Intra- and inter-annual changes in isoprene emission from central Amazonia

Gomes Alves, Eliane; Aquino Santana, Raoni; Quaresma Dias-Júnior, Cléo; Botía, Santiago; Taylor, Tyeen; Yáñez-Serrano, Ana Maria; Kesselmeier, Jürgen; Lembo Silveira de Assis, Pedro Ivo; Martins, Giordane; de Souza, Rodrigo; Duvoisin Júnior, Sérgio; Guenther, Alex; Gu, Dasa; Tsokankunku, Anywhere; Sörgel, Matthias; Nelson, Bruce; Pinto, Davieliton; Komiya, Shujiro; Martins Rosa, Diogo; Weber, Bettina; Barbosa, Cybelli; Robin, Michelle; Feeley, Kenneth J.; Duque, Alvaro; Londoño Lemos, Viviana; Contreras, Maria Paula; Idarraga, Alvaro; López A., Norberto; Husby, Chad; Jestrow, Brett

doi:https://doi.org/10.5194/egusphere-2023-168

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https://doi.org/10.5194/egusphere-2023-168

Preprints

22 Feb 2023

| 22 Feb 2023

Intra- and inter-annual changes in isoprene emission from central Amazonia

Eliane Gomes Alves, Raoni Aquino Santana, Cléo Quaresma Dias-Júnior, Santiago Botía, Tyeen Taylor, Ana Maria Yáñez-Serrano, Jürgen Kesselmeier, Pedro Ivo Lembo Silveira de Assis, Giordane Martins, Rodrigo de Souza, Sérgio Duvoisin Júnior, Alex Guenther, Dasa Gu, Anywhere Tsokankunku, Matthias Sörgel, Bruce Nelson, Davieliton Pinto, Shujiro Komiya, Diogo Martins Rosa, Bettina Weber, Cybelli Barbosa, Michelle Robin, Kenneth J. Feeley, Alvaro Duque, Viviana Londoño Lemos, Maria Paula Contreras, Alvaro Idarraga, Norberto López A., Chad Husby, and Brett Jestrow

Abstract. Isoprene is a chemical compound emitted naturally by soil, microorganisms, plants, and animals into the atmosphere. But plants are the largest emission source, and the amount of emission depends on plant species, weather conditions, and environmental conditions, including exposure to environmental stresses such as heat and drought. Isoprene is very reactive in the atmosphere and is involved in atmospheric physicochemical processes that can impact atmospheric chemistry, air quality, and regional climate. Quantification and understanding of the atmospheric processes influenced by isoprene result from a combination of observational experiments and estimates obtained from computational models. However, only a few long-term observational experiments have been conducted in the largest source of isoprene to the global atmosphere – the Amazon rainforest, and there are still uncertainties in the model estimates. Recent experiments have also shown that the models have greater uncertainty when estimating intra- and inter-annual variations in isoprene. This study aimed to improve our understanding of isoprene emission from a central Amazonian site by considering biological and environmental factors influencing emission on intra- and interannual time scales. By combining observational datasets, we adapted a widely used computational model of isoprene emission to observed conditions in the field. Our observations indicated that isoprene emission was not as high as the model estimated when the forest experienced environmental stress, such as heat and drought, in the 2015 El-niño year. In addition, observations revealed that the model performed well when diurnal variations were analyzed but not when long-term variations occurred. The performance for estimating intra- and inter-annual isoprene emission improved when the model was modified on two biological factors – (i) the amount of different leaf ages throughout the year and (ii) the emission rates of these different leaf ages. This shows that isoprene emission estimates can be improved when biological processes are mechanistically incorporated into the model.

How to cite. Gomes Alves, E., Aquino Santana, R., Quaresma Dias-Júnior, C., Botía, S., Taylor, T., Yáñez-Serrano, A. M., Kesselmeier, J., Lembo Silveira de Assis, P. I., Martins, G., de Souza, R., Duvoisin Júnior, S., Guenther, A., Gu, D., Tsokankunku, A., Sörgel, M., Nelson, B., Pinto, D., Komiya, S., Martins Rosa, D., Weber, B., Barbosa, C., Robin, M., Feeley, K. J., Duque, A., Londoño Lemos, V., Contreras, M. P., Idarraga, A., López A., N., Husby, C., and Jestrow, B.: Intra- and inter-annual changes in isoprene emission from central Amazonia, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-168, 2023.

Received: 03 Feb 2023 – Discussion started: 22 Feb 2023

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Journal article(s) based on this preprint

21 Jul 2023

Intra- and interannual changes in isoprene emission from central Amazonia

Eliane Gomes Alves, Raoni Aquino Santana, Cléo Quaresma Dias-Júnior, Santiago Botía, Tyeen Taylor, Ana Maria Yáñez-Serrano, Jürgen Kesselmeier, Efstratios Bourtsoukidis, Jonathan Williams, Pedro Ivo Lembo Silveira de Assis, Giordane Martins, Rodrigo de Souza, Sérgio Duvoisin Júnior, Alex Guenther, Dasa Gu, Anywhere Tsokankunku, Matthias Sörgel, Bruce Nelson, Davieliton Pinto, Shujiro Komiya, Diogo Martins Rosa, Bettina Weber, Cybelli Barbosa, Michelle Robin, Kenneth J. Feeley, Alvaro Duque, Viviana Londoño Lemos, Maria Paula Contreras, Alvaro Idarraga, Norberto López, Chad Husby, Brett Jestrow, and Iván Mauricio Cely Toro

Atmos. Chem. Phys., 23, 8149–8168, https://doi.org/10.5194/acp-23-8149-2023,https://doi.org/10.5194/acp-23-8149-2023, 2023

Short summary

Eliane Gomes Alves et al.

Interactive discussion

Status: closed

RC1: 'Comment on egusphere-2023-168', Anonymous Referee #2, 07 Mar 2023

Well-written paper showing isoprene concentration and flux (11 days) measurements with PTR-TOF-MS and its comparison to various MEGAN model runs at ATTO site, central Amazonia. Paper shows for the first time emission factors of isoprene which differs by tree species and age. That makes this contribution special. In addition, authors did multiple MEGAN model runs to show comparison of measured fluxes of isoprene by eddy covariance and MEGAN with and without those specific Es. Results show substantial improvement; however, an overestimation of MEGAN model still remains. Authors discuss that the reason, among other, might be an emission of "heavier" compounds instead of isoprene.
Paper reads well and goes directly to the point. Maybe in discussion there should be mention the uncertainty of isoprene emissions by eddy covariance itself. If isoprene would be measured with H3O+ primary ions (which reader unfortunately does not know), then 232MBO (2-methyl-3-buten-2-ol) goes to m/z 69.07 too. However, maybe authors did their measurement in NO+ mode. Or isoprene might be fragmented and therefore you measured lower fluxes. Anyway, it should be clarified in M&M part and discussed properly.

Here are more detailed remarks:
line 145: 2380 mm of precipitation is average from 2013-2019?
line 162: please indicate the exact version of PTRMS by Ionicon, primary ions used, E/N ratio, Td. Please indicate calibration here too. Was isoprene present in the cylinder? Although it is in Yãnez-Serrano et al. (2015), it should be mentioned here too. In addition, version of the instrument and primary ions used is not mentioned even in Yãnez-Serrano et al. (2015).
line 175: indicate frequency of anemometer
line 244: "was determined by laboratory analysis" - sounds odd
line 372: "Combretaceae" should be in italics too
fig 2: fig would benefit from making x and y axes descriptions bigger
line 448: what does mean "higher gross primary productivity (GPP) fluxes"? I think it should be without "fluxes"

Citation: https://doi.org/10.5194/egusphere-2023-168-RC1
RC2: 'Comment on egusphere-2023-168', Anonymous Referee #3, 08 May 2023

Overall, this paper presents some very interesting data about leaf age/phenology and its impacts on canopy isoprene emissions in an Amazonian rainforest. The seasonality of tropical isoprene emissions is complicated, with significant changes in the drivers of light and temperature. But there has been much speculation about other changes due to water status and leaf age. This study provides information about both whole-canopy phenology by camera and also leaf-level studies of both age and emission. The manuscript is overall well written and clear. The are only a moderate number of minor mistakes and the figures are visually effective.
In addition to some relatively minor points, my major concern is with the interpretation of the isoprene concentration data. Using canopy measurements of isoprene concentrations as a proxy for whole-canopy flux is always problematic and is particularly difficult given the micrometeorological complexity of a tropical rainforest canopy. Small differences in canopy height and ground topography can lead to tricky situations. Also, the high levels of total heat flux and the complicated dynamics around the Bowen ratio, (sensible/latent heat) make vertical mixing an important process for interpreting isoprene concentrations. My ‘major corrections’ comments are mainly focused on the simplistic interpretation of concentrations as a proxy for flux. While I do not believe that addresses these comments will lead to substantial changes in the manuscript, I am requesting major revisions due to the underlying scientific concern.
Major corrections

Lines 420-431: need to discuss and consider the impact of micrometeorology on the isoprene concentration profiles. The concentration profiles are a combination of emissions and mixing. During a dry year, the Bowen ratio shifts. There is less moisture available throughout the canopy, and more sensible heat flux is generated versus latent heat flux. More sensible heat leads to more intense vertical mixing. You should consider this effect and there may be ancillary data to test if there was increased vertical mixing.

Lines 438-440: Again, need to consider changes in micrometeorology, not just sources.

Lines 441-456: this entire section is very speculative and post hoc. Need to be much more cautious and give some caveats. Overall, you are trying to interpret observations instead of testing hypotheses.

Lines 613-617: again, you are ignoring the impact of vertical mixing. As discussed above, temperature, radiation and moisture availability all change vertical mixing and these factors also affect isoprene emissions. That means equating mixing ratios to fluxes is quite problematic.

Lines 685-686: again, this could be due to enhanced vertical mixing during the dry period.
Minor corrections

Line 148: select another term for “utmost”.

Lines 160-163: give the line inside/outside diameter and the flow rates. And state if there was a bypass flow for when the lines weren’t being sampled.

Line 173: 41 m is a relatively low sample height given a canopy height of 35 m. State why this inlet height was selected for the EC measurements.

Lines 197-199: what was the spatial arrangement of the transects? Where they all parallel?

Lines 471: Ontogeny refers to an organism. Phenology is the correct term for leaves, which are part of an organism and are cyclic.

Lines 477-483: you show the unscaled data in Figure 3 but describe the scaled data in the text. It would be nice to have a figure which shows the 36% reduction.

Line 533: “fractionated” select another term.

Lines 588-590: why use this procedure instead of simply finding adjust Es by 2.68 for S2? Then S3 would be 1 in line 592, correct?

Lines 624-634: Need to remove the monthly averaging: this is not a statistically sound approach. If you have a poor fit with your data, trying to average it away by temporal binning is incorrect. That’s why your p value is not improving. And that’s why only considering r2 isn’t a good idea. You reduced to four points. If you had gone to 2, you’d have a perfect r2!

Lines 655-673: work on this paragraph a bit. It has a strong beginning, but I am having trouble following the logic. The final two sentences are fine, but the logic in the middle is confusing and reasoning doesn’t connect to the final statement.

Lines 701-702: is this from the current study? Do you mean isoprene concentrations?

Line 1367 (Figure 6): for panel (d), the title says linear regression, but the fit is quadratic. Also, for panel (h), it’s the ratio of simulations to observations, not obs/MEGAN as stated.

Line 1393 (Figure 7): as mentioned above, remove panel (b)

Citation: https://doi.org/10.5194/egusphere-2023-168-RC2
AC1: 'Comment on egusphere-2023-168', Eliane Gomes Alves, 09 Jun 2023

Dear Editor,
I am here on behalf of all co-authors submitting the responses to the two reviewers that reviewed our manuscript.
I have combined all responses, including figures, in the .pdf file attached.
Best regards,
Eliane Gomes Alves

Citation: https://doi.org/10.5194/egusphere-2023-168-AC1

Interactive discussion

Status: closed

RC1: 'Comment on egusphere-2023-168', Anonymous Referee #2, 07 Mar 2023

Well-written paper showing isoprene concentration and flux (11 days) measurements with PTR-TOF-MS and its comparison to various MEGAN model runs at ATTO site, central Amazonia. Paper shows for the first time emission factors of isoprene which differs by tree species and age. That makes this contribution special. In addition, authors did multiple MEGAN model runs to show comparison of measured fluxes of isoprene by eddy covariance and MEGAN with and without those specific Es. Results show substantial improvement; however, an overestimation of MEGAN model still remains. Authors discuss that the reason, among other, might be an emission of "heavier" compounds instead of isoprene.
Paper reads well and goes directly to the point. Maybe in discussion there should be mention the uncertainty of isoprene emissions by eddy covariance itself. If isoprene would be measured with H3O+ primary ions (which reader unfortunately does not know), then 232MBO (2-methyl-3-buten-2-ol) goes to m/z 69.07 too. However, maybe authors did their measurement in NO+ mode. Or isoprene might be fragmented and therefore you measured lower fluxes. Anyway, it should be clarified in M&M part and discussed properly.

Here are more detailed remarks:
line 145: 2380 mm of precipitation is average from 2013-2019?
line 162: please indicate the exact version of PTRMS by Ionicon, primary ions used, E/N ratio, Td. Please indicate calibration here too. Was isoprene present in the cylinder? Although it is in Yãnez-Serrano et al. (2015), it should be mentioned here too. In addition, version of the instrument and primary ions used is not mentioned even in Yãnez-Serrano et al. (2015).
line 175: indicate frequency of anemometer
line 244: "was determined by laboratory analysis" - sounds odd
line 372: "Combretaceae" should be in italics too
fig 2: fig would benefit from making x and y axes descriptions bigger
line 448: what does mean "higher gross primary productivity (GPP) fluxes"? I think it should be without "fluxes"

Citation: https://doi.org/10.5194/egusphere-2023-168-RC1
RC2: 'Comment on egusphere-2023-168', Anonymous Referee #3, 08 May 2023

Overall, this paper presents some very interesting data about leaf age/phenology and its impacts on canopy isoprene emissions in an Amazonian rainforest. The seasonality of tropical isoprene emissions is complicated, with significant changes in the drivers of light and temperature. But there has been much speculation about other changes due to water status and leaf age. This study provides information about both whole-canopy phenology by camera and also leaf-level studies of both age and emission. The manuscript is overall well written and clear. The are only a moderate number of minor mistakes and the figures are visually effective.
In addition to some relatively minor points, my major concern is with the interpretation of the isoprene concentration data. Using canopy measurements of isoprene concentrations as a proxy for whole-canopy flux is always problematic and is particularly difficult given the micrometeorological complexity of a tropical rainforest canopy. Small differences in canopy height and ground topography can lead to tricky situations. Also, the high levels of total heat flux and the complicated dynamics around the Bowen ratio, (sensible/latent heat) make vertical mixing an important process for interpreting isoprene concentrations. My ‘major corrections’ comments are mainly focused on the simplistic interpretation of concentrations as a proxy for flux. While I do not believe that addresses these comments will lead to substantial changes in the manuscript, I am requesting major revisions due to the underlying scientific concern.
Major corrections

Lines 420-431: need to discuss and consider the impact of micrometeorology on the isoprene concentration profiles. The concentration profiles are a combination of emissions and mixing. During a dry year, the Bowen ratio shifts. There is less moisture available throughout the canopy, and more sensible heat flux is generated versus latent heat flux. More sensible heat leads to more intense vertical mixing. You should consider this effect and there may be ancillary data to test if there was increased vertical mixing.

Lines 438-440: Again, need to consider changes in micrometeorology, not just sources.

Lines 441-456: this entire section is very speculative and post hoc. Need to be much more cautious and give some caveats. Overall, you are trying to interpret observations instead of testing hypotheses.

Lines 613-617: again, you are ignoring the impact of vertical mixing. As discussed above, temperature, radiation and moisture availability all change vertical mixing and these factors also affect isoprene emissions. That means equating mixing ratios to fluxes is quite problematic.

Lines 685-686: again, this could be due to enhanced vertical mixing during the dry period.
Minor corrections

Line 148: select another term for “utmost”.

Lines 160-163: give the line inside/outside diameter and the flow rates. And state if there was a bypass flow for when the lines weren’t being sampled.

Line 173: 41 m is a relatively low sample height given a canopy height of 35 m. State why this inlet height was selected for the EC measurements.

Lines 197-199: what was the spatial arrangement of the transects? Where they all parallel?

Lines 471: Ontogeny refers to an organism. Phenology is the correct term for leaves, which are part of an organism and are cyclic.

Lines 477-483: you show the unscaled data in Figure 3 but describe the scaled data in the text. It would be nice to have a figure which shows the 36% reduction.

Line 533: “fractionated” select another term.

Lines 588-590: why use this procedure instead of simply finding adjust Es by 2.68 for S2? Then S3 would be 1 in line 592, correct?

Lines 624-634: Need to remove the monthly averaging: this is not a statistically sound approach. If you have a poor fit with your data, trying to average it away by temporal binning is incorrect. That’s why your p value is not improving. And that’s why only considering r2 isn’t a good idea. You reduced to four points. If you had gone to 2, you’d have a perfect r2!

Lines 655-673: work on this paragraph a bit. It has a strong beginning, but I am having trouble following the logic. The final two sentences are fine, but the logic in the middle is confusing and reasoning doesn’t connect to the final statement.

Lines 701-702: is this from the current study? Do you mean isoprene concentrations?

Line 1367 (Figure 6): for panel (d), the title says linear regression, but the fit is quadratic. Also, for panel (h), it’s the ratio of simulations to observations, not obs/MEGAN as stated.

Line 1393 (Figure 7): as mentioned above, remove panel (b)

Citation: https://doi.org/10.5194/egusphere-2023-168-RC2
AC1: 'Comment on egusphere-2023-168', Eliane Gomes Alves, 09 Jun 2023

Dear Editor,
I am here on behalf of all co-authors submitting the responses to the two reviewers that reviewed our manuscript.
I have combined all responses, including figures, in the .pdf file attached.
Best regards,
Eliane Gomes Alves

Citation: https://doi.org/10.5194/egusphere-2023-168-AC1

Peer review completion

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

AR by Eliane Gomes Alves on behalf of the Authors (12 Jun 2023) Author's response Author's tracked changes Manuscript

ED: Publish subject to technical corrections (16 Jun 2023) by Thomas Karl

AR by Eliane Gomes Alves on behalf of the Authors (19 Jun 2023) Manuscript

Journal article(s) based on this preprint

21 Jul 2023

Intra- and interannual changes in isoprene emission from central Amazonia

Atmos. Chem. Phys., 23, 8149–8168, https://doi.org/10.5194/acp-23-8149-2023,https://doi.org/10.5194/acp-23-8149-2023, 2023

Short summary

Eliane Gomes Alves et al.

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https://doi.org/10.5194/egusphere-2023-168-supplement

Eliane Gomes Alves et al.

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Short summary

Isoprene is emitted mainly by plants and can influence atmospheric chemistry and air quality. But, there are uncertainties in model emission estimates and follow-up atmospheric processes. In our study, with long-term observational datasets of isoprene and biological and environmental factors from central Amazonia, we show that isoprene emission estimates could be improved when biological processes were mechanistically incorporated into the model.


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