Evaluating the contribution of the unexplored photochemistry of aldehydes on the tropospheric levels of molecular hydrogen (H 2 ).

. Molecular hydrogen, H 2 , is one of the most abundant trace gases in the atmosphere. The main known chemical source of H 2 in the atmosphere is the photolysis of formaldehyde and glyoxal. Recent laboratory measurements and ground-state pho-tochemistry calculations have shown other aldehydes photo-dissociate to yield H 2 as well. This aldehyde photochemistry has not been previously accounted for in atmospheric H 2 models. Here, we used two atmospheric models to test the implications of the previously unexplored aldehyde photochemistry on the H 2 tropospheric budget. We used the AtChem box model imple-5 menting 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 H 2 . We also used the GEOS-Chem 3-D atmospheric chemical transport model to test the impacts of the new photolytic 10 H 2 source on the global scale. A new H 2 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 H 2 . We found an increase in the chemical production of H 2 over tropical regions where high abundance of isoprene results in the secondary generation of methylglyoxal, glycolaldehyde and methacrolein, ultimately yielding H 2 . We calculated a final increase of 0.4 Tg yr − 1 in the global chemical production budget, compared to a baseline production of ∼ 41 15 Tg yr − 1 . Ultimately, both models showed that H 2 production from the newly discovered photolysis of aldehydes leads to only minor changes in the atmospheric mixing ratios of H 2 , 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 H 2 budget, including emissions and soil uptake.


Introduction
The current global climate crisis has prompted governments to take actions towards decreasing greenhouse gas emissions.

Box modelling results: contributions of aldehydes to the photochemical production of H 2
Because of the short modelled times (limited by available measurement constraints), none of the baseline simulations represented steady state conditions. As a result, we focus on interpretation of changes to chemical production rather than changes 125 to mixing ratios. However, we first briefly describe mixing ratios in the baseline simulations to provide context for our results.
Select modelled species from the baseline simulations for London, Cape Verde and Borneo are shown in Figures S1-S3 respectively. The baseline mixing ratio of H 2 increased continuously from its initial value of 530 ppbv to 639.97 ppbv at London and 533.96 ppbv at Borneo. At Cape Verde, the mixing ratio of H 2 decreased during the simulated period to 517.23 ppbv. These changes are equivalent to an increase in H 2 of ∼17% over 12 days for London, an increase of ∼1% over 6 days for Borneo, 130 and a decrease of ∼2% over 12 days for Cape Verde. These final H 2 mixing ratios are not representative of the actual values 5 https://doi.org/10.5194/acp-2021-1052 Preprint. Discussion started: 18 January 2022 c Author(s) 2022. CC BY 4.0 License. over the selected locations particularly because of the lack other relevant physical processes such as emissions, transport and uptake by soil.
For the London and Borneo simulations, the H 2 increase over time in the baseline run was effectively caused by the photolysis of formaldehyde and glyoxal (the only H 2 sources in this simulation). The decrease in modelled H 2 at Cape Verde was a result 135 of imbalances in the chemical sources and sinks in this regime. For the Cape Verde simulation, neither formaldehyde nor glyoxal had available measurement constraints (see Table 1); however, both were produced chemically, with formaldehyde production from the degradation of methane, ethene, propene, toluene and benzene and glyoxal production from ethene and toluene precursors (Stavrakou et al., 2009). These five precursor species were all constrained in the Cape Verde simulations (see Table 1, footnote b). Figure S2 shows the time series of selected species modelled for Cape Verde, including formaldehyde, 140 which had an average modelled value of ∼800 pptv (∼2×10 10 molecules cm −3 ). For comparison, Whalley et al. (2010) reported an average noon value of 328 pptv for their MCM simulations at Cape Verde during May-June 2007 (note that they do not report values for glyoxal). Considering that our modelled formaldehyde mixing ratios were higher than those reported previously by Whalley et al. (2010), and because of the formaldehyde and glyoxal lifetimes of a few hours, we conclude that our simulations included sufficient precursor concentrations and therefore that the decrease in H 2 in the baseline Cape Verde 145 simulation implies that the available H 2 was consumed by OH more rapidly than it could be produced by formaldehyde and glyoxal, yielding an effective loss over the 12 days modelled.
H 2 chemical production provides a more realistic and useful outcome from the box model simulations. At all three modelled sites, the relative rate of H 2 chemical production in the sensitivity simulations increases relative to the baseline simulation and scales linearly with the quantum yield over the 1-10% range studied here (see Figures S4 and S5). This linearity makes 150 it reasonable to interpolate the predicted MCM production rates simulated here for as-yet unmeasured aldehydes to whatever experimental quantum yield is ultimately determined.
We use the sensitivity simulations to evaluate the relative importance of each aldehyde. Figure 1 displays the relative daytime contribution of each newly-considered aldehyde to the total aldehyde-derived photolysis H 2 production rates modelled using a 1% quantum yield (not including the contributions from formaldehyde and glyoxal, which were not modified in this work). For Borneo, the modelled distribution of the aldehyde contributions to H 2 production was completely different than modelled at the other two sites. Aliphatic aldehydes provided only a minor contribution. There was a particularly notable difference in the influence of acetaldehyde, which represented more than half the new H 2 production at London and Cape Verde but only 5% of the production at Borneo. Meanwhile, the contributions of methylglyoxal (46%), glycolaldehyde (35%) and other unsaturated aldehydes were markedly larger at Borneo than at the other two sites. The results for Borneo clearly show the influence of 170 biogenic isoprene in the rainforest atmosphere, as methylglyoxal, glycolaldehyde and methacrolein are all products of isoprene oxidation (Wennberg et al., 2018). The isoprene in Borneo reached values of up to 2350 pptv (5.7×10 10 molecules cm −3 ) (Hewitt et al., 2010) (see Figure S3). As a comparison, the isoprene mixing ratios in London were much lower at about ∼17% of the Borneo values. No isoprene was simulated for Cape Verde, but previously reported typical noon values at Cape Verde of ∼10 pptv  imply its contribution to H 2 production from aldehydes there would be negligible. The larger 175 effect of the new photochemical H 2 sources at Borneo relative to the other sites due to the abundance of biogenic VOCs implies the newly discovered photochemical production pathways will have most influence in biogenic source regions, and this will be explored in the next section using the global model.
The box modelling with the MCM v3.3.1 allowed us to test H 2 production from the photolysis of a wide range of aldehydes in a complex and explicit chemical mechanism. While H 2 did not reach steady state in any of the box models (due to the 180 short simulation period), these box model simulations identified the aldehydes that are expected to contribute the most to photolytic production of H 2 under distinct environmental conditions. In urban environments, modelled as the London site, linear aliphatic aldehydes (especially acetaldehyde and propanal) are the most relevant. For regions with substantial vegetation (e.g., tropical forested areas such as Borneo), aldehydes that are produced from the oxidation of isoprene, such as methylglyoxal and glycolaldehyde, are the most important. At all three sites, aside from glycolaldehyde, none of the oxygenated aldehydes modelled here (blue tones in Figure 1) featured with any significance to the formation of H 2 . However, the short simulation times (driven by lack of appropriate observational constraints) and the absence of physical sources and sinks limit the usefulness of the box model results for further quantifying the effects of the relevant identified aldehydes on tropospheric photochemical formation of H 2 . We therefore turned to a global chemical transport model (GEOS-Chem), in which we were able to include not only the new photochemistry for the most relevant species as identified by the box modelling but also physical processes 190 (emissions and soil uptake). With the global model, we were also able expand the evaluation to diverse environments across the globe and to run simulations for periods long enough to allow H 2 to reach steady state, providing more robust results. The global modelling of H 2 is described in the following section. The default version of GEOS-Chem v12.5.0 does not include H 2 as an active species, and so the H 2 mixing ratio has a fixed concentration of 500 ppbv across the troposphere. However, observations compiled by CSIRO at four sites, two located in the Northern Hemisphere (Krummel et al., 2021b, a) and two in the Southern Hemisphere (Krummel et al., 2021d, h) show that on 205 average the global mixing ratio of H 2 is ∼530 ppbv. Based on these observations, the initial mixing ratio of H 2 was modified in GEOS-Chem to match the average observed value of 530 ppbv.
For our baseline configuration, we added known H 2 physical sources and sinks into GEOS-Chem. We scaled H 2 emissions to inventory estimates of carbon monoxide (CO) emissions as done previously in other studies (Ehhalt and Rohrer, 2009) as there are no dedicated emission inventories available for H 2 . The scaling was performed using the Harmonized Emissions Compo-210 nent (HEMCO) in GEOS-Chem (Lin et al., 2021). Two different emission ratios were implemented, one for anthropogenic combustion sources (0.042 g H 2 /g CO) and the other for biomass burning sources (0.021 g H 2 /g CO) based on the fractions used by Price et al. (2007). For anthropogenic H 2 emissions, the Community Emissions Data System (CEDS) global inventory (Hoesly et al., 2018) was used. The CEDS emissions were overwritten by more detailed regional emission inventories where applicable: APEI for Canada, DICE-Africa for Africa (Marais and Wiedinmyer, 2016), EPA/NEI11 for North America and  We also added the atmospheric H 2 sink from soil uptake. The soil uptake of H 2 involves both biological (enzymatic and microbial activity) and physical (molecular diffusion) processes, which jointly determine the magnitude of the sink (Yver et al., 2010). The correlation of the enzymatic and microbial activity with soil temperature and moisture drives the seasonality 230 of atmospheric H 2 . Soil temperatures between 20 • C and 30 • C are optimal to capture H 2 , with no capture below −20 • C or above 40 • C. Likewise, arid and frozen soils have been shown to have low values of H 2 uptake (Yashiro et al., 2011). The rate of soil uptake of H 2 has been measured as a dry deposition velocity and thus is typically parameterised in models as a dry deposition process (Ehhalt and Rohrer, 2009;Yver et al., 2010;Yashiro et al., 2011).  Deposition onto water bodies is not considered in our simulations. Although Punshon et al. (2007)  water bodies, we did not include this sink and expect this would have a negligible impact on the findings reported here.
Our baseline simulation also includes H 2 chemical production and loss. The standard chemical mechanism in GEOS-Chem already includes the major known chemical sources of H 2 : photolysis of formaldehyde and glyoxal, reaction of excited oxygen atoms with methane, and reaction of the H atom with the hydroperoxyl radical. Similarly, the standard mechanisms also includes the only known significant chemical H 2 sinks: reaction of H 2 with the hydroxyl radical and with chlorine atoms.

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While these sources and sinks were already present in GEOS-Chem v12.5.0, they did not influence simulated H 2 as it was set as a "fixed" species, with a constant value of 500 ppbv. Here we change H 2 to an active species so that the H 2 concentrations change in response to the chemical sources and sinks outlined above.

GEOS-Chem modelling results: evaluation of the baseline simulation
Before testing the impact of the new H 2 source from aldehyde photolysis, we first evaluated the performance of the baseline 265 simulation.  (Hauglustaine and Ehhalt, 2002) to 172 Tg (Sanderson et al., 2003). Our estimate for the H 2 lifetime is 2 years, in agreement with previous reports that range from 1 year (Rhee et al., 2006;Xiao et al., 2007) to 270 2.3 years (Sanderson et al., 2003).  approach used in other studies (including our baseline). The generally good agreement in the H 2 chemical source between our baseline and the other studies indicates that photolysis of formaldehyde and glyoxal yields H 2 production consistent with prior estimates, providing an appropriate baseline to compare to the so far unexplored photochemical production of H 2 from other aldehydes.
As in previous work, the soil uptake sink was almost three times higher than the chemical sink in our baseline simulation. We use the CSIRO measurements (Krummel et al., 2021b, c, d, e, f, g, h, a;?) to assess the H 2 seasonal cycles. Model biases and other statistical metrics calculated are shown in Table S2 in the supplementary material. The supplement also includes 310 a comparison of modelled and observed H 2 vertical profiles using aircraft measurements (Krummel et al., 2021i). These are shown in Figure S7 and are not discussed further here. Figure 4 shows a seasonal spatial average of H 2 mixing ratios in surface air averaged over 2015 and 2016, with simulated values overlaid by the observations of CSIRO. Modelled mixing ratios at 500 hPa can be seen in Figure S6. As expected, in each hemisphere, the H 2 mixing ratios are lower in the corresponding summer and autumn than in spring and winter months.

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This seasonal trend is driven by the soil uptake ( Figure 3) and its relationship with soil temperature and moisture. During summer and autumn, the temperature conditions are optimal for the soil uptake of H 2 , yielding lower concentrations of H 2 in surface air.
In the Northern Hemisphere, the mixing ratios of H 2 were highest during the December-January-February (DJF) and the March-April-May (MAM) periods. Modelled H 2 was lowest in SON over Russia (∼400 ppbv), followed by North America  modelled estimates of H 2 over China and Korea is DJF. A similar trend in the estimated mixing ratios of CO implies that the anthropogenic emissions inventories used over this region are likely responsible for the high values of these modelled gases.
In the Southern Hemisphere, elevated H 2 mixing ratios on the order of 550-600 ppbv modelled over Africa and Indonesia 325 in austral winter-spring (JJA and SON) coincide with the seasonal cycle of biomass burning emissions (Pak et al., 2003;Edwards et al., 2006). Throughout the year, the lowest H 2 mixing ratios globally are found in South America, in particular in the Amazon region. Over these regions, modelled mixing ratios are consistently lower than 450 ppbv. To our knowledge, there are no available measurements of H 2 for South America that could be used to evaluate the modelled mixing ratios there.
Observations are also lacking over most of the Middle East, parts of Asia, Africa and Australia. H 2 measurements over these 330 regions would provide particularly valuable constraints in further modelling endeavours. Figure 4 show that there are different biases in different locations, with notable underestimates at the the Southern Hemisphere observing sites.

The visual comparisons in
While limited in spatial extent, the CSIRO data is well suited for evaluating modelled mixing ratios and seasonal patterns.  (Krummel et al., 2021b, c, d, e, f, g, h, a). At the two sites located in the Northern Hemisphere (Alert, ALT and Mauna Loa, MLO), GEOS-Chem was able to capture both the magnitude and the majority of the variability over the two years. At the six sites in the Southern Hemisphere (Cape Ferguson, CFA; Cape Grim, CGO; Macquarie Island, MQA; Casey, CYA; Mawson, MAA and South Pole, SPO) the model captures the observed seasonality but is biased low by >∼20 ppbv. In other words, the CSIRO measurements indicate a persistent low bias in modelled Southern Hemisphere H 2 mixing ratios. The 340 measurements at sites like Cape Grim (CGO) represent baseline-selected (clean air masses) only. The model output analyzed was not filtered to match background conditions at some of the CSIRO sites, a condition that could be a minor contributing factor to some of the observed bias. Figure S8 shows that the baseline-selected in-situ data have differences of ∼3 ppb and are in good agreement with baseline-sampled flask data. On the other hand, a misrepresentation of biomass burning emissions or biased inter-hemispheric modelled mixing ratios are unlikely the cause of the difference between observations and predictions 345 because of the good model performance shown in CO estimates. However, a revision of the mass fractions used to scale the emissions inventories of CO to H 2 is recommended. Figure S9 in the supplement shows that the Southern Hemisphere modelled bias is unique to H 2 and is not seen in CO. Given the large ocean area in this part of the world, underestimated ocean H 2 emissions are a possible driver of the bias. Improvements to ocean H 2 emission parameterisations with particular emphasis on the Southern Ocean should be a priority for future model development.

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Overall, our baseline model was able to capture the main features of observed spatial and seasonal variability of the H 2 reported by CSIRO (Krummel et al., 2021b, c, d, e, f, g, h, a). Combined with the fact that the simulated H 2 budget, burden, and lifetime are all consistent with previous estimates, the observational evaluation lends confidence to the suitability of our baseline model configuration. In what follows, we further adapt our baseline configuration to test the impact on tropospheric H 2 of its generation from photolysis of aldehydes other than formaldehyde and glyoxal. The GEOS-Chem chemical mechanism includes nine aldehydes: formaldehyde, glyoxal, glycolaldehyde, acetaldehyde, methylglyoxal, methacrolein, hydroperoxyaldehydes (HPALD), dihydroperoxide dicarbonyl and a lumped species called RCHO representing other aldehydes with three or more carbon atoms. As mentioned previously, the standard mechanism already includes direct H 2 production from photolysis of formaldehyde and glyoxal. Here we tested the impacts of the direct formation of H 2 360 from photolysis of the rest of the aldehydes in GEOS-Chem (with the exception of dihydroperoxide dicarbonyl as it was not present in the box modelling test).
Photolytic H 2 production from aldehydes was added to the existing standard chemistry mechanism using KPP embedded within GEOS-Chem. We assigned the 1% quantum yield found by Harrison et al. (2019) for acetaldehyde to the selected aldehydes tested in GEOS-Chem, analogously to what was done for the box modelling (Section 2.1). The 1% from acetaldehyde 365 was taken as the reference quantum yield to test given that measurements for the rest of the aldehydes are not available, but the energy barriers for the production of H 2 from aldehyde photolysis indicates that the dissociation channels are accessible (Rowell et al., 2021). For acetaldehyde, glycolaldehyde, HPALD and RCHO, a branching ratio on the existing photolysis channels was added to account for the primary production of H 2 in addition to the existing photolysis products. For methacrolein and methylglyoxal, additional steps had to be taken as the current GEOS-Chem implementation of Fast-JX for methacrolein and created that separated the cross sections from the quantum yield. The cross sections for the two species were retrieved from Sander et al. (2020) and processed using the Fast-J v7.3c model, which covers 18 wavelength bins from 177 to 850 nm (Prather, 2015). The resulting binned cross sections and 1% quantum yield were then configured back into the customized version of Fast-JX v7.0 used in GEOS-Chem Eastham et al. (2014). Beyond these changes to the photochemistry, all other sources and 375 sinks were identical to those used in the baseline. We ran this modified version of the simulation with the new photochemistry from June 2014 to December 2016, again using the first six months as spin-up. This simulation will hereafter be referred to as the aldehyde photolysis scenario. Figure 6 shows the percentage difference in total tropospheric H 2 chemical production between the aldehyde photolysis scenario and the baseline simulation. The increase in the chemical production of H 2 from the new photochemistry for aldehydes 380 is widespread across the globe. Figure 6a shows that the increase in total column H 2 chemical production reached a maximum of ∼10%, with the biggest changes taking place over the Amazon. Forested regions in the African tropics, Indonesia, Papua New Guinea and northeast Australia show increases that ranged from 2% to 8%. At the surface ( Figure S10a), the increase in H 2 chemical production was up to 14% with the same spatial distribution as seen in Figure 6a for the troposphere as a whole.
In the vertical profile (Figure 6b and 6c), the increases in H 2 chemical production extended to 700 hPa over the tropics. This 385 increase well above the surface layer may be a result of the strong vertical transport in this region , with rapid transport of aldehydes from the surface to the mid-troposphere followed by their photolysis to yield H 2 .
The strongest response to the new aldehyde photochemistry is seen in regions with dense vegetation cover characterized by high isoprene emissions. The most relevant aldehydes for the formation of H 2 over densely vegetated areas are thus those related to the oxidation of isoprene and of its primary products, methacrolein and methyl vinyl ketone. Of particular importance 390 here are methylglyoxal and glycolaldehyde, products from the OH-initiated oxidation of both methacrolein and methyl vinyl ketone, which account for ∼79% and ∼49%, respectively, of the global sources of these aldehydes (Fu et al., 2008;Wennberg et al., 2018).
We conducted additional model sensitivity simulations to compare the H 2 production from each of the new aldehyde sources (e.g., excluding formaldehyde and glyoxal). From these sensitivity simulations, we find that methylglyoxal contributes ap-395 proximately 91% to the enhanced tropospheric H 2 chemical production from these additional aldehydes ( Figure S11a) while glycolaldehyde, methacrolein, and the other non-isoprene related aldehydes (acetaldehyde, HPALD and RCHO) collectively account for the remaining 9% ( Figure S11b). These results imply that the most relevant aldehyde to include in global model simulations for the direct photochemical formation of H 2 is methylglyoxal. We note that the estimated methylglyoxal mixing ratios in our simulations ( Figure S12) are comparable to those modelled and reported by Fu et al. (2008). Fu et al. (2008) com-400 pared their modelled methylglyoxal estimates against available observations finding no systematic bias at land sites. Although Fu et al. (2008) used few northern midlatitudes locations to perform their comparison, the similarity between our methylglyoxal mixing ratios and the ones by Fu et al. (2008) gives us confidence in our modelled methylglyoxal and subsequent generation of H 2 from its photolysis.
Despite the substantial increase in H 2 chemical production associated with the new aldehyde photochemistry, the change in 405 the tropospheric H 2 mixing ratios is very small, with a maximum change of 0.3% over South America as shown in Figure 7a. This equates to a change at the surface over South America of ∼0.5% (see Figure S13a).As seen previously for the chemical production, the biggest changes occur over the tropics. The influence of long-range transport (facilitated by the ∼2-year H 2 lifetime) can be seen in the figure, with an increase of up to 0.2% in the H 2 mixing ratios over the oceans. Figure 7b and 7c also show the injection of H 2 to higher levels in the troposphere, particularly in the tropics where the increase extends to 500 410 hPa, but as seen in the figure, the enhancement in the mixing ratios does not exceed ∼0.2%. At higher latitudes, the change is almost imperceptible, as expected by the lack of precursor aldehydes at those latitudes. values over the Amazon. Elsewhere the situation is much the same: the enhanced H 2 produced from aldehyde photolysis is largely deposited in the same locations, making the atmospheric enhancement of H 2 from aldehyde photolysis small. This implies that the increases in production had a tendency to occur in places and times where the loss rates are stronger than the global average. Although the effect is smaller than seen for the soil sink, the chemical loss of H 2 from reaction with OH ( Figure   19 https 8b) also increases as expected in response to the enhanced production, further contributing to the balance between additional 420 H 2 production and loss in the aldehyde photolysis scenario.
The tropospheric budget from the aldehyde photolysis scenario is shown alongside the budget from the baseline simulation in Table 2. Overall, the new photochemistry led to an increase in H 2 sources, sinks, and tropospheric burden compared to the baseline simulation, but all remained within the ranges reported by previous studies (Table 2). Summed over the global troposphere, the total increase in tropospheric H 2 chemical production from inclusion of direct H 2 production from newly-425 discovered aldehyde photolysis was only 0.98% for 2015 and 0.96% for 2016. Given the small changes in H 2 mixing ratios described above, there were no significant changes in model performance relative to observations at measurement sites. The low model bias observed in the Southern Hemisphere did not improve, which allows us to conclude that missing chemical sources are not likely to resolve the remaining uncertainties and biases in the modelled H 2 seen in the baseline simulation.  We configured the box model at three sites (London, Cape Verde and Borneo) to explore the production of H 2 under distinctive atmospheric conditions and constrained each box model simulation with measurements. The standard MCMv3.3.1 considers 18 aldehydes and their corresponding reactions, with formaldehyde and glyoxal already including a H 2 channel. We evaluated the generation of H 2 from the remaining 16 aldehydes in MCM by comparing a baseline simulation against 4 sensi-440 tivity scenarios each using different H 2 quantum yields (1%, 2%, 5% and 10%). The selected quantum yields for the sensitivity analysis were chosen based on experiments by Kharazmi (2018) that showed that methylpropanal has an 8% quantum yield for the H 2 channel. Our box model results allowed us to identify the aldehydes that are more likely to contribute to the H 2 production.

Summary and conclusions
Excluding the contributions from formaldehyde and glyoxal, which remain the biggest photochemical H 2 sources, in an 445 urban atmosphere, aliphatic aldehydes such as acetaldehyde and propanal contributed over 80% of the simulated photochemical generation of H 2 from aldehydes. Unsaturated olefinic aldehdydes and vegetation-related species like methylglyoxal, methacrolein and acrolein provided a collective contribution of less than 10%. The remaining minor contributions came from glycolaldehyde. In a marine atmosphere, results were similar, with acetaldehyde and propanal contributing to 90% of the H 2 .
In an atmosphere over a tropical rainforest, the oxidation products of vegetation-emitted species (i.e., methylglyoxal, glyco-450 laldehyde, methacrolein and acrolein) contributed to 81% of the H 2 produced. Based on the contribution at each modelled site, out of the 16 aldehydes tested with MCM, six were identified as the most relevant for H 2 production: acetaldehyde, propanal, glycolaldehyde, methylglyoxal, methacrolein, acrolein. Based on this finding from the box modelling, the global impacts of H 2 production from five of these aldehydes (excluding acrolein) were further investigated by using global atmospheric chemical transport modelling.