Manuscript Number: MS#ApJ82546
Manuscript Title: Synergistic Study of Hydrocarbon Photochemistry in the Laboratory and the
Atmosphere of Titan
Dear Dr. Federman
We have made revisions to our manuscript that address the comments of the referee and outline
them below. We will first reproduce the referee’s question in italics, followed by our response. In
several important cases, some of the major concerns of the reviewer could be addressed simply
by providing more or clearer details both here in response and in the revised version of the
manuscript. In several other cases, we have performed the tests that the reviewer suggested and
find our results are not compromised. We believe that these changes and tests address the
reviewer's concerns, as well as make the manuscript more readable.
Another important revision we made to the paper is to emphasize the preliminary nature of our
results. We have changed the title to “Bridging the Gap Between Laboratory Kinetics and
Atmospheric Composition: A Case Study Using the Adjoint Method”. Therefore, the
emphasis of this paper is on the innovative method rather than the final results. Consequently, we
carried out two major changes: (a) identification of some major weaknesses in the presently
available laboratory experiment data, and possible improvements for future experiments (b) the
paper has been substantially reduced in scope. The original paper adopted in the forward model
both the kinetics sets of Moses et al. (2000) and Moses et al. (2005), and applications include
Titan and Jupiter (the latter is in an Appendix). The revised paper has been shortened by
eliminating the cases for Moses et al. (2005) and Jupiter. These cases will be deferred till better
laboratory data become available.
As new and better experiments will be carried out in the laboratory to elucidate the chemistry of
planetary atmospheres, our method will assume greater importance and this paper is just a
beginning.
All authors concur with the changes that have been made.
Although I applaud both the testing of reaction schemes against lab data and the introduction of
adjoint models to the planetary photochemistry community, I think there are some serious
implementation problems with the modeling -- particularly for the laboratory simulations -- that
would prevent this paper from being published in its current form. Major revisions are required
due to point 2 below. I am not even sure these problems can be fixed. Going to a much finer grid
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near the window of the chamber may resolve some of these problems, but I have my doubts. The
experimental conditions (total optical depth ~60, or even higher at short wavelengths) are not
favorable for simulations of the fate of the CH4 photolysis products because all the interesting
chemistry is occurring in the first few millimeters of the 36-cm reaction chamber, right near the
window. There may be heterogeneous reactions on the window that are important and not
accounted for with the model, and there will certainly be species gradients that affect the derived
abundances that are not being accounted for with the current simulations. It would be better to
model an optically thin or nearly optically thin case here if the authors want to reliably test
reaction schemes. In any case, the model grid is not sufficient to resolve the abundances near the
window and thus cannot accurately track production and loss rates in the chamber. Given that
fact, the rest of the modeling -- including the adjoint model -- is moot.
Reply: The model resolution is not a problem, as we describe in more detail below in our
response. Our model grid was not set uniformly and does properly take into account radiative
transfer near the deuterium lamp source on the smaller scales necessary. We have made this clear
in the revised version by stating “Since most of the UV radiation in the laboratory experiments is
absorbed by molecules in the top few cm of the reaction cell, the model grid (58 layers) is chosen
carefully to ensure that the UV attenuation is calculated correctly; the grid size varies from 10-3
to ~1 cm, with higher resolution near the light source.”
Heterogeneous wall reactions are a common laboratory problem; we have addressed at least
some of the reviewers concerns by the following:
1. We now include experimental details comparing the 16L stainless steel volume experimental
data modeled here with data from similar experiments in the same lab with the same light source
performed in a 1L quartz volume that was designed to check for wall effects. The behavior of
hydrocarbon species produced in the smaller quartz volume was identical (apart from calculable
differences due to the smaller volume itself), suggesting that wall effects are not dominating the
chemistry in either case. This is now discussed in the experimental section, and further details
are available in the PhD dissertation of Mate Adamkovics, which is easily available on the web.
2. In case there are still remaining effects due to wall reactions in the laboratory hydrocarbon
production rates, we have also added text in various places in the manuscript to add this caveat
when appropriate. For example, we speculate in section 2.2 on reactions that may turn gaseous
hydrocarbons into aerosols. Later in the manuscript, since there remains poor agreement between
lab measurements and the adjoint model calculations, we clarify that the disagreement is due to
missing chemistry and that it is possible that that missing chemistry may include heterogeneous
chemistry, such as stating “Thus, we stress that the optimized values themselves for the rate
coefficients should not be interpreted as actual physical recommendations. Rather, this method
provides new insight into and guidelines for identifying possible missing chemistry and further
laboratory measurements that are needed to test them.” in page 16.
Point 1 below is also of major concern and may prevent the paper from being published at all,
unless the authors can convince themselves (and myself) that KINETICS is reliable enough for
this kind of time-variable box modeling. If they implement the three tests that I lay out in my
point 1 discussion and get consistent results, I will be satisfied.
Reply: The model is indeed capable of doing time-dependent calculations, as we explain in more
detail below in response to more specific reviewer comments and suggested tests.
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My general point 3 should also be of concern, but it is less major than points 1 and 2. The walleffect issue could possibly also be a major concern; note that the reaction chamber and the RGA
have walls, and the planets do not, and note that their fit to the planetary data is much better. I
think point 1 and 2 explain this problem, but one should not discount the possibility that
heterogeneous wall effects are important for the chemistry in the chamber. ApJ should reveal my
identity (Julie Moses), and I would be happy to run some tests of my own if the authors send me
a valid flux file.
Major points:
1. General major concern. The algorithm used by the Caltech KINETICS code was not designed
to be used for accurate predictions of time variability leading up to steady state, according to
what the code's developer, Yuk Yung, once told me -- and note that Yuk is a coauthor on this
paper. KINETICS does an excellent job of deriving the steady-state solution, but it apparently
does not do so well with the intermediate steps in getting there. I have tried to do this kind of box
modeling myself for simulations of laboratory data, and I eventually found (unfortunately, after I
had already published something) that the KINETICS code is unreliable for the time variability.
Specifically, when I varied the time step (and number of time steps), I got a completely different
answer after a specified number of hours for different time-stepping scenarios. When I ran this
problem by Yuk, he advised that I switch to a code that utilizes the Gear method. I was able to
get some more consistent results when I went to a very strict convergence criterion (CONVF
parameter in KINETICS of 1.0e-05), but the code hangs up on some applications with that
CONVF, and I have never been convinced that the code is supplying the correct results, even in
the case when this does work and I get more consistent results. I would suggest that the authors
try three tests: (1) divide their normal DELT by 10 and multiply NTIME by 10... assuming you
are using an appropriately short time step to begin with. Do they get the same answer after a set
number of minutes or hours? (2) do the same thing, but this time multiply/divide by 100 and/or
1000. (3) Keep their normal time-stepping procedure, but reduce CONVF by a factor of 10 and
then 100. Are they getting a different answer each time? If so, KINETICS seemingly cannot be
trusted here, and they should be using some other code... or get advice from Yuk on how to
proceed with KINETICS with these time-variable box models (and tell me!). Or, do some
analytic tests or something that convinces them that the results can be believed. Can KPP be
used for these kinds of forward box models? If so, try using that. If not, I do not know what to tell
the authors other than that some of the model-data mismatch may be an artifact of the
KINETICS time-variable models and not necessarily a problem with the Moses et al. kinetic
schemes.
Reply: We have done the series of tests for KINETICS model suggested by the reviewer. We
varied CONF from 1e-3 to 1e-5 and the time step from 1 sec to 100 sec. The maximal difference
(loose CONVF=1e-3 with time step 100 sec vs. CONVF=1e-5 and time step 10 sec) is 5% for
radicals such as atomic hydrogen and <<1% for stable molecules. Indeed, the validity of timedependent calculations for KINETICS was shown in 1980s by Allen et al. (Allen, M., J. I.
Lunine, and Y. L. Yung. (1984). "The Vertical Distribution of Ozone in the Mesosphere and
Lower Thermosphere." Journal of Geophysical Research-Atmospheres 89(ND3): 4841-4872.)
Based on these tests, we argue that the model is indeed capable of providing reliable timedependent results.
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The reviewer is correct that the KPP toolbox can be used to solve for time-dependent chemical
kinetics, as the numerical method employed is a third order Rosenbrock scheme (i.e., implicitly
stable with an adaptive time step). However, given that the KINETICS results were not found to
be highly susceptible to the time stepping and convergence parameters, validating the
KINETICS results using the more accurate KPP scheme does not seem necessary.
2. General major concern. The initial CH4 density in the chamber is 2.3e+18 cm-3. The authors
describe the chamber as being 36 cm in length, and they divide the simulated chamber into 58
grid layers of ~0.6 cm each. That can be compared with the 140-nm photoabsorption cross
section of CH4 at 295 K of 6.9e-19 cm2 (Chen and Wu 2004). The UV photons reach an optical
depth of 1 in the first grid layer, even for 140 nm, and the situation is worse for the shorter
wavelengths. At 130 nm there is still a lot of lamp flux, but the CH4 cross section is now ~1.7e17 cm2, which means optical depth one is reached a mere 0.25 mm into the chamber. They are
not sufficiently resolving all the complex chemistry that is occurring at sub-cm scales in the
chamber, and they therefore cannot accurately track the column production and destruction
rates in the chamber with their current modeling procedure. It is much better to attempt to
simulate an experiment that is nearly optically thin than very optically thick, as there is a lot that
can go wrong in the optically thick case. They would actually need to go to a much finer grid to
simulate the Adamkovics and Boering experiment reliably, even if they trusted KINETICS. That
is particularly important for the first ~1 cm of the chamber, so maybe they could switch to a
variable-length grid with very fine scaling in the first couple cm, with broader spacing after that.
Figure out what they need for Lyman alpha, or wherever the CH4 cross section is highest in the
region before the lamp flux starts to drop off at short wavelengths, and calculate where optical
depth unity is in that situation. Then reduce the grid spacing to below this value.
Reply: The grid size was chosen carefully so that the radiative transfer was done correctly and in
fact was not uniform, with much higher resolution near the window, as the reviewer points out is
required. However, we neglected to state this explicitly in the previous version of the manuscript.
We have now clarified this important point in the revised version, which has been revised to now
read (Page 6, line 169):
“Since most of the UV radiation in the laboratory experiments is absorbed by molecules in the
top few cm of the reaction cell, the model grid (58 layers) is chosen carefully to ensure that the
UV attenuation is calculated correctly; the grid size varies from 10-3 to ~1 cm, with higher
resolution near the light source.”
The validity of the radiative transfer in the model with this non-uniform grid size was tested
against the experimental production rate of H2, which directly reflects the photolysis rate of CH4.
Note also that there will be enormous gradients in the abundances of the radical species in the
chamber -- perhaps even for the stable species if mixing is not effective (although I cannot
imagine that it would not be, especially with the leak to the RGA) -- so it is not clear that the
RGA is sampling the entire chamber volume. Transport in the chamber, which is not well
constrained, will be important when species production is dominant near one end of the chamber.
If the stable species are well mixed, the RGA sampling procedure might be okay, but the authors
should then be using the column-average mixing ratios for their comparisons. Since the
concentrations of radicals will be very high right near the window, their overall production rate
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for hydrocarbons will be very sensitive to their grid spacing. I am not even sure that going to a
finer grid would help. Since the radicals are produced so near the window, it is likely that
heterogeneous wall effects could be contributing to the chemistry, and they are not considered in
the model. They would be much better off finding or running an experiment with more optically
thin conditions to do their testing and optimizations. Note that they can still test the scheme at 70
torr, if desired. Reduce the CH4 concentration in the chamber and add an inert non-110-130 nm
absorbing gas to bring the total pressure up to 70 torr or any other desired pressure.
Reply: First, we note again that the model is highly resolved near the window. Second, we have
added experimental details on the time scale for mixing of stable gases in the reaction chamber to
the revised manuscript (which we note below when this comes up again in further reviewer
comments). And, third, yes, experiments performed under more optically thin conditions and at
lower pressures are being pursued, but each set of experimental conditions presents its own
problems and challenges, and it is difficult to achieve production rates that exceed experimental
detection limits at lower pressures given limitations of the photon fluxes of UV light sources and
path lengths attainable in the laboratory. Indeed, this is one of the major reasons that there is
such a dearth of time-dependent laboratory data for CH4 photolysis; to date, we know only of
Adamkovics and Boering [2003], Vuitton et al. [2006], and Romanzin et al. [2010]. (We are not
aware that any of the older studies that the reviewer suggests are really for CH4 photolysis, but
usually in electric discharges). Each of these recent experimental setups has strengths and
weaknesses. For example, the Vuitton work was performed in a very large atmospheric chamber
and thus has the smallest perturbation from heterogeneous wall reactions; however, "indirect"
photolysis of CH4 had to be achieved by irradiating C2H2 with a set of 32 Hg lamps dispersed
throughout the chamber; this "photosensitized" photodissociation initiates the chemistry of
interest, but C2H2 has to be spiked into the chamber several times during the experiment;
furthermore, O2 leaked into the chamber over the course of the experiment and was found to
perturb the hydrocarbon chemistry (albeit with interesting results), and the photon flux
distribution throughout the chamber was unknown. The Romanzin et al. experiments use FTIR
spectroscopy (and thus avoid a leak valve to a mass spec), but they found very different results
using Lyman alpha vs an eximer pulsed laser and only detected species up to C2 hydrocarbons;
furthermore, their chamber size was an order of magnitude smaller than that in Adamkovics and
Boering, so that heterogeneous wall effects could arguably be larger in their study. Finally, the
Adamkovics and Boering experiments used mass spec not IR detection and so were able to
measure the time-dependent formation of H2, a critical species in the modeling done here that is
not available in the other studies, in addition to measurements of higher hydrocarbons that are
not available in the other studies. In short, we chose to use Adamkovics and Boering in this
manuscript because there is arguably nothing that is essentially better to test against that is
currently available. In light of the important questions the reviewer raises, however, we now
include in the manuscript a comparison of the strengths and limitations of these 3 studies in a
paragraph similar to this one. We have also gone through the manuscript and revised text in
several places to make the idea more clear that this experimental dataset has some strengths but
several important weaknesses, and that we use it as a "proof of concept" for the adjoint model to
point the way to what can be done when additional time-dependent laboratory experimental
results (from any lab in the world) are available.
3. General major concern. The authors are letting the optimization converge to unreasonable
values of the rate coefficients in most of their adjoint modeling. That is not appropriate. It is not
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a good application of the adjoint model, and ending up with optimized constraints that are
physically implausible renders the whole exercise meaningless. Set reasonable uncertainty
values on the rate coefficients. Some are extremely poorly known, and others are well known.
Also, these rate coefficients and their uncertainties are likely correlated, not uncorrelated as
they have assumed, but I am not sure what the authors can do about that. Keep it in mind, though.
Since they have arguments as to why it does not matter that they have unreasonable optimized
rate coefficients on p. 15-16, this problem is not as serious as 1 and 2 above. However, once they
resolve problems 1 and 2 and switch to another more appropriate photolysis experiment to
simulate, they will likely get a better fit the lab data, so they should apply the additional
constraints from the measurement uncertainties in both the lab measurements and the rate
coefficients, or their adjoint procedure will not be useful in illuminating the details of the real
reaction scheme.
Reply: Yes, we did show some results by setting errors for chemical reactions (p. 15-16), yet no
conclusive conclusion can be drawn. Rather, our current work presents the sensitivity of results
to chemical reactions which cannot easily be obtained by an iterative method. We also
understand that quite a few modifications are not reasonable, but we state this explicitly in
section 5. In the revised version, we now discuss in more detail in section 5 on key sets of
chemical reactions, which we hope will resolve the reviewer’s concern. The point is that -without the adjoint model -- it would be difficult to identify key reactions since the whole
chemical scheme is highly non-linear.
To minimize to the confusion, we moved the original table 2 to the appendix and added a new
table 2 that summarizes the key reactions, which we think is the most important outcome of the
paper.
------------------------------------------------------------- Specific points:
p. 3, first sentence. CH4 mixing ratio of 2% on Titan needs reference(s)
Reply: Reference added.
p. 3, lines 83-85. the authors are focusing on older Titan models here and ignoring the numerous
more recent (post-Cassini) Titan photochemical models, many of which do a good job of
reproducing the available Cassini, Voyager, and ground-based data. Be careful what is said
here, and they should update their references and discussion to include papers from authors like
Lavvas, Vuitton, Dobrijevic, Hebrard, and perhaps also cite papers from Krasnopolsky, de La
Haye, Yelle, Cui, Carrasco, Cravens, and Strobel, although some of the latter focus on the upper
atmosphere.
Reply: Four additional references that we think are crucial are added: Hebrard et al. 2007;
Lavvas et al. 2008; Vuitton et al. 2008; Krasnopolsky 2009
So far the only model that can reproduce the observed C2H4 abundance in the lower atmosphere
comes from Crespin et al. (2008, Icarus). They did not include upper atmospheric
photochemistry but simply prescribed a downward flux, which is not realistic. See section 2 and
Table 1 of their paper. So we didn’t include the reference.
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p. 4, line 107. Problem at line 107... "because t a" is unclear
Reply: “t” is removed.
p. 5, line 127. "A first attempt at simultaneously monitoring..." Delete "first" here or reword.
There are groups in France, the United States, and I think Israel and the UK who have been
doing CH4 photolysis experiments for decades, including monitoring the time variation of
products, ever since CH4 was detected on the giant planets and Titan... but also for basic gasphase kinetic information. The simultaneous monitoring of gas and aerosols in the 1970-1980s
was crude and restricted to optical depth measurements on windows and the like, but claiming
that this experiment was the first appears to be incorrect.
Reply: We have completely changed this introductory paragraph, explaining some of the
strengths and weaknesses of the "current generation" of experiments. We are unaware, however,
of older time-dependent studies of the formation of higher hydrocarbons or aerosol from CH4
'photolysis', as most previous studies used electric discharges. That's exactly the problem: it's
very hard to get a high enough UV photon flux in the lab that one can then detect products.
This leads to all sorts of complications. We hope the new paragraph in the introductory section
and additional reflections on possible wall effects will provide more clarity about the challenges
that experimentalists face.
p. 5, lines 133-134. Neither the authors nor Adamkovics and Boering provide the area of the
window into the reaction chamber. Also it would be useful if they provided fluxes in absolute
units rather than normalized arbitrary units in Fig. 1 since there is not enough information in
either paper to determine the flux going into the chamber. I would like to at least run some backof-the-envelope tests.
Reply: The spectrum is shown in Figure 1 and the total flux of 8.8x1015 photons/s between 120
and 300 nm is given in section 2.1. We've added in section 2.1 that the lamp aperture diameter is
1.0 mm.
p. 5, lines 150-151. H2 is not chemically inert under these conditions, as it reacts with C2H3,
CH3, and CH2 (and other things) under the experimental conditions. If H2 loss is really a factor
in the experiments, how will that affect the conclusions here and in Adamkovics and Boering
(2003)?
Reply: We have removed this clause, since what we meant was that the production rate of H2 is
much greater than its loss rate, not that it is chemically inert. The production rate of H2 is more
than a factor 20 higher than the loss rate, and the production is mainly due to the photolysis of
CH4.
p. 6. Are concentrations for the measured species uniform in their box-model simulations over
the 36-cm long grid? If not, where was the RGA emplaced, and is this issue taken into account?
Reply: Transport in the reaction chamber and model is achieved by random motions. The
modeled concentrations of stable molecules are nearly uniform, with deviations along the grid
being only ~10% for C2H4 and only ~0.1% for H2. Such differences are smaller than the
experimental errors associated with the mass spec measurements themselves, and so the
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placement of the RGA with respect to the UV light source does not need to be taken into account.
We now add the statement in section 2.2: “Molecules are allowed to diffuse freely in the model
box, and additional transport by eddy mixing is not considered. Such transport is sufficient
enough in uniformizing stable molecules. For example, the maximum percentage difference of
C2H4 and H2 are about 10% and ~0.1%, respectively, which are smaller than the experimental
errors.”
p. 6, lines 174-175. re. molecules diffuse freely... at what assumed diffusion coefficient?
Molecular diffusion only, or do the authors include some kind of turbulent diffusion? Given the
leak into the RGA, do they expect mixing to be effective, or not?
Reply: We only consider molecular diffusion in KINETICS model simulation. In the experiment,
stable gases are expected to be well-mixed in the reaction chamber by diffusion, based on
separate experiments in which the UV light source was turned off and on again at ~33 and 48
hours elapsed time, respectively. The gas phase species concentrations measured by the RGA
remained constant for those 15 hours until the light source was switched back on and then began
to increase again at the RGA within the time expected for diffusion. We have added this
information into the experimental section, as well as included the distance of the leak valve for
the RGA from the top of the chamber where the deuterium lamp is located for completeness.
p. 8, lines 215-216. Rate coefficients do not have infinite uncertainty, and the uncertainties are
frequently correlated. They have me worried about their assumptions for the adjoint model.
Reply: To clarify, this is an assumption of the inversion, not the adjoint model. Regardless, we
were concerned as well, hence the additional calculations using constrained parameters now
discussed on page 17.
p. 10, lines 282-284 are not clear. Table 1 shows the modifications for the seven cases with the
Moses et al. (2000) chemistry. Are the authors saying that for the seven additional cases with the
Moses et al. (2005) chemistry, they adopted the same modifications? If so, why?
Reply: Yes. The same modification factors applied to both the 2000 and 2005 chemical schemes.
The purposes are (1) to show the non-linear dependence of chemical reactions on the resulting
chemical abundances and (2) to demonstrate the laborious iterative methods compared with the
adjoint model which automatically calculates the sensitivity of the whole set of chemical
reactions.
p. 10, line 275-284 and Table 1. The authors have multiplied several reaction rate coefficients by
factors of 10, 100, or even 100,000. Did they check to see whether these changes were
reasonable? For example, 2H + M = H2 + M is a well-studied reaction at room temperature. It
will be occurring at its low-pressure limit under their conditions. At 295 K, lab data indicate the
rate is ~9e-33 with H2 as the background gas and ~6e-33 with Ar as the background gas -- data
also exist for background gases H2O, N2, H, NH3, and several noble gases, but not for CH4 or
hydrocarbons. These values might be uncertain by a factor of 3, but not more than that. They
cannot arbitrarily increase a rate coefficient like this by five orders of magnitude. Perhaps they
are doing this as a proxy for any missing reactions, such as recombination of H on the reaction
chamber walls. In that case, they should provide some kind of discussion of this issue here and
mention whether increasing the effective rate of 2H + M is a good way to handle the wall
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reactions and/or other potential missing reactions. They should be looking at all the reactions
here to determine whether their changes are reasonable, and if not, provide some discussion.
(CH3 + C2H3 and CH3 + C2H5 are reasonably well studied but the others are not). I note that
all the other reactions here provide some mechanism to get CH3 back to CH4, and I wonder if
increasing these reactions is also supposed to simulate CH3 + H recombination on the chamber
walls? That would also help cut down on C2H6.
Reply:
In any case, the authors definitely need some kind of discussion about whether you think wall
effects (in both the reaction chamber and RGA) are important under those experimental
conditions, and whether that might be a cause of the model-data mismatch. It is suspicious that
the reaction list does so well for a wall-less planet and so poorly (many orders of magnitude off)
for the experiments, especially when their optimization and "adjustments" are tweaking some
reaction rates that are relatively well known. I can believe that there are definite problems with
the Moses et al. (2000, 2005) reaction schemes, especially since they were designed for low
temperatures and not room temperature, and Lyman alpha CH4 photolysis, but errors of many
orders of magnitude make me concerned about the reliability of your box-model simulations (see
major point 1 above). I also am concerned whether they are really adopting my photolysis
branching ratios, etc., and/or if photolysis could be the major problem here. [note that I wrote
this before I checked the location of optical depth unity in the chamber, see point 2 above; now I
think that points 1 and/or 2 are the main problems, but these other issues should be checked].
Reply:. KB's new comment: is there a sufficient job done now in the revised manucript with
respect to this???
Table 1. What exactly does Case 1 "H2 profile normalized ... none" mean?
Reply: We replaced “H2 profile …none” by “Baseline model.”
p. 11, and really a general concern of the paper. One immediately obvious cause of an
overprediction of the C2H6 abundance and an underprediction of the C2H2 and C2H4
abundances (and the other complex unsaturated hydrocarbons that depend on them) is a wrong
photolysis branching ratios and/or photolysis cross sections for CH4. Note that CH and to some
extent CH2 help produce unsaturated hydrocarbons, whereas CH3 will end up as CH4 and
C2H6. Most of their photolysis is occurring in the > 130 nm wavelength region, where
branching ratios have been less well studied. The Lyman alpha branching ratios, which control
the process on the outer planets and Titan, have been better studied in recent years. From this
standpoint alone, it is not surprising that the model does a better job with real planets. Plus, I
am not convinced that the authors are truly using the Moses et al. photolysis reactions exactly as
implemented in those models. The reactions themselves may come from those papers, but are
they using my absorption cross sections and photolysis branching ratios? It is not clear -- I
would be happy to send them to you, in any case. Note that I specifically adopted lowtemperature (~150 K) cross sections whenever I found them in the literature, so they would need
to switch to room-temperature values for the experimental simulations. What did they assume for
CH4 photolysis, in particular? My branching ratios at Lyman alpha are different from values at
other wavelengths where they have high lamp flux. Perhaps that right there is the major problem
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with the model-data comparisons, if either I or they or both have inappropriate CH4 photolysis
branching ratios at wavelengths longer than Lyman alpha. I also have several complicated
pressure dependencies that must be implemented carefully, so I am not convinced the authors
are truly testing the Moses et al. (2000, 2005) schemes. There are a small number of reactions
that affect C2H6, and this model mismatch should have been their first line of attack in figuring
out the problems.
[Note that I wrote the above before I checked the optical depth in the chamber, see point 2 above.
Now that I see that it is a hugely optically thick situation that the authors are not spatially
resolving, I can understand some of the model-data mismatch. The radical concentrations will be
very high near the window, so radical-radical reaction rates will be higher than they are getting
in their simulation. 2H + M = H2 + M will be more effective, C2H5 + C2H5 + M = C4H10 + M
will be able to compete with H + C2H5 = 2CH3 and eventual C2H6 formation so that the
C4H10/C2H6 abundance will be increased, and unsaturated hydrocarbon production will be
greatly increased. These effects all head in the right direction for comparisons with the lab
measurements. The only thing I do not understand is the low abundance of C2H6 and C3H8,
which both indicate a reduced CH3 concentration... perhaps because the CH3 is more efficiently
converted back to methane?]
Reply:?
p. 11, lines 331-332. yes, the total destruction rate of methane is determined in the experiments.
Does the simulation match that total destruction rate? If not, the authors are misestimating the
photolysis rates or misestimating the net recycling of methane. They do not actually discuss
whether the total destruction rate is well reproduced by the model here, and their focus on
normalizing all of the figures rather than plotting actual concentrations or mixing ratios makes it
difficult to tell.
Reply: We add the initial mean photolysis rate coefficient of CH4 ~510-7 s-1 in section 2.1 (line
176). The same normalization constant is applied to both lab measured and model simulated
mixing ratios. For example H2 in Fig 2, the fig labeled value of 1 corresponds to the physical
volume mixing ratio of 0.06 stated in the fig caption.
p. 12, lines 355-360. The C4H2 abundance is hugely (and non-linearly) dependent on the C2H2
abundance, and if the authors were to find the cause of the C2H2 problem and fix it, they would
likely get reasonable C4H2 abundances.
Reply:?
p. 13, line 394. Their net equation is not balanced (they need two H's on the right side).
Reply: Corrected.
p. 15, re. error covariance terms. I did not think they could even do an adjoint model without
considering the error covariance terms... and they should not do one without considering
realistic uncertainties in the individual parameters (rate coefficients, in this case). Most
reactions have uncertainties associated with them from some of the major compilations (e.g.,
Baulch, NIST), the individual lab reports (where total errors seem to be typically
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underestimated), or they can come up with some estimates themself based on scatter in the
literature. Do not let the adjoint model modify the rate coefficients without these guidelines.
Reply: To clarify, it is indeed entirely possible to run an adjoint model without specifying either
measurement error or parameter uncertainty, as the adjoint model itself will calculate the
gradient of any scalar valued cost function with respect to the parameters. While not as
quantitative as an inversion with detailed error covariance estimates, such an unconstrained
inversion can still provide results that have useful interpretations, which is why we first stressed
the qualitative aspects of inversion in section 3.2. And yet we, as well the reviewer, are
nevertheless concerned about the specification of error and uncertainty on the inverse model,
which is why additional inversions were performed varying these aspects. Uncertainty estimates
of the parameters were estimated as a factor of twenty, lower than those reported in the cited
studies of Hebrard et al. Still, the overall interpretation of the results was the same as the
unconstrained inversion. Hence, we feel we have already addressed the reviewer’s concerns in
this area as we (a) didn’t overly interpret the quantitative aspects of the unconstrained inversions
and (b) did include additional tests with constraints drawn from the literature.
p. 16, lines 462-466. Although we may be missing reactions in the hydrocarbon chemistry
schemes, I doubt that the situation is as dire as the authors are deriving. I think there are serious
problems with their model simulations of the Adamkovics and Boering experiments (see points 1
and 2 above).
Reply: We rephrase the statement: This further suggests that we are indeed missing chemical
processes such as heterogeneous reactions for higher hydrocarbons. Indeed applying the lab
constraints for planetary purposes may not be appropriate at the current stage. It nevertheless
gives us some ideas of the sensitivity of the current hydrocarbon chemistry (see section 5).
whole paper. The authors do not cite the other papers that have tried to take a systematic look at
the sensitivity of the planetary hydrocarbon abundances to rate coefficients and their
uncertainties (e.g., Greg Smith's Jupiter study, or the Dobrijevic group's studies of Saturn,
Neptune... they do cite some of their Titan work). They also could have looked at the Moses et al.
specific sensitivity tests to help guide their adjustment choices in section 3.1.
Reply: We add a description in the introduction section: This suggests that the hydrocarbon
kinetics is incomplete and/or that the rate coefficients are incorrect (see also Hebrard et al. 2006a)
for the higher hydrocarbons. Several attempts have been made to study the sensitivity of the
current hydrocarbon schemes (Dobrijevic et al. 2003; Smith and Nash 2006; Hebrard et al. 2006;
Hebrard et al. 2007). Indeed, there is a dearth of laboratory measurements of the rate coefficients
of many relevant photochemical processes, especially at the extreme ranges of temperatures and
pressures encountered in planetary atmospheres.
Section 5 and the rest of the paper are speculations based on the questionable simulations of the
laboratory experiments. These speculations will likely change with a proper implementation of
the box-model laboratory simulations, ideally using a more tractable laboratory experiment.
Reply: We note again here that the reviewer's main concerns expressed here are likely addressed
by the validity of the time-dependent calculations and by the fact that radiative transfer near the
UV window are in fact handled sufficiently well. In addition, there really isn't a "more tractable
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laboratory experiment" available to us now for this work; we have made that more clear by
adding details of this and others' laboratory experiments and their strengths and weaknesses.
The overall length of the paper is appropriate, it is well written, and the application of the
adjoint model is an excellent idea if applied with proper constraints from rate-coefficient
uncertainties. I have no problems with the goals of the paper... I just think that the laboratory
simulations have some major flaws that are affecting the model-data comparisons. The
Adamkovics and Boering experiments are not well designed for the study of the details of CH4
photolysis -- the gas in the chamber is too optically thick to reliably simulate what is going on.
Reply: We thank the reviewer for the good and constructive comments in improving our paper.
We add a few more sentences in the conclusion section to stress the porosity of the lab
measurements. “Certainly there remain major gap in interpreting and modeling the laboratory
simulation, especially the wall effect. Future experiments done at less optically thick conditions
for CH4 photolysis are crucial to resolve the difficulties we are facing now. However the
comparison between the laboratory simulation and planetary application is still meaningful after
applying the adjoint model to analyze the laboratory results.”
Sincerely,
Mao-Chang Liang
Academia Sinica
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