Volatility of aerosol particles from NO<sub>3</sub> oxidation of various biogenic organic precursors

Graham, Emelie L.; Wu, Cheng; Bell, David M.; Bertrand, Amelie; Haslett, Sophie L.; Baltensperger, Urs; El Haddad, Imad; Krejci, Radovan; Riipinen, Ilona; Mohr, Claudia

doi:https://doi.org/10.5194/egusphere-2022-1043

Preprints

https://doi.org/10.5194/egusphere-2022-1043

Preprints

10 Oct 2022

| 10 Oct 2022

Volatility of aerosol particles from NO₃ oxidation of various biogenic organic precursors

Emelie L. Graham, Cheng Wu, David M. Bell, Amelie Bertrand, Sophie L. Haslett, Urs Baltensperger, Imad El Haddad, Radovan Krejci, Ilona Riipinen, and Claudia Mohr

Abstract. Secondary organic aerosol (SOA) is formed through the oxidation of volatile organic compounds (VOC), which can be of both natural and anthropogenic origin. While the hydroxyl radical (OH) and ozone (O₃) are the main atmospheric oxidants during the day, the nitrate radical (NO₃) becomes more important during the night time. Yet, atmospheric nitrate chemistry has received less attention compared to OH and O₃.

The Nitrate Aerosol and Volatility Experiment (NArVE) aimed to study the NO₃-induced SOA formation and evolution from three biogenic VOCs (BVOC), namely isoprene, α-pinene and β-caryophyllene. The volatility of aerosol particles was studied using isothermal evaporation chambers, temperature-dependent evaporation in a volatility tandem differential mobility analyzer (VTDMA), and thermal desorption in a filter inlet for gases and aerosols coupled to a chemical ionization mass spectrometer (FIGAERO-CIMS). Data from these three setups present a cohesive picture of the volatility of the SOA formed in the dark from the three biogenic precursors. Under our experimental conditions, the SOA formed from NO₃ + α-pinene was generally more volatile than SOA from α-pinene ozonolysis, while the NO₃ oxidation of isoprene produced similar, although slightly less volatile SOA than α-pinene under our experimental conditions. β-caryophyllene reactions with NO₃ resulted in the least volatile species.

Three different parametrizations for estimating the saturation vapor pressure of the oxidation products were tested for reproducing the observed evaporation in a kinetic modelling framework. Our results show that the SOA from nitrate oxidation of α-pinene or isoprene is dominated by low volatility organic compounds (LVOC) and semivolatile organic compounds (SVOC), while the corresponding SOA from β-caryophyllene consists primarily of extremely low volatility organic compounds (ELVOC) and LVOC. The parameterizations yielded variable results in terms of reproducing the observed evaporation, and generally the comparisons pointed to a need for re-evaluating the treatment of the nitrate group in such parameterizations. Strategies for improving the predictive power of the volatility parameterizations, particularly in relation to the contribution from the nitrate group, are discussed.

Received: 05 Oct 2022 – Discussion started: 10 Oct 2022

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.

Download & links

Preprint (PDF, 1936 KB)

Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
Preprint (1936 KB)

Supplement (1160 KB)

Download & links

The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.

Journal article(s) based on this preprint

05 Jul 2023

Volatility of aerosol particles from NO₃ oxidation of various biogenic organic precursors

Emelie L. Graham, Cheng Wu, David M. Bell, Amelie Bertrand, Sophie L. Haslett, Urs Baltensperger, Imad El Haddad, Radovan Krejci, Ilona Riipinen, and Claudia Mohr

Atmos. Chem. Phys., 23, 7347–7362, https://doi.org/10.5194/acp-23-7347-2023,https://doi.org/10.5194/acp-23-7347-2023, 2023

Short summary

Emelie L. Graham, Cheng Wu, David M. Bell, Amelie Bertrand, Sophie L. Haslett, Urs Baltensperger, Imad El Haddad, Radovan Krejci, Ilona Riipinen, and Claudia Mohr

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2022-1043', Gabriel Isaacman-VanWertz, 31 Oct 2022

The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-1043/egusphere-2022-1043-RC1-supplement.pdf

Citation: https://doi.org/10.5194/egusphere-2022-1043-RC1
- AC1: 'Reply on RC1', Emelie Graham, 16 Mar 2023
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-1043/egusphere-2022-1043-AC1-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2022-1043-AC1
RC2:
'Comment on egusphere-2022-1043', Anonymous Referee #2, 07 Nov 2022

General comments:

In this work, “Volatility of aerosol particles from NO3 oxidation of various biogenic organic precursors,” the authors examine analytically combining the use of different experimental setups, as a thermodenuder, an isothermal chamber and a FIGARO-CIMS system, formula-based parameterizations and an evaporation model in order to try to estimate volatility from the NO3 oxidation of a-pinene, isoprene and b-caryophyllene, a topic that is very understudied and scarce information exists about these volatility estimations. Volatility estimation is a topic that requires a lot of effort, the combination of different experimental and modeling techniques and sometimes the results about it can be failing or varied. This happens because of the complexity of the mechanisms of aging and reactions that happen in the atmosphere that makes the fate of the precursors highly uncertain. Also using modeling techniques there are many assumptions that have to be made in order to infer volatility that make the problem even more complex. The authors manage to use rigorously a combination of methods and finally provide us with a descriptive analysis of the volatility distributions and composition of SOA formed from nitrate oxidation for the three precursors. In the end the formula-based parameterizations were re-evaluated and showed that improvements in their description have to be incorporated in the future. I find this work very valuable and almost ready to be published while a few comments could be addressed a bit better and some technical corrections could be performed in order to be clearer.

Specific comments:

In Table 1 are presented the experiments performed for this work and while most of the results of them are presented experiment 4 is not used in the analysis. It is only referred to figure S2 when trying to show the sensitivity of different initial mass loadings from the nitrate oxidation of a-pinene. Is there any specific reason to not in the main figures as well? Also in the table there are many missing values, this could be explained in the bottom why is it happening as a footnote. Also while the nitrate experiments of a-pinene are 5, is there any reason there are 3 for isoprene and 2 for b-caryophyllene. Probably some description for the decision of the design of these experiments could be helpful in the main article. Finally for the isothermal evaporation experiments while most experiments finish at 240 min some stop after 150 min, this is probably because the experiment had to stop or there was equilibrium and no extra evaporation was noticed after that?

The evaporation model that is used for the analysis from Riipinen et al. (2010) depends on many parameters and some work has been done to investigate the sensititivity of them as it is done in Figure S3 where there is used a different value for the vaporization enthalpy of 70kJ/mol, different accommodation coefficients of 0.01 and 0.1 compared to unity of the base case as well as a mass-dependent diffusion coefficient. This analysis has been focused only on the ozonolysis of a-pinene though that is not the centre of interest in this work and in any case it showed to have better comparisons with the measurements. The b-caryophyllene nitrate oxidation products seem to have a more bimodal volatility distribution that make it more difficult to capture its “fingerprint” with the VFR in the thermodenuder and isothermal evaporation chamber, it could be probably fruitful to try to see for the three different parameterizations used how changing dHvap (with values of 70 kj/mol but also higher even 150 kj/mol), am (0.01 and 0.1) and mass-dependent diffusion coefficients would change these thermograms. This could be repeated for the isoprene case for a more broad and complete picture for the sensitivity to these parameters.

In Figure 3 the authors show the volatility distributions in the form of VBS as derived from the three different parameterizations that are examined, while someone can see the composition in ELVOCs, LVOCs and SVOCs it would be useful here to also add in the figure somewhere what is the average C* from each parameterization for each case of precursor. This would make it clearer understanding which parameterization shows higher or lower volatilities for each case.

Technical corrections:

Table 1: In footnote change S5 to S4 (there is no figure S5)

Line 227: Change 240 s to 240 min.

Line 228: model inputs instead of input

Line 229: Change concentrations estimated to concentration estimates to be clearer

Line 267: change to “agree with the VTDMA data”

Line 327: A bit complicated sentence, rewrite clearer

In Figure 4 I think the shading should change because right now it is not very easy and clear to see the differences, especially in the green shades.

Line 378 Change Though to Although

Line 387 something is missing, rewrite “and experimental approach developed by the authors”

Line 399: Change to “ an hydroxyl”

Line 408: Change to “ of the observations”

Line 450: Taken together, change the expression, suggest that the SOA … contain, rewrite a bit the sentence.

In Supplementary:

Figure S1: Change Narve, 2019 to NArVE campaign 2019 as it is mentioned in the article or This work

Figure S3: Change blue to cyan (you use cyan color)

Figure S3: Describe a,b,c,d,e,f in legend.

Citation: https://doi.org/10.5194/egusphere-2022-1043-RC2
- AC2: 'Reply on RC2', Emelie Graham, 16 Mar 2023
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-1043/egusphere-2022-1043-AC2-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2022-1043-AC2

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2022-1043', Gabriel Isaacman-VanWertz, 31 Oct 2022

The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-1043/egusphere-2022-1043-RC1-supplement.pdf

Citation: https://doi.org/10.5194/egusphere-2022-1043-RC1
- AC1: 'Reply on RC1', Emelie Graham, 16 Mar 2023
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-1043/egusphere-2022-1043-AC1-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2022-1043-AC1
RC2:
'Comment on egusphere-2022-1043', Anonymous Referee #2, 07 Nov 2022

General comments:

In this work, “Volatility of aerosol particles from NO3 oxidation of various biogenic organic precursors,” the authors examine analytically combining the use of different experimental setups, as a thermodenuder, an isothermal chamber and a FIGARO-CIMS system, formula-based parameterizations and an evaporation model in order to try to estimate volatility from the NO3 oxidation of a-pinene, isoprene and b-caryophyllene, a topic that is very understudied and scarce information exists about these volatility estimations. Volatility estimation is a topic that requires a lot of effort, the combination of different experimental and modeling techniques and sometimes the results about it can be failing or varied. This happens because of the complexity of the mechanisms of aging and reactions that happen in the atmosphere that makes the fate of the precursors highly uncertain. Also using modeling techniques there are many assumptions that have to be made in order to infer volatility that make the problem even more complex. The authors manage to use rigorously a combination of methods and finally provide us with a descriptive analysis of the volatility distributions and composition of SOA formed from nitrate oxidation for the three precursors. In the end the formula-based parameterizations were re-evaluated and showed that improvements in their description have to be incorporated in the future. I find this work very valuable and almost ready to be published while a few comments could be addressed a bit better and some technical corrections could be performed in order to be clearer.

Specific comments:

In Table 1 are presented the experiments performed for this work and while most of the results of them are presented experiment 4 is not used in the analysis. It is only referred to figure S2 when trying to show the sensitivity of different initial mass loadings from the nitrate oxidation of a-pinene. Is there any specific reason to not in the main figures as well? Also in the table there are many missing values, this could be explained in the bottom why is it happening as a footnote. Also while the nitrate experiments of a-pinene are 5, is there any reason there are 3 for isoprene and 2 for b-caryophyllene. Probably some description for the decision of the design of these experiments could be helpful in the main article. Finally for the isothermal evaporation experiments while most experiments finish at 240 min some stop after 150 min, this is probably because the experiment had to stop or there was equilibrium and no extra evaporation was noticed after that?

The evaporation model that is used for the analysis from Riipinen et al. (2010) depends on many parameters and some work has been done to investigate the sensititivity of them as it is done in Figure S3 where there is used a different value for the vaporization enthalpy of 70kJ/mol, different accommodation coefficients of 0.01 and 0.1 compared to unity of the base case as well as a mass-dependent diffusion coefficient. This analysis has been focused only on the ozonolysis of a-pinene though that is not the centre of interest in this work and in any case it showed to have better comparisons with the measurements. The b-caryophyllene nitrate oxidation products seem to have a more bimodal volatility distribution that make it more difficult to capture its “fingerprint” with the VFR in the thermodenuder and isothermal evaporation chamber, it could be probably fruitful to try to see for the three different parameterizations used how changing dHvap (with values of 70 kj/mol but also higher even 150 kj/mol), am (0.01 and 0.1) and mass-dependent diffusion coefficients would change these thermograms. This could be repeated for the isoprene case for a more broad and complete picture for the sensitivity to these parameters.

In Figure 3 the authors show the volatility distributions in the form of VBS as derived from the three different parameterizations that are examined, while someone can see the composition in ELVOCs, LVOCs and SVOCs it would be useful here to also add in the figure somewhere what is the average C* from each parameterization for each case of precursor. This would make it clearer understanding which parameterization shows higher or lower volatilities for each case.

Technical corrections:

Table 1: In footnote change S5 to S4 (there is no figure S5)

Line 227: Change 240 s to 240 min.

Line 228: model inputs instead of input

Line 229: Change concentrations estimated to concentration estimates to be clearer

Line 267: change to “agree with the VTDMA data”

Line 327: A bit complicated sentence, rewrite clearer

In Figure 4 I think the shading should change because right now it is not very easy and clear to see the differences, especially in the green shades.

Line 378 Change Though to Although

Line 387 something is missing, rewrite “and experimental approach developed by the authors”

Line 399: Change to “ an hydroxyl”

Line 408: Change to “ of the observations”

Line 450: Taken together, change the expression, suggest that the SOA … contain, rewrite a bit the sentence.

In Supplementary:

Figure S1: Change Narve, 2019 to NArVE campaign 2019 as it is mentioned in the article or This work

Figure S3: Change blue to cyan (you use cyan color)

Figure S3: Describe a,b,c,d,e,f in legend.

Citation: https://doi.org/10.5194/egusphere-2022-1043-RC2
- AC2: 'Reply on RC2', Emelie Graham, 16 Mar 2023
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-1043/egusphere-2022-1043-AC2-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2022-1043-AC2

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

AR by Emelie Graham on behalf of the Authors (28 Mar 2023) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (05 Apr 2023) by Thomas Berkemeier

RR by Gabriel Isaacman-VanWertz (17 Apr 2023)

Suggestions for revision or reasons for rejection

In their manuscript "Volatility of aerosol particles from NO3 oxidation of various biogenic
organic precursors", the authors present a revised discussion of volatility of observed products classified by molecular formula, comparing four volatility parameterizations and two volatility measurement approaches. This is a valuable contribution and is nearly ready for publication once an issue in the Daumit parameterization is addressed (see major comment 1).

I think the reviewers for their thoughtful responses and appreciate their detailed discussion of the C*-T_D relationship from FIGAERO, which I know has been the subject of a lot of work since I last dealt with it. I look forward to looking at their data to see what else we can learn.

Major comments:
(1) I am not convinced the implementation of the Daumit method is really correct. The assumption that the only source of DBE is carbonyl (and nitrate) is not necessarily correct, since rings add DBE and may be preserved in a-pinene and B-caryophyllene products. This is typical for the Daumit method, but the impact of rings should probably be mentioned explicitly, since a-pinene and B-cary products can very possibly have rings preserved. More importantly though, this issue can be dangerous given the equations as written. If there are other sources of DBE (e.g., rings), the number of carbonyls Eq. 6 will produce can actually return more carbonyls than there are functional groups. For example, the a-pinene product C10H14N2O8 (observed in this work as shown in Fig. AC3) is calculated to have 3 carbonyls (10-14/2-2/2+1 = 3), though in reality there are likely two only two non-nitrate other functional groups. (and probably a preserved ring). For other cases, for instance C7H9NO5 which GECKO-A predicts as a product, equation 6 estimates 3 carbonyls (7-9/2-1/2+1 = 3), again impossible as there are only two non-nitrate oxygens. Another example is C9H12O3, a GECKO-A predicted non-nitrate product that equation 6 estimates contains 5 carbonyls despite having only 3 oxygens. This issue probably applies to a minor fraction of formulas, but is probably present to some degree.

Part of the issue comes from the definition of n_carbonyl, which is defined here as DBE-n_NO3. For one thing, I don't think the double bond in the nitrate actually matters in terms of carbonyl groups because it doesn't come at the expense of two hydrogens on the arbon backbone like the carbonyl does (in other words, it is not giving us any information about double-bonded carbons, which is used to estimate carbonyl number). However, the nitrate group itself does come at the expense of a hydrogen, so it is more accurately considered as n_carbonyl = DBE = n_C-(n_H+n_N)/2+1. The end equation is actually the same, so maybe it doesn't matter, but I'm not sure it is actually correct as written. More importantly, though, is the excess DBE problem. I think you have to write it as n_carbonyl = min(n_C-(n_H+n_N)/2+1 , n_O-3*n_N). Basically, you can't have more carbonyls than you have functional groups. This issue is inherent in this formulation of the Daumit method, which was originally developed to estimate carbon number from AMS data. I think it has to be implemented in the form log c* = log a + b_0 + b_C*n_C + b_OH*n_OH + b_=O*n_=O + b_NO3*n_NO3. I'm not sure where that leaves you with Eq. 8, but this approach would still allow the authors to tune the b_NO3 as done in Table 2.

This change probably won't have significant influence on your figures or conclusions, but should be implemented prior to publication.

(2) The results in figure AC3 are very interesting. As the authors note in their reply, the impact of structure is of course quite important (trying to quantify it was in fact the main goal of Isaacman-VanWertz and Aumont), so it is interesting to see here. In particular, the C10H16N2O6 desorption temperatures are very different between the systems. The structures are of course quite different, since the isoprene structure must be a dimer, but it is nevertheless fascinating to see such a large difference, since the functional groups are probably very similar,so it is probably an interaction term that will be hard to capture. I look forward to exploring the data once posted!

Technical comments:
Line 59 is still not correct. Should be "there are many fewer", not there are "much fewer"

Line 154. Should be "Samples were" not "Samples was"

Line 363. I would clarify a little and say that "DMT leads to higher VFR than the observation *at long evaporation time*...", since until then it is basically on time of observations, more or less like MHR.

Line 427-428. This point about the C-O non-ideality is a very good one I think I had missed before. It is probably the reason for the difference in the Li modification between using the coefficient change (as used here) and the algorithmic conversion of NO3 to OH (as used in Isaacman-VanWertz and Aumont). The NO3 oxygen should almost certainly be excluded from the non-ideality as in the MHR equations. I agree it was not done in the Isaacman-VanWertz and Aumont discussion of this approach, but I'm not sure that was actually correct (and, as I mentioned, the paper figures actually use the funcational group conversion approach) and should maybe be corrected in this present work. The author's response to my comment about re-working the equation does make sense though; in fact, it makes it easier to correct the issue with the non-ideality.

Line 459. Should be "either" instead of "neither"

Line 497. The authors state an intention to make the data public, so data access should be described in the Data Availability statement

Hide

ED: Publish subject to minor revisions (review by editor) (17 Apr 2023) by Thomas Berkemeier

AR by Emelie Graham on behalf of the Authors (19 May 2023) Author's response Author's tracked changes

EF by Polina Shvedko (23 May 2023) Manuscript

ED: Publish as is (24 May 2023) by Thomas Berkemeier

AR by Emelie Graham on behalf of the Authors (30 May 2023)

Journal article(s) based on this preprint

05 Jul 2023

Volatility of aerosol particles from NO₃ oxidation of various biogenic organic precursors

Emelie L. Graham, Cheng Wu, David M. Bell, Amelie Bertrand, Sophie L. Haslett, Urs Baltensperger, Imad El Haddad, Radovan Krejci, Ilona Riipinen, and Claudia Mohr

Atmos. Chem. Phys., 23, 7347–7362, https://doi.org/10.5194/acp-23-7347-2023,https://doi.org/10.5194/acp-23-7347-2023, 2023

Short summary

Emelie L. Graham, Cheng Wu, David M. Bell, Amelie Bertrand, Sophie L. Haslett, Urs Baltensperger, Imad El Haddad, Radovan Krejci, Ilona Riipinen, and Claudia Mohr

Supplement

https://doi.org/10.5194/egusphere-2022-1043-supplement

Emelie L. Graham, Cheng Wu, David M. Bell, Amelie Bertrand, Sophie L. Haslett, Urs Baltensperger, Imad El Haddad, Radovan Krejci, Ilona Riipinen, and Claudia Mohr

Viewed

Total article views: 582 (including HTML, PDF, and XML)

HTML	PDF	XML	Total	Supplement	BibTeX	EndNote
394	172	16	582	61	4	19

HTML: 394
PDF: 172
XML: 16
Total: 582
Supplement: 61
BibTeX: 4
EndNote: 19

Views and downloads (calculated since 10 Oct 2022)

Month	HTML	PDF	XML	Total
Oct 2022	129	53	7	189
Nov 2022	81	32	3	116
Dec 2022	24	12	0	36
Jan 2023	25	10	0	35
Feb 2023	34	13	1	48
Mar 2023	36	16	4	56
Apr 2023	19	19	0	38
May 2023	20	10	0	30
Jun 2023	21	7	1	29
Jul 2023	5	0	5
Aug 2023	0
Sep 2023	0
Oct 2023	0
Nov 2023	0
Dec 2023	0
Jan 2024	0
Feb 2024	0
Mar 2024	0
Apr 2024	0
May 2024	0
Jun 2024	0
Jul 2024	0
Aug 2024	0
Sep 2024	0

Cumulative views and downloads (calculated since 10 Oct 2022)

Month	HTML	PDF	XML	Total
Oct 2022	129	53	7	189
Nov 2022	81	32	3	116
Dec 2022	24	12	0	36
Jan 2023	25	10	0	35
Feb 2023	34	13	1	48
Mar 2023	36	16	4	56
Apr 2023	19	19	0	38
May 2023	20	10	0	30
Jun 2023	21	7	1	29
Jul 2023	5	0	5
Aug 2023	0
Sep 2023	0
Oct 2023	0
Nov 2023	0
Dec 2023	0
Jan 2024	0
Feb 2024	0
Mar 2024	0
Apr 2024	0
May 2024	0
Jun 2024	0
Jul 2024	0
Aug 2024	0
Sep 2024	0

Viewed (geographical distribution)

Total article views: 566 (including HTML, PDF, and XML) Thereof 566 with geography defined and 0 with unknown origin.

Country	#	Views	%

Cited

Latest update: 19 Sep 2024

Download

The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.

Preprint (1936 KB)
Metadata XML

Short summary

The volatility of an aerosol particle is an important parameter for describing its atmospheric lifetime. We studied the volatility of secondary organic aerosols from nitrate initiated oxidation of three biogenic precursors with experimental methods and model simulations. We saw higher volatility than for the corresponding ozone system and our simulations produced variable results with different parameterizations which warrant for a re-evaluation of the treatment of the nitrate functional group.


Total:	0
HTML:	0
PDF:	0
XML:	0

Volatility of aerosol particles from NO3 oxidation of various biogenic organic precursors

Journal article(s) based on this preprint

Interactive discussion

Interactive discussion

Peer review completion

Suggestions for revision or reasons for rejection

Journal article(s) based on this preprint

Supplement

Viewed

Viewed (geographical distribution)

Cited

1 citations as recorded by crossref.

Volatility of aerosol particles from NO₃ oxidation of various biogenic organic precursors