Photochemical Control of the Distribution of Venusian Water and
Comparison to Venus Express SOIR Observations
Christopher D. Parkinson1,*, Yuk Yung2, Larry Esposito3, Peter Gao2, Stephen Bougher1, and
Mathieu Hirtzig4
1
Department of Atmospheric, Oceanic, and Space Sciences
University of Michigan
*
To whom correspondence should be addressed
2455 Hayward Street, Ann Arbor, MI, 48109, USA
email: theshire@umich.edu
2
Division of Geological and Planetary Science
California Institute of Technology, CA, USA
3
Laboratory for Atmospheric and Space Physics
University of Colorado, CO, USA
4
LESIA, Observatoire de Paris,
Section de Meudon, 92195 Meudon Cedex, France.
5
Foundation “La main à la pâte”, Montrouge, France.
Submitted to Planetary and Space Science
Submitted DATE
Preprint submitted to Elsevier Science
3/14/16
Abstract
We use the JPL/Caltech 1-D photochemical model to solve the continuity diffusion
equation for the atmospheric constituent abundances and total number density as a
function of radial distance from the planet Venus. The photochemistry of the Venus
atmosphere from 58 to 112 km is modeled using an updated and expanded chemical
scheme (Zhang et al., 2010; 2012), guided by the results of recent observations. We
mainly follow Zhang et al. (2010; 2012) to guide our choice of boundary conditions for
40 species. We fit the SOIR Venus Express results of 1 ppm at 70-90 km (Berteaux et al
(2007) by modeling water from between 10 – 35 ppm at our 58 km lower boundary and
using an SO2 mixing ratio of 25 ppm as our nominal reference value. We then vary the
SO2 mixing ratio at the lower boundary between 5 and 75 ppm and find that it can control
the water distribution at higher altitudes.
1. Introduction
Venus is the closest planet to the Earth, in terms of both distance and mass. However,
Venus has lost most of its atmospheric and surface water, most likely as an indirect
consequence of its greater proximity to the Sun. Hence, much of the carbon dioxide on
the Earth that has been processed by the oceans to produce carbonates is still free in the
atmosphere of Venus. Subsequently, the Venus atmosphere is very massive by terrestrial
standards, with a surface pressure of about 92 bars and a relatively high surface
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temperature at around 725 K.
In the modern atmosphere of Venus, chemical reactions coupled with transport and
radiative processes regulate the abundances of the most
significant minor
constituents. Of the utmost importance are the cycles involving water vapor, sulphuric
acid, and their products, which maintain the cloud layers and involve reactions between
the atmosphere and the surface.
The atmosphere of Venus can be organized into regions determined by composition,
chemistry, and clouds. The upper atmosphere, above ~110 km, has low densities and
overlaps with the ionosphere so that photodissociation, ion-neutral, and ion-ion reactions
are increasingly dominant with increasing altitude. The middle atmosphere, ~60–110 km,
receives sufficiently intense ultraviolet (UV) radiation from the sun so that it is
dominated by photochemistry. The lower atmosphere, below ~60 km, receives little UV
radiation from the sun, and thermochemistry dominates increasingly with decreasing
altitude owing to the high atmospheric temperatures. In the region near the boundary
between the lower and middle atmospheres are the cloud and haze layers which extend
from ~30–90 km with the main cloud deck lying at ~45–70 km. Competing processes
between the middle atmosphere, dominated by photochemistry, and the lower
atmosphere, dominated by thermochemistry (Esposito et al., 1997; Mills 2007) play a key
role in this upper cloud deck region. Owing to massive cloud formation, lightning could
occur and produce NO (Krasnopolsky, 2006) and heterogeneous chemistry on aerosol
and cloud particle surfaces may be important (Mills, 2006; Parkinson et al., 2006; Yung
et al., 2008). Finally, in the lowest scale height of the atmosphere a region exists where
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surface/atmosphere interactions most likely dominate.
Following Yung and DeMore (1982), Krasnopolsky and Pollack (1993), Mills (2006),
Yung et al. (2008) and others, three dominant chemical cycles have been identified in the
Venus atmosphere: the CO2 cycle, the sulphur oxidation cycle, and the polysulphur cycle.
The CO2 cycle features photodissociation of CO2 on the dayside with subsequent
transport of a significant fraction of the products, CO and O, to the night side. Also
important is the production of O2, emission of highly variable oxygen airglow on both the
day and night sides, and conversion of CO and O2 into CO2 via catalytic processes. CO is
very abundant (with mixing ratios of the order of a few parts per thousand by volume) in
the upper atmosphere of Venus, as would be expected from the action of solar ultraviolet
radiation on carbon dioxide. On the other hand, it is strongly depleted in the cloud layers
(<1 ppmv) since it is involved in reactions with SO2 and the other species that make up
the sulphur cycle. However, below the clouds and near the surface, the carbon monoxide
value recovers to some few tens of parts per million by volume and shows a marked
equator-to-pole increasing gradient (Collard et al., 1993; Taylor et al., 1995). It seems
likely that CO is transported downwards rapidly from the thermosphere in the polar
vortices to the troposphere, where it is gradually removed by reactions in the hot lower
atmosphere and at the surface. The sulphur oxidation cycle involves conversion of OCS
into SO2 and its subsequent upward transport, whereupon a significant fraction of the SO2
is oxidized to form H2SO4, which condenses with H2O to form most of the cloud and
haze layers. The sulphuric acid is then transported downwards in the form of cloud
droplets, which evaporate back into H2SO4 and H2O vapor below the clouds. The cycle is
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completed with the production of SO2 from the thermal decomposition of H2SO4. There
is solid observational evidence for both the CO2 and the sulphur oxidation cycles. The
putative polysulphur cycle until recently has been seen as more speculative but plausible
based on existing laboratory data and limited observations. Recently, Yung et al (2008)
described an innovative scheme involving the upward transport of sulphur as either SO2
or OCS, photodissociation to produce S, formation of polysulphur (Sx) via a series of
association reactions, downward transport of Sx, thermal decomposition of Sx, and
reactions with oxygen and CO to produce SO2 and OCS, respectively. Each of the cycles
involves a number of trace species, such as ClOx, HOx, NOx, and SOx. The three cycles
most likely interact through these trace species. The strength of these links between the
cycles in existing models depends on parameters that have significant uncertainties and
few constraints from direct observational evidence.
2. Model Description
2.1 Photochemistry and Chemical Kinetics
The JPL/Caltech KINETICS model is a 1-D photochemical model that solves the
continuity diffusion equations for the constituent abundances and total number density, n,
as a function of radial distance from the planet. The number densities of the chemical
species are calculated by solving the continuity equation for each species, i,
¶n i ¶fi
+
= Pi - Li
¶t
¶z
(1)
where the vertical flux i is given by
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f i = f iK + f iD
(2)
The eddy flux Ki
f iK = -K(
¶ni
n
+ i )
¶z H av
(3)
represents the vertical flux that parameterizes macroscopic motions, such as the large
scale circulation and gravity waves, while Di
(4)
is the vertical flux as a result of molecular diffusion. Hi and Hav denote the species and
atmospheric scale heights, respectively; a small correction due to temperature gradients
has been included. Pi and Li are the chemical production and loss rates (cm-3 s-1),
respectively, at altitude z and time t (see, e.g., Chamberlain and Hunten, 1987; Yung and
DeMore 1999). All the chemistry is contained in the Pi and Li terms. Di(z) and K(z) are
respectively the molecular and eddy diffusion coefficients. The former is rigorously
based on fundamental physics and laboratory measurements. The latter is usually derived
empirically from observations of tracers in the atmosphere and are taken from Mason and
Marrero (1970) and Atreya (1986) where applicable.
We use the JPL/Caltech KINETICS 1-D photochemical model to produce an atmosphere
with number densities of key species as a function of temperature and altitude. Our
nominal reference model atmosphere parameters are the species mixing ratios (cf. Table
1) and the eddy diffusion at the homopause, Kh. The standard reference atmosphere used
for this paper uses the mixing ratios from the models of Yung and DeMore (1982),
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Krasnopolsky and Pollack (1993), Mills et al (2006), Yung et al (2008), and Zhang et al
(2010; 2012).
The photochemistry of the Venus atmosphere from 58 to 112 km is modeled using an
updated and expanded chemical scheme from Zhang et al (2010; 2012) for trace species,
such as ClOx, HOx, and SOx combined with the results of recent observations. Sensitivity
studies including an observationally constrained parameter space search of water and SO2
mixing ratios have been considered. Reactions using the peroxychloroformyl radical
(ClC(O)OO) described by Pernice et al (2004) are included and O2 column values are
within a factor of 2 of what was expected.
Tables 2 – 4 list the most important reactions for the major compounds of carbon,
oxygen, hydrogen, sulphur and chlorine. These tables also include their rate coefficients,
with many updated from the values in Yung and DeMore (1982), as specified. Tables 2
and 3 show two and three body reactions (and their reaction rates), respectively. Table 4
shows the halogen reactions and reaction rates.
The speculative reactions involving
HSO3 and the (SO)2 dimer (and their rate coefficients) from Tables A1 and B1 of Yung
and DeMore (1982) have not been included in this work. It is not our intention here to
review or critically assess the very detailed analysis given by Yung and DeMore (1982)
and Zhang et al (2010; 2012) except where immediately germane to the discussions
below. In general, the chemistry for the various species is well defined and described
elsewhere (e.g. Mills et al., 2006, Yung and DeMore, 1982; Krasnopolosky and Pollack,
1993; Prinn 1975). Rather, our starting point is to update the rate coefficients and eddy
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diffusion profiles of the JPL/Caltech KINETICS model (Zhang et al, 2010; 2012) from
those used by Yung and DeMore (1982) for sensitivity studies at and above the cloud
tops.
2.2 Temperature
There exist experimental data on the atmosphere of Venus obtained after 1985, when the
VIRA (Venus International Reference Atmosphere) or COSPAR model was published.
For our calculations, we have adopted a standard reference temperature profile based on
the VIRA data from the surface at 92 bar to 100 km, corresponding to 0.01 mbar. This
temperature profile is shown in Figure 1.
2.3 Eddy Diffusion, K
For most cases, K = Ko (n(z)/n_ref)-a, where Ko is the eddy diffusion coefficient at some
reference altitude, n is the number density, z is altitude, and a is an exponent with value
less than unity. The standard value for the eddy diffusion coefficient at the homopause,
Kh, adopted herein is based on the work of Yung and DeMore (1982) which used a value
of Kh  2 × 106 cm2 s−1. As the eddy diffusion profile, K, varies with height, z, we
consider a profile such that Ko = Kh at the homopause. For the altitude range from 58 to
112 km, we have selected a profile following the above relation for K where a has the
value of 0.5. This profile is also shown in Figure 1 and matches that given in Zhang et al
(2010; 2012).
3. Results and Discussion
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The major pathways for the photochemistry of SO2 above the cloud tops are shown in
Figure 2. SO2 exchanges rapidly with SO and SO3. However, formation of H2SO4
followed by condensation sequesters SO2 in aerosol particles and removes it from active
chemistry. The reaction that forms H2SO4 appears to involve a complex with H2O:
SO3 + H2O  SO3·H2O
SO3·H2O + H2O  H2SO4 + H2O
We adopt the expression for the rate of formation of H2SO4 from Lovejoy et al. (1996)
Figures 3 to 5 show our standard reference atmosphere for key species.
Figure 6 shows the VEx SOIR water mixing ratio profile from Berteaux et al (2008),
from which we see that there is ~1 ppm of water between 70 – 90 km. Using our model,
we try to fit the Berteaux et al (2008) SOIR observation as illustrated in Figure 7. This
plot shows H2O resultant profiles obtained when we hold the SO2 mixing ratio to be fixed
at the lower 58 km boundary at a nominal reference value of 25 ppm (Marcq et al, 2007)
and vary water between 10 – 35 ppm at the lower boundary. We find the best fit to this
SO2 mixing ratio boundary value corresponds to 18 ppm of water at the lower boundary
of the model, which is consistent with the VEx VIRTIS SO2 measurement of 24  3 ppm
(Marcq et al, 2006) at ~40 km. As expected, if the H2O lower boundary is increased, the
amount of water above 70 km is stable and remains relatively constant, though much
increased over our standard reference value. However, when the H2O lower boundary is
decreased by only slightly, we witness a sudden collapse in the mixing ratio of water
between ~70-90 km for our fixed standard SO2 boundary value. It recovers above 90 km
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owing to SO2 concentrations falling off rapidly above 100 km – near the upper boundary
of our model simulations.
Similarly, we can consider a fairly wide range of mixing ratios about our nominal value
for SO2 at the lower boundary, viz., 5 ppm to 100 ppm while holding water fixed at the
lower boundary. This successfully yields number density profiles of key species from 58
to 112 km above the surface. Our modeling agrees with previous measurements of SO2,
SO, and CO (e.g. Mills 1998) as well as those in the companion issue of this paper by
Mahieux et al (2014) (cf. Figure 5).
First, we see that SO2 profiles can change
significantly with changes of SO2 mixing ratio at the lower boundary as shown in Figure
8. For purposes of analysis we use a lower boundary mixing ratio of 18 ppm for water,
which ensures that our model matches the Berteaux et al. (2008) observation of ~1 ppm
of water between 70 – 90 km, as well as the Marcq et al. (2006) SO2 measurement of 24
 3 ppm at about ~40 km. Although these species are part of the chemical pathway that
produces sulphuric acid (H2SO4), the H2SO4 number density profile does not change for
the cases considered since it follows the H2SO4 saturation vapor pressure curve. Similar
to the water curves in Figure 7, we see that a higher mixing ratio of SO2 at the lower
boundary results in a stable, large SO2 mixing ratio over most of our altitude range being
considered, while lower SO2 mixing ratios at the lower boundary leads to a sudden
decrease in the SO2 mixing ratio between 70 and 90 km.
However, Figures 7 and 8 do not explain the whole story, as only the black curves are
correlated (viz., 18 ppm water and 25 ppm SO2 for our standard reference case). There is
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a stronger interplay between H2O and SO2 than these plots reveal. Adjusting SO2 at the
lower boundary for a fixed lower boundary value for water and looking at the varying
SO2 profiles does not make it immediately clear the degree to which this affects the H2O
profile for each case or for other lower boundary water mixing ratio values. What
happens to the water profile over our altitude range when the SO2 mixing ratio increases
or decreases just above the cloud deck region at 58 km corresponding to source pulse (i.e.
changes in the transport rates for SO2 resulting in large changes in SO2 above the cloud
tops) of SO2 from below this region? The same is true for changes in the water profile
due to alteration of its lower boundary value while the SO2 abundance at the lower
boundary is held fixed at the standard reference value. It isn’t immediately clear what
general effects this has on the distribution of SO2 in the altitude range under
consideration. Clearly, when we change the lower boundary values of these two species
about the standard reference values, the profiles of these species change radically as well.
We quantify this by separately plotting values for H2O and SO2 at ~80 km as a function
of pairs of mixing ratios of these species at our lower boundary (58 km). This is shown
in Figures 9 and 10, which together illustrate a remarkable phenomenon that we dub
“chemical bifurcation”. Figure 9 represents our water sensitivity by plotting the mixing
ratio of SO2 at 80 km and Figure 10 shows the SO2 sensitivity by plotting the mixing
ratio of H2O at 80 km. We see that the two figures are “anti-symmetric” and that there is
a dramatic chemical bifurcation in the middle of each plot. In regions of high SO2
abundance in Figure 9, we have a corresponding low H2O abundance in Figure 10, and
vice versa. These results are hinted at in Figures 7 and 8, but the full impact is made clear
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in these figures.
The way we can understand this is by realizing that both SO2 and H2O are removed above
the cloud tops by the formation of H2SO4. As H2SO4 aerosols are removed, they represent
a net sink of SO2 and H2O, thereby explaining their rapid decrease with altitude. The
abundances of SO2 and H2O are of the same order of magnitude. An excess of H2O
would result in the rapid removal of SO2 and vice versa. Hence, SO2 and H2O can
regulate each other via formation of H2SO4.
We interpret this as follows. In regions of high mixing ratios of SO2 there exists a
“runaway effect” such that SO2 gets oxidized to SO3, which quickly soaks up H2O
causing a major depletion of water between 70 and 100 km, thereby explaining the
drastic changes in the 10 and 15 ppm curves of Figure 7. This reasoning can also be
applied to regions of high H2O and applied to explain the sudden decreases in SO2 as
seen in Figure 8. In the companion work of Mahieux et al (2014) in this issue, we see
SO2 profiles as obtained by the SOIR instrument aboard the VEx spacecraft similar to
those simulated in this paper in the altitude range of interest. The observed straight,
vertical distributions of SO2 mixing ratios should correspond to regions of low water
abundance, while other observations showing SO2 profiles remarkably similar to our
black curve in Figure 8 should correspond to regions of high water abundance. For these
and other similar cases, we’d expect to see a similar plot to the black curve in Figure 7
corresponding to this case. However, H2O could exhibit a bifurcation as its value falls
below a critical value, which can be determined using Figures 9 and 10 for values other
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than the standard ones chosen for Figures 7 and 8. Further work on this in collaboration
with the authors of that paper will be done to confirm these results and specifically
answer whether, below a critical value, H2O could be completely sequestered in H2SO4
aerosols.
Though our work could explain some of the observed variability in SO2 and H2O on
Venus, it can also shed light on the observations of dark and light banding in the Venus
atmosphere as viewed in the ultraviolet spectrum, possibly due to an unknown sulphur
related UV absorber. Higher abundances of SO2 (and associated chemistry and
subsequent formation of aerosols, as described by Bougher et al (2014) and Parkinson et
al (2014), both companion papers in this issue) with the relative absence of water due to a
chemical bifurcation could correspond to the darker regions, while areas of depleted SO2
and moderate to high values for H2O could correspond to the lighter regions, as lower
SO2 abundances could be detrimental for the formation of such an UV absorber.
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Table 1:
Species
CO2
CO
O
O(1D)
O2
O2(1D)
O3
H
H2
H2O
OH
HO2
H2O2
S
S2
SO
(SO)2
SO2
SO3
S2O
HSO3
Cl
Cl2
ClO
HCl
HOCl
ClCO
COCl2
ClCO3
ClS
ClS2
Cl2S
Cl2S2
OSCl
CLSO2
OCS
Mixing ratio at lower boundary
0.965
25 ppm
0.0
0.0
0.0
0.0
0.0
0.0
0.0
18 ppm
0.0
0.0
0.0
0.0
0.0
0.0
0.0
25 ppm
0.0
0.0
0.0
0.0
0.0
0.0
0.1 ppm
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.5 ppm
Flux at top of atmosphere
5.0 x 1011
-5.0 x 1011
-5.0 x 1011
0.0
9.0 x 108
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
-1.0 x 10-7
0.0
0.0
1.0 x 10-7
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Table 2: Two Body reactions and rates
R1
Reaction
O3 + O  O2 + O2
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Reaction Rate
8.010-12 e-2060/T
Reference
a
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R2
R3
H + O3  OH + O2
H2 + O  OH + H
R4
R5
R6
H2 + O(1D)  OH + H
H2O + O(1D)  OH + OH
OH + CO  CO2 + H
R7
R8
R9
OH + O  O2 + H
OH + H2 -> H2O + H
OH + OH  H2O + O
R10
R11
R12
OH + O3  O2 + HO2
HO2 + O  OH + O2
HO2 + O3  O2 + O2 + OH
R13
HO2 + H  OH + OH
 H2 + O2
 H2O + O
HO2 + HO2  H2O2 + O2
HO2 + OH  O2 + H2O
H2O2 + OH  H2O + HO2
O(1D) + CO2  O + CO2
S + CO2  SO + CO
S + O2  SO + O
S + OH  SO + H
S + HO2  SO + OH
S2 + O  SO + S
SO + O2  SO2 + O
SO + O3  SO2 + O2
SO2 + O3  SO3 + O2
SO + OH  SO2 + H
SO + HO2  SO2 + OH
SO + SO  SO2 + S
SO3 + H2O  H2SO4
SO3 + SO  2SO2
HSO3 + O2  HO2 + SO3
HS + O  SO + H
HS + H  S + H2
HS + S  H + S2
HS + HS  H2S + S
H2S + O  HS + OH
H2S + H  HS + H2
R14
R15
R16
R17
R18
R19
R20
R21
R22
R23
R24
R25
R26
R27
R28
R29
R30
R31
R32
R33
R34
R35
R36
R37
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1.010-10 e-366.95/T
3.4410-13 e-3160/T
(T/298.0)2.67
1.110-10
1.010-10
1.4410-13 (1.0 +
n/4.01019)
2.410-11 e224/T
7.710-12 e-2100/T
6.210-14 e945/T
(T/298)2.6
1.7210-12 e-940/T
2.710-11 e224/T
2.0310-16 e693/T
(T/300)4.57
(7.2e-11 + 5.6e-12 +
2.4e-12)
b
c
1.510-12 e19/T
4.810-11 e250/T
2.9110-12 e-161/T
7.4110-11 e120/T
1.010-20
2.110-12
6.5910-11
3.110-11
2.010-11 e-84/T
1.610-13 e-2280/T
4.510-12 e-1170/T
3.010-12 e-7000/T
8.5910-11
2.310-11
3.510-15
9.010-13
1.9910-15
1.310-12 e-330/T
1.6010-10
2.1610-11
4.9810-12
4.0010-11
9.2110-12 e-1800/T
2.3110-7 (T/298)1.94
e-455/T
f
a
g
a
c
a
a
c
a
a
c
a
a
c
a
a or < 40 km
a
a
a
a
a
a
a
a
d
a
c
c
c
c
c
c
e
3/14/16
R38
R39
R40
R41
R42
H2S + OH  HS + H2O
HS + O3  HSO + O2
HS + HO2  HSO + OH
HSO + O2  SO2 + OH
HSO + O3  HS + 2O2
6.110-12 e-80/T
9.510-12 e-280/T
1.010-11
1.710-15
2.5410-13 e-384/T
a
a
a
a
a
Table 3: Three Body Reactions and rates
R43
R44
R45
R46
R47
R48
R49
R50
R51
Reaction
O + CO + M  CO2 + M
O + O + M  O2 + M
O2 + O + M  O3 + M
H + O2 + M  HO2 + M
2H + M  H2 + M
S + S + M  S2 + M
SO + O + M  SO2 + M
SO2 + O + M  SO3 + M
SO2 + OH + M  HSO3 + M
Reaction Rate
2.2110-33 e-1780/T n3
5.2110-35 e900/T n3
6.010-34 (T/300.0)-2.6 n3
5.4 10-32 (T/300)-1.8 n3
8.8510-33 (T/298)-0.6 n3
1.1810-29
5.1010-31
8.010-32 e-1000/T
4.3910-23 T-3.3
Reference
h
i
a
a
j
a
a
k
a
Table 4: Halogen species reactions and rates
R52
R53
R54
R55
R56
R57
R58
Reaction
HCl + O(1D)  products
HCl + O  OH + Cl
HCl + H  H2 + Cl
HCl + OH  H2O + Cl
Cl + O3  O2 + ClO
Cl + H2  HCl + O
Cl + HO2  HCl + O2
R59 Cl + HO2  OH + ClO
R60
R61
R62
R63
R64
Cl + H2O2  HCl + HO2
ClO + SO2  Cl + SO3
Cl + HS  HCl + S
Cl + H2S  HCl + HS
ClO + SO  Cl + SO2
Reaction Rate
1.510-10
1.010-11 e-3300/T
2.3910-11 e-1730/T
2.6110-12 e-350/T
2.9110-11 e-260/T
4.710-11 e-2300/T
r1 = 1.810-11 e171/T
r2 = 4.110-11 e-448/T
r1/(r1+r2)
r1 = 1.810-11 e171/T
r2 = 4.110-11 e-448/T
r2/(r1+r2)
1.110-11 e-980/T
1.010-18
1.110-10
3.710-11 e210/T
2.8110-11
Reference
c
a
c
c
c
c
c
c
c
c
c
c
c
(a) Sander et al. (2006)
(b) Yu and Varandas, (1997)
Preprint submitted to Elsevier Science
3/14/16
(c) Yung and DeMore (1982)
(d) Gericke and Comes (1981)
(e) Atkinson (1989)
(f) Christensen et al. (2002)
(g) Int. J. Chem. Kinet. 14 1149 1982, 250-370K, 0.03-0.04Bar, Ar, measured
(h) Inn, E.C.Y., 257-272, 1974
(i) Tsang and Hampson 1986
(j) Baulch (1992)
(k) Krasnopolsky (2006)
(l) Molina et al. (1981)
(m) Moses et al. (2002)
(n) Yung et al (2008) Branching ratio estimated
(o) Lu et al. (2006)
(p) Mills (1998)
(q) Yung et al (2008) Estimated based on analogy with O + CO + M  CO2 + M
Figure Captions
Figure 1: Temperature profile and Eddy Diffusion Coefficient
Figure 2: Chemical pathways of importance
Figure 3: VEx SOIR water mixing ratio profile plot (Berteaux et al, 2008)
Figure 4: SOx profiles std ref
Figure 5: HOx profiles std ref
Figure 6: ClOx profiles std ref
Figure 7: Water mixing ratio profiles with fixed SO2 lower boundary of 25 ppm: H2O
10-35 ppm
Figure 8: SO2 mixing ratio profiles with fixed H2O lower boundary of 18 ppm: SO2 5100 ppm
Figure 9: Water sensitivity study: Mixing ratio of SO2 at 80 km
Figure 10: SO2 sensitivity study: Mixing ratio of H2O at 80 km
Preprint submitted to Elsevier Science
3/14/16
Figure 1:
Preprint submitted to Elsevier Science
3/14/16
Figure 2:
Preprint submitted to Elsevier Science
3/14/16
Figure 3:
Figure 4:
Figure 5:
Preprint submitted to Elsevier Science
3/14/16
Figure 6:
Preprint submitted to Elsevier Science
3/14/16
Figure 7:
Figure 8:
Preprint submitted to Elsevier Science
3/14/16
Figure 9:
Preprint submitted to Elsevier Science
3/14/16
Figure 10:
Preprint submitted to Elsevier Science
3/14/16