the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 03 Apr 2024
Instantaneous intraday changes in key meteorological parameters as a proxy for the mixing ratio of BVOCs over vegetation under drought conditions
Abstract. Biogenic volatile organic compounds (BVOCs) exert a significant influence on photochemical air pollution and climate change, with their emissions strongly affected by meteorological conditions. However, the effect of drought on BVOC emissions is not well-characterized, limiting the predictive power of this feedback on climate change and air quality. This study hypothesized that under severe drought conditions, BVOC emissions will be more sensitive to instantaneous intraday variations in meteorological parameters than to the absolute values of those parameters. To test this hypothesis, we employed proton transfer reaction time-of-flight mass spectrometry to quantify the mixing ratios of a suite of soluble and insoluble VOCs, including isoprene, monoterpenes, sesquiterpenes, acetone, acetaldehyde, methanol, ethanol, formaldehyde, formic acid, acetic acid, 1,3-butadiene, dimethyl sulfide (DMS), and H2S, under severe drought conditions in a natural Eastern Mediterranean forest in autumn 2016. Except for H2S, which was used as a control, and to a certain extent DMS, all measured VOCs exhibited a strong response to changes in relative humidity, with lower mixing ratios observed around noon, suggesting inhibition of BVOC emission under the relatively high temperature and low relative humidity of drought conditions. Notably, our analysis revealed that instantaneous changes in meteorological conditions, especially in relative humidity, can serve as a better proxy for drought-related changes in BVOC emission rate than the absolute values of meteorological parameters. These findings are supported by direct flux measurements conducted in a mixed Mediterranean forest under drought conditions, in the same region, and presented as a companion article. The findings further highlight the importance of analyzing the effect of meteorological conditions on BVOC emissions under drought conditions on a daily—or shorter—timescale, and support biogenic emission sources for 1,3-butadiene.
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RC1: 'Comment on egusphere-2024-717', Anonymous Referee #1, 16 May 2024
The manuscript by Li et al. presents BVOC concentrations measured by PTR-TOF during six days in a natural Eastern Mediterranean forest (Beit Keshet Forest (Shibli) site) during autumn drought. The authors argue that instantaneous intraday changes in relative humidity can be used as a proxy for the mixing ratio of BVOCs over vegetation under drought conditions.
Thank you for giving me the opportunity to read this. The manuscript is rather well-written, but many of the figures are confusing. It’s clear that the intention was to measure not only the concentration of BVOCs, but also the ecosystem scale emission, but due to measurement problems that didn’t happen. Considering that you measured BVOCs with enclosure in your companion manuscript and that your argumentation and conclusions are basically the same in both manuscripts, one should consider if it is really justified to publish two separate papers or if they should rather be combined.
The main issue is that your entire manuscript is based on the assumption that BVOC mixing ratios can be used as a proxy for BVOC emissions. I do not think this is a valid assumption and your argumentation does not convince me. I do not think the assumption is valid based on what existing publications show, considering that some of the BVOCs you deal with have lifetimes in the scale of days to weeks and it is well known that some of the BVOCs you consider are not only emitted from vegetation, but also produced in the atmosphere and that production makes up a significant fraction of the total BVOC concentrations. Either you should just skip this entire assumption and be honest to say that you are just investigating how the different environmental factors correlate with the concentration of BVOCs, or then you need to do much more to convince the reader that your assumption is valid. You could refer to previous studies - preferably from the same region - which present both BVOC emission and concentration measurements which support your assumption. You could analyse if your measured BVOC mixing ratios depend on the daily behaviour of your measured ozone concentration, BLH (reanalysis, etc), and use your light measurements as some proxy for the concentration of OH. You could also have left out the BVOCs with long lifetimes from your analysis. You should also state that one reason why you only include day time measurements in the analysis is to avoid a larger fraction of the BLH effect.
Specific comments:
Page 2, L30-32: “Notably, our analysis revealed that instantaneous changes in meteorological conditions, especially in relative humidity, can serve as a better proxy for drought related changes in BVOC emission rate than the absolute values of meteorological parameters” - I think you can’t claim this - at least not in so strong words - because you did not measure the emission of BVOCs, only the concentration. Also, the word “reveal” is quite strong considering that you only have six days of measurements.
Sec 2.4: Firstly, I do not understand why you included MEGAN simulation output, because to my understanding you only use it for calculating the H value for MT in Table 2 and that is perhaps not super crucial. Secondly, why did you use MEGAN v2.1 when MEGAN v3 was published already 5 years ago? Do your BVOC emission simulations only include a drought stress algorithm for isoprene? Perhaps this would be good to spell out for the reader as some might think drought affects your simulations of the emission of all BVOCs. I think it’s good that you have chosen the minimalistic approach In Sec 2.4 and left out equations which can be found in other papers, but perhaps you could elaborate a bit on the Wang et al.’s PDS algorithm - like what are the parameters it includes and what is the main underlying idea of how drought impacts the BVOC emission. Most of your readers probably know MEGAN quite well, but perhaps less know the Wang algorithm and drought is the focus of your manuscript.
P9, L184 + Table 1: Since VOC emissions and concentrations are not comparable quantities, they should not be compared. I think it is fine enough that you include both emission estimates and concentration measurements in Table 1, but you should avoid using the word “compare” and you should change the column titles to emphasis that you are showing emission rates and concentrations in order to avoid readers believing that both columns show emission rates (for example, that’s what I thought you had when I first browsed the manuscript). For example, you could write “MEGAN simulated BVOC emission rates (mg m-2 h-1)” and “Measured BVOC mixing ratio (ppbv)”. You should also already here (in text and table) clarify for what time frame (24hr mean, 8:00-17:00 mean, …?) your values are. In general, the information that you only include daytime concentrations in your analysis comes very late and it’s also basically only obvious from the figures what is meant by “daytime”.
Figure 2: I don’t understand the figure. What do those 10 and 20% refer to? How large a fraction of the time the compound comes from the different wind directions? What’s the values in the boxes? Concentrations? Then I guess a unit is missing? What’s the values in the box for the “time” plot? To be more transparent and illustrative, you could consider instead to add the individual mixing ratio data points (or half hour averages) and let the circular lines represent the windspeed. Then the reader would have a better idea about if the VOCs you measure are more local or from far away.
L430-432: OK to how you calculated the H value for MT and SQT, but why didn’t you use a similar approach to calculate the OH and O3 rate coefficients?
Figure 6 and related text: Delta RH/ delta time has the highest association with the BVOC mixing ratios, except for with the concentration of sesquiterpenes. At the same time, only the concentration of sesquiterpenes is short-lived. Could the difference in lifetime (and hence source) be an explanation for this? It would also be interesting to see a wind rose plot for delta RH/delta time to see if the cause of the correlation is RH or wind direction.
I wonder if “proxy” is the correct word to use in this manuscript, because it gave me the expectation that you would also present an equation for estimating the concentration of BVOCs. So, for example in the title, would it be more fitting to say that instantaneous changes in meteorological conditions is a better indicator for changes in the concentration of BVOCs during drought than the absolute values of those parameters? Or something like that?
Technical corrections:
P10, L186-187: You should mention that you are referring to the measured concentrations, not the modelled emissions.
Table 2: Spell out DDSI and in general all abbreviations in tables and figures so one does not need to go dig the text to figure out what you show. In the text (L396-7) it says you didn’t include DOY306, but in the table caption it says you did.
Citation: https://doi.org/10.5194/egusphere-2024-717-RC1 - AC1: 'Reply on RC1', Eran Tas, 07 Aug 2024
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RC2: 'Comment on egusphere-2024-717', Anonymous Referee #2, 25 Jun 2024
The authors conducted field measurements of ambient VOC mixing ratios with a PTR-MS. They present results correlating those mixing ratios with various meteorological parameters, but this approach is fundamentally flawed. Mixing ratios are a function of emissions (source), boundary layer dynamics (dilution and transport), atmospheric chemistry (sink), and deposition (sink). They do not take any boundary layer dynamics or chemical processing into account. This can be accomplished with some supplementary modeling efforts that would help them make sense of this dataset. For example, the abstract states that "lower mixing ratios were observed around noon, suggesting inhibition of BVOC emission under the relatively high temperature and low relative humidity of drought conditions," but it is very typical for mixing ratios to decrease at the height of the day due to dilution in the growing boundary layer and increased photochemical loss processes! It doesn't necessarily tell you anything about the emissions. Furthermore, the data visualization was extremely difficult to interpret. I encourage the authors to think through what their main takeaway is for each figure and revise the visualization to more effectively communicate that message. They were generally too busy and appeared to be "first draft" figures without much synthesis. The manuscript was difficult to read, in part due to illogical organization. For example, they present some methods in the results section (e.g. DDSI calculations) and it is unclear what they mean by "emissions being more sensitive to intraday variation than to absolute values of met parameters." Can they provide more support for this idea? The abstract abruptly ends with a statement about biogenic sources of 1,3-butadiene that did not logically flow from any of the previous sentences. The authors should also be careful about using a PTR to quantitatively measure formaldehyde. This is very difficult to accomplish since formaldehyde has a proton affinity just slightly higher than water and therefore the back-reaction can (and does) occur. The formaldehyde sensitivity of the instrument is therefore a function of humidity. I didn't see any discussion of this in the manuscript, but apologies if I just missed it.
The dataset is interesting and valuable, but the authors need to take some more time making sense of it. Measurements of ambient mixing ratios are not the same as "emissions" or "fluxes" and the synthesis will require more supplemental modeling to get there.
Citation: https://doi.org/10.5194/egusphere-2024-717-RC2 -
AC2: 'Reply on RC2', Eran Tas, 07 Aug 2024
Publisher’s note: this comment is a copy of AC3 and its content was therefore removed.
Citation: https://doi.org/10.5194/egusphere-2024-717-AC2 - AC3: 'Reply on RC2', Eran Tas, 07 Aug 2024
-
AC2: 'Reply on RC2', Eran Tas, 07 Aug 2024
Status: closed
-
RC1: 'Comment on egusphere-2024-717', Anonymous Referee #1, 16 May 2024
The manuscript by Li et al. presents BVOC concentrations measured by PTR-TOF during six days in a natural Eastern Mediterranean forest (Beit Keshet Forest (Shibli) site) during autumn drought. The authors argue that instantaneous intraday changes in relative humidity can be used as a proxy for the mixing ratio of BVOCs over vegetation under drought conditions.
Thank you for giving me the opportunity to read this. The manuscript is rather well-written, but many of the figures are confusing. It’s clear that the intention was to measure not only the concentration of BVOCs, but also the ecosystem scale emission, but due to measurement problems that didn’t happen. Considering that you measured BVOCs with enclosure in your companion manuscript and that your argumentation and conclusions are basically the same in both manuscripts, one should consider if it is really justified to publish two separate papers or if they should rather be combined.
The main issue is that your entire manuscript is based on the assumption that BVOC mixing ratios can be used as a proxy for BVOC emissions. I do not think this is a valid assumption and your argumentation does not convince me. I do not think the assumption is valid based on what existing publications show, considering that some of the BVOCs you deal with have lifetimes in the scale of days to weeks and it is well known that some of the BVOCs you consider are not only emitted from vegetation, but also produced in the atmosphere and that production makes up a significant fraction of the total BVOC concentrations. Either you should just skip this entire assumption and be honest to say that you are just investigating how the different environmental factors correlate with the concentration of BVOCs, or then you need to do much more to convince the reader that your assumption is valid. You could refer to previous studies - preferably from the same region - which present both BVOC emission and concentration measurements which support your assumption. You could analyse if your measured BVOC mixing ratios depend on the daily behaviour of your measured ozone concentration, BLH (reanalysis, etc), and use your light measurements as some proxy for the concentration of OH. You could also have left out the BVOCs with long lifetimes from your analysis. You should also state that one reason why you only include day time measurements in the analysis is to avoid a larger fraction of the BLH effect.
Specific comments:
Page 2, L30-32: “Notably, our analysis revealed that instantaneous changes in meteorological conditions, especially in relative humidity, can serve as a better proxy for drought related changes in BVOC emission rate than the absolute values of meteorological parameters” - I think you can’t claim this - at least not in so strong words - because you did not measure the emission of BVOCs, only the concentration. Also, the word “reveal” is quite strong considering that you only have six days of measurements.
Sec 2.4: Firstly, I do not understand why you included MEGAN simulation output, because to my understanding you only use it for calculating the H value for MT in Table 2 and that is perhaps not super crucial. Secondly, why did you use MEGAN v2.1 when MEGAN v3 was published already 5 years ago? Do your BVOC emission simulations only include a drought stress algorithm for isoprene? Perhaps this would be good to spell out for the reader as some might think drought affects your simulations of the emission of all BVOCs. I think it’s good that you have chosen the minimalistic approach In Sec 2.4 and left out equations which can be found in other papers, but perhaps you could elaborate a bit on the Wang et al.’s PDS algorithm - like what are the parameters it includes and what is the main underlying idea of how drought impacts the BVOC emission. Most of your readers probably know MEGAN quite well, but perhaps less know the Wang algorithm and drought is the focus of your manuscript.
P9, L184 + Table 1: Since VOC emissions and concentrations are not comparable quantities, they should not be compared. I think it is fine enough that you include both emission estimates and concentration measurements in Table 1, but you should avoid using the word “compare” and you should change the column titles to emphasis that you are showing emission rates and concentrations in order to avoid readers believing that both columns show emission rates (for example, that’s what I thought you had when I first browsed the manuscript). For example, you could write “MEGAN simulated BVOC emission rates (mg m-2 h-1)” and “Measured BVOC mixing ratio (ppbv)”. You should also already here (in text and table) clarify for what time frame (24hr mean, 8:00-17:00 mean, …?) your values are. In general, the information that you only include daytime concentrations in your analysis comes very late and it’s also basically only obvious from the figures what is meant by “daytime”.
Figure 2: I don’t understand the figure. What do those 10 and 20% refer to? How large a fraction of the time the compound comes from the different wind directions? What’s the values in the boxes? Concentrations? Then I guess a unit is missing? What’s the values in the box for the “time” plot? To be more transparent and illustrative, you could consider instead to add the individual mixing ratio data points (or half hour averages) and let the circular lines represent the windspeed. Then the reader would have a better idea about if the VOCs you measure are more local or from far away.
L430-432: OK to how you calculated the H value for MT and SQT, but why didn’t you use a similar approach to calculate the OH and O3 rate coefficients?
Figure 6 and related text: Delta RH/ delta time has the highest association with the BVOC mixing ratios, except for with the concentration of sesquiterpenes. At the same time, only the concentration of sesquiterpenes is short-lived. Could the difference in lifetime (and hence source) be an explanation for this? It would also be interesting to see a wind rose plot for delta RH/delta time to see if the cause of the correlation is RH or wind direction.
I wonder if “proxy” is the correct word to use in this manuscript, because it gave me the expectation that you would also present an equation for estimating the concentration of BVOCs. So, for example in the title, would it be more fitting to say that instantaneous changes in meteorological conditions is a better indicator for changes in the concentration of BVOCs during drought than the absolute values of those parameters? Or something like that?
Technical corrections:
P10, L186-187: You should mention that you are referring to the measured concentrations, not the modelled emissions.
Table 2: Spell out DDSI and in general all abbreviations in tables and figures so one does not need to go dig the text to figure out what you show. In the text (L396-7) it says you didn’t include DOY306, but in the table caption it says you did.
Citation: https://doi.org/10.5194/egusphere-2024-717-RC1 - AC1: 'Reply on RC1', Eran Tas, 07 Aug 2024
-
RC2: 'Comment on egusphere-2024-717', Anonymous Referee #2, 25 Jun 2024
The authors conducted field measurements of ambient VOC mixing ratios with a PTR-MS. They present results correlating those mixing ratios with various meteorological parameters, but this approach is fundamentally flawed. Mixing ratios are a function of emissions (source), boundary layer dynamics (dilution and transport), atmospheric chemistry (sink), and deposition (sink). They do not take any boundary layer dynamics or chemical processing into account. This can be accomplished with some supplementary modeling efforts that would help them make sense of this dataset. For example, the abstract states that "lower mixing ratios were observed around noon, suggesting inhibition of BVOC emission under the relatively high temperature and low relative humidity of drought conditions," but it is very typical for mixing ratios to decrease at the height of the day due to dilution in the growing boundary layer and increased photochemical loss processes! It doesn't necessarily tell you anything about the emissions. Furthermore, the data visualization was extremely difficult to interpret. I encourage the authors to think through what their main takeaway is for each figure and revise the visualization to more effectively communicate that message. They were generally too busy and appeared to be "first draft" figures without much synthesis. The manuscript was difficult to read, in part due to illogical organization. For example, they present some methods in the results section (e.g. DDSI calculations) and it is unclear what they mean by "emissions being more sensitive to intraday variation than to absolute values of met parameters." Can they provide more support for this idea? The abstract abruptly ends with a statement about biogenic sources of 1,3-butadiene that did not logically flow from any of the previous sentences. The authors should also be careful about using a PTR to quantitatively measure formaldehyde. This is very difficult to accomplish since formaldehyde has a proton affinity just slightly higher than water and therefore the back-reaction can (and does) occur. The formaldehyde sensitivity of the instrument is therefore a function of humidity. I didn't see any discussion of this in the manuscript, but apologies if I just missed it.
The dataset is interesting and valuable, but the authors need to take some more time making sense of it. Measurements of ambient mixing ratios are not the same as "emissions" or "fluxes" and the synthesis will require more supplemental modeling to get there.
Citation: https://doi.org/10.5194/egusphere-2024-717-RC2 -
AC2: 'Reply on RC2', Eran Tas, 07 Aug 2024
Publisher’s note: this comment is a copy of AC3 and its content was therefore removed.
Citation: https://doi.org/10.5194/egusphere-2024-717-AC2 - AC3: 'Reply on RC2', Eran Tas, 07 Aug 2024
-
AC2: 'Reply on RC2', Eran Tas, 07 Aug 2024
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