the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 24 Feb 2025
Effects of different emission inventories on tropospheric ozone and methane lifetime
Abstract. This study assesses the influence of anthropogenic emission inventories of ozone (O3) precursor species (i.e., NOx, CO and non-methane hydrocarbons (NMHCs)) prescribed in the simulations of the two phases of the Chemistry-Climate Model Initiative (CCMI) on tropospheric O3, the hydroxyl radical (OH) and the methane (CH4) lifetime. We performed two transient simulations for the period 2000–2010 with the chemistry-climate model EMAC, one prescribing the emission inventory of CCMI-1, and the other that of CCMI-2022. Using the tagging approach, we attribute the differences of O3, OH and the tropospheric CH4 lifetime to individual emission sectors. It is, to our knowledge, the first application of the tagging approach to attribute changes of the simulated CH4 lifetime to individual emission sectors.
The emission inventory used for CCMI-2022 leads to a 3.7 % larger tropospheric O3 column, and to a 3.2 % shorter tropospheric CH4 lifetime compared to CCMI-1 in the northern hemisphere. In the southern hemisphere, the tropospheric O3 column is 4.5 % larger, and the tropospheric CH4 lifetime 4.3 % shorter. Differences in tropospheric O3 are largely driven by changes of emissions from the anthropogenic non-traffic and land transport sectors in the northern hemisphere. In the southern hemisphere, the primary contributors are emissions from anthropogenic non-traffic, biomass burning and shipping. These sectors also play a significant role in reducing the simulated tropospheric CH4 lifetime. However, the contribution of a particular sector to changes in O3 does not necessarily align with its impact on the CH4 lifetime.
Competing interests: At least one author is member of the editorial board of ACP.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.- Preprint
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2025-294', Anonymous Referee #1, 20 Mar 2025
The manuscript “Effects of different emission inventories on tropospheric ozone and methane lifetime” investigates the influence of ozone precursor emissions on model simulations of ozone concentrations and methane lifetime. The authors applied a tagging approach to attribute differences in these variables to specific emission sectors. The manuscript is well-written, and the results provide valuable insights into inter-model differences in tropospheric ozone and OH concentrations. I recommend the manuscript for publication after addressing the following minor comments:
L120: Are there other non-methane volatile organic compounds included in the biogenic emissions besides C5H8?
Line 150 and Table 3: It would be beneficial to include both absolute and relative differences in emissions between the EMIS-01 and EMIS-02 simulations. This would provide a clearer comparison of the two emission inventories.
Section 2.2.3 The TAGGING submodel is used to attribute O3 production and OH mixing ratios to different emission sectors. However, given the highly nonlinear chemistry of O3 and OH, a more detailed explanation of how the TAGGING method attributes O3 and OH to individual emissions sectors would enhance the reader’s understanding of the results.
In equation (9), are there other ozone precursors (e.g. CO, NMVOC) also contributing to B(O3)? Are the differences in burden efficiency influenced by other ozone precursors?
The authors use two different methods to calculate changes in CH4 lifetime attributable to individual emission sources. While the two methods yield similar results for most sectors, they show divergent results for the land transportation sector (in Figure 7, method 1 indicates a large negative contribution, while method 2 shows a positive contribution). This discrepancy warrants further explanation. I recommend that the authors calculate the global tropospheric CH4 reaction-weighted OH concentrations contributed by each emission sector and simulation. This would provide a clearer understanding of how emissions influence CH4 lifetime.
L354 “the CH4 reduction from EMIS-01 to EMIS-01 in the NH”. I think it should be “the CH4 lifetime reduction from EMIS-01 to EMIS-02 in the NH”.
Citation: https://doi.org/10.5194/egusphere-2025-294-RC1 -
AC2: 'Reply on RC1', Patrick Jöckel, 17 Jun 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-294/egusphere-2025-294-AC2-supplement.pdf
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AC2: 'Reply on RC1', Patrick Jöckel, 17 Jun 2025
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RC2: 'Comment on egusphere-2025-294', Anonymous Referee #2, 08 Apr 2025
The manuscript “Effects of different emission inventories on tropospheric ozone and methane lifetime” by Acquah et al. presents a modeling study of the effects of differing emissions inventories on metrics of climate and air quality interest, namely, tropospheric ozone and hydroxyl radical (OH) burdens and the resulting methane lifetime. Based on two simulations performed by the EMAC model for two different phases of the Chemistry Climate Model Initiative (CCMI), each with its own prescribed emissions inventories, the authors observed significant differences in the metrics listed above and go on to evaluate the sectors (industrial, land transport, shipping, etc.) driving those differences using a tagging approach. Tropospheric ozone is more abundant in the simulation using more up-to-date emissions and methane lifetime is shorter in both hemispheres. Some budget closure calculations are also performed to understand the sectoral contributions for methane lifetime, and burden efficiency calculations are performed to understand the influence of nitrogen oxides (NOx) emissions changes specifically on ozone burden in a given sector.
Overall I find the presented analysis to be reasonably thorough for a model-focused study, well polished, and clear in its conclusions and methods. The findings are not “ground-breaking” but are instead, in my mind, an important contribution by quantifying and systematically seeking to understand a phenomenon that modeling groups often know is happening but is not always well characterized. By describing in detail the changes in tropospheric ozone, OH, and methane lifetime that might be expected from a routine update or switch of emissions inventories, the authors are assisting the modeling community and those seeking to constrain present-day and historical values of these quantities across models and through time. The authors are clear about the limitations of the study and also do a good job of citing past work and putting into context some of the specific changes in emissions sectors and species. I offer some minor comments for clarification, readability, and correction, but otherwise regard this manuscript as a strong candidate for publication in ACP.
Minor comments
L37: In this paragraph, sources of precursors are described but seem to me incomplete – first there’s anthropogenic NOx, then natural NOx. Then anthropogenic CO only, and natural NMHC only. Why not also include natural CO (biomass burning, to the degree it is natural, and from natural methane, I presume?), and anthropogenic NMHC (industry)?
L47: For this sentence, if the authors deem a citation helpful, Duncan et al., 2024 might be an appropriate reference, as it discusses the infeasibility of global observations of OH:
Duncan, B. N., et al.: Opinion: Beyond global means – novel space-based approaches to indirectly constrain the concentrations of and trends and variations in the tropospheric hydroxyl radical (OH), Atmos. Chem. Phys., 24, 13001–13023, https://doi.org/10.5194/acp-24-13001-2024, 2024.
L122: I’m not familiar with this phrase, “binary identical”. I don’t see how meteorology can be binary, but are met-dependent emissions binary, as in, either on or off? Please clarify or remove “binary”.
L150: For Figs. S6, S7, and S8, it would be helpful to include in legend that solid lines represent EMIS-01, dashed lines represent EMIS-02 instead of it being buried in one of the captions.
Technical corrections
L28: Not sure that citing Seinfeld and Pandis twice in this sentence is necessary; once at the end would convey the same attribution, in my mind.
L60: Should this state “CCMI-2022” rather than “CCMI-2”?
L74: “targeted” misspelled
L150: In Fig. S8, “anthropogenic” is misspelled in legend.
L151: 1010 should be 2010
L261: Remove “hemisphere,” redundant
L271: Fig. S12 y-axis label has misspelling of “efficiency”
L286: Fig. 4 y-axis label “efficiency” misspelled
L334: One of these EMIS-01’s should be an EMIS-02 I presume; directionality dependent on whether “CH4,” as stated, or “CH4 lifetime” is the quantity being compared.
L413: Both instances of “from EMIS-01 to EMIS-01” in this sentence should instead state “from EMIS-01 to EMIS-02” I believe
L433: remove one “that”
L452: “available” misspelled
Citation: https://doi.org/10.5194/egusphere-2025-294-RC2 -
AC1: 'Reply on RC2', Patrick Jöckel, 17 Jun 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-294/egusphere-2025-294-AC1-supplement.pdf
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AC1: 'Reply on RC2', Patrick Jöckel, 17 Jun 2025
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RC3: 'Comment on egusphere-2025-294 - Effects of different emission inventories on tropospheric ozone and methane lifetime by Acquah et al.', Anonymous Referee #3, 08 Apr 2025
This is a very nice paper that examines the response of some key climate variables to model input data from two versions of emissions from the Chemistry-Climate Model Intercomparison CCMI project. The authors use a well-established chemistry-climate model together with some innovative process-level outputs to investigate the response of tropospheric ozone, hydroxyl radical and methane lifetime to changes in emissions between two eras of CCMI.This work is significant for understanding both the sensitivity of models to evaluated emissions data and to begin to describe the source of intermodel diversity by defining model sensitivities. The study is well-designed and this paper fits well within the remit of ACP.
After a short introduction, Section1, Section 2 describes the study's Methods and Data. Section 2.1 describes the model in very short detail, and could be combined with section 2.2.1 which currently describes the components and other options chosen, as well as some of the emissions and with Section 2.2.2 which describes other emissions. Overall, I think the MS would be better if all the chemical species - methane, N2O, NOx and CO, BVOC etc- were discussed together in one section, and if L114-119 and L124-126 were moved up the MS. Similarly I think all of the text from L1-L20 of the Supplementary should be moved either to this section, or the Discussion. Section 2.2.3 describes the tagging methodology, and 2.3 the calculation of methane lifetime. In this section, and in the MS overall, I think the word category becomes rather laborious. Where the categories are emissions from a specific sector, it would be helpful, and the MS would be improved, if the word 'sector' was retained in favour of 'category', and the other non-emission tagging labels were called e.g. 'N2O decomposition processes' or something similar. (The authors in fact seem to prefer the word sector in their Conclusions section).
In section 2.3, on methane lifetime, the terminology used there might also be confusing to some readers - 'total' lifetime is often defined to include other loss processes, e.g. stratospheric loss, loss with Cl - so would it be better to define terms and specifying OH consistently and explicitly, e.g. L220 the term 'total lifetime', tau_CH4, OH_total, would be better as 'total OH lifetime'. Similarly for L201 tau_CH4,sum would appear to be tau_CH4,sum_OH.Section 3 presents the results. §3.1 highlights the change in the tropospheric ozone column between the two experiments. It would be interesting to know whether these changes bring the model into better or worse agreement with observational data on tropospheric ozone columns, if available. Consistent use of the labels from Table 2 and in this section would help ('N2O' category vs 'N2O decomposition' category). The discussion of the drivers of the ozone column changes would be improved by diagnosing the response of O3P and O3L budget terms, if available for these tagged experiments. Including a calculation of ozone production efficiency would allow comparisons with other studies. Additionally, supplementary plots of zonal mean emission changes (latitude vs altitude) could help explore how emission changes impact ozone distribution.
§3.2 discusses OH and shows the absolute-scale change in OH mole fraction (mol per mol) between the two experiments.The differences are plotted in terms of the changes in OH attributed to each of the tagging categories, with differences shown between EMIS-01 and 02. §3.2.2 discusses the methane lifetime. Figures 5 and 6 could be improved by plotting the CH4+OH-weighted OH, as discussed in Lawrence et al. (2001, [https://doi.org/10.5194/acp-1-37-2001](https://doi.org/10.5194/acp-1-37-2001)), to better understand the drivers of methane lifetime changes.
§3.3 serves as a synthesis section. Breaking this section into subsections—such as "What categories are generally important?" and "How does the importance of these categories change and why?"—would improve focus. Here the discussion becomes somewhat confusing in places, not least because,in the two experiments, some
'categories' involve a change in emissions and consequent change in chemistry, where the authors are easily able to connect the change in emissions to the observed change in ozone column, while in other places the tagging analysis is about processes only, e.g. lightning that has changed between the two experiments, and produced a change in O3. In the latter case, this could be described more fully to explain its impact on O3 columns or methane lifetime.The discussion section 4 on limitations and comparison with previous results could be folded into the discussion if the authors choose.
Conclusions are nicely written and add a lot of value.
Specific Comments
Figures
Figure 1: REFD1 should be capitalized in the caption. Additionally, I could not find a reference to Figure 1 in the text.
Figure 3 The labels of the RH colorbars are smaller than neighboring labels, making them difficult to read. The bottom-right panel appears incomplete.
Figure 6: The font size on the difference plot colorbar is inconsistent with neighboring labels.L105 could the authors add an explanation for their choice of labels (rather than keeping the CCMI-1 and CCMI-2022)?
L107 Clarify whether EMAC uses methane emissions or a boundary condition. If it’s the latter, consistent terminology (e.g., "lower boundary") should be used for both N₂O and CH₄ in §2.2.
L112 Reword 'The influence of the changed prescribed' to 'the influence of the change in the prescribed ODS'?
Table 2 caption needs consistent use of 'non-traffic'
L220 does 'in dependence' mean the dependence of delta tau_CH4,i on delta tau_CH4, OHi?
L254-L264 Reword "However, only for land..." to "The TRA and IND..."
L307 Sentences like "The shipping category also shows..." would benefit from discussing process-level changes (e.g., "In CCMI-1, the tagged OH from X category is larger than in CCMI-2022...").
L336 categories occurs twice in the same sentence
L397 show the increase, rather than show that the increase?
L413 EMIS-01 is repeated
L428 Use "sector" for aviation and biomass burning.
L436 biomass burning sector
L440 Replace "present day" with "recent historical."
L447 Regional tagging would be a valuable addition, enabling closer examination of regional responses.Citation: https://doi.org/10.5194/egusphere-2025-294-RC3 -
AC3: 'Reply on RC3', Patrick Jöckel, 17 Jun 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-294/egusphere-2025-294-AC3-supplement.pdf
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AC3: 'Reply on RC3', Patrick Jöckel, 17 Jun 2025
Data sets
Effects of different emission inventories on tropospheric ozone and methane lifetime, results of EMIS-01 simulation Catherine Acquah, Laura Stecher, Mariano Mertens, and Patrick Jöckel https://doi.org/10.5281/zenodo.14712801
Effects of different emission inventories on tropospheric ozone and methane lifetime, results of EMIS-02 simulation Catherine Acquah, Laura Stecher, Mariano Mertens, and Patrick Jöckel https://doi.org/10.5281/zenodo.14712939
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