Coagulation occurs over size-distributed systems of cloud elements by a
variety of physical mechanisms and, because of this, is a rather poorly
understood and mathematically complex process. Comprehensive analyses
of coagulation processes have been performed by Berry and Reinhardt
(1974). Coagulation can be considered an important initiator of
precipitation in single-phase clouds (water or ice). In mixed-phase
clouds, the Bergerson-Findeisen process can be expected to enhance the
coagulation process by widening the droplet size distribution, as well
as contributing to precipitation growth in a direct sense.
5Coagulation is often referred to as autoconversion in the cloud
physics literature. It is interesting to notice in this context that,
while coagulation tends to accumulate nucleated pollutants, the
Bergeron-Findeisen process tends to re-liberate nucleated pollutants to
the air.
6-16
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Once a moderate number of precipitation-sized elements have been
generated, the process of accretion rapidly begins to dominate as a
means for generating precipitation water. As noted previously, this
process occurs by the "sweeping" action of large hydrometeors falling
through the field of smaller elements, attaching them on the way. As
was the case with coagulation, the accretion process tends to accumulate
the pollutant burden of all collected elanents.
Accretion can occur via drop-drop, drop-crystal, and crystal-
crystal interactions. Drop-crystal interactions are particularly
important in mixed-phase clouds; when supercooled droplets are accreted
by falling ice crystals, the process is usually referred to as
riming.
Although the above discussion has been confined primarily to
deposition in conjunction with rain and snow, it should be emphasized
that fog deposition often is an important secondary process for
conveying pollutants to the Earth's surface. A "fog" is (rather
pragmatically) defined here as any cloud adjacent to the Earth's
surface. Classification of fog-bound pollutant deposition is
problematic for two major reasons. The first of these is that no sharp
demarcation exists between "fog droplets" and "water-containing
aerosols;" thus the choice of considering fog deposition as simply the
dry-deposition of wet particles, or the wet-deposition of contaminated
water depends primarily on personal preference. Secondly, no real
distinction exists between fog droplets and precipitation. Cloud
physicists often find it convenient to categorize condensed atmospheric
water into "precipitation" and "cloud" classifications, with the
presumption that cloud water has a negligible sedimentation velocity.
Such a classification is of limited use when we consider fog deposition,
however, because fog droplets do have significant gravitational fall
speeds. A 50-micron diameter fog droplet, for example, will fall at a
rate of about 10 cm s"1. This, combined with the fact that typical
fogs and clouds contain droplet-size distributions ranging between 0 to
100 microns (Pruppacher and Klett 1978), suggests that gravitational
transport of fog droplets will indeed be a significant pollution-
deposition pathway under appropriate circumstances.
In addition to purely gravitational transport, fog droplets have a
strong tendency to impact on projected surfaces. The rates of fog
impaction depend in a complex fashion upon drop size, wind velocity, and
geometry of the projected object. The common observations of rime-ice
accumulation on alpine forests and on power-transmission lines give
direct testimony to the effectiveness of this process.
Chemical deposition by fogs is directly proportional to fog-bound
pollutant concentration, and this fact often acts to enhance
substantially the pathway's overall effectiveness. Owing to their
proxmity to the Earth's surface, fogs typically form in conjunction with
high pollutant concentrations. Attaching particles and gases via the
variety of mechanisms described in Section 6.2.3, the droplets typically
accumulate extremely high burdens of material. It is not difficult to
6-17
-------
find evidence to support this point. Scott and Laulainen (1979), for
example, reported sulfate and nitrate concentrations approaching 500
ym £-1 in water obtained near the bases of clouds over Michigan,
while the SUNY group has reported (Falconer and Falconer 1980) numerous
similar concentrations (as well as extremely low pH measurements) in
clouds sampled at the Whiteface Mountain, New York observatory.
Recently, Waldman et al. (1982) have reported nitrate and sulfate
concentrations in Los Angeles fogs ranging up to and beyond 5000 ym
£-1. This compares with typical precipitation-borne concentrations
of about 35 ym £-1 for the northeastern United States.
Recently Lovett et al. (1982) have applied a simple impaction model
to estimate fog-bound pollutant deposition to subalpine balsam fir
forests, and have concluded that chemical inputs via this mechanism
exceed those by ordinary precipitation by 50 to 300 percent. This is
undoubtedly an extreme case, and it would be more meaningful to possess
a regional assessment indicating the general importance of fog
deposition on an area! basis. This requires substantial effort,
however, involving climatological fogging analysis (Court 1966) as well
as numerous additional factors, and no really satisfactory evaluation of
this type is presently available. Regardless, it is appropriate to
conclude that fog-deposition processes probably play an important, if
secondary role in pollutant delivery on a regional basis. In the
future, more effort should address this important research area.
6.2.6 Combined Processes and the Problem of Scavenging Calculations
The preceding discussion of individual steps in the scavenging
sequence has been intentionally presented on a highly visual and non-
mathematical basis, with appropriate references given for the reader
interested in more detailed pursuit. Despite the qualitative nature of
this presentation, however, it should be obvious that the most direct
and expedient approach to model development is first to formulate
mathematical expressions corresponding to each of these steps and then
to combine them in some sort of a model framework that describes the
composite process. This subject will be examined in greater detail in
Section 6.5, which specifically addresses scavenging models.
6.3 STORM SYSTEMS AND STORM CLIMATOLOGY
In the present text the term "storm" is intended to denote any
system in which precipitation occurs. This definition thus encompasses
all occurrences, ranging from mild precipitation conditions up to and
through the major and cataclysmic events.
6.3.1 Introduction
From the preceding discussion, it is easy to imagine that
scavenging rates and pathways will be dictated to a large extent by the
basic nature of the particular storm causing the wet removal to occur.
Storms containing water that is predominantly in the ice phase, for
6-18
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example, will provide little opportunity for attachment mechanisms
associated with droplet nucleation, accretion, or phoretic processes.
The abundance of liquid water and the temperature distribution in a
given storm will have a direct bearing on the degree to which
aqueous-phase chemistry can occur. Storms containing no ice phase
whatsoever will be generally ineffective as generators of precipitation,
and thus will tend to inhibit the scavenging process. An interesting
indication of the importance of storm type in this regard is presented
in Figure 6-23 (see Section 6.5.4), which presents estimated scavenging
efficiencies which vary extensively with storm classification.
Different storm types differ profoundly with regard to inflow, internal
mixing, vertical development, water extraction efficiency, and cloud
physics; consequently it is appropriate at this point to consider
briefly the major classes and climatologies of storm systems occurring
over the continental United States.
Two major points should be stressed at the outset of this
discussion. The first of these is the essential fact that all storms
are initiated by a cooling of air, which leads to a condensation
process. Such cooling may occur by the transport of sensible heat, such
as when a comparatively warm, moist air parcel flows over a cold land
surface. The dominant cooling mode for most storm systems, however, is
expansion, which occurs via vertical motion of the air parcel to
elevations of lower pressure. The second noteworthy point in this
context is that the overwhelming majority of storm systems is strongly
associated with fronts between one or more air masses. The primary
reason for this associaton is that thermodynamic perturbations and
discontinuities associated with the frontal surfaces provide the
opportunity for vertical motion (and thus expansion processes) to occur.
This relationship is an essential component of storm classification
systems, and will emerge repeatedly in the following discussion.
Overlaps in the characteristics of different storm types render a
strict classification largely impossible. For practical purposes,
however, it is convenient to segregate mid-latitude continental storms
into two classes, which are usually described as being "convective" and
"frontal." These two major categories then can be subdivided further as
deemed expedient for the purpose at hand, although it should be noted
that significant overlap among storm types occurs even at this major
level of classification. Frontal storms, for example, often possess
significant convective character in their basic composition, and true
convective storms often occur as the consequence of fronts. Because of
this, the following discussion will use storm classification primarily
as a descriptive aid and will not belabor taxonomic detail.
6.3.2 Frontal Storm Systems
Much of what is understood today regarding mid-latitude
frontal-storm systems stems from the pioneering work of the Norwegian
meteorologist Bjerknes, who conducted a systematic survey of large
numbers of storm systems and from this survey developed a conceptual
6-19
-------
model of frontal-storm development and behavior. Characterized
schematically in Figure 6-5, the Bjerknes model can be understood most
easily by considering a cool northern air mass, separated from a warm
southern air mass by an east-west front, as indicated in Figure 6-5a.
The progression of figures represents a typical result of the
atmosphere's natural tendency to exchange heat from southern to northern
latitudes across this front. This is often referred to as a "tongue" of
warm air intruding into the cold air mass. In the northern hemisphere
this wave will tend to propagate in an easterly direction; thus the
intrusion is bound by two moving fronts--a warm front followed by a cold
front, as shown in Figure 6-5c.
Flows associated with the wave system occur in a manner such that a
depression in atmospheric pressure occurs at the vertex of the warm-air
intrusion; as a consequence a general counterclockwise or "cyclonic"
circulation pattern emerges. Because of this feature, Bjerknes1
conceptual model is often referred to as the "Bjerknes cyclone theory,"
and frontal storms associated with this pattern are termed "cyclonic"
storms. A typical feature of storms of this type is the tendency for
the cold front to overtake the warm front and ultimately annihilate the
wave. The "occluded" front created as a consequence of this behavior is
shown schematically in Figure 6-5d. In view of this birth-death
sequence of the Bjerknes cyclone model, the progression depicted in
Figure 6-5 often has been termed the "life history" of a cyclone. Some
idea of spatial scale and the general cyclonic flow pattern of a mature
cyclone are given in Figure 6-6. In viewing these indicated flow
patterns, however, the reader should note carefully that considerable
vertical structure exists in such systems, and marked deviations of the
wind field with elevation are typical. In particular, one should take
care not to confuse the indicated general circulation patterns with
corresponding surface winds.
Although created from the limited observational base available
during the early twentieth century, the fundamental precepts of the
Bjerknes theory have proven valid even as more sophisticated
observational and analytical facilities have become available.
Certainly nonidealities and deviations from this model occur; but its
general concepts have proven to be immensely valuable as a conceptual
basis and as an idealized standard for the assessment of actual storm
systems. Comprehensive descriptive and theoretical material pertaining
to such systems is available in the classic text by Godske et al.
(1957), and more elaborate and modern extensions are given in the
periodical literature (e.g., Browning et al. 1973, Hobbs 1978).
6.3.2.1 Warm-Front Storms--!t is important to note that the plane views
exhibited by Figure 6-6 are gross simplifications, since they do nothing
to characterize the three-dimensional nature of the cyclonic system. If
one were to construct a vertical cross section of the warm front (A-A1
in Figure 6-6), then typically one would observe an inclined frontal
surface as shown in Figure 6-7. (See Table 6-1 for definitions of cloud
abbreviations.) In this situation the presence of warm air aloft
6-20
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Figure 6-5. Cyclonic storm development according to Bjerkne's conceptual model.
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Figure 6-6. General flow patterns in the vicinity of an idealized cyclonic storm system. Arrows denote
general circulation patterns and should not be interpreted as surface winds (cf. Figures
6-7, 6-8, and 6-9).
-------
TABLE 6-1. SUMMARY OF CLOUD TYPES APPEARING
IN FIGURES 6-7 THROUGH 6-9
Type Abbreviation
Cirrus Ci
Cirrostratus Cs
Cirrocumulus Cc
Altostratus As
Atlocumulus Ac
Stratus St
Stratocumulus Sc
Nimbostratus Ns
Cumulus Cu
Cumulonimbus Cb
6-23
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FLOATING ICE NEEDLES
FALLING ICE NEEDLES
FLOATING FOG DROPS
"ICE NUCLEI LEVEL"
FALLING SNOW
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Km
600 800
FALLING RAIN
::':!":::. FALLING DRIZZLE
0°C ISOTHERM
RELATIVE VELOCITY OF WARM AIR
RELATIVE VELOCITY OF COLD AIR
A'
Figure 6-7. Vertical cross section of a typical warm front (Section A-A1 on Figure 6-6) Adapted
from Godske et al. (1957).
-------
creates a relatively stable environment, which inhibits vertical mixing
of air between the two air masses. The warm, moist air moves up over
the cold air wedge, expanding, cooling, and ultimately forming clouds
and precipitation. Typically the warm air supplying moisture for this
purpose has been advected from deep within the southern air mass,
carrying water vapor and pollutant over extensive distances. This
transport trajectory has been aptly compared to a "conveyor belt" for
moisture by Browning et al. (1973). It is appropriate to note that this
moisture conveyor belt is a conveyor belt for pollution as well.
Warm-front storms are often associated with long periods of
continuous precipitation, although significant structure can exist
within such systems. Important structurally in this regard are the
prefrontal rain bands, which take the form of concentrated areas of
precipitation embedded within the major storm system. At present, the
factors contributing to rain-band formation are not totally understood,
although mechanisms such as seeding from aloft by ice crystals and
nonlinearities of the associated thermodynamic and flow processes
undoubtedly contribute to a major extent.
Warm-front storms usually can be expected to be rather effective as
scavengers of pollution originating from within the warm air mass,
especially if temperatures in the feeder region are sufficiently high to
allow the presence of liquid water and the nucleation-accretion process.
Scavenging of pollutants from the underlying cold air mass will usually
be less effective, owing to the relative scarcity of clouds and
generally less definitive flows in this sector. Scavenging in both
regions will of course depend upon the physiochemical nature of the
pollutant of interest and the microphysical attributes of the cloud
system in general. Methods for estimating scavenging rates in such
circumstances are discussed in Section 6.5.
6.3.2.2 Cold-Front Storms--A typical vertical cross section (B-B1 in
Figure 6-6) of a cold-front storm is shown in Figure 6-8. This differs
substantially from the warm-front situation in the sense that, instead
of flowing over the frontal surface, the warm air is forced ahead by the
moving cold air mass. This action produces a more steeply inclined
frontal surface that, combined with the presence of low-elevation warm
air, creates a relatively unstable situation leading to convective
uplifting and the formation of clouds and precipitation.
Although discussed here in a frontal-storm context, this
precold-front situation composes an important class of convective
storms, which will be discussed in some detail later. Scavenging rates
and efficiencies associated with such storm systems will again depend
upon the pollutant and the physical attributes of the particular cloud
system involved.
6.3.2.3 Occluded-Front Storms--Because occluded fronts are formed via
merger of warm and cold fronts, it seems reasonable to expect that
storms associated with occlusions should share characteristics of the
respective elementary systems. Figure 6-9, which shows a typical
6-25
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FLOATING ICE NEEDLES
FALLING ICE NEEDLES
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FLOATING FOG DROPS
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FALLING SNOW
FALLING RAIN
FALLING DRIZZLE
0°C ISOTHERM
RELATIVE VELOCITY OF WARM AIR
•«— RELATIVE VELOCITY OF COLD AIR
Figure 6-8. Schematic vertical cross section of a typical cold front (Sction B-B1 on Figure 6-6)
Adapted from Godske et al. (1957).
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Figure 6-9.
FALLING SNOW
FALLING RAIN
FALLING DRIZZLE
0°C ISOTHERM
RELATIVE VELOCITY OF WARM AIR
RELATIVE VELOCITY OF COLD AIR
RELATIVE VELOCITY OF COLDEST AIR
Schematic vertical cross section of a typical occluded front (Section C-C' on Figure 6-6)
Adapted from Godske et al. (1957).
-------
vertical cross section (Section C-C1 on Figure 6-6) of an occluded
system, demonstrates this point. Typically the easterly flow of warm
air aloft maintains a relatively stable environment to the east of the
occlusion, and clouds and precipitation occur in this region largely as
a consequence of ascending flow from the south. Much more detailed
accounts of occluded systems can be found in standard references such as
the book by Godske et al. (1957).
6.3.3 Convective Storm Systems
An idealized cross section of a typical convective storm is shown
in Figure 6-10. Such storms depend upon atmospheric instabilities to
induce the necessary vertical motions and concurrent cooling and
condensation processes and are therefore most likely to occur under
warm, moist conditions where the energetics are most conducive to this
process. Often convective storm systems occur as "clusters" of cells,
such as that shown in Figure 6-10, and exhibit a marked tendency to
exchange moisture and pollutant between cells; thus, the flow dynamics
and scavenging characteristics of such systems tend to be extremely
complex.
Typically the moisture and pollutant input to a convective cell
occurs primarily through the storm's updraft region (cf., Figure 6-10),
although entrainment from upper regions is possible as well. Dynamics
of this process are such that violent updraft velocities capable of
lifting entrained air, water vapor, and pollution to extremely high
elevations (sometimes breaching the stratosphere) often occur. Along
this course, entrained pollutant is subjected to a large variety of
environments and scavenging mechanisms; as will be noted in Section 6.5,
convective storms tend to be highly effective scavengers of air
pollution.
As was stated earlier, convective storms often are associated with
frontal systems, although frontal influence is not absolutely necessary
for their presence. An isolated air mass, for example, is totally
capable of acquiring sufficient energy and water vapor to induce a
convective disturbance on its own accord. Perturbations arising from
fronts, however, often contribute to the creation of convective
activity—if for no other reason than supplying a "trigger" to initiate
convection in a conditionally unstable atmosphere.
6.3.4 Additional Storm Types: Nom'deal Frontal Storms, Orographic
Storms and Lake-Effect Storms
As noted previously, the Bjerknes cyclone model represents
something of an idealized concept, and numerous features can contribute
to deviations from this "textbook" behavior. Orographic effects are
highly important in this regard. Consider, for example, a cyclonic
disturbance approaching the North American continent from across the
Pacific Ocean; the frontal patterns typically lose much of their
6-28
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3
ro
o
o
-s
TEMPERATURE (°C)
-------
original identity after impacting with the western mountainous regions.
In addition to the physical distortion of flow patterns, the lifting
induced by the terrain encourages further precipitation, resulting in
large spatial variability in rainfall patterns and pronounced local
phenomena such as "rain shadows" and chinooks. Precipitation-formation
and precipitation-scavenging processes associated with such systems tend
to be highly complex.
Frontal systems often tend to reconstitute their structure after
crossing the Rocky Mountains, but continental effects still impart a
marked impact on their basic makeup. In the midwest-northeast region,
for example, fronts tend to orient themselves in an east-west direction
and become stationary for extended periods, often punctuated by several
minor low-pressure areas. Even under relatively ideal conditions
continental frontal storms tend to possess more convective flavor in
their basic makeup than do their oceanic counterparts.
As indicated above, terrain-induced or "orographic" effects are
usually most important in augmenting major storm systems, although
relatively isolated orographic storms (such as oceanic "island-induced"
storms) certainly do occur. Orographic effects obviously will tend to
be most pronounced in regions where radical terrain changes occur; but
even the small elevation changes typical of the Midwest can contribute
significantly at times. Orographic effects also are suspected to
influence storm behavior over substantial downwind distances. Lee waves
from the Rocky Mountains, for example, have been suggested to trigger
thunderstorm formation at extended distances.
Lake-effect storms are yet another example of a somewhat nonideal
phenomenon superimposed with more major meterological patterns.
Typically such storms occur during fall and early winter, when land
surfaces tend to be cooler than their adjoining water bodies. Con-
sidering an air parcel moving on an easterly course across Lake
Michigan, for example, we note the warm lake surface tends to supply
both heat and water vapor as it proceeds. As this parcel is advected
across the downwind shore, however, two important things will occur.
First, the cold land mass will extract the heat from the air; second,
the orographic lifting (on the order of a few tens of meters) will
result in ascent, expansion, and further cooling. The net result is a
lake-effect storm. Such storms can induce highly variable precipitation
patterns in specific areas around the Great Lakes region. Although
confined largely to this portion of the United States, these storms
account for a majority of the snowfall that accumulates in specific
cities such as Muskegon, Michigan, and Buffalo, New York. Some
appreciation for the magnitude of this effect can be gained by viewing
the climatological precipitation map given in Figure 6-11.
6.3.5 Storm and Precipitation Climatology
The exceedingly complex subject of storm climatology will be
discussed here only to the point necessary to describe some key
attributes and indicate references for more detailed pursuit. Factors
6-30
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70
30
v
iOUTH BEND
Figure 6-11.
Average annual snowfall pattern (inches) over Lake Michigan
and environs. Adapted from Changnon (1968).
6-31
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especially important in the context of precipitation scavenging are
temporal and spatial precipitation patterns, storm-trajectory behavior,
and storm duration statistics. These will be discussed in the following
paragraphs.
6.3.5.1 Precipitation Climatology—Figure 6-12 provides cl imatological
averages of monthly precipitation amounts at various stations throughout
the United States. This figure, taken directly from the U.S.
Cl imatological Atlas (1968), requires little elaboration at this point.
It is interesting to note, however, that precipitation amounts do not
vary radically throughout the year at most northeastern U.S. stations;
this contrasts especially with the western and arid stations, whose
seasonal variabilities tend to be pronounced. It should be noted as
well that actual precipitation amounts for a given single month can vary
appreciably from the climatological averages presented here.
6.3.5.2 Storm Tracks—Because of the difficulties noted previously with
regard to precise classification or definition of storms, a truly
concise climatological summary of storm-pathway behavior is largely
impossible. Some useful information can be generated, however, by
observing the tracks of the cyclonic (low-pressure) centers associated
with major storm systems. Klein (1958), for example, has conducted a
systematic survey of cyclonic centers in the northern hemisphere and
from this has constructed monthly climatological maps of low-pressure
tracks. Figure 6-13, taken from the book by Haurwitz and Austin (1944),
presents the combined results of the analyses by several previous
authors. On the basis of the previous discussion it should be
re-emphasized that, owing to the complex flow processes associated with
cyclonic systems, one should not interpret the motion of these low
pressure centers as being identical with feeder trajectories for the
storms themselves. Successful interpretation of such information in the
context of source-receptor analyses requires careful and skilled
meteorological guidance.
Several additional points should be emphasized in the context of
Figure 6-13. First, it should be noted that this presents a long-term
composite average and that marked deviations from this pattern can be
expected to occur with season. Second, the statistical variability of
storm tracks is such that substantial departures from the long-term
averages can be expected for any particular year. Finally, substantial
evidence documents longer-term shifts in average storm-track
distributions (Zishka and Smith 1980); thus presentations (such as
Figure 6-13) that are based upon historical data may vary considerably
from storm patterns to be observed over the next twenty years. The
implications of this with regard to long-term acidic deposition
forecasting are obvious.
Additional features of cyclonic storm climatology can be found in
standard climatological textbooks (e.g., Haurwitz and Austin 1944).
Convective-storm climatology, which tends to be much more region-
specific, can be evaluated from such references as well, although more
6-32
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NORMAL MONTHLY TOTAL PRECIPITATION (Inches)
I
CO
co
Figure 6-12. Cl Imatological Summary of U.S. Precipitation. From U.S. Climatological Atlas (1968).
-------
Figure 6-13.
Major climatological storm tracks for the North American
continent. Adapted from Haurwitz and Austin (1944). Dashed
lines denote tropical cyclone centers, and solid lines denote
those of extratropical cyclones.
6-34
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recent weather modification programs such as METROMEX, NHRE, and HIPLEX
have generated a considerable amount of new information in this area.
6.3.5.3 Storm Duration Statistics—In preparing regional scavenging
models, it often is desirable to create some sort of statistical average
of storm characteristics so that "average" wet-removal behavior can be
defined. Although little activity has been devoted to this area until
very recently, the usefulness of such an approach to regional model
development suggests accelerated effort during future years.
The analysis by Thorp and Scott (1982) provides an example of one
such effort. These authors compiled data from hourly precipitation
records from northeastern U.S. stations to obtain seasonally-stratified
duration statistics, which were expressed in terms of probability plots
as shown in Figure 6-14. As can be noted from these plots, "average"
storm durations during summertime are significantly less than durations
of their wintertime counterparts, reflecting relative influences of
short-term convective behavior. Some of the references given in Section
6.5 suggest potential modeling applications for these statistical
summaries.
6.4 SUMMARY OF PRECIPITATION-SCAVENGING FIELD INVESTIGATIONS
For the purposes of this document "field investigations" of
precipitation-scavenging mechanisms will be differentiated from routine
precipitation-chemistry network measurements, which are intended
primarily for characterization purposes. Of course a great deal of
overlap occurs between these two classes of measurements, and
significant reciprocal benefit is generated as a consequence of each.
Some essential differences exist between the two, however, and it is
convenient for present purposes to differentiate them accordingly.
The primary distinguishing feature 9f a scavenging field
investigation is that the study usually is designed around the basis of
some sort of conceptual or interpretive model(s) of scavenging behavior,
which is tested on the basis of the field data. If the model
predictions and data disagree, then some basic precepts of the model
must be invalid, and additional mechanistic insights must be generated
to rectify the situation. In the event that predictions and data agree,
then this may be taken as evidence that the precepts may be correcTT
Regardless of whether positive or negative results are obtained (and
assuming that the field study has been well-designed and
well-interpreted), an advance in understanding has been achieved. The
importance of such input cannot be overemphasized. Examples exist
wherein field investigations have demonstrated then-accepted models to
be in error by several orders of magnitude (e.g., Hales et al. 1971).
Field studies have been essential in keeping the models "honest."
Field studies of precipitation scavenging began in earnest during
the early 1950's to gain an understanding of radioactive fallout.
Pioneering studies in this area were performed in England by Chamberlain
(1953); they pertained to radioactive pollutant releases from point
6-35
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9£-9
PRECIPITATION PER STORM DURATION CLASS AS A FRACTION OF
GRAND SUM SEASONAL PRECIPITATION
cu n
o
e
ro
CD
O H-
• •
CO o
e
ro
CUMULATIVE FRACTION OF NORMALIZED TOTAL REGIONAL PRECIPITATION
-------
sources in anticipation of reactor accidents and related phenomena.
These constituted the basis for the washout-coefficient approach to
scavenging modeling (see Section 6.5). Other studies focused primarily
on nuclear-detonation fallout, thus approaching the scavenging problem
from a more global point of view.
Following the English lead, nuclear-oriented studies were conducted
by the United States, Canada, and the Soviet Union. These included
studies of tracers as well as those of the radionuclides themselves.
Although some of this material still remains in the classified
literature, it may be stated with certainty that most of what we know
today regarding scavenging processes has been generated as a consequence
of the nuclear era. The review "Scavenging in Perspective" by Fuquay
(1970) presents a comprehensive account of this early stage of
scavenging field studies.
During the late 1960's field-experiment emphasis shifted to more
conventional pollutants, with the general recognition of precipitation
scavenging's importance in preserving atmospheric quality and its
potential adverse impacts of deposition on the Earth's ecosystem. Since
that time a variety of large and small field studies have been
conducted. These are summarized in Table 6-?., which provides a logical
classification in terms of source type, pollutant type, and geographical
scale.
Although field studies have been focused strongly on quantitative
aspects of precipitation scavenging, they have provided important
qualitative information regarding acidic precipitation processes as
well. The ensemble of studies listed in Table 6-2 presents a rather
cohesive base of evidence in this regard; and although some conflicting
results and uncertainties do exist, a generally coherent picture can be
constructed in several important areas. Although there is considerable
overlap of source-receptor distance scales among these studies, they
tend to group rather conveniently into three classes of areal extent: 0
to 20 km, 0 to 200 km, and 0 to 2000 km. These classes shall be termed
loosely as "local," "intermediate," and "regional" scales in the
following discussion, where key qualitative features are illustrated by
considering the fate of specific acidic precipitatin precursors (SOX,
NOX, and HC1) as they are transported over these increasing scales of
time and distance.
On a local scale (0 to 20 km), field studies have generally
demonstrated the precipitation scavenging of sulfur and nitrogen oxides
from conventional utility and smelting sources to be minimal. The
virtual absence of excess nitrate or nitrite ion in precipitation
samples collected beneath such plumes (Dana et al. 1976) provides strong
evidence that direct uptake of primary nitric oxide and nitrogen dioxide
by precipitation and cloud elements is a negligibly slow process.
Nonreactive scavenging of plume-borne sulfur dioxide is solubility
dependent and tends also to be a rather inefficient process, although it
is definitely detectable in field studies conducted in relatively clean
6-37
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TABLE 6-2. SUMMARIES OF SOME PRECIPITATION SCAVENGING FIELD INVESTIGATIONS
General source type
Specific source type
Selected references
I
GO
00
Continuous Point
Source
Tower releases of aerosols
Tower releases of radioactive
gases and simulated tracers
Tower releases of S02
Tower releases of tritiated
water vapor
Tower releases of organic
vapors
Power-plant plumes
Smelter plumes
Chamberlain (1953), Engelmann (1965), Dana
(1970)
Chamberlain (1953), Engelmann (1965)
Dana et al. (1972), Hales et al. (1973)
Dana et al. (1978)
Lee and Hales (1974)
Dana et al. (1973, 1976, 1982), Granat and Rodhe
(1973), Granat and Soderlund (1975),
Hales et al. (1973), Barrie and Kovalick (1978),
Hutcheson and Hall (1974), Enger and
Hogstrom (1979), Radke et al. (1978)
Kramer (1973), Larson et al. (1975)
Mil Ian et al. (1982), Chan et al. (1982)
"Instantaneous" and/ Aircraft releases of rare-
or Moving Sources earth tracers
Dingle et al. (1969), SI inn (1973), Young et al.
(1976), Gatza (1977), Changnon et al. (1981)
Rocket releases of radioactive Shopauskas et al. (1969), Burtsev et al. (1976),
tracers
-------
TABLE 6-2. CONTINUED
General Source Type
Specific Source Type
Selected References
Urban Sources
General and Regional
Sources
I
CO
Uppsalla, Sweden
St. Louis, MO
Los Angeles, CA
Regional pollution flowing
into lake-effect storms
General sources in western
Canada
Regional pollution in the
eastern U.S. and Canada
Regional aerosol loadings at
a specific receptor point
Hostrom (1974)
Hales and Dana (1979a)
Morgan and Liljestrand (1980)
Scott (1981)
Summers and Hi tenon (1973)
MAP3S/RAINE (1981), Easter (1982), Mosaic (1979)
Graedel and Franey (1977), Davenport and Peters
(1978)
Global and Strato- Cosmogenic radionuclides
spheric Sources
Nuclear fallout
Young et al. (1973)
Numerous studies; see Fuquay (1970)
aThe reference by Gatz provides a comprehensive list of past tracer studies of precipitation
scavenging.
-------
environments (Hales et al. 1973; Dana et al. 1973, 1976). This
phenomenon, which is suppressed under conditions involving high rain
acidity, is relatively well understood at present (Hales 1977, Drewes
and Hales 1982).
Nonreactive scavenging of sulfate aerosol can be an efficient
removal process. The preponderance of relevant field tests in Table
6-2, however, have demonstrated that wet deposition of sulfate from
local power-plant and smelter plumes occurs rather slowly. This is
undoubtedly a consequence of the small amounts of primary sulfate
available for scavenging under such circumstances.
Field tests conducted under situations wherein sulfur trioxide was
intentionally injected into the stack of a coal-fired power plant (Dana
and Glover 1975) show correspondingly high sulfate scavenging rates, and
it has been suggested that under certain operating conditions some types
of power plants (especially oil-fired units) will produce sufficient
primary sulfate to account for appreciable local deposition. To date,
however, no really strong field evidence has supported this point.
Hogstrom (1974) reported the observation of substantial sulfate
scavenging from the local plume of an oil-fired power plant in Sweden,
but these results are rather dependent upon the interpretation of
background contributions. Granat and Soderlund (1975) performed a
similar investigation in the vicinity of a second Swedish oil-fired
plant and found a comparatively small scavenging rate.
Reactive scavenging of plume-borne sulfur dioxide to form rainborne
sulfate is difficult to differentiate from primary sulfate removal. The
previously noted findings of low excess sulfate in below-plume rain
samples, however, suggest that neither process is particularly effective
in near-source plume depletion.
The scavenging of hydrochloric acid to produce chloride and
hydrogen ions in precipitation will most certainly be a highly effective
process, depending upon the quantities of hydrochloric acid available.
Considerable theoretical and laboratory work has been conducted in this
area for space-shuttle impact assessment, and limited data suggest that
hydrogen chloride is scavenged in measureable amounts from power-plant
plumes (Dana et al. 1982).
With the exception of studies conducted under rather clean ambient
conditions (e.g., Dana et al. 1973, 1976), the influence of background
contributions has made the interpretation of plume scavenging a
difficult task. Typically the sulfate and nitrate concentations in
precipitation collected adjacent to the plume are quite variable, and
subtracting this influence to determine source contributions involves
substantial levels of uncertainty. This difficulty of "source
attribution" at the local scale is compounded appreciably as greater
scales of time and distance are considered.
6-40
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On a more intermediate scale (0 to 200 km) an enhancement of
sulfate and nitrate precipitation-scavenging seems to occur, presumably
because the precursors have had more opportunity to dilute and to react
under these circumstances. Hogstrom (1974), using an extended network
of samplers in the vicinity of Uppsala, Sweden, reported substantial
scavenging rates of sulfur compounds. Hales and Dana (1979a) have
observed summertime convective storms to remove appreciable fractions of
urban NOX and SOX burdens in the vicinity of St. Louis, MO.
Although both of these studies were subject to the usual uncertainties
with regard to background contributions there is little doubt about
their general conclusions of significant scavenging under such
circumstances.
On a regional scale (0 to 2000 km) relatively few data come from
intensive field experiments. Precipitation-chemistry network data are
of some use in this regard, however, and several analyses have applied
these measurements to specific ends. One result of these analyses is
the suggestion that, in the northeastern quadrant of the United States,
roughly one third of the emitted NOX and SOX are removed by wet
processes (Galloway and Whelpdale 1980). Network data for the Northeast
(MAP3S/RAINE 1982) show also that the molar wet delivery rates of
NOX and SOX are roughly equivalent. Combining this result with
regional emission inventories suggests that nitrogen compounds begin to
wet deposit with a significantly enhanced efficiency as distance scales
become regional in extent.
The above changes in behavior with increasing scale seem to be a
logical consequence of current understanding regarding the atmospheric
chemistry of SOX and NOX. On local scales neither is scavenged very
effectively owing to the chemical makeup of the primary emissions. On
intermediate scales both groups have had some opportunity to react into
more readily scavengable substances. Depending upon ambient conditions,
nitrogen oxides will have participated to some extent in initial
photolysis reactions and proceeded to form scavengable products such as
nitric acid, peroxyacetyl nitrate, and nitrate aerosol. Sulfur dioxide
also will have reacted homogeneously to a limited extent; more
importantly, however, this compound will have been diluted to levels
where limited reactants (and possibly catalysts) win facilitate
its oxidation in the aqueous phase. On a regional scale this
progression continues with the relative acceleration of NOx
scavenging.
Present field-study indications that NOX scavenging may occur
primarily through the attachment of gas-phase reaction products, while
the scavenging of SOX may depend much more heavily upon aqueous-phase
oxidation processes, are also reflected in precipitation-chemistry data.
A possible consequence of this difference in mechanisms is illustrated
in Figure 6-15, which is a time-series of daily precipitation-chemistry
6-41
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150
100
50
TOTAL SULFUR
'
AV- .7X*»* y\'
:/-.A . *A'i .•/•A.
100
50
NITRATE
0 0.5 1.0 1.5 2.0 2.5
YEARS SINCE JULY 1976
3.0 3.5 4.0
Figure 6-15.
Sulfate and nitrate concentration data for event
precipitation samples collected at Penn State University,
PA. Lines are least-squares of linear and periodic
functions (MAP3S/RAINE 1982).
6-42
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measurements for a northeastern U.S. site. The decidedly periodic6
behavior of sulfate-ion concentrations has been suggested to occur as a
consequence of an aqueous-phase oxidation of sulfur dioxide, which
proceeds more rapidly during summer months. Whatever the cause, it is
readily apparent from this figure that scavenging mechanisms for these
two species differ appreciably.
An noted above, most past field experiments have have experienced
difficulty in resolving precisely which source(s) of pollution has been
responsible for material wet-deposited at sampled receptor sites, and
this problem is typically amplified as time and distance scales
increase. Source attribution is particularly uncertain on a regional
scale, and the basic data obtainable from standard precipitation-
chemistry networks are of little help in this regard. Combined with the
lack of data from well-designed regional field studies, this problem of
source attribution poses one of the most important and uncertain
questions facing the acidic deposition issue at present.
As a consequence of this need, a major regional field experiment
has recently been designed and conducted in the northeastern United
States (MAP3S/RAINE 1981, Easter 1982). Known as the Oxidation and
Scavenging Characteristics of April Rains (OSCAR) study, this field
experiment was based upon the concept of characterizing, as completely
as possible, the dynamic and chemical features of major cyclonic storm
systems as they traverse the continent. Specific objectives were:
1. To assess spatial and temporal variability of precipitation
chemistry in cyclonic storm systems, and to test the adequacy
of existing networks to characterize this variability;
2. To provide a comprehensive, high-resolution data base for
prognostic, regional deposition-model development; and
60ne should note in Figure 6-15 that the periodic functions are fit to
the total data, whereas the linear regressions are fit only for the
period January 1, 1977-December 31, 1979; thus the cyclic functions are
not exactly symmetric about the linear regression curves. Some idea of
statistical improvement in fit may be obtained using the expression
2 n2
r = p linear regression - q periodic fit
a2linear regression
where thea2's pertain to variances of the data points over the
three and one-half period. For sulfate in Figure 6-15 r2 equals
0.22, indicating a significant reduction in variance; the corresponding
r2 value for nitrate is 0.01, suggesting that no significant
annual periodicity exists in this case.
6-43
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3. To develop increased understanding of the transport, dynamic
and physiochemical mechanisms that combine to make up the
composite wet-removal process, and to identify source areas
responsible for deposition at receptor sites.
The data collected and assembled by the OSCAR project are summarixed in
Table 6-3. These are being made available to the general user community
in a computerized data base.
A general layout of the OSCAR precipitation-chemistry network is
shown 1n Figure 6-16. The points and triangles on this map represent
locations of sequential precipitation-chemistry stations on an
"intermediate-density" network; the open square overlapping Indiana and
Ohio depicts a concentrated network of 47 additional sites. Specific
design criteria for this configuration are discussed in the supporting
literature MAP3S/RAINE (1982).
The OSCAR data set is presently under intensive investigation, and
only preliminary results are currently available It is of interest to
consider some of these results at this point, however, to evaluate the
potential future utility of this material. One early result, presented
by Raynor (1981), is primarily of qualitative interest and involves the
first-sample--last-sample pH data obtained by the sequential rain
samplers for individual storms, typified by the plots shown in Figures
6-17 and 6-18. It is interesting to note that Figure 6-17 is strongly
reminiscent of annual- or multi-year-average plots for the northeastern
United States in the sense that it shows the familiar acid "core" region
centered upon Pennsylvania. The final-sample distribution in Figure
6-18 is quite different. Besides indicating a much cleaner sample set,
very little structure exists in this final distribution. This relative
cleanliness of late-storm precipitation is consistent with the general
OSCAR finding that most of the pollutant is scavenged comparatively
early in a storm's life cycle (Easter and Hales 1983a).
It should be noted in this context that field studies having higher
spatial resolution (e.g., Semonin 1976, Hales and Dana 1979b) indicate
that significant fine structure typically exists in spatial pH
distributions. Much of this fine structure can be expected to be hidden
within the relatively coarse sampling mesh shown in Figures 6-17 and
6-18.
Substantial source-receptor analysis is presently being conducted
in conjunction with the Indiana-Ohio concentrated network. One early
analysis, conducted for the April 22,24, 1981 storm is presented in
Figure 6-19. Back trajectories of this type are currently being
combined in diagnostic scavenging models with aircraft and surface data
to evaluate source-receptor relationships in greater detail (Easter and
Hales 1983a,b).
6-44
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TABLE 6-3. SUMMARY OF DATA COLLECTED FOR THE OSCAR DATA BASE
METEOROLOGICAL DATA
0 North American standard 12-hour upper air observations
(rawinsondes)
o OSCAR special rawinsonde data
° North American 3-hour standard surface observations
o North American hourly precipitation amount data
o Trajectory forecast data (Limited Fine Mesh and Global
Spectral Models)
Gridded forecast data (Limited Fine Mesh Model)
Satellite observations
PRECIPITATION-CHEMISTRY DATA
0 OSCAR network: Sequential measurements of rainfall,
field pH. lab pH, conductivity, NOa", N02~, $042-, S0s2-, Cl",
NH4+, Ca2+, Mg2+, K , Na*, A13+, po4x-, total Pb
0 Additional networks: Time-averaged data as available
from sources such as NADP, CANSAP, CCIW, and APN
° Special rainborne ^02 measurements
AIRCRAFT DATA
Trace gases: 03, NO/NOX, S02, HNOa, NH3
° Aerosol parameters: scattering coefficient (b^t). Aitken
nuclei, aerosol sulfur, sulfate size distribution, aerosol
size distribution, aerosol acidity
o Cloud water chemistry: N03", NO?", S042~, S0a2-, pH, NH4+,
conductivity, CT, Ca2+, Mg2+, K , Na+, total Pb.
0 Meteorological parameters: Temperature, humidity, liquid,
water content, wind speed and direction, cloud droplet size
distribution
0 Position parameters: Latitude, longitude, altitude, time
6-45
409-261 0-83-17
-------
TABLE 6-3. CONTINUED
SURFACE AIR CHEMISTRY DATA
OSCAR SAC site (Fort Wayne 40°49.8'N, 85°27.6'W): H202,
peroxyacetyl nitrate, sulfur aerosol size distribution, NH3,
S02, $042-, 03, NO/NOX, HNOs, aerosol composition
vs particle size, aerosol acidity
0 Selected air quality data from specific surface monitoring
sites throughout eastern North America
EMISSIONS
0 MAP3S/RAINE standard inventory
6-46
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CT>
. EXISTING
MAP3S SITES
SUPPLEMENTAL
REGIONAL SITES
'I | NE INDIANA GRID
r____
Figure 6-16. General layout of OSCAR sequential precipitation chemistry network, showing hypothetical
"design-basis" cyclonic system.
-------
CO
V
Figure 6-17. pH distribution for initial precipitation sampled during OSCAR storm of 22-24 April 1981.
-------
.£>
VO
1 T '4'5
Figure 6-18. pH distribution for final precipitation sampled during OSCAR storm of 22-24 April 1981.
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6.5 PREDICTIVE AND INTERPRETIVE MODELS OF SCAVENGING
6.5.1 Introduction
A precipitation-scavenging model can be defined as any
conceptualization of the Individual or composite processes of Figure
6-Z, In a manner which allows their expression In mathematical form.
Often such models take the form of submodels or "modules" within a
larger calculatlonal framework, such as a composite regional pollution
code. When considered 1n a modular sense the lines connecting the boxes
of Figure 6-2 can be considered as channels for Information exchange
within the overall framework, whereas the boxes (or clusters of boxes)
can be Identified with the modules, themselves. This modular
relationship Is described 1n somewhat more detail In Chapter A-9, where
composite regional models are discussed.
Scavenging models are currently rapidly evolving, and a profusion
of associated computer codes and computational formulae Is currently
available. Indeed, one of the major problems 1n precipitation-
scavenging assessment Is determining precisely which model to select
from the large number of available candidates. A major aim of the
present subsection 1s to guide the reader In this pursuit.
There are a number of potential uses for precipitation-scavenging
models, and the Intended use will to a large extent determine just which
model should be employed. Some of the more Important potential uses are
Itemized as follows:
0 Predicting the Impact on precipitation chemistry of proposed
new sources, source modifications, and alternate emission-
control strategies;
0 Predicting long-range precipitation chemistry trends;
0 Estimating relative contributions of specific sources to
precipitation chemistry at a chosen receptor point;
o Estimating transport of acidic precipitation precursors
across political borders;
0 Estimating and predicting a1r-qual1ty Improvements occurring
as a consequence of the scavenging process;
o Selecting sites for precipitation-chemistry network sampling
stations;
0 Designing field studies of precipitation scavenging; and
0 Elucidating mechanistic behavior of the scavenging process on
the basis of field measurements.
6-51
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In selecting an appropriate model, the user should review his
intended application carefully with regard to the pollutant materials of
interest, time and distance scales, processes covered in Figure 6-2,
source configuration, precipitation type, and the mechanistic detail
required. The question of pollutant materials is particularly important
when precipitation acidity is of interest. Acidity in precipitation is
determined by the presence of a multitude of chemical species, so in
principle one must compute (via a model) the scavenging of each species
and then estimate acidity on the basis of an ion balance:
[H+] = E Anions - ( I Cations other than H+). [6-1]
Inorganic ions usually important in precipitation chemistry are
itemized in Table 6-4. Organic species play a secondary role in the
acidification process, which appears to vary widely by region. Modeling
of all of these species simultaneously requires substantial effort, and
all "acidic-precipitation" models to date have focused upon only one or
just a few of the more important species, with contributions of the
others estimated empirically. Currently, newer models tend to
accommodate larger numbers of these species; but complete modeling
coverage of them will not be achieved in the foreseeable future.
Mechanistic detail is another important feature determining the
basic composition of a scavenging model. A comprehensive mathematical
description of the scavenging process can rapidly become overwhelming,
and there is usually a need to represent these relationships in a
comparatively simple, albeit approximate, manner. The process of
consolidating complex behavior in this fashion is often referred to as
lumping the system's parameters. The resulting simplified expressions
are termed parameterizations. Consolidating the effects of non-modeled
species in empirical form, described in the preceding paragraph, is one
example of lumping. Numerous other examples will arise throughout the
remainder of this section.
This section will not attempt to provide the reader with a detailed
treatise on how models should be formulated and applied.7 The
approach, rather, will be to develop a basic understanding of the
fundamental elements of a scavenging model and then to provide a
systematic procedure for choosing and locating appropriate models from
the literature. The following subsection discusses the basic
conservation equations, which constitute the conceptual bases for
7For the reader interested in more detailed pursuit of this area, the
works by Hales (1983) and Slinn (1983) are recommended. The Hales
reference is something of a beginner's primer, while SI inn's treatment
delves substantially deeper into mechanistic detail. Together they
constitute a reasonable starting point for understanding and modeling
basic scavenging phenomena.
6-52
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TABLE 6-4. SOME INORGANIC IONS IMPORTANT
IN PRECIPITATION CHEMISTRY3
Cations Anions
H+
NH4+ CT
Na+ N03~
K+ S032-
Ca2+ S042'
Mg2+ P043'
C032-
3A11 ions are presented here in their completely-
dissociated states. The reader should note, however,
that various states of partial dissociation are
possible as well (e.g., HS03", HC03~).
6-53
-------
scavenging models in general. This discussion is followed in turn by
two simple applications of these relationships, which are presented to
illustrate usage and to define some terms commonly used in scavenging
models. The final subsection attacks the problem of model selection,
using a flow-chart approach designed to guide the user to a valid choice
in a systematic manner that avoids many of the pitfalls normally
encountered on such endeavors.
6.5.2 Elements of a Scavenging Model
6.5.2.1 Material Balances—In Figure 6-3 the various arrows between
boxes correspond physically to streams of pollutant and/or water. From
this it is not difficult to realize that any characterization of this
system must include material balances, which form the underlying
structure for all scavenging models. To formulate a material balance,
one simply visualizes some chosen volume of atmosphere, summing overall
inputs and outputs of the substance in question.
Two basic types of material balance are possible:
1. "Microscopic" material balances, based upon summation over a
limiting small volume element of atmosphere; and
2. "Macroscopic" material balances, based upon summation over a
larger volume element of atmosphere (e.g., a complete storm
system).
Microscopic material balances invariably lead to differential equations,
which must be integrated over finite limits to obtain practical results.
Macroscopic balances result in mixed, integral, or algebraic, equations.
Again the choice of material-balance type depends upon the specific
modeling purpose at hand.
An important general form of the differential material balance for
a chosen pollutant (denoted by subscript A) is given by the equations
(cf., Hales 1983)
• WA + rAy (9as phase) [6-2]
ctt
and
^Equations 6-2 and 6-3 are quite general in the sense that the
velocity vectors denote velocity of pollutant (rather than that of the
bulk media) and thus provide for all modes of transport (convective,
diffusive, ...) without yet specifying how this transport is to occur.
These equations are not yet time-smoothed; thus, no closure assumptions
have been applied at this point.
6-54
-------
CAx= -V.CAX^AX + WA + rAx (aqueous phase). [6-3]
Here CA» and CAX denote concentrations of pollutant 1n the gaseous
and condensed-water phases, respectively. The time rate of change of
these concentrations within the differential volume element 1s related
to the sum of inputs by 1) flow through the walls of the element, 2)
Interphase transport between the gaseous and condensed phases, and 3)
chemical (and/or physical) reaction within the element. The ^
terms in Equations 6-2 and 6-3 denote velocity vectors, while v. 1s
the standard vector divergence operator. The interphase transport term
WA accounts for all "attachment" processes (impaction, phoresis,
diffusion, ...) as well as any reverse phenomena such as pollutant-gas
desorption, while the r terms denote chemical conversion rates in the
usual sense. To formulate a usable model from these equations, one
needs to specify values for the functions v, w, and r and then solve
differential Equations 6-2 and 6-3 (subject to appropriate Initial and
boundary conditions) to obtain the desired concentration fields
and CAX- A simple example of this procedure is given in Section
6.5.4.
6.5.2.2 Energy Balances—Many terms in Equations 6-2 and 6-3,
especially yAx,*A» and rAx, depend strongly upon the amount,
state, and interconversion rates of condensed water and it is important
to note that atmospheric water itself obeys material-balance expressions
of this form. In selecting a scavenging model, one often is confronted
with the problem of deciding whether to estimate precipitation
attributes and these related terms independently on the basis of
assumptions or previous information, or to attempt to compute the
desired entities directly by solving appropriate forms of Equations 6-2
and 6-3.
If the latter of these alternatives is chosen, then including an
energy-balance equation 1s mandatory. This need arises because the
evaporation-condensation process Influences, and is Influenced by, a
variety of energy-related considerations. These include temperature
influences on vapor pressure and latent-heat effects, which can be
incorporated in the model via an energy balance performed over the same
element of atmosphere as that of the associated material balances. In
microscopic form, a general expression of the energy balance (cf., Bird
et al. 1960), is
pv 3j_ = _ 7afj . pv.v + r _ D . [6-4]
3t
Here the time rate of change of temperature relates to the sum of inputs
by 1) flow through the walls of the element and 2) generation via a)
compression work, b) latent heat effects, and c) frictional dis-
sipation. The vector terms h and v denote sensible heat flux and fluid
velocity, respectively, while r and D pertain to latent heat and
6-55
-------
dissipation; P and Cy denote fluid density and specific heat in the
usual sense. A straightforward example of the incorporation of Equation
6-4 for scavenging modeling purposes is given by Hales (1982).
6.5.2.3 Momentum Balances—Solutions to Equations 6-2 to 6-4 depend
upon the existence of some previous description of fluid velocity v
(or VAV in the case of Equation 6-2). As was the case for the
preceding parameters associated with the energy balance, velocity may be
specified for the model on the basis of previous measurements or
assumptions. Flow patterns in storm systems may be sufficiently complex
to defy empirical specification, however, and the modeler may wish to
compute the associated fields on the basis of a modeling approach. If
this is to be done, a momentum-balance equation must be employed. In
microscopic form the general momentum balance may be expressed (cf.,
Bird et al. 1960) as
3pv = -v.pvv -vp - FV + Pg- [6-5]
"at"
Here the time rate of change of momentum (PV) is expressed as
the sum of inputs by 1) flow through the walls of the element, 2)
pressure forces, 3) viscous drag forces, and 4) gravitational forces.
To apply Equation 6-5 for modeling purposes, one specifies frictional,
pressure, and gravitational terms and solves the differential equation
subject to appropriate initial and boundary conditions to obtain fields
of the velocity vector v. An example applying Equation 6-5 for
scavenging modeling purposes is given by Hane (1978).
Incorporating energy and momentum balances, Equations 6-4 and 6-5,
into a scavenging model is a rather challenging exercise, and a
relatively small number of models that apply these equations for this
purpose exist. The usual tack is simply to "pre-specify" the required
parameters and proceed with material-balance calculations alone.
Numerous examples of both types of models will be presented in Section
6.5.5.
6.5.3 Definitions of Scavenging Parameters
Four key parameters often arise in the context of scavenging
models, and it is appropriate at this point to define these terms and
indicate their general application. Reference to these entities as
"parameters" is consistent with the usage applied in the previous
section, in that they serve to "lump" the effects of a number of
mechanistic processes in a simple formulation. These will be discussed
sequentially in the following paragraphs.
The first parameter to be defined is the attachment efficiency.
Also known as the capture efficiency, this term can be visualized most
easily by considering a hydrometeor falling through a volume of polluted
air space, as shown in Figure 6-20. This hydrometeor sweeps out a
6-56
-------
o
Figure 6-20.
Schematic of a scavenging hydrometeor falling through a
volume element.
6-57
-------
volume of air during its passage, and attachment efficiency is defined
as the amount of collected pollutant divided by the amount initially in
this volume. The efficiency can exceed 1.0 if pollutant from outside
the swept volume becomes attached to the drop.
From the discussion in Section 6.2.3, we know attachment efficiency
accounts for a multitude of processes. Usually the efficiency is less
than 1; but mechanisms such as diffusion, electrical effects, and
interception can give rise to larger values, especially when the
collecting element's fall velocity is small. Efficiencies can be
negative if the element is releasing pollutant to the surrounding
atmosphere, such as in the case of pollutant-gas desorption. Typical
efficiencies for aerosol particles collected by raindrops are shown in
Figure 6-4.
Another important parameter is the scavenging coefficient. This
entity is basically an expression of the law of mass action, defined by
the form
_ [6-6]
_
CAy
where (in a manner consistent with Equations 6-2 and 6-3) w/^ is the
rate of depletion of pollutant A from the gaseous phase by attachment to
the aqueous phase in a differential volume element. This is similar to
a rate of expression for a first-order, irreversible chemical reaction,
and as such it applies strictly only to irreversible attachment
processes (e.g., aerosols or highly-soluble gases). A can be related
to the attachment efficiency E by the form (which assumes spherical
hydrometeors)
A(a) = - 7rNT A2vz(R)E(R,a)fR(R)dR , [6-7]
0
where a and R denote aerosol and hydrometeor radii, respectively; vz
is the hydrometeor fall velocity; and NT and fR are the total number
and probability-density functions for the size-distributed hydrometeors
residing in the volume element of Figure 6-20 at any instant in time.
From this, one can note that A essentially extends the parameteriza-
tion over the total spectra of hydrometeor sizes.
Atmospheric aerosol particles are typically distributed over
extensive size ranges. Because of this it is often desirable to possess
some sort of an effective scavenging coefficient, which represents a
weighted average over the aerosol size spectrum. Figure 6-21 presents a
family of curves corresponding to such averages, which are based upon
assumed log-normal particle-size spectra, with different geometric
standard deviations. From these curves one can observe that for the
same geometric mean particle size, changes in spread of the size
distribution can result in dramatic changes in the effective scavenging
coefficient.
6-58
-------
10
i
FRONTAL RAIN SPECTRUM
Computed effective scavenging coefficients for size-distributed aerosols. Based on a log-
normal aerosol radius distribution with geometric means and standard deviations a and a .
A typical frontal-rain dropsize spectrum is assumed. Adapted from Dana and Hales9(1976).
-------
Including reversible attachment processes in a scavenging model
usually involves using the mass-transfer coefficient. This parameter can
be defined in terms of the flux of pollutant moving from the scavenging
element as
Flux = - . (cAy - h'cA) . [6-8]
Here Ky is the mass-transfer coefficient and 6A is the concentration,
within the scavenging element, of collected pollutant; h1 is essentially a
solubility coefficient which, when multiplied by cA, produces a
gas-phase equilibrium value, c is the molar concentration of air
molecules, which appears in Equation 6-8 because of the manner in which
has been defined. Thus, the flux can be either to the drop or away
rom it, depending upon the relative magnitude of the parenthetical
terms. Equation 6-8 can be integrated over all drop sizes in a manner
similar to that used in Equation 6-7 (cf., Hales 1972), to form the
following expression for WA:
WA = _l!±L_ /°VfR(R)Ky(R) (cAy-h' CA) dR
The final scavenging parameter to be described here is the
scavenging ratio. This entity is usually the result of a model
calculation, rather than an input, and is defined by the form
C,
5 = JL [6-10]
cAy
where CA is the concentration of pollutant contained in a
collected precipitation sample. 5 is a term immediately usable for a
number of pragmatic purposes, because once its numerical value is known,
it can be applied directly to compute precipitation-chemistry
concentrations on the basis of air-quality measurements. Tables of
measured (Engelmann 1971) and model -predicted (Scott 1978) scavenging
washout ratios have been published, although caution is advised in the
application of these values. A simple example of scavenging-ratio
application is given in the following section.
It is useful for the sake of visualization to discuss briefly the
qualitative features of the scavenging parameters noted above. The
parameter E is easy to visualize in the context of Figure 6-20; it is,
simply, the collection efficiency of an individual cloud or
precipitation element and as such should be expected to fall numerically
in the approximate range between zero and one. The scavenging
coefficient A can be visualized as a first-order removal rate, in much
the same manner as that of a first-order reaction-rate coefficient. As
such it may be used roughly as a characteristic time scale for wet
6-60
-------
removal. A= 1 hr-1, for example, would imply that the scavenging
process will cleanse 100 (1-1/e) percent of the pollutant in one hour if
conditions remain constant and competitive processes do not occur. From
this one can note that 1 hr-1 is a moderately large scavenging
coefficient. A's ranging from zero to 1 hr-i and beyond have been
reported in the literature (Figure 6-21).
The mass-transfer coefficient Ky is essentially a normalized
interfacial flux of pollutant between the atmosphere and an individual
droplet. Little needs to be said here regarding magnitudes of Ky,
except to note that a variety of different definitions of Ky exist,
and one must be congnizant of these definitions when employing values
obtained from outside sources. The washout ratio, ?, is essentially a
measure of the concentrating power of precipitation in its extraction of
pollutant from the atmosphere. As will be noted in the next section,
precipitation often has the ability to concentrate airborne pollution by
a factor of a million or more. S's ranging from below 100 up through
ID** and higher have been reported in the literature.
The expected magnitudes and uncertainty levels associated with the
scavenging parameters listed in this section depend strongly upon the
substance being scavenged and the environment in which the scavenging
takes place. Large aerosol particles in below-cloud environments, for
example, are characterized by scavenging efficiencies in the range of
1.0 {Figure 6-4), which can be estimated with relatively high precision.
Smaller particles, especially those in the "Greenfield-Gap" region are
much more difficult to simulate, and associated errors in estimated
efficiencies may approach an order of magnitude or more. Errors in
these efficiency estimates will of course be compounded by uncertainties
in raindrop size spectra, if extended to scavenging coefficients via
Equation 6-7. In the case of gases, the mass-transfer coefficient
usually can be estimated to within a factor of two or less; again this
error can be expected to compound when integrated over assumed raindrop
size-spectra.
In the case of in-cloud scavenging of aerosols our capability for
estimating transport parameters is seriously impeded, owing to the
profusion of mechanisms and the complex environments involved. Typical
uncertainties in both A and 5 can be expected to approach an order
of magnitude in some cases. Some appreciation for the factors
influencing in-cloud scavenging coefficients can be obtained from the
work of SI inn (1977), who attempts to evaluate theoretical,
"storm-averaged" values for A. An idea of the magnitudes and
uncertainties of 5 is given in Figure 6-23.
In all cases involving reactive gases, the values of E, A, and
£ are heavily contingent upon the aqueous-phase chemical processes
involved. Much remains to be accomplished in our understanding of
aqueous-phase chemistry before a meaningful assessment of associated
uncertainties is possible.
6-61
-------
As a final note in this context it should be emphasized that
uncertainties in scavenging parameters dictate uncertainties in
scavenging calculations in a complex fashion, and that errors associated
with the microscopic phenomena can be either amplified or attenuated by
their applications in macroscopic models to produce practical results.
Uncertainties associated with macroscopic modeling applications will be
discussed at some length in a later section.
6.5.4 Formulation of Scavenging Models: Simple Examples of Microscopic
and Macroscopic Approaches'
As noted previously, the description given in this document will
refrain in general from deriving and applying scavenging models
explicitly. This is too broad and complex a subject to be discussed in
detail here, and the reader is referred to the previously-cited
literature for more detailed pursuit of this subject. For purposes of
illustration, however, it is worthwhile to consider two very simple
examples of scavenging-model formulations that demonstrate the
microscopic and macroscopic approaches to the problem. The present
subsection is addressed to this task.
The microscopic material balance approach will be considered first.
For this example, it is useful to visualize an idealized situation where
rain of known characteristics is falling through a stagnant volume of
atmosphere that contains a well-mixed, nonreactive pollutant with
concentration CAy The air velocity Is known (v=0), so solution of
the momentum equation (Equation 6-5) is not required. The raindrop size
distribution is presumed to remain constant; thus, evaporation-
condensation and other energy- related effects are immaterial, and the
energy equation (Equation 6-4) may be disregarded.
Because the pollutant 1s well-mixed, no concentration gradients
occur; thus, the divergence term 1n Equation 6-2 is zero. Because of
nonreactlvity the reaction term Is zero as well.
Now presume that the pollutant is an aerosol, whose attachment can
be characterized in terms of the known scavenging coefficient A, using
Equation 6-6. The corresponding reduced form of Equation 6-2 1s, then,
= - A cAy . [6-2a]
at
Given some initial pollutant concentration CAyo» Equation 6-2a can be
integrated to obtain the form
CAy (t) = CAyo exp (-At), [6-11]
which expresses the decrease of the gas-phase pollutant concentration
with time. Counterpart expressions for rainborne concentrations may be
derived by subjecting Equation 6-3 to a similar treatment.
6-62
-------
The reader is cautioned to consider this treatment as an example
only and to recognize that actual atmospheric conditions seldom conform
to the idealizations invoked above. Gas-phase concentrations are
usually not uniformly distributed in space, raindrop characteristics are
usually not invariant with time and wind fields are usually not well
characterized by v=0. A is usually not a time-independent
constant, and many pollutants are usually not well characterized by the
washout coefficient approximation. The pollutant often is not
unreactive. Examples of existing models where these constraints are
relaxed in various ways are presented in the following subsection.
Figure 6-22 illustrates the formulation of a macroscopic type of
scavenging model. Here, in contrast to the differential -element
approach, the material balances are formulated around a large volume
element, in this case a total storm. If one denotes concentrations and
flow rates of water and pollutant as follows
CAy = airborne concentration of pollutant
H = airborne concentration of water vapor into cloud
CA = concentration of scavenged pollutant in rainwater
w = density of condensed water
w-jn = flow rate of water vapor into the storm
wout = fl°w rate °f water vapor out of the storm
fjn = flow rate of pollutant into the storm
fout = flow rate °f pollutant out of the storm
W = flow rate of precipitation out of the storm
F = flow rate of scavenged pollutant out of the storm,
then extraction efficiencies for water vapor and pollutant can be
defined, respectively, as
£P = W [6-12]
and e = . [6-13]
nn
If one further performs material balances over this storm system for
pollutant and water vapor, and then combines the two, the following form
is obtained:
5=fA = epPw [6-14]
cAy "FFT
where the scavenging ratio, £ , is as defined earlier in Section 6.5.3.
6-63
-------
CONDENSATION,
PRECIPITATION FORMATION,
POLLUTANT ATTACHMENT
FLOW RATE OF WATER VAPOR OUT = w
FLOW RATE OF POLLUTANT OUT = fQut
x^
/v
FLOW RATE OF WATER VAPOR IN = w,.
FLOW RATE OF POLLUTANT ... -1n
^IBHI
3OR IN = win\ \\V\\MV\^V\\\v
riN = f.n \m\\A
FLOW RATE OF PRECIPITATION OUT = W
FLOW RATE OF SCAVENGED POLLUTANT OUT = F
DEFINITIONS OF EFFICIENCIES:
WATER REMOVAL
E_ «
POLLUTANT REMOVAL
Figure 6-22. Schematic of a typical macroscopic material balance.
6-64
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Equation 6-14 is an important result in the sense that it
demonstrates once again the strong linkage between water-extraction and
pollutant-scavenging processes. If both occur with equal efficiency^
(ep = e ) for example, then
5 -fj -10-5 „ 10-6- [6-151
Experimentally-measured scavenging ratios often fall in this range,
although wide variability often may be observed.
Using a rather involved series of arguments pertaining to
cloud-physics processes and attachment mechanisms, Scott (1978) has
created a family of curves expressing scavenging ratio as a function of
precipitation rate. Shown in Figure 6-23, curves 1, 2, and 3 pertain
respectively to convective storms, nonconvective warm-rain process
storms, and cold storms where the Bergeron-Findeisen process is active.
A major assumption in Scott's analysis is that storms ingest
pollutants in the form of aerosol particles that are active as cloud
condensation nuclei. The analysis also assumes a steady-state storm
system and complete vertical mixing of pollutant between the storm
height and the surface. Under such conditions Scott's curves can be
considered reasonably good estimators of actual scavenging behavior.
More elaborate systems, involving reactive pollutants, gases, and
homogeneous systems, are discussed in references given in the following
section.
6.5.5 Systematic Selection of Scavenging Models: A Flow-Chart
Approach
Hales (1983) has suggested a flow-chart approach to aid in
selecting a scavenging-model. Presented with a decision tree in Figure
6-24, the user proceeds by answering a series of questions that relate
to the model's intended use, the temporal and geographical scales, the
pollutant characteristics, the choice between macroscopic and micro-
scopic material balances, and the type of conservation (i.e., material,
energy, momentum) equations involved. Various pathways through this
decision tree are discussed in the original reference.
^There is no direct reason to expect that ep should be similar to
ein magnitude. In the absurd circumstance where all the pollutants
were concentrated into one particle, for example, then scavenging of
that pollutant by a very light rainfgall would yield e=1.0»ep.
Conversely a large storm processing an insoluble gaseous pollutant
(SFs, say) would provide e=0« p. For practical conditions involving
acid-forming aerosols, however, the scavenging of vapor and water
pollutant appears to be sufficiently related to allow en^eto be
employed as an approximate rule-of-thumb.
6-65
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99-9
to
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SCAVENGING RATIO (VOLUME BASIS) (5)
°oo
i i r \ 1111 j
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m
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-------
PRECIPITATION
CHARACTERISTICS
AND
CONCENTRATION
FIFID
PRECIPITATION
CHARACTERISTICS ,
/AND CONCENTRATION^
FIELD OR
SOURCE STRENGTH
PRECIPITATION
CHARACTERISTICS
AND
CONCENTRATION
FIELD
PLUME MODEL
COMPUTE GASEOUS-
ANO AQUEOUS-PHASE
CONCENTRATIONS
1
PRECIPITATION /
CHARACTERISTICS /
NO CONCENTRATION/
I ELD OR SOURCE /
STRENGTH /
COMPUTE WASHOUT
COEFFICIENTS
'
PARAMATERIALIZE
AEROSOL SIZE
DISTRIBUTION
J
J~
IS CONDENSE
OF WATER
PRIMARY AE*
SIGNIFICAI
|NO
COMPUTE SI
01STRIBUTIO
SECONDARY Al
TION
ON
OSOL
-------
Proceeding through Figure 6-24 in this manner, the user can arrive
at simple or complex end points, depending upon the nature of his
particular application. A trivial example is pathway 1-5-6, which
instructs the user to disregard modeling and rely solely upon past
measurements. The simple microscopic-balance example of Section 6.5.4
can be traced through pathway 1-2-7-8-21-23-15-16.
Table 6-5 itemizes some currently-available models, which can be
related directly to the pathways of Figure 6-24. This provides the
reader with a rapid and efficient means of access to current modeling
literature, while minimizing the chance of pitfall encounters that can
arise from the inadvertent use of inappropriate physical constraints.
For a more definitive description of this model selection process, the
reader is referred to Hales' original reference.
6.6 PRACTICAL ASPECTS OF SCAVENGING MODELS: UNCERTAINTY LEVELS AND
SOURCES OF ERROR
Quantitatively assessing the predictive capability of present
wet-removal models is a complex task, well beyond the scope of this
document. There are, however, a number of general statements that are
highly useful for focusing in on this question and for providing
insights pertaining to model reliability. These are itemized
sequentially below.
o The predictive capability of a scavenging model is strongly
contingent upon its desired application.
As noted in 6.5.1, a variety of different applications exist for
scavenging models, and some are much more difficult to fulfill than
others. One can, for example, employ existing regional models to
reproduce distributions of annually-averaged, wet-deposited,
sulfate ion in eastern North America with moderate success. If 9ne
is charged with the task of relating specific sources to deposition
at a chosen receptor site, however, our predictive capability can
be expected to be relatively imprecise. Similarly, if one is
expected to forecast the change in deposition that would occur in
response to some future change in emissions, then the associated
uncertainty level would be very high indeed. The question of
nonlinear response is of paramount importance in this last
application.
A large component of our uncertainty in predicting source
attribution and transient response is based simply on the fact that
we do not have adequate data bases for testing model perf9rmance
for these applications. Our present models may in actuality be
better predictors in this respect than anticipated, but because we
have no immediate way of confirming this, our uncertainty level
remains high (Section 6.4).
6-68
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TABLE 6-5. PERTINENT LITERATURE REFERENCES FOR WET-REMOVAL MODELS
Model
Type of Balance
Equation! s)
Mechanism(s)
Typical Application
Pertinent References
en
i
cr>
1. Classical Washout
Coefficient
2. Distributed Washout
Coefficient
3. "Two-Stage" Nuclca-
tion-Accretion
Nonreactive Gas
Scavenging
Reactive Gas
Scavenging
6. In-Cloud Aerosol
Scavenging
7. In-Cloud Aerosol
Scavenging
8. In-Cloud Reactive
Gas and Aerosol
Scavenging
9. In-Cloud Reactive
Gas and Aerosol
Scavenging
Material
(Differential)
Material
(Differential)
Material
(Differential)
Material
(Differential)
Material
(Differential)
Material
(Differential)
Irreversible Attachment
Irreversible Attachment
Irreversible Attachment
Reversible Attachment
Reversible Attachment
with Aqueous-Phase
Reaction
Irreversible Attachment
Material (Integral) Irreversible or
Reversible Attachment
Below-cloud scavenging
of aerosols and reactive
gases
Below-cloud scavenging of
size-distributed aerosols
Condensation-enhanced
below-cloud scavenging of
aerosols
Below-cloud scavenging of
nonreactive gases
Below-cloud scavenging of
reactive gases
Scavenging in storm systems
(nonreactive)
Scavenging in storm systems
Material
(Differential)
Material (Integral)
Transport, Reaction and Scoping studies
Deposition
Irreversible or
Reversible Attachment
with Chemical Reaction
Interpretation of field
study data
Chamberlain (1953), Engelmann (1968), Fisher
(1975), Scriven and Fisher (1975), Wangen and
Williams (1978)
Dana and Hales (1976), SI inn (1983)
Radke et al. (1978), Slinn (1983)
Hales et al. (1973, 1979), Slinn (1974b),
Barrle (1978)
Hill and Adamowicz (1977), Adamowicz (1979),
Overton et al. (1979), Durham et al. (1981),
Drewes and Hales (1982)
Junge (1963), Dingle and Lee (1973), Storebo
and Dingle (1974), Klett (1977), Lange and Knox
(1977), Slinn (1983)
Engelmann (1971), Gatz (1972), Scott (1978),
Hales and Dana (1979a), Slinn (1983)
Gravenhorst et al. (1978), Omstedt and Rodhe
(1978)
Scott (1982)
-------
TABLE 6-5. CONTINUED
Model
Type of Balance
Equation! s)
Mechanlsm(s)
Typical Application
Pertinent References
10. Composite Analytical
Material Transport, Reaction and Regional scale deposition
(Differential) Deposition
Astarlta et al. (1979), Fay and Rosenzwelg
(1980)
11. Composite Trajectory Material
(Differential)
en
i 12. Composite Grid
~-j
o
13. Composite
Statistical
14. Nonreactive
15. Reactive
Material
(Differential)
Material
Transport, Reaction and Regional scale deposition
Deposition
Transport, Reaction and Regional scale deposition
Deposition
Transport, Reaction and Scoping studies and
Deposition life-time assessment
Material Energy and Irreversible Attachment, In-cln"<1 scavenging analysis
Momentum Honreactive
(Differential)
Material and Energy All modes of scavenging In-cloud scavenging analysis
(Differential) Including chemical
reaction
Bolln and Persson (1975), Hales (1977),
Ellassen (1978), Fisher (1975), Bass (1980),
Heffter (1980), Henml (1980), Sampson (1980),
Bhumralkar et al. (1980), Klelnman et al.
(1980), Shannon (1981), McNaughton et al.
(1981) Patterson et al. (1981); Voldner (1982)
Liu and Durran (1977), Prahm and Christensen
(1977), W1lken1ng and Ragland (1980), Lavery
(1980), Lee (1981), Carmichael and Peters
(1981), Lamb (1981)
Rodhe and Grandell (1972, 1981)
Molenkamp (1974), Hane (1978), Kreltzburg and
Leach (1978)
Hales (1982)
-------
Regardless of the above considerations it should be emphasized
strongly that the first step in scavenging model evaluation must be
the precise definition of the intended uses of the model. All
subsequent efforts will be confounded in the absence of this focal
point.
The predictive capability of a scavenging model depends upon the
choice of model .
At first sight this appears to be a self-evident and trivial
statement. A profusion of scavenging models exist, however, and it
is not at all difficult to choose an inappropriate candidate
inadvertently. Such inappropriate selections have on occasion
resulted in reported calculations that have been in error by
several orders of magnitude (Section 6.5.1).
This component of error may of course be totally eliminated by
selecting the most appropriate model for the intended application.
The flow chart presented in Figure 6-24 is a useful guide for this
purpose, especially for those only casually familiar with the
field.
The predictive capability of a scavenging model depends strongly
upon the processes model ecT
As noted in the context of Figure 6-2 a scavenging model may
encompass one, several, or all of the steps in the composite
wet-removal sequence. If only a small portion of this sequence is
being considered, the model depends heavily upon information
supplied from the remaining components. This information may
originate from assumptions, from empirical measurements, or from
the output of other models. Assuming that all input information is
error-free, then it may be stated generally that the more steps in
Figure 6-2 encompassed by a given model, the greater will be its
predictive uncertainty. This is simply a consequence of
propagating errors and must be considered as a primary factor when
one addresses the validation of wet-removal calculations.
The predictive capability of a scavenging model depends upon its
areal range.
This statement is largely a corollary of the one immediately above.
As a scavenging model is extended to, say, a regional scale it is
forced to include essentially all of the components of Figure 6-2.
As noted previously, this is likely to increase uncertainty levels
appreciably.
The predictive capability of a scavenging model is contingent upon
its temporal averaging
Owing to the propensity of stochastic phenomena to average out to
mean values, the predictive capabilities of (especially regional)
6-71
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scavenging models can be expected to improve somewhat as averaging
times increase (see Chapter A-9). This improvement is, of course,
gained at the expense of sacrificing temporal resolution, and a
value judgment is necessary (again requiring a precise definition
of intended model application) at this juncture.10
This observation should be tempered by the fact that, in addition
to random errors, scavenging models can be expected to possess
substantial systematic biases. In general these biases do not
decrease with averaging time and in fact many lead to cumulative
discrepancies on occasion. Examples of systematic errors are
biases in trajectory calculations and artificial offsets induced by
the superimposition of random events on nonlinear processes.
Again the seriousness of such factors is heavily contingent on the
intended model application (Section 6.5.1).
In general summary, it may be stated that several important factors
lead to widely varying levels of uncertainty in scavenging-model
predictions. One may predict, for example, the scavenging of $03
from a local power-plant plume by using existing models and expect
to match measured results within a factor of two. On the other
hand, similar predictions of, ,say, the fraction of sulfate at a
given receptor and originated from some particular source can be
expected to have orders-of-magnitude associated uncertainty. Both
a comprehensive model-evaluation effort and a substantially-
improved data base will be required before this situation can be
remedied to any appreciable extent (Section 6.4).
6.7 CONCLUSIONS
This chapter has provided an overview of meteorological processes
contributing to wet removal of pollutants and has sumamrized the current
state of our capability to describe these complex phenomena in
mathematical form. Because of the magnitude of this problem, it has
been necessary to refrain from detailed descriptions of models and
modeling techniques; rather, we have chosen to describe the general
mathematical basis for wet-removal modeling, to give two simple examples
of direct application, and then to supply the reader with a means for
efficiently pursuing the available literature for specific applications
of interest.
In conclusion to this discussion it is appropriate to summarize the
state of these calculational techniques by asking the following
questions:
*°This Issue is especially pertinent in view of the contention, often
voiced by some scientists within the acid-precipitation effects
community, that temporally-averaged results (averaging times of a few
months or more) are totally adequate for assessment purposes.
6-72
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0 Just how accurate and valid are current wet-removal modeling
techniques as predictions of precipitation chemistry and wet
deposition; that is, how well do they fulfill the needs
itemized in Section 6.5.1?
o What must be accomplished before the present capabilities can
be improved?
The answers to these questions are somewhat mixed. Certainly the
techniques discussed in this section, if used appropriately, are capable
of order-of-magnitude determinations in many circumstances; and under
restricted conditions they can even generate predictions having factor-
of-two accuracy or better. Moreover, there is ample explanation in
existing theories of wet removal to account easily for the spatial and
temporal variabilities observed in nature.
These capabilities, however, cannot be considered to be very satis-
factory in the context of current needs. The noted ability to explain
spatial and temporal variability on a semi quantitative basis has not
resulted in a large competence in predicting such variability in
specific instances. Moreover, we possess very little competence in
identifying specific sources responsible for wet deposition at a given
receptor site. Finally, the order-of-magnitude predictive capability
noted above hardly can be judged satisfactory for most assessment
purposes.
In reviewing the discussions of this section against the backdrop
of these deficits, several research needs become apparent. The most
important of these are itemized in the following paragraphs:
0 Much more definitive information is needed with regard to the
scavenging efficiencies of submicron aerosols, for both rain
and snow. Especially important in this regard is the effect
of condensational growth of such aerosols in below-cloud
environments (Section 6.5.3).
0 We need to know much more about aqueous-phase conversion
processes, which are potentially important as alternate
mechanisms resulting in the presence of species such as
sulfate and nitrate in precipitation. Since virtually nothing
is known presently regarding the chemical formation of such
species in clouds and precipitation, there is a tendency to
lump these effects with physical removal processes in most
modeling efforts, expressing them in terms of pseudo
scavenging coefficients or collection efficiencies. Such
phenomena must be resolved in finer mechanistic detail than
this before a satisfactory treatment is possible, and this
requires a knowledge of chemical transformation processes that
is much more advanced than exists at present (Sections 6.2.4
and 6.5.3 and Chapter A-4).
6-73
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0 Much more extensive understanding of the competitive
nucleation capability of aerosols In in-cloud environments Is
needed, especially for those substances that do not compete
particularly well In the nucleatlon process. The Influence of
aerosol-particle composition—especially for "Internally-
mixed" aerosols (those containing individual particles
composed of mixed chemical species)—is particularly important
in this regard (Section 6.2).
» Identifying specific sources responsible for chemical
deposition at a given receptor location requires that we
possess a much more accomplished capability to describe
long-range pollution transport. Progress in this area during
recent years has been encouraging, but much more remains to be
achieved before we are sufficiently proficient for reliable
source-receptor analysis (Section 6.4).
o We still need to enhance our understanding of the detailed
microphyslcal and dynamic processes that occur in storm
systems. Besides providing required knowledge of basic
physical phenomena, such research is important in providing
valid parameterizations of wet-removal for subsequent use in
composite regional models (Section 6.4).
As a final note, it is useful to reflect once again on the fact
that scavenging modeling research—as treated in this chapter—has been
in a rather continuous state of development over the past 30 years.
While progress has been indeed significant during this period, a number
of important and unsolved problems still exist. Accordingly, one must
use this perspective in assessing our rate of advancement during future
years. Reasonable progress in resolving the above items can be expected
over the next decade; but the complexity of these problems demands that
a serious and sustained effort be applied for this purpose.
6-74
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scavenging of aerosol particles. Proc. Cloud Physics and Atmospheric
Electricity. American Met. Soc., Boston, MA.
Raynor, G. S. 1981. Design and preliminary results of the intermediate
density precipitation-chemistry experiment. Report BNL 29992. For
presentation at Third Joint AMS/APCA Conference on Applications of Air
Pollution Meteorology, January. San Antonia, TX.
Rodhe, H. and J. Grandell. 1972. On the removal time of aerosol
particles from the atmosphere by precipitation scavenging. Tell us
24:442-454.
Rodhe, H. and J. Grandell. 1981. Estimates of characteristic times for
precipitation scavenging. J. Atm. Sci. 38:370-386.
Saffman, P. G. and J. S. Turner. 1955. On the collision of drops in
turbulent clouds. J. Fluid Mech. 1:16-30.
Sampson, P. J. 1980. Trajectory analysis of summertime sulfate
concentrations in the northeastern United States. J. Appl. Met.
19:1382-1394.
Scott, B. C. 1978. Parameterization of sulfate removal by
precipitation. J. Appl. Met. 17:1375-1389.
Scott, B. C. 1981. Sulfate washout ratios in winter storms. J. Appl.
Met. 20:619-625.
6-82
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Scott, B. C. 1982. Predictions of in-clpud conversion rates of S02
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Scott, B. C. and N. S. Laulainen. 1979. On the concentration of
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Scriven, R. A. and B. E. A. Fisher. 1975. The long range transport of
airborne material and its removal by deposition and washout. Atmos.
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Semonin, R. G. 1976. The variability of pH in convective storms.
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Shannon, J. 1981. A regional model of long-term average sulfur
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Shopauskas, K., B. Styra, and E. Verba. 1969. Spreading and rainout of
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Slinn, W. G. N. 1973. In-cloud scavenging studies. Annual Report to
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6-83
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6-84
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THE ACIDIC DEPOSITION PHENOMENON AND ITS EFFECTS
A-7. DRY DEPOSITION PROCESSES
(B. B. Hicks)
7.1 INTRODUCTION
The presence of acidic and acidifying substances in the atmosphere
is a result of natural and anthropogenic emissions, atmospheric
transformations, and transport. Receptors are exposed to these
substances through wet deposition discussed in the previous chapter.
These substances also impact on various receptors in the form of dry
depositions. This chapter addresses many of the questions associated
with the dry deposition phenomenon.
The acidic and acidifying substances associated with dry deposition
include the gases, S02, NOx, HC1, and NH3 and the particulate
aerosols of sulfate, nitrate, and ammonium salts. Some of the questions
addressed are: How does dry deposition differ from wet deposition? How
is dry deposition measured in the field, in the laboratory? What
modeling techniques are available currently for predicting dry
deposition for specified atmospheric concentrations and other
controlling factors? The important issues addressed begin with the
identification of the various chemical, physical, and biological factors
that play an important role in the processes controlling the rate of dry
deposition as a function of time and space. These take into account the
aerodynamics near receptor surfaces, boundary layer effects, and other
receptor surface phenomena.
The following chapter of the document discusses monitoring of dry
and wet deposition. Wet deposition network data are analyzed and
interpreted so as to provide maps of the U.S. and Canada with sampling
site locations, median concentration data for specified sampling periods
for sulfates, nitrates, ammonium ion, calcium, chloride, and pH.
7.2 FACTORS AFFECTING DRY DEPOSITION
7.2.1 Introduction
The rate of pollutant transfer between the air and exposed surfaces
is controlled by a wide range of chemical, physical, and biological
factors which vary in their relative importance according to the nature
of the surface, the characteristics of the pollutant, and the state of
the atmosphere. The complexity of the individual processes involved and
the variety of possible interactions between them combine to prohibit
easy generalization; nevertheless, a "deposition velocity", v
-------
Particles larger than about 20 vm diameter will be deposited at a
rate controlled by Stokes1 law, although with some enhancement due to
inertial impaction of particles transported near the surface in
turbulent eddies. The settling of submicron particles in air is
sufficiently slow that turbulent transfer tends to dominate, but the net
flux is often limited by the presence of a quasi-laminar layer adjacent
to the surface, which presents a considerable barrier to all mass fluxes
and especially to gases with very low molecular diffusivity. The
concept of a gravitational settling velocity is inappropriate in the
case of gases, but transfer is still often limited by diffusive
properties very near the receptor surface. The case of particles
between 1 and 20 ym diameter is especially complicated, because all of
these various mechanisms are likely to be important.
Sehmel (1980a) presents a tabulation of factors known to influence
the rate of pollutant deposition upon exposed surfaces. Figure 7-1 has
been constructed on the basis of SehmeVs list and has been organized to
emphasize the greatly dissimilar processes affecting the fluxes of gases
and large particles. Small, sub-micron particles are affected by all of
the factors indicated in the diagram; thus, simplification is especially
difficult for deposition of such particles. In reality, Figure 7-1
already represents a considerable simplification, since it omits many
potentially important factors. In particular, the diagram emphasizes
properties of the medium containing the pollutants in question; a
similarly complicated diagram could be constructed to illustrate the
effects of pollutant characteristics. For particles, critical factors
include size, shape, mass, and wettability; for gases, concern is with
molecular weight and polarization, solubility, and chemical reactivity.
In this context, the acidity of a pollutant that is being transferred to
some receptor surface by dry processes is an especially important
quality that may have a strong impact on the efficiency of the
deposition process itself.
Figure 7-2 summarizes particle size distributions on a number,
surface area, and volume basis. In this way, the three major modes are
brought clearly to attention. The number distribution emphasizes the
transient (or Aitken) nuclei range, 0.005 to 0.05 urn diameter, for
which diffusion plays a role in controlling deposition. The area
distribution draws attention to the so-called accumulation size range
formed largely from gaseous precursors (0.05 to 2 ym diameter,
affected by both diffusion and gravity). The remaining mode (2 to 50
ym diameter, most evident in the volume distribution) is the
mechanically generated particle range for which gravity causes most of
the deposition. In most literature, the 2 ym diameter is used as a
convenient boundary between "fine" and "coarse" particles.
As discussed in Chapter A-5, atmospheric sulfates, nitrates, and
ammonium compounds are primarily associated with the accumulation size
range. Figure 7-3 demonstrates that very little acidic or acidifying
material is likely to be associated with the coarse particle fraction in
background conditions. However, the larger particles include
soil-derived minerals, some of which can react chemically with airborne
7-2
-------
AIRBORNE SOURCE
LARGE
PARTICLES
GASES
AERODYNAMIC
FACTORS 1
NEAR-SURFACE
PHORETIC
EFFECTS
QUASI-LAMINAR
LAYER
FACTORS
SETTLING
I
TURBULENCE
THERMOPHORESIS
I
ELECTROPHORESIS
DIFFUSIOPHORESIS
-, mr4
and
STEFAN FLOW
IMPACTION
i
INTERCEPTION
BROWNIAN DIFFUSION
1
IMCll C
rlULt
1
TURBULENCE
STEFAN FLOW
CULAR DIFFUSION
SURFACE
PROPERTIES
IFLEXIBILITYI | WAX i NESS
|STOMATA| | WETNESS j
i
CHEMISTRY |
SMOOTHNESS | { VESTITURE
j EMISSIONS
MOTION] | EXUDATESI
RECEPTOR
Figure 7-1. A schematic representation of processes likely to influence
the rate of dry deposition of airborne gases and particles.
Note that some factors affect both gaseous and particulate
transfer, whereas others do not.
7-3
-------
15
X
CO
10
0.001
(a)
0.01
0.1 1
DIAMETER (yin)
Figure 7-2. Diagrammatic representations of aerosol size distributions
according to number concentration (a), surface area (b),
and volume (c). Data are for typical urban area. Adapted
from Whitby (1978).
7-4
-------
01
E
a.
a
en
o
3
-------
and deposited acids. Moreover, it has been suggested that some of these
larger particles may provide sites for the catalytic oxidation of sulfur
dioxide (e.g., when the particles are carbon; Cofer et al. 1981; Chang
et al. 1981). Little is known about the detailed chemical composition
of large particle agglomerates. However it is accepted that their
residence time is quite short (i.e., they are deposited relatively
rapidly), that there are substantial spatial and temporal variations in
both their concentrations and their composition, and that their
contribution to dry acidic deposition should not be ignored.
To evaluate deposition rates, several different approaches are
possible. Average deposition rates can be deduced from field
experiments that monitor changes over time in some system of receptors.
More intensive experiments can measure the deposition of particular
pollutants in some circumstances. Neither approach is capable of
monitoring the long-term, spatial-average dry deposition of pollutants.
To understand why, we must first consider in some detail the processes
that influence pollutant fluxes and then relate these considerations to
measurement and modeling techniques currently being advocated. The
logical sequence illustrated in Figure 7-1 will be used to guide these
discussions.
7.2.2 Aerodynamic Factors
Except for the obvious difference that particles will settle slowly
under the influence of gravity, small particles and trace gases behave
similarly in the air. Trace gases are an integral part of the gas
mixture that constitutes air and, thus, will be moved with all of the
turbulent motions that normally transport heat, momentum, and water
vapor. However, particles have finite inertia and can fail to respond
to rapid turbulent fluctuations. Table 7-1 lists some relevant
characteristics of spherical particles in air (based on data tabulated
by Fuchs 1964, Davies 1966, and Friedlander 1977). The time scales of
most turbulent motions in the air are considerably greater than the
inertia! relaxation (or stopping) times listed in the table. These time
scales vary with height, but even as close as 1 cm from a smooth, flat
surface, most turbulence energy will be associated with time scales
longer than 0.01 seconds, so that even 100 pm diameter particles would
follow most turbulent fluctuations. However, natural surfaces are
normally neither smooth nor flat, and it is clear that in many
circumstances the flux of particles will be limited by their inability
to respond to rapid air motions.
Naturally-occurring aerosol particles are not always spherical,
although it seems reasonable to assume they are in the case of
hygroscopic particles in the submicron size range. Chamberlain (1975)
documents the ratio of the terminal velocity of non-spherical particles
to that of spherical particles with the same volume. In all cases, the
non-spherical particles have a lower terminal settling speed than do
equivalent spheres. The settling speed ratio is indicated by a
"dynamical shape factor," a, as listed in Table 7-2.
7-6
-------
TABLE 7-1. DYNAMIC CHARACTERISTICS OF UNIT DENSITY AEROSOL
PARTICLES AT STANDARD TEMPERATURE AND PRESSURE,
CORRECTED FOR STOKES-CUNNINGHAM EFFECTS
DATA ARE FROM FUCHS 1964, DAVIES 1966, FRIEDLANDER 1977.
Particle Radius
(ym)
Diffusivity
(cm2 s-1)
Stopping Time
(s)
Settling Speed
(cm s"1)
0.001 1.28 x 10'^ 1.33 x 10"^ 1.30 x 10"^
0.002 3.23 x 10"^ 2.67 x 10"^ 2.62 x 10"?
0.005 5.24 x 10"; 6.76 x 10"^ 6.62 x 10~°
0.01 1.35 x 10"? 1.40 x 10"° 1.37 x 10~j?
0.02 3.59 x 10~l 2.97 x 10"° 2.91 x 10"^
0.05 6.82 x 10~£ 8.81 x 10"° 8.63 x 10"J
0.1 2.21 x 10"° 2.28 x 10"; 2.23 x 10"^
0.2 8.32 x 10"; 6.87 x 10"' 6.73 x 10~5
0.5 2.74 x 10"; 3.54 x 10"° 3.47 x 10",
1.0 1.27 x 10"' 1.31 x 10"^ 1.28 x 10"^
2.0 6.10 x ID"" 5.03 x 10"J 4.93 x 10"f
5.0 2.38 x 10'° 3.08 x 10"J 3.02 x 10"1
10.0 1.38 x 10"b 1.23 x 10"J 1.20 x 10U
7-7
-------
TABLE 7-2. DYNAMIC SHAPE FACTORS, a, BY WHICH NON-SPHERICAL PARTICLES
FALL MORE SLOWLY THAN SPHERICAL PARTICLES (CHAMBERLAIN 1975)
Shape Ratio of axes
Ellipsoid 4 1.28
Cylinder 1 1.06
Cylinder ? 1.14
Cylinder 3 1.24
Cylinder 4 1.32
Two spheres touching, vertically 2 1.10
Two spheres touching, horizontally 2 1.17
Three spheres touching, as triangle - 1.20
Three spheres touching, in line 3 1.34-1.40
Four spheres touching, in line 4 1.56-1.58
7-8
-------
Thus, trace gases and small particles are carried by atmospheric
turbulence as if they were integral components of the air itself,
whereas large particles are also affected by gravitational settling
which causes them to fall through the turbulent eddies. In general,
however, the distribution of pollutants in the lower atmosphere is
governed by the dynamic structure of the atmosphere as much as by
pollutant properties.
In daytime, the lower atmosphere is usually well mixed up to a
height typically in the range 1 to 2 km, as a consequence of convection
associated with surface heating by insolation. Pollutants residing
anywhere within this mixed layer are effectively available for
deposition through the many possible mechanisms. Atmospheric transfer
does not usually limit the rate of delivery of pollutants to the surface
boundary layer in which direct deposition processes are active.
However, at night, the lower atmosphere may become stably stratified and
vertical transfer of non-sedimenting material can be so slow that, at
times, pollutants at heights as low as 50 to 100 m are isolated from
surface deposition processes.
The fine details of turbulent transport of pollutants remain
somewhat contentious. Notable among the areas of disagreement is the
question of flux-gradient relationships in the surface boundary layer.
It is now well accepted that the eddy diffusivity of sensible heat and
water vapor exceeds that for momentum in unstable (i.e., daytime) but
not in stable conditions over fairly smooth surfaces (see Dyer 1974, for
example). However, it is not clear that the well-accepted relations
governing heat or momentum transfer are fully applicable to particles or
trace gases; some disagreement exists even in the case of water vapor.
The situation is even more uncertain in circumstances other than over
large expanses of horizontally uniform pasture. When vegetation is
tall, pollutant sinks are distributed throughout the canopy so that
close similarity with the transfer of any more familiar quantity such as
heat or momentum is effectively lost. There is even considerable
uncertainty about how to interpret profiles of temperature, humidity,
and velocity above forests (Garratt 1978, Hicks et al. 1979, Raupach et
al. 1979).
7.2.3 The Quasi-Laminar Layer
In the immediate vicinity of any receptor surface, a number of
factors associated with molecular diffusivity and inertia of pollutants
become important. Large particles carried by turbulence can be impacted
on the surface as they fail to respond to rapid velocity changes. The
physics of this process is similar to that of sampling by inertial
collection.
Inertial impaction is a process that augments gravitational
settling for particles in the size range typically between 2 and 20 ym
(SI inn 1976b). Larger particles tend to bounce, and capture is
therefore less efficient, while smaller particles experience difficulty
7-9
-------
In penetrating the quasi-laminar layer that envelops many receptor
surfaces. Figures 7-2 and 7-3 show that many air-borne materials exist
In the size range likely to be affected by Inertlal impaction. However,
from the viewpoint of acidic particles, Inertia! Impactlon may not be
Important to dry deposition because most acidic species are associated
with particles (see Figure 7-2) which are not strongly affected by this
process. But, because many of the chemical constituents of soil-derived
particles are capable of neutralizing deposited acids, inertial
impaction may have important indirect effects upon acidic deposition.
To illustrate the role of molecular or Brownian diffusivity, it is
informative to consider the simple ideal case of a knife-edged thin
smooth plate, mounted horizontally and with edge normal to the wind
vector. As air passes over (and under) the plate, a laminar layer
develops, of thickness <5 = c(vx/ul/2, where v is kinematic
viscosity, x is the downwind distance from the edge of the plate, and u
is wind speed. According to Batchelor (1967), the value of the numerical
constant c is 1.72. Thus, for a 5 cm plate in a wind speed of 1 m
s~l, we should imagine a boundary layer thickness reaching about 1.5
mm thick at the trailing edge.
Over non-ideal surfaces, the internal viscous boundary layer is
frequently neither laminar nor constant with time. The layer generates
slowly as a consequence of viscosity and surface drag as air moves
across a surface. The Reynolds number Re ( = ux/v, where u is the
wind speed, x is the downwind dimension of the obstacle, and v is
kinematic viscosity) is an index of the likelihood that a truly laminar
layer will occur. For large Re, air adjacent to the surface remains
turbulent: viscosity is then incapable of exerting its influence. In
many cases, it seems that the surface layer is intermittently turbulent.
For these reasons, and because close similarity between ideal surfaces
studied in wind tunnels and natural surfaces is rather difficult to
swallow, the term "quasi-laminar layer" is preferred.
Wind-tunnel studies of the transfer of particles to the walls of
pipes tend to support the concept of a limiting diffusive layer adjacent
to smooth receptor surfaces. Transfer across such a laminar layer is
conveniently formulated in terms of the Schmidt number, Sc = v/D, where
v is viscosity and D is the pollutant diffusivity. The conductance, or
transfer velocity, vj_, across the quasi-laminar layer is proportional
to the friction velocity u*:
vx = Au* Sca [7-1]
where A and a are determined experimentally. Most studies agree that
the exponent a is about -2/3, as is evident in the experimental data
represented in Figure 7-4. However, a survey by Brutsaert (1975a)
indicates exponents ranging from -0.4 to -0.8. The value of the
constant A is also uncertain. The line drawn through the data of Figure
7-4 corresponds to A = 0.06, yet the wind-water tunnel results of
Moller and Schumann (1970) appear to require A - 0.6. These values
7-10
-------
10~F I—i i i i i IN
- • '
i I I I I II
1 I I I MM
O
10
-4
4
LEGEND
O HARRIOT and HAMILTON (1965)
A HUBBARD and LIGHTFOOT (1966)
• MIZUSHINA et al. (1971)
10
-5
J I I I I Mi
J I I I I I II
J I I I I III
10*
10'
Figure 7-4. Laboratory verification of Schmidt-number scaling for
particle transfer to a smooth surface. The quantity plotted
is BEVd/u*, evaluated for transfer across a quasi-laminar
layer of molecular diffusion immediately adjacent to a smooth
surface. Data are reported by Lewellen and Sheng (1980).
The line drawn through the data is Equation 7-1, with
exponent a = -2/3 and constant of proportionality A = 0.06.
7-11
-------
span the value of A - 0.2 recommended for the case of sulfur dioxide
flux to fibrous, vegetated surfaces (Shepherd 1974, Wesely and Hicks
1977).
Laminar boundary layer theory imposes the expectation that particle
deposition to exposed surfaces will be strongly influenced by the size
of the particle, with smaller particles being more readily deposited by
diffusion than larger. It is clear that many artificial surfaces or
structures made of mineral material will have characteristics for which
the laminar-layer theories might be quite appropriate. However the
relevance to vegetation can be questioned. Microscale surface roughness
elements can penetrate the barrier presented by this quasi-laminar layer
and should be suspected as sites for enhanced deposition of both
particles and gases (Chamberlain 1967). Figure 7-5 is a photograph of
the surface of a mature corn leaf (Zea mays), showing the dense blanket
of leaf hairs, or trichomes, which covers the surface. These hairs are
easily visible to the naked eye and provide an obvious example of a case
in which the limiting transfer characteristics of the quasi-laminar
layer next to the surface might not be a critical issue.
7.2.4 Phoretic Effects and Stefan Flow
Particles near a hot surface encounter a force that tends to drive
them away from the surface. Thermophoresis depends on the local
temperature gradient in the air, on the thermal properties of the
particle, on the Knudsen number Kn = A/r (where x is the mean
free path of air molecules, and r is the radius of the particle), and on
the nature of the interaction between the particle and air molecules
(see Derjaguin and Yalamov, 1972). For very small particles (< 0.03
urn diameter, according to Davies 1967), this "thermophoresis" can be
visualized as the consequence of hotter, more energetic air molecules
impacting the side of the particle facing the hot surface. As a "rule
of thumb", the thermophorectic velocity of very small particles (< 0.03
viti diameter) is likely to be about 0.03 cm s~l (estimated from
values quoted by Davies 1967). For larger particles, radiometric forces
become important (Cadle, 1966). In theory, thermal radiation can cause
temperature gradients across particles that are not good thermal
conductors, resulting in a mean motion of the particle away from a hot
surface. For particles exceeding 1 ym diameter, the velocity will be
about four times less.
Diffusiophoresis results when particles reside in a mixture of
intermixing gases. In most natural circumstances, the principle concern
is with water vapor. Close to an evaporating surface, a particle will
be impacted by more water molecules on the nearer side. Because these
water molecules are lighter than air molecules, there will be a net
"diffusiophoresis" towards the evaporating surface.
Diffusiophoresis and thermophoresis both depend on the size and
shape of the particle of interest and hence, neither can be predicted
with precision, nor can safe generalizations be made. These subjects
are sufficiently complicated that they constitute specialities in their
7-12
-------
Figure 7-5. A photograph of a leaf of common field corn (Zea mays) , highlighting
the leaf hairs that potentially provide a mechanism for partially
circumventing the otherwise limiting quasi-laminar layer in contact
with the surface. (Photgraph by R. L. Hart, Argonne National Laboratory)
7-13
-------
own right. Excellent discussions have been given by Friedlander (1977)
and Twomey (1977). These phoretic forces are generally snail, and their
influence on dry deposition can usually be disregarded.
Many workers include Stefan flow in general discussion of
diffusiophoresis, but because of the conceptual difference between the
mechanisms involved it is of current relevance to consider them
separately. Stefan flow results from the injection into the gaseous
medium of new gas molecules at an evaporating or subliming surface.
Every gram-molecule of substrate material that becomes a gas displaces
22.41 liters of air, at STP. Thus, for example, a Stefan flow velocity
of 22.41 mm s"1 will result when 18 g of water evaporates from a 1
m2 area every second. Generalization to other temperatures and
pressures is straightforward. Daytime evaporation rates from natural
vegetation often exceed 0.2 g nr2 s'1 for considerable times during
the midday period, resulting in Stefan flow of more than 0.2 mm s~r
away from the surface. Detailed calculation for specific circumstances
is quite simple. For the present, it is sufficient to note that Stefan
flow is capable of modifying surface deposition rates by an amount that
is larger than the deposition velocity appropriate for many small
particles to aerodynamically smooth surfaces.
Electrical forces have often been mentioned as possible mechanisms
for promoting deposition (as well as retention; see Section 7.1.5) of
small particles, particularly through the "viscous" quasi-laminar layer
immediately above receptor surfaces. Wason et al. (1973) report
exceedingly high rates of deposition of particles in the size range 0.6
to 6 ym to the walls of pipes when a space charge is present.
Chamberlain (1960) demonstrated the importance of electrostatic forces
in modifying deposition velocities of small particles, when fields are
sufficiently high. Plates charged to produce local field strengths of
more than 2000 V cm~l, experienced considerably more deposition of
small particles than uncharged plates, by factors between 2 and 15.
However, in fair-weather conditions, field strengths are typically less
than 10 V cnr1, so the net effect on particle transfer is likely to be
small. Further studies of the ability of electrostatic forces to assist
the transfer of partial!ate pollutants to vegetative surfaces were
conducted by Langer (1965) and Rosinski and Nagomoto (1965). According
to Hidy (1973), a series of experiments was conducted using single
conifer needles and conifer trees. "For single needles or leaves,
electrical charges on - 2 ym-diameter ZnS dust with up to eight
units of charge had no detectable effect at wind speeds of 1.2 to 1.6 m
s~l. The average collection efficiency was found to be ~ 6 percent
for edgewise cedar or fir needles, with broadside values an order of
magnitude lower. Bounce-off after striking the collector was not
detected, but reentrainment could take place above ~ 2 m s-1 wind
speed. Tests on branches of cedar and fir by Rosinski and Nagamoto
(1965) suggested similar results as for single needles." It should be
noted, however, that the electrical mobility of a particle is a strong
negative function of particle size, ranging from 2 cm s~* per V cm"1
of field strength for 0.001 ym-diameter particles, to 0.0003 cm s-1
per V cm-1 for 0.1 ym particles (Davies 1967).
7-14
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7.2.5 Surface Adhesion
Most workers assume pollutants that contact a surface will be
captured by it. For some gases, this assumption is clearly adequate.
For example, nitric acid vapor is sufficiently reactive that most
surfaces should act as nearly perfect sinks. Less reactive chemicals
will be less efficiently captured. The case of particles is of special
interest, however, because of the possibility of bounce and
resuspension.
The role of electrostatic attraction in binding deposited particles
to substrate surfaces remains something of a mystery. The process by
which particles become charged and set up mirror-charges on the
underlying surface is fairly well accepted. For smaller particles, the
principle charging mechanism is thermal diffusion, leading to a Boltzman
charge distribution. The resulting van der Waals forces are often
mentioned as the major mechanism for binding particles once they are
deposited. For large, non-spherical particles, dipole moments can be
set up in natural electric fields and can help promote the adhesion at
surfaces. These matters have been conveniently summarized by Billings
and Gussman (1976), who provide mathematical relationships for
evaluating the electrical energy of a particle on the basis of its size,
shape, dielectric constant, and the strength of the surrounding
electrical field.
Condensation of water reduces the effectiveness of electrostatic
adhesion forces, since leakage paths are then set up and charge
differentials are diminished. However, the presence of liquid films at
the interfaces between particles and surfaces causes a capillary
adhesive force that compensates for the loss of electrostatic
attraction. These "liquid-bridge" forces are most effective in high
humidities, and for coarse particles (> 20 ym, according to Corn,
1961).
Billings and Gussman (1976) draw attention to the effect of
microscale surface roughness in promoting adhesion of particles to
surfaces. Much of the experimental evidence is for particle diameters
much greater than the height of surface irregularities (e.g., Bowden and
Tabor 1950). It is the opposite case that is likely to be of greater
interest in the present context, as will be discussed later.
7.2.6 Surface Biological Effects
The efficiency with which natural surfaces "capture" impacting
particles or molecules will be influenced considerably by the chemical
composition of the surface as well as its physical structure. The "lead
candle" technique for detecting atmospheric sulfur dioxide is an
historically interesting example of how chemical substrates can be
selected to affect the deposition rates of particular pollutants.
Uptake rates of many trace gases by vegetation are controlled by
biological factors such as stomatal resistance. In daytime, this is
7-15
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known to be the case for sulfur dioxide (Spedding 1969, Shepherd 1974,
Wesely and Hicks 1977) and for ozone in most situations (Wesely et al.
1978). The similarity between sulfur and ozone is not complete,
however, because the presence of liquid water on the foliage will tend
to promote S02 deposition, and to impede uptake of ozone; the former
gas is quite soluble until the solution becomes too acidic, whereas the
latter is essentially insoluble (Brimblecombe 1978).
The role of leaf pubescence in the capture of particles has
received considerable attention. Chamberlain (1967) tested the roles of
leaf stickiness and hairiness in his wind-tunnel tests. He concluded
that "with the large particles (32 and 19 ym) the velocity of
deposition to the sticky artificial grass was greater than to the real
grass, but with those of 5 ym and less, it was the other way round,
thus confirming . . . that hairiness is more important than stickiness
for the capture of the smaller particles." The importance of leaf hairs
appears to be verified by studies of the uptake of 21°Pb and 2l°Po
particles by tobacco leaves (Martell 1974, Fleischer and Parungo 1974),
and by the wind tunnel work of Wedding et al. (1975), who report
increases by a factor of 10 in deposition rates for particles to
pubescent leaves compared with smooth, waxy leaves. It remains to be
seen how greatly biological factors of this kind influence the rates of
deposition of airborne particles to other kinds of vegetation.
7.2.7 Deposition to Liquid Water Surfaces
Trace gas and aerosol deposition on open water surfaces is of
considerable practical interest, especially considering concern with the
acidification of poorly buffered inland waters. Air blowing from land
across a coastline will slowly equilibrate with the new surface at a
rate strongly dependent on the stability regime involved. If the water
is much warmer than upwind land, dynamic instability over the water will
cause relatively rapid adjustment of the air to its new lower boundary,
but if the water is cooler, stratified flow will occur and adjustment
will be very slow. In the former (unstable) case, dry deposition rates
of all soluble or chemically reactive pollutants are likely to be much
higher than in the latter. Clearly, air blowing over small lakes will
be less likely to adjust to the water surface than will air blowing over
larger water bodies. Thus, during much of the summer, inland water
surfaces will tend to be cooler than the air, and hence may be protected
from dry deposition, because of the strongly stable stratification that
will then prevail. This phenomenon will occur more frequently over
small water bodies than larger ones (Hess and Hicks 1975).
Following the guidance of chemical engineering gas-transfer
studies, workers such as Kanwisher (1963), Liss (1973), and Liss and
Slater (1974), have considered the role of Henry's law constant and
chemical reactivity in controlling the rate of trace gas exchange
between the atmosphere and the ocean. In general, acidic and acidifying
species like S02 are readily removed upon contact with a water
surface. Thus, Hicks and Liss (1976) neglected liquid-phase resistance
and derived net deposition velocities appropriate for the exchange of
7-16
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reactive gases across the air-sea interface. The work of Hicks and Liss
is intended to apply to water bodies of sufficient size that the bulk
exchange relationships of air-sea interaction research are applicable.
Their considerations indicate that deposition velocities for highly
soluble and chemically reactive gases such as NH3, HC1, and $03 are
likely to be between 0.10 percent and 0.15 percent of the wind speed
measured at 10 m height. The analysis leading to this conclusion
assumes that the molecular and eddy diffusivities can be combined by
simple addition. This assumption has been shown to approximate the
transfer of water vapor and sensible heat from water surfaces. However,
for fluxes of trace gases, Deacon (1977) and SI inn et al. (1978) argue
that it is better to introduce molecular diffusivity through a term
analogous to the Schmidt (or Prandtl) number of Equation 7-1, with the
exponent a - -2/3. (In contrast, the linear assumption used by Hicks
and Liss implies a = -1.0). Hasse and Liss (1980) discuss the matter
from the viewpoint of surface-film behavior, with emphasis on the role
of capillary waves. In view of the uncertainties mentioned in
discussion of Equation 7-1, further comment on the implications and
ramifications of these alternative assumptions is not warranted.
In the limiting case of a trace gas of low solubility, the
deposition velocity is determined by the large liquid-phase resistance,
which is directly influenced by the Henry's law constant.
It is probable that breaking waves will modify the simple gas
transfer formulation derived from chemical engineering pipe-flow and
wind-tunnel work. It is not clear to what extent such features account
for the apparent discrepancy between the various Schmidt number
dependencies of the kind expressed by Equation 7-1. However, the
fractional power laws are basically extensions of laboratory work,
whereas the unit-power, additive-diffusivities result is an
approximation to field data. It is to be hoped that the two approaches
produce results that will converge in due course.
Wind tunnel results such as shown in Figure 7-6, indicate
exceedingly low deposition velocites to water surfaces for particles in
the size range of most acidic pollutants. As in the case of gas
exchange, there are conceptual difficulties in extending these results
to the open ocean. The role of waves in the transfer of small particles
between the atmosphere and water surfaces remains essentially unknown.
Not only does engulfment by breaking waves provide an alternative path
across the quasi-laminar sublayer where molecular (or Brownian)
diffusion normally controls the transfer, but also waves are a source of
droplets which can scavenge particulate material from the air [see,
however, the study of Alexander (1967) which indicates otherwise]. Hicks
and Williams (1979) have proposed a simple model of air-sea particle
exchange that extends smooth-surface, wind- and water-tunnel results (as
in Figure 7-6) to natural circumstances, by permitting rapid transfer to
occur whenever waves break. This results in very low deposition
velocities in light winds, but rapidly increasing velocities when winds
increase above about 5 m s-1. SI inn and SI inn (1980) also suggest
that particle transfer is more rapid than the wind-tunnel studies of
7-17
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Figure 7-6 might indicate, but they present an alternative hypothesis
for this more rapid transfer: that hygroscopic particles grow rapidly
when exposed to high humidities such as are found in air adjacent to a
water surface, resulting in increased gravitational settling and
impaction to the water surface.
7.2.8 Deposition to Mineral and Metal Surfaces
Acidic deposition is an obvious source of worry to architects,
historians and others concerned with the potentially accelerated
deterioration of structures (see Chapter E-7). Many popular building
materials react chemically with acidic air pollutants, generating new
chemical species that can contribute directly to the decay process even
if they are rapidly and efficiently washed off by precipitation.
Furthermore, in some cases the chemical product causes a visual
degradation that cannot be easily rectified, such as the blackening of
metal work exposed to hydrogen sulfide. Livingston and Baer (1983)
summarize the various mechanisms involved, and relate them to the
formulations that have been developed in laboratory studies.
The presence of water at the surface is known to be a key factor in
promoting the fracturing and erosion of stone. Water penetrates pores
and cracks and causes mechanical stresses both by freezing and by
hydration and subsequent crystallization of salts (see Winkler and
Wilhelm 1970, Fassina 1978, Gauri 1978). The earlier discussion of
surface effects that influence dry deposition indicated that surface
scratches and fractures will cause accelerated dry deposition rates in
localized areas. Moreover, phoretic effects are likely to be more
important than in the case of foliage (because dry surfaces exhibit
wider temperature extremes than moist vegetation). Stefan flow
associated with dewfall is also probably more important than for
vegetation. Some of the more important considerations can be summarized
as follows (after Hicks 1982):
1. Particle fluxes will tend to be greatest to the coolest parts
of exposed surfaces.
2. Both particle and gas fluxes will be increased when
condensation is taking place at the surface, and decreased when
evaporation occurs.
3. If the surface is wet, impinging particles will have a better
chance of adhering, and soluble trace gases will be more
readily "captured."
4. The chemical nature of the surface is important; if reaction
rates with deposited pollutants are rapid, then surfaces can
act as nearly perfect sinks.
5. Biological factors can influence uptake rates, by modifying the
ability of the surface to capture and bind pollutants.
7-19
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6. The texture of the surface is Important. Rough surfaces will
provide better deposition substrates than smoother surfaces,
and will permit easier transport of pollutants across the
near-surface quasi-laminar layer.
7. Microscale surface roughness features probably result in
greater deposition velocities for aerosols, due to disruption
of the quasi-laminar layer that normally limits transfer of
particles to aerodynamically smooth surfaces.
The importance of these factors is emphasized by the results of
corrosion tests conducted during the 1960's at 57 sites of the National
Air Sampling Network (see Haynie and Upham 1974). The data indicate a
nonlinear time dependence, such that the build-up of corrosion tends to
reduce the rate of further deposition of the trace gases and aerosols
causing the corrosion. Correlation analyses indicate significant
effects of surface moisture, similar to what is outlined above, but no
support is provided for the expectation that deposition rates will
generally be greater to colder parts of exposed surfaces. Statistical
analyses of the kind used by Haynie and Upham provide excellent
information on the general features of corrosion of exposed metal
surfaces, but generally fail to yield clear-cut evidence as to which
processes are controlling the deposition that causes the corrosion. The
subject of damage to materials surfaces is dealt with elsewhere in this
document (Chapter E-7).
7.2.9 Fog and Dewfall
The processes that cause aerosol particles to nucleate, coalesce,
and grow into cloud droplets are precisely the same as those which
assist in the generation of fog. Whenever surface air supersaturates,
fog droplets form on whatever hygroscopic nuclei are available. These
small droplets slowly settle onto exposed surfaces, or are deposited by
interception and impaction. The characteristics of the liquid that is
deposited are much the same as those of cloud liquid water (see Chapter
A-6).
Low-altitude surface fogs form under conditions of strong
stratification in which vertical turbulent transport is minimized. The
frequency of fogs varies widely with location and with time of year.
The depth is also highly variable. However, it must be assumed that
fogs constitute a mechanism whereby the lower atmosphere (say the bottom
hundred meters or so) can be cleansed of particulate and some gaseous
pollutants.
At higher elevations, fog droplets are precisely the same as the
cloud droplets that in other circumstances would grow and finally
precipitate in substantially diluted form. The importance of cloud
droplet interception has recently been demonstrated by Lovett et al.
(1982), at an altitude of 1200 m in New Hampshire. Most of the net
deposition of acidic species is by cloud droplet interception.
7-20
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The presence of liquid water on exposed surfaces helps promote the
deposition of soluble gases and wettable particles. This surface water
arises through the action of several mechanisms other than the direct
effect of precipitation. Some plants exude fluid from foliage, usually
at the tips of leaves, by a process known as guttation. Moisture can
evaporate from the ground and recondense on other exposed surfaces, a
mechanism known as distillation. However, these mechanisms are
frequently confused with dewfall, which is properly the process by which
water vapor condenses on surfaces directly from the air aloft. In
practice, the origin of the surface moisture is immaterial to pollutants
that come in contact with it. However, dewfall and distillation are
processes that assist pollutant deposition through Stefan flow, whereas
guttation does not. According to Monteith (1963), the maximum rate of
dewfall is of the order of 0.07 mm hr'1, so that the maximum Stefan
flow enhancement of the nocturnal deposition velocity is about 8 cm
hr'1 (see Section 7.2.4).
7.2.10 Resuspension and Surface Emission
Deposited particles can be resuspended into the air, and
subsequently redeposited. The mechanisms involved are much the same as
those that cause saltation of particles from the beds of streams and
from eroding soils. These subjects are of great practical importance in
their own right, and have been studied at length. Concern about
resuspension of radioactive particles near sites of accidents or weapons
tests injected a note of some urgency into related studies during the
1950's and 1960's, as evidenced in the large number of papers on the
subject included in the volume "Atmosphere-Surface Exchange of
Particulate and Gaseous Pollutants" (Engelmann and Sehmel 1976).
The momemtum transfer between the atmosphere and the surface is the
driving force that causes surface particles to creep, bounce, and
eventually saltate. There is a minimum frictional force that will cause
particles of any particular size to rise from the surface. Bagnold
(1954) identifies u*2 as a controlling parameter, so that it is the
few occurrences of strongest winds that are the most important. While
most thinking seems to center on wide-spread phenomena like dust storms,
Sinclair (1976) points out that dust devils provide a highly efficient
light-wind mechanism for resuspending surface particles and carrying
them to considerable altitudes. Clearly, very large particles will not
be moved frequently, or far. Very small particles are bound to the
surface by adhesive forces that have already been discussed, and tend to
be protected in crevices or between larger particles.
Chamberlain (1982) has provided a theoretical basis for linking
saltation of sand particles and snowflakes, and for relating these
phenomena to the generation of salt spray at sea.
It is not clear how saltation and related phenomena affect acidic
deposition. Surface particles that are injected into the air by the
action of the wind do not normally move far, nor do they offer much
7-21
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opportunity for interaction with other air pollutants (firstly, because
they are confined in a fairly shallow layer near the surface, and
secondly, because they have a very short residence time). Their effects
are largely local .
Many smaller particles (in the submicron size range) are generated
by reactions between atmospheric oxidants and organic trace gases
emitted by some vegetation, especially conifers (Arnts et al . 1978).
Once again, it is not obvious how these should best be considered in the
present context of acidic deposition. This is but one of many natural
surface-sources that provide a conceptual mechanism for injecting
particles and trace gases into the lower atmosphere. The subject is
dealt with in Chapter A-2.
7.2.11 The Resistance Analog
Discussing the relative importance of the various factors that
contribute to the net flux of some particular atmospheric pollutant and
determining which process might be limiting in specific circumstances
are simplified by considering a resistance model analogous to Ohm's law.
Figure 7-7 illustrates the way in which the concept is usually applied.
An aerodynamic resistance, ra, is identified with the transfer of
material through the air to the vicinity of the final receptor surfaces.
This resistance is defined as that associated with the transfer of
momentum; it is dependent on the roughness of the surface, the wind
speed, and the prevailing atmospheric stability. The aerodynamic
resistance can be written as
where Cfn is the appropriate friction coefficient (the square root of
the familiar drag coefficient) in neutral stability, u* is the
friction velocity (a scaling quantity defined as the root mean
covariance between vertical and longitudinal wind fluctuations), k is
the von Karman constant, and vc is a stability correction function
that is positive in unstable, negative in stable, and zero in neutral
stratifications (see Wesely and Hicks 1977). Equation 7-2 is obtained
by straightforward manipulation of standard micrometeorological
relations, as given by Wesely and Hicks, for example. The value of k is
usually taken to be about 0.4. Table 7-3 lists typical values of the
friction coefficient for a range of surfaces.
The surface boundary resistance, r^, (separated further in Figure
7-7 between components rbf and rbs, associated with foliage and
soil, respectively) is that which accounts for the difference between
momentum transfer (i.e., frictional drag) at the surface and the passage
of some particular pollutant through the near-surface quasi-laminar
layer. In agricultural meteorology literature, a quantity B"1 is
frequently employed for this purpose (Brutsaert 1975a). The
relationship between these quantities can be clarified by relating both
to the micrometeorological concept of a roughness length, z0 (the
7-22
-------
rbs.
cs
Figure 7-7. A diagrammatic illustration of the resistance model
frequently used to help formulate the roles of processes
like those given in Figure 7-1. Here, ra is an aerodynamic
resistance controlled by turbulence and strongly affected by
atmospheric stability, r^f and rbs represent surface
boundary layer resistances that are determined by molecular
diffusivity and surface roughness, and rcf and rcs are the
net residual resistances required to quantify the overall
deposition process, to the eventual sink. The subscripts f
and s are intended to indicate pathways to foliage and to
soil respectively. There are many other pathways that might
be important; the diagram is not intended to be more than a
simple visualization of some of the important factors.
7-23
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TABLE 7-3. ESTIMATES OF ROUGHNESS CHARACTERISTICS TYPICAL OF NATURAL
SURFACES. VALUES OF THE FRICTION COEFFICIENT Cfn ( = u*/u)
ARE EVALUATED FOR NEUTRAL CONDITIONS, AT A HEIGHT 50 CM
ABOVE THE SURFACE OR TOP OF THE CANOPY
Approx. Canopy Roughness Neutral Friction
Surface Height (m) Length (cm) Coefficient, Cfn
Smooth ice 0 0.003 0.042
Ocean 0 0.005 0.045
Sandy Desert 0 0.03 0.055
Tilled Soil 0 0.10 0.066
Thin Grass 0.1 0.70 0.095
Tall thin grass 0.5 5. 0.16
Tall thick grass 0.5 10. 0.21
Shrubs 1.5 20. 0.25
Corn 2.3 30. 0.29
Forest 10. 50. 0.23
Forest 20. 100. 0.24
7-24
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height of apparent origin of the neutral logarithmic wind profile).
Then the total atmospheric resistance, R, between the surface in
question and the height of measurement z can be written as
R =
= (ku*)-l(£n(z/z0) + £n(z0/zoc) - yc
= ra + (ku*)-l . £n(z0/zoc) [7-3]
where ZQC is a roughness length scale appropriate for the transfer of
the pollutant. The residual boundary-layer resistance, rb = R - ra,
is then
rb = (ku*H . n(z0/zoc), [7-4]
which alternatively is written as
rb = (u*B)-l. [7-5]
B is, therefore, a measure of the non-dimensional ized limiting
deposition velocity for concentrations measured sufficiently close to a
receptor surface such that the resistance to momentum transfer can be
disregarded.
It should be noted that some workers refer to rb as the
aerodynamic resistance and use the symbol ra for it, (e.g., O'Dell et
al. 1977).
Shepherd (1974) recommends using a constant value kB-1 =
£n(z0/zoc) = 2.0 for transfer to vegetation, on the basis of
results obtained over rough, vegetated surfaces. However, the role of
the Schmidt number in accounting for diffusion near a surface needs to
be taken into account. Wesely and Hicks (1977) advocate using a Schmidt
number relationship like that of Equation 7-1, so that surface boundary
layer resistance would then be written as
rb - 5 Sc23/u* . [7-6]
Equation 7-6 implies a value of 0.2 for A in the boundary layer
relationship given by Equation 7-1, as was mentioned earlier.
The final resistances in the conceptual chain of processes
represented diagramatically by Figure 7-7 are those which permit
material to be transferred to the surface itself. For many pollutants,
it is necessary only to consider the canopy foliage resistance, rcf,
but for some it is also necessary to consider uptake at the ground by
invoking a resistance to transfer to soil (or a forest floor), rcs.
In concept, it is also appropriate to differentiate between boundary
layer resistances rbf and rbs for transfer to foliage and soil,
respectively, as is shown in the diagram. Many other resistances can be
7-25
409-261 0-83-19
-------
identified and might often need to be considered, but further
complication of Figure 7-7 is unnecessary. Its main purpose is
illustrative.
Transfer of many trace gases to foliage occurs by way of stomatal
uptake, which, because of stomatal physiology, imposes a strong diurnal
cycle on the overall deposition behavior. Following initial work by
Spedding (1969), studies of foliar uptake of sulfur dioxide have
repeatedly confirmed the controlling role of stomatal resistance.
Chamberlain (1980) summarizes results of experiments by Belot (1975) and
Garland and Branson (1977), who compared surface conductances of sulfur
dioxide with those for water vapor, over a broad range of stomatal
openings (which largely govern stomatal resistance). The conclusion
that stomatal resistance is the controlling factor when stomata are open
appears to be well founded. However, once again, it is necessary to
apply corrections to account for the diffusivity of the trace gas in
question; the higher the molecular diffusivity of the gas, the lower the
stomatal resistance.
Fowler and Unsworth (1979) point out that S02 deposition to wheat
continues even when stomata are closed, at a rate suggesting significant
deposition at the leaf cuticle. Thus, it is not always sufficient to
compute the canopy-foliage resistance r^f on the assumption that S02
uptake is via stomata alone (although this may indeed be a sufficient
approximation in most circumstances). Instead, it is more realistic to
estimate rcf from its component parts via
rcf - (rst-l + rcut-l)-l/(LAI) [7-7]
(following Chamberlain 1980), where rst is the stomatal resistance,
and r~U£ is the cuticular resistance. LAI is the leaf area index
(total area of foliage per unit horizontal surface area). Note that in
most literature the LAI is assumed to be the single-sided leaf area
index. However, sometimes both sides of the leaves are counted.
The resistance analogy permits a closer look at the mechanisms that
transfer gaseous material into leaves. Figure 7-8 illustrates the
pathways involved: via stomatal openings and into the interior of the
leaf (involving stomatal and mesophyllic resistances, rst and rm) or
through the epidermis (involving a cuticular resistance, rcut).
The resistance model is somewhat limited by the manner in which it
structures the chain of relevant processes, each being represented by a
resistance to transfer that occupies a prescribed location in a
conceptual network. The structure of this network is sometimes not
clear; furthermore, there are important processes that do not
conveniently fit into the resistance model. Mean drift velocities
(e.g., gravitational settling of particles) are not easily accommodated
in the simple resistance picture, and it is doubtful whether some of the
biological factors are relevant to the question of particle transfer.
Studies of leaves show that stomata are typically slits of the order of
2 to 20 ym long. For stomatal uptake of particles to be a controlling
7-26
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EPIDERMIS
SPONGY,
MESOPHYLLIC
CELLS
PALISADE
CELLS
Figure 7-8. An illustration of the roles of different resistances
associated with trace gas uptake by a leaf. Material is
transferred along several possible pathways, of which two
are shown. These involve cuticular uptake via a resistance
rcut, and transfer through stomatal pores (via r$t) into
substomatal cavities, with subsequent transfer to mesophyllic
tissue (via rm). The way in which the various resistances
are combined to provide the best visualization of the overall
transfer process in not clear-cut.
7-27
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factor of deposition, we would need to hypothesize spectacularly good
aim by the particles.
7.3 METHODS FOR STUDYING DRY DEPOSITION
7.3.1 Direct Measurement
There is little question that the deposition of large particles is
accurately measured by collection devices exposed carefully above a
surface of interest. Deposit gauges and dust buckets have been
important weapons in the geochemical armory for a long time. They are
intended to measure the rate of deposition of particles which are
sufficiently large that deposition is controlled by gravity. In studies
of radioactive fallout conducted in the 1950's and 1960's, these same
devices were used. In the case of debris from weapons tests, the major
local fallout was of so-called hot radioactive particles, originating
with the fragmentation of the weapon casing and its supporting
structures, and the suspension of soil in the vicinity of the explosion.
These large particles fall over an area of rather limited extent
downwind of the explosion. This area of greatest fallout was the major
focus of the work on fallout dry deposition. It was largely in this
context that dustfall buckets were used to obtain an estimate of how
much radioactive deposition occurred. It was recognized that collection
vessels failed to reproduce the microscale roughness features of natural
surfaces. However, this was not seen as a major problem, since the
emphasis was on evaluating the maximum rate of deposition that was
likely to occur so that upper limits could be placed on the extent of
possible hazards. Nevertheless, efforts were made to "calibrate"
collection vessels in terms of fluxes to specific types of vegetation,
soils, etc. (Hardy and Harley 1958).
Much further downwind, most of the deposition was shown to be
associated with precipitation, since the effective source of the
radioactive fallout being deposited was typically in the upper
troposphere or the lower stratosphere. The acknowledged inadequacies of
collection buckets for dry deposition were then of only little concern,
since dry fallout composed a small fraction of the total surface flux.
In the context of present concerns about acidic deposition, we must
worry not only about large, gravitationally-sett!ing particles, but also
about small "accumulation-size-range" particles that are formed in the
air from gaseous precursors, and about trace gases themselves. All of
these materials contribute to the net flux of acidic and acidifying
substances by dry processes. It is known that collection vessels do
indeed provide a measure of the flux of large particles. However,
accumulation-size-range particles, typically less than 1 ym diameter,
do not deposit by gravitational settling at a significant rate. These
small particles are transported by turbulence through the lower
atmosphere and are deposited by diffusion to surface roughness elements,
with the assistance of a wide range of surface-related effects (e.g.,
phorectic processes, Stefan flow, etc.), many of which will be
influenced by the detailed structure of the surface involved.
7-28
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Early work on the deposition of radioactive fallout made use of
collection vessels and surrogate surface techniques that were frequently
"calibrated" in terms of fluxes to specific types of vegetation, soils,
etc. Studies of this kind were relatively easy, especially in the case
of radioactive pollutants, because very small quantities of many
important species could be measured accurately by straightforward
techniques. Most of the radioactive materials that were of interest do
not exist in nature, so experimental studies benefited from a zero
background against which to compare observed data. Moreover, major
emphasis was on the dose of radioactivity to specific receptors, a
quantity strongly influenced by contributions of large, "hot" particles
in situations of practical interest. Such circumstances included
deposition of bomb debris, fission products, and soil particles from the
radioactive cloud downwind of nuclear explosions. In such cases,
highest doses were incurred near the source, and were due to these
larger particles.
The applicability of collection vessels and surrogate surfaces in
studies of the dry deposition of acidic pollutants is in dispute (see
also Chapter A-8, Section 8.2). Principal among the conceptual
difficulties concerning their use is their inability to reproduce the
detailed physical, chemical, and biological characteristics of natural
surfaces, which are known to control, or at least strongly influence,
pollutant uptake in most instances. Furthermore, the continued exposure
of already-deposited materials to airborne trace gases and aerosol
particles undoubtedly causes some changes to occur, but of unpredictable
magnitude and unknown significance. A recent intercomparison between
different kinds of surrogate surfaces and collection vessels has
indicated that fluxes derived from exposing dry buckets are greater than
those obtained using small dishes, which in turn exceed values obtained
using rimless flat plates (Dolske and Gatz 1982). This provides a
tantalizing tidbit of evidence for an ordering of performance
characteristics according to the total exposed surface area per unit
horizontal projection. In this context, the similarity with arguments
concerning leaf area index seems especially attractive.
Micrometeorological data obtained during the same experiment fall
between the extremes represented by the buckets and the flat plates.
Dasch (1982) reports on a comparison between many different
configurations of flat-plate collection surfaces, pans, and buckets.
The results indicate that glass surfaces provide the greatest flux
estimates for almost all chemical species considered, and teflon the
lowest. Plastic bucket data generally fall midway in the range.
Tracer techniques developed in the radioecology era for
investigating fluxes to natural surfaces offer some promise. A
B-emitting isotope of sulfur, S-35, lends itself to use in studies of
S02 uptake by crops because measurements of low rates of sulfur
accumulation are then possible. Garland et al. (1973), Owers and Powell
(1974), Garland and Branson (1977), and Garland (1977) report the
7-29
-------
results of a number of studies of 35S02 uptake by various vegetated
surfaces ranging from pasture to pine plantation, and by non-vegetated
surfaces such as water.
In concept, it is feasible to extend studies of this kind to the
deposition of sulfurous particles, but as yet no such experiment has
been reported. However, analogous studies of particle deposition using
non-radioactive aerosol tracers have been carried out. In wind-tunnel
experiments, Wedding et al. (1975) employed uranine dye particles in
conjunction with lead chloride particles to study the influence of leaf
microscale roughness on particle capture characteristics; uranine
particles are relatively easy to measure by fluorimetry, whereas
measurements of lead deposition require far more painstaking chemical
analysis of the deposition surface. The particle sizes used by Wedding
et al. were in the range 3 to 7 ym diameter.
Considerably larger particles have been used in many studies. In
detailed wind-tunnel studies, Chamberlain (1967) used lycopodium spores
(-30 ym aerodynamic diameter). Workers at Brookhaven National
Laboratory extended these wind-tunnel techniques to real-world
circumstances by conducting a series of experiments employing pollen in
the same general size range (Raynor et al. 1970, 1971, 1972, 1974).
In general, these methods of tracer measurement have not been
applied to natural circumstances for the particle sizes of major
interest in the present context of acidic deposition. An important
exception concerns studies of deposition on snow surfaces. The
retention of deposited material at the top of or within a snowpack has
been studied in some detail and continues to be an intriguing area of
research. Particulate materials such as sulfate were considered by
Dovland and Eliassen (1976), who studied the accumulation upon snow
surfaces during periods of no precipitation and found average deposition
velocities in the range 0.1 to 0.7 cm s~*, depending on the assumption
made regarding the contribution by gaseous S02 deposition. Similar
work by Barrie and Walmsley (1978) yielded average sulfur dioxide
deposition velocities to snow in the range 0.3 to 0.4 cm s"1, with a
standard error equivalent to about a factor of two.
Eaton et al. (1978) and Dillon et al. (1982) present examples of
the use of calibrated watersheds to estimate atmospheric deposition.
Dry deposition fluxes are estimated as a residual between measured
fluxes out of a conceptually-closed system, assumed to be in steady
state, and measured wet deposition into it. Considerable effort is
required to document annual chemical mass balances for specific
watersheds. Once the effort is made, it appears possible to draw
conclusions regarding dry deposition, although obviously such estimates
will be the result of the difference between fairly large numbers.
According to Eaton et al., the annual dry deposition flux estimate
obtained at the Hubbard Brook Experimental Forest in New Hampshire is
accurate to about + 35 percent (one standard error). The data do not
7-30
-------
permit apportionment between gaseous and participate sulfur inputs, but
the total sulfur flux corresponded to a deposition velocity of about 0.6
cm s"1.
7.3.2 Wind Tunnel and Chamber Studies
Figure 7-1 illustrates the overall complexity of the problem of dry
deposition. While it is indisputable that no indoor experiment can
provide a comprehensive evaluation of pollutant deposition that would be
applicable to the natural countryside, laboratory studies provide the
unique attraction of controllable conditions. It is feasible to compare
the relative importance of various factors, as in Figure 7-1, and
especially as in Figure 7-8, and to formulate these processes in a
logical manner. In this general category, we must include the extensive
wind tunnel work referred to earlier, the pipe-flow and flat-plate
studies conducted in experiments more aligned to problems of chemical
engineering, and the chamber experiments favored by ecologists and plant
physiologists. Distinction among these kinds of experiments is often
difficult. Many exposure chambers and pipe-flow studies have features
of wind tunnels.
The utility of chamber studies is well illustrated by the series of
results reported by Hill (1971). By comparing the rates of deposition
of various trace gases to oat and alfalfa canopies exposed in large
chambers, Hill concluded that solubility was a critical parameter in
determining uptake rates of trace gases by vegetation. The ordering of
deposition velocities was: hydrogen fluoride > sulfur dioxide > chlorine
> nitrogen dioxide > ozone > carbon dioxide > nitric oxide > carbon
monoxide. Furthermore, the chamber studies indicated a wind speed
dependence of the kind predicted by turbulent transfer theory, and
demonstrated a physiological effect of chlorine and ozone uptake on
stomatal opening: exposure to high concentrations of either quantity
caused partial stomatal closure, thus limiting the fluxes of all trace
gases that are stomatally controlled.
Experiments conducted by Judeikis and Wren (1977, 1978) yielded
valuable information on the deposition of hydrogen sulfide, dimethyl
sulfide, sulfur dioxide, nitric oxide, and nitrogen dioxide to
non-vegetated surfaces (Table 7-4). The values listed were derived from
initial deposition rates obtained before surface accumulation limited
uptake rates. For comparison, surface resistances derived from Hill's
(1971) studies of trace gas uptake by alfalfa are also listed. On the
whole, the ordering of deposition velocities suggested by Hill's work
appears to be supported, providing some justification for extending the
ordering to CO, H2S, and (CH^^S in the manner indicated in the
table. Residual surface resistance to uptake of soluble gases by solid,
dry surfaces appears to be substantially greater than for vegetation,
which is as would be expected.
The values listed in Table 7-4 represent resistances to transport
very near the surface, much like the surface boundary-layer resistance
discussed earlier to which other resistances must be added to obtain
7-31
-------
TABLE 7-4. RESISTANCES TO DEPOSITION (S CM-1) OF SELECTED TRACE
GASES, MEASURED FOR SOLID SURFACES IN A CYLINDRICAL FLOW REACTOR
(JUDEIKIS AND STEWART 1976) AND FOR ALFALFA IN A GROWTH CHAMBER
(HILL 1971)a
Substrate Surface
Pollutant Adobe Clay Sandy Loam Alfalfa
CO
H?S
(CHo)-S
NO C
C09
°a
Nu9
so|
HF
62.0
3.6
7.7
-
-
1.3
1.1
••
67.0
16.0
5.3
-
-
1.7
1.7
mm
oo
m.
_
10.0
3.3
0.7
0.5
0.5
0.4
0.3
aSolid-surface data are derived from Table 2 of Judeikis and Wren
(1978). The alfalfa values are obtained from Table 1 of Hill (1971)
7-32
-------
values representative of natural, out-door conditions. The reciprocals
of the tabulated numbers provide upper limits of the appropriate
deposition velocities.
Similarly, informative data have been obtained about particle
deposition on surfaces that can be contained in wind tunnels. Studies
of this kind are an obvious extension of pipe-flow investigations by
workers such as Friedlander and Johnstone (1957) and Liu and Agarwal
(1974), which provide strong support for theories involving particle
inertia and Schmidt number scaling. Wind-tunnels provide a means to
extend chamber and pipe-flow investigations to situations more closely
approximating natural conditions.
Results obtained in studies of particle deposition to dry gravel
(Sehmel et al. 1973a) are shown in Figure 7-9. Experiments on the
deposition to wet gravel were also conducted. These indicated
deposition velocities some 30 percent less than the values evident in
Figure 7-9 (for particles in the 0.2 to 1.0 ym size range), as might
be expected from considerations of Stefan flow and diffusiophoresis.
When surface roughness was increased, deposition velocities also
increased. The wind speed effect evident in these data is fairly
typical and applies also in the case of vegetation (Figure 7-10).
Chamberlain (1967) extended his earlier (1966) wind tunnel studies
of gas transfer to "grass and grass-like surfaces" by considering parti-
cle deposition to rough surfaces. Sehmel (1970) conducted similar wind
tunnel experiments, employing monodisperse particles ranging from about
0.5 to 20 ym diameter. Figure 7-10 combines results from Chamberlain
(1967) and Sehmel et al. (1973b). The Chamberlain data refer to live
grass, but the Sehmel et al. data were obtained using 0.7 cm high
artificial grass. Moreover, the two sets of data were obtained at
different wind speeds (Chamberlain, u* - 70 cm s~l; Sehmel et
al., u* - 19 cm s"1). Further tests conducted by Chamberlain
(1967) indicated that deposition velocities to natural grass exceeded
those to artificial grass by a factor of about two for particles smaller
than about 5 ym. This appears contrary to the indication of Figure
7-10, where v
-------
CO
S=
DEPOSITION VELOCITY (cm s"1)
~~l
co
I— > • fD
VO CTi
--J C
OO O — '
o> 3 v>
. Q. o
_j. -(,
QJ
3 S
ro -j-
c+ 3
ro Q.
-s
fD
tQ — •
Oi CO
< el-
n> c:
— ' Q.
Q- O
fa -t,
T3
rt-TJ
CD O>
Q- -S
rh
-h -••
-S O
O — •
3 rt>
00 Q.
fD fD
3 O
fD CO
e-t-
0> -"•
e-t O
TJ
73
t—i
O
73 o
-------
co
CJ1
fD
COIQ TO
fD -S fD
3" a> co
CO
fD CU
rt- CO O
—• fD S.
. -a -"•
O 3
-—- ~S Q.
i—> ct-
tX> fD c-i-
~-J Q. C
00 3
CT CT 3
-—<< fD
I O
3" CO
O 01 r+
c 3 c
-S cr CL
fD -5 fD
—i co
-"• O
3 -(,
Q)
-S
1 fD
CL CL
O fD
DEPOSITION VELOCITY (cm s"1)
CO o
»• CO
Of rj-'
O- o'
3
-o
3>
O
m
a
m
-------
methods that impose no surface or environmental modification. In
concept, if an area is sufficiently homogeneous, flat, and contains no
areas of strong sources or sinks, pollutant fluxes can be assumed to be
constant with height. Therefore, questions regarding dry deposition can
be addressed by measuring the flux of material through a horizontal
layer of air at some more convenient level above the surface. The
intent of any such study is to investigate dry deposition fluxes in
carefully-documented natural situations to identify and quantify
controlling properties. The results of these investigations are formu-
lations of surface mechanisms, surface boundary layer resistances,
stomatal resistances, etc. The demanding site criteria are required to
enable these results to be obtained from the experiments; the surface
parameterizations that are derived are far more widely applicable.
Several micrometeorological methods are suitable for measuring dry
deposition fluxes in intensive case studies. The flux can be measured
directly by eddy-correlation, a process that evaluates instantaneous
products of the vertical wind speed, w, and pollutant concentration, C,
to derive the time-average vertical flux Fc as
Fc = pw'C' [7-8]
where Pis the air density and the primes denote deviations from mean
values. The over-bar indicates a time average. This is an extremely
demanding task and constitutes a specialized field of micrometeorology
in its own right. Details of experimental procedures are given, for
example, by Dyer and Maher (1965), Kaimal (1975), and Kanemasu et al.
(1979).
Figure 7-11 shows examples of sensor output signals fundamental to
the eddy-correlation technique. Fast-response sensors of any pollutant
concentration can be used; the trace shown for C02 in the diagram is
an interesting example of considerable agricultural relevance. As a
basic requirement, sensors suitable for eddy correlation applications
should have response times shorter than one second for operation at
convenient heights on towers. For application aboard aircraft (Bean et
al. 1972, Lenschow et al. 1980) considerably faster response is
required.
Eddy-correlation methods have been used in field experiments
addressing the fluxes of ozone (Eastman and Stedman 1977), sulfur
(Galbally et al. 1979, Hicks and Wesely 1980), nitric oxides (Wesely et
al. 1982b), carbon dioxide (Desjardins and Lemon 1974, Jones and Smith
1977), and small particles (Wesely et al. 1977).
Rates of transfer through the lower atmosphere are governed by
turbulence generated by both mechanical mixing and convection. In this
context, three atmospheric quantities cannot be separated: the vertical
flux of material, the local concentration gradient (3C/3z), and its
corresponding eddy diffusivity (K). Knowledge of any two of these
quantities will permit the third to be evaluated. Often, when sensors
7-36
-------
-~J
oo
330
C02 (ppm) 319
308'
0.8n
0.2-1
27.0-
T (°C) 25.5-
24.0J
12:35
12:36
TIME (hr:min)
12:37
Figure 7-11.
An example of atmospheric turbulence near the surface. These traces of C02 concentration,
vertical velocity (w), wind speed (u), and temperature (T) were obtained over a corn
canopy by workers at Cornell University at a few meters above the surface.
-------
suitable for direct measurement of pollutant fluxes are not available,
assumptions regarding the eddy diffusivity are made to provide a method
for estimating fluxes from measurements of vertical concentration
gradients:
Fc =PK(9C/9z). [7-9]
Hicks and Wesely (1978) and Droppo (1980) have summarized a number of
critical considerations. In particular, with a typical value of u*
= 40 cm s'1 and neutral stability, the concentration difference
between adjacent levels differing in height by a factor of two is about
9 percent, for a 1 cm s"1 deposition velocity (v,j). In unstable
(daytime) conditions, smaller gradients would be expected for the same
V(j; in stable conditions, they would be greater.
The demands for high resolution by the concentration measurement
technique are obvious. Nevertheless, a substantial quantity of
excellent information has been obtained, especially concerning fluxes of
S02 (Whelpdale and Shaw 1974, Garland 1977, Fowler 1978).
It should be emphasized that the stringent site uniformity
requirements mentioned above for the case of eddy-correlation approaches
are also relevant for gradient studies. Detecting a statistically
significant difference between concentrations at two heights is not
necessarily evidence of a vertical flux and can only be interpreted as
such after extremely demanding siting criteria have been satisfied.
Gradients of particle concentration present special problems
because it is often not possible to derive internally-consistent results
from alternative measurements. Droppo (1980) concludes that "(t)he
particulate source and sink processes over natural surfaces cannot be
considered as a simple unidirectional single-rate flux." Thus, the
proper interpretation of gradient data in terms of fluxes might not be
possible for airborne particles, even in the best of siting
circumstances, because of the role of the surface in emitting and
resuspending particles. In this case, eddy correlation methods will
still provide an accurate determination of the flux through a particular
level, but this flux will be made up of a downward flux of airborne
material and an upward flux of similar material of surface origin.
Disentangling the two is likely to present a considerable problem.
None of the various micrometeorological methods has yet been
developed to the extent necessary for routine application. Rather, they
are research methods that can be used in specific circumstances,
requiring considerable experimental care, the use of sensitive
equipment, and fairly complicated data analysis. They are more suitable
for investigating the processes that control dry deposition than for
monitoring the flux itself.
Nevertheless, some new techniques for dry deposition measurement
are presently under development. A "modified Bowen ratio" method is
being developed in the hope that it might permit an accurate
7-38
-------
determination of vertical fluxes without the need for very rapid
response or great resolution (Hicks et al. 1981). High-frequency
variance methods are also being advocated but have yet to be fully
investigated; for these, sensors having very rapid response are
required. An eddy-accumulation method that bypasses the need for rapid
response of the pollutant sensor is of long-standing interest (e.g.,
Oesjardins 1977) but has yet to be applied to the pollutant flux problem
with significant success.
7.4 FIELD INVESTIGATIONS OF DRY DEPOSITION
7.4.1 Gaseous Pollutants
Table 7-5 summarizes a numoer of recent field experiments on trace
gas deposition to natural surfaces. The listing is drawn from a variety
of sources (especially Sehmel 1979, 1980a; Garland 1979; and Chamberlain
1980); it is not meant to be exhaustive, but is intended to demonstrate
that many of the available data on surface fluxes of trace gases are
biased toward daytime conditions, when "canopy" resistances are usually
the controlling factors. Extrapolation of these deposition velocities
to nighttime conditions is dangerous on two grounds; first, because of
the large changes that might accompany stomatal closure and, second,
because of the much greater influence of aerodynamic resistance in
nighttime, stable conditions.
Figure 7-12 illustrates the large diurnal cycle typical of the dry
deposition rates of most pollutants. These observations were made over
a pine plantation in North Carolina, using eddy correlation to measure
each quantity (Hicks and Wesely 1980). The eddy fluxes of total sulfur
demonstrate a diurnal cycle that appears to be as strong as for the
meterological properties, a result which is not surprising when it is
remembered that many of the causative factors are common (e.g., vertical
turbulent exchange). Some caution must be associated with interpreting
the negative (upward) fluxes of sulfur evident on two periods as
evidence of emission or resuspension from the canopy. Similarly, large
diurnal cycles of S02 deposition are reported by Fowler (1978).
ra = 0.25 s cm-1
rfo = 0.25 s cm~l
rst = 1.0 s cm-1
rcut = 2.5 s cm'*
For deposition to dry soil, Fowler suggests using rcs = 10.0 s cm"*,
and rcs = 0 when the soil is wet.
Aerodynamic resistance, ra, influences the deposition of all
non-sedimenting pollutants. It is not possible for any trace gas to
have a deposition velocity greater than l/ra, i.e., about 4 cm s"1
in the daytime conditions of Fowler's experiment. Because of stability
7-39
-------
TABLE 7-5. RECENT EXPERIENCE ON TRACE GAS DEPOSITION TO NATURAL SURFACES
1
-F*
O
Worker
S02
Hill (1971)
Garland et al.
(1973)
Owers and Powell
(1974)
Shepherd (1974)
Method
35
S02 with stable S02 carrier
over alfalfa
35
S02 over pasture
35
S02 over pasture
S02 gradients over grass
Results and Comments
Vd = 2.3 cm s" (daytime)
Implies rc - 0.4 s cm~
Vd - 1.2 cm s (daytime)
rc = 0.6 s cm"
Vd - 1.3 cm s~ (daytime)
Vd - 1.3 cm s (daytime)
Whelpdale and Shaw
(1974)
Garland (1977)
Fowler (1978)
Dannevik et al.
(1976)
Garland and Branson
(1977)
S02 gradients over snow, water, and
grass
S02 gradients, calcareous soils
S02 gradients, over - wheat
- soybean
S02 gradients over wheat
35
S02 over a pine plantation
0.3 cm s (autumn)
- 1 cm s (daytime for
grass, water, and snow)
- 1.2 cm s~
rc - 0.01 s cm
-1
-1
- 0.4 cm s"
- 1.3 cm s
- 0.4 cm s
-1
-1
- 0.1 - 0.6 cm s
-1
-------
TABLE 7-5 CONTINUED
Worker
Method
Results and Comments
Belot (1975) (as
summarized by
Chamberlain 1980)
Gal bally et al. (1979)
Dovland and Eliassen
(1976)
Barrie and Walmsley
(1978)
34
over a pine plantation
Eddy correlation over pine forest
Accumulation to snow
Accumulation to snow
< 1 cm s
-1
= 0.2 cm s
- 0.1 cm s
-1
-1
- 0.2 cm s
-1
. NO,
Wesely et al. (1982b)
Eddy correlation
-soybeans
Vd - 0.6 cm s'1 (daytime)
rc = 1.3 s cm (daytime)
= 15 s cm" (night)
Gal bally and Roy
(1980)
Wesely et al. (1978,
1982b)
Gradients over wheat
Eddy correlation over a range of
natural surfaces
- 0.7 cm s
-1
Implies rc - 1.4 s cm
rc = 0.8 s cm~ (daytime)
- 1.8 s cm"1 (night)
-1
-------
SULFUR DEPOSITION (yg ni2 s1)
SENSIBLE HEAT (W rii2) FRICTION VELOCITY (cm s'1)
fD
^J
ro
O r+
O O
3 c+
<-+ OJ
-s —•
CT to
c c
CH- —'
-•• -h
O C
3 -S
CO
c:
OJ
DJ
Q.
ro
o
-h
Id
QJ
to
ro
o
OJ
3
Q.
O
DJ
d-
ro
i
H-1
ro
to -a rt- < 73
c. o o ro ro
—• -S —' O
-h rt- a> o o
c --• o -s
-s o -a -"• Q.
3 -"• rt- to
O to 3 "<
o ro o
O rt- -+)
Q.
to
to
ro
3
i/>
-J.
cr
— '
ro
3-
ro
3 3" 3 C —'
o ro rt-ca -t)
rt- &> 3" C
to rt- -S
cr c ->• oo
ro —' o -h
-h 3 a. —•
a. c cu c
ro -s ^^^ x
r+ 31 to -
ro a_ -<•
o a> o o
rt- r-h 7T -h
ro o to
r~> QJ
. -i. Q) 3
3 3
CL Q.
J» -<• 3
c-h O . .
a> ro ro 3-
Qi r+ to 3
—i ro ro to
__i
TD
c+ ro
-1- -s
3 -". vr> to c
ro o oo rt- x
to a_ o c -
u to ^ ^ Q_
• *s< QJ
r+ S 3
3-3- 00.
ro ro —i -h
33- -h
a. ro a. -s
OJ tO ~S —'•
rt- QJ Q.^ O
OJ to Q) rt-
ro -s Q- -••
-s o TT ro o
ro c ro -a 3
-fi to -s O
ro to
-s -"•
rt-
rt- -"•
O O
3
ro
o
o
to
73
O
o
o
o
o
-------
effects, the maximum possible deposition velocity at night would be
considerably lower. Many of the exceedingly large deposition velocities
reported in the open literature appear to exceed the limits imposed by
our knowledge of the aerodynamic resistance. Thus, several of the
results included in the exhaustive tabulation presented by Sehmel
(1980a) should be viewed more as indications of experimental error than
as determinations of a physical quantity.
Figure 7-13 addresses the question of the time variation of the
deposition velocity v^. Values plotted are the maximum deposition
velocity permitted by the prevailing aerodynamic resistance, evaluated
directly from eddy fluxes of heat and momentum determined during the
pine plantation experiment of Figure 7-12. In daytime, deposition
velocities could be as much as 20 cm s'1 if the surface resistance is
zero, implying ra = 0.05 s cm~l during midday periods. At night,
however, vj can decrease to 0.1 cm s~* on infrequent occasions but
often is less than 2.0 cm s~l. Fowler's recommendations are probably
representative of the long-term average.
The importance of diurnal cycles in pollutant deposition and the
close relationship with other meteorological quantities is further
illustrated by Figure 7-14, which provides examples of the trend from
nighttime, through dawn, and into the afternoon of the residual canopy
resistance rc for ozone and water vapor determined using eddy-
correlation (Wesely et al. 1978). These data were obtained over corn
(Zea mays) in July 1976. The upper sequence shows good matching between
rc for ozone and water vapor, with the former exceeding the latter by
a small amount, on the average. As the day progresses, rc increases
gradually, presumably as a consequence of increasing water stress and
eventual stomatal closure. The lower data sequence has two features of
considerable interest. First, the gradual initial decrease of rc for
03 corresponded to a period of evaporation of dewfall (note the rela-
tively low value of rf for H20 during the same period), suggesting
that the presence of liquid water on the leaf surfaces might inhibit
ozone deposition (much as might be expected on the basis of ozone
insolubility in H20). This would not be the case for S02 deposition
(Fowler 1978). Second, the peak in both evaluations of rc at about
1000 hr is associated with the passage of clouds, which caused a rapid
and strong decrease in incoming radiation and lasted for about an hour.
The peak is seen as further evidence for stomatal control, because some
stomatal closure would be expected with reduced insolation.
The proceeding discussion of both S02 and 03 deposition
confirms the generalization made by Chamberlain (1980) that the
deposition of such quantities might be modelled after the case of water
vapor transfer with considerable confidence.
Recently, Wesely et al. (1982b) have reported a field study in
which both 03 and N02 fluxes were measured. For a soybean canopy,
bulk canopy resistances to ozone uptake exceeded water vapor values by
about 0.5 s cm"1 during daytime, with rc for N0£ still greater by
a similar amount.
7-43
-------
W-L
IQ
(D
MAXIMUM DEPOSITION VELOCITY (cm s"1)
I
I— >
oo
3 3 QJ
a. < — •
fD C
z: -s fD
fD f t/>
in fO
(D O
— ' O -h
«< -h
<-h
*— »c+ 3"
h- > 3" (D
UD a>
CO 3
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-"-I'D X
. -s _i.
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a. c
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-S CT
n> — •
in n>
«i.
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V
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n
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e-HQ
-j. (D
o co
3 »
n> a.
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ro n>
-s -s
fD 3
3 fD
c+ Q.
O CU
31 C+
->• 3"
O fD
O
•
o
o
o
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o
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o
o
o
o
o
o
o
(D
to
O
O
O
O
00
*
00
-------
u
.p.
on
o
8
10
12 14
HOUR (CST)
Figure 7-14.
Evaluations of the residual "canopy resistance" rc, to the transfer of ozone and water
vapor, based on eddy fluxes measured above mature corn in central Illinois on 29 July
1976 (upper sequence) and 30 July 1976 (lower sequence). Data are from Wesely et al.
(1978).
-------
7.4.2 Particulate Pollutants
No technique for measuring particle fluxes has been developed to
the extent necessary to provide universally accepted data. Use of
gradient methods, for example, is limited by the inability to resolve
concentration differences of the order of 1 percent. Turbulence methods
require rapid-response, yet sensitive chemical sensors which are not
often available. In both cases, practical application is hindered by
the need for a site meeting stringent micrometeorological criteria.
Nevertheless, results from several applications of micrometeorological
flux-measuring methods have been published. Table 7-6 provides a list
that illustrates the narrow range of available information. The
evidence points to a difference between the deposition characteristics
of small particles and sulfate; the latter seems to be transferred with
deposition velocities somewhat greater than the value of 0.1 cm s-1
that has been assumed in most assessment studies, and greater than the
values appropriate for small particles, on the average. At this time,
the possibility that sulfate fluxes are promoted by the strong effect of
a few large particles cannot be dismissed.
As must be expected, taller canopies are associated with higher
values of vj, on the average. Figure 7-15 shows how small particle
fluxes varied with time of day over a pine plantation in North Carolina
during 1977 (Wesely and Hicks 1979). These eddy-correlation results
display a run-to-run smoothness that engenders considerable confidence;
moreover, they are supported by the finding that simultaneous eddy
fluxes of momentum and heat closely satisfied the usual surface
roughness and energy balance constraints. There is little doubt that
the surface under scrutiny (or at least the air below the sensor) did
indeed represent a source of particles rather than a sink for
substantial periods (Arnts et al. 1978). A basic question then arises
about the meaning of the measured deposition rates, since these probably
represent a net result of continuing but varying surface emission and a
deposition flux that is also varying with time. In particular, it is
not obvious how to relate such results to the common situation in which
we wish to evaluate the atmospheric deposition rate of some particulate
pollutant that is not emitted or resuspended from the surface.
Figure 7-12 identifies periods of the 1977 pine plantation study
during which no gaseous sulfur was detectable. These occasions were
used by Hicks and Wesely (1978) to evaluate residual canopy resistances
for particulate sulfur that averaged about 1.5 s cnr1 (with a standard
error margin of about + 15 percent) for 17 July, and about 1.1 s cm-1
(+_ 25 percent) for 18 Tuly.
Two tests of sulfate gradient equipment over arid grassland.
reported by Droppo (1980), yielded values of 0.10 and 0.27 cm s-1 for
v
-------
TABLE 7-6. FIELD EXPERIMENTAL EVALUATIONS OF THE DEPOSITION VELOCITY
OF SUBMICRON DIAMETER PARTICLES
Surface
Size and Method
Results and Comments
Snow
Dovland and Eliassen
(1976)
Wesely and Hicks
(1979)
Open Water
SI even ng et al.
(1979)
Williams et al.
(1978)
Bare Soil
Wesely and Hicks
(1979)
Grass
Sehmel et al.
(1973b)
Chamberlain (1960)
Lead aerosol, surface
sampling
0.05-0.1 ym parti-
cles eddy correlation
0.2-1.0 ym parti-
cles, gradients
0.05-0.1 ym parti-
cles, eddy
correlation
0.05-0.1 ym parti-
cles, eddy correla-
tion
Polydispersed
rhodamine-B particles
with mass median
diameter 0.7 ym,
deposited to
artificial grass
exposed outdoors
Radon daughters
deposited to natural
grass. Work attri-
buted to Megaw and
Chadwick
0.16 cm s"1 in
stable stratification,
greater values in neutral.
All light-wind data.
Net fluxes small but
upwards; vj too small
be determined.
to
Gradients highly variable.
Range of vj typically 0.2
- 1.0 cm s"1 in magnitude.
Including reversed gradients
in long-term average reduces
average v^ to near zero.
(See Hicks and Williams
1979).
Preliminary indications
only: vd very small, 95%
certainty < 0.05 cm s"*.
Surface frequently a
source: v
-------
TABLE 7-6. CONTINUED
Surface
Size and Method
Results and Comments
Hudson and Squires
(1978)
Davidson and
Fried!ander (1978)
Wesely et al. (1977)
Cloud condensation
nuclei fluxes
measured by gradient
methods over
sagebrush and grass.
Particle size prob-
ably 0.002-0.04 ym
- 0.03 ym parti-
cles, gradients over
wild oats
0.05-0.1 ym parti-
cles, eddy correla-
tion
Everett et al. (1979) Particulate lead and
sulfur, gradients
- 0.04 cm s-1
Average vj = 0.9 cm
Direction of flux sometimes
changes. During deposition
periods, v^ - 0.8 cm
s~l, but much lower on the
average
vj greater for sulfur ( ~ 1
cm s-1) than for lead from
more local sources
Si even'ng (1982)
Hicks et al. (1982)
0.15-0.3 ym parti-
cle gradients over
mature rye and wheat
Sulfate by eddy
correlation
Wesely et al. (1982a) Sulfate by eddy
correlation
Crops
Droppo (1980)
Wesely and Hicks
(1979)
Particulate trace
metals, gradients:
senescent maize
Vd averaged 0.4 +_ 0.3 cm
s"l in light winds, unstable
stratification
Vd as high as 0.7 cm s-1
in daytime, about 0.2 cm
s'1 as a long-term average
vd largest for daytime lush
grass (- 0.5 cm s"1), much
less for short dry grass (~
0.2 cm s"1), strongly stable
conditions
varying widely with
fement, ranging up to about 1
cm s-1
0.05-0.1 ym parti- Strong diurnal variation in
cles, eddy correla- the direction of the flux.
tion: senescent maize Long-term average vd - 0.1
cm s~l
7-48
-------
TABLE 7-6. CONTINUED
Surface
Size and Method
Results and Comments
Trees
Hicks and Wesely
(1978, 1980)
Wesely and Hicks
(1979)
Sulfate particles,
eddy correlation,
Loblolly pine
0.05-0.1 ym parti-
cles, eddy correla-
tion
Strong diurnal variability
but less marked than for small
particles: average vj =
0.7 cm s"l
Very strong diurnal
variation with the canopy a
net source. During
deposition periods, vd
probably greater than 0.6 cm
Lindberg et al.
(1979)
Pb, Cd, S, etc. par- v,j > 0.1 cm s'1 for all
tides foliar washing quantities on the average
Wesely et al. (1982a) sulfate particles,
eddy-correlation
v
-------
ro
DEPOSITION VELOCITY (cm s"1)
-vj
I
en
o
i
i—»
en
->. ro i—' o cr o
3 x UD OJ << ro
CL rt- ~-J ~5 "O
—'• ro >*D o ro o
n 3 1 a. en
OJ CL • -j. Q. _j.
rt- ro 3 << rt-
ro CL OJ ->•
CL "Z. no
T3 O -"• O 3
CT ro r-t- 3 -S
<< -s ro -s <
—'• i—' ro ro
rt- O rt- UD —' —'
3" CL 3" ~-J Q) O
ro co ro *-j rt- o
3 o
ro -h
to
QJ ro
co
.—- o
re 3
< co
ro co
.. o n o>
3 3 7T CT
CQ to O
CL oj ro
• —'. 3
C CL O)
-s
-a -s oj ro ->•
O OJ —' CO 3
to r-t- ro ro
-"• 3" O —'
rt- ro ^ rt-T3
-j. -s n —
1 H-• O>
ro vo 3
= o
CL 3
ro
o
3
rt-
O
to
OJ
-o
o>
-s
rt-
O
ro
00
< OJ CO OJ
ro 3 s: •» <-(••
O Q-
n ro
-J.T3
rt- O
-J. 00
rt- s: o o
3- ro 3 •
00 i—•
-h ro ->.
-S —' 3 C
ro «< 3
ro -••
co rl--Q
= -•• C OJ O
— o ro 3 -s
• 3 3 CL , •
OJ
to
OJ
00
c:
ro
D_
O
c:
oo
-------
the nature of the surface present in the gradient studies is taken into
account.
Results of an extensive series of eddy correlation measurements of
particulate sulfur fluxes to a variety of vegetated surfaces have been
summarized by Wesely et al. (1982a). In daytime conditions, deposition
velocities to grass range from about 0.2 to 0.5 cm s-1. Values for a
deciduous forest in winter (few leaves) are not significantly different
from zero. In general, somewhat lower values are appropriate at night.
In almost all of the case summarized by Wesely et al., normalization of
surface transfer conductances by u* appears to reduce the residual
variance. Hicks et alI. (1982) present supporting data from another
study of the same series, also over grassland.
Considerable controversy remains concerning the value of v^
appropriate for formulating the deposition of sulfate aerosol (and
presumably all similar particles). Garland (1978) advocates the
continued use of values of 0.1 cm s~l or less, because experiments
conducted over grass in England failed to detect a significant gradient.
However, some of the experiments listed in Table 7-6 indicate quite high
deposition velocities for sulfate particles. The possibility of a
strong contribution by particles much larger than the usual accumulation
size mode has been discussed (Garland 1978), and different deposition
velocities (0.025 and 0.56 cm s-1) have been postulated for the
submicron and larger particles, respectively.
There are great uncertainties about results obtained by deposition
plates or other surrogate collection surfaces. Workers sometimes assume
that the collection characteristics of some artificial surface are the
same as those of the natural surface of interest. Clearly, this
assumption will be valid when particles are sufficiently large that
gravity is the controlling factor. However, small particles are
transferred predominantly by turbulence, with subsequent impaction on
the surface of microscale surface roughness elements; these features of
the collecting surface are not easily reproduced by commonly-used
artificial collecting devices. Monitoring the accumulation of particles
in collection vessels continues to be a wide-spread practice (See
Chapter A-8); however, relating the data obtained to natural
circumstances is difficult (Hicks et al. 1981). In a special category
of its own, however, is the method of foliar washing, as used by
Lindberg et al. (1979). As applied in careful studies of particle dry
deposition at the Walker Branch Watershed in Tennessee, this method of
removing and analyzing material deposited on vegetation has succeeded in
demonstrating long-term average values of v^ larger than the usually
accepted values for several elements.
7.4.3 Routine Handling in Networks
The discussion given in this chapter is intended to focus on the
processes that cause dry deposition, and on methods by which these
processes can be investigated. Discussion of network monitoring of
dry deposition is left for Chapter A-8. However, for the sake of
7-51
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completeness a brief summary of present capabilities to monitor dry
deposition should be given here.
It is important to recognize dry deposition for what it is: a
highly variable exchange of trace gases and aerosols between the
atmosphere and exposed surfaces. In some special circumstances, natural
surfaces are such that the accumulation of deposited material can be
measured directly, such as in the case of some icefields, snowpacks,
stone, and metals. However, in general there is no "monitor" that will
give a clear-cut measurement of dry deposition rates to natural
surfaces. Work on developing such a monitor must continue, but should
be conducted with the realization that science has yet failed to develop
such a device for monitoring the surface fluxes of meteorological
quantities such as sensible heat, moisture, and momentum. Even in these
cases, micro meteorological methods such as eddy correlation and
gradient interpretation remain research tools that are applied with
great care in intensive case studies. These field studies are intended
to formulate the atmosphere/surface exchange in a manner that can then
be extended to other situations. Laboratory and modeling studies
provide the basic understanding necessary for developing the techniques
for interpolating between infrequent direct measurements (by any
available method) and for extending them to other situations.
It appears unlikely that collection-vessel or surrogate-surface
methods will be capable of providing direct measurements of dry
deposition fluxes of trace gases and aerosols to natural surfaces.
Likewise, micrometeorological methods seem unable to address the case of
particles that fall under the influence of gravity, and a
micrometeorologically-based deposition "monitor" does not seem an
immediate possibility. Thus, any network for evaluating dry deposition
should concentrate on providing data from which surface fluxes can be
evaluated, by applying the rapidly expanding understanding of dry
deposition processes that is presently being developed. The minimum
requirements would be for data on atmospheric concentrations of the
relevant trace gas and aerosol species, and for sufficient
meteorological data to enable appropriate deposition velocities to be
calculated for specified surface characteristics and for the species of
interest. Surrogate surface devices might be used to evaluate fluxes of
particles falling under the influence of gravity.
These matters are discussed at greater length in Chapter A-8. A
summary of methods for measuring dry deposition, with emphasis on the
suitability of various techniques as deposition "monitors" has been
presented by Hicks et al. (1981).
7.5 MICROMETEOROLOGICAL MODELS OF THE DRY DEPOSITION PROCESS
7.5.1 Gases
Almost all models of dry deposition of trace gases have as their
foundation either the resistance analogy illustrated in Figures 7-7 and
7-8 or some equivalent to it. The convenience of this approach is
7-52
-------
obvious: it permits separate processes to be formulated and combined in
a manner that mimics nature, while providing a clear-cut mechanism for
determining which processes can be omitted from consideration in
specific circumstances. The relevance of the resistance approach to the
matter of particle deposition is not so obvious, especially when
gravitational settling must be considered.
A useful start is to identify the properties of interest and
possible processes that control the uptake of various gases:
$02: Uptake by plants is largely via stomata during daytime, with
about 25 percent apparently via the epidermis of leaves (Fowler
1978). At night, stomatal resistance will increase
substantially, but cuticular resistance should be unchanged.
When moisture condenses on the depositing surface, associated
resistances to transfer should be allowed to decrease to near
zero (Murphy 1976, Fowler 1978). To a water surface,
water-vapor appears to provide an acceptable analogy to SO?
flux.
03: Behavior is like S02 but with significant cuticular uptake at
night (rcut ~ 2 to 2.5 s cnr1 at night; see rc quoted by
Wesely et al. 1982b) and with surface moisture effectively
minimizing uptake. Deposition to water surfaces, in general, is
very slow.
Similar to 03 in overall deposition characteristics, but with
a significant additional resistance (possibly mesophyllic; see
Wesely et al. 1982a) of about 0.5 s cm-1. Even though NO?
is insoluble in water in low concentrations (see Chapter A-4),
deposition to water surfaces might be quite efficient. Chamber
studies (Table 7-4) indicat similar overall surface resistances
for S02 and N02.
NO: Typical canopy resistances are in the range 5 to 20 s cm-1, as
indicated by chamber studies (Table 7-4) and field experiments
(Wesely et al. 1982a). NO appears to be emitted by surfaces at
times, possibly as a consequence of NO? deposition and of the
intimate linkage with ozone concentrations (Galbally and Roy
1980).
HNOs: No direct information is available; however, on the basis of its
high solubility and chemical reactivity, substantial similarity
to HF should be expected. Consequently, the use of rc = 0
appears to be a reasonable first approximation.
NH3: Again, no direct measurements are available but in this case
similarity with S02 appears likely. Natural surfaces may be
emitters of NH3 because of a number of biological processes
occurring in and on soil.
7-53
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Variations in aerodynamic resistance must be expected to modulate
all of the behavior patterns summarized above. In many circumstances,
deposition rates at night will be nearly zero solely because atmospheric
stability is so great that material cannot be transferred through the
lower atmosphere. The evaluations given in Figure 7-12 are especially
informative, because even over a pine forest whose surface roughness
operates to maximize v
-------
7.5.2 Particles
Modeling of particle deposition is complicated by three major
factors: (1) gravitational settling, which causes particles to fall
through the atmospheric turbulence that provides the conceptual basis
for conventional micrometeorological models (Yudine 1959); (2) particle
inertia, which permits particles to be projected through the near-
surface laminar layer by turbulence, but also prohibits particles from
responding to the high-frequency turbulent motions that transport
material near receptor surfaces; and (3) uncertainty regarding the
processes that control particle capture. These three factors are
interrelated in such a manner that clearcut differentiation of their
separate consequences is not possible.
The problem has attracted the attention of many theoreticians, and
many numerical models have been developed. Each model represents a
selected combination of processes, chosen for consideration on the basis
of the modeler's understanding of the problem. Without adequate
consideration of all of the mechanisms involved, none of these models
can be considered as a simulator of natural behavior. This is not to
question the worth of such models, but rather to emphasize that each
should be applied with caution, and only to those situations
commensurate with its own assumptions.
The many numerical models can be classified in several different
ways. Some extend chemical engineering results to surface geometries
that are intended to represent plant communities. Others extend
agrometeorological air-canopy interaction models by including critical
aspects of aerosol physics. Both approaches have benefits, and the
final solution will probably include aspects of each.
An excellent review of model assumptions has been given by Davidson
and Friedlander (1978). They trace the evolution of models from the
1957 work of Friedlander and Johnstone (which concentrated on the
mechanism of inertial impaction and assumed that particles shared the
eddy diffusivity of momentum) to the canopy filtration models of Slinn
(1974) and Hidy and Heisler (1978). Early work concerned deposition to
flat surfaces and made various assumptions about the surface collection
process. Friedlander and Johnstone (1957) permitted particles to be
carried by turbulence to within one free-flight distance of the surface,
upon which they were assumed to be impacted by inertial penetration of
the quasi-laminar "viscous" sublayer. Beal (1970) introduced viscous
effects to limit the transfer of small particles, while retaining
inertial impaction of larger particles. Sehmel (1970) assumed that all
particles that contact the surface will be captured and used empirical
evidence obtained in his wind-tunnel studies to determine the overall
resistance to transfer, assumed to apply at a distance of one particle
radius from the surface. Sehmel's work has been updated recently to
provide an estimate of deposition velocities to canopies of a range of
geometries in different meteorological conditions (Sehmel 1980b).
The above models are based largely on observations and theory
regarding the deposition of particles to smooth surfaces, usually of
7-55
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pipes. More micrometeorologically-oriented models have been presented
by workers such as Chamberlain (1967), who extended the familiar
meteorological concepts of roughness length and zero plane displacement
to the case of particle fluxes. Much of this work was considered as an
extension of models developed for the case of gaseous deposition to
vegetation, which in turn were based on an extensive background of
agricultural and forest meteorology, especially concerning
evapotranspiration. A recent development of this genre is the canopy
model of Lewellen and Sheng (1980), which uses recent techniques in
turbulence modeling to reproduce the main features of subcanopy flow and
combines these with particle deposition formulations like those
represented in Figure 7-4. Lewellen and Sheng emphasize their model's
omission of several potentially critical mechanisms, especially
electrical migration, coagulation, evolution of particle size
distributions, diffusiophoresis, and thermophoresis. To this list we
can add a number of other factors about which little is known at this
time, such as subcanopy chemical reactions, interactions with emissions,
and the effect of microscale roughness elements.
Although outwardly simpler than the case of particle deposition to
a canopy, deposition to a water surface has given rise to a similar
variety of models. Once again, however, different models focus on
different mechanisms. That of Sehmel and Sutter (1974) is based on
their wind tunnel observations and lacks a component that can be
identified with wave effects. SI inn and SI inn (1980) invoke the rapid
growth of hygroscopic aerosol particles in very humid air to propose
rather rapid deposition to open water; deposition velocities on the
order of 0.5 cm s-1 appear possible in this case. On the other hand,
Hicks and Williams (1979) propose negligible fluxes unless the surface
quasi-laminar layer is interrupted by breaking waves. At present, none
of these models has strong experimental evidence to support it.
However, experimental and theoretical studies are proceeding, and a
resolution of the matter can certainly be expected.
7.6 SUMMARY
All of the many processes that combine to permit airborne materials
to be deposited at the surface have aspects that are strongly surface
dependent. While broad generalities can be made about the velocities of
deposition of specific chemical species in particular circumstances,
wide temporal and spatial variabilities occur in most of the controlling
properties. The detailed nature of the vegetation covering the surface
is often a critical consideration. If depositional inputs to a special
sensitive area need to be estimated, then this can only be accomplished
if characteristics specific to the vegetation cover of the area in
question are adequately taken into account.
Recent field studies investigating the fluxes of small particles
have confirmed wind tunnel results that point to a surface limitation.
Studies of the rate of deposition of particles to the internal walls of
pipes and investigations of fluxes to surfaces more characteristic of
nature, exposed in wind tunnels, tend to confirm theoretical
7-56
-------
expectations that surface uptake is controlled by the ability of
particles to penetrate a quasi-laminar layer adjacent to the surface in
question. The mechanisms that limit the rate of transfer of particles
involve their finite mass. Particles fail to respond to the high
frequency turbulent fluctuations that cause transfer to take place in
the immediate vicinity of a surface. However, the momentum of particles
also causes an inertia! deposition phenomenon that serves to enhance the
rate of deposition of particles in the 10 to 20 ym size range.
The general features of particle deposition to aerodynamically
smooth surfaces are fairly well understood. Studies conducted so far
support the theoretical expectation that particles smaller than about
0.1 ym in diameter will be deposited at a rate largely determined by
Brownian diffusivity. In this instance, the limiting factor is the
transfer by Brownian motion across the quasi-laminar layer referred to
above. On the other hand, particles larger than about 20 ym in
diameter are effectively transferred via gravitational settling, at
rates determined by the familiar Stokes-Cunningham formulation.
Particles in the intermediate size ranges are transferred very slowly.
The minimum value of the "well" of the deposition velocity versus
particle size curve is approximately 0.001 cm s"1.
However, natural surfaces are rarely aerodynamically smooth. Wind
tunnel studies have shown that the "well" in the deposition velocity
curve is filled in as the surface becomes rougher. Although studies
have been conducted, in wind tunnels, of deposition fluxes to surfaces
such as gravel, grass, and foliage, the situation involving natural
vegetation such as corn, or even pasture, remains uncertain. It is well
known that many plant species have foliage with exceedingly complicated
microscale surface roughness features. In particular, leaf hairs
increase the rate of particle deposition; studies of other factors, such
as electrical charges associated with foliage and stickiness of the
surface, indicate that a natural canopy might be considerably different
from a simplified surface that is suitable for investigation in the
laboratory and wind tunnel.
Caution should be exercised in extending laboratory studies using
artificially-produced aerosol particles to the situation of the
deposition of acidic quantities. Special concern is associated with the
hygroscopic nature of many acidic species. Their growth as they enter
into a region of high humidity and their liquid nature when they strike
the surface are both potentially important factors that might work to
increase otherwise small deposition velocities. Moreover, there is
evidence that acidic species, especially sulfates, might be carried by
larger particles; the rates of deposition of such complicated particle
structures are essentially unknown. However, the shape of particles can
have a considerable influence upon their gravitational settling speed
and probably on their impaction characteristics as well.
It is not clear to what extent special considerations appropriate
for acidic species, such as those mentioned above, contribute to the
finding of unexpectedly high deposition velocities for atmospheric
7-57
409-261 0-83-20
-------
sulfate particles (sometimes exceeding 0.5 cm s-1), as reported in
some recent North American studies. European work has been fairly
uniform in producing velocities closer to 0.1 cm s-1, while North
American experience has generated larger values.
It is informative to consider the flux of any airborne quantity to
the surface underneath in terms of an electrical analog, the so-called
resistance model developed initially in studies of agrometeorology. In
this model, the flux of the atmospheric property in question is
identified with the flow of current in an electrical circuit; individual
resistances can then be associated with readily identifiable atmospheric
and surface properties. While the electrical analogy has obvious
shortcomings, it permits an easy visualization of many contributing
processes and enables a comparison of their relative importance.
Micrometeorological studies of the fluxes of atmospheric heat and
momentum show that the aerodynamic resistance to transfer (i.e., the
resistance to transfer between some convenient level in the air and a
level immediately above the quasi-laminar layer) ranges from between 0.1
s cnrl in strongly unstable, daytime conditions, to more than 10 s
cnrl in many nocturnal cases.
There are several resistance paths that permit gaseous pollutants
to be transferred into the interior of leaves. An obvious pathway is
directly through the epidermis of leaves, involving a cuticular
resistance. An alternative route, known to be of significantly greater
importance in many cases, is via the pores of leaves, involving a
stomatal resi stance that controls transfer to within stomatal cavities,
and a subsequent mesophyllic resistance that parameterizes transfer from
substomatal cavities to leaf tissue.Comparison among resistances to
transfer for water vapor, ozone, sulfur dioxide, and gases that are
similarly soluble and/or chemically reactive, shows that in general such
quantities are transferred via the stomatal route, whenever stomata are
open. Otherwise, cuticular resistance appears to play a significant
role. Cuticular uptake of ozone and of quantities like NO and NOg
appears to be quite significant, whereas for S02 this pathway appears
to be less important. When leaves are wet, such as after heavy dewfall,
uptake of sulfur dioxide is exceedingly efficient until the pH of the
surface water becomes sufficiently acidic to impose a chemical limit on
the rate of absorption of gaseous S02. However, the insolubility of
ozone causes dewfall to inhibit ozone dry deposition.
The same conceptual model can be applied to the case of particle
transfer with considerable utility. While the roles of factors such as
stomatal opening become less clear when particles are being considered,
the concept of a residual surface resistance to particle uptake appears
to be rather useful. Studies of the transfer of sulfate particles to a
pine forest have shown that this residual surface resistance is of the
order of 1 to 2 s cnrl. it appears probable that substantially larger
values for residual surface resistance will be appropriate for non-
vegetated surfaces, especially to snow, for which the values are more
likely to be approximately 15 s cnrl. At this time, an exceedingly
limited quantity of field information is available; however, it appears
7-58
-------
that in North American conditions the surface resistance to uptake of
sulfate particles will be in the range 1.5 to 15 s cm-1.
While sulfate particles have received most of the recent emphasis,
the general question of acidic deposition requires that equal attention
be paid to nitrate and ammonium particles. There is no information
regarding the deposition velocities of these particles, but likewise
there is no strong indication that they are different from the case of
sulfate.
Regarding trace gas uptake, sulfur dioxide has received the
majority of recent attention. Chamber studies and some recent field
work indicate that highly reactive materials such as hydrogen fluoride
(and presumably iodine vapor, nitric acid vapor, etc.) are readily taken
up by a vegetative surface, whereas a second set of pollutants,
including S02, N02, and 03, seems to be easily transferred via
stomata, and a third category of relatively unreactive trace gases is
poorly taken up.
Transfer to water surfaces presents special problems, especially
when the surface concerned is snow. As mentioned above, surface
resistances to particle uptake by snow appear to be of the order 15 s
cnrl. Soluble gases will be readily absorbed by all water surfaces,
so equivalence to transfer of water vapor might be expected. An
important exception occurs in the case of S02, in which case absorbed
S02 can increase the acidity of the surface moisture layer to the
extent that further S02 transfer is cut off. Trace gas transfer to
liquid water surfaces is influenced by the Henry's Law constant.
Wind tunnel studies of particle transfer to water surfaces all show
exceedingly small deposition velocities of particles in the 0.1 to 1
urn size range. Several workers have suggested mechanisms by which
larger deposition velocities might exist in natural circumstances; for
example, the growth of hygroscopic particles in highly-humid, near-
surface air can cause accelerated deposition of such particles, and
breaking waves might provide a route that bypasses the otherwise
limiting quasi-laminar layer in contact with the surface. Once again
field observations are lacking.
While large deposition velocities of soluble trace gases to open
water surfaces might appear quite likely, water bodies are frequently
sufficiently small that an air-surface thermal equilibrium cannot be
achieved. Air blowing from warm land across a small, cool lake, for
example, will not rapidly equilibrate with the smooth, cooler surface.
Flow will then be stable and largely laminar, with the consequence that
very small deposition velocities will apply for all atmospheric
quantities. In many circumstances, especially in daytime summer
occasions, deposition velocities are likely to be so small as to be
disregarded for all practical purposes. On the other hand, during
winter when the land surface is frequently cooler than the water, the
resulting convective activity over small water bodies will induce the
air to come into fairly rapid equilibrium with the water, and rather
7-59
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high deposition velocities (in agreement with the open water surface
expectations) will probably be attained.
An associated special case concerns the effect of dewfall, which
can accelerate the net transfer of trace gases and particles in some
circumstances. The velocities of deposition involved are small;
however, they permit an accumulation of material at the surface in
conditions in which the atmospheric considerations are likely to predict
minimal rates of exchange (i.e., limited by stability to an extreme
extent). When surface fog exists, the highly humid conditions will
permit airborne hygroscopic particles to nucleate and grow rapidly.
This process provides a mechanism for cleansing the lower layers of the
atmosphere of most airborne acidic particles. The small fog droplets
that are formed around the hygroscopic acidic nuclei are transferred by
the classical process of fog interception, to foliage and other surface
roughness elements.
Recent workshops (e.g., Hicks et al. 1981) have concluded that it
is not possible to measure the dry deposition of acidic atmospheric
materials by using exposed collection vessels because they fail to
collect trace gases and small particles in a manner that can be related
in a direct fashion to natural circumstances. However, surrogate
surface methods appear to be useful in indicating space and time
variations of deposition in some cases, and may provide reasonable
estimates of fluxes to individual leaves under some conditions. It is
possible to measure the flux of some airborne quantities by micro-
meteorological means, without interfering with the natural processes
involved. These studies, and laboratory and wind tunnel investigations,
provide evidence that the controlling properties in the deposition of
many trace gases and aerosols are associated with surface structure,
rather than with atmospheric properties. The exception to this
generalization is the nocturnal case, in which atmospheric stability may
often be sufficient to impose a severe restriction on the rate of
delivery of all airborne substances to the surface below.
7.7 CONCLUSIONS
The conclusions presented above can be summarized as follows:
o Dry deposition of small aerosol particles and trace gases is a
consequence of many atmospheric, surface, and pollutant-related
processes, any one of which may dominate under some set of
conditions. The complexity of each individual process makes it
unlikely that a comprehensive simulation will be developed in
the near future (Section 7.2).
° The convenient simplicity afforded by the concept of a
deposition velocity (or its inverse, the total resistance to
transfer) makes it possible to incorporate dry deposition
processes in models in a manner adequate for modeling and
assessment purposes. The simplicity of the deposition velocity
7-60
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approach imposes limitations on its application. For example,
using average deposition velocities is inappropriate when time-
or space-resolved details of deposition fluxes are needed
(Section 7.2.1).
Sufficient information is known about the processes controlling
the deposition of trace gases that in many instances deposition
velocities can be considered to be known functions of properties
such as wind speed, atmospheric stability, surface roughness,
and biological factors such as stomatal aperture. Impr«*t< nt
exceptions concern the case of insoluble (or poorly soluble)
gases, and deposition to non-simple surfaces such as forests in
rough terrain (Section 7.2).
The deposition of particles larger than about 20 ym diameter
is controlled by gravity and can be evaluated using the
straightforward Stokes-Cunningham relationship. Smaller
particles are also influenced by gravity, and many will
contribute to the deposition of acidic and acidifying
substances (Sections 7.2.2 and 7.2.3).
The deposition of small particles remains an issue of
considerable disagreement. On the whole, model predictions
agree with the results of laboratory and wind tunnel studies, at
least for test surfaces that are usually smoother than pasture,
but field experiments provide data that indicate greater
deposition velocities. The reasons for the apparent
disagreement are not yet clear (Sections 7.3, 7.4.2, and 7.5.2).
Over water surfaces, there are almost no field data on the
deposition of small particles. Different models have been put
forward, predicting a wide range of deposition velocities. At
this time, there is little evidence that would permit us to
choose among them. The situation for trace gases like sulfur
dioxide and ammonia is much better. On the whole, models agree
with the available field data, although there is disagreement
among the models on how factors such as molecular diffusivity
should be handled (Sections 7.2.7 and 7.5.2).
Dry deposition to the surfaces of materials used in the
construction of buildings, monuments, etc., can be measured in
many instances by taking sequential samples of the surface over
extended periods. However, many of the drawbacks of surrogate-
surface sampling are also of concern here (Section 7.2.8).
Particulate material at the surface can creep, bounce, and
eventually resuspend under the influence of wind gusts. The
large particles entrained in this way can cause a local
modification of the acidic deposition phenomenon that is
associated with accumulation-size aerosol particles and trace
gases of more distant origin (Section 7.2.10).
7-61
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For both case-study measurement purposes and for long-term
monitoring, accurate measurements of pollutant air
concentrations are necessary. For monitoring purposes,
measurement of airborne pollutant concentrations in a manner
carefully designed to permit evaluation of dry deposition rates
by applying time-varying deposition velocities specific to the
pollutant and site in question appears to be the most attractive
option (Section 7.3).
Micrometeorological methods for measuring dry deposition fluxes
have been developed from the techniques conventionally used to
determine fluxes of sensible heat, moisture, and momentum. These
methods are technologically demanding, and their use in routine
monitoring applications is not yet possible (Section 7.3.3).
7-62
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Parts A and B, PNL Ann. Report to the USAEC, DBER, 1973; BNWL-1850, Pt.
3, Battelle-Northwest, Richland, WA; available from NTIS, Springfield,
WA.
Slinn, W. G. N. 1976a. Formulation and a solution of the diffusion,
deposition, resuspension problem. Atmos. Environ. 10:763-768.
7-71
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SI inn, W. G. N. 1976b. Dry deposition and resuspension of aerosol
particles - a new look at some old problems; pp. 1-40 of
Atmospheric-Surface Exchange of Participate and Gaseous Pollutants -
1974, R. J. Englemann and G. A. Sehmel, (Coord.); available as ERDA
CONF-740921 from NTIS, Springfield, VA.
SI inn, S. A. and W. G. N. Si inn. 1980. Predictions for particle
deposition on natural waters. Atnos. Environ. 14:1013-1016.
Slinn, W. G. N., L. Hasse, B. B. Hicks, A. W. Hogan, D. Lai, P. S. Liss,
K. 0. Munnich, G. A. Sehmel, and 0. Vittori. 1978. Some aspects of the
transfer of atmospheric trace constituents past the air-sea interface.
Atmos. Environ. 12:2055-2087.
Spedding, D. J. 1969. Uptake of sulphur dioxide by barley leaves at
low sulphur dioxide concentrations. Nature 224:1229-1231.
Twomey, S. 1977. Atmospheric Aerosols. Elsevier Scientific Publishing
Company, Amsterdam. 302 pp.
Wason, D. T., S. K. Wood, R. Davies, and A. Lieberman. 1973. Aerosol
transport. Particle charges and re-entrainment effects. J. Colloid
Interface Sci. 43:144-149.
Wedding, J. B., R. W. Carlson, J. J. Stiekel, and F. A. Bazzaz. 1975.
Aerosol deposition on plant leaves. Env. Sci. and Technol. 9:151-153.
Wesely, M. L. and B. B. Hicks. 1977. Some factors that affect the
deposition rates of sulfur dioxide and similar gases on vegetation. J.
Air Pollut. Contr. Assoc. 27:1110-1116.
Wesely, M. L. and B. B. Hicks. 1979. Dry deposition and emission of
small particles at the surface of the earth. Proceedings Fourth
Symposium on Turbulence, Diffusion and Air Quality (Reno, NV, 15-18
January). Am. Meteorol. Soc., Boston, MA. pp. 510-513.
Wesely, M. L., D. R. Cook, R. L. Hart, B. B. Hicks, J. L. Durham, R. E.
Speer, D. H. Stedman, and R. J. Trapp. 1982a. Eddy-correlation
measurements of dry deposition of particulate sulfur and submicron
particles. Proc. Fourth International Conference on Precipitation
Scavenging, Dry Deposition, and Resuspension. Santa Monica, California,
29 November - 3 December, in press.
Wesely, M. L., J. A. Eastman, D. R. Cook, and B. B. Hicks. 1978.
Daytime variation of ozone eddy fluxes to maize. Boundary-Layer
Meteorology 15:361-373.
Wesely, M. L., J. A. Eastman, D. H. Stedman, and E. D. Yalvac. 1982b.
An eddy-correlation measurement of N02 flux to vegetation and
comparison to 03 flux. Atmos. Environ. 16:815-820.
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Wesely, M. L., B. B. Hicks, W. P. Dannevik, S. Frisella, and R. B.
Husar. 1977. An eddy correlation measurement of particulate deposition
from the atmosphere. Atmos. Environ. 11:561-563.
Whelpdale, D. M. and R. W. Shaw. 1974. Sulphur dioxide removal by
turbulent transfer over grass, snow, and other surfaces. Tellus 26:
196-204.
Whitby, K. T. 1978. The physical characteristics of sulfur aerosols.
Atmos. Environ. 12:135-139.
Williams, R. M., M. L. Wesely, and B. B. Hicks. 1978. Preliminary eddy
correlation measurements of momentum, heat, and particle fluxes to Lake
Michigan. Argonne National Laboratory Radiological and Environmental
Research Division Annual Report. Jan. - Dec. 1978. ANAL-7865, Part
III, pp. 82-87.
Winkler, E. M., and E. J. Wilhelm. 1970. Saltburst by hydration
pressures in architectural stone in urban atmosphere. Geol. Soc.
America Bull. 81:576-572.
Yudine, M. I. 1959. Physical considerations on heavy-particle
diffusion, pp. 185-191. lr± Advances in Geophysics, Volume 6. H. E.
Landsberg and J. van Mieghem, eds. Academic Press, New York.
7-73
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THE ACIDIC DEPOSITION PHENOMENON AND ITS EFFECTS
A-8. DEPOSITION MONITORING
8.1 INTRODUCTION (G. J. Stensland)
The previous two chapters have discussed the deposition processes
by which acidic and acidifying substances in the atmosphere impact on
various receptors. Wet deposition in the form of rain, fog, and snow
and dry deposition of gases and partiuclate matter have been addressed.
This chapter considers both wet deposition monitoring during
periods of precipitation and dry deposition monitoring during periods of
no precipitation. Techniques are discussed for collecting deposition
data on a routine basis to determine the broad spacial patterns of
deposition and their changes over time. Most of the techniques are also
applicable for measuring deposition over smaller space and time scales,
such as in research projects to study transformation and scavenging
processes (Chapters A-4, A-6 and A-7). The first section of this
chapter will discuss techniques and data bases for wet deposition
networks. The next section will emphasize dry deposition techniques.
The second major purpose of this chapter is to present and discuss
data available from routine, long term networks. Such data for dry
deposition are limited and therefore are combined with the techniques
discussion in Section 8.3. Section 8.4 will discuss wet deposition
data. Section 8.5 will examine the data record from glacier studies.
Glaciochemical investigations are given as a tool in historical
delineation of acid precipitation problems and as a bench mark on the
natural background void of anthropogenic pollution and contamination.
Wet deposition monitoring techniques vary with the chemical species
being investigated. This wet deposition discussion will be limited to
the major soluble species in precipitation which account for most of the
measured conductance of the samples. This list would include the
following ions: hydrogen, bicarbonate, calcium, magnesium, sodium,
potassium, sulfate, nitrate, chloride, and ammonium. Experience has
shown that measurements of the last eight ions in the list allow one to
calculate a pH value which is usually in good agreement with the
measured pH value. Samples from remote locations can be strongly
affected by organic acids and are thus one group of exceptions (Galloway
et al. 1982). The fact that we can often successfully calculate the pH
of precipitation samples indicates that the rather small list of
measured ions are probably sufficient for studies of wet deposition
emphasizing the acid precipitation phenomena.
How good are those current network data? Are the networks
adequately distributed and operated to provide a good evaluation of the
8-1
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temporal and spatial variations relative to pH and the acidic and
acidifying substances of interest? Which measurements need improvement,
what are the nature of the improvements, and the reasons for them? Are
surrogate types of air and water quality measurements available for
trend analysis?
The next chapter presents deposition models to predict exposure of
receptors to concentrations of specific pollutants. Such models are
needed to predict deposition over required periods and with required
resolution.
8.2 WET DEPOSITION NETWORKS (G. J. Stensland)
8.2.1 Introduction and Historical Background
The measurement of chemicals in precipitation is not just a recent
endeavor. In 1872, for example, Smith discussed the relationship
between air pollution and rainwater chemistry in his remarkable book
entitled Air and Rain: The Beginnings of Chemical Climatology. Gorham
(1958a) reported that hydrochloric acid should be considered in
assessing the causes of rain acidity in urban areas. Junge (1963)
discussed the role of sea salt particles in producing rain from clouds.
There are several recent reports describing wet deposition networks
and the data generated by them: the Acid Rain Information Book,
prepared by GCA Corporation in 1980 for the U.S. Department of Energy
(GCA 1980); the Battelle Northwest Laboratories (Dana 1980) report for
the American Electric Power Service Corporation; and the Environmental
Research and Technology Incorporated report for the Utilities Air
Regulatory Group (Hansen et al. 1981) are but three examples.
Networks to monitor wet deposition can be physically characterized
by:
1. Space scale—The total area covered by the sampling network.
2. Space density—The area represented by each site in the
network, i.e., network area divided by the number of sites
3. Time scale--The time span during which data were collected at
the network
4. Time density—The frequency of sample collection (the sampling
interval).
Networks have been of all spatial and temporal sizes and densities,
ranging from 1 site operated for only a few days to more than 50 sites
distributed over several countries and operated for over 30 years.
The time and space configurations of networks are dictated by
scientific objectives and available financial resources. Networks are
8-2
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often classified either as research networks or as monitoring networks.
Research networks usually have smaller space and time dimensions than do
monitoring networks. However, the data generated by all types of
monitoring networks are eventually used for research purposes, and the
data from single site research networks are frequently used to monitor
the changes in time of wet deposition. Therefore, characterizing
networks according to monitoring or research purposes does not produce a
unique distinction.
8.2.2 Definitions
Some widely used technical terms that relate to deposition
monitoring are defined as follows:
j>H - For typical rain and melted snow solutions the pH ranges from
3.0 to 8.0. The pH indicates the acidity, i.e., the free hydrogen-ion
concentration, and mathematically pH = -logjo[H+]. Each unit of
decrease on the pH scale represents a 10-fold increase of acidity.
Chemically a pH of 7.0 is approximately neutral (for T = 20 C); a pH of
less than 7.0 is acidic, and a pH of more than 7.0 is alkaline.
Therefore, rain water with a pH less than 7.0 is acidic. However, pure
water in equilibrium with atmospheric carbon dioxide has a pH of about
5.6. Therefore, in practice many scientists adopt 5.6 as the reference
value, with samples of rain and melted snow having pH less than 5.6
referred to as acidic precipitation. This pH = 5.6 reference point will
be adopted for this chapter. However, discussion to follow (Section
8.4.2) will indicate that natural rain in areas unaffected by man can
have pH values of 5.0 or less and therefore the value of 5.6 is more
arbitrary than natural.
A more rigorous chemical discussion of pH is provided in Chapter
E-4, Sections 4.2.2 and 4.4.3.1.
Weighted mean concentration - The mean concentration of a
precipitation constituent such as sulfate for five samples would be
simply the sum of the five concentration values divided by five. The
volume-weighted-mean concentration for five samples for sulfate is the
sum of five products {each sample volume x the sulfate concentration in
the sample) divided by the sum of the five volumes. The precipitation-
weigh ted-mean concentration is calculated in the same way except the
precipitation amount from a standard rain gauge is used instead of the
volume from the precipitation chemistry sampling device. For the ions
generally considered to be conservative when samples are mixed together
(sulfate, nitrate, ammonium, chloride, calcium, magnesium, sodium and
potassium), the weighted mean concentration for five samples is
conceptually the same as the single value that would be measured if all
five samples had been poured into one large container. This is not
conceptually true for non-conservative ions (such as hydrogen and
bicarbonate ions). However, if all the precipitation samples are in
equilibrium with atmospheric carbon dioxide and have pH values less than
about 5.0, then bicarbonate concentrations are relatively small and
8-3
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the hydrogen ion would be conserved in the mixing process. The pH
calculated from the volume- or precipitation-weighted-mean hydrogen
concentration will be referred to in this chapter as the weighted pH.
Precipitation - The term will be used to denote aqueous material in
liquid or solid form, derived from the atmosphere. Dew, frost, and fog
are technically included but in practice poorly measured, except by
special instruments.
Acidic rain - A popular term with many meanings; generally used to
describe precipitation with a pH of less than 5.6.
Acidic precipitation - Water from the atmosphere in the form of
rain, sleet, snow, and hail, with a pH of less than 5.6. (This is how
scientists in the past have used the term.)
Wet deposition - A term that refers to: (1) the amount of material
removed from the atmosphere and delivered to the ground by rain, snow,
or other precipitation forms; and (2) the process of transferring gases,
liquids, and solids from the atmosphere to the ground during a
precipitation event.
Dry deposition - A term for (1) all materials deposited by the
atmosphere in the absence of precipitation; and (2) the process of such
deposition.
Total atmospheric deposition - Transfer from the atmosphere to the
ground of gases, particles, and precipitation, i.e., the sum of wet and
dry deposition. Atmospheric deposition includes many different types of
substances, nonacidic as well as acidic.
Acidic deposition - The transfer from the atmosphere to the ground
of acidic substances, via wet or dry deposition.
8.2.3 Methods, Procedures, and Equipment for Wet Deposition Networks
For data comparability, it would be ideal if all wet deposition
networks used the same equipment and procedures. In reality, this
rarely happens. The following discussion outlines procedures and
equipment which vary among networks, past and present, and indicates how
the data user should check for data comparability.
Site selection - The selection of monitoring sites is based on
criteria which should be described in the network documentation. The
siting criteria depend on the objectives of the network.
Sample containers - The containers for collecting and storing
precipitation vary, depending on the chemicals to be measured.
Reuseable plastic collection containers are currently used in most
acidic wet deposition networks. However, they are unacceptable for
monitoring pesticides in precipitation. Glass collection containers are
8-4
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considered less desirable than plastic ones (Galloway and Likens 1979).
Frequent quality control blank checks are necessary to monitor
procedures for cleaning containers, and great care is necessary to
maintain acceptably low blank levels. Acid washing procedures can
potentially produce precipitation pH levels that are too low, while
detergent washing may have the opposite effect. Several networks now
avoid these washing procedures.
Sampling mode - There are three sampling modes. In bulk sampling
the collection container is continuously exposed to the atmosphere for
sampling and thus collects a mixture of both wet and dry deposition.
Bulk sampling has been used frequently in the past and is still often
used for economic reasons. For studies of total deposition, wet plus
dry, bulk sampling may be suitable. A problem is that exactly what
component of dry deposition is sampled by open containers is unknown.
The continuously exposed containers are subject to varying amounts of
evaporation unless equipped with a vapor barrier. For studies to
determine the acidity of rain and snow samples, bulk data pH must be
used with great caution (only in conjunction with comprehensive system
blank data). For wet deposition sites that will be operated for a long
time (more than 1 year), site operation and central laboratory expenses
are large enough that wet-only or wet-dry samplers should be used
instead of bulk samplers to maximize the scientific output from the
project.
For both wet-only and wet-dry sampling the automatic device has
been sometimes replaced by an observer making manual container changes,
an undesirable alternative except in very special situations.
In wet-only sampling, dry deposition is excluded from the
precipitation samples by automatic devices that uncover the sampling
containers only during precipitation events. Three types of automatic
wet-only samplers were evaluated for event collection in a Pennsylvania
State University study, which found differences in both the reliability
of the instruments and the chemical concentrations in the samples
(dePena et al. 1980). In wet-dry sampling, the automatic collecting
device includes one container to capture wet deposition and a second
container to capture dry deposition where a precipitation sensor
activates a motor which moves a cover from one container to the other.
As with bulk sampling, the dry container of a wet-dry sampler collects a
not-well-defined fraction of the total dry deposition.
In sequential sampling, a series of containers are exposed to the
atmosphere to collect wet deposition samples, with consecutive advances
to new containers being triggered on a time basis, a collected volume
basis, or a combination. Sequential samplers can be rather complicated
and are usually operated only for short time periods during specific
research projects. Again an observer sometimes replaces the automatic
device to provide manual sequential sampling.
Field measurements - Conductivity, pH, sample weight or volumes,
and rainfall amount are frequently measured at field laboratories.
8-5
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Making these additional measurements requires that site operators have
greater training and work longer periods for each sample than operators
at sites where samples are only collected and forwarded to a central
analytical laboratory. Rainfall amount determined with a standard rain
gauge is necessary as it provides an assessment of the fraction of the
precipitation captured by the precipitation chemistry stamp!er.
Sample handling - Chemical changes with time in the sample are
decreased through the addition of preservatives to prevent biological
change, refrigeration, aliquoting, and filtering. Peden and Skowron
(1978) have reported that filtering is more effective than refrigeration
for stabilizing Illinois samples. When the filtering procedure is used,
it is important to obtain frequent filter blank samples, because the
chemistry of relatively clean rain samples can be easily altered.
Analytical methods - Appropriate analytical methods are available
to measure the major ions found in precipitation, but special
precautions are necessary because the concentrations are low; thus, the
samples are easily contaminated. Although pH is deceptively easy to
determine with modern equipment, achieving accurate results requires
special care because of the low ionic strength of rain and snow samples.
Frequent checks with low ionic strength reference solutions are required
to avoid the frequent problem of malfunctioning pH electrodes.
Data screening - Network data are in effect screened out if
technicians in the field or at the central laboratory discard samples
because they look "unduly contaminated." After samples are analyzed,
the data can be flagged or removed because samples were not collected in
the field according to standard protocol or because the data are
statistical outliers.
Quality control reports - For most wet deposition networks, too few
quality control checks are performed routinely, too few procedures and
results undergo continuous evaluation, and too few results are
summarized into formal written quality assurance reports. Quality
control reports are often considered analytical laboratory reports that
document the methods used to measure chemical parameters and the bias
and precision of the analytical methods. However, for wet deposition
monitoring networks, a much greater effort should be made to develop a
quality program that addresses all of the steps resulting in the data
base. While quality control reports can be easily produced for the
analytical methods, some of the greatest uncertainties in comparing data
from different networks involves estimating the bias resulting from
differences in sampling mode, sample handling, and related aspects.
Quality assurance programs are very costly. Therefore, a network
must be quite large and be planned to run for a long time to warrant
implementing an elaborate quality assurance program. A research project
that operates five sites for 1 year, for example, generally cannot
afford to produce an array of written documents to describe all the
quality control procedures and data.
8-6
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Because different networks collect daily samples, weekly samples or
monthly samples, the data user is often faced with deciding whether two
different data sets are comparable. Thus, quality control reports for
the separate networks should contain all the information needed to
assess data bias and precision for that network. However, the use of
colocated sites for various networks is one of the most direct ways to
assess network design differences. Several colocated sites sites are
necessary to evaluate network data differences at sites having different
meteorological and pollution environments. The operation of co-located
sites should be continuous rather than a one-time endeavor.
8.2.4 Wet Deposition Network Data Bases
The wet deposition data bases available for North America have been
summarized by many authors (e.g., Eriksson 1952, Niemann et al. 1979,
Miller 1981, Wisniewski and Kinsman 1982). Miller points out that the
history of precipitation chemistry measurements in North America has
been very erratic, with networks being established and disbanded without
thought of long-term considerations. Miller suggested one possible time
grouping of network data:
1. 1875-1955, the period when agricultural researchers measured
nutrients in precipitation to determine the input to the soil
system;
2. 1955-1975, the period when atmospheric chemists were measuring
the major ions in precipitation to better understand chemical
cycles in the atmosphere; and
3. 1975-present, the period when network measurements were often
primarily to evaluate ecological effects.
Table 8-1 (Miller 1981) summarizes the "agricultural data bases" taken
from the review by Eriksson (1952).
Table 8-2 summarizes some regional- and national-scale wet
deposition networks in Canada and the United States that have begun
operation since 1955. These networks were generally not established to
monitor acidic precipitation. The first two are no longer in operation.
The PHS/NCAR and EML-DOE networks include sites influenced by large
urban areas and thus are not as useful in addressing acidic
precipitation issues on larger scales as are other networks. All the
networks followed the pattern of the Junge network in measuring the
major inorganic ions that account for most of sample conductance.
Sulfate was measured in all the networks; pH was not measured in the
Junge network.
In addition to regional- and national-scale wet deposition
networks, local networks also exist. These local networks:
1. may consist of only one site (e.g., Larson and Hettick 1956),
or 85 sites concentrated in a rather small area (Gatz 1980);
8-7
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TABLE 8-1. AGRICULTURAL DATA BASES (1875-1955)
(ADAPTED FROM ERIKSSON 1952)
Period
Number of studies
Locations of sites
1875 - 1895
1895 - 1915
1915 - 1935
1935 - 1955
3
7
8
Missouri, Kansas, Utah
Ottawa, Iowa, Tennessee,
Wisconsin, Illinois, New York,
Kansas
Kentucky, Oklahoma, New York,
Illinois, Texas, Virginia,
Tennessee
Alabama, Georgia, Indiana,
Minnesota, Mississippi,
Tennessee, Massachusetts
8-8
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TABLE 8-2. SOME NORTH AMERICAN WET DEPOSITION DATA BASES (1955-PRESENT)
00
APPROXIMATE
NETWORK
National
Junge
PHS/NCARb
WMO/EPA/NOAAC
Canadian
CANSAP0
NADPe
PERIOD
1955-1956
1959-1966
1972-P resent
1977-P resent
1978-Present
NUMBER OF
SITES
60
35
10
59
110
SAMPLING
MODEa
W-M
W
W
W
W-D
SAILING
INTERVAL
Daily, (with monthly
compositing)
Monthly
Monthly (Joined NADP in
1980)
Daily, (with monthly compos
ing) (monthly before 1980
Weekly
Regional
US Geological
Survey Eastern
(USGS)
Canadian Centre
for Inland
Waters (CCIW)
Tennessee Valley
Authority
MAP3sf
1964-Present 18
1969-Present 15
1971-Present 11
1976-Present 9
W
W-D
W
Monthly
Biweekly
Daily
-------
TABLE 8-2. CONTINUED
00
1— >
o
NETWORK
Canadian APN9
EML-DOEh
UAPS1
U.S. EPAj
Great Lakes
NUMBER OF
PERIOD SITES
1978-Present 6
1976-Present 7
1978-Present 19
1977-Present 30
SAMPLING SAMPLING
MODE3 INTERVAL
W Daily
B, W-D Monthly
W Daily
B, W Monthly and Weekly
aB for bulk, W for wet only with automatically opening device, W-M for wet only via manual
operation, W-D for wet-dry with automatic device.
bU.S. Public Health Service/National Center for Atmospheric Research.
cWorld Meteorological Organization/U.S. Environmental Protection Agency/National and Oceanic
and Atmospheric Administration. These sites are now part of NADP.
dCanadian Network for Sampling Precipitation.
National Atmospheric Deposition Program.
^Multistate Atmospheric Power Production Pollution Study.
^Canadian Air and Precipitation Network.
Environmental Measurements Laboratory of the U.S. Department of Energy.
Utility Acid Precipitation Study.
JUnited States Environmental Protection Agency.
-------
2. may have operated for a year (e.g., the central Illinois study,
Larson and Hettick 1956); or much longer (e.g., the Hubbard
Brook data base, Likens 1976); and
3. may have studied a particular pollution source (e.g., the St.
Louis area, Gatz 1980) or the plume from power plants (Li and
Landsberg 1975, Dana et al. 1975).
Some of the local network data have been very useful in interpretating
time trends of chemical concentrations in precipitation.
Wisniewski and Kinsman (1982) have prepared a detailed tabultation
of national, regional, and state or province networks currently in
operation in the United States and Canada, and Mexico. A total of 69
networks are described.
Whelpdale (1979) has prepared a tabulation of seven major wet
desposition networks and programs in the world. These include CANSAP,
MAP3S, and NADP (which have been included in Table 8-2); the
Organization for Economic Cooperation and Development (OECD) network to
study the long-range transport of air pollutants which operated from
1972 to 1975; and the three currently operating networks summarized in
Tables 8-3 through 8-5. Most of the World Meteorological Organization
(WMO) sites (see Table 8-3) in Canada, the United States, and Europe are
sites operated as part of the CANSAP, NADP, or Economic Commission for
Europe (ECE) networks. The ECE network (see Table 8-4) is noteworthy in
that (1) only pH and sulfate are required to be measured in the
precipitation samples (for many sites other major ions are also
measured), (2) aerosol sulfate and gaseous sulfur dioxide must be
measured, (3) each participating country has one or more laboratories to
perform chemical analyses on samples collected in that country, and (4)
the sample collection period is 24 hours. The European Atmospheric
Chemistry Network (EACN) (see Table 8-5) is noteworthy in that its early
data provided evidence that Scandanavian precipitation is acidic. Over
the last 20 years, these data have been central to discussions of why
Scandanavian precipitation is so acidic and what adverse effects are
linked to this acidity. Whelpdale (1979) and Wall en (1981) discuss the
European and world networks and provide maps of site locations.
8.3 MONITORING CAPABILITIES FOR DRY DEPOSITION (B. B. Hicks)
8.3.1 Introduction
Dry deposition delivers materials to the surface in both solid and
gaseous phases, and sometimes in liquid (e.g., when the humidity is so
great that "solid" hygroscopic particles are, in fact, wet), without the
convenience of a natural process (precipitation) to organize and
concentrate its delivery. Rainfall delivers pollutants in irregular but
comparatively intense doses, in a manner that permits relatively simple
sampling. Dry processes are far slower yet more continuous. Neverthe-
less, assessments such as by Galloway and Whelpdale (1980) and by
Shannon (1981) suggest that wet and dry deposition processes are of
8-11
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TABLE 8-3. CHARACTERISTICS OF THE WORLD METEOROLOGICAL ORGANIZATION
(WHO) AIR POLLUTION NETWORK (WHELPDALE 1979)
Program name: WMO BACKGROUND AIR POLLUTION NETWORK.
Organizatlon/Country/Agency: World Meteorological Organization
Purpose: to obtain, on a global and regional basis, background
concentration levels of atmospheric constituents, their variability and
possible long-term changes, from which the influence of human activities
on the composition of the atmosphere can be judged.
Number of stations: approximately 110.
Location; in 72 countries throughout the world.
Period of program: from 1970 continuing indefinitely.
Collector type: recommended procedure is to use either open buckets
during periods of precipitation only, or automatic precipitation
collectors with a tight seal. Some baseline stations and regional
stations with extended programs also do air and particulate sampling
(procedures are not yet standard).
Parameters: sample volume, 50*2-, ci~, NH^, Ca2+, Mg2+ Na2+, K+,
alkalinity or acidity, electrical conductivity, pH.
Collection period: 1 month; some European stations have adopted the 24
hour sampling period of the Economic Commission for Europe (ECE)
Cooperative Program for Monitoring and Evaluation of the Long-Range
Transmission of Air Pollutants in Europe (EMEP).
Quality control: U.S. Environmental Protection Agency - sponsored
reference precipitation sample exchanges.
Contact: Secretary General, World Meteorological Organization, Geneva,
Switzerland. Directors, National Meteorological Services.
Data/Reports/References; WMO 1974, WMO Operations Manual for Sampling
and Analysis Techniques for Chemical Constituents in Air and
Precipitation, WMO No. 299, Geneva.
WMO/EPA/NOAA, 'Atmospheric Turbidity and
Precipitation Chemistry Data for the World', Environmental Data Service,
NCC, Asheville (annually).
8-12
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TABLE 8-4. CHARACTERISTICS OF THE ECONOMIC COMMISSION FOR EUROPE
(ECE) AIR POLLUTION NETWORK (WHELPDALE 1979)
Program name: COOPERATIVE PROGRAM FOR MONITORING AND EVALUATION OF THE
LONG-RANGE TRANSMISSION OF AIR POLLUTANTS IN EUROPE.
Orgam'zation/Country/Agency: Economic Commission For Europe.
Purpose: to provide governments with information on the deposition and
concentration of air pollutants, as well as on the quantity and
significance of long-range transmission of pollutants and fluxes across
boundaries.
Number of stations: operating or planned by 1979 - precipitation 42,
aerosol 52, gas 53 (~ 1 station/105 km2).
Location: Europe and Scandinavia
Period of program: 1977 to 1980 (first phase).
Collector type; for precipitation: open polyethylene gauges and some
automatic collectors; for air: pump and bubbler going to pump and filter
pack; for particles: pump and bubbler going to pump and filter pack.
Parameters: precipitation: pH, S042"; optional - H+, N03", NH4+, Mg2+,
Na+, CT, Ca2+
aerosol: S042-; Opt1onal _ TSP, H+, NH4+
gas: S02; optional- N02
Collection period: 24 hours
Quality control; inter-laboratory sample exchange (NILU); laboratory
quality assurance programs; statistical analysis of data; cation-anion
balance, acidity-pH checks.
Special features: (1) network is part of a larger program which
includes modelling, and comparison of field measurements and model
calculations;
(2) some of these stations are stations in the EACN
(see Table 8-5) and were stations in the Long Range Transport of Air
Pollutants (LRTAP) network.
Contact: H. Dovland, Norwegian Institute for Air Research (NILU),
Box 130, 2001 Lillestrj6m, Norway.
8-13
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TABLE 8-4. CONTINUED
Data/Reports/References: ECE 1977, Cooperative Program for Monitoring
and Evaluation of the Long-Range Transmission of Air Pollutants in
Europe - Recommendations of the ECE Task Force, ECE/ENV/15, Annexe 11,
10 pp.
Data listings will be published regularly by NILU.
8-14
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TABLE 8-5. CHARACTERISTICS OF THE EUROPEAN ATMOSPHERIC CHEMISTRY
NETWORK (EACN) (WHELPDALE 1979x
Program name: EUROPEAN ATMOSPHERIC CHEMISTRY NETWORK (EACN)
Organlzation/Country/Agency: International Meteorological Institute
(IMI), Stockholm, Sweden.
Purpose; initially, to study the transport from the atmosphere to the
ground of some nutrients, particularly nitrogen. It now has a more
general atmospheric chemistry direction, including long-range transport
and acidic rain.
Number of stations: a maximum of about 120 in 1959, currently about 50
( ~ 1 station/105 km2).
Location: Scandinavia and western Europe.
Period of program: started in 1946 in Sweden, expanded to western
Europe in 1955; continuing.
Collector type: funnel and bottle thermostated to collect either rain
or snow; automatic wet-only collectors (Granat type, AAPS type) coming
into use.
Parameters: precipitation amount, pH, conductance, acidity, S042~, Cl",
N03-, NH4+, Na+, K+, Ca2+, Mg2+, HC03-.
Collection period: 1 month
Quality control: inter-laboratory sample exchanges; laboratory quality
assurance programs; cation-anion balance, measured-calculated
conductivity, acidity-pH checks; much analysis of data.
Special features: (1) supplementary measurement programs in Swedish
part of network examine network design aspects;
(2) several sites are equipped with air and particle
sampling systems, primarily to investigate anthropogenic-acidity related
phenomena.
Contact: L. Granat, Department of Meteorology, University of Stockholm,
Arrhenius Laboratory, S-106 91 Stockholm, Sweden.
Data/Reports/References; Granat, L., 1972, Deposition of sulfate and
acid with precipitation over northern Europe, Report AC 20, University
of Stockholm, Department of Meteorology/International Meteorological
Institute, Stockholm, 19 pp.
8-15
409-261 0-83-21
-------
TABLE 8-5. CONTINUED
Granat, L., Soderlund, R. and Back!in, L.,
1977, The IMI Network in Sweden. Present equipment and plans for
improvement, Report AC40, University of Stockholm.
Granat, L., 1978, Sulfate in precipitation as
observed by European Atmospheric Chemistry Network, Atmospheric
Environment 12:413-424.
Data for period 1955-59 published in Tellus by Eriksson.
Subsequent data available from Granat.
8-16
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roughly equal importance in the average deposition of specific chemical
species.
As is explained at length in Chapter A-7, dry deposition rates are
influenced strongly by the nature of the surface and by the configuration
of appropriate sources. Surface emissions are held in close contact with
the ground considerably more than are emissions released at greater
altitudes, so that in the former case rates of dry deposition would be
expected to be greater. As a direct consequence, dry deposition fluxes
must be expected to be highest near sources, whereas the highest rates of
wet deposition of the same pollutants may be found much farther
downstream. Thus, a network designed specifically to study dry
deposition will not be the same as one designed only to study wet.
Nevertheless, the intent of most networks is to obtain the maximum amount
of information on the deposition of pollutants by all processes;
consequently, networks such as that of the U.S. National Atmospheric
Deposition Program (NADP) have emphasized the importance of obtaining
data on both wet and dry deposition rates and amounts.
In Chapter A-7, Section 7.3, considerable attention has been given
to methods by which dry deposition fluxes can be measured. The
techniques discussed are those used for detailed case studies of
deposition fluxes, intended to provide information on the processes that
contribute to the net transfer of pollutants to the surface, and usually
designed to help formulate the deposition process. The emphasis in
Section 7.3 is on trace gases and submicron particles, which appear to be
of major interest in the context of acidic and acidifying deposition.
Few of the methods discussed are capable of long-term routine operation.
The material that follows addresses similar questions, but the present
emphasis will be on methods suitable for long-term monitoring of air
pollution deposition fluxes either by direct measurement or by
application of the deposition parameter!'zations resulting from the
studies described in Chapter A-7. Many of the comments made earlier are
equally applicable here. Repetition will be avoided as much as possible.
8.3.2 Methods for Monitoring Dry Deposition
Essentially two schools of thought on monitoring dry deposition
exist. The first advocates the use of collecting surfaces and the
subsequent careful chemical analysis of material deposited on them. For
particles sufficiently large that deposition is controlled by gravity,
surrogate surface and collection vessels have obvious applicability.
Furthermore, they provide samples in a manner suitable for chemical
analysis using fairly conventional techniques. Collecting vessels have
been used for generations in studies of dustfall; standards governing the
methods used have been in place for a considerable time (ASTM D 1739-70),
and intercomparisons between measuranent protocols have been conducted
(Foster et al. 1974a). Collection vessels gained considerable popularity
following their successful use in studies of radioactive fallout during
the 1950's and 1960's. For some gaseous pollutants, species-specific
surrogate surface techniques have been used to evaluate air
concentrations rather than deposition fluxes. Standards exist concerning
8-17
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sulfation plates used to monitor sulfur dioxide concentrations (ASTM D
2010-65), and once again technique intercomparisons have been conducted
(Foster et al. 1974b).
The second school of thought prefers to infer deposition rates from
routine measurements of air concentration of the pollutants of concern
and of relevant atmospheric and surface quantities. These inferential
methods assume the eventual availability of accurate deposition
velocities suitable for interpreting concentration measurements, and they
assume that accurate concentration measurements can be made. They are
applicable in cases in which deposition is not controlled by gravity,
i.e., for trace gases or small particles. They do not provide samples as
convenient for chemical analysis as do the various surrogate surface
methods, but they do not impose any artificial modification to the
detailed nature of the surface on which deposition is normally occurring.
Clearly, a comprehensive monitoring program would use both
concentration monitoring and surrogate surface methods, since
contributions of neither trace gases nor large particles can be rejected
on the basis of present knowledge.
8.3.2.1 Direct Collection Procedures—There is no question that the
deposition of large particles is adequately monitored by collection
devices exposed carefully over the surface of interest. Deposit gauges
and dustbuckets have been in use in geochemistry for a considerable time,
and their use is well accepted for measuring the rate of deposition of
soil and other airborne particles sufficiently large that their
deposition is controlled by gravity. In the era of concern about
radioactive fallout, dustfall buckets were used to obtain estimates of
radioactive depostion, especially of so-called local fallout immediately
downwind of explosions. There was much concern about how well deposited
particles were retained within collecting vessels. Some workers used
water in the bottom of collectors to minimize resuspension of deposited
material, and others used various sticky substances for the same purpose.
It was recognized that the collection vessels failed to reproduce the
microscale roughness features of natural surfaces. However, this was not
viewed as a major problem because the need was to determine upper limits
on deposition so possible hazards could be assessed.
Much farther downwind, so-called global fallout was shown to be
associated with submicron particles similar to those of interest in the
context of acid deposition. However, most of the distant radioactive
fallout was transported in the upper troposphere and lower stratosphere,
and deposition was mainly by rainfall. The acknowledged inadequacies of
collection buckets for dry deposition collection of global fallout were
of relatively little concern because dry fallout was a small fraction of
the total surface flux.
Special wet and dry collecting vessels were developed and deployed
worldwide. In their most highly-developed form, these devices employed
covers that moved automatically to expose a wet collection bucket when
precipitation was detected and to cover it and expose a dry collection
8-18
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bucket at all other times. The convenience and relative simplicity of
these devices has contributed to their continued acceptance to this day.
A major factor that led to their general acceptance was the finding that
dry and wet collection buckets of the same geometry provided answers that
satisfied the global budget of strontium-90 (Volchok et al. 1970).
However, as mentioned above, worldwide radioactive fallout was primarily
delivered to the surface via precipitation (as much as 95 percent in some
locations). Consequently, an error of a factor of two or three in the
measurement of the residual dry deposition component might not have been
too obvious.
Concern regarding the meaning of col lection-vessel data is not only
recent. Hewson (1951) comments that the limitations of deposit gauges
are like those of rain gauges. Deposit guages are funnel-like collection
devices that have been used for generations. They are familiar to most
meteorologists, and the drawbacks involved are well known (Owens 1918,
Ashworth 1941).
Bucket dry deposition data collected by the NADP have been examined
for evidence of bird droppings and locally suspended soil particles
(Hicks 1982). The results of chemical analyses of two-monthly dryfall
collections were examined for phosphate and calcium concentrations. High
levels of phosphate were considered to be evidence of contamination by
guano, and calcium was used as an indicator of soil-derived particles.
The data indicate frequent contamination of samples by bird droppings and
by soil particles, presumably of local origin. It is obvious, however,
that relatively simple remedial steps can be taken. Prongs arranged
around collecting vessels can be used to minimize the effects of perching
birds and the collectors can be placed sufficiently far above the surface
that wind-blown soil particles will be collected only under extreme
conditions.
A recent comparison of collection devices (Dolske and Gatz 1982)
indicates that buckets of the kind normally used in wet/dry collectors
yield sulfate dry deposition rates averaging about three times the values
provided by flat surrogate surfaces. Hardy and Harley (1958) report
large differences between radioactive fallout dry deposition rates to
buckets and other artificial collection devices and to natural
vegetation.
On all of the grounds mentioned above, there is reason to be
concerned about the use of bucket collection devices for studies of
acidic dry deposition. Surrogate surfaces such as flat, horizontal
plates, share many of the conceptual problems normally associated with
collection vessels, yet appear to have considerable utility in some
special circumstances (see Chapter A-7, Section 7.3). For example,
Lindberg and Harriss (1981) and Lindberg et al. (1982) show that the
deposition of trace metals to surrogate surfaces mounted within a forest
canopy is quite similar to the deposition to individual leaves, when
expressed on a unit area basis. Later work (Lindberg and Lovett 1982)
has extended these studies to particle-associated sulfate, nitrate, and
ammonium. In general, it seems that the rates of deposition to surrogate
8-19
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surfaces are within a factor of about two of the rates measured to
foliage elements. It is not yet clear how data concerning individual
canopy elements can be combined to evaluate the net removal by a canopy
as a whole.
8.3.2.2 Alternative Methods--The acknowledged limitations of surrogate-
surface and col lection-vessel methods for evaluating dry deposition have
caused an active search for alternative monitoring methods. In general,
these alternative methods have been applied in studies of specific
pollutants for which specially accurate and/or rapid response sensors are
available. The aim of these experiments has not been to measure the
long-term deposition flux, but instead to develop formulations suitable
for deriving average deposition rates from other, more easily obtained
information such as air concentrations, wind speed, and vegetation
characteristics.
Chapter A-7 discusses the processes involved and summarizes a number
of recent experimental case studies. The results obtained in these
detailed experiments are conveniently expressed in terms of the familiar
deposition velocity, which enables deposition fluxes to be deduced
directly from measurements of air concentration. The special case
studies are providing a rapidly expanding body of information concerning
the factors that determine deposition velocities. Once the important
deposition processes are formulated and quantified, it will no longer be
necessary to measure dry deposition fluxes directly since measurements of
atmospheric concentration made in an appropriate manner could be used to
infer them. This philosophy has formed the basis for monitoring networks
in Scandinavia (Granat et al. 1977) and in Canada (Barrie et al. 1980).
It should be noted that using the concentration-monitoring procedure does
not remove completely the necessity for conventional dustfall monitoring
because the purpose of the concentration measurements is to permit
evaluation of dry deposition rates only of those materials that do not
fall under the control of gravity.
Several initiatives are underway to develop micrometeorological
methods for monitoring the surface fluxes of particular pollutants.
Hicks et al. (1980) have summarized a range of potential micrometerologi-
cal methods and have evaluated their potential as routine monitors of dry
deposition fluxes. They conclude that "at present, the most promising
methods for monitoring are eddy accumulation, modified Bowen ratio, and
variance." The first of these has been of special interest, because it
offers the possibility of using slowly-responding chemical monitors to
deduce deposition fluxes, bypassing the usual eddy-correlation
requirement for a fast-response chemical sensor. The method compares air
in updrafts with air in downdrafts (the former having slightly lower
concentrations of depositing pollutants) by measuring each in separate
sampling systems. Estimates of deposition velocity are readily obtained
from such concentration differences, provided the samples are collected
in an appropriate manner. The method has been demonstrated for
meteorological variables (e.g., sensible heat; Desjardins 1977) for which
updraft/downdraft differences are large but has yet to be successfully
demonstrated for a slowly depositing quantity.
8-20
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The techniques loosely classified as "modified Bowen ratio" all
sidestep the need for direct measurement of the pollutant flux itself by
relating some feature of pollutant concentration, such as the vertical
gradient or the concentration variance in a selected frequency band, to
the same characteristic of some better understood quantity for which the
flux is known. Easy interpretation of this sort of information requires
assumptions of similarity and of pollutant source and sink distributions
that are often hard to verify, such as when researchers are working over
forests. The method has been used in tests involving carbon dioxide
(Allen et al. 1974) and ozone (Leuning et al. 1979) but has yet to be
used to monitor pollutant fluxes.
Methods for deducing fluxes of atmospheric quantities from measure-
ments of the variance of their concentration have been developed and
applied primarily in studies of the transfer of sensible heat, moisture,
and momentum. Techniques of this kind might be especially attractive for
some pollutants, but once again a successful system has not been
demonstrated. These three micrometeorological methods are identified by
Hicks et al. (1980) as "possibly worthy for development for use in
monitoring." However, each imposes special sensor requirements that
appear difficult to satisfy. Methods based on measurement of
concentration variance require rapidly responding sensors with low noise
levels and linear response, and the eddy accumulation and modified Bowen
ratio methods involve the acccurate measurement of concentration
differences on the order of 1 percent.
Attempts to improve sampling by surrogate-surface methods are
continuing. Recent comparisons between different kinds of surface and/or
collection vessels have been reported by Dolske and Gatz (1982), Dasch
(1982), and Sickles et al. (1982). Models of deposition processes are
also being improved, and considerable emphasis is being given to the role
of microscale surface roughness features (e.g., in the model studies
reported by Davidson et al. 1982). It must be expected that the lessons
learned in such modeling exercises will be used to improve the similarity
between artificial collection devices and natural surfaces.
In some circumstances, deposition fluxes can be measured directly
using some special technique unique to the occasion. Efforts must be
encouraged to compare fluxes determined by any micrometeorological,
surrogate-surface, or collection vessel technique to the answers obtained
in such special situations, which include suitably calibrated watersheds
(Eaton et al. 1978, Dillon et al. 1982), snowpacks and icefields (Dovland
and Eliassen 1976, Barrie and Walmsley 1978, Butler et al. 1980, Section
8.5), some lakes, and mineral surfaces.
8.3.3 Evaluations of Dry Deposition Rates
The paucity of accurate information on dry deposition rates to
natural landscapes is a continuing problem to ecologists, geochemists,
and meteorologists alike. Although relatively few data exist on which to
base estimates of deposition rates using the techniques outlined above
(and explained in detail in Chapter A-7), it is appropriate to consider
8-21
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in some detail a selected set of information to illustrate the techniques
involved as well as to derive some initial estimates of deposition
fluxes. The data set reported by Johnson et al. (1981) has been selected
for this purpose. These data were obtained by using a limited network of
particle samplers, modified to provide aerosol samples suitable for
subsequent analysis by infrared spectroscopy.1 The sites used were
confined to the northeast quadrant of the United States: State College,
PA; Charlottesville, VA; Rockport, IN; Upton, Long Island, NY; and
Raquette Lake, NY. Between two and three years of data were obtained at
each site, starting during 1977, except for the Raquette Lake site, where
observations started late in 1978. Size-resolved measurements were made
of sulfate, nitrate, ammonium, and total acidity of the aerosol. For the
present, main attention will be given to the three chemical species.
A unique feature of the Johnson et al. data set is the fine time
resolution of the data, designed specifically to enable detailed analysis
of rapidly time-varying atmospheric phenomena. Figures 7-12, 7-13, and
7-14 demonstrate the inherent time dependence of the factors that control
dry deposition, and the resulting strong diurnal cycle of the
depositional flux. The data set of Johnson et al. permits the effects of
this variability to be taken into account.
Figure 8-1 presents average diurnal cycles of sulfate, nitrate, and
ammonium in aerosol measured in the surface boundary layer (at about 2 m
elevation), as given by Johnson et al. (1981). Figure 8-2 shows the
average diurnal cycle of the aerodynamic resistance to transport between
2 m elevation and the surface, deduced from data presented by Hicks
(1981) for arid grassland (actually the Wangara meteorological
experiment; see Clarke et al. 1971) and by Hicks and Wesely (1980) for
transfer to a pine plantation. These two examples are selected to
demonstrate the large differences that occur in atmospheric transport
above surfaces of different aerodynamic roughness. Averages are
constructed over the same time intervals as were used in the aerosol
sampling program.
For the aerosols under present consideration, surface and/or canopy
resistances are not accurately known. However, scrutiny of Table 7-6
(Chapter A-7) and consideration of the related discussion leads to the
conclusion that a value of about 1.5 s cm-1 is likely to be appropriate
for the pine plantation case and about 5 s cm-1 for grassland. It
should be emphasized, however, that considerable disagreement about these
lit is appreciated that these data might be influenced by sampling
difficulties, especially for ammonium and nitrate (see Chapter A-5).
The intent here is to demonstrate the method by which deposition fluxes
can be evaluated from suitably detailed concentration data. The purpose
is not to attempt to quantify the various fluxes in an unequivocal
manner.
8-22
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SULFATE
0.9T 1 0.5
0.8
0.7
1.4
1.2
J I
0.4
0.3
0.7
0.6
AMMONIUM NITRATE
0.2
0.1
0
0.1
1 1 1
i I I
1.0 I I I I J 0.5 I. I I I
1.6 i — 1 0.3
1 1
^V
1 t 1
1
2
1 1 i
1 1
1.2
0.8
1.2
0.8
0.4
0.9
0.7
1 1 1
0.2
0.1
0.2
0.1
0
0.2
0.1
1 1
1 1
1 t t
0 12 24
0 12 24
TIME OF DAY
0 12 24
Figure 8-1. Average diurnal cycles of near-surface concentrations of
sulfate, ammonium, and nitrate aerosol, as reported by
Johnson et al. (1981) for rural sites located at Raquette
Lake (NY; A), Upton, Long Island (NY; B), Rockport (IN; C),
Charlottesville (VA; D), and State College (PA; E).
Concentrations are all in yg nf 3
8-23
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c
u
oo
UJ
CJ
GO
t — I
GO
UJ
a:
Q
O
a:
0
12
TIME OF DAY
18
Figure 8-2. Average diurnal variability of atmospheric resistance to
pollutant transfer to the surface from convenient measuring
heights above the surface, for the cases of a pine plantation
(open circles),and grassland (solid circles). Standard error
bars are drawn wherever they are large enough to be visible.
8-24
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values remains, with many workers preferring to continue with the
approximation 0.1 cm s"1 for the deposition velocity, regardless of the
nature of the surface or the atmosphere. The various arguments that are
involved will not be discussed here. Instead, we will apply the results
of the experimental programs and overlook the fact that many of the
detailed deposition models fail to agree.
To estimate deposition velocities suitable for interpreting the data
of Figure 8-1, we must add these estimates of surface resistance to the
time-varying aerodynamic resistances of Figure 8-2, yielding (as the
inverse of the resulting sums) deposition velocities that have a small
diurnal variation, averaging about 0.59 cm s"1 for the pine forest and
about 0.17 cm s-1 for the grassland. It should be noted, in passing,
that the lack of a strong diurnal cycle of the deposition velocity is a
direct consequence of the assumption that the surface resistance is
relatively large but constant with time, which is known to be erroneous
for the case of trace gas transfer but is presently assumed for particles
in the lack of sufficient understanding to permit a better assumption,
notwithstanding the evidence of Figure 7-15 (Chapter A-7). Once again,
it is clear that surfaces of different kinds will receive substantially
different dry deposition fluxes.
Table 8-6 summarizes the deposition fluxes evaluated using the
deposition velocities determined above and the diurnally varying
concentrations of Figure 8-1. It must be emphasized that the values
quoted are indeed estimates; several potentially important factors are
disregarded. For example, the special circumstances of snow cover have
not been considered. The evaluations given in Table 8-6 are intended to
provide realistic estimates of dry deposition rates to specific
ecosystems rather than precise determinations appropriate for detailed
analysis.
Sheih et al. (1979) have combined deposition data from many
experimental sources with land-use and meteorological information to
produce deposition velocity "maps" for sulfate aerosol. Figure 8-3 (from
Masse and Voldner 1982) is a recent extension of this approach. If
time-averaged concentrations of sulfate in air near the surface are
known, then average deposition rates can be estimated by using the mean
deposition velocities illustrated in the diagram.
As mentioned above, biological factors play an important role in
determining deposition velocities appropriate for the deposition of trace
gases. Stomatal resistance to sulfur dioxide transfer can vary by more
than an order of magnitude between day and night (see Chamberlain 1980,
for example). In consequence, exceedingly strong diurnal cycles of
deposition must be expected and interpretation of trace gas concentration
data obtained over long averaging times might be quite difficult. At
this time, we lack rural trace gas concentration data that can be used to
illustrate this point. However, the difficulties involved can be
illustrated by the conceptual example of a situation in which the
atmosphere aloft supplies some trace gas to surface air at a constant
rate, with concentrations building at night when surface deposition is
8-25
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TABLE 8-6. ESTIMATES OF AVERAGE DRY DEPOSITION LOADINGS TO AREAS OF
FOREST AND GRASSLAND IN THE NORTHEAST UNITED STATES, BASED ON SULFATE,
NITRATE, AND AMMONIUM PARTICLE CONCENTRATION DATA REPORTED BY JOHNSON ET
AL. (1981). THE PARTICLE SIZE RANGE MEASURED WAS 0.3 TO 1.0 MICROMETER
DIAMETER. FLUXES TO FORESTS ARE GIVEN IN BRACKETS. UNITS ARE KG
HA-1 YR-1 OF ELEMENTAL SULFUR AND NITROGEN DELIVERED BY EACH
CHEMICAL SPECIES. NOTE THAT THESE FLUX ESTIMATES ARE BASED ON
PRELIMINARY DATA, INCLUDING RATHER CRUDE EVALUATIONS OF APPROPRIATE
DEPOSITION VELOCITIES. ERRORS OF THE ORDER OF A FACTOR OF
TWO MUST BE EXPECTED.
Sulfur Nitrogen Nitrogen
Location (S04 - S) (N03 - N) (NH4 - N)
Raquette Lake (NY) 0.7 0.01 0.2
(0.5) (0.03) (0.6)
Upton, Long Island (NY) 0.2 0.01 0.3
(0.8) (0.03) (1.0)
Rockport (IN) 0.4 0.02 0.6
(1.3) (0.07) (2.0)
Charlottesville (VA) 0.3 0.01 0.3
(0.9) (0.03) (1.2)
State College (PA) 0.2 0.02 0.3
(0.8) (0.05) (1.0)
8-26
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prohibited by biological factors. In daytime, the vegetated surface will
act as an efficient sink and airborne concentrations near the surface
will be reduced. In this situation, measurements of nighttime
concentrations are essentially irrelevant to depositional flux
calculations, yet they contribute most of the impact on average air
quality that may be of considerable importance for other reasons.
Figure 8-4 (also from Masse and Voldner 1982) shows isopleths of
estimated sulfur dioxide deposition velocity for eastern North America.
The diagram is derived by combining land use descriptions with
meteorological and biological factors, as in the case of Figure 8-3 for
sulfate aerosol. The analysis follows initial work reported by Sheih et
al. (1979). Both of the deposition velocity maps reproduced here provide
estimates typical of conditions in April. At other times, different
distributions of deposition velocity apply.
At this time, no monitoring program in the United States reports air
concentrations of pollutants in a manner such that dry deposition fluxes
of acidic and acidifying pollutants can be readily evaluated, although
several networks offering suitable information have operated for limited
periods (see Hidy 1982, and see Figure 8-5). Such networks are in
operation elsewhere, particularly in Scandinavia (Granat et al. 1977) and
in Canada (Barrie et al. 1980). A wet-chemical device is used in the
Scandinavian network, whereas filter-packs are used in the Canadian. No
measurement method permits accurate measurement of all of the trace gases
and small particles of importance in the context of acid precipitation.
Sampling artifacts are discussed elsewhere in this document, as are
problems associated with isokinetic sampling of particles. Furthermore,
it is obvious that the quality of dry deposition data evaluation from any
such concentration information is at the mercy of the deposition velocity
assumptions made as the intermediate steps. If the need exists for
accurate evaluations of average dry deposition rates of gases and small
particles, then it seens necessary to place almost equal emphasis on the
requirements for accurate concentration data and for reliable and
appropriate deposition velocity evaluations. At the same time, it must
be remembered that none of the various methods for interpreting
concentration data is intended for use in the case of large particles
that fall under the influence of gravity. In this particular case, use
of collection devices remains an obvious preference.
8.4 WET DEPOSITION NETWORK DATA WITH APPLICATIONS TO SELECTED PROBLEMS
(G. J. Stensland)
8.4.1 Spatial Patterns
There is a vast amount of precipitation chemistry data available.
This section will discuss the general spatial patterns for the United
States and Canada. The first set of contour maps will be based on data
from the National Atmospheric Deposition Program (NADP). Although data
from other recent networks could have been included, this would not have
altered the general patterns and could have added some additional
uncertainties since, for example, sampling intervals other than weekly
8-28
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DRY DEPOSITION VELOCITY OF S02 FOR APRIL (cm
r
0.1 - 0.3
0.4 - 0.5
0.6 -0.7
0.8 -1.0
Figure 8-4. Caculated deposition velocities appropriate for sulfur
8-29
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1-HOUR
$02 (ppb)
Figure 8-5. Examples of pollution concentration isopleth information
of the kind suitable for applying deposition velocity
maps such as in Figures 8-3 and 8-4. Shown are the
arithmetic (for sulfur dioxide) and geometric (for sulfate)
means of data obtained during 5 months between August 1977
and July 1978. Adapted from Hilst et al. (1981). •
8-30
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were used. At this time the NADP is the only network with sites
throughout the United States and thus the NADP data will allow for
comparisons between the West and the East, where the acid precipitation
problem is generally perceived to occur.
Concentration and deposition maps will be presented, with the
contours drawn by hand instead of by computer. All objective analysis
and computer plotting packages will not produce identical maps.
Likewise hand-drawn maps will be somewhat subjective. As data values
will be shown on the contour maps in the section, the reader can
determine if he agrees with the contour shapes. Sites with only a few
samples can produce "bulls-eye" contour patterns; this effect has been
minimized by using the hand-drawn contours instead of computer-produced
contours. Because there are year-to-year variations in the average site
concentrations of the ions it would be best in determining the general
spatial patterns to include only sites with several years data.
However, at this time we do not have enough data to adopt this rule.
Therefore for the hand-produced contours in this section, we did not try
to precisely contour the site data values but instead did some
subjective smoothing.
For some ions both the weighted-mean concentrations and the median
concentrations will be included to allow for a comparison of these two
measures of central tendency. For sites with a rather small total
sample number the median probably gives a better estimate of central
tendency than the weighted means because in the latter, one or two
samples with unusually large volumes can produce unreasonably large
weighted means. No corrections for sea-salt influences have been made
for the NADP data shown in this chapter.
For the combined picture of the United States and Canada, data maps
from the U.S./Canada memorandum of Intent (MOD report (which is nearing
completion) were used. In the MOI report only 1980 data are used, and
therefore the reader has yet another type of contour map for purposes of
comparison.
For many studies related to effects annual deposition values are
needed. Other chapters in this document may have selected deposition
values from monitoring networks which provided greater space densities
in the area of concern as well as longer time records. These data can
be compared to the 1980 deposition maps included in this chapter. Some
maps have been included in this chapter for specific use in effects
studies, an example being the nitrogen deposition map which includes
both nitrate and ammonium inputs of nitrogen.
The National Atmospheric Deposition Program (NADP) began in July
1978. By October 1978, 20 sites were operating, mostly in the
Northeast. Figure 8-6 shows the number of weekly samples as of
approximately the end of 1980 for weeks when at least 0.02 in of liquid
equivalent precipitation was collected {NADP 1978, 1979, 1980). The
data were screened at the NADP Central Analytical Laboratory to remove
8-31
-------
Figure 8-6. Map of National Atmospheric Deposition Program site
locations and number of wet deposition samples for
each site thru approximately December 1980 (using
data from NADP, 1978, 1979, and 1980)
8-32
-------
data for samples that were obviously contaminated or collected by
nonstandard procedures. The quantity of data varies from 6 weekly
samples for a California site to 128 for the West Virginia site.
Figure 8-7 shows the median concentration contour pattern for
sulfate. The low site density in some areas and the short data record
for some sites suggest that the depicted patterns will be subject to
change as more data become available. The medians displayed on the
contour map are better indicators of certain tendency for small data
sets than are other statistical parameters. The site data values are
shown on the maps to indicate the degree of subjective smoothing
involved in drawing the contour lines. For example the 2.0 mgA"1
contour line in Figure 8-7, cutting through northern Wisconsin, could
have been placed further north to accommodate the 2.2 mg £~1 value
at the northeastern Minnesota site. However from Figure 8-6 one notes
that the 2.2 mg «,-! value is the median of only six values and thus
can not be considered very reliable. The 2.0 mg £-1 contour line
passes through the north-central Wisconsin site having a median value of
1.3 mg £-1 illustrating that a subjective decision was made to show
rather smooth contour lines instead of lines bent to match each site
value. On most of the maps in this section, contour lines to the left
of an imaginary line from northwestern North Dakota to southeastern
Texas have been dashed to indicate that the site density and length of
data record are such that the contour lines probably do not well
represent the true patterns.
Sulfate in precipitation has a strong seasonal pattern for sites in
the Northeast (Bowersox and dePena 1980, Pack and Pack 1980, Pack 1982).
Thus, several years of data will be required before a very stable annual
average pattern can be expected. Figure 6-16 in Chapter A-6 shows the
seasonal pattern for sulfate and also indicates the great variability
among event samples for sulfate and nitrate.
Consistent with the known emission pattern for sulfur dioxide, the
maximum sulfate concentrations in Figure 8-7 are in the Northeast. The
contour values decrease eastward across New York and New England. The
limited data for Arizona show a sulfate maximum in the Southwest.
Because a similar maximum is present in the calcium map (see Figure
8-11), soil dust may be the major source for this maximum. The arid
site at Bishop, CA, also has an extremely large sulfate value, but only
six samples are available. The sample-volume-weighted-average sulfate
values shown in Figure 8-8 are generally similar to those for the
median values.
Pack (1980) found the MAP3S and EPRI precipitation chemistry data
from August 1978 to June 1979 to be comparable. The precipitation
weighted-average sulfate values in an area from central Illinois to
western Massachusetts were 2.9 mg «,-! or greater. The maximum
sulfate values were 3.3, 3.4, and 3.7 mg £-1 for three sites in Ohio
and Pennsylvania. The five NADP sites in Ohio and Pennsylvania have
volume-weighted average concentrations of 3.3, 3.5, 3.6, 3.7, and
8-33
-------
2/0
,-1
so42-)
Figure 8-7. Map of median sulfate concentrations (mg a " as
for NADP wet deposition samples through approximately
December 1980 (using data from NADP 1978, 1979, and
1980).
8-34
-------
1.0
2.0
Figure 8-8. Map of volume-weighted average sulfate concentrations
(mg SL~L as SO^") for NADP wet deposition samples
through approximately December 1980 (using data from
NADP 1978, 1979, and 1980).
8-35
-------
4.0 mg £-1 for the data record indicated in Figure 8-8. These
values are very similar to those Pack reported.
Figure 8-9 shows the nitrate pattern, which has general
similarities to that for sulfate. Again the higher values in the
northeastern quadrant of the United States are consistent with the known
anthropogenic NOX emission pattern. One difference is that in Figure
8-9 the values in South Dakota and Nebraska are about the same as those
in Ohio but this is not true for sulfate in Figure 8-8. The rather high
nitrate values at the upper plains sites do not seem to be consistent
with known anthropogenic combustion NOX sources. The nitrate maximum
in east central California is questionable because of the small number
of samples (see Figure 8-6). Possible sample evaporation after
collection or enhanced raindrop evaporation must be considered as
partial explanations for the high concentrations of all the ions in the
precipitation of the Southwest. Recent research has indicated that most
of the available air quality data for nitrate in the Northeast are of
limited value because of sampling problems (Spicer and Schumacher
1977); therefore, the precipitation nitrate data have become
increasingly important.
Figure 8-10 shows the contour pattern for the ammonium ion. The
general pattern is very similar to that for nitrate in Figure 8-9. As
for nitrate, the values for the northwest Indiana site are elevated,
probably indicating the effect of the upwind industrial areas. There is
a definite maximum in the upper plains, probably due to ammonia
emissions from livestock production. In particular, there are several
large cattle feedlots in the vicinity of the Nebraska site. Two sites
in New York have elevated values for both ammonium and nitrate but the
site just east of Lake Ontario had only 17 samples (see Figure 8-6).
The ammonium values are lowest in the Northwest. The median values of
0.02 are analytical detection limit values.
Figure 8-11 shows the calcium concentration pattern, the values for
which are very high in the Southwest and relatively high in the upper
Plains. Dust from soils and unpaved roads probably accounts for the
generally elevated calcium levels in the central United States. Urban
and industrial sources may account for the relatively high values at the
site in Indiana. The central Illinois site is an example of a site
surrounded by an area of intensive cultivation, with corn and soybeans
being the major crops in the area. The median calcium concentration
there is surprisingly low, considering the surroundings.
Figure 8-12 shows the chloride concentration pattern. Sites closer
to the major chloride source, the sea, have higher levels.
In addition to the ions displayed in Figures 8-7 through 8-12,
ammonium, magnesium, potassium, and sodium are measured in NADP and most
other networks. The data in Table 8-7 demonstrates the relative
importance of all the ions at three NADP sites. The concentrations in
8-36
-------
Figure 8-9. Map of median nitrate concentrations (mg £-1 as NOg")
for NADP wet deposition samples through approximately
December 1980 (using data from NADP 1978, 1979, and 1980),
8-37
-------
Figure 8-10. Map of median ammonium ion concentrations (mg &~1 as
NH4+) for NADP wet deposition samples through approximately
December 1980 (using data from NADP 1978, 1979, and 1980).
8-38
-------
Figure 8-11.
Map of median calcium concentrations (mg ft,'*-) for NADP
wet deposition samples through approximately December
1980 (using data from NADP 1978, 1979, and 1980).
8-39
-------
Figure 8-12.
Map of median chloride concentrations (mg JT1) for NADP
wet deposition samples through approximately December
1980 (using data from NADP 1978, 1979, and 1980).
8-40
-------
TABLE 8-7. MEDIAN ION CONCENTRATIONS FOR 1979 FOR THREE
NAOP SITES (yeq JT1)
No. Samples
S042-
N03~
Cl"
HC03~ (calculated)
An ions
NH4+
Ca2+
Mg2+
K+
Na+
H+
Cations
Median pH
42
38.9
11.6
8.2
0.3
59.0
5.5
5.0
2.4
0.7
17.6
17.8
49.3
4.75
37
45.8
24.2
4.2
10.3
84.5
37.7
28.9
6.1
2.0
13.7
0.5
88.9
6.31
NYC
49
44.8
25.0
4.2
0.1
74.1
8.3
6.5
1.9
0.4
4.9
45.7
67.7
4.34
aThe Georgia Station site in west central Georgia.
The Lamberton site in southwest Minnesota.
cThe Huntington Wildlife site in northeastern New York.
8-41
-------
cation sum. If all ions are measured and if there is no analytical
uncertainty, then the anion sum would equal the cation sum. In Table
8-7, the values for hydrogen ion concentration, H+, were calculated
from the measured median pH value, and the values for bicarbonate,
HC03~, were calculated by assuming that the sample was in
equilibrium with atmospheric carbon dioxide. Although the sulfate and
nitrate levels shown are similar at the MN and NY sites, the pH differs
greatly due to the much higher levels of the ammonium, calcium,
magnesium, sodium, and potassium ions at the Minnesota site. These ions
are frequently associated with basic compounds. The data in Table 8-7
suggest that the concentrations of all the major ions must be considered
for the time and space patterns of pH to be fully understood. Currently
sites in Ohio, Pennsylvania, New York and West Virginia have the feature
shown for the New York site in Table 8-7 where H+, S042~, and
N(h- are the dominant ions. For the New York site, the acidity
(H*) could be 100 percent accounted for if all the SO^2' had been
sulfuric acid while nitrate as nitric acid could have accounted for
about 50 percent of the acidity. By applying multiple linear regression
analysis, Bowersox and dePena (1980) have concluded for a central
Pennsylvania site that on the average the principal contributor to
(H+) is sulfuric acid, but the acidity in snow is determined
principally by nitric acid.
Figure 8-13 shows the median pH from the NADP data. Except in
Minnesota, western Wisconsin, and southern Florida, the region east of
the Mississippi River has median pH values less than 5.0, while the
Northeast has values less than 4.7. The pH data are frequently reported
as the pH calculated from the sample-volume-weighted hydrogen ion
concentration, which will be referred to as the weighted pH values in
this chapter. When weighted pH values are considered, the Northeast
still has average pH values less than 4.7. However, the weighted pH
values at the Nebraska and southwestern Minnesota sites are 4.95 and
5.14, respectively, compared to median values of 5.95 and 6.19.
Therefore, the averaging procedure needs to be specified in detailed
analyses and comparisons of pH patterns.
Figures 8-14 through 8-23 show data consolidated for 1980 from
NADP, MAP3S, and CANSAP (Barrie and Sirois 1982, Barrie et al. 1982).
Site data were included in the analysis if the site had been in
operation for at least two-thirds of the year. For the CANSAP and MAP3S
sites, precipitation-weighted-average concentrations were calculated and
used in the figures. For NADP sites, sample volume-weighted-average
concentrations were used . Deposition values were calculated by
multiplying the concentrations by the 1980 precipitation amounts.
Contour lines of ion concentrations and depositions were drawn by hand.
The structure in the concentration contours indicates that all site
values were assumed to be equally valid or representative. The authors
elected to not draw contour lines in the western United States due to
the small number of sites. The contour lines for deposition have more
structure than appears justified. This resulted from using the
concentration field to calculate deposition values at the 250 Class I
Canadian weather service sites and on a 100 km x 100 km grid in the
8-42
-------
Figure 8-13. Map of median pH for NADP wet deposition samples through
approximately December 1980 (using data from NADP 1978,
1979, and 1980).
8-43
-------
United States. Thus the greater density of weather sites that measure
precipitation amount results in more structure in the deposition
contours than if the precipitation amounts at the smaller number of
chemistry sites had been used. The maps by Barrie et al. (1982) show
the units of millimoles per liter and millimoles per square meter. For
this chapter, sites values were converted to the units shown but the
published contour lines are used. [Note: These maps have been redrawn
and the lines have not been verified].
Figure 8-14 shows data for sulfates. The Canadian sulfate data
were corrected for sea salt but the U.S. data were not. Corrections for
sulfate are generally negligible (< 5 percent) except at locations
within 5 km of open ocean areas (Barrie et al., 1982). The general
pattern for sulfates in the Northeast is similar in Figures 8-8 and
8-14. However, by comparing the location of the 1,9 and 2.9 mg £-1
contours in Figure 8-14 with the 2.0 and 3.0 mg &"1 contours in
Figure 8-8, we note that spatial differences of more than 200 kilometers
are sometimes evident. In central Illinois and western New York the
NADP and MAP3S sulfate values differ by more than 25 percent. In
western New York the two sampling locations are several miles apart. In
the MAP3S program, very small rainfall samples, which generally have
high ion concentrations, are not analyzed. The actual reasons for the
rather large differences in 1980 sulfate ion concentrations at these two
locations are not known and would require a detailed study.
Figure 8-15 shows the 1980 nitrate concentration pattern. The high
nitrate values in the western plains of Canada are attributed to wind-
blown dust. In the east the highest values are in southern Ontario. The
notch in the 1.9 mg &"1 contour in Pennsylvania and New York might
be rather important if it is real. Such features should be useful in
relating emission patterns to acid precipitation patterns. However, at
this time, the fine structure in the sulfate and nitrate patterns are
unreliable. The uncertainty in the location of the contour lines for
different areas, averaging times, averaging procedures, site densities,
and networks have not been determined. The correlative evidence for a
general link between known emission sources and the composition of
precipitation is, however, convincing. When quality data are available
for a sufficiently long period of time and the uncertainties in the
placement of the contour lines are established, it may then be possible
to use such patterns to answer more specific questions such as transport
distances and scavenging mechanisms.
Figure 8-16 displays the 1980 ammonium pattern. The very high
concentrations observed in Figure 8-10 are not found in Canada.
Figure 8-17 and 8-18 show the weighted pH and hydrogen ion
concentrations. The lowest pH values are found in Ohio, Pennsylvania,
and New York. The 5.0 contour line through the central United States is
peculiar to the weighted-averaging procedure as was discussed in rela-
tion to Figure 8-13. The area in the United States enclosed by the 4.2
contour line is substantially larger in Figure 8-17 as compared to
Figure 8-13. The larger area of intense acidity in Figure 8-17 is due to
the pH values of 4.17 and 4.20 in Illinois. The pH values in Ohio in
8-44
-------
UNITED STATES
• NADP
• MAP3S
Figure 8-14. Weighted average sulfate ion concentrations for 1980,
for wet deposition samples (mg sr1). Adapted from
Barrie et al. (1982).
8-45
-------
LEGEND
CANADA UNITED STATES
• CANSAP • NADP
• APN • MAP3S
A OHE
Figure 8-15. Weighted average nitrate ion concentrations for 1980,
for wet deposition samples (mg £~1). Adapted from
Barrie et al. (1982).
8-46
-------
LEGEND
CANADA UNITED STATES
• CANSAP • NADP
• APN • MAP3S
A ONE
Figure 8-16. Weighted average ammonium ion concentrations for 1980,
for wet deposition samples (mg JT1). Adapted from
Barrie et al. (1982).
8-47
1*09-261 0-83-22
-------
5.5
LEGEND
CANADA UNITED STATES
• CANSAP
• APN
A ONE
1980 pH
Figure 8-17. pH from weighted average hydrogen concentration for
1980 for wet deposition samples (reproduced from
Barrie et al. 1982)
8-48
-------
LEGEND
CANADA UNITED STATES
• CANSAP • NADP
Figure 8-18. Weighted average hydrogen concentrations for 1980, for
wet deposition samples (yeq jr*). Adapted from Barrie
et al. (1982).
8-49
-------
Figure 8-17 are lower than those in Figure 8-13. The data in Table 8-8
allow a comparison between 1979 and 1980 and between median and weighted
pH values. The weighted pH values for these sites are on the average
about 0.07 units lower than the median values. On the average, the 1980
median pH values are 0.07 unit lower than the 1979 values; the 1980
weighted pH values are 0.10 unit lower. So both the year-to-year
variation and the choice of weighted pH instead of median pH contribute
to the apparent larger area of intense acidity in the United States in
1980.
Figures 8-19 to 8-23 depict wet deposition for 1980. The wet
deposition patterns are probably more variable from year-to-year than
concentration patterns because of the added variability of annual
precipitation patterns.
The variability in concentration between weekly precipitation
events for eight sites distributed across the United States is shown in
Table 8-9. The negative values in the table represent analytical
detection limit concentrations. The 90 percentile value divided by the
10 percentile value ranges from about 10 to 15 for calcium and
magnesium; 10 to 40 for potassium, sodium, and ammonium; and 5 to 10 for
nitrate, chloride, and sulfate. Rather interesting is the fact that the
90 percentile pH value minus the 10 percentile pH value is very nearly
the same at the eight sites; about 1.7 +_ 10 percent.
8.4.2 Remote Site pH Data
Galloway et al. (1982) have reported precipitation chemistry data
for the five remote sites listed in Table 8-10. The samples were
collected within 24 hours after a storm ended. At sites where bulk
deposition was sampled, the collectors were installed for a maximum of
24 hours before an event began in order to minimize dry deposition
amounts. Galloway et al. noted that previous research at the San Carlos
location had indicated that the precipitation was acidic (Clark et al.
1980, Herrera 1979, Jordan et al. 1980). However, since samples
analyzed for constituents other than H+ were collected monthly in
these studies, Galloway et al. felt dry deposition effects would have
been too large to allow for a valid comparison with their own samples.
In the study by Galloway et al. (1980) samples with adequate volume
were split in the field into two 250 ml aliquots. One of the aliquots
was treated with chloroform to prevent biological activity. They found
that the untreated aliquots were subject to pH changes during storage
and shipment, with the acidity decreasing. This evidence, combined with
preliminary results from ion chroma trograph measurements, indicated that
the sample changes were associated with degredation of organic acids in
the samples. Estimates of the importance of organic acids compared to
sulfuric and nitric acids at the five remote sites are shown in Table
8-10. The importance of organic acids is clearly site dependent. This
presence of organic acids again illustrates that a simple comparison of
pH data is insufficient to address time trends of acidity associated
with anthropogenic emissions.
8-50
-------
TABLE 8-8. NUMBER OF WEEKLY SAMPLES (N) AND
AVERAGE pH VALUES FOR 1979 AND 1980
1979 1980
MedianWeighted N Median Weighted
pH pH pH pH
Bondville, IL 32 4.34 4.35 38 4.29 4.17
Salem, IL 23 4.33 4.20
Delaware, OH 49 4.34 4.25 45 4.15 4.11
Caldwell, OH 44 4.22 4.15 44 4.15 4.08
Wooster, OH 45 4.29 4.25 44 4.21 4.17
8-51
-------
LEGEND
CANADA UNITED STATES
• CANSAP • NADP
• APN • MAP3S
OME
Figure 8-19. Sulfate ion deposition for 1980 for wet deposition
samples (kg ha"1). Adapted from Barrie et al. (1982).
8-52
-------
LEGEND
CANADA UNITED STATES
• CANSAP • NADP
• APN • MAP3S
OHE
Figure 8-20. Hydrogen ion deposition for 1980 for wet deposition
samples (meq m~2). Adapted from Barrie et al. (1982),
8-53
-------
LEGEND
CANADA UNITED STATES
• CANSAP « NADP
• APN • MAP3S
A OWE
1980 DN03-
Figure 8-21. Nitrate ion deposition for 1980 for wet deposition
samples (kg ha'1). Adapted from Barried et al. (1982)
8-54
-------
LEGEND
CANADA UNITED STATES
• CANSAP • NADP
• APN • MAP3S
A OME
Figure 8-22. Ammonium ion deposition for 1980 for 1980 for wet
deposition samples (kg ha"-'-). Adapted from Barrie et al
(1982).
8-55
-------
LEGEND
CANADA UNITED STATES
• CANSAP • NADP
• APN • MAP3S
A OME
Figure 8-23. Total nitrogen deposition (calculated from nitrate and
ammonium deposition) for wet deposition samples (kg ha~l)
Adapted from Barrie et al. (1982)
8-56
-------
TABLE 8-9. TEN, FIFTY, AND NINETY PERCENTILE ION CONCENTRATIONS (rug a~l),
pH, AND CONDUCTANCE FOR EIGHT NADP SITES9
Sites Percentlles (ea«+) (Mga+) (K+) (Na+) (NH4+) (M°3") (C1") (S042-) pH
00
C71
NE-ME
NE-NY
WV
GA
Central IL
N-MN
NE-CO
NW-OR
10
50
90
10
50
90
10
50
90
10
50
90
10
50
90
10
50
90
10
50
90
10
50
90
.04
.12
.36
.04
.13
.45
.08
.25
.78
.04
.10
.42
.06
.28
.98
.09
.29
1.04
.10
.43
2.08
.05
.17
.31
.006
.020
.071
.009
.022
.090
.010
.030
.080
.013
.030
.134
.011
.035
.143
.016
.043
.183
.013
.052
.245
.012
.036
.106
-.002
.015
.049
.005
.018
.050
.014
.035
.084
.005
.027
.124
.007
.027
.094
.017
.044
.154
.009
.076
.391
.010
.033
.144
.018
.088
.707
.017
.081
.623
.025
.100
.650
.065
.278
1.291
.015
.065
.195
.032
.139
1.014
.043
.189
1.222
.077
.288
2.150
-.02
.08
.38
-.02
.21
.64
-.02
.21
.65
-.02
.11
.55
.16
.42
• 1.18
-.02
.30
1.01
.11
.68
2.51
-.02
.04
.14
.31
1.08
2.52
.58
1.88
4.49
.82
2.00
4.64
.30
.88
2.10
.92
1.96
4.26
.50
1.42
3.41
.90
.19
.57
.20
.41
1,68
.09
.16
.42
.06
.16
.35
.08
.18
.37
.14
.30
1.35
-.03
.20
.40
.07
.17
.35
.08
.19
.57
.20
.41
1.68
.64
1.98
3.50
.70
2.31
5.90
1.54
3.47
7.00
.91
2.00
5.91
1.91
3.27
5.60
.51
1.50
3.50
.67
1.88
5.44
.21
.73
1.77
4.20
4.46
5.70
3.99
4.30
4.83
3.92
4.25
4.59
4.11
4.62
5.65
3.98
4.31
4.65
4.52
5.17
6.15
5.30
6.03
6.86
4.95
5.52
6.50
7.0
19.5
29.2
9.5
27.0
53.4
15.1
31.4
61.7
8.3
16.6
40.3
16.0
27.5
51.2
6.9
12.0
24.3
6.2
12.7
33.4
3.7
6.8
21.9
31
100
128
91
72
94
42
99
All measurements were made at the central laboratory and all samples were weekly
collections when the equivalent collected rainfall was > 0.05 cm (using data from NADP
1978, 1979, and 1980
-------
TABLE 8-10. pH AND CONTRIBUTIONS TO FREE ACIDITY (%) FOR FIVE REMOTE SITES
(ADAPTED FROM GALLOWAY ET AL. 1982)
Collector Type
No. Sample sb
Average pHc
pH Ranged
H2S04
HN03
oo HXe
en
no , ... . .. -.,., .
St. Georges,
Bermuda
W/Da and Bulk
67
4.79
3.8-6.2
< HI
< 35
> 0
Poker Flat,
Alaska
W/D
16
4.96
4.7-5.2
< 65
< 17
> 18
Amsterdam
Island
Bulk (Funnel
and Bottle)
26
4.92
4.3-5.4
< 73
< 14
> 13
Katherine,
Australia
W/D
40
4.78
4.2-5.4
< 33
< 26
> 41
San Carlos
Venezuela
Bulk
14
4.81
4.4-5.3
5 18
< 17
> 65
aW/D refers to an automatic sampler which collects a wet only sample in one container and a
dry fall sample in the second container.
cAverage pH here refers to the pH corresponding to the weighted-average hydrogen ion
concentration.
eThe authors indicate that HX could be HC1, organic acids, or ^04 but they believe it
was organic acid.
dThis range is for pH measurements made at the Virginia laboratory, on the samples treated
with chloroform.
^These samples were treated with chloroform at the field sites. Samples with volumes less
than about 500 ml were not treated with chloroform at the field sites.
-------
Measurements in June 1980 of the pH and the major inorganic ions
for over 300 samples collected in Hilo, Hawaii showed that the acidity
was due mainly to sulfuric acid instead of nitric or hyrochloric acid
(Stensland 1981). Since about one to four weeks elapsed between
collection and pH measurements, it is possible that any significant
organic acid contribution would have been missed due to sample changes
as reported by Galloway et al. (1982). In the same study about 75
additional samples collected at different elevations on the island of
Hawaii were measured for pH within 24 hours and again about 5 months
later. The hydrogen ion concentrations were observed to typically
decrease by 10 to 20 yeq £-1. For some of the samples, pH changes
related to the slow dissolution of dust particles could be definitely
ruled out. Thus it seems likely that organic acids are making a
significant contribution to some rain samples collected in Hawaii.
It has often been stated that the pH of natural precipitation is
controlled by the equilibrium with atmospheric COg, producing pH
values of 5.6. Charlson and Rodhe (1982) have examined various aspects
of the atmospheric sulfur and nitrogen cycles for areas unaffected by
anthropogenic perturbations. They conclude that substantial variations
in precipitation pH should be expected, perhaps in the range of pH 4.5
to 5.6, due to the variability of the sulfur cycle alone, in maritime
areas where basic constituents such as ammonia gas and CaC03 have low
concentrations. Charlson and Rodhe and several other authors have thus
pointed out that it is not appropriate to use pH = 5.6 as a reference
value against which human influences should be judged. Charlson and
Rodhe emphasize that generally pH will be a poor indicator of manmade
acidification, but instead the natural elemental cycles must be studied
in order that manmade influences on these cycles can be recognized and
quantified.
8.4.3 Precipitation Chemistry Variations Over Time
8.4.3.1 Nitrate Variation Since 1950's--Likens (1976) reported
significant increases in the annual volume-weighted concentrations of
nitrate in data from New York and the Hubbard Brook Experimental Forest,
New Hampshire. Additionally, various other authors conclude that NOX
emissions from fossil fuel combustion are the most important sources of
precipitation nitrate increases in the eastern United States, but that
the role of increased fertilizer use has not been rigorously assessed.
Comparing the 1955-56 Junge data (Figure 8-24) with the current
NADP data in Figures 8-9 and 8-25, reveals a broad spatial picture of
the increased nitrate levels. The average nitrate concentrations in
Figure 8-24 were obtained by weighting the quarterly values of nitrate
reported by Junge (1958) with the quarterly precipitation for the sites
(Stensland 1979). Attention should be focused on the eastern United
States, where the NADP data record is most complete. The nitrate
concentrations are clearly greater in the recent NADP data than they are
in the 1955-56 Junge data. Significantly, the approximate magnitude of
the increase is consistent with the reported increase in combustion-
related NOX emissions over the same time period. However, it would be
8-59
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Figure 8-24. Map of precipitation-weighted average nitrate
concentrations (mgj~^ as NC^Z-) for the 1955-56
Junge data (adapted from Stensland 1979)
8-60
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inappropriate to infer a quantitative relationship between NOX
emissions and increases in precipitation nitrate concentrations because
error bars for the emission and precipitation data are not yet
available.
The volume-weighted-nitrate concentrations in Figure 8-25 are
generally lower than the median values shown in Figure 8-9. The
difference appears to be very substantial when the 2.0 contour is
compared in the two figures. However, the extension of the 2.0 contour
in Figure 8-9 into South Dakota and Nebraska results from data at only
three sites, and illustrates why it is important to show the data values
at the sites instead of only contour lines. The volume weighted values
in Figure 8-25, averaged for the 78 sites, are 14 percent lower than the
median values in Figure 8-9. By way of comparison, the volume weighted
sulfate values in Figure 8-8 were only 5 percent lower than the median
sulfate values in Figure 8-7.
8.4.3.2 pH Variation Since 1950's--Cogbi11 and Likens (1974) and Likens
and Butler (1981) have published eastern U.S. maps of precipitation pH
for the mid-1950's, 1960's, and 1970's. Likens and Butler have
concluded that this mixture of calculated and measured pH values that
there has been a large spread and probable intensification of acid
precipitation (pH < 5.6) in eastern North America during the past 25
years. As noted, these conclusions were based on trends shown on the pH
maps, but trends in emissions and precipitation concentrations of acidic
species were also used.
Stensland (1979) also calculated the pH distribution for 1955-56
from Junge's data. He found it necessary to apply a correction factor
to the calculated pH values to bring the values into agreement with
measured pH values, the largest adjustment being required for calculated
pH > 6.0. The resulting pH map for 1955-56 by Stensland is very similar
to the Likens and Butler map for 1955-56. Stensland (1979) also
presents a series of pH maps to demonstrate that the calculated pH
pattern is very sensitive to the concentrations of calcium and
magnesium. Tables 8-11 and 8-12 demonstrate the significance of these
sensitivity tests (Stensland and Semonin 1982). The 1977-78 data in
Table 8-11 are for 1 year of sampling at two MAP3S sites with automatic,
wet-only deposition collectors. The 1955-56 Junge data for a nearby
site, at Williamsport, PA, were from a bulk collector. However, because
the operators at the Junge sites were instructed to place the bulk
collectors out only when precipitation was imminent, the procedure can
be described as manual, wet-only collection. The magnesium
concentration at Williamsport was estimated (Stensland 1979) because
Junge did not measure this parameter. The data in the column labeled
'change1 in Table 8-11 indicates that the difference in the calculated
pH for the two time periods, 4.67 versus 4.18, is due more to the change
in the cations instead of the change in the anions. A similar analysis
for Illinois is shown in Table 8-12.
The 1953-54 data in Table 8-12 are a summary of the results of
Larson and Hettick (1956). The Larson and Hettick samples were wet-only
8-61
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1.
1.0
Figure 8-25.
Map of volume-weighted average nitrate concentrations
(mg JT1 as N0s~) for NADP wet deposition samples through
approximately December 1980 (using data from NADP 1978,
1979, and 1980).
8-62
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TABLE 8-11. WEIGHTED AVERAGE CONCENTRATIONS9 (yeq £-1)
FOR MAP3S AND JUNGE DATA (ADAPTED FROM STENSLAND AND SEMONIN 1982)
Cornell Penn.
Univ. NY, State Univ. Mean of
9/21/77- 9/24/77- the
9/29/78 9/15/78 two sites
Williamsport,
PA
7/1/55-
6/30/56 £-1)
Change
Na
K+
NH4
Sum
5.4
1.5
1.5
.6
13.4
22.4
4.5
1.1
1.5
.7
12.9
20.7
5.0
1.3
1.5
.6
13.2
21.6
38.4.
J
+=6.3
15.6
20.9
3.6
5.05
83.5
+=54.0 -47.7
-19.4
-3.0
+8.2
S042-
N03"
CT
Sum
55.4
27.4
4.4
87.2
55.5
27.6
4.5
87.6
55.4
27.5
4.4
87.3
72.5
21.1
11.3
104.9
-17.1
+6.4
-6.9
Calculated
PH
Measured,
Weighted pH
Number of
Samples
4.19
4.15
55
4.17 4.18
4.16
80
4.67
MAP3S data are sample volume-weigh ted averages and Junge data are
precipitation amount weighted averages.
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TABLE 8-12. MEDIAN PRECIPITATION CONCENTRATIONS (yeq £-1) AT
CHAMPAIGN, ILLINOIS (ADAPTED FROM STENSLAND AND SEMONIN 1982)
Cations
,,.
Na+
K+
NH4+
Sum
An ions
S042-
N03"
cr
Sum
Calculated
pH
Measured,
Weighted pH
Number of
Samples
5/21/77-
1/16/78
10.5
+=12.9
2 A'
1.9
0.5
17.7
33.0
78.9
29.8
4.8
113.5
4.09
4.02
63
10/26/53 Change
8/12/54 (yeq A-D
84.59 _71.6
7.1 -5.2
2.2 -1.7
18.6 -0.9
112.4
64.5 +14.4
20.2 + 9.6
7.3 - 2.5
92.0
6.52
-
30
Measured hardness.
8-64
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deposition samples for which the collection funnel was rinsed, just
prior to sample collection, to reduce the possibility of contamination
by dust between rain events. The 1977-78 data in Table 8-12 are also
from an automatic, wet-only collector at the same site as the Larson and
Hettick study. The decrease in calcium plus magnesium is the major
reason for the increased acidity of the 1977-78 Illinois samples.
Comparison with the 1980 data for the NADP site located 10 kilometers
from the Larson and Hettick site results in the same conclusion.
Both the 1953-54 Larson and Hettick samples and the 1955-56 Junge
samples were collected during the severe drought of the 1950's.
Stensland and Semonin (1982) have hypothesized that this drought
produced unusually high dust levels in the atmosphere. In turn, the
high dust levels produced unusually high pH values for the available
precipitation chemistry data for the 1950's. When the calcium plus
magnesium levels measured by Junge are reduced to levels currently being
measured, the calculated pH for the entire Northeast is less than 4.6.
Stensland and Semonin suggest (1) that the drought-corrected pH pattern
for the 1950's should be compared with current data and (2) that the
error bars associated with the calculations make it difficult to discern
a pH time trend over the last 25 years.
Hansen et al. (1981) have discussed other features of the
historical data record that make establishing the magnitude of the pH
time trend difficult, and Barrie et al. (1982) have reviewed information
relative to acidity trends in North America and state:
"As a consequence of this continuing debate, one can conclude that
it is presently unsafe to utilize existing network data to draw any
reliable conclusions with regard to acidity trends in eastern
North America."
The clear increase of nitrate in precipitation and of NOv and SOx
emissions suggests but does not prove that the acidity of precipitation
has increased in the last 25 years. However, the historical pH data,
measured or calculated, do not allow quantification of an acidity
increase.
8.4.3.3 Calcium Variation Since the 1950's--Tab1e 8-13 shows calcium
concentrations for various networks, sites, and time periods. The
calcium levels for the MAP3S and NADP networks are small relative to
those for the other networks. Bulk samples were collected in the USGS
network probably accounting for their higher calcium levels. However,
urban areas such as Albany, NY, a U.S. Geological Survey (USGS) site,
can also produce relatively high atmospheric dust levels, thus, high
calcium levels. The NCAR and WHO networks used automatic, wet-only
collectors, but, because of sampler design, the covers probably did not
make firm contact with the sampling bucket. Thus, dust probably leaked
in during nonprecipitation periods, producing the relatively high
calcium concentrations.
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TABLE 8-13. CALCIUM CONCENTRATIONS (mg £-1) FOR VARIOUS NETWORKS,
SITES, AND TIME PERIODS (FROM HANSEN ET AL. 1981)
Si tes
Jungea
1955-56
NCARb
1960-66
WMOC
1974-76
USGSd
1966-78
MAP3S6
1978-79
NADPf
1979
Rocky Mountain
Alamosa, CO 2.65
Grand Junction, CO 3.41 7.25
Pawnee, CO 0.53
Midwest
Grand Island, NE 3.12 0.96
Huron, SD 2.40 2.74
Lamberton, MN 0.58
Mead, NE 0.53
St. Cloud, MN 1.02 1.12
Northeast
Albany, NY 1.97 2.83
Caribou, ME 0.63 0.39 0.36
Hinkley, NY 0.70
Huntington, NY 0.13
Mays Point, NY 1.48
Ithaca, NY 0.14
Williamsport, PA 0.77
Southeast
Charlottesville, VA 0.15
Georgia Station, GA 0.10
Greenville, SC
Raleigh, NC
Roanoke, VA
Sterling, VA
0.31
0.32
0.30
0.67
0.20
aWeighted averages, manual wet-only sampling, July 1955-June 1956,
Weighted averages, wet-only sampler, NCAR/Public Health Service.
^Medians, wet-only.
"Medians, bulk sampling.
eMedians, wet-only sampler, July 1978-June 1979.
^Medians, wet-only sampler.
8-66
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If dust leaks into the sample containers of wet-only collectors or
is included in the precipitation sample via bulk sampling, the measured
pH may be significantly different than that for rain and snow that falls
into clean containers. For a given collector, the problem will be most
severe in arid regions. The data in Table 8-13 suggest this problem may
also occur in the eastern United States. The magnitude of this dust
leakage effect should be continuously evaluated at all sampling sites
through collection, analysis, and reporting of appropriate blank
samples. These steps have been taken at very few networks in the past,
and they are only rarely taken now.
8.4.4 Seasonal Variations
Herman and Gorham (1957) reported that snow sampled in the early
1950's contained lower sulfur and nitrogen concentrations than did rain
sampled during the same period. They speculated that this difference
might have resulted from snow's having a lower collection efficiency
than rain or from arctic air bearing snows being cleaner than tropical
air. In the late 1960's, Fisher et al. (1968) observed lower
precipitation sulfate in the cold season. Bowersox and dePena (1980),
Pack and Pack (1980), and Pack (1982) reported strong seasonal
variations in sulfate in precipitation at MAP3S sites in New York,
Pennsylvania, and Virginia.
Bowersox and Stensland (1981) analyzed NADP data for seasonal
variations in sulfate and nitrate. Because the data base was small, two
to seven sites were grouped into five regions in the eastern United
States and the data for each region were averaged for the cold season
(November to March) and the warm season (May to September). The
resulting warm-to-cold-period ratios for sulfate varied from about 2.0
in the New England region to 1.25 in the Illinois region. The
investigators noted that aerosol sulfate has a similar seasonal
variation but that SOX emissions for the Northeast have a relatively
small seasonal variation.
For nitrate, Bowersox and Stensland (1981) found a maximum
warm-to-cold-period ratio of 1.5 for the region in the Southeast, but
three of the remaining regions had little or no seasonal variation.
Determining whether different patterns of seasonality for nitrate and
sulfate are predicted by numerical simulations would be valuable. The
acidity of the precipitation was greater in the warm period for all the
regions and reflected the mixture of the patterns for sulfate and
nitrate.
Bowersox and dePena (1980) found only slightly higher nitrate in
precipitation in the winter than they did in other seasons at the MAP3S
site in Pennsylvania, Hydrogen had a strong maximum in the warm months
and sulfate was the principal anion affecting acidity. Nitrate, at
concentrations similar to those of sulfate, did not correlate well with
hydrogen ions in liquid precipitation but did correlate with hydrogen
ions in snow and frozen precipitation.
8-67
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The seasonal pattern of precipitation sulfate concentration is
different for western Europe than it is for the eastern United States.
Granat (1978) averaged the data for many European sites and reported a
maximum sulfate concentration in the spring 1.6 times greater than the
minimum value observed in the fall. The sulfur emissions in the region
are at maximum in the winter (Ottar 1978).
8.4.5 Very Short Time Scale Variations
The concentrations of the major ions in precipitation vary
considerably during a rainshower (Robertson et al. 1980). Samples
collected sequentially during rainshowers in Arizona had calcium
variations up to 1000 ercent over a sampling period of less than 15
minutes (Dawson 1978). Dawson found that the correlation between ions
having a common source were not significantly different from those
between components not having a common immediate source. Therefore,
Dawson concluded that the observed concentration changes were primarily
determined by precipitation processes.
8.4.6 Air Parcel Trajectory Analysis
Attempts have been made to link the precipitation chemistry
patterns to the emission source regions through the use of air parcel
trajectory analysis. There are many different approaches to calculate
trajectories of air parcels. Forland (1973) used surface geostrophic
analysis to determine air parcel trajectories. This analysis involved
using surface air pressure gradients to calculate the wind speed and
direction to move the air parcel. Recently, many investigators have
calculated trajectories with the National Oceanic and Atmospheric
Administration (NOAA) Air Resources Laboratory (ARL) model, which uses
surface layer wind observations (Miller et al. 1978, Wilson et al.
1980, Miller et al. 1981). With the ARL model, an average wind through
a surface layer, such as that 300 to 1500 meters above the ground, is
used to calculate the trajectories. Many scientists argue that air
parcel trajectory techniques need to be further developed and verified
with field experiments.
Some conclusions from recent trajectory studies are as follows.
Forland (1973) found that, for a site at the southwestern tip of Norway,
the precipitation pH values were 4 to 5 for air parcels originating in
central Europe or England and 5.1 to 6.6 for parcels originating in the
North Sea. He concluded that acidic precipitation in southern Norway is
mainly a result of $03 emissions from northern Europe. Ottar (1978)
reported that aerosol sulfate at European sites examined by sector (air
parcel) analysis showed that sectors associated with high concentrations
are directed towards areas of major sulfur emissions. Similar analysis
for precipitation illustrated that, to a large extent, acidity is
strongly influenced by the availability of ammonia, with air masses
passing over the sea showing the least degree of neutralization.
8-68
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Miller et al. (1981) used the ARL trajectory analysis to stratify
the pH of precipitation samples collected at Bermuda. They found that
pH was generally less than 5.0 for trajectories originating in the
eastern United States and greater than 5.0 for trajectories originating
southwest to southeast of Bermuda.
Wolff et al. (1979) used trajectory analysis to characterize
precipitation pH for samples from eight sites in the New York City area.
They found higher pH values for air parcels from the ocean or from the
north and lower pH for air parcels from the south through northwest
sectors. The lowest average pH was for air parcels from the southwest
sector. They also classified the precipitation events according to
synoptic meteorological conditions and found air mass thunderstorms and
precipitation associated with cold fronts in the absence of closed lows
to be the most acidic. Because showers and thunderstorms are usually
associated with southwesterly flow, whether the low pH detected by this
study was more strongly related to source direction or to
characteristics of the scavenging processes taking place in these types
of precipitation events must be questioned.
Raynor and Hayes (1981) also classified pH data by synoptic type
and found the lowest pH with cold fronts and squall lines, or with
thunderstorms and rainshowers. Although these are predominately warm
season rainfall types, Raynor and Hayes found that the low pH was not a
function of season alone.
The question of the importance of atmospheric transformation and
scavenging processes in explaining the observed association between
southwest trajectories and low pH is discussed by Wilson et al. (1980),
who maintain that:
Normally, trajectory analysis of individual events will lead to
some basic source-receptor relationships. Vital information is
still missing on the overall transport/transformation processes
that take place in the atmosphere relevant to the formation and
deposition of "acid rain".... In summary, the known source
regions for precursor gases to "acid rain" cannot yet be
unequivocally linked to receptors with the meteorological,
physical and chemical information available today.
Wilson et al. (1981) emphasize the importance of recognizing the
relation between precipitation amount and ion concentration. When they
normalized the MAP3S data for precipitation amount they found that the
sulfate deposition per centimeter of precipitation is greater at the
MAP3S Illinois site than at the Pennsylvania and New York sites. Stated
another way, more sulfate is deposited annually at the Pennsylvania site
than at the Illinois site, mainly because of the greater precipitation
amounts.
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8.5 GLACIOCHEMICAL INVESTIGATIONS AS A TOOL IN THE HISTORICAL
DELINEATION OF THE ACIDIC PRECIPITATION PROBLEM (W. B. Lyons and
P. A. Mayewski)
Precipitation in the Northern Hemisphere has been recently
recognized to have hydrogen ion concentrations 10 to 500 times higher
than expected for natural precipitation (Likens and Bormann 1974,
Cogbill and Likens 1974, Lewis and Grant 1980). However, controversy
has arisen regarding the nature of the acidity of the precipitation
sampled and whether, indeed, the pH of North American precipitation has
increased over time (Miller and Everett 1979, Lerman 1979, Stensland
1980, Sequeria 1981, Charlson and Rodhe 1982). In most locations pH
records have been constructed rather imperfectly due to differences in
sampling, handling, and analytical procedures used (Galloway and Likens
1976, 1978; Galloway et al. 1979). The lower pH's measured in Northern
Hemisphere precipitation are thought to be due to the input of sulfur
and nitrogen oxides from fossil fuel-burning (Likens and Bormann 1974)
and in some cases hydrogen chloride (Gorham 1958a). Few baseline data,
however, are available on the pH of precipitation in areas of the
Northern Hemisphere remote from North American and European sources of
anthropogenic sulfur emissions. In addition, monitoring records of pH
and acidic chemical species are of rather short time duration ~ 15 to
20 years at most), limited geographic coverage, and provide little
useful information prior to the early 1960's (Hornbeck 1981). Baseline
studies of pH and related chemical species as well as historical time
series data are warranted if we are to understand man's effect on the
environment.
The National Academy of Sciences (1978) recommends that historical
studies of glacier snow and ice should be conducted. Such studies are
needed to better understand the atmospheric transport of anthropo-
genically introduced chemical species to remote areas. In addition, a
more recent NAS report (1980) states that a major scientific goal of the
1980's should be to "identify the significant natural and anthropogenic
factors contributing to acid rain." Detailed glaciochemical studies
should provide this type of needed information.
Snow and ice cores collected from appropriately chosen glaciers
provide samples of entrapped chemical species that, unlike those derived
from any other medium, are nearly to entirely unaltered since their
deposition. This technique has barely been applied to the study of acid
precipitation despite the fact that it provides a very sensitive record
of precipitation chemistry.
8.5.1 Glaciochemical Data
Past glaciochemical studies (early studies are reviewed in Langway,
1970) have provided information concerning 1) the documentation of
individual storm events (Warburton and Linkletter 1978, Mayewski et al.
1983a), 2) the dating and seasonal accumulation of snow and ice (Langway
et al. 1975, Herron and Langway 1979, Butler et al. 1980, Mayewski et
al. 1983b), as well as 3) long-term climatic change (Delmas et al.
8-70
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1980b), Thompson and Mosley-Thompson 1981, Johnson and Chamberlain
1981). Our discussion will deal primarily with the use of
glaciochemical studies in delineating the acid precipitation phenomenon.
The text that follows is divided into a section on primary measurements
including sulfate, nitrate, pH and total acidity, and a section
concerning analog measurements or trace metals. For both primary and
analog measurements the discussion is subdivided into results from polar
glaciers and from alpine glaciers.
The glacier division adopted in this text is used primarily as a
means to separate the results of glaciochemical studies for review
purposes. Polar glaciers, including the Antarctic and Greenland ice
sheets, are characteristically lower in temperature and accumulation
rate and larger in size than alpine glaciers. Hence, polar glaciers
classically are used to retrieve longer glaciochemical time-series,
often with less subannual detail than time-series from alpine glaciers.
Although there are many fewer glaciochemical studies available from
alpine glaciers, they are included here because these glaciers are less
remote from industrialized sites than are polar glaciers and, therefore,
have considerable potential as proxy indicators of man's effect on the
environment.
8.5.1.1 Sulfate - Polar Glaciers—The early work by Koide and Goldberg
(1971), Weiss et al. (1975) and Cragin et al. (1975) and more recent
work by Busenberg and Langway (1979) has suggested that the
concentration of sulfate in recent Greenland snow and ice (past 20 yr)
has increased by at least a factor of 2. This increase has been
attributed to fossil fuel burning. However, other investigations have
suggested that these enrichments may be also linked to natural processes
and/or local contamination (Boutron 1980, Boutron and Del mas 1980).
Herron (1982) most recently indicates that S042~ has been
enriched by a factor of 1.6 to 3.7 in Greenland snow and ice in the past
200 years and that this enrichment is due to the burning of fossil fuel.
No anthropogenic input of S042- has been observed in Antarctic ice
cores (Delmas and Boutron 1978, 1980; Herron 1982). Recent work by Rahn
(Kerr 1981) indicates that the northern polar regions receive pollutant
S042~ on a seasonal basis, and mass budget considerations indicate
that approximately 2.5 times the natural atmospheric emission leaves
eastern North America every year (Galloway and Whelpdale 1980). Shaw's
(1982a) work confirms that of Rahn, indicating that the Arctic haze
observed in Alaska has its source in Eurasia, with smelting operations
in Siberia being a possible major contributor.
Natural processes may also have a profound effect on S042-
profiles in glacier ice. For example, Bonsang et al. (1980) have shown
that aerosols of marine origin have much higher S04/Na ratios than
seawater, indicating that S042~ enrichments in precipitation need
not be all due to anthropogenic emissions. Recent work by Hammer et al.
(1980) indicates that Greenland ice concentrations of $04^" are
greatly affected by world-wide volcanism. The active volcano Mt. Erebus
may be a major sulfate source to the Antarctic continent (Radke 1982).
8-71
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Volcanically produced $042- has been observed in Antarctic and
Greenland ice cores (Kyle et al. 1982, Herron 1982). As one proceeds
away from the ocean in both Antarctica and Greenland, sea salt becomes
less of a contributor to the $042- concentration in-the ice and snow
(Boutron and Delmas 1980), and in Antarctica gas derived $642- as
well as N03" and Cl~ becomes very important (Delmas et al. 1982).
In addition to the possible volcanic input of $03 into the
atmosphere, biogenic emission, particularly in lower latitude regions
may also be an important contributor of SO? (Lawson and Winchester
1979, Stallard and Edmond 1982, Haines 1983). Due to the very long
residence time of sulfate in Antarctic aerosols (Shaw 1982b), the
oxidation of marine derived gases such as dimethyl-sulfide may be a
major contributor of sulfate to Antarctic precipitation (Delmas 1982).
Herron (1982) has also suggested a biogenic source for a portion of the
sulfate observed in Greenland ice. Gas adsorption onto particles may
also be an important source of $042- in some locations (Mamane et
al. 1980). It is also thought that the sulfate present in Arctic
aerosols is formed from the conversion of continentally produced
pollutant S02 during transport (Rahn and McCaffrey 1980).
8.5.1.2 Nitrate - Polar Glaciers—The work of Parker et al. (1977,
1982) shows downhole variations in the N03- concentration of snow
ice. Parker et al. (1977) have suggested that this historic and
variation is due to changes in sunspot, auroral, and/or cosmic ray
activities and not due to variations in anthropogenic inputs. These
workers have recently observed seasonal, 11 and 22 yr periodicities as
well as long term changes in Antarctic ice (Parker et al. 1982). The
highest values were associated with winter darkness and heightened solar
activity. They observed no anthropogenic N03~. Kyle et al. (1982)
have observed Volcanically introduced 1*103- in Antarctic ice. How-
ever, Aristarain (1980) has observed on James Ross Island, Antarctica,
no variation in NOg-, on at least the seasonal level. Risbo et al.
(1981) and Herron (1982), on the other hand, observed no relationship of
N03~ with solar activity in Greenland. Herron (1982) did note a
seasonal variation of N03~ in Greenland ice; however, the highest
values were associated with the summer season. He also observed an
anthropogenic doubling of N03~ in surface samples, indicating for
the first time the introduction of N03~ into this region, probably
through fossil fuel burning.
8.5.1.3 pH and Acidity - Polar Glaciers--Hammer (1977, 1980; Hammer et
al. 1980) has measured the acidity of Greenland ice cores and found a
"background" value of pH - 5.4 although much lower values appear
during times of high volcanic input (e.g., Laki Eruption in 1783, pH of
ice = 4.4). However, in most cases Hammer has not measured pH directly
but rather has used conductivity techniques.
Berner et al. (1978) first measured the acidity of Antarctic ice by
using strong acid titrations. They observed values ranging from 6.0 to
7.5. Delmas et al. (1980a) found an average pH in Antarctic ice of 5.3.
These investigators, like Berner et al. (1978), used the strong acid
8-72
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titration technique rather than direct measurements of pH. More recent
work (Legrand et al. 1982) has substantiated the fact that Antarctic
precipitation is acidic with maximum reported values of 7 yeq £-!.
Much of the earlier pH work on glacier snow and ice is unusable due
to possible sampling and handling artifacts (e.g., filtration and hence
degassing prior to analysis, and sample storage in glass rather than
plastic; Gorham 1958b; Elgmork et al. 1973).
The polar data acidity, pH, and acid anion concentrations suggest
there has been a negligible contribution of fossil fuel by-products
transported to Antarctica, as expected due to its great distance from
Northern Hemispheric sources. The most recent data, those of Herron
(1982), indicate however that Greenland has been affected by fossil fuel
burning with SCty2- and N03~ enrichments in surface snows of ~ 2
above preindustrial times. However, it should be noted that these
enrichments are based on very few data points, and more detailed study
may be warranted.
8.5.1.4 Sulfate - Alpine Glaciers--To our knowledge, no published data
exist for SO^- concentrations in glacier ice from alpine areas.
8.5.1.5 Nitrate - Alpine Glaciers—Butler et al. (1980) have observed
values of from < 0.03 to 2.80 yM in a short core from Athabasca
Glacier, Alberta. They observed higher values during the warmer months
of the year. In addition, their mean N03~ value was approximately
15 times lower than that observed in central Alberta snows close to
populated areas. High elevation surface samples from Kashmir, India
demonstrate values as high as 1.3 yM in snow from pristine air masses
(Mayewski et alI. 1983a)). Nitrate values of between < 0.1 and 4.4 yM
have been obtained from a ~ 17 m core on Sentik Glacier in Kashmir,
India, close to the surface sampling site discussed in Mayewski et al.
(1983a). The source of the N03~ is unknown, although variations in
airmass source and/or accumulation rate may be important.
8.5.1.6 pH and Acidity - Alpine Glaciers--Although identifying the pH
of snow and ice may be more complex than simply measuring strong mineral
acid contributions, Delmas and Aristarain (1979) have observed in the
Mt. Blanc area of the French Alps strong mineral acid values that
increase from ~0 yeq &-1 for 1963 to above 10 yeq £-1 in 1976. It
should be pointed out, however, that this increase from 1963 to 1976 is
only represented by 4 data points. It does however provide insight into
the possible usefulness of high altitude alpine glaciers as historic tools.
Delmas and Aristarain (1979) have argued that this strong acid increase is
due to increased fossil fuel burning.
Clement and Vandour (1967) have reported pH values of snow from the
southern French Alps in the range 4.2 to 7.0, noting changes in pH with
time, type of snow, and elevation. These authors have suggested that,
in general, low pH's correspond to winter snow accumulation, freshly
fallen snows, and higher elevation snow. Lyons et al. (1982) and
Mayewski et al. (1983a) have also observed an elevation vs pH
8-73
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relationship for Himalayan surface snows. These authors have suggested
that the majority of the pH vs elevation trend observed is a function of
increased COg saturation with decreasing temperature. A number of
workers (Scholander et al. 1961, Berner et al. 1978, Stauffer and
Berner, 1978, Oeschger et al. 1982) have shown that polar ice and snow
are easily "contaminated" with CO?. If these data and the
interpretations are correct, detailed ionic balance studies must be
undertaken to understand completely the nature of the acidity and/or pH
of ultrapure snow and ice.
More recently Koerner and Fisher (1982) have discussed the
adsorption of C02 as it related to snow pH measurements and snow
density. They have argued that the pH contribution due to CO?
"contamination" should increase with depth in glacial ice. If this is
true, the pH of snow and ice, especially downhole, may have little
relevance to the acid precipitation phenomenon. The measurement of
acidity via titration eliminates this contribution of C0£ to pH from
the ice as well as any contribution from the ambient atmosphere upon
melting. The newly developed acid titration technique of Legrand et al.
(1982) appears to be the best suited for snow and ice pH work.
8.5.2 Trace Metals - General Statement
In studies aimed at determining the effects of fossil-fuel burning
on the environment, various investigators have used trace metal
concentrations in precipitation as well as lacustrine sediments and
soils as analogs of acidic compounds (Andren and Lindberg 1977, Galloway
and Likens 1979, Wiener 1979, Anderssen et al. 1980, Jeffries and Snyder
1981). Mass budget calculations indicate that by burning fossil fuel
man has contributed both metals as well as acid into the atmosphere
(Bertine and Goldberg 1971, Lantzy and Mackenzie 1979). However, some
controversy exists as to whether this anthropogenic metal introduction
via burning is regional or global in scale (e.g., Nriagu 1979, 1980;
Landy et al. 1980; Boutron 1980; Boutron and Delmas 1980). This is
coupled with the fact that contamination problems and analytical
uncertainties severely limit the interpretation of much of the data and
complicate the use of trace metal concentrations as acid surrogates
(Murozumi et al. 1969, Boutron and Delmas 1980, Ng and Patterson 1981).
8.5.2.1 Trace Metals - Polar Glaciers--The original glaciochemical
analyses of Pb in Greenland and Antarctic ice by Murozumi et al. (1969)
indicated: 1) a rise from 1 nq kg'1 in Greenland prior to 800 BC to
values greater than 200 ng kg-I in 1968 with the sharpest rise since
1940 and 2) a rise in Antarctica from less than 1 ng kg-1 to 20 ng
kg-1 in 1968. These authors suggest that the sharp rise in Greenland
concentrations post-1940 was due to the increased consumption of leaded
gasoline. The lower values in Antarctica were because most of the
fossil fuel burning occurs in the Northern Hemisphere and little if any
troposphere mixing occurs across the equator. The work of Murozumi et
al. (1969) also demonstrated much more terrestrial material in Greenland
ice compared to Antarctic ice ( ~ 15 to 20 times more) while the
Antarctic ice contained about twice as much sea salt as the Greenland
8-74
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precipitation. Unpublished work by Boutron and Patterson now indicates
little if any (possibly a factor of 2) increase (from 1.5 ng kg'1 to 3
to 4 ng kg-1) in Pb in the surface snows of Antarctica compared to
older ice samples, and that all previous data were erroneously high.
The work of Weiss et al. (1975) showed that in Greenland ice (Camp
Century and Dye 3), Hg, Cd and Cu were enriched in the surface layers,
and they suggested that this enrichment was due to increased fossil fuel
burning. Similar surface enrichments were measured for Ag in Antarctic
ice and attributed to weather modification programs such as cloud
seeding (Warburton et al. 1973).
The work of Herron et al. (1977) suggested for the first time that
"natural" enrichments of several orders of magnitude for several trace
metals occur in the atmosphere. This work was corroborated by
additional investigations on Alaskan snow (Weiss et al. 1978). The
process causing this "natural" enrichment for metals such as Zn, Pb, Cd,
Cu, As, Se, Hg and even Na was suggested to be volcanism. Although
volcanism may have a pronounced effect on atmospheric aerosol chemistry
great distances from its source (Meiner et al. 1981), volcanic emission
studies are in conflict as to whether volcanism is a major source of
volatile trace metals to the atmosphere (Unni et al. 1978, Lepel et al.
1978).
Due to its remoteness from North American emissions, it is now
apparent that any enrichments of trace metals with the posssible
exception of Pb in Antarctic ice may not be due to pollution but
possibly to volcanism (Boutron and Lorius 1977, 1979; Boutron 1979a,
Boutron 1983). Although metal enrichment factors show temporal changes,
these changes do not vary systematically on a short-term or long-term
basis (Boutron and Lorius 1979, Landy and Peel 1981). In addition, the
present day metal fluxes of Cd, Cu, Zn, and Ag are similar to those 100
yrs ago, again suggesting little to no anthropogenic input (Boutron
1979a). However, man-made radionuclides are measurable in Ross Ice
Shelf samples in Antarctica as well as in Greenland (Koide et al. 1977,
1979). The detectable concentrations of these weapon test products in
Antarctic ice do indicate that some high altitude interhemispheric
transport of man-made products does occur (Koide et al. 1979).
Obviously the mode of transport, the altitude of transport, and the size
of the transporting particles all affect pollutant dispersion and
distribution.
In Greenland, the recent findings of Ng and Patterson (1981) have
confirmed the earlier work of Murozumi et al. (1969). Their data
indicate that the concentration of "naturally" occuring Pb in ice during
pre-industrial times was less than 1 ng kg'1 and that surface snows
show a ~ 200-to-300 fold increase above this background level. These
data, along with those collected by Patterson and his colleagues in the
SEAREX group, confirm the hypothesis that Pb introduced by human
activities is ubiquitous in the Northern Hemisphere. Furthermore, these
data allow for a better understanding of pollutant dispersion from
Northern Hemispheric sources and provide an inventory of current back-
8-75
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ground levels of Pb in continental as well as oceanic areas (Shirahata
et al. 1979, Schaule and Patterson 1981, Settle et al. 1982, Flegal and
Patterson 1982). Whether the record of other anthropogenically intro-
duced trace metals beside Pb can be discerned in Greenland snow and ice
is still controversial (Herron et al. 1977, Boutron 1979a,b; Boutron and
Del mas 1980; Nrigau 1980; Boutron 1980). Much more data gathering and
detailed sampling should be accomplished in Arctic areas before this
question can be adequately answered.
8.5.2.2 Trace Metals - Alpine Glaciers—Few data are available on time
series profiles of trace metals in alpine glacier ice and snow.
Jaworoski et al. (1975) reported Cd and Pb values from Storbreen
Glacier, Norway. The 1954 to 1972 profiles of Pb show no trend with
depth but a slight increase in Cd since 1965 appears. These authors
have recently published metal data from a number of alpine glaciers
including samples from Norway, the Austrian Alps, the Nepalese
Himalayas, the Peruvian Andes, and the Ugandan Ruwenzori {Jaworoski et
al. 1981). However, their Pb values from Antarctic snow and ice are
orders of magnitude higher than accepted values (Murozumi et al. 1969,
Boutron and Lorius 1979, Ng and Patterson 1981); and hence, their entire
data set must be considered suspect.
Briat (1978) has measured various trace metals in a profile
(1948-74) on Mt. Blanc at 4280 m. Much temporal variation occurs in the
data, but Briat argues that there has been a two-fold increase in Pb, Cd
and V since 1950 in the precipitation deposited at the Mt. Blanc site.
Based on the review of the literature, with the possible exception
of Pb, Zn, and possibly V, one would be hard put to argue that the
previous glaciochemical work has shown that fossil fuel-burning has
affected the precipitation of glaciated areas. One of the problems with
this interpretation, however, is the lack of data, especially from
alpine glaciers in both areas close to and remote from man's activities.
In addition, the previous alpine glaciochemical studies have produced
time-series of only a few years.
In conclusion, the alpine glacier data available could be con-
sidered sparse at best, unreliable at worst, and the limited number of
glaciers sampled does not provide an adequate picture as to the regional
effect of fossil fuel burning.
8.5.3 Discussion and Future Work
With the exception of Pb, $042-, and N03~ in the northern
polar regions, little conclusive evidence is available from glacier ice
and snow samples to interpret with any certainty the effect of fossil
fuel emissions through time. The large majority of stratigraphic
information regarding trace metals and anionic acid species concentra-
tions is from Antarctica and Greenland. Few if any data come from
glacier ice and snow in lower latitude areas. Because a very large
percentage of fossil fuel burning takes place in the Northern
Hemisphere, the Antarctic data provide little historic insight into past
8-76
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and present anthropogenic emissions. It is apparent, however, that
Antarctic data do provide information concerning background concentra-
tions of various chemical constituents in frozen precipitation. Until
recently, the glacier data can be termed controversial in that different
workers have interpreted the results in different ways (Herron et al.
1977, Murozumi et al. 1979, Boutron 1980, Nriagu 1980, Landy et al.
1980, Boutron and Delmas 1980). The most recent work of Ng and
Patterson (1981) and Herron (1982) indicates more than a two-order-of-
magnitude increase in Pb in the Greenland area and a factor of two
increase in sulfate and nitrate.
Even less information is available from alpine glaciers. Although
there is a suggestion that trace metal emissions have increased in
alpine ice (Briat 1978) and that anthropogenic nitrate inputs occur in
Canadian Rocky glaciers (Butler et al. 1980), it must be emphasized that
little definitive information is available at this time to eludicate
long-term historic trends in regions where they should be easily
detected (i.e., mid-latitude alpine regions both close to and remote
from emission sites).
Owing to the potential post-depositional modifications inherent in
many temperate ice sampling areas, the majority of time-series
relationships sought through ice and snow analyses have been conducted
on polar glaciers. Information concerning climatic events and hence
records potentially pertinent to resolution of chemical time-series in
polar regions have been retrieved for periods on the order of 10° to
104 years (i.e., Cragin et al. 1975, Hammer et al. 1980). Polar
glaciers, however, owing to their low accumulation rates (mm to cm
yr-1) and unique geographic location provide only a portion of the
potential snow and ice core record. Full realization of the potential
climatic and, therefore, chemical sequences recoverable from snow and
ice studies is currently in progress with the addition of temperate
glacier snow and ice cores (i.e., Thompson 1980, Mayewski et al. 1983a,
b). These glaciers, by virtue of their higher accumulation rates (cm to
m y*""1), provide short-term time series (10° to 102 yr) with
considerable sub-annual detail. Proper selection of temperate glacier
core sites, most particularly with respect to elevation and latitude is
necessary if pristine snow and ice samples, unaffected by post-
depositional effects such as melting and diffusion are to be recovered
(Murphy 1970, Oeschger et al. 1977, Thompson 1980, Davies et al. 1982,
Mayewski et al. 1983b). As Hastenrath (1978) has demonstrated, through
direct measurement of net short- and net long-wave radiation and albedo
on Quelccaya ice cap, Peru, a condition of zero to negligible glacier
surface melt can be maintained if the sampling site is at a high enough
altitude, in this case 5400 m, even at 13° 56' latitude.
Although the recent work of Herron (1982) has contributed greatly
to understanding the effect of fossil fuel burning on precipitation in
remote northern polar regions, more detailed ice sampling and analyses
of the past 100 to 150 years record would provide a better comparison
with records such as fossil fuel burning through time in the Northern
Hemisphere.
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Sampling on glaciers requires great care in sample collection,
handling and analysis (Murozumi et al. 1969, Vosters et al. 1970,
Boutron 1979c, Boutron and Martin 1979, Boutron and Delmas 1980). With
the advent of "ultraclean" laboratories and procedures as well as more
sophisticated coring and/or sampling devices (e.g., teflon coated augers
and PICO's new all kevlar coring unit) this, we believe, can be
accomplished for at least the anionic species of interest. If care in
sample acquisition and handling is taken, modern analytical techniques
such as isotope dilution mass spectrometry, flameless atomic absorption,
auto-analyzer visible spectrophometry, and ion chromatography can be
used to determine the various chemical species of interest at extremely
low levels.
To ascertain what is controlling the pH of the snow and ice
sampled, ionic balances must also be undertaken (Granat 1972). This
should at least involve determining N03~, S042~ as well as Cl~ and
Nfy . If possible Na+, K+, Ca2+, Mg2+, and P043-, should also
be determined in each sample. With this information the strong mineral
acid contribution to the total H+ concentration can be determined
independently of pH or acid titration measurements.
In addition to the glaciochemical studies, more information is
needed on possible aerosol-snow fractional on and aerosol source
location. Perhaps the most serious concern raised regarding the use of
glaciochemistry as an historic time series tool is the possibility that
atmospheric compositions are not fully represented in resultant surface
snow compositions. Although the correlation between the compositions at
the South Pole were good (Zoller et al. 1974), similar studies in the
Arctic yielded no correlation (Rahn and McCaffrey 1979).
Superimposed on these problems are the effects of seasonality of
transport in the northern polar region (Rahn and McCaffrey 1980, Rahn et
al. 1980), as well as the time lapsed between precipitation events
(i.e., dry vs wet deposition) and snow-air fractionation (Rahn and
McCaffrey 1979, Davidson et al. 1981). Rahn and McCaffrey (1980) have
suggested that winter Arctic aerosols originate from polluted European
sources and hence contribute fossil fuel emission products to northern
polar ice and snow. In addition, in the case of sulfate, the record in
ice cores may be dampened with respect to what is observed in the
atmosphere (Scott 1981). This demonstrates the need for complimentary
air and snow/ice studies to evaluate properly the results of the latter.
Little doubt exists that the aerosol-snow link requires extensive study
and that aerosol studies are needed in conjunction with surface snow and
ice sampling to enhance the resolution capabilities of such snow/ice
studies (Davidson et al. 1981).
In addition, aerosol source and possible cyclicity in source(s)
must be investigated in more detail. Source discrimination for certain
chemical species has been undertaken in some glaciochemical studies
(Gorham 1958a, Cragin et al. 1975, Busenberg and Langway 1979, Herron
1982). An effort should be made to better qualify the source of acids
to the snow and ice. Samples could be analyzed for F~ using ion
8-78
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chromatography (Herron 1982). Samples with high F- concentrations may
have had a significant input of volcanic acid (Lazrus et al. 1979,
Stoiber et al. 1980). Table 8-14 summarizes the potential sources of
chemical species in the atmosphere and hence glacier snow and ice, with
estimations of spatial and temporal controls on the input of these
species to glacier sampling sites. As an example of the type of data
needed to quantify the approach taken in Table 8-14, decreases in
chemical concentration as a function of distance in Antarctica (Boutron
et al. 1972, Johnson and Chamberlain 1981) have been investigated. This
type of information is needed if a more quantitative assessment of
anthropogenic vs natural sources is to be made. Determining metal or
acid sources may also clarify the nature and cause of the high aerosol
enrichment factors observed for most volatile elements, even in remote
areas (Dams and DeJonge 1976, Davidson et al. 1981). Knowledge of the
acid source in frozen precipitation is necessary if the problem of acid
precipitation is to be completely understood.
8.6 CONCLUSIONS
The following conclusions may be drawn from the preceding
discussion of deposition monitoring.
0 Although precipitation sampling networks have been operated many
times at many locations, assessments of national or regional
patterns and trends must be cautiously used because of variability
in the methods of collection and analytical techniques. Usually
the networks have been of limited spatial or temporal extent
(Section 8.1).
0 Bulk sampling, used in many networks, does not generally provide
data useful in determining quality of precipitation, although this
approach has some potential to estimate total deposition (Section
8.2.3).
0 Automatic devices designed to exclude dry deposition canproduce wet
deposition samples contaminated by dry deposition if the protective
lid does not seal the collection bucket tightly. Wet deposition
networks should be designed to estimate dry deposition
contamination, by site and by chemical element (Section 8.2.3).
0 Most precipitation chemistry networks have only measured the
soluable fraction of the major ions. This procedure is reasonable
for acidic wet deposition studies because major ions generally can
be used to predict a pH that is close to the measured pH (Section
8.2.4).
0 Understanding reasons for pH changes sometimes observed during
handling and storage requires consideration of other chemical
constituents and measurement of both the soluable and insoluable
fractions (Section 8.2.4).
8-79
409-261 0-83-23
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TABLE 8-14. POTENTIAL SOURCES FOR CHEMICAL SPECIES FOUND
IN SAMPLES OF GLACIER ICE
Chemical
Species
*1,4,5
h'ogenic
Emission
1,2,4,5,6
Crustal
Weathering
1,2
Lightning
Discharge
1,2,4,5
Seasalt
2,4,5
Volcanism
1,2,3,4,5
Anthropo-
genic
Emission
Volatile
trace
metals
(Pb, Hg)
* Source Characteristics
? - species production from
this source uncertain.
Temporal Distribution
1 - cyclic (seasonal)
2 - non-cyclic (inter-annual &/or intra-annual)
3 - significant only as of post-AD 1850
Spatial Distribution and magnitude of species
4 - distance &/or elevation source to site
5 - atmospheric circulation pattern source to site
6 - aerial distribution of local ice-free terrain
(increasing importance of factors such as 5 (i.e., monsoonal flow) and 6
increase likelihood of 1 compared to 2)
8-80
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Sampling networks should be operated for periods of many years to
determine variability in the general patterns of precipitation
quality. Deposition patterns over time are highly variable because
they include the variability of both the ion concentration and the
precipitation amount patterns (Section 8.2.4).
Regional and national wet deposition networks with automatic
collectors have been operated continuously in the United States and
Canada since the late 1970's (Section 8.2.4).
These networks provide reasonable resolution of major ion
concentrations for eastern precipitation but, to date, only an
indication of what western patterns might generally be. The
difference in sampling site density accounts for the difference in
our knowledge of precipitation chemistry in the two areas.
Inadequate site density in the west will be corrected in the near
future through the National Trends Network (Section 8.4.1).
Maximum sulfate, nitrate, and hydrogen ion concentrations in
precipitation are observed in the northeast quadrant of the United
States. Levels decrease to the west, south, and farther north in
New England. Elevated levels extend into southeastern Canada
(Section 8.4.1).
Highest calcium concentrations occur in the central regions of the
United States (Section 8.4.1).
Highest chloride concentrations occur along the coasts (Section
8.4.1).
Patterns for each of these ions are consistent with the known
source regions (Section 8.4.1).
Nitrate in U.S. precipitation has increased since the 1950's
(Section 8.4.3.1).
Calcium measured in U.S. precipitation has decreased, perhaps due
to lack of extreme drought recently as compared to the 1950*s, but
more certainly due to improved sampling procedures (Section 8.4.5).
Sulfate and hydrogen ion are much higher in warm season
precipitation in the eastern United States than in cold season
precipitation. The trend follows the aerosol sulfate trend but not
the trend of SOX emissions (Section 8.4.4).
Although precipitation pH in the northeastern United States has
been reported to have decreased in the past 20 to 30 years, several
recent revaluations have suggested that the data do not support
the idea of a sharply decreasing pH trend (Section 8.4.3.2).
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Remote site pH data suggest that the common reference to C02
atmospheric equilibrium value of pH 5.6 is not very useful. Recent
measurements in Hawaii and other locations not strongly influenced
by alkaline dust, indicate that the precipitation is less than pH
5.0. Samples at some remote sites have been found to be unstable,
with pH rising with time, presumably due to organic acid loss.
These relatively acid samples at remote sites meed to be explained
to better understand the acidic samples in areas with strong
anthropogenic influences (Section 8.4.2).
Snow and ice cores collected from appropriately chosen glaciers
provide samples of entrapped chemical species. This technique has
barely been applied to the study of acid precipitation despite the
fact that it provides a very sensitive record of precipitation
chemistry. Little definitive information is available at this time
to elucidate long-term historic trends in regions where they should
be easily detected (i.e., mid-latitude alpine regions both close to
and remote from emission sites) (Section 8.5.3).
Air trajectory analysis, frequently applied to precipitation
chemistry in attempts to identify important source regions for
receptor sites, is qualitative at best. Degree of success probably
varies with location. Applying this fairly simple approach to such
a complex problem leads to doubts about the utility of the
approach (Section 8.4.6).
Wet and dry deposition processes are roughly of equal importance in
the average deposition of specific chemical species (Section 8.3.1)
Direct methods of monitoring dry deposition consist of collecting
vessels, surrogate surfaces, and concentration monitoring from
which deposition rates are inferred. The latter applies to trace
gases and small particles (< 1 to 5 ym diameter), i.e., where
deposition is not controlled by gravity. Surrogate surface methods
apply to particles of a size controlled by gravity and gases for
which species-specific surfaces are used to evaluate air
concentrations (Section 8.3.2.1)
Micrometeorological methods have been developed as alternative
monitoring techniques for surface fluxes. These include eddy-
accumulation, modified Bowen ratio, and variance (Section 8.3.2.2)
Limited data are available on which to base estimates of dry
deposition rates using concentration techniques. A study conducted
for sulfate, nitrate, and ammonium in aerosol measured in the
surface boundary layer had a resolution of four-hour intervals and
gave average diurnal cycles of near-surface concentrations (Section
8.3.3)
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THE ACIDIC DEPOSITION PHENOMENON AND ITS EFFECTS
A-9. LONG-RANGE TRANSPORT AND ACIDIC DEPOSITION MODELS
(C. M. Bhumralkar and R. E. Ruff)
9.1 INTRODUCTION
The previous chapters have described our state-of-knowl edge of the
fundamental physical and chemical processes that affect effluents as
they are transported between sources and receptors. When transport
covers distances of 500 kilometers and above, models that numerically
simulate these physico-chemical processes are called Long-Range
Transport (LRT) models. Currently, justifiable concern about the
adequacy of these models leads researchers to test LRT model performance
quantitatively by comparing model calculations with field measurements.
However, such comparisons have been severely hindered by data bases that
are limited in spatial and temporal coverage and in the types of
parameters that have been measured. As a result, how well model results
compare with the real world is not known. Current research attempts to
improve this situation.
Dozens of different LRT models have been used to establish
quantitative relationships between acidic deposition and emission
levels. Most of these have dealt strictly with sulfur dioxide and
sulfate. There is large variation of the inherent detail from simple to
complex models. The complex models attempt to incorporate the most
detailed (but not necessarily established) treatments that the
state-of-knowl edge will permit. However, in practice, no conclusive
evidence indicates that detailed models can outperform the simpler
models. Both types have given unverified answers, but the simpler ones
have done so at a much more attractive cost. Fortunately, researchers
have recognized the need to continue work on simple and complex models
while awaiting improved data bases that will help resolve existing
questions about performance and applicability.
Several of the models discussed in this chapter have been studied
by the modeling group (U.S.-Canadian Working Group 1982) established
under auspices of the Memorandum of Intent (MOD on Transboundary Air
Pollution signed by the United States and Canada on 5 August 1980.
However, some of the models studied by this group, hereafter referred to
as the MOI group, are not specifically mentioned by name. Rather, this
chapter focuses on generic model types representative of the various
approaches employed to date.
9.1.1 General Principles for Formulating Pollution Transport and
Diffusion Models
The problem of transport can be reduced to solving an equation
representing the conservation of mass. Written in terms of the concen-
tration of a particular chemical species, say C-j, this equation is
9-1
-------
. = Si - Ri + kiV2Ci [9-1]
at
where:
t = velocity vector,
Si = sources of species 1,
Ri = sinks of species i, and
ki = molecular diffusivity of species 1.
The process of physical transport is complicated because the
atmospheric velocity field is not constant in either time or space. To
incorporate the effect of the fluctuation in velocity field on
transport, an averaging assumption is introduced by which all the
variables are redefined as mean values:
Ci = Ci + Ci'. [9-2]
where Ci is the average concentration and Ci1 is the instantaneous
deviation from the average.
Equation 9-1 is then averaged using mean values to give:
1 + ^ • v Ci = Si - Ri + kiV2Ci - v • cV [9-3]
at
where the last term is called the turbulent correlation term.
Generally, the turbulent correlation term is interpreted as a flux of
species i across some surface due to the turbulent velocity, V, i.e.,
= -v • KiVCi [9-4]
which formally defines Ki, the eddy diffusivity of the 1 species.
Because the eddy diffusivity Ki is much larger than the molecular
diffusivity ki, the latter term can be neglected in Equation 9-3.
Thus the equation
3—L + V -V Ci = Si - Ri + V • KiV Ci [9-5]
at
can be used as a representation of the conservation of mass.
Significance has been attached to the difference between the second
term on the left side and the last term on the right side of Equation
9-5. The former represents advection or bulk movement of the average
concentration by the average velocity; the latter represents the
diffusion of material by the turbulent velocity field. Most
considerations in atmospheric transport and diffusion modeling are based
9-2
-------
on a simplification and idealization of either or both of these
processes.
9.1.2 Model Characteristics
Air quality models have a variety of characteristics that can be
defined in terms of:
0 Frame of reference
° Average temporal and spatial scales
0 Treatment of turbulence
° Transport
0 Reaction mechanisms
° Removal mechanisms.
These models may be steady state or time dependent; may incorporate the
effect of complex terrain on wind flow and deposition; and may treat
emissions from point sources or area sources or both, perhaps
distinguishing between elevated and ground emissions. Table 9-1 shows
some of the significant characteristics of the three model types
classified by frame of reference.
Most LRT models are related to a coordinate system or reference
frame that may be fixed either at the earth's surface, at the source of
the pollutant (for either fixed or moving sources), or on a puff of
pollutant as it moves downwind from the source. Models whose reference
frames are fixed at the surface, or on the source, are called Eulerian
models; those whose frames are fixed on the puff of pollutant are called
Lagrangian. Lagrangian models are usually more practical than Eulerian
models in accounting for emissions from individual source locations and
describing diffusion as the pollutants are carried by the wind.
Eulerian models are more capable of accounting for topography,
atmospheric thermal structure, and non-linear processes such as those
governing reactive pollutants.
9.1.2.1 Spatial and Temporal Scales—Atmospheric motions span a range
of spatial scales from the microscale (centimeters) to large synoptic
scales (1000 km). LRT models employ input data representative of the
synoptic scale because of the large transport distances (500 to 2500
km). This includes incorporation of data from the rather sparse upper
air network in North America (approximately 50 stations for the eastern
United States and southeastern part of Canada; these stations measure
winds and temperatures aloft twice a day). When source-to-receptor
distances of less than 500 km become important, a model capable of
treating sub-synoptic scale motions should be employed. In general, LRT
models do not have this capability.
For temporal scales, the assumption has been that the physical and
biological effects are dominated by long term (e.g., annual) dosages of
acidic precursors. However, it appears that insufficient interaction
has occurred among the modelers and effects researchers on this subject.
9-3
-------
TABLE 9-1. CHARACTERISTICS OF POLLUTION TRANSPORT MODELS BY FRAME OF REFERENCE1
Model class
( frame of
reference)
Eulerlan
Lagranglan
Hybrid
(mixed
Eulerian-
Langranglan
Types
of models
Rollback
Statistical
Gaussian plume
and puff
Box and mul ti-
box
Grid
Gaussian plume
and puff
Trajectory
Box and
mul t1 box
Statistical
trajectory
Trajectory
Particle-
In-cell
Puff-on-cell
Physical
Space
Si te-
spedfic/
local
Regional
Site-
specific/
local
Regional
Local
and
regional
Time
Dally
(Episodic)
Daily or
long-term
(monthly
seasonal
annual)
Daily or
long-term
(monthly
seasonal
annual)
Treatment
of
turbulence
Implicit
Eddy
diffusivities
Complex formu-
lation (higher
moment theory)
Well -mixed
vol ume
Eddy
diffusivities
Implicit
Eddy
diffusivities
Complex formu-
lation (not
applicable to
physical models)
Reaction
mechanism
Nonreactlve
Monli nearly
reactive
Nonreactlve
Heavily
parameterized,
linearly
reactive
Nonreactlve
Nonli nearly
reactive
Removal
mechanism
Implicit
Dry and
wet
Dry and
wet
Dry and
wet
Ability
to quantify
source-receptor
relationship
Possible hut
difficult to
implement
Yes
Yes
^Adapted from Drake et al. (1979) and Hosker (19RO).
-------
9.1.2.2 Treatment of Turbulence—Atmospheric turbulence dilutes and
mixes gaseous and particulate pollutants as they are transported by the
mean wind. Turbulence, one of the most important atmospheric phenomena,
is produced by the wind, temperature, and, to a lesser extent, humidity
gradients that occur in the atmosphere.
In a given model, atmospheric turbulence may be represented by a
well-mixed volume, semi-empirical diffusion coefficients, eddy
diffusivities, Lagrangian statistics, or more complex (higher-moment)
turbulence models. The well-mixed volume approach basically ignores
turbulence except in a loosely implicit manner. The most common
parameters in current pollution transport models are semi-empirical
diffusion coefficients determined from field diffusion studies over flat
terrain, usually under neutral stability conditions. Most working-grid
and multibox models use the eddy diffusivity formulation, which is based
on theoretical, physical, and numerical studies of the planetary
boundary layer (PBL).
To account for some of the physical inconsistencies in the eddy
diffusivity formulation, several investigators have developed more
complex formulations of turbulence. These require specifying more
parameters and thus introduce additional uncertainties and increase
computational costs.
Some models have incorporated turbulence effects by applying
Lagrangian statistics generated from field data. This presents a
problem because most field data are obtained in an Eulerian framework.
9.1.2.3 Reaction Mechanisms--LRT models describe the fates of airborne
gases and particles.As these pollutants are transported, physical and
chemical changes may occur. These may be nonreactive mechanisms,
reactive (photochemical and nonphotochemical) mechanisms, gas-to-
particle conversions, gas/particle processes, and particle/particle
processes. However, not all of these processes are explicitly treated
in LRT models.
Both the S02/sulfate and photochemical models have gas-to-
particle components to account for the production of particles directly
from gases via gaseous reactions or condensation. In LRT models this
treatment most frequently is limited to the conversion of sulfur dioxide
to sulfate. Other acidic precursors (e.g., NC^) usually are ignored.
The gas/particle components in the models take into account particle
growth by condensation or gas absorption. Particle/particle processes
in aerosol models treat coagulation, breakup, condensational growth, and
diffusion of particles.
9.1.2.4 Removal Mechanisms--Removal is the reduction of mass of
airborne pollutants by either wet or dry deposition. Wet deposition is
the removal of pollutants by precipitation elements, by both below-cloud
and in-cloud scavenging processes. Dry deposition is the removal of
pollutants by transfer from the air to exposed surfaces.
9-5
409-261 0-83-24
-------
Removal mechanisms used in pollution transport models can vary
widely. Some models listed in Table 9-1 (such as rollback or
statistical models) are not well suited to deposition modeling because
they do not treat physical processes explicitly. Others (such as
Gaussian or Langrangian trajectory models) treat these processes in a
rather straightforward manner. Grid models are especially well suited
to use complex precipitation scavenging and cloud dynamics in treating
wet deposition, although this capability has not been exercised very
often.
9.1.3 Selecting Models for Application
9.1.3.1 General—LRT modeling specialists have made progress in
developing new techniques to meet the challenges of simulating pollution
transport and deposition. A number of excellent comprehensive reviews
of transport models have been prepared, for example Fisher (1978), Drake
et al. (1979), MacCracken (1979), Smith and Hunt (1979), Bass (1980),
Eliassen (1980), Hosker (1980), Niemann et al. (1980), and Johnson
(1981). These and other review papers have indicated that most of the
existing models have been used to:
o Estimate contributions of given sources to receptors of
interest.
0 Estimate consequences of projected emissions changes.
0 Fill gaps between observations.
0 Assist in field study planning, determining such factors as
which variables to measure and where to site stations.
o Assist in interpreting data, e.g., by inferring
transformation or deposition rates.
Most of these tasks can be accomplished only by using models in concert
with field measurements where available.
9.1.3.2 Spatial Range of Application—Model calculations have been
performed over spatial scales classified as short range (< 100 km),
intermediate range (100 to 500 km), and long range (> 500 km). Table
9-2 lists some of the model types that are commonly used for each of
these ranges. Terminology specific to spatial scales has changed over
the years. Lately, the terms regional and long-range transport have
both been used to describe models capable of treating distances of 100
km and greater.
Generally, the Gaussian plume model has been the choice for
short-range calculations. However, in hilly terrain the Gaussian model
is inadequate even at short distances. In such cases, a trajectory
model is perhaps more suitable. For intermediate ranges, a Gaussian
plume model is sound if uncertainty about dispersion coefficients at
9-6
-------
TABLE 9-2. MODEL TYPES USED WITH DIFFERENT SPATIAL RANGES
Spatial Range
Model Type
Short
(< 100 km)
Intermediate
(100-500 km)
Gaussian plume
Trajectory
Particle-in-cell
Puff-on-cell
Gaussian plume
Trajectory
Grid
Particle-in-cell
Puff-on-cell
Long
(> 500 km)
Trajectory
Grid
Box
9-7
-------
these distances is taken into account. Applying intermediate range
Gaussian models in this range presents problems if wind and
precipitation distributions vary significantly. In complex terrain,
shorelines, or forested terrain, a trajectory model, with plume or puff
dispersion, is more appropriate for intermediate ranges. For long-range
transport, trajectory ensemble models, box models, or grid models can
be used.
9.1.3.3 Temporal Range of Application—Table 9-3 lists general types of
models on the basis of the averaging time used in their applications. A
host of Lagrangian trajectory-type LRT models have been used for
long-term applications. Some modelers (e.g., Bhumralkar et al. 1981)
have also developed a short-term model, modifying the long-term model by
incorporating a more detailed treatment of boundary layer and diffusion
processes. A few Eulerian models have been developed for long-range and
short-term applications (e.g., Durran et al. 1979).
9.2 TYPES OF LRT MODELS
Table 9-4 lists some of the LRT models that have been developed to
date. Their properties are discussed below.
9.2.1 Eulerian Grid Models
The Eulerian grid model divides the geographical area of the volume
of interest into a two- or three-dimensional array of grid cells.
Advection, diffusion, transformation, and removal (deposition) of
pollutant emissions in each grid cell are simulated by a set of
mathematical expressions, generally involving the K-theory assumption
(that the flux of a scalar quantity is proportional to its gradient).
Some finite-difference technique is usually employed in the numerical
solution of these equations.
The major advantages of the Eulerian grid approach are:
o Eulerian grid models are capable of sophisticated
three-dimensional physical treatments.
0 The approach can handle nonlinear chemistry.
0 Data input is simplified on the Eulerian grid.
The disadvantages of the Eulerian grid approach are:
0 Such models usually require large amounts of computer time,
computer storage, and input data.
o These models, when they incorporate non-linear modules,
are cumbersome to use to determine contributions from
individual sources.
o Artificial (computational) dispersion can be significant.
9-8
-------
TABLE 9-3. SHORT-TERM AND LONG-TERM MODELS
Temporal Range
Model Type
Short term
(hourly, daily)
Long term
(monthly, seasonal,
and annual)
Gaussian puff
Lagrangian trajectory
Particle-in-cell
Puff-on-cell
Grid
Gaussian plume and puff
Lagrangian trajectory
Statistical trajectory
9-9
-------
TABLE 9-4. LONG AND INTERMEDIATE RANGE TRANSPORT MODELS
Model Type
and Method
Investigator
Eulerlan
Finite Differencing
Pseudospectral method
Lagrangian
Statistical trajectory
Receptor orienteda
Source oriented
Hybrid; Mixed
Lagrangi an-Euleri an
Particle-in-cell (PIC)
Atmospheric diffusion
Particle-in-cell (ADPIC)
Puff-on-Cell
Lavery et al. (1980); Durran et
al. (1979); Carmichael and Peters
(1979); Egan et al. (1976); Nordo
(1976, 1974); Pedersen and Prahm
(1974)
Berkowicz and Prahm (1978);
Prahm and Christensen (1977),
Christensen and Prahm (1976);
Fox and Orsag (1973)
Fay and Rosenzweig (1980);
Venkatram et al. (1980); Shannon
(1979); Fisher (1978, 1975);
Mills and Hirata (1978); Sheih
(1977); McMahon et al. (1976);
Bolin and Persson (1975); Scriven
and Fisher (1975); Rodhe (1974,
1972)
Samson (1980); Henmi (1980);
Olson et al. (1979); Ottar
(1978); Szepesi (1978); Eliassen
and Saltbones (1975)
Bhumralkar et al. (1981);
Bhumralkar et al. (1980); Heffter
(1980); Powell et al. (1979);
Johnson et al. (1978); Maul
(1977); Wendell et al. (1976)
Sklarew et al. (1971)
Lange (1978)
Sheih (1978)
aReceptor oriented models usually have options to compute forward
(source oriented) and backward trajectories.
9-10
-------
9.2.2 Lagrangi'an Models
9.2.2.1 Lagrangian Trajectory Models--A characteristic feature of these
models is that calculations of pollutant diffusion, transformation, and
removal are performed in a moving frame of reference tied to each of a
number of air "parcels" that are transported around the geographical
region of interest in accordance with an observed or calculated wind
field.
As indicated in Table 9-4, Lagrangian trajectory models can be
either receptor oriented, in which trajectories are calculated backward
in time from the arrival of an air parcel at a receptor of interest, or
source oriented, in which trajectories are calculated forward in time
from the release of a pollutant-containing air parcel from an emission
source.
Most source-oriented Lagrangian trajectory models simulate
continuous pollutant emissions by discrete increments or "puffs" of
emission occurring at set time intervals, usually between 1 and 24 hr,
depending upon the designed averaging time of the model outputs. Such
models simulate movement and behavior of a pollutant plume from a
continuous source, as shown by one of the four approaches illustrated in
Figure 9-1 (Bass 1980).
Some of the advantages of Lagrangian trajectory models are:
0 The models may be used to estimate contributions from
individual sources.
o The models are relatively inexpensive to run on a computer.
° Pollutant mass balances are easily calculated.
o Individual sources or receptors can be treated separately.
The disadvantages of these models are:
o The extension to three dimensions is not straightforward.
o Nonlinear physical and chemical formulations are difficult to
incorporate.
0 Horizontal and vertical diffusion are highly parameterized.
The two most important features of the Lagrangian trajectory model
are its capability for calculating detailed source-receptor
contributions and its computational efficiency. To achieve the latter,
most models of this type are more highly parameterized and thus are
potentially less physically realistic than some Eulerian grid
approaches.
9-11
-------
CONTINUOUS PLUME MODEL
SEGMENTED PLUME MODEL
m
PUFF SUPERPOSITION MODEL
"SQUARE PUFF" MODEL
Figure 9-1. Trajectory modeling approaches. Adapted from Bass (1980).
9-12
-------
9.2.2.2 Statistical Trajectory Models--As shown In Table 9-4, several
Lagrangian models are characterized as statistical trajectory models.
Although many different kinds of statistical trajectory models exist,
each has one or more of the following characteristic features that
distinguish the type:
0 Large numbers of air trajectories are calculated either
forward in time from source areas or backward in time from
receptor areas, and the results are statistically
analyzed to give average pollutant contributions.
o Meteorological variables are frequently averaged over long
time periods before such parameters as concentrations and
depositions are calculated.
Statistical trajectory models have the following advantages:
° Computational requirements are modest.
° The models are cost efficient for repeated runs using
alternative emissions scenarios.
0 The models do not suffer from computational dispersion.
0 The models may be used to estimate contributions from
individual sources.
° Pollutant mass balances can be estimated.
Disadvantages of statistical trajectory models are:
o Most types are not adaptable to short averaging times (i.e.,
episodes).
0 Dispersion and other processes are usually highly
parameterized.
o Some types ignore dependence between meteorological variables
(e.g., wind and precipitation).
In summary, the low computational cost of statistical trajectory
models is often obtained at the expense of physical realism.
9.2.3 Hybrid Models
In the hybrid (mixed Lagrangian/Eulerian) approach, pollutants,
whose distribution is represented by Lagrangian particles or puffs, are
transported through a fixed Eulerian grid that divides physical space
into several cells. The particles or puffs are moving horizontally in a
derived velocity field in the model domain. The hybrid approach offers
advantages of both Eulerian and Lagrangian models. For example, hybrid
models can provide treatment of nonlinear reactions between the
9-13
-------
compounds of Interest (In the Eulerian framework) and the source-
receptor relationship (in the Lagrangian framework). One of the main
disadvantages of the hybrid approach (especially the particle-in-cell
method) is that to simulate spatial distribution of pollution satis-
factorily, a large number of particles must be used. This has been
obviated considerably by the POC (puff-on-cell) method developed by
Sheih (1978).
9.3 MODULES ASSOCIATED WITH CHEMICAL (TRANSFORMATION) PROCESSES
9.3.1 Overview
Primary air pollutants undergo reactions in the atmosphere, forming
secondary pollutants such as ozone from M0x-hydrocarbon reactions and
sulfates from SO^ oxidation reactions. The compounds that appear in
rainwater are mainly sulfate and nitrate anions and hydrogen and
ammonium cations; they typically account for more than 90 percent of the
ions in rainwater.
Theoretical, laboratory, and field experiments seem to indicate
that both homogeneous and heterogeneous processes are important.
However, the range of transformation rates, the conditions by which they
vary, and the actual mechanisms still largely remain beyond simulation
capabilities.
9.3.2 Chemical Transformation Modeling
As source emissions are changed from gases to aerosols, or (through
a reaction with other materials in the atmosphere) to different com-
pounds, their wet and dry removal rates will change, affecting their
subsequent concentrations. Furthermore, the chemical transformations at
any given time will depend on prior transformation, dilution, and
removal.
Considerable research has been performed to understand the combined
processes of atmospheric transport, diffusion, wet/dry removal, and
chemical transformation. The LRT model normally incorporates a separate
module that treats each of these processes. As is the case with most
modules, chemical routines are most often gross simplifications of more
detailed kinetic models that were developed independently of the overall
modeling effort.
There are two approaches to modeling chemical transformations:
0 By approximation with simplified first-order reactions. As
described in Chapter A-4, the conversion of S02 to sulfate
is usually treated this way.
0 With more complex sets of reactions describing transformations
among many compounds. However, only a few developmental
models (e.g., Carmichael and Peters 1979) employ non-linear
mechanisms.
9-14
-------
The simplified first-order approximations can be used with all
approaches to the modeling of pollution transport: Eulerian,
statistical or Lagrangian trajectory, and hybrid models. The
multlreaction schemes are most suitable for implementation in Eulerian
or hybrid models. Lagrangian models, under some special circumstances,
can use multireaction schemes. In general, this is possible only when
the emissions from one source can be treated separately from those of
other sources. Thus, such models can treat the chemical transformations
taking place in a plume from an isolated source within the vicinity of
that source, extending out to the point where it begins to overlap
significantly with plumes from other major sources.
9.3.2.1 Simp!ified Modules—Currently, many models treat transforma-
tions either by assuming that they take place at a constant rate or by
using simple first-order reactions. This type of treatment usually
ignores secondary pollutants (e.g., ozone, HO) and their dependence on
time of day, season, and latitude (Altshuller 1979). This simplified
treatment usually ignores any heterogeneous reactions that may take
place. Please refer to Chapter A-4 for a detailed discussion on
transformations.
The currently used simple modules of chemical transformation are
chosen such that the model results are consistent with observations
rather than on the basis of their consistency with theory. Because most
models have been trajectory models and, therefore, superposition of
plumes is assumed, linear chemistry is required to treat transformation.
It is common for models to assume that about 1 percent of the $63 is
converted to $042- each hour. Many models have yet to consider
dependence on temperature, relative humidity, photochemical activity,
time of day/year, particulate loading, or concentrations of other
pollutants. To illustrate dependencies of model calculations to such
parameters, a recent set of model calculations has made the transforma-
tion rate a function of zenith angle and of source type. This resulted
in a variation of 5 to 10 percent in predicted $03 and S042"
concentrations in comparison with results from the same model using a
fixed transformation rate.
9.3.2.2 Multireaction Modules--Although more realistic treatment is
possible with multireaction simulations {particularly with Eulerian
models), their implementation is often difficult. For example, the
model reaction schemes frequently emphasize photochemical processes
because those processes are more easily defined. The reactions between
the pollutants may be well known and characterized. The chemical models
may simulate laboratory smog-chamber experiments, with their well-
defined conditions and concentrations, quite reasonably. Nevertheless,
the application of these multireaction sets to the real world is often
difficult because of the wide variety of ambient conditions and
pollutant concentrations that occur. The detailed knowledge required
for simulating many of the reactions calls for air quality or
meteorological data not available on a sufficiently dense spatial scale,
horizontally and vertically. Data assumptions that must then be made to
exercise the detailed chemical modules are often not very different,
philosophically, from the cruder reaction assumptions in simpler models.
9-15
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Another major weakness of most chemical transformation modules is
the way heterogeneous reactions are handled. Under conditions of high
humidity or weak sunlight, these reactions are important. In the
context of acidic deposition, many of the more important heterogeneous
reactions involve conversion from sulfur dioxide to sulfate. Among the
catalysts and reactants are:
o Oxygen
0 Iron
o Manganese
0 Carbon (soot)
o Ozone
0 Hydrogen peroxide.
Freiberg and Schwartz (1981) have pointed out some of the difficulties
in handling heterogeneous reactions involving sulfur compounds. They
note that heterogeneous formation of sulfate can take place over a
number of different paths, including uncatalyzed oxidation, reactions
with oxidizing agents (e.g., ozone or hydrogen peroxide), oxidation
catalyzed by transition metal ions, or surface-catalyzed reactions.
Furthermore, all the processes are complicated by finite mass transfer
rates between phases. Although heterogeneous transformations are
undeniably important, their inclusion in chemical transformation modules
has heretofore been cursory at best.
Chapter A-4 describes a variety of the chemical transformation
mechanisms that have been proposed. However, incorporating such
mechanisms into a long range transport model with spatial resolutions of
tens of kilometers (typically 80 km) is not always consistent with the
sub-grid scale of the actual physical process. In general, the spatial
scale is more consistent with urban modeling (typically less than 5 km).
For this reason, some compromise must be struck between a comprehensive
chemical scheme and practical application in LRT modeling. A number of
factors must be considered in striking this compromise; these factors
will relate to the intended applications of the model. For example, if
only source/receptor relationships entailing total amounts of sulfur are
required, chemical transformations involving sulfur compounds are
important only to the degree that they affect removal processes. When
pH is important, the number of important reactants and reactions
increases dramatically to include a broad range of sulfur- and
nitrogen-containing compounds, oxidants, potential catalysts, and
precursors to all of these.
9.3.3 Modules for N0y Transformation
Until quite recently, treatment of nitrogen pollutants in LRT
models had been set aside in favor of work on sulfur pollutants. This
is partially because of the emphasis on sulfur pollutants in the past
few years and partially because nitrogen chemistry has been considered
too complex for incorporation into a simple model. One problem has been
how to incorporate NOX chemistry into present models that require a
9-16
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linear parameterization; another problem is the difference in the time
scales on which NOX and SOX chemistry occurs. For example, in LRT
models, because of the relatively slow rate of conversion of S02 to
$042-, it is possible to use coarse emission grids and a 3-hr
integration time step, which enables these models to be used
economically. However, with the more rapid NOjj chemistry, such coarse
spatial and temporal resolution cannot be justified, thereby making
model application impractial.
The problem of modeling NOX conversion in the atmosphere can also
be attributed to two other considerations. First, the primary end
products of NOX conversion in the atmosphere (mainly, HN03 and PAN)
do not appear until after most of the NO has been converted to N02,
which takes approximately 2 to 3 hours. This reaction delay for fresh
emissions into an air column must be preserved in a transport model.
The second point is that most of the end products in both the simulation
and measurements in urban air masses are gaseous. These account for at
least 90 percent of converted nitrogen in the atmosphere. Aerosol
nitrates constitute only about 5 to 10 percent of the end product
(Spicer et al . 1981).
Despite the difficulties discussed above, researchers have started
to incorporate NOX chemistry into LRT models. However, these NOX
modules have not yet been evaluated by comparison of results with
reliable measurements. Most of the researchers have assumed that the
NOX conversion could be handled by simple first-order rate equations
analogous to those for S02« Recently, an intermediate product, PAN,
was introduced into the calculations in a short-term version of the
ENAMAP model (Bhumralkar et al. 1982). The research suggests
application of the simplified set of reactions and constants given in
Table 9-5. In this approach first order rate equations are used to
determine the concentrations of the reaction products. For example, the
rate equation for N02 is:
= -a(kn[N02])+b(kp[PAN]). [9-6]
dt
The other reaction products (PAN, HN03, and N03~) are governed by
similar equations. In this example, the partition constants, a and b,
are unity. For the other products, these constants are different and
are chosen to give the partition percentages given in Table 9-6. Table
9-6 shows that a large proportion of PAN is formed during the day but is
removed at night. This removal is caused by thermal decomposition and
is accompanied by a conversion of PAN to N02.
The above formulation neglects the explicit incorporation of
hydrocarbons (HC), primarily the influence of the HC/NOX ratio. As
described in Chapter A-4, this ratio appears to have a strong influence
on the N02 conversion rate and on the ratio of PAN to HN03-
9-17
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TABLE 9-5. AN EXAMPLE OF CHEMICAL REACTIONS AND RATES (HR-1) FOR AN
NOX MODULE (BHUMRALKAR ET AL. 1982)
Reaction Rate
Reaction Day Night
NO •? N02a
*n
N02 •* PAN + HN03 + N03" 0.1 0.02
kd
PAN + PAN + HN03 + N03~ 0.1 0
"P
PAN •* N02 0 0.02
aThe ratio N02/N0 is assumed to be at equilibrium
with a value of 2 during the day and 50 at night.
9-18
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TABLE 9-6. PARTITION OF CONVERSION PRODUCTS OF EXAMPLE NOX REACTIONS
(BHUMRALKAR ET AL. 1982).
Day Night
Product (%) (%)
HN03 (gas) 40 85
PAN (gas) 50 0
N03" (aerosol) 10 15
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9.4 MODULES ASSOCIATED WITH WET AND DRY DEPOSITION
9.4.1 Overview
Existing pollution transport models represent pollution deposition
removal in several different ways. The simplest approach involves
incorporating a nonspecific decay form intended to treat both wet and
dry processes. As pointed out by a number of reviewers, such as
MacCracken (1979), Eliassen (1980), and Hosker (1980), the values of
deposition coefficients used in various pollution transport models vary
widely, sometimes by more than a factor of ten. This is partly caused
by the different model formulations, but it also reflects, in a major
way, a basic lack of knowledge in the area. The problem of
incorporating removal by deposition in LRT models is made more difficult
because the measurements of deposition coefficients for many chemical
species of interest are either nonexistent or exhibit a major degree of
variability even when stratified, indicating that the values of
coefficients are influenced by a number of factors. Some of the factors
known to have significant effects on wet and dry depositions are:
Wet deposition:
0 Atmospheric properties
- Precipitation rate and type
- Cloud type and size
- Storm intensity
- Temperature and humidity.
o Pollutant properties
- Form (and size distribution if particulate)
- Solubility and reactivity
- Concentration vertical profile
- Location relative to clouds.
Dry deposition:
0 Atmospheric properties
- Solar radiation
- Wind speed
- Atmospheric stability
- Surface aerodynamic roughness
- Humidity.
0 Pollutant properties
- Form (and size distribution if particulate)
- Concentration vertical profile
- Solubility and reactivity.
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0 Vegetation properties
- Type, size, leaf area, density
- Stomatal condition
- Growth stage
- Stress condition
- Wetness.
0 Other surface (non-vegetation) properties
The current models account for wet and dry deposition with highly
parameterized treatments that do not explicitly include many of the
factors in the above lists. Some of the effects of these variables can
be considered to be "averaged out" over the long travel distances and
large spatial averaging areas involved in interregional-scale modeling.
Comparing model-calculated depositions to available measured values
produces information useful to help select suitable values for such
"integrated" values of deposition coefficients. In general, however,
much additional fundamental knowledge about the deposition processes is
needed to facilitate further progress in developing models for studying
acidic deposition problems.
The discussion in this chapter is strictly confined to modules for
treatment of wet and dry deposition in current pollution transport
models. The basic theory and principles pertaining to these have been
described in Chapters A-6 and A-7.
9.4.2 Modules for Wet Deposition
9.4.2.1 Formulation and Mechanism—Various parameterization techniques
are used for modeling washout in terms of rainfall rate and
characteristic scavenging efficiency. These offer at least the
capability to describe wet deposition formally. Precipitation rates can
be highly variable, and spatially limited, especially during active
convective situations. Therefore, it is difficult, if not impossible,
to categorize rainfall rate on a scale adequate to describe the fate of
a plume, especially in its early stages.
In existing models, removal by wet deposition has been
parameterized in terms either of the scavenging coefficient, A, or
washout ratio, W, (Dana 1979; Refer to Chapter A-6 for a more
comprehensive discussion of the scavenging coefficient). The former
results from the assumption that wet deposition is an exponential decay
process obeying the equation:
Ct = CQ exp (- At) [9-7]
where:
C^ = atmospheric concentration at time t,
CQ = atmospheric concentration at initial time, and
A = scavenging coefficient (in units of time-*).
9-21
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The concept of a washout ratio is used frequently in steady-state
models. It is defined as the concentration of contaminant in
precipitation divided by its concentration in air (usually at the
surface level); i.e.,
W = % [9-8]
where:
X = concentration of contaminant in precipitation,
C = concentration of contaminant in unscavenged air, and
W = washout ratio (dimensionless).
The spatial and temporal distribution of the concentrations
determine how A and W are related. For example, for the simple case
of pollutant washout from a column of air having a uniform concentration
over height, h, one obtains:
A = W [9-9]
where:
R = the precipitation intensity.
The values of washout coefficients, at least for S02 and
SO/}2', vary widely among various modelers, with disagreement even on
which pollutant is scavenged most efficiently.
9.4.2.2 Modules Used in Existing Models--Wet deposition is usually
calculated by using Equation 9-7 and allowing A to vary with position
to account for precipitation changes over the region of interest.
However, the basic problem in applying equation 9-7 is the actual
evaluation of A which depends on the characteristics of the rainfall
and the scavenged effluent. Also, because the scavenging rate approach
inherently assumes an irreversible collection process, it is suitable
for gases only if they are extremely reactive. For gases that form
simple solutions in water, it is essential to account for possible
desorption of gas from droplets as they fall from regions of high
concentrations toward the ground (Hosker 1980).
The wet deposition of soluble gases in Gaussian plume models has
been calculated under simplifying assumptions of steady state, negli-
gible chemical reactions, and vertical fall of raindrops. However, many
gases of interest become acids when in solution, and their solubility
then becomes a function of pH. Inability to calculate actual pH forces
an empirical approach to estimating washout ratios, W, for gases,
similar to those for particulates. However, some empirical approaches
(e.g., Barrie 1981) have suggested ways of estimating improved S02
washout ratios.
Some models represent wet deposition in terms of wet deposition
velocity, Vw, given by
9-22
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_ wet flux . [9-10]
w concentration in air at the surface
This has been estimated from empirically determined washout ratios W
given by Equation 9-8 (SIinn 1978). Because wet flux to the surface
is simply X-R (where R is the precipitation rate), Vw has been
estimated by using
Vw = WR . [9-11]
The wet deposition velocity has been used in models for the wet removal
process. In some cases, the washout ratio has been used directly to
give an exponential decay term for a plume if the thickness of the wet
layer of plume is known (Heffter et al. 1975, Draxler 1976).
In Lagrangian puff and trajectory models (e.g., Bhumralkar et al.
1981) wet deposition is generally treated via an exponential decay term
(Equation 9-7) where the parameter depends on the characteristics of the
effluent and the precipitation. This technique is applicable to
irreversible scavenging of particles and highly reactive gases.
In Eulerian grid models, wet deposition is generally handled by an
exponential decay term, exp(- At), although some models simply assume
that all the effluent is scavenged immediately when precipitation is
encountered (e.g., Peterson and Crawford 1970, Sheih 1977). An
interesting variation is contributed by Bolin and Persson (1975), who
calculate the wet removal rate from
3 / Xdz . [9-12]
0
The coefficient 3 is an "expected" overall scavenging rate that takes
into account the probability of rainfall, its likely duration and
intensity, and the actual scavenging rate 3 expected for such
precipitation (Rodhe and Grande!! 1972). Evidently 3 can vary with
locale and season; the method seems best suited to long-term-average
investigations. Wet deposition velocities, washout ratios, or both, do
not seem to have been used in grid models to any extent. However, work
on such formulations is in progress.
Complex numerical models dealing with wet deposition, including
cloud dynamics, have been described by Molenkamp (1974), Hane (1978),
and others. These models deal with the equations of motion for cloud
formation, precipitation formation, and the various scavenging phenomena
that may apply. For example, an interactive cloud-chemistry model has
been used to calculate effects of cloud droplet growth and S02
oxidation within the droplet on pH. With this approach, nucleation
scavenging can be examined for different types of clouds (e.g., wave
cloud and stratus cloud). This type of work is still in a research
phase. It requires parameter!'zations of only partially understood
9-23
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processes and (like most deposition models) is still unvalidated. Such
research, while potentially useful, is presently unsuitable for
practical application.
In hybrid (Lagrangian plus Eulerian) transport models (e.g.,
particle-in-cell), treatment of wet deposition is more complicated.
Whereas it is relatively easy to deal with aerosols/particulates,
problems occur in dealing with gases. However, the wet deposition
velocity concept can be used for gases in these types of models.
9.4.2.3 Wet Deposition Modules for Snow—It is sometimes necessary to
differentiate between wet deposition by snow and rain. This is based on
the following considerations:
° The scavenging coefficients vary with season and depend on the
precipitation intensity.
° The scavenging coefficient is a function of raindrop and
snowflake size distribution and effective scavenging area.
0 The scavenging coefficient is strongly dependent on the type
of snow (e.g., plane dendrites are much more effective as
scavengers than grouped); no such differentiation is applicable
to rain.
To date, very few LRT models have incorporated the above
considerations explicitly in the modeling of wet deposition.
9.4.2.4 Wet Deposition Modules for NOX--Very little information is
available in the literature concerning treatment of wet deposition of
nitrogen compounds in transport models. As a general rule, the
information that has been given is expressed as a fraction of the rates
estimated for sulfur compounds. The approach is obviously crude, and
this is certainly an area where extensive use could be made of data
bases that have been collected in recent years.
McNaughton (1981) has made some progress in developing
relationships among sulfate, nitrate, and precipitation pH for use in
modeling. He has used wet deposition observations available from a
number of research and monitoring networks, including MAP3S (Multistate
Atmospheric Power Production Pollution Study), EPRI (Electric Power
Research Institute), NAOP (National Atmospheric Deposition Program),
CANSAP (Canadian Network for Sampling Precipitation), and Ontario Hydro,
in model evaluation studies (e.g., McNaughton 1980). It may be noted
that, whereas deposition networks are not as dense as modelers of
pollution transport and deposition would prefer, considerable wet
deposition data exist for model verification.
9.4.3 Modules for Dry Deposition
9.4.3.1 General Considerations—The dry deposition rate of gases and
particles has usually been parameterized using a deposition velocity
V
-------
Vd = F/C [9-13]
where
F = the flux of material,
C = the ambient concentration at a particular height, and
V(j (which is a function of height) refers to the same level as
the concentration measurement.
This simplified treatment of a deposition velocity conveniently ignores
the complexities of the governing processes as described in Chapter A-7.
However, such simplifications are consistent with other treatments
imbedded in LRT models. Sehmel (1980) has summarized many of the
parameters that affect dry deposition rates; these concepts are examined
in Chapter A-7.
A common approach used in many models has been to assume a constant
dry deposition velocity for each pollutant over the entire model domain.
Of course, this is unrealistic because pollutants are absorbed
differently by different surfaces (e.g., vegetation, soil, or water),
and because atmospheric stability can also be a factor, particularly
during nighttime.
Recently, models have used dry deposition velocities that are
functions of land-use types and atmospheric stability. Sheih et al.
(1979) have prepared maps of surface deposition velocities for sulfur
dioxide and sulfate particles over eastern North America that take into
account land use, atmospheric stability, and seasonal differences.
Variations in deposition rates for nitrogen compounds can also be mapped
in a similar fashion, although the necessary field studies for
characterizing different surfaces and stabilities are only beginning to
be conducted.
Among the reasons for characterizing deposition rate according to
season is that the character of the earth's surface changes from season
to season—deciduous vegetation changes with the growth and loss of
leaves; in grasslands, the grass dies and and is replaced by a snow
cover. The reason for including atmospheric stability as part of the
categorization scheme is that dry deposition depends on the concen-
tration of material in the lowest layers, just above the surface. These
low-level concentrations in turn depend on the rate at which material
is transported from higher layers to replace that which is lost to the
surface; these transfer rates depend on atmospheric stability. The
latter effect can be simulated more directly if the atmosphere is
subdivided into layers for purposes of modeling. A compromise can be
struck between detailed simulation of the vertical structure of the
atmosphere and stability-based parameterization, using a surface layer
formulation, which controls deposition based on observed vertical
distribution of the material of concern.
Verifying dry deposition simulations is currently difficult because
we lack monitoring instrumentation. A number of carefully controlled
field measurements of dry deposition fluxes have been made, principally
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by the eddy correlation method. The results can be used in examining
the scientific validity of the parameterization used in the models.
9.4.3.2 Modules Used in Existing Models- -In Lagrangian puff/trajectory
models, generally the vertically integrated concentration of puffs is
depleted by an exponential factor
[9-14]
where:
k = dry deposition flux
vertically integratedconcentration
Most of these models compute the dimension!ess value for kd from
Vd-C
where h is the height of the surface layer. For simpler models there is
only one uniformly mixed layer so h is simply the mixing height. Some
Lagrangian models (e.g., Shannon 1981) incorporate several layers in the
vertical, and dry deposition processes are allowed to remove material
from only the surface layer. Eddy diffusivity controls the redistribu-
tion between the vertical layers. These models sometimes also include
treatments that allow the dry deposition velocities to vary with season,
time-of-day, type of underlying surface, and atmospheric stability.
In Eulerian grid type models, dry deposition is treated in a way
similar to that discussed above. These models are especially well
suited to use the relation between mass flux, dry deposition velocity,
and concentration at or just above the surface. Constant values for
Vd are often used, probably for simplicity, although some grid models
(Durran et al. 1979) include an algorithm that allows Vd to vary in
time and space, reflecting changes in terrain, ground cover, and
atmospheric conditions.
9.4.3.3 Dry Deposition Modules for N0x--As stated previously, most
models treat the sulfur oxTde-sulfate cycle exclusively. The nitrogen
oxides-nitrate cycle is being treated in only a few models (e.g.,
Bhumralkar et al. 1982). For these models, the mathematics of dry
deposition treatment remains the same is it was for the sulfur version.
However, the values for the dry deposition velocity are different.
Chapter A-7 gives a comparison of experimentally determined dry
deposition velocities.
9.4.4 Dry Versus Wet Deposition
The relative significance of dry and wet deposition in LRT models
has not been examined in a systematic way, but is now being studied via
9-26
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field experiments. In early field experiments, the emphasis was on the
wet removal process; consequently, few data on dry deposition were
collected and hence large uncertainties exist on dry deposition
velocities.
A reasonable comparison between dry and wet removal rates can be
made when the deposition modules incorporate the roles of pollutant
release height and precipitation frequency. For example, whereas dry
deposition will play an important role in removing pollutants near
ground level, wet deposition can be expected to be spotty and
intermittent because of naturally occurring spatial and temporal
variation in precipitation events.
9.5 STATUS OF LRT MODELS AS OPERATIONAL TOOLS
9.5.1 Overview
The ability to simulate complex physical and chemical processes of
the natural environment is essential for making regulatory and policy
decisions. There is no economical way to gather enough observations to
determine, from the data alone, all the possible combinations that can
occur in the real world. In addition, the effect of altering the
existing situation cannot be assessed by collecting observations before
such alterations take place. Thus, modeling is the only means by which
the efficiency and advisability of control strategies can be assessed.
The past decade has seen increasing concern about production and
long-distance travel of pollutants such as sulfates and nitrates and
deposition of these precursors of acid on sensitive areas at long
distances from sources. Such concern has given impetus to developing
and applying several LRT models, not only for studying acidic deposition
processes but also for policy-making and regulatory purposes.
The understanding of the complex processes that act to transform
and transport pollutants is incomplete, and the capacities of even the
largest computers do not permit easy simulation of the almost infinite
combination of physics, chemistry, and hydrodynamics of the real world.
It is therefore necessary to simplify and parameterize the mathematical
simulations. The effects of these simplifications are not fully
understood and understanding will not be achieved until the models
undergo rigorous evaluation. The evaluation is not limited to the model
itself, but must extend to the data base that drives the model and the
data base that is used to assess performance. In the remainder of this
section, model applicability and performance are discussed along with
their attendant data requirements.
9.5.2 Model Application
9.5.2.1 Selection Criteria
Ideally, the choice of a particular model as an operational tool is
based on the specifications of the particular application at hand; how
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well the model has performed in comparable applications; and the
availability of suitable data to drive the model. In turn, the
specifications of the application should be determined by certain air
quality regulations (when applicable) and the ecological effects being
addressed. Such criteria determine the spatial and temporal scales and
the chemical compounds that the selected model must treat.
The spatial ranges of concern might require treatment of long-range
transport (> 500 km), intermediate range transport (100 to 500 km),
short range transport (< 100 km), or combinations of all three. The
discussion here has focussed on the long-range problem with the
assumption that the resolution is sufficient for smaller (spatial) scale
problems. When the receptor locations of interest are influenced by
large sources within distances of 500 km, the resolution in these LRT
models may be inadequate (unless they include smaller scale treatments).
Obviously, for some applications, this is a serious limitation in almost
all existing 1RT models.
In most LRT models, temporal scales germane to acidic deposition
have been assumed to be long-term (e.g., monthly, seasonal, and annual
averages). The underlying assumption is that the effects of acidic
deposition result from long-term build-ups, not short-term episodes.
Only a limited number of models have been developed to address the
short-term (e.g., 3-hr averages). Most of these applications have
focused on ground level concentrations, not depositions, of certain acid
precursors (primarily $02)• Until recently, treatment of wet
deposition was ignored in most short-term models. Now, a host of
short-term models treat both wet and dry depositions of acid precursors.
However, much less effort has been put into the evaluation of these
long-range, short-term models in comparison with those designed for
long-term calculations. As a result almost no knowledge exists on the
performance of short-term models in calculating depositions of acidic
compounds.
A major problem is that there are certain types of applications for
which no single model may be appropriate. The majority of LRT models
have been designed to calculate long-term concentrations and depositions
of sulfur dioxide and sulfate. Some of these models also treat nitrogen
oxides and nitrates, but much less is known about model performance for
nitrogen oxides or any other reactive compounds (other than sulfur).
For more complete chemical systems, LRT models are still in the research
phase and, in general, are not ready as operational tools.
9.5.2.2 Regional Concentration and Deposition Patterns—A better
understanding of LRT model design and application can be obtained by
examining one particular Lagrangian modeling approach—the
EURMAP/ENAMAP--on the basis that it can be considered as a typical
example of such models. There are two versions of EURMAP (European
Regional Model of Air Pollution): EURMAP-1 (Johnson et al. 1978) is a
long-term model that calculates monthly, seasonal, and annual values;
EURMAP-2 (Bhumralkar et al. 1981) is a short-term model that calculates
24-hourly values. ENAMAP-1, Eastern North American Model of Air
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Pollution (Bhumralkar et al. 1980) is a closely related version of
EURMAP-1 that has been adapted for application to the geographical
region covering the eastern United States and southeastern Canada, as
illustrated in Figure 9-2.
The EURMAP and ENAMAP models are designed to have minimal
computation requirements for making long-term calculations while
simulating the most important processes involved in the transboundary
air-pollution problem. These models can be used to calculate daily,
monthly, seasonal, and annual S02 and S042~ air concentrations;
S02 and $042- dry and wet deposition patterns; and interregional
exchanges resulting from the S02 and S042~ emissions over a
specified domain. The models use long sequences of historical
meteorological data as input, retaining all the original temporal and
spatial detail inherent in the data.
The short-term models, EURMAP-2 and ENAMAP-2, use the same general
design as the long-term models but have a number of important
differences, which are necessary to incorporate more details into the
emissions and meteorological simulations to be consistent with the much
shorter (24-hr) averaging time. In particular, atmospheric
boundary-layer processes have been treated in a more detailed manner
than in long-term versions.
The results from both EURMAP and ENAMAP models are obtained in the
following forms:
° Graphical displays of the distribution of S02
and S042- concentrations
0 Graphical displays of the distributions of S02
and S042~ wet and dry depositions
o Tabulated results showing the interregional exchanges
of sulfur pollution between individual source and
receptor regions.
Examples are presented in Figures 9-3 and 9-4 and Table 9-7,
respectively, of each of the above types of products resulting from the
ENAMAP application.
9.5.2.3 Use of Matrix Methods to Quantify Source-Receptor Relationships
--For long-range transport, environmental assessment must consider
potential impacts of emissions on areas far removed from the source.
Transport across the boundaries of air quality planning regions, states,
and even nations can be important. At the present state-of-the-art of
modeling, the models that have been used to quantify source-receptor re-
lationships are based on the principle of tracking the trajectories of
emitted pollutants. These models are used to compute "transport
matrices (e.g., Table 9-7) that permit assessment of air pollution
impacts for multiple scenarios of emissions. The transport matrix
9-29
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SOUTH QUEBEC
(a) EPA Regions used in this study
33
30
20
10
1
.VIII-NORTH
V
0
I]
Ul
l-
0
VII
.VI-EAS1
1 1
V-NORTh
1
ON
LV-SOUTH
J
SOUTH
TAR 1C
1 1 1
SOUTH Q
IV-NORT
V-SOU7
H
,
II
II
UE
3EC
I
-
0 20 30 40 43
(b) Emission Grid and Model Domain
Figure 9-2. Eastern North American domain and EPA regions used in the
ENAMAP modeling study. Adapted from Bhumralkar et al.
(1980).
9-30
-------
Local maximum values shown apply at points marked by plus signs.
Figure 9-3. Calculated SO? and S042- concentrations for August 1977.
Adapted from Bhumralkar et al. (1980).
9-31
-------
DRY DEPOSITION
16
„*-•
WET DEPOSITION
Local maximum values shown apply at points marked by plus signs
Figure 9-4. Calculated annual dry and wet depositions of SOzp (10 mg
for 1977. Adapted from Bhumralkar et al. (1980).
9-32
-------
TABLE 9-7. ANNUAL INTERREGIONAL EXCHANGES OF SULFUR DEPOSITION FOR 1977
AS CALCULATED BY THE ENAMAP - 1 MODEL (BHUMRALKAR ET AL. 1980)
I
CO
CO
TOTAL CONTRIBUTION TO S DEPOSITIONS WITHIN RECEPTOR REGIONS
EMITTER
REGION
1 VIII - NORTH
2 V - NORTH
3 S. ONTARIO
4 VII
5 VIII - SOUTH
6 VI - EAST
7 V - SOUTH
8 IV - SOUTH
9 IV - NORTH
10 III
11 II
12 I
13 S. QUEBEC
TOTAL (K TON S )
EMITTER
REGION
1 VIII - NORTH
2 V - NORTH
3 S. ONTARIO
4 VII
5 VIII - SOUTH
6 VI - EAST
7 V - SOUTH
8 IV - SOUTH
9 IV - NORTH
10 III
11 II
12 I
13 S. QUEBEC
1
10.
3.
0.
1.
0.
1.
2.
0,
0.
0.
0.
0.
0.
18.
1
55.
19.
3.
3.
0.
7.
9.
1.
0.
2.
1.
0.
0.
2
1.
655.
66.
43.
0.
4.
186.
8.
19.
11.
1.
0.
2.
997.
2
0.
66.
7.
4.
0.
0.
19.
1.
2.
1.
0.
0.
0.
3
0.
290.
820.
10.
0.
1.
145.
7.
24.
57.
53.
1.
105.
1514.
3
0.
19.
54.
1.
0.
0.
10.
0.
2.
4.
4.
0.
7.
4
2.
4fi.
2.
367.
0.
40.
135.
16.
11.
3.
0.
0.
0.
621.
PERCENT
4
n.
7.
0.
59.
0.
6.
22.
3.
2.
1.
0.
0.
0.
5
0.
0.
0.
0.
0.
1.
0.
0.
0.
0.
0.
0.
0.
1.
6
0.
3.
1.
26.
0.
401.
14.
44.
13.
1.
0.
0.
0.
503.
CONTRIBUTIONS TO
5
6.
0.
0.
0.
0.
92.
1.
0.
0.
0.
0.
0.
0.
6
0.
1.
0.
5.
0.
80.
3.
9.
3.
0.
0.
0.
0.
7
0.
229.
49.
137.
0.
7.
1566.
31.
221.
178.
1.
1.
1.
2422.
8
0.
6.
2.
22.
0.
35.
59.
949.
108.
14.
1.
0.
0.
1197.
S DEPOSITIONS WITHIN
7
0.
9.
2.
6.
0.
0.
65.
1.
9.
7.
0.
0.
0.
8
0.
0.
0.
2.
0.
3.
5.
79.
9.
1.
0.
0.
0.
9
0.
24.
7.
41.
0.
6.
425.
279.
929.
141.
4.
2.
0.
1856.
RECEPTOR
9
0.
1.
0.
2.
0.
0.
23.
15.
50.
8.
0.
0.
0.
(Mlotons)
10
0.
78.
74.
12.
0.
1.
520.
25.
159.
1363.
37.
9.
2.
2280.
REGIONS
10
0.
3.
3.
1.
0.
0.
23.
1.
7.
60.
2.
0.
0.
11
0.
50.
87.
3.
0.
0.
92.
2.
15.
179.
204.
91.
8.
732.
11
0.
7.
12.
0.
0.
0.
13.
0.
2.
24.
28.
12.
1.
12
0.
18.
40.
2.
0.
0.
30.
1.
7.
56.
65.
207.
41.
467.
12
0.
4.
9.
0.
0.
0.
6.
0.
1.
12.
14.
44.
9.
13
0.
23.
87.
2.
0.
0.
26.
2.
6.
21.
14.
22.
204.
407.
13
0.
6.
21.
0.
0.
0.
6.
1.
1.
5.
3.
5.
50.
-------
concept is based on the assumption that the average concentra-
tion/deposition of a pollutant in one geographic region (the "receptor")
is the sum of contributions received from emissions in every other
region (the "sources"). The matrix method has been used in several
assessment studies and for analyses of policy issues (Ball 1981).
Table 9-8 (from Ball 1981) exemplifies some of the features of
results presented in the matrix format. The Brookhaven National
Laboratory (BNL) AIRSOX model (Meyers et al. 1979) was used to generate
the results which quantify the transport of sulfates from one Federal
(EPA) region to another. Terms along the diagonal of the matrix are the
intraregional (locally produced) contributions. Summation of the off-
diagonal contributions of the receptor regions gives the imported
fraction of sulfate concentrations. Table 9-8 shows that the imported
fraction varies from 6 percent (Region 9) to 92 percent (Region 1).
Examining the individual contributions to the Region 1 totals in the
first column, it is seen that slightly over one-half the total impact of
5.461 yg m~3 is calculated to originate from Region 5 which has an
incremental contribution of 2.817 yg nr3.
While the matrix method is a reasonable way to present the source-
receptor relationship results of the transport models in a convenient
form, important questions remain about their validity in general and
also about the accuracy of matrices derived with current models. Chemi-
cal and physical processes that transform and remove air pollutants,
such as sulfur oxides, from the air often are not linear in terms of the
amount of pollutant present. However, most large-scale, long-range
transport models in current use are based on linear approximations.
This is due to the difficulties in simulating nonlinear processes and
lack of knowledge about the processes.
Finally, all the model results must be regarded as preliminary.
The results presented previously (Figures 9-2, 9-3; Table 9-7) primarily
indicate the type of information and the format that can be provided for
use by others. The results (Tables 9-7 and 9-8) also give some useful
indications, or trends, regarding the relative importance of various
source regions on the sensitive receptor areas presently of interest.
But at this time the absolute values of the numbers in the matrices
should not be given too much importance, and certainly the results of
any one model should not be taken in preference to the others.
9.5.3 Data Requirements
9.5.3.1 General--Figure 9-5 shows schematically how the components of a
general transport model are interconnected and how they interact with
basic data sources. The diagram represents a model that is
meteorologically diagnostic in that it does not attempt to generate
meteorological information from dynamic principles but instead makes
maximum use of available meteorological observations. Two other cate-
gories of input information are required in addition to meteorological
data: geographical information (e.g., surface characteristics and
topography), and detailed emissions data from both point and distributed
sources. Input data requirements are shown in column 1 of the figure.
9-34
-------
TABLE 9-8. INTERREGIONAL CONTRIBUTIONS TO SULFATE CONCENTRATIONS
AMONG FEDERAL REGIONS (BALL 1981)
10
i
CO
en
Emitter
Receptor
10
1
2
3
4
5
6
7
8
9
10
Local
Import
Total
0.453
0.540
1.232
0.646
2.817
0.035
0.174
0.008
0.008
0.000
0.453 (S%)
U.461 (92%)
5.914
0.059
1.199
2.212
0.934
4.120
0.058
0.295
0.014
0.019
0.000
1.199 (13%)
7.712 (87%)
8.911
0.009
0.328
4.728
2.559
5.640
0.098
0.322
0.007
0.014
0.000
4.728 (34%)
8.976 (66%)
13.704
0.002
0.037
0.518
3.832
1.730
0.228
0.283
0.006
0.011
0.000
3.832 (58%)
2.815 (42%)
6.647
0.000
0.009
0.171
1.042
4.420
0.293
0.966
0.114
0.041
0.007
4.420 (63%)
2.642 (37%)
7.062
0.000
0.000
0.012
0.256
0.121
1.032
0.169
0.059
0.484
0.004
1.032 (48%)
1.105 (52%)
2.137
0.000
0.000
o.oni
0.209
0.617
0.755
1.113
0.243
0.287
0.012
1.113 (34%)
2.124 (66%)
3.237
0.000
0.000
0.000
0.007
0.026
0.278
0.050
0.530
0.791
0.080
0.530 (30%)
1.232 (70%)
1.762
0.000
0.000
0.000
0.000
0.000
0.068
0.000
0.026
1.848
0.026
1.848 (94%)
0.121 (6%)
1.969
0.000
0.000
0.000
0.000
0.000
0.003
0.000
0.061
0.250
0.316
0.316 (50%)
0.314 (50%)
0.630
Note: Values are from BML AIRSOX model for average of January and July 1974 meteorology; units are mlcrograms per cubic meter.
-------
COLUMN 1
COLUMN 2
COLUMN 3
CO
CTI
PRIMARY DATA
TIME-VARYING FIELDS
METEORLOGICAL DATA
• SURFACE (HOURLY,
3 HOURLY)
• UPPER AIR [6-,
12-HOURLf)
• SYNTHESIZED FROM
NUMERICAL WEATHER
GEOGRAPHICAL INFORMATION
• TOPOGRAPHY
• SURFACE CHARACTER-
ISTICS (LAND USE)
EMISSIONS
• MAJOR POINT SOURCES
- SPECIES
- TIME VARIATION
- LOCATION (3-d)
- OTHER
CHARACTERISTICS
• DISTRIBUTED SOURCES
- SPECIES
- TIME VARIATION
- LOCATION (2'-d)
PRECIPITATION
-RATE
-TYPE
3-d HUMIDITY
)IATION
3-d WIND
- HORIZONTAL
- VERTICLE
3-d TURBULENT
DIFFUSION
CHARACTERISTICS
2-d SURFACE
UPTAKE
CHARACTERISTICS
3-d SOURCE FLUX
DISTRIBUTIONS
BY SPECIES
MAJOR COMPONENTS
OF A
POLLUTION TRANSPORT MODEL
A
CHEMICAL
TRANSFORMATION
TRANSPORT
AND
DILUTION
WET
REMOVAL
REDISTRIBUTED
CONCENTRATIONS
VISIBILITY
DRY
REMOVAL
Figure 9-5. Interaction among the data sources and components of a pollution transport model.
-------
All LRT models are to a large extent driven by a set of time-
varying scalar and vector fields like those shown in column 2 of the
figure. Some of the input data required in transport model simula-
tions, such as rainfall rate (used in calculating wet deposition) and
humidity (used in chemical transformations), can be generated from data
processing components external to the LRT model. The boxes in column 3
represent the major components of a model. Although some processes must
be simulated in all types of models (Lagrangian/Eulerian), the choice of
formulation influences the character of the model's other components.
9.5.3.2 Specific Characteristics of Data Used in Model Simulations--!t
is evident that to obtain accurate, meaningful, and useful information
from models, the input data must be of a quality and quantity consistent
with the structure and assumptions of the model in question. The
following discussion examines these aspects 1n some detail.
9.5.3.2.1 Emissions. Characterization of emissions directly affects
model results. Comprehensive sulfur emission inventories have been
prepared for western Europe (Semb 1978) and North America (Mann 1980,
Mueller et al. 1979). The SURE, Sulfate Regional Experiment, emissions
(Mueller et al. 1979), and MAP3S (MacCracken 1979) emission inventories
were specifically prepared to meet the needs of LRT models.
Two major sources of error in emission inventories can be
identified. The first of these relates to the surrogates for emissions
that are used (e.g., fuel consumption rates, population densities,
employment figures, traffic, and industrial production rates). The
second potential source of error lies in the factors or algorithms used
to convert these surrogates into estimates of emissions at a particular
time and place. These uncertainties must be quantified because they
will directly affect any model's performance. For example, a major un-
certainty is the importance of primary sulfates (e.g., SOX emitted
from the stacks already in the form of sulfate). This has become a con-
troversial issue during the last year because of possible implications
involving comparisons of local sources and distant sources and their
relative contributions to sulfur concentrations and depositions.
The inventories are normalized to annual average emission rates
with seasonal an diurnal adjustment factors (multipliers) incorporated.
However, these factors are average values and are subject to large
errors at any particular simulation time. Spatial resolution is
typically 80 km because the inventories are gridded to that size.
Emissions from large point sources are usually inventoried separately
such that the modeler has the option to treat these sources separately
or to combine their emissions into the 80 x 80 km grid cells.
Klemm and Brennan (1981) have estimated the uncertainties in annual
emission rates in the SURE inventory. Their estimates were separated by
broad source categories. For sulfur dioxide emissions, the error ranged
from 12 percent for electric utility sources to 32 percent for
commercial sources and had an overall error value of 17 percent. In
other words, the estimated emissions were said to be within 17 percent
of the actual emissions from the sources inventoried. (Their analysis
9-37
409-261 0-83-25
-------
was restricted to anthropogenic sources.) Their error estimate for NO
emissions was also 17 percent but was thought to be low because of the
high uncertainty for transportation source emissions. Errors in
sulfate, nitrogen dioxide, and hydrocarbon emission values were
estimated to be several times higher than those for sulfur dioxide.
9.5.3.2.2 Meteorological Data. Existing LRT models operate in the
diagnostic mode using available meteorological measurements, which are
quite sparse. To date the wind fields for the LRT models are
interpolated directly from these measurements and have not been coupled
with the calculations of boundary layer models (BLMs). The BLMs use the
meteorological measurements as initial conditions to solve the
hydro-dynamic equations that govern the wind flow. The marriage of BLM
and LRT models is a current research topic.
Most of the meteorological data for North America are obtained from
the National Climatic Center (United States) and the Atmospheric
Environment Service (Canada). Some special data (e.g., meteorological
tower data) are also available. Most LRT models require upper air winds
(e.g., 500 m) that must be derived from an estimated 50 upper air
stations (for eastern North America) taking measurements every 12 hr.
These measurements must be interpolated in time (e.g., 3-hr time steps)
and space (e.g., 50-km resolution) prior to being operated on by the LRT
model. It is recognized that the existing density of stations (less
than one every 100,000 km?) is insufficient to compute realistic
trajectories on a short-term basis. It is assumed (with some supporting
evidence) that, for long-term calculations, the distribution of
calculated trajectories is a reasonable approximation of the
distribution of actual trajectories. However, insufficient field data
exist to quantify the accuracy of this assumption.
Detailed cloud and precipitation data are needed by the model for
the estimation of wet removal. These precipitation data are obtained
from standard reporting surface stations. Hourly data are available
within the United States, but only daily values are reported in Canada.
Cloud data are not currently used by any of the models and, hence,
treatment of in-cloud processes is completely ignored. This is a major
limitation in the data bases and models. Cloud data are not available
in a readily useful form and as a result, it appears that most modelers
have chosen not to pursue the rather massive effort to incorporate such
data.
Other important data for model simulations pertain to atmospheric
stability, mixing height, and surface characteristics. These are
critical in calculating diffusion coefficients. Information about
surface characteristics (land use type) is used in estimating dry
deposition velocities. For estimating wet removal parameters,
considerably detailed cloud and precipitation data are required.
9.5.4 Model Performance and Uncertainties
9.5.4.1 General--The evaluation of model performance must consider
accuracies inherent in:
9-38
-------
0 the model itself--!.e., the package of algorithms
containing the mathematics designed to represent the physical
processees germane to acid deposition;
0 the raw information (unprocessed input data) that must be
transformed into a format compatible with the model;
° the preprocessors—i.e., the procedures that operate on the raw
information generating the model compatible input; and
0 the test data base containing the measurements that are compared
with the model calculations.
A major limitation in most assessments of model performance is that the
cause of disagreements between calculations and measurenents cannot be
isolated among the four items mentioned above. Normally, the four items
are considered as a package with the assumption that, if agreement is
"good," the model is a "valid" representation of the real world.
The primary objectives of model evaluation are to ensure that
modeled physical and chemical processes are as representative as
possible of real-world conditions and to quantify the uncertainties
inherent in the model. Some progress has been made toward developing an
accepted protocol for performance evaluation (Fox 1981). A widely
accepted protocol proposed by Bowne (1980) lists three steps in the
evaluation process:
° Technical evaluation: "Does the model perform as intended and
is it scientifically sound?"
0 Operational evaluation: "Does the model compute the correct
values?"
o Dynamic evaluation: "Can the model be extended or adapted to
other regions?"
To answer the questions posed in Bowne's protocol, four kinds of
analysis should be performed:
0 Accuracy analysis—use of accepted performance measures to
quantify the model's performance relative to observed
conditions.
o Diagnostic analysis—identification of conditions associated
with accuracies and inaccuracies in the model's performance.
0 Uncertainty analysis—quantification of the modeling
uncertainties, both inherent in the model and in the response of
the model to uncertainties in the input data.
0 Scientific Evaluation—a comprehensive technical evaluation of
the model's conformity with the appropriate physical and
computational principles.
9-39
-------
With the exception of the last item in the above list, an appropriate
data base is essential for the required analysis.
9.5.4.2 Data Bases Available for Evaluating Models--Extensive data
bases that can be used to evaluate transport models are scarce; however,
enough data exist to calculate performance measures over fairly broad
confidence intervals. Niemann's (1981) examination of the available
data set indicated that, while it is adequate for initial evaluation of
sulfur pollution transport models and perhaps wet sulfur deposition, it
is inadequate for substantially refining the current generation of
models.
The years 1978 and 1980 are most frequently used for LRT model
evaluation. The former corresponds to the second year of SURE, which
collected the most comprehensive air quality data base. However, the
coverage and quality of precipitation chemistry data were not up to the
standard that existed in the year 1980, when several Canadian and United
States networks were operational (see Chapter A-8). Of the networks,
the NADP offers the most coverage, having approximately 100 sites with
the greatest density in the eastern United States. However, regional
air quality data coverage was not comprehensive in 1980, and it appears
that only the Canadian APN network collected daily (regional) sulfate
concentration data. (The MOI group has assembled this data base for
1980). Evaluation data bases are also available from other parts of the
world, especially from western Europe, which has provided data bases
that have been used to evaluate performance of several LRT models (e.g.,
Eliassen and Saltbones 1975; Johnson et al. 1978; Bhumralkar et al.
1980, 1981).
9.5.4.3 Performance Measures--Various groups have been developing
procedures for evaluating models (e.g., Martinez et al. 1980, Ruff 1980,
United States/Canadian Working Group 1981).
Many of the widely used performance measures require data bases
from relatively dense networks of ground stations. Data bases for
evaluating performance of pollution transport models often emphasize
airborne sensors. Many of the performance measures are suitable for
application to airborne observations, but some are not. This is a
weakness in current evaluation methodologies. There seems to be a need
for performance measures and evaluation methodology that can take full
advantage of all the available airborne data.
Model evaluation statistics and displays generally try to answer
the following questions:
o How closely does a model calculation match the corresponding
observed value?
0 How well do the fluctuations In the predictions follow the
fluctuations of the measured parameter in time and space?
9-40
-------
For the most part, paired values of observations, C0, and predictions,
Cn, are used to calculate quantitative measures that address the above
questions. A difference, d, is defined such that:
d = C0(x,t) - Cp(x,t) . [9-15]
When answering the first question in the above list, we often define
this difference in terms of measurements and predictions from the same
place, x, and time, t.
If the difference, d, is always zero, the model would be considered
perfect. Most often, the average and standard deviation of d are
computed because they are measures of the model bias and precision,
respectively. Correlation coefficients are also used as performance
measures and accompanied by scatterplots with regression coefficients.
These statistics and graphical displays of scatterplots (and sometimes
frequency distribution comparisons) traditionally have been used by
modelers since the time of the early model evaluation studies. One of
the reasons they remain useful is that they are more or less the
universally accepted language on the subject.
9.5.4.4 Represent!'vity of Measurements—The evaluation of model
performance has been discussed in terms of how well the results from the
model, or from one of its components, agree with some observed value.
This assumes that the observed values are accurate and representative.
To legitimize this assumption, extensive quality assurance measures
should govern the acquisition and verification of the data base. Most
data bases have been subjected to considerable screening to ensure that
data are consistent and reliable, but it is not clear that the measure-
ments (especially precipitation) are representative of conditions on the
scale represented by the model. This must be taken into account when
comparisons are made.
9.5.4.5 Uncertainties—Modeling uncertainty consists of two components.
One part of theuncertainty can be thought of as "reducible" by means
of improvements to the model and its prescribed input data; a second
part is considered "irreducible" and is generally attributed to the
uncertainty inherent in the small-scale and short-term fluctuations in
atmospheric behavior, which never can be completely characterized by the
finite amount of data used for input to existing LRT models. To date
little progress has been made on this subject.
Some estimates of the reducible uncertainty could be made by
conducting a sensitivity analysis. In such an analysis the model's
sensitivity to input errors (or data parameterization errors) can be
qualified and distinguished from errors in the basic formulation.
Methods to estimate the irreducible uncertainty are currently being
developed by the research community. For instance, a recently proposed
model evaluation framework (Venkatram 1982) incorporates statistics that
attempt to quantify these uncertainties.
9-41
-------
9.5.4.6 Selected Results—Numerous examples of LRT model evaluation
exercises exist in the open literature. However, most of these are
presented In a qualitative manner or with very minimal statistical
evidence. Research programs underway will greatly enhance existing
information on the subject. The MOI, EPRI, EPA, and National Park
Service are all sponsoring such studies, and results will appear in the
literature within the next year.
In this presentation, example model evaluation studies are
presented to be more or less illustrative of the state of knowledge.
The first study (Voldner et al. 1981) examined seasonal averages of
concentration and depositions calculated by a modified Long-Range
Transport of Air Pollutants (LRTAP) program and compared them with
atmospheric sulfate concentrations from the SURE network and
precipitation sulfate concentrations from the CANSAP network. For the
month of October 1977, the examination found that the monthly average
computed sulfate concentrations and depositions agreed with the
measurements within 60 percent. This agreement held for the four
combinations of wet and dry removal parameteric values that were
presented. The correlation coefficient between measurements and
predictions varied from 0.55 to 0.59 for atmospheric sulfate
concentrations and from 0.86 to 0.91 for precipitation sulfate
concentrations.
In another study (Mayerhofer et al. 1981), monthly averaged sulfur
dioxide and sulfate atmospheric concentrations calculated by the ENAMAP
model, were compared with measurements from the SURE network for January
and August, 1977. Scatterplots of the sulfate comparison are presented
in Figure 9-6. The correlation coefficients are 0.51 and 0.23 for
January and August, respectively. The sulfur dioxide concentrations
(Figure 9-7) compared more favorably with correlation coefficients of
0.71 (January) and 0.48 (August).
The preliminary Phase III results of the MOI group addressed the
comparisons of observations and model calculations of sulfate
concentrations and wet depositions. The eight models listed in Table
9-9 were exercised to calculated annual and monthly averages for the
year 1978. The model calculations were compared with measurements from
the SURE, MAP3S, and CANSAP programs using performance measures
described earlier in this section. A very limited partial listing of
the MOI results is given in Table 9-10. This listing allows one to
visually compare the average model calculation (t), the bias (cf), and
the root-mean-square error (sd). it was noted that the number of
locations used in the evaluation did vary among models. The MOI group
also noted that the models appeared to perform better for wet deposition
than for the ambient concentration. They found this surprising because
wet deposition is episodic in nature, whereas the model results were
presented as non-episodic or longer term. No consideration was given to
S02 concentrations because they were considered to be always affected
by local sources. A major conclusion of the MOI is that it is not
possible to recommend a "best" model (among the eight compared) because
of the uncertainties in the emissions and precipitation data and in the
measurement data used for evaluation.
9-42
-------
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3" CU 3"
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-h -••<<
fD O
-S 3 <
to cu
fD —'
r+ -h c
O fD
Cu -S C/l
CU to
i—' c n
VO Cu Cu
°°^0
c
CU —•
3 CU
Q. c+
fD
Q.
oo
cr>
ro
o
ro
oo
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ro
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O
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oo
ro
ro
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73
o
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ro
g K
ro
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co
CM
-------
ro
i
05
3.
LU
CJ
O
o
CM
O
o
CJ
co
I
o
o
o
a:
CM
O
o
LU
<
3
O
_l
O
30 40 50 60 70 80 90 100
OBSERVED S02 AIR CONCENTRATION (ug nf°)
(a) JANUARY
54
48
42
36
30
24
18
12
6
0
0 6 12 18 24 30 36 42 48 54 60
OBSERVED S02 AIR CONCENTRATION (yg m"3)
(b) AUGUST
Figure 9-7. Scatter diagram of observed monthly values vs calculated
monthly values of SOo concentrations for January and
August 1977. Adapted from Mayerhofer et al. (1981).
9-44
-------
TABLE 9-9. LONG-RANGE TRANSPORT MODELS ASSEMBLED
BY THE MOI REGIONAL MODELING SUBGROUP
Model Name
Acronym
Reference3
Atmospheric Environment Service
Long-Range Transport Model
Advanced Statistical Trajectory
Regional Air Pollution Model
Center for Air Pollution Impact and
Trends Analysis - Monte Carlo Model
Eastern North American Model of
Air Pollution
Transport of Regional Anthropogenic
Nitrogen and Sulfur (TRANS) Model of
Meteorological and Environmental
Planning, Ltd.
Ontario Ministry of Environment
Long-Range Transport Model
University of Illinois Regional
Climatological Dispersion Model
University of Michigan Atmospheric
Contributions to Interregional
Deposition Model
AES
MEP
MOE
Olson et al. 1979
ASTRAP Shannon 1981
CAPITA Patterson et al.
1981
ENAMPA-1 Bhumralkar et al.
1980
Weisman 1980
Venketram et al.
1980
RCDM-3 Fay and Rosenzweig
1980
UMACID Samson 1980
aSome of the model characteristics may have been revised since these
references were printed.
9-45
-------
Model
TABLE 9-10. MOI PRELIMINARY COMPARISON BETWEEN MODELED
AND MEASURED SULFATE CONCENTRATIONS AND DEPOSITIONS
January
July
Annual
(a) Sulfate Concentrations (yg nr3), 1978
AES
MOEa
MEP
ENAMAP
UMACID
CAPITA
RCDM
ASTRAP
AESb
MOEb
MEpb
ENAMAP
UMACID
CAPITA
RCDM
ASTRAP
7.5
-
4.0
5.4
6.2
7.5
3.1
6.0
(b)
0.8
_
0.8
0.8
0.1
0.5
0.4
0.7
-0.7
_
2.6
1.3
-0.4
-0.7
3.7
0.8
Sulfate
-0.1
_
0.0
0.0
0.3
0.2
0.3
0.0
2.4
-
1.7
1.8
0.4
1.8
1.6
3.0
8.5
-
11.9
8.1
10.8
11.9
9.0
8.9
Depositions
0.6
_
1.0
0.2
0.3
0.7
0.7
0.8
0.9
—
0.2
0.7
0.1
0.8
0.4
0.9
2.7
_
-0.4
3.5
0.5
-0.3
2.6
2.6
(kg ha-1
0.2
_
0.7
0.6
0.9
0.3
0.7
0.2
2.3
_
2.1
3.6
2.4
3.2
2.7
3.2
10.0
7.0
8.3
_
_
10.3
7.2
7.2
-0.9
2.1
0.8
-
_
-1.2
1.9
1.9
1.7
2.3
0.9
_
_
1.6
1.6
2.8
period-1), 1978
0.4
—
0.4
0.4
0.3
0.2
0.5
0.3
9.7
10.1
6.5
_
-
6.4
6.6
8.1
1.2
0.8
4.4
_.
-
4.5
4.2
2.7
4.0
2.8
2.5
_
-
3.5
4.1
4.3
Background of 2 yg m~3 added to the calculation.
bBackground of 2 kg ha"1 added to the annual calculations only,
9-46
-------
The major point here is that, in a limited number of studies, monthly
concentration and deposition concentrations are often moderately
correlated (in a statistical sense) to measured values and often agree
within a factor of 2. Hence, LRT model results may provide a useful
estimate of reality. However, the accuracy and uncertainties of these
estimates must be quantified more thoroughyy. Also, the evaluation
studies are limited strictly to comparisons of sulfur dioxide and
sulfate concentrations.
9.6 CONCLUSIONS
A host of Eulerian and trajectory models have been developed to
treat long-range transport (LRT) problems. The majority of these models
have been of the trajectory type—statistical or Lagrangian--and
primarily have been developed to calculate long-term (monthly and
annual) averages for sulfur dioxide and sulfate concentration and
depositions over transport distances of 500 km and above. The Eulerian
grid model is capable of treating complex physical and chemical
processes in a more realistic manner than the trajectory model, but this
capability has not been employed frequently on the LRT scale. Hence,
treatments in the most detailed Lagrangian trajectory models are similar
in complexity to those in Eulerian models.
Current LRT models treat the processes of transport, diffusion,
chemical transformation, and (wet and dry) deposition, but even the most
detailed treatments represent gross simplifications of existing
knowledge about these processes. The effect of these simplifications on
model performance has yet to be determined. These limitations lead to
somewhat more specific conclusions described below:
0 At present, calculations from LRT models alone are not a
sufficient basis for supporting policy decisions about acidic
deposition because the validity of the modeled
source-to-receptor relationships has not been established
(Sections 9.4.1 and 9.5.4).
0 In a limited number of model evaluation studies, comparing
sulfur dioxide and sulfate concentrations, LRT model
calculations are moderately correlated with field measurements.
A more definitive statement on this subject should be possible
within the next year when the results of current model
evaluation studies are reported. Unfortunately, such a
statement probably will address sulfur compounds only, ignoring
other compounds germane to acidic deposition (e.g., nitrogen
oxides) (Section 9.5.4).
0 In general, LRT models are capable of treating only large
synoptic scale processes. As a result, many important smaller
(sub-grid) scale processes are ignored (Section 9.5.3). These
include lack of treatments of:
9-47
-------
- processes in individual clouds and precipitation events (cloud
data are not treated by existing models and precipitation data
are not sufficiently resolved),
- effects of nearby sources (e.g., within 100 km of a receptor)
whose effluents may dominate acidic precursor concentrations
in certain situations, and
- gross differences in the transport winds that might occur
within the small scale.
o Previous and existing measurement programs have not provided
sufficient data to evaluate models or model components to the
extent needed. Additionally, the raw (input) data operated on
by the models need improvement in spatial and temporal detail.
The sparcity of the existing upper air meteorological network is
a prime example of this problem (Sections 9.4.1. and 9.5.3).
Current research programs are addressing many of the topics
mentioned above and progress is inevitable. Some of this effort is
devoted to quantifying model accuracy and uncertainty using existing
data bases. Better guidelines on how and when to use LRT results
ultimately will emerge.
9-48
-------
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consider studies by ... in
making conclusions
20 P3L5 "Susceptible to change" would be
more appropriate than "sensitive"
4. When commenting on specific sections/discussion and paragraphs/
statements, some suggested reviewers responses that may be useful
include (with additional appropriate details by reviewer):
- information/statement inaccurate
- information/statement incorrectly interprets available
data and/or literature
- information/statement is based on insufficient data and/or
literature
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Commonly, reviewer's comments note "this information is not correct!"
You should be aware that unless specific evidence is provided
demonstrating that the information is, in fact, inaccurate, no action
can be taken.
During your review of each chapter, it will be necessary to keep in
mind the intended purpose and scope of this document as outline,, in the
Preface. This is not a criteria document and is not designed to address
policy option issues. The Acidic Deposition Phenomenon and Its Effects:
Critical Assessment RevTewTapers Ts an authored document. Comments
will be addressed by the authors in cooperation with the editors as
deemed appropriate. These authors are charged with producing a
scientifically sound and accurate document and are not expected to make
recommendations for the use of the material in future decision-making
processes. They will therefore address comments on technical accuracy
only.
Only one copy of the review form follows. This form should be
copied and used for all written comments.
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MANUSCRIPT REVIEW FORM
Title/Draft
The Acidic Deposition Phenomenon and Its
Effects: Critical Assessment Review Papers
Public Review, Draft, May 1983
Review Coordinator/Return to:
Ms. Betsy A. Hood
CAD Coordinator
NCSU Acid Precipitation Program
1509 Varsity Drive
Raleigh, NC 27606
Reviewer/Organization/Address
Chapter No./Title
SUMMARY RATING
Please rate the manuscript as follows: Satisfactory Unsatisfactory
Cont^it "nd sr' p» ,
QrganiTatinn and prp^ontation
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material presented
Technical accuracy _.--—,
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Other (specify)
RECOMMENDATIONS
D (1) Acceptable as is
D (2) Acceptable after minor revision
D (3) Acceptable after major revision
If you have checked either 3 or 4,
please specifically state reason(s) in
the comments space below.
Reviewer's Signature Date
General Comments (Use extra pages if needed but please be concise)
U.S. GOVERNMENT PRINTING OFFICE : 1983 0 - 409-261
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U.S. Env':
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United States
Environmental Protection
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