Interaction Processes of Environment and Plant Ecophysiology with BVOC Emissions from Dominant Greening Trees

Round 1

Reviewer 1 Report

The paper "Interaction processes of environment and plant ecophysiology with BVOC emissions from dominant greening trees" by Duan et al., reports the influencing factors of BVOC emissions from six common plant species in the region of Xiamen, China. The authors sampled BVOC from 3 replicates of each species across urban, suburban and rural areas during two seasons. They measured environmental and ecophysiological factors and used a PA model to identify the direct and indirect factors influencing BVOC emissions. 

The information is relevant to the BVOC community as well as for greening urbanism and air pollution studies in China, therefore I recommend publication after some corrections have been addressed:

-abstract: I suggest to shorten the abstract and report only the main findings (for ex. lines 19-21 and 24-27 could be omitted). 

-introduction: 

L33: too vague, please report global fluxes and lifetimes.

L37-39: where was this increase registered and caused by what? It would be interesting to have more information about the greening activities in China in the introduction.

L 40: "and contribute" in place of "to"

L45: better "regulating" than "preventing"

L49: Kuhn and Kesselmeier studies could be cited here.

Methods:

L 83-85: Please indicate the average air T and RH for winter and summer, while the authors sampled VOCs

L 97: How many samples were collected as background values?

L 98: "Clear days" refers to less air pollution or more sunny days?

L 100-105: I suggest to represent the sampling technique with a figure or photos if any available. It is not clear how many samples and replicates the authors took for individuals, seasons, and tree species. Was the blank collected simultaneously? The sampling was conducted on one day or on several days continuously? How long was the branch kept inside the enclosure system before starting sampling?

L120: "standard" mass spectra means EI=-70 ev?

L124: How much was the volume?

L125: into an adsorption tube

L123-128: what was the material of the tube? Where were the standards purchased? Were the solutions stable or any isomerism between the monoterpenes was noticed?

L131-132: "concentration" instead of "mass"

L 132-133: "of" instead of "for"

L 135-136: Please describe briefly the Model G93 equations.

L 165-181: please give more details and describe the acronyms used (PA, CMIN, DF..)

Results:

3.1& 3.2 : I find this part valuable. It would be interesting to organize the section into : seasonal differences , differences among sample replicates and tree replicates (was there any trend spotted between urban, suburban and rural species?), differences between broadleaf & needle. Please include on top of each bar the number of sample replicates, ER mean and SE. 

3.3& 3.4: R2= 0.32 and numbers below are too low values for describing a relationship between factors as a correlation. All the values reported in this section are quite weak, and if not really useful for the PA model, would be good to move the entire section to the supplementary information. I wonder why these values are so weak though, is that happening for both isoprene and monoterpenes ER? I would expect to see a stronger correlation between isoprene ER with PAR and T. 

3.5: here it is important to know what was used from the previous section for the PA model. I find figure 5 and the color coding helpful to follow the text in 3.5 but still a bit confusing. Can the authors improve somehow this figure? Maybe with the help of a table or by improving the schematic of figure 6. 

Supplement:

Table A1: There could be a typing or formatting error in the PAR unit and the headings in this table seem shifted to the right

L 548-549: the reported LOD of the GC-MS is quite a broad range, is it possible to distinguish the LOD for the different species and/or report only the values above the LOD in the tables?

  

Author Response

Thank you very much for reviewing our manuscript (forests-2191119 entitled "Interaction processes of environment and plant ecophysiology with BVOC emissions from dominant greening trees"). Your comments are very constructive and valuable. We have studied the comments carefully and tried our best to revise the manuscript according your recommendations. The point-by-point responses to all the comments are listed as follows.

The paper "Interaction processes of environment and plant ecophysiology with BVOC emissions from dominant greening trees" by Duan et al., reports the influencing factors of BVOC emissions from six common plant species in the region of Xiamen, China. The authors sampled BVOC from 3 replicates of each species across urban, suburban and rural areas during two seasons. They measured environmental and ecophysiological factors and used a PA model to identify the direct and indirect factors influencing BVOC emissions.

The information is relevant to the BVOC community as well as for greening urbanism and air pollution studies in China, therefore I recommend publication after some corrections have been addressed.

1. Abstract: I suggest to shorten the abstract and report only the main findings (for ex. lines 19-21 and 24-27 could be omitted).

Response: Thank you for your suggestion. We have deleted the lines 19-21 and 24-27 to shorten the abstract and report only the main findings.

-introduction:

2. L33: too vague, please report global fluxes and lifetimes.

Response: Thank you for the reminder. The sentence in line 33 has been revised to “Isoprene (C₅H₈) and monoterpenes (C₁₀H₁₆) are significant BVOCs with global fluxes of 299.1-440.5 Tg C yr^-1 and 63.2-82.7 Tg C yr^-1 and exhibit high reactivity with the atmospheric chemical lifetimes of minutes to hours”. And we have added some relevant references.

3. L37-39: where was this increase registered and caused by what? It would be interesting to have more information about the greening activities in China in the introduction.

Response: Thank you for your careful attention. Recent satellite data (2000-2017) reveal a greening pattern that is strikingly prominent in China and India, and human land-use is a dominant driver of Greening Earth. We have supplemented the main areas and the reason for global greening in line 41-42: “which was strikingly prominent in China and India driven by land-use management”. In addition, we have added more information about the greening activities in China in line 42-44: “In China, forest area increased by 19% in a single decade due to the implementation of several programs to protect and expand forests, and it contributed 42% to the increase in leaf area”.

4. L40: "and contribute" in place of "to".

Response: Thank you for your suggestion. We have used “and contributes” in place of “to contribute” in line 40.

5. L45: better "regulating" than "preventing"

Response: Thank you for your suggestion. We have used “regulating” in place of “preventing” in line 45.

6. L49: Kuhn and Kesselmeier studies could be cited here.

Response: Thank you for the reminder. We have took a good look at Kuhn and Kesselmeier studies. And we have added relevant references published by Kuhn and Kesselmeier, such as “Significant light and temperature dependent monoterpene emissions from European beech (Fagus sylvatica L.) and their potential impact on the European volatile organic compound budget”, “Coupling isoprene and monoterpene emissions from Amazonian tree species with physiological and environmental parameters using a neural network approach”.

Methods:

7. L83-85: Please indicate the average air T and RH for winter and summer, while the authors sampled VOCs.

Response: Thank you for your careful attention. According to Xiamen weather station data, the average air temperature (Tair) and relative air humidity (RH) were 16 ℃ and 72% in December 2020 (winter), and 28 ℃ and 85% in June 2021 (summer). We have indicated the Tair and RH for winter and summer in line 91-93 in the revised manuscript: “In Xiamen, the average air temperature (Tair) and relative air humidity (RH) were 16 ℃ and 72% in December 2020 (winter), and 28 ℃ and 85% in June 2021 (summer).”

8. L97: How many samples were collected as background values?

Response: Thank you for your careful attention. In our study, the sample number as background values is 48: 8 (tree species) * 3 (gradients of urbanization) * 2 (seasons).

9. L98: "Clear days" refers to less air pollution or more sunny days?

Response: Thank you for the reminder. "Clear days" refers to more sunny days. To better articulate, "clear days" in line 98 has been revised to “sunny days”.

10. L100-105: I suggest to represent the sampling technique with a figure or photos if any available. It is not clear how many samples and replicates the authors took for individuals, seasons, and tree species. Was the blank collected simultaneously? The sampling was conducted on one day or on several days continuously? How long was the branch kept inside the enclosure system before starting sampling?

Response: Thank you for your suggestion. We have added “Figure A2. Schematic diagram of the dynamic enclosure system used for BVOC sampling” to represent the sampling technique.

Our study measured 8 tree species in 3 gradient of urbanization in 2 seasons and 3 replicates of each tree from each region, so the total sample size was 144. And we have added the number of sample replicates in figure 1, figure 2 and figure 3 to make it clearer.

The blank was collected simultaneously. We simultaneously used 4 sets of the dynamic enclosure systems to collect BVOCs emitted by a certain tree species in a certain urbanized area in a certain season, among which 3 sets were used as repetitions and 1 set was used to collect background value.

The sampling was conducted on several days. The sampling was carried out over a period of 8 days in December 2020 (winter), and 8 days in June 2021 (summer). We have provided the sampling data in Table A1.

After the sampling bag filled with clean air, an air sampler pump, drying tube, ozone scrubber, Teflon bag, and adsorption tube were sequentially connected via Teflon tubes to establish an enclosure system to collect BVOCs. Usually, when the VOCs in the sampling bag are collected several times, the stabilization time needs to be made in order to minimize the environmental variations within the sampling bag. In our experiment, although each branch was sampled only once, the stabilization time is worth considering. In further experiments, we do consider the stabilization time.

 

Figure A2. Schematic diagram of the dynamic enclosure system used for BVOC sampling.

11. L120: "standard" mass spectra means EI=-70 ev?

Response: Thank you for your careful attention. In the NIST 8 library, standard mass spectra means EI=70 eV.

12. L124: How much was the volume?

Response: Thank you for your careful attention. The injection volumes of standard mixtures were 1 μl, 2 μl, 3μl, 4μl, 5μl, and 6μl in order to product 6 levels.

13. L125: into an adsorption tube.

Response: Thank you for the reminder. We have revised “into adsorption tube” to “into an adsorption tube”.

14. L123-128: what was the material of the tube? Where were the standards purchased? Were the solutions stable or any isomerism between the monoterpenes was noticed?

Response: Thank you for your careful attention. The adsorption tube contains of Tenax GR and Carbopack B. We have mentioned the material of the adsorption tube in line 111 in the revised manuscript: “adsorption tube containing Tenax GR and Carbopack B”.

The standards were purchased from J&K Scientific (www.jkchemical.com/). And we have the AccuStandard certificate of analysis for the purchased standards.

The solutions were stored at low temperature and away from light, and they were stable. In our study, we measured 7 isomers of monoterpenes (C₁₀H₁₆), including α-pinene (7785-26-4), β-myrcene (123-35-3), β-pinene (18172-67-3), 3-carene (498-15-7), α-terpinene (99-86-5), d-limonene (5989-27-5), and γ-terpinene (99-85-4). To identify the 8 isomers of monoterpenes in the standard mixture, we measured the standard of each monoterpene by TD-GC-MS to determine the retention time.

 

15. L131-132: "concentration" instead of "mass".

Response: Thank you for the reminder. We have revised “mass” in line 131-132 to "concentration".

16. L132-133: "of" instead of "for".

Response: Thank you for the reminder. We have revised “for” in line 132-133 to "of".

17. L135-136: Please describe briefly the Model G93 equations.

Response: Thank you for your suggestion. We have added the description on the Model G93 equations in line 144-147 in the revised manuscript: “In Model G93, the emission of isoprene was calculated by multiplying a standard isoprene emission factor with functions of a temperature dependence and a light dependence. Monoterpene emission rates were calculated by multiplying a standard emission factor with an exponential function depending only on temperature.”

18. L165-181: please give more details and describe the acronyms used (PA, CMIN, DF.).

Response: Thank you for your suggestion. “PA” is the acronym of “path analysis”, which was described in line 60 in the revised manuscript. CMIN/DF refers to chi-square/degrees of freedom, which has been described in line 179-180 in the revised manuscript: “CMIN/DF (chi-square/degrees of freedom)”.

Results:

19. 1&3.2: I find this part valuable. It would be interesting to organize the section into: seasonal differences, differences among sample replicates and tree replicates (was there any trend spotted between urban, suburban and rural species?), differences between broadleaf & needle. Please include on top of each bar the number of sample replicates, ER mean and SE.

Response: Thank you for your suggestion. The sectors of 3.1 and 3.2 have been revised to “3.1. Seasonal variations in isoprene and monoterpene emission rates”, “3.2. Differences of isoprene and monoterpene emissions in urban, suburban and rural” and “3.3. Differences of isoprene and monoterpene emissions between broadleaf and needle”. And we have added “Figure 1. Seasonal patterns of the isoprene (A) and monoterpene (B) emission rates.”, “Figure 2. Isoprene (A) and monoterpene (B) emission rates of dominant greening plants in urban, suburban and rural regions.” and “Figure 3. Emission rates of isoprene (A) and monoterpenes (B) of broadleaf and needle.”. The figures include the number of sample replicates, ER mean and SE.

 

Figure 1. Seasonal patterns of the isoprene (A) and monoterpene (B) emission rates. The data are the mean±SE of 24 replicates. The different lowercase letters denote significant differences of BVOC emission rates in between winter and summer at p˂0.05 level.

 

Figure 2. Isoprene (A) and monoterpene (B) emission rates of dominant greening plants in urban, suburban and rural regions. The data are the mean±SE of 8 replicates. The different capital letters denote significant differences between winter and summer at p˂0.05. The different lowercase letters denote significant differences in urban, suburban and rural (p˂0.05).

 

Figure 3. Emission rates of isoprene (A) and monoterpenes (B) of broadleaf and needle. The data are the mean±SE. The replicates are 36 for broadleaf and 12 for needle. The different lowercase letters denote significant differences of BVOC emission rates between broadleaf and needle at p˂0.05 level.

20. 3&3.4: R2= 0.32 and numbers below are too low values for describing a relationship between factors as a correlation. All the values reported in this section are quite weak, and if not really useful for the PA model, would be good to move the entire section to the supplementary information. I wonder why these values are so weak though, is that happening for both isoprene and monoterpenes ER? I would expect to see a stronger correlation between isoprene ER with PAR and T.

Response: Thank you for your careful attention. The figures in sectors of 3.3 and 3.4 have been moved to the supplementary information. And we have deleted “3.3. Relationship between the BVOC emissions and environmental factors” and “3.4. Correlation between the BVOC emissions and plant ecophysiology” in the results. The causal relationships in PA model were based on regression coefficients and scientific findings. We have rewritten the relationship of BVOC emissions with environmental factors and plant ecophysiology, and state only what is useful to the PA model in sector “3.4. PA model of environment-plant ecophysiology-BVOC emissions interaction” in the revised manuscript.

The isoprene emission rates of broad-leaved trees were not strongly related to environ-mental factors, while closely related to plant physiological parameters. The isoprene emission rates of broad-leaved trees exhibited positive linear correlations with Pn, Tr and Gs (p˂0.05), and the regression coefficients were 0.43, 0.41 and 0.39 in winter respectively. As the results of PA model, the isoprene emission rate depended on photosynthesis directly, and PAR and Tair indirectly determined the isoprene emission rate by influencing the plant photosynthetic parameters. The monoterpene emission rates of needle-leaved trees exhibited positive correlations with PAR (R²=0.32, p˂0.05) and Tair (R²=0.25, p˂0.05), while they were not strongly related to plant ecophysiological parameters.

For some emitters with high isoprene, the isoprene emission rates have strong correlations with PAR and Tair. For example, the isoprene emission rates of C. equisetifolia exhibited positive correlations with PAR (R²=0.38, p˂0.05) and Tair (R²=0.66, p˂0.05).

21. 5: here it is important to know what was used from the previous section for the PA model. I find figure 5 and the color coding helpful to follow the text in 3.5 but still a bit confusing. Can the authors improve somehow this figure? Maybe with the help of a table or by improving the schematic of figure 6.

Response: Thank you for the reminder. We established the pathways of PA model based on the Pearson’s correlations between the factors, and the causal relationships based on the regression coefficients and scientific findings. We have stated what was used from the previous section for the PA model in line 345-347 in the revised manuscript.

We have improved “Figure 5. Pearson’s correlations among the isoprene and monoterpene emission rates and the environmental factors and plant ecophysiology” to make it clearer and more beautiful.

And, we have added “Table A2. Standard effects of environmental factors and plant ecophysiology on the emission rates of isoprene and monoterpenes in the PA model” to make the results of Figure 6 more legible and accessible.

 

Figure 5. Pearson’s correlations among the isoprene and monoterpene emission rates and the environmental factors and plant ecophysiology. * is significant at p˂0.05; ** is significant at p˂0.01.

Supplement:

22. Table A1: There could be a typing or formatting error in the PAR unit and the headings in this table seem shifted to the right.

Response: Thank you for the reminder. The PAR unit should be “umol m^-2 s^-1”. We have revised the PAR unit and the headings in Table A1.

23. L 548-549: the reported LOD of the GC-MS is quite a broad range, is it possible to distinguish the LOD for the different species and/or report only the values above the LOD in the tables?

Response: Thank you for your careful attention. The GC-MS (QP2010, Shimadzu, Japan) can detect VOCs at ppb-ppt levels. In the table, monoterpene emission rates were calculated according to the equation: E=(M-M0)/mt, where E (μg g^-1 h^-1) is the BVOC emission rate, M (μg) is the BVOC concentration contained in the adsorption tube of the sampled branch, M0 (μg) is the BVOC concentration contained in the adsorption tube of the blank sample, m (g) is the dry weight of leaves in the sampling bag, and t (h) is the sampling time. M and M0 were determined by GC-MS.

Reviewer 2 Report

The innovation of this research is that it uses the PA model to quantify the interactions among environmental, plant ecophysiology, and BVOC emissions from emitters. I believe that this strategy is a meaningful and appropriate approach. However, there are two major issues in this research and I recommend a major revision. 

The first issue is the inappropriate selection of data. To analyze the BVOC emission characteristics, it should not include data of non-emitters or low-emitters of isoprene and monoterpenes. The result of the emission characteristics including such plants is very difficult to interpret.

The second issue is the difference between the observed values measured by LI-6400XT using leaves near the Teflon bag and the actual environment inside the Teflon bag. In the case of the closed-loop system, the humidity inside the bag would increase significantly during the 45-minute period by transpiration. In addition, it is better to use the actual leaf surface temperatures in the bag for analysis rather than the outside air temperature. In Table A3, the monoterpene emission rates in this study are significantly lower than in previous studies. The relationship between RH and monoterpene emission rate in Figure A4 shows almost no emissions at RH above 50%. The monoterpene emission rates may be greatly underestimated by the high humidity inside the bags. In my opinion, an analysis focused on data from plants with strong isoprene emitters may yield more reliable results.

 

The following are specific comments.

 

Line 1: It may be better to include “PA analysis” in the title or keywords.

 

Line 98: I wonder why there were many days with low PAR in Table A1 even though it is described that it were all clear days in the main text? Why were there few high PAR data in Figure A2 and Figure A3?

 

Line 100: How did you insert the leaves in the bag without causing injury effects on it?

Author Response

Thank you very much for reviewing our manuscript (forests-2191119 entitled "Interaction processes of environment and plant ecophysiology with BVOC emissions from dominant greening trees"). Your comments are very constructive and valuable. We have studied the comments carefully and tried our best to revise the manuscript according your recommendations. The point-by-point responses to all the comments are listed as follows.

The innovation of this research is that it uses the PA model to quantify the interactions among environmental, plant ecophysiology, and BVOC emissions from emitters. I believe that this strategy is a meaningful and appropriate approach. However, there are two major issues in this research and I recommend a major revision.

1. The first issue is the inappropriate selection of data. To analyze the BVOC emission characteristics, it should not include data of non-emitters or low-emitters of isoprene and monoterpenes. The result of the emission characteristics including such plants is very difficult to interpret.

Response: Thank you for your careful attention and suggestion. To analyze the BVOC emission characteristics, it should not include data of non-emitters or low-emitters of isoprene and monoterpenes. We have deleted the data of non-emitters or low-emitters of isoprene and monoterpenes to avoid the inappropriate selection of data. In the sector “4.1. BVOC emission characteristics”, we have deleted “Table A3. BVOC emission patterns of the dominant tree species in Xiamen”, which described the BVOC emission patterns of the 8 tree species and compared the standard emission rates of isoprene and monoterpenes of our study with previous studies. And we have deleted the description and discussion on the emission characteristics of non-emitters or low-emitters of isoprene or monoterpenes. Pinus massonian, Pinus elliotti, Litchi chinensis, Dimocarpus longan and Acacia confusa were the low-emitters of isoprene. Casuarina equisetifolia, D. longan and A. confusa were the low-emitters of monoterpenes. Indeed, for the non-emitters or low-emitters of isoprene and monoterpenes, the result of the emission characteristics is very difficult to interpret. And we only describe and interpret the emission characteristics of high isoprene or monoterpenes emitters. E. grandis, E. citriodora and C. equisetifolia were the high-emitters of isoprene. E. grandis, E. citriodora, P. massonian, P. elliotti and L. chinensis were the high-emitters of monoterpenes. The relevant statements in sector “4.1. BVOC emission characteristics” have been revised to “Eucalyptus trees (E. grandis and E. citriodora) are the high BVOC emitters, with standard isoprene emission rates of 39.78±16.04 µg g^-1 h^-1 and 19.13±5.80 µg g^-1 h^-1, and standard monoterpene emission rates of 0.44±0.16 µg g^-1 h^-1 and 0.32±0.08 µg g^-1 h^-1. Compared with the mature trees in our study, the Eucalyptus trees with 12 to 24 months old showed higher emission rates of isoprene and monoterpene [46]. C. equisetifolia was a emitter with high isoprene, whose standard isoprene emission rate with 9.57±2.15 µg g^-1 h^-1 was higher than that measured by Zhao et al. [47] and Huang et al. [48] using a static enclosure sampling method. Pinus trees (P. massoniana and P. elliottii) are the emitters with high mono-terpenes. The standard monoterpene emission rate of P. massoniana with 0.90±0.23 µg g^-1 h^-1 was similar to that measured by Yang et al. [49] and Huang et al. [48].”

2. The second issue is the difference between the observed values measured by LI-6400XT using leaves near the Teflon bag and the actual environment inside the Teflon bag. In the case of the closed-loop system, the humidity inside the bag would increase significantly during the 45-minute period by transpiration. In addition, it is better to use the actual leaf surface temperatures in the bag for analysis rather than the outside air temperature. In Table A3, the monoterpene emission rates in this study are significantly lower than in previous studies. The relationship between RH and monoterpene emission rate in Figure A4 shows almost no emissions at RH above 50%. The monoterpene emission rates may be greatly underestimated by the high humidity inside the bags. In my opinion, an analysis focused on data from plants with strong isoprene emitters may yield more reliable results.

Response: Thank you for your careful attention and suggestion. There is a certain difference between the observed values measured by LI-6400XT using leaves near the Teflon bag and the actual environment inside the Teflon bag. In the course of BVOC sampling, we used an LI-6400 XT instrument to measure environmental factors and gas exchange parameters at 10-min intervals. If the leaf chamber of LI-6400 were put into the 10L sampling bag, only one group leaf/leaves was used to measure gas exchange parameters due to the enclosure system, and the representation of data was questionable. According to Simin et al. (2021), at each measurement, new one or more leaves near the sampling bag were randomly selected to fill the leaf chamber. The mean values of multiple records represent the environmental conditions and leaf physiology during the measurement period. BVOC samples and leaf gas exchange parameters were measured simultaneously to analyze the BVOC emission rates and influential factors of leaves of the tree species. We chose leaves near the sampling bag to fill the leaf chamber to ensure as much as possible that BVOC samples and leaf gas exchange parameters were measured in the same environment.

Considering the humidity inside the bag would increase significantly during the 45-minute period by transpiration, we used drying tube (allochroic silicagel) to reduce water vapour in the sampling enclosure system.

In further experiments, we will improve the experimental design to yield more reliable results. In the course of BVOC sampling, air temperature and relative humidity inside and outside the enclosure will be recorded using a data logger attached to the branch. Thermocouples inside the enclosure will be attached to the abaxial surfaces of selected leaves using porous medical tape. PAR will be recorded using a LiCOR 1400 (LI-COR, Lincoln, NE, USA) via a probe inserted into the enclosed bag.

In Table A3, the standard monoterpene emission rates of E. grandis with 0.44±0.16 µg g^-1 h^-1 and E. citriodora with 0.32±0.08 µg g^-1 h^-1 in our study were lower than in the study of He et al. (2000), mainly because of the difference of tree age. We chose mature trees, while He et al. (2000) chose the Eucalyptus trees with 12 to 24 months old. Young trees of Eucalyptus showed higher monoterpene emission rates than mature trees. For P. massoniana, the standard monoterpene emission rate ranging from 0.90±0.23 µg g^-1 h^-1 in our study was similar to that measured by Yang et al. (2001) with 0.96 µg g^-1 h^-1 and by Huang et al. (2011) with 1.39 µg g^-1 h^-1.

Most monoterpenes emitted from needle trees. For broadleaf trees, the monoterpene emission rates were low at RH above or below 50%. For needle trees, RH in our study ranged from 36.34% to 54.27%, and the monoterpene emission rates ranged from 0.04 µg g^-1 h^-1 to 2.65 µg g^-1 h^-1. The monoterpene emission rates of needle trees ranged from 0.17 µg g^-1 h^-1 to 1.19 µg g^-1 h^-1, when the RH was greater than 50%.

We used drying tube to reduce water vapour in the sampling enclosure system. During the sampling period, there was no high humidity inside the bag. The monoterpene emission rates were reliable. To yield more reliable results, we will record relative humidity and air temperature inside and outside the sampling bag using a data logger during BVOC sampling.

3. Line 1: It may be better to include “PA analysis” in the title or keywords.

Response: Thank you for your suggestion. We have added “path analysis” to the keywords.

4. Line 98: I wonder why there were many days with low PAR in Table A1 even though it is described that it were all clear days in the main text? Why were there few high PAR data in Figure A2 and Figure A3?

Response: Thank you for your careful attention. Even on sunny days, PAR can be low, especially in forests. Some plants have small forest gaps, which may result in low PAR in the lower canopy.

In Figure A2 and Figure A3, the PAR ranged from 4.78 µmol m^-2 s^-1 to 1462.82 µmol m^-2 s^-1. And 8.33% of the PAR values were greater than 1000 µmol m^-2 s^-1.

5. Line 100: How did you insert the leaves in the bag without causing injury effects on it?

Response: Thank you for your careful attention. We used the 10L sampling bag. In situ, we inserted a branch into the bag without breaking the branch or removing the leaves artificially. When tying a bag, it could cause a little damage to the branches. We carefully bagged the branches to minimize damage.

Round 2

Reviewer 1 Report

The authors have taken into account all my comments and revised their manuscript accordingly. 

I would like to suggest some further small improvements that can help the reader to understand the authors' results and help the authors to conduct more accurate studies on BVOC emissions. I recommend publication of the revised manuscript once the authors have taken into account these minor revisions.

 1. It would be valuable to include all the information about the experimental design, calibrations, instrumental uncertainties, purchased standards etc. provided in the authors answers in a text to be included in the supplementary material, as supplementary information about the method.

2. I find more appropriate to define the relationships among variables as trends instead of correlations when Pearson's and determination coefficients are below 0.5. I would also try to include the intermediate values and minor ticks in the legend of the color-scale used in Fig. 5.

3. It is not clear what the labels Aa Ab Ba etc. in the histograms stand for. Can the authors improve their definition in the captions of the respective figures?

4. I am not entirely convinced by the set-up used for the sampling. Mechanical damage on plants induce BVOC emission and can bias the analysis, some stabilization time is needed before conducting any sampling. It is not clear how the background sample was taken. I would recommend to take a background of the set-up when the bag is filled with clean air before starting any experiment, in further experiments. I would also recommend to test if moving the dryer and the scrubber before the sampling tube, after the Teflon bag is inducing any difference in sampled BVOC concentration with respect to the current set-up. 

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

I think the manuscript has been improved. Thank you for your sincere response.

In Figure A2(B), I wonder why there is no activated charcoal tube to clean air. Did you use the drying tube to clean the air, not only to dry?

In Figure A2(C), why there is no the Nafion tube dryer like Perma pure dryer? If the drying tube was connected directly to the circulation line, the drying tube may affect VOC concentrations.

Author Response

Thank you very much for reviewing our manuscript (forests-2191119 entitled "Interaction processes of environment and plant ecophysiology with BVOC emissions from dominant greening trees"). Your comments are very constructive and valuable. We have studied the comments carefully and tried our best to revise the manuscript according your recommendations. The point-by-point responses to all the comments are listed as follows.

I think the manuscript has been improved. Thank you for your sincere response.

1. In Figure A2(B), I wonder why there is no activated charcoal tube to clean air. Did you use the drying tube to clean the air, not only to dry?

Response: Thank you for your careful attention. When activated charcoal tube is used for C₂, C₃, C₄ hydrocarbons, it should be careful. Activated charcoal tube cannot effectively adsorb all VOCs in the air pumped into the sampling bag. We used a set of dynamic sampling enclosure system without a branch to collect background value.

We used the drying tube to dry the air, and the KI tube to adsorb O₃ in the air.

2. In Figure A2(C), why there is no the Nafion tube dryer like Perma pure dryer? If the drying tube was connected directly to the circulation line, the drying tube may affect VOC concentrations.

Response: Thank you for the reminder. Considering the humidity inside the bag would increase significantly during the 45-minute period by transpiration, we used drying tube (allochroic silicagel) to reduce water vapour in the sampling enclosure system. In further experiments, we will try to use the Nafion tube dryer like Perma pure dryer.

Author Response File: Author Response.docx