Short lifetimes of organic nitrates in a sub-urban temperate forest indicate efficient assimilation of reactive nitrogen by the biosphere

Andersen, Simone T.; Sander, Rolf; Dewald, Patrick; Wüst, Laura; Seubert, Tobias; Türk, Gunther N. T. E.; Schuladen, Jan; McGillen, Max R.; Xue, Chaoyang; Mellouki, Abdelwahid; Kukui, Alexandre; Michoud, Vincent; Cirtog, Manuela; Cazaunau, Mathieu; Bauville, Astrid; Bouzidi, Hichem; Formenti, Paola; Denjean, Cyrielle; Etienne, Jean-Claude; Garrouste, Olivier; Cantrell, Christopher; Lelieveld, Jos; Crowley, John N.

doi:https://doi.org/10.5194/egusphere-2024-3437

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https://doi.org/10.5194/egusphere-2024-3437

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12 Nov 2024

| 12 Nov 2024

Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).

Short lifetimes of organic nitrates in a sub-urban temperate forest indicate efficient assimilation of reactive nitrogen by the biosphere

Simone T. Andersen, Rolf Sander, Patrick Dewald, Laura Wüst, Tobias Seubert, Gunther N. T. E. Türk, Jan Schuladen, Max R. McGillen, Chaoyang Xue, Abdelwahid Mellouki, Alexandre Kukui, Vincent Michoud, Manuela Cirtog, Mathieu Cazaunau, Astrid Bauville, Hichem Bouzidi, Paola Formenti, Cyrielle Denjean, Jean-Claude Etienne, Olivier Garrouste, Christopher Cantrell, Jos Lelieveld, and John N. Crowley

Abstract. Alkyl nitrates (ANs) and peroxycarboxylic nitric anhydrides (PANs) are important reservoirs of reactive nitrogen that contribute significantly to the rate of formation and growth of secondary organic aerosols and support the transport of reactive nitrogen from polluted areas to remote areas. It is therefore critical to understand their sources and sinks in different environments. In this study we use measurements of OH, O₃, NO₃ reactivity, VOCs, ∑ANs and ∑PANs during the ACROSS campaign to investigate different production and loss processes of ANs and PANs in a temperate forest. At daytime OH-initiated processes were the dominant source of ANs (69–72 %) followed by NO₃ (18–20 %) and O₃ (8–12 %). At nighttime the contribution from OH decreased to 43–53 %, and NO₃ increased to 26–40 % with that of O₃ largely unchanged. Of the measured ∑PANs, 48–78 % was modelled to be peroxyacetic nitric anhydride (PAN). Physical loss (e.g. deposition) was an important sink for both ANs and PANs and contributed significantly to the very short lifetimes of 1.5 ± 1 h for ANs and 0.08–1.5 h for PANs observed during the campaign.

How to cite. Andersen, S. T., Sander, R., Dewald, P., Wüst, L., Seubert, T., Türk, G. N. T. E., Schuladen, J., McGillen, M. R., Xue, C., Mellouki, A., Kukui, A., Michoud, V., Cirtog, M., Cazaunau, M., Bauville, A., Bouzidi, H., Formenti, P., Denjean, C., Etienne, J.-C., Garrouste, O., Cantrell, C., Lelieveld, J., and Crowley, J. N.: Short lifetimes of organic nitrates in a sub-urban temperate forest indicate efficient assimilation of reactive nitrogen by the biosphere, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-3437, 2024.

Received: 04 Nov 2024 – Discussion started: 12 Nov 2024

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CC1:
'Comment on egusphere-2024-3437', Domenico Taraborrelli, 18 Nov 2024 reply

In this study the box model CAABA/MECCA has been used. Its chemical scheme includes the gas-phase oxidation of over 40 emitted VOCs including APINENE,

BPINENE, C3H8, C5H8, CH3CHO, CH4, LIMONENE, and NC4H10. The scheme considers the alkyl nitrate yields as a function of heavy atoms number, functional groups, temperature and pressure (Sander et al. 2019). The updates, corrections and additions to the mechanism in the version 4.7.0 have recently been presented by Wieser et al. (2024). The authors have not used this VOC oxidation mechanism. Instead they have used MCM v3.3.1. The latter has constant alkyl nitrate yields pre-calculated at 298K and and many oxidation pathways have not been updated in a while. Can the authors comment on why they chose MCM for the analysis?
References
Wieser, F., Sander, R., Cho, C., Fuchs, H., Hohaus, T., Novelli, A., Tillmann, R., and Taraborrelli, D.: Development of a multiphase chemical mechanism to improve secondary organic aerosol formation in CAABA/MECCA (version 4.7.0), Geosci. Model Dev., 17, 4311–4330, https://doi.org/10.5194/gmd-17-4311-2024, 2024.

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Citation: https://doi.org/10.5194/egusphere-2024-3437-CC1
- CC2:
  'Reply on CC1', Rolf Sander, 19 Nov 2024 reply
  
  We'd like to thank Domenico Taraborrelli for his comment. Indeed, the mechanism presented by Wieser et al. improves the modeling of alkyl nitrates. Unfortunately, however, the final version of the mechanism by Wieser et al. was not yet available when we performed the model simulations for our manuscript. In fact, merging the improved alkyl-nitrate chemistry into the main branch of the MECCA code is still work in progress.
  We think that using the MCM mechanism for our study is an adequate choice because we focus on PANs, not on alkyl nitrates. We don't expect any major changes for the PANs when upgrading to the new mechanism by Wieser et al.
  
  Reply
  
  Citation: https://doi.org/10.5194/egusphere-2024-3437-CC2
  - CC3: 'Reply on CC2', Domenico Taraborrelli, 20 Nov 2024 reply
    
    I would like to thank Rolf Sander for the prompt reply.
    He is right saying that the mechanism by Wieser et al. (2024) is not yet final and included in the main equation file of MECCA. Nevertheless, it is already available in the model version 4.7.0 and I think it would have as well been an adequate mechanism for the analysis presented in this manuscript. If the focus of the latter is really on PANs I would expect anyway some differences compared to the results with MCM. Indeed in an idealized setup Sander et al. (2019) has already shown that the default mechanism predicted about 25% less PAN than MCM. Part of the reason is surely a different set of rate constants and branching ratios for the reactions involving CH3CO3. I would not exclude even larger differences under different conditions.
    Another remark
    L379 - L384 The authors state that the reason for the model-observation discrepancy for XO2 is not known. Vereecken et al. (2021) has shown that many isomers of XO2s from the NO3-initiated oxidation of isoprene are produced and that a large portion cannot be detected by LIF systems. As also shown by Wieser et al. (2024), model-observations discrepancies for XO2 can be very large. However, in L509 - L516 the authors suggest that in the high precursor day their large model-observation discrepancy is not a measurement issue. Therefore, the new NO3-isoprene chemistry seems to have the potential for reducing the model-observation gap presented in Fig. S6 especially for the nighttime.
    References
    Vereecken, L., Carlsson, P., Novelli, A., Bernard, F., Brown, S., Cho, C., Crowley, J., Fuchs, H., Mellouki, W., Reimer, D., Shenolikar, J., Tillmann, R., Zhou, L., Kiendler-Scharr, A., and Wahner, A.: Theoretical and experimental study of peroxy and alkoxy radicals in the NO3-initiated oxidation of isoprene, Phys. Chem. Chem. Phys., 23, 5496–5515, https://doi.org/10.1039/D0CP06267G, 2021.
    
    Reply
    
    Citation: https://doi.org/10.5194/egusphere-2024-3437-CC3
RC1:
'Comment on egusphere-2024-3437', Anonymous Referee #1, 22 Nov 2024 reply

Summary
This paper reports new measurements of organic nitrate concentrations and reactivity, alongside box modelling, in order to constrain the lifetime of alkyl and peroxyalkyl nitrates. The analysis uses measurements made during the ACROSS campaign in 2022, at a tower sit in a Rambouillet forest, 50 km southwest of Paris, France. The major result is an apparently very short (deposition) lifetime for these organic nitrate species over the forest, due to their low observed concentrations. The modelling applied to interpret the data is rather complex. Because no speciated monoterpene data was available, different MT mixtures were tested, including a cutoff correction to treat the effect of (frequent) thermal inversion periods on the MT mixture. The complexity of the modelling made the analysis a bit difficult to follow and given the goal of determining lifetimes, I wonder if it could be made simpler / clearer. Of larger concern are the surprisingly high inferred contribution of OH to nitrate formation at night (when OH contributions are typically considered to be low), and the 4 x model overestimation of XO2 concentration relative to measurements. Could there be biases in these OH and XO2 measurements that skew this analysis substantially?
General Comments:
1) You use the term “peroxycarboxylic nitric anhydrides” throughout for PAN. I understand this is a correct IUPAC name, but I think “peroxyacetyl nitrate” is more commonly used in atmospheric chemistry community – might make your paper clearer understood (and more likely successfully searched for) if you use the latter name?
2) Section 3.1: You refer to the measurement site as a tower in a clearing, which to me sounds like no trees directly around the tower, but later it’s clear that your inlets are partly shaded (you mention the difference in photolysis rates if you were to use the above-clearing radiation measurements). Were they in the woods? Or are the trees so tall that even faraway trees shade your inlets for substantial parts of the day? I think a photo or diagram of the site might help here. And sometime when you talk about inside or outside the clearing, do you mean on the tower above the treetops? Some clarifying language could help here.
3) in line109 you introduce the variable k^NO3, and in line 117 you say you will henceforth refer to this as k^BVOC because BVOC losses are dominant. But later you introduce additional k’s to describe the losses to various oxidants, so it’s confusing to lose the oxidant here. Why not k^NO3+BVOC, to be completely clear?
4) around line 120: was O3 measured on the same inlet line? (the diagram of relevant sampling instrumentation would avoid readers wondering things like this)
5) Because your OH and XO2 results are so surprising, I think the descriptions of the OH and XO2 measurements in section 3.2.2. are key. Can you add some discussion of potential interferences or reasons for non-zero backgrounds? And explain how the XO2 is determined subtractively from the NO converted channel minus no NO channel, and what the associated uncertainties are. Is there any possibility of additional reactions between the conversion reactor and measurement? (diagram helpful here too)
6) around line 153, where you talk about the neglect of upwelling radiation which could cause an underestimate of 5-10%, it would be helpful to know a bit more what the canopy is like. (again, perhaps a diagram + photo figure would help here). How shaded is the container? Maybe add a plot comparing the top of tower radiation to that at the measurement container, and show the percentage difference over the daily cycle.
7) around line 165: At what height was the PTR-MS sampling? (again, diagram would help). Maybe discuss this in the context of your MT composition estimates – are you measuring at the same position as the reactivity or a different height, and might there be gradients?
8) around line 185: the limonene fraction sensitivity analysis is rather confusing. It’s not clear why the specific 3 mixtures are chosen, and in Figure 3B it doesn’t look like the fraction of limonene matters much. What matters is that most of the time, you actually use the delta-T cutoff and assume you don’t have any limonene at all in the reactivity mix. What motivated the choice of delta-T = 1 for the cutoff? This feels strangely arbitrary, and in figure 3 you see that the cutoff case seems to apply to most of the data. Why not just omit limonene altogether and make your discussion less complicated? Or at least, if the limonene does affect the low concentrations / daytime modelling, why present the 3 scenarios and not just your best estimate of the daytime vs. limonene fraction? This brings a lot of extra discussion that may confuse your main message.
9) towards the end of section 4.2: How did you partition XO2 into RO2 and HO2 to determine how to weight the RO2 / HO2 rate constants? Or you could just show the reaction as k_XO2 and explain how you estimated that aggregated rate constant.
10) In section 4.4 where you mention mixture 2 again, could just state the assumed mixture to avoid confusion (why 2?), and if you keep the delta-T threshold, remind the reader of how that works briefly here –e.g., “temperature inversions and resulting assumed removal of all limonene at the surface.” Also, somewhere early in this section say that you report all errors as +/- 1 sigma, and then don’t repeat it after every number. At line 333, you mention mixture 2 again – state that at the outset somewhere that it applies to all further analysis, so you don’t need to keep interrupting the text with it. Readability gets compromised by these repetitions, and mixture 2 could get confused with phase 2, etc.
11) The very high simulated OH contribution to PANs at night is quite surprising, so it would be good to see how else you can corroborate this. Does your box model reproduce the measured high nighttime OH concentration, with a reasonable assumption of OH recycling from the O3 reactions? (I assume that has to be where it’s coming from). Or could there have been some other (spurious?) local source of OH?
12) Lines 378 – 384: the 4 times higher modeled XO2 than measured is also shocking. It doesn’t seem satisfactory to just say the origin is not known and then use the higher modeled value. Can you look more into what the highest individual XO2 concentrations are in your model and try to figure out whether there could be some erroneous pathways or some that might not be relevant to your site?
13) Lines 480-483: Why do you bring up HPAN here and not when you introduce all the other reactions? Also, the use of an “arbitrary loss term” is not well justified. Why not just omit HPAN formation from the model, if they have never been observed and you have to make them go away with an arbitrarily high loss term to get things right?
14) Mid-page 13: You describe the differences in daytime vs. nighttime physical loss rates based on vertical mixing, but it sounds (here) like in your model you use one physical loss rate. At this point I’m wondering, why not account for the different daytime and nighttime loss rates by tuning them separately? But then on the top of p. 14 you describe separate lifetimes for daytime and nighttime. I’m a bit confused whether these refer to separately tuned parameters in a single model, or the optimized (full-diurnal-cycle) parameter in cases where you tune to match daytime or nighttime better. I suggest a careful edit of the last 3 paragraphs of this section (lines 484-527) to sharpen and clarify the description of what you did to obtain the day and night lifetime estimates. The table is a helpful addition, but the text is still a bit difficult.
15) Figure 5 now confuses me again about your MT scenarios. Limonene does not appear to be a fixed 20% of MTs during the day, when you are not switching off limonene. Is it 20% of emissions in your model, not concentration? You discussion made me think you had partitioned by concentration, but this looks like it contradicts that.
Minor/ technical corrections and suggestions:
Line 35: format both lifetimes the same, ie., either x +/-y, or xx – yy
Line 51: dependent, resulting in
Line 68-69: (SOA), thereby
Line 84: large variety of instruments were
At lines 105-106, you might already mention that no NO3 or N2O5 results were used in this study, because they were all below DL?
Line 124: suggest to mention briefly (even though you cite a reference) generally what NO measurements were corrected for.
Line 178: fractional contributions (a_i) from different monoterpenes as described in equation (2), where k_NO3+I is the rate coefficient
Line 238: Is NO3 photolysis to NO and O2 really an important atmospheric reaction?
Line 252: (eqn 3) error in superscript should be PNO3ANS
Line 282: missing “i” index under summation
Around line 296: I think it would be clearer if you laveled the fraction alpha^RO2+NOrather than just alpha^RO2
Line 344: daytime and nighttime from those
Line 392-393: MACR), methyl vinyl ketone (…, MVK), and a-pinene, after multiple
Line 397: In summertime forested environments, where
Line 408-410: For PAN, MPAN … depends on the concentration of NO, … XO2 designates the sum
Line 422: (R23) from 7.5 hours at 283 K to 40 minutes
Line 427: an important role, depending
Line 431: plots the measured mixing ratio for sumPANS (=PAN + MPAN + PPN + other PANs)
Line 434: campaign result in a …magnitude, from 15 hours at 279 K to 3 minutes at 314 K as shown in Figure 7B (i.e, remove the parenthetical)
Line 440-441: Figure 7), when measurements … available, have been modelled
Line 450-452: and the prescribed 20% limonene monoterpene mixture described above. Note that
Line 454: modelled day, 507 pptv
Line 460: frequencies thus determined were
Lines 534 and 535: There are 2 instances of using the word “reactant” where I think “VOC” would be true and more clear.
Figure 1: I think heat in a reaction scheme is typically indicated with a capital delta and not DELTA T. In the caption, what do you mean by OH formation in reactions of HO2 with OH? That reaction does not result in net OH formation.
Figure 2: Suggest to report NOx, isoprene and sum(MT) in ppbv rather than pptv. Also, could you put more of the traces on the same axes so that each individual plot is a bit taller and has a few more ticks on the y axis? For example, could combine sum MTs and isoprene on same panel, and perhaps NO2 and CH3CHO.
Figure 4: suggest to switch colors to red is hotter and blue cooler (more intuitive)
Figure 6 panels E and F: suggest to make y axis 0 – 1500 so you can see the measurements (even though this will push the without loss case offscale sooner – you’re not arguing that it’s a realistic case anyway, so it’s fine if it runs offscale.

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Citation: https://doi.org/10.5194/egusphere-2024-3437-RC1
- RC2: 'Reply on RC1', Anonymous Referee #1, 22 Nov 2024 reply
  
  Apologies, I somehow missed copying in the 2nd paragaph, this text should go just above General Comments:
  The results of this paper, showing rapid deposition of organic nitrates to a forest, are quite interesting and will be of strong interest to the nitrogen cycle community. I hope the authors can respond to the below comments and questions to help make the report clearer and clarify the limitations of the interpretation.
  
  Reply
  
  Citation: https://doi.org/10.5194/egusphere-2024-3437-RC2
RC3: 'Comment on egusphere-2024-3437', Anonymous Referee #2, 09 Dec 2024 reply

The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-3437/egusphere-2024-3437-RC3-supplement.pdf
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Citation: https://doi.org/10.5194/egusphere-2024-3437-RC3

Supplement

https://doi.org/10.5194/egusphere-2024-3437-supplement

Data sets

ACROSS_MPIC_RambForest_5ch-PNs-ANs_10min_L2 S. T. Andersen and J. N. Crowley https://doi.org/10.25326/706

ACROSS_MPIC_RambForest_5ch-NO2_1min_L2 S. T. Andersen and J. N. Crowley https://doi.org/10.25326/705

ACROSS_MPIC_RambForest_O3_10min_L1 J. N. Crowley https://doi.org/10.25326/707

ACROSS_CNRM_RambForest_MTO-1MIN_L2 C. Denjean https://doi.org/10.25326/437

ACROSS_MPIC_RambForest_ KNO3_10min_L2 P. Dewald and J. N. Crowley https://doi.org/10.25326/545

ACROSS_LPC2E_Rambforest_OH_L2 A. Kukui https://doi.org/10.25326/510

ACROSS_LPC2E_Rambforest_RO2_L2 A. Kukui https://doi.org/10.25326/509

ACROSS_2022_RambForest_LISA_PTRMS_VOCs_Belowcanopy_10min_20220617 - 20220723 V. Michoud et al. https://doi.org/10.25326/685

ACROSS_ICARE_RambForest_NO_L2 C. Xue et al. https://doi.org/10.25326/512

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Short summary

Measurements and modelling of reactive nitrogen gases observed in a suburban temperate forest in Rambouillet, France circa 50 km southwest of Paris in 2022 indicate that the biosphere rapidly scavenges organic nitrates of mixed biogenic and anthropogenic origin, resulting in short lifetimes for e.g. alkyl nitrates and peroxy nitrates.


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