Evaluating the contribution of the unexplored photochemistry of aldehydes on the tropospheric levels of molecular hydrogen (H2)
- 1School of Chemistry, University of New South Wales, Sydney, NSW, Australia
- 2Centre for Atmospheric Chemistry, School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, NSW, Australia
- 3Department of Soil, Water and Climate. University of Minnesota, Saint Paul, MN, USA
- 4Earth System Division, National Institute for Environmental Studies, Tsukuba, Japan
- 5Climate Science Centre, CSIRO Oceans & Atmosphere, Aspendale, Australia
- 1School of Chemistry, University of New South Wales, Sydney, NSW, Australia
- 2Centre for Atmospheric Chemistry, School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, NSW, Australia
- 3Department of Soil, Water and Climate. University of Minnesota, Saint Paul, MN, USA
- 4Earth System Division, National Institute for Environmental Studies, Tsukuba, Japan
- 5Climate Science Centre, CSIRO Oceans & Atmosphere, Aspendale, Australia
Abstract. Molecular hydrogen, H2, is one of the most abundant trace gases in the atmosphere. The main known chemical source of H2 in the atmosphere is the photolysis of formaldehyde and glyoxal. Recent laboratory measurements and ground-state photochemistry calculations have shown other aldehydes photo-dissociate to yield H2 as well. This aldehyde photochemistry has not been previously accounted for in atmospheric H2 models. Here, we used two atmospheric models to test the implications of the previously unexplored aldehyde photochemistry on the H2 tropospheric budget. We used the AtChem box model implementing the nearly chemically explicit Master Chemical Mechanism at three sites selected to represent variable atmospheric environments: London, Cape Verde and Borneo. We conducted five box model simulations per site using varying quantum yields for the photolysis of 16 aldehydes and compared the results against a baseline. The box model simulations showed that the photolysis of acetaldehyde, propanal, methylglyoxal, glycolaldehyde and methacrolein yield the highest chemical production of H2. We also used the GEOS-Chem 3-D atmospheric chemical transport model to test the impacts of the new photolytic H2 source on the global scale. A new H2 simulation capability was developed in GEOS-Chem and evaluated for 2015 and 2016. We then performed a sensitivity simulation in which the photolysis reactions of six aldehyde species were modified to include a 1 % yield of H2. We found an increase in the chemical production of H2 over tropical regions where high abundance of isoprene results in the secondary generation of methylglyoxal, glycolaldehyde and methacrolein, ultimately yielding H2. We calculated a final increase of 0.4 Tg yr−1 in the global chemical production budget, compared to a baseline production of ~41 Tg yr−1. Ultimately, both models showed that H2 production from the newly discovered photolysis of aldehydes leads to only minor changes in the atmospheric mixing ratios of H2, at least for the aldehydes tested here when assuming a 1% quantum yield across all wavelengths. Our results imply that the previously missing photochemical source is a less significant source of model uncertainty than other components of the H2 budget, including emissions and soil uptake.
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Maria Paula Pérez-Peña et al.
Status: final response (author comments only)
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RC1: 'Comment on acp-2021-1052', Anonymous Referee #1, 20 Mar 2022
The authors analyzed the contribution of aldehydes on the chemical production and tropospheric levels of H2 using a box model and a 3-D atmospheric chemical transport model. The authors concluded that their results imply that the previously missing photochemical source is a less significant source of model uncertainty than other components of the H2 budget. Overall, the paper is well written and well organized.
Major comment:
My only concern is that the global model simulations were conducted with a resolution of 4x5. As the authors found in Section 2, the conditions over urban environments and regions with substantial vegetation are very different. Urban size is usually smaller than this scale. Can the model properly represent that with this resolution?
And below are a few minor comments.
Line 95: “The the” to “Then the”?
Line 216: Here it is “GFED4” but later it was denoted “GFEDv4s”. Please make it consistent.
Line 345: Change “difference between observations and predictions” to “difference between observations and model simulations”?
Figure 1. The colors are hard to differentiate especially the orange colors.
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RC2: 'Comment on acp-2021-1052', Anonymous Referee #2, 21 Mar 2022
In this study the authors estimate the contribution of aldehyde photolysis on the production of H2.
Using a chemical transport model, the authors conclude that this recently identified source makes a very small contribution to the overall H2 budget.
This analysis is performed using a newly-developed simulation of H2 in the GEOS-Chem model.The findings are interesting but require additional analysis for publication in ACP.
Major comments:
A) Section 2.
1) Given the limitations of the box model, the interpretation of the simulated H2 concentration is quite challenging as pointed out by the authors. I suggest to focus on the production rates [i.e., remove lines 125 to line 146]
2) Fig. 1. Please indicate the H2 production associated with aldehyde photolysis at each site and the time period considered. What is the production of H2 from the photolysis of formaldehyde and glyoxal at these sites. If the production from aldehydes is very small relative to that from formaldehydes and glyoxal, the authors need to clarify why they expect a different result from the global model.3) It's unclear why the authors restrict themselves to these 3 sites. Would it be possible to perform the same type of analysis using data from NOAA/NASA airborne intensive campaigns (acetaldehydes and glycoladelhydes are often measured)? This would help better constrain the importance of this process.
B) Section 3
Section 3 describes the representation of H2 in the GEOS-Chem model.
This representation is very similar to the one presented in Price et al. in 2007.
The authors have included a very detailed representation of aldehydes photolysis although the impact if minimal.
In contrast, the representation of other processes (emission, vd) does not entirely account for recent advances.1) Emission inventory
The authors use a constant emission factor to convert anthropogenic CO emissions to H2 emissions. Instead Ehhalt et al (2010) recommended using different emission factors for transportation.
Similarly, Akagi (2011) et Andreae (2019) reviews provide biome-specific emission factors for H2. It's unclear why the authors didn't use these.
Indeed, the Akagi estimates are already used by GFED4s.2) Deposition velocity
a) The authors need to discuss how the Yashiro model differs from the one presented by Ehhalt (2013). The Ehhalt model parameterization was used in two recent studies (Bertagni (2021) and Paulot (2021)). It would be interesting to test the model against against observations collected at Harvard Forest by Meredith (2017)
b) It's unclear why the authors do not calculate vd(H2) dynamically in the model using the parameterization described by Yashiro and soil moisture/temperature available from reanalysis (see Bertagni (2021), for instance). This would provide a significant improvement over the approach used by Price (2007) that solely (but interactively) accounts for the impact of snow cover and temperature.
c) I am not sure that I understand the benefit of using daily vd(H2) derived for a different period from the one considered here.
This will not account for the significant swings in H2 removal associated with soil moisture (see Bertagni (2021) for instance).
3) Impact of hydrogenThe authors need to describe how the improved representation of H2 in GEOS-Chem impacts the lifetime of CH4, the tropospheric and stratospheric O3 budget, and the stratospheric H2O budget.
As detailed in many studies (Derwent et al. (2000,2020), Field (2021), Paulot, (2021), Vogel (2012))), these are critical to understanding the indirect impact of H2 on radiative forcing.
4) EvaluationWhy aren't airborne observations discussed (Fig. S7). This is a unique dataset and the model does show significant biases that should be discussed.
Technical comments
1) Fig. 1 Please use IUPAC names for chemicals.
2) Fig. 3 is very difficult to read. Please use different colors for model and observations.
3) Are the authors using the results of the box model to select the aldehydes used in GC?
4) A fairly recent H2 budget was provided by Paulot (2021), which could be added to Table 2.
5) The AGAGE network provides H2 observations at Mace Head that should be considered.
6) The lifetime of H2 is ~2.5 years. Isn't a 6-month spin up much too short?
7) Fig. 5. Are these dry mixing ratios?
8) Line 348. The model seems to be biased low everywhere. Isn't CH4 oxidation another possible culprit.
9) Fig. 2a. I cannot distinguish between brown and red
10) Fig. 5. Please show the impact of aldehydes on the simulated H2 profile.
ReferencesAkagi S, Yokelson R, Wiedinmyer C, et al (2011) Emission factors for open and domestic biomass burning for use in atmospheric models. Atmospheric Chemistry and Physics 11:4039–4072. https://doi.org/10.5194/acp-11-4039-2011
Andreae MO (2019) Emission of trace gases and aerosols from biomass burning – an updated assessment. Atmos Chem Phys 19:8523–8546. https://doi.org/10.5194/acp-19-8523-2019
Bertagni MB, Paulot F, Porporato A (2021) Moisture Fluctuations Modulate Abiotic and Biotic Limitations of H2 Soil Uptake. Global Biogeochem Cy 35:. https://doi.org/10.1029/2021gb006987
Paulot F, Paynter D, Naik V, et al (2021) Global modeling of hydrogen using GFDL-AM4.1: Sensitivity of soil removal and radiative forcing. Int J Hydrogen Energ. https://doi.org/10.1016/j.ijhydene.2021.01.088
- AC1: 'Comment on acp-2021-1052', Maria Paula Perez-Pena, 20 May 2022
Maria Paula Pérez-Peña et al.
Maria Paula Pérez-Peña et al.
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