From the journal Environmental Science: Atmospheres Peer review history
Drone-based particle monitoring above two harmful algal blooms (HABs) in the USA
Round 1
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21-Jun-2022
Dear Professor Schmale III:
Manuscript ID: EA-ART-05-2022-000055
TITLE: Drone-Based Particle Monitoring Above Two Harmful Algal Blooms (HABs) at Grand Lake St Marys and Lake Erie, Ohio, USA
Thank you for your submission to Environmental Science: Atmospheres, published by the Royal Society of Chemistry. I sent your manuscript to reviewers and I have now received their reports which are copied below.
I have carefully evaluated your manuscript and the reviewers’ reports, and the reports indicate that major revisions are necessary.
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Reviewer 1
Title: Drone-Based Particle Monitoring Above Two Harmful Algal Blooms (HABs) at Grand Lake St Marys and Lake Erie, Ohio, USA
This manuscript describes the use of a drone-based particle monitoring system for the evaluation of algal blooms airborne particle emissions over freshwater. The drone system was furnished with different instruments such as an impinging device (ID) and an optical particle counter (OPC). The used of these techniques for the collection of the samples in combination with different analytical techniques, flow cytometry and liquid chromatography-mass spectrometry, allowed the identification o biotic objects and the quantitation of potential cyanotoxins.
Harmful algal blooms (HABs) occur naturally in freshwater systems. These phenomena are often associated with high levels of cyanotoxins that could affect human and domestic animals’ health. However, little is known about the transport and fate of aerosolized particles associated with HABs. In this way, the development of drone-based particle monitoring system will provide a useful tool for the clarification of this topic. In addition, the results obtained using this approach are promising. However, the evaluation of the potential associations between the particle numbers and a small number of environmental/meteorological variables is questionable. Additional variables, not considered in this study, might also affect the results.
Therefore, this manuscript is not deserved for its publication in Environmental Science: Atmospheres in the present form, but it could be published after clarification of the following points:
Title
HABs phenomena occur naturally in freshwater systems over the world. In this way, sampling site specification is not required in the title.
Abstract
Some quantitative results should be provided in the abstract section.
Line 25. The use of a specific name for the drone-based sampling system is not required.
Lines 30-32. Potential effect of drone propellers on the results should be clarified in the abstract.
Line 39. Please, avoid the use of the term ppb in the text.
Introduction
This section contains information that could be included in the experimental section (sampling places).
It could be interesting provide additional information about the formation of algal blooms.
Additional information about the different techniques and practices used for the analysis and monitoring of aerosol particles associated with harmful alga blooms should be provided in the introduction.
Line 49. According to Association for Uncrewed Systems (AAUS) and the Association for Uncrewed Vehicle Systems International (AUVSI) both recently replaced ‘unmanned’ for ‘uncrewed’. It could be interesting to replace the term manned by crewed. This information might be relevant in other places of the manuscript such as line 73.
Line 58. Please check m9.
Materials and methods
Study sites
Figure 1 might be included as supplementary information.
Information included in the introduction should be included into this section.
Line 100. Have these parameters been studied in LE?
Lines 101-103. Additional information about the calibration procedure should be clarified in the text.
In addition, if this is a well-established procedure, a reference should be included in the text.
Airborne DROne Particle-monitoring System (AirDROPS)
Have the authors evaluated the effect of the sampler position of the results?
Lines 137-139. This information is not required in the manuscript.
Cyanotoxin analyses sing LC-MS/MS
Additional information about the mass spectrometer ionization and fragmentation and detection conditions should be provided in the text.
Table 2 should be provided as supplementary information.
Ground-based measurements of windspeed and wind direction
The use of abbreviations or open names for the lakes names should be consistent through the text.
Drone-based wind velocity measurements
The abbreviation SoDAR should be defined in the text before its first use.
Data analyses
The different algorithms used for the statistical analysis should be clarified in the text.
Results
The number of figures is too large, some of them should be summarized and others moved to the supplementary information.
Results section should be divided into different subsections for the different topics of the study (calibration, results achieved for natural samples, statistical analysis, etc.).
In addition, it could be a good idea to joint results and discussion sections into a single one.
LCMS results are missing in the text.
Lines 240-242. Not needed to specify. It could be found on the figure.
Lines 245-246. It cannot be assumed that windspeed is the main factor to control the number of particles on the collected samples. Many other parameters and variables might affect the particle number (particle formation rate, particle dispersion, particle accumulation over the surface of the lake, etc.).
Lines 253-254. A potential explanation for this phenomenon should be provided in the text.
Line 277. The algorithm used for the development of the model should be clarified in the text.
Table 1 might be included as supplementary information.
Reviewer 2
This manuscript investigates the transport and fate of aerosolized particles over two harmful algal blooms at the Grand Lake St Marys and Lake Erie using an unmanned aerial vehicle (UAV) equipped with an impinger and an optical particle counter. Samples were collected 10 m above water level. Results show that particle concentration decreased over time due to the increase in wind speed. Particle concentration was observed to be much higher over GLSM than over Lake Erie. Biotic objects, detected by fluorescence imaging cytometer, were observed in more than half of the samples collected in the impinger. No cyanotoxins were detected in any of the samples. Overall, the UAV technique is novel and the results are interesting. However, I have some major concerns regarding the UAV sampling methodologies, size distribution of aerosols and biotic objects, the origin of the aerosols detected, and the prediction of aerosols over the lakes.
1. Line 30: “One calibration flight was conducted at GLSM over land”. What is calibrated? Please clarify.
2. Introduction: Information regarding how bioaerosols are produced over the lake is needed in the introduction for a better understanding of the manuscript. What are the physicochemical characteristics (e.g., composition, size) of the aerosols produced?
3. Line 99: The samples were collected 10 m above the water surface. Why 10 m? How do aerosols transport over the lake once emitted? What was the vertical distribution of the aerosols? Have the authors tried to collect samples at different heights and compare the results?
4. Lines 109-114: The weight of the payload can significantly affect the flight time of the UAV. What were the weights of the impinging device and OPC?
How were the pumps powered, by UAV power supply or external power supply? Why a flow rate of 0.6 L/min was used? Was there any solvent/glue applied inside the impinger prior to sampling? What are the collection efficiencies of particles at different sizes (e.g., 0.3-10 microns)?
5. Line 118: “The inlet was located 330 mm above the horizontal plane”. Depending on the position of the inlet, air sampling can be significantly affected by UAV downwash. Compared to gaseous species, aerosols may be subject to a greater impact due to their size. Please discuss the effects of UAV disturbance on aerosol sampling in this study.
6. Line 120: OPC records size in the range of 0.3-10 microns. Again, what are the sizes of HAB-related aerosols do you expect? Any literature references can be cited?
7. Figure 3: What is the meaning of the numbers at the left top corner of each sub-figure (e.g., 1251, 1825, 3887, 3976)? Is “7 um” in the left bottom corner of each sub-figure the scale for the particle size? Please clarify in the caption. What about the image of abiotic particles? Please provide an example for comparison.
8. Lines 149-150: “One mL of the impinged liquid sample was spun twice at 3,000 x gravity for five minutes”. Again, was there any solvent applied inside the impinger prior to sampling? If so, what was the solvent? If not, why there was liquid in the impinger?
9. Lines 161-162: “The objects counted in the red channel were considered to be biotic in origin, regardless of fluorescence level”. The OPC detects particles greater than 0.3 microns. What is the smallest size of the particle that can be observed by the Cytometer?
10. Lines 167-168: “the average of the total BF obj/mL for the zero red channel runs were assigned to a discrete size bin.” What about the size distribution of the biotic objects in the samples? This information is not present in the current manuscript. Can it be estimated from the results of the Cytometer?
11. Lines 207-208: “Drone-based wind velocity measurements were derived from a 3DR Solo quadrotor using the model-based wind estimation technique described in (González-Rocha et al, 2019; 2020).17,18”. First of all, the numbering of the references is wrong. Please check all the references to make sure they are correctly cited.
Reference 19 “Application of multirotor sUAS wind profiling for resolving microscale flows in complex environments” is still in preparation. Please provide this reference for review. Otherwise, please provide data to validate the results from UAV-based wind measurements presented in this study.
12. Figure 6: What is the diurnal time series of biotic objects over the two lakes? Please provide a similar figure as Figure 6.
13. Lines 263-264: “During our sampling throughout the day. the windspeed increased by 2 to 3 times the morning speed (Figure 7)”. Wrong figure. Do you mean Figure 5?
14. Lines 265-267 and elsewhere: Based on the wind information, the authors claimed that the sources of the collected particles were from the lakes. How can the authors be sure that the particles are produced solely from the lake? Although the dominant wind directions were off the lake, land-lake interactions such as lake breeze (land-lake air recirculation) can transport land-origin particles over the lake to be detected. Please discuss the influence of land-origin particles on the current results.
15. Lines 270-271: “An association between object concentrations and particle counts was not observed (Figure 8).”
What do you mean by the unit of the object number (#/mL R1) in Figure 8? Why object number is much higher than the OPC number? Is it because that OPC data unit is #/mL air and the unit of Cytometer data is #/mL liquid? Please clarify.
16. Lines 273-274: “Impinger samples were also analyzed for a suite of cyanotoxins using LC-MS/MS, but no cyanotoxins were detected in any of the samples.” The authors also collected water samples over Lake Erie. What is the typical concentration of MCs and nodularin cyanotoxins in the surface water of Lake Erie at the sampling site?
17. Figure 9 Prediction: The prediction was based on the data from August 5 on GLSM. Can the prediction be applied to the data collected on the other day (i.e., August 6)? Also, can the prediction be applied to the data collected over Lake Erie? According to Lines 306-322 and Figures 6-8, there were significant differences between aerosols produced over GLSM and Lake Erie. It seems that the prediction might only be suitable for a specific day at a specific cite (e.g., GLSM) and height (e.g., 10 m) under some specific weather conditions (e.g., fine weather, onshore winds). If so, what’s the point of generating this prediction equation?
18. Lines 283-290 and Figure 10: This paragraph shows the calibration and validation of OPC measurement. The information of this paragraph is disconnected from previous ones. I suggest the authors move this paragraph to the earlier part of the manuscript or to the supporting information.
19. Lines 317-318: “Lake Erie, however, would be more likely to produce larger numbers of aerosols from wave breaking and bubble-bursting due to the larger size and depth”. Isn’t this conflict with the information shown in Figures 6 and 7?
20. Lines 350-351: “Higher windspeeds may decrease total particle counts above a lake, but also drive aerosol production closer to the lake surface.” Any sample collection at the surface to support this statement?
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August 30, 2022
Editor, Environmental Science: Atmospheres themed collection on UAS in atmospheric science
Dear Editor,
Attached please find our revised manuscript EA-ART-05-2022-000055 now titled ‘Drone-Based Particle Monitoring Above Two Harmful Algal Blooms (HABs) in the USA’ to be considered for publication in Environmental Sciences: Atmospheres as part of the themed collection on UAS in atmospheric science. The revised manuscript and associated materials have been uploaded through the online manuscript submission and peer review system. Changes have been ‘tracked’ in MS Word. A separate file containing our detailed responses to the two reviewers has also been included following this letter.
The highlights of our major revisions include:
• Three figures and one table have been moved to online supplementary information.
• Additional data have been added to the abstract.
• Additional information has been added about the placement of the sampler above the airframe to limit the effects of propeller downwash that can corrupt measurements taken below the drone. Moreover, multiple references have been added citing the use of above-airframe drone mounts to study windspeed and wind direction.
• Details regarding the sampling locations have been moved to the methods section.
• Additional information and references about the formation of HABs have been added to the introduction.
• We have added two new paragraphs to the introduction regarding techniques to monitor aerosolization processes, and have also expanded the introduction to included information on red tides in oceans. Additional references have also been added.
• Additional information about the calibration and the use of the drone to determine windspeed and wind direction have been added to the text.
• We conducted a new analysis using a different JMP model (a neural network) used in the paper and added more of an explanation as to how it was trained and tested.
• We changed the wording to reflect association between wind speed and particle count without implying direct causation.
• We have added additional details regarding the airframe, power, and payload specifications.
• We have added additional language regarding the impinger. The impinger contained 2.5mL of sterile water which was added immediately prior to each sampling mission. Air samples were impinged in the fluid with a very high efficiency, as previously described by Powers et al. 2018.
• We have added a new figure that shows the size distribution ranges of the biotic objects from 0.2 microns to 8.9 microns. The biotic objects in that size range were all larger than 1.5 microns with the majority of the objects being between 2.8 and 5.6 microns radius. Since this range falls within the bin sizes of the OPC we were able to compare object counts and particle counts.
• We have added an additional paragraph to the discussion to address that we can only speculate on the origin of the particles, and acknowledge that background sources upwind of the lakes could have produced particles. We have offered future ideas for experiments to address this.
We look forward to having our paper published in Environmental Science: Atmospheres.
Sincerely,
David G. Schmale III, Ph.D.
REVIEWER REPORT(S):
Referee: 1
Comments to the Author
Title: Drone-Based Particle Monitoring Above Two Harmful Algal Blooms (HABs) at Grand Lake St Marys and Lake Erie, Ohio, USA
This manuscript describes the use of a drone-based particle monitoring system for the evaluation of algal blooms airborne particle emissions over freshwater. The drone system was furnished with different instruments such as an impinging device (ID) and an optical particle counter (OPC). The used of these techniques for the collection of the samples in combination with different analytical techniques, flow cytometry and liquid chromatography-mass spectrometry, allowed the identification o biotic objects and the quantitation of potential cyanotoxins.
Harmful algal blooms (HABs) occur naturally in freshwater systems. These phenomena are often associated with high levels of cyanotoxins that could affect human and domestic animals’ health. However, little is known about the transport and fate of aerosolized particles associated with HABs. In this way, the development of drone-based particle monitoring system will provide a useful tool for the clarification of this topic. In addition, the results obtained using this approach are promising. However, the evaluation of the potential associations between the particle numbers and a small number of environmental/meteorological variables is questionable. Additional variables, not considered in this study, might also affect the results.
Therefore, this manuscript is not deserved for its publication in Environmental Science: Atmospheres in the present form, but it could be published after clarification of the following points.
Response: We thank the reviewer for the detailed comments and suggestions. We have made significant revisions to the manuscript to address your comments and concerns. Below, please find our detailed responses.
Title
HABs phenomena occur naturally in freshwater systems over the world. In this way, sampling site specification is not required in the title.
Response: Excellent suggestion with a much broader reach. We have changed the title to be ‘Drone-Based Particle Monitoring Above Two Harmful Algal Blooms (HABs) in the USA’
Abstract
Some quantitative results should be provided in the abstract section.
Response: We have provided additional quantitative data in the abstract for particle counts and windspeed.
Line 25. The use of a specific name for the drone-based sampling system is not required.
Response: We thank the reviewer for this suggestion, but respectfully disagree and wish to retain the acronym AirDROPS throughout the manuscript. The acronym succinctly describes the system (Airborne DROne Particle-monitoring System) and is also a reference to what the system was designed in part to collect ‘air drops’.
Lines 30-32. Potential effect of drone propellers on the results should be clarified in the abstract.
Response: A sentence has been added to the abstract to address this salient point. Moreover, additional references have been added that demonstrate the importance and relevance of sampling undisturbed air above the drone.
Line 39. Please, avoid the use of the term ppb in the text.
Response: Though ppb is a common acronym for units of cyanotoxins, we have removed it from the text since the audience for this manuscript is likely to be unaware of this use.
Introduction
This section contains information that could be included in the experimental section (sampling places).
Response: Details regarding our sampling locations have been moved to the methods section as suggested.
It could be interesting provide additional information about the formation of algal blooms.
Response: Additional information and references about the formation of HABs have been added to the introduction.
Additional information about the different techniques and practices used for the analysis and monitoring of aerosol particles associated with harmful alga blooms should be provided in the introduction.
Response: We have added two new paragraphs to the introduction regarding techniques to monitor aerosolization processes, and have also expanded the introduction to included information on red tides in oceans. Additional references have also been added.
Line 49. According to Association for Uncrewed Systems (AAUS) and the Association for Uncrewed Vehicle Systems International (AUVSI) both recently replaced ‘unmanned’ for ‘uncrewed’. It could be interesting to replace the term manned by crewed. This information might be relevant in other places of the manuscript such as line 73.
Response: Thank you for reminding us of this important change. We have changed ‘unmanned’ to ‘uncrewed’ throughout the paper.
Line 58. Please check m9.
Response: We fixed the reference on depth of GLSM.
Materials and methods
Study sites
Figure 1 might be included as supplementary information.
Response: We have moved the figure to supplementary information as suggested.
Information included in the introduction should be included into this section.
Response: We have moved some of the study site information here from the introduction.
Line 100. Have these parameters been studied in LE?
Response: Unfortunately, we were unable to study similar parameters at Lake Erie due to obstruction of the sonic anemometer by trees. We have added additional language to clarify these issues faced at LE with regards to collection due to the lack of open space for the sonic anemometer.
Lines 101-103. Additional information about the calibration procedure should be clarified in the text. In addition, if this is a well-established procedure, a reference should be included in the text.
Response: Additional information about the calibration and the use of the drone to determine windspeed and wind direction have been added to the text.
Airborne DROne Particle-monitoring System (AirDROPS)
Have the authors evaluated the effect of the sampler position of the results?
Response: Additional information has been added about the placement of the sampler above the airframe to limit the effects of propeller downwash that can corrupt measurements taken below the drone. Moreover, multiple references have been added citing the use of above-airframe drone mounts to study windspeed and wind direction.
Lines 137-139. This information is not required in the manuscript.
Response: We removed the sentence on lines 137-139
Cyanotoxin analyses using LC-MS/MS
Additional information about the mass spectrometer ionization and fragmentation and detection conditions should be provided in the text.
Response: We have included a statement regarding additional details on these methods and have provided another reference.
Table 2 should be provided as supplementary information.
Response: We have moved table 2 to supplementary materials. It is now supplementary Table 1.
Ground-based measurements of windspeed and wind direction
The use of abbreviations or open names for the lakes names should be consistent through the text.
Response: We have reviewed and updated all of the acronyms throughout the text.
Drone-based wind velocity measurements
The abbreviation SoDAR should be defined in the text before its first use.
Response: This has been defined in the text.
Data analyses
The different algorithms used for the statistical analysis should be clarified in the text.
Response: We conducted a new analysis using a different JMP model (a neural network) used in the paper and added more of an explanation as to how it was trained and tested.
Results
The number of figures is too large, some of them should be summarized and others moved to the supplementary information.
Results section should be divided into different subsections for the different topics of the study (calibration, results achieved for natural samples, statistical analysis, etc.).
Response: Three of the figures have been moved to online supplements. The results section now includes separate section headings as suggested.
In addition, it could be a good idea to joint results and discussion sections into a single one.
Response: Though we appreciate this suggestion, we would prefer to retain the results and discussion as separate sections. We trust that the re-formatting of the results into separate headings will also help provide clarity and relevance to both of these separate sections.
LCMS results are missing in the text.
Response: LC/MS results are included in section 3.4
Lines 240-242. Not needed to specify. It could be found on the figure.
Response: We removed the sentence on lines 240-242.
Lines 245-246. It cannot be assumed that windspeed is the main factor to control the number of particles on the collected samples. Many other parameters and variables might affect the particle number (particle formation rate, particle dispersion, particle accumulation over the surface of the lake, etc.).
Response: We changed the wording to reflect association between wind speed and particle count without implying direct causation.
Lines 253-254. A potential explanation for this phenomenon should be provided in the text.
Response: We provide an explanation for Lake Erie measurements being lower and consistent due to the conditions at Lake Erie showing less intense signs of a HAB. We explain the lower particle counts as a potential result of LE not experiencing a HAB of the severity of the HAB at GLSM.
Line 277. The algorithm used for the development of the model should be clarified in the text.
Response: We reworked the JMP model to improve its ability to predict particle counts on multiple days as well as including an explanation for the development of the model.
Table 1 might be included as supplementary information.
Response: We prefer to retain Table 1 in the manuscript. We have moved the other table and three of the figures to supplementary information. Moreover, we have added additional impinger particle data to Table 1.
Referee: 2
Comments to the Author
This manuscript investigates the transport and fate of aerosolized particles over two harmful algal blooms at the Grand Lake St Marys and Lake Erie using an unmanned aerial vehicle (UAV) equipped with an impinger and an optical particle counter. Samples were collected 10 m above water level. Results show that particle concentration decreased over time due to the increase in wind speed. Particle concentration was observed to be much higher over GLSM than over Lake Erie. Biotic objects, detected by fluorescence imaging cytometer, were observed in more than half of the samples collected in the impinger. No cyanotoxins were detected in any of the samples. Overall, the UAV technique is novel and the results are interesting. However, I have some major concerns regarding the UAV sampling methodologies, size distribution of aerosols and biotic objects, the origin of the aerosols detected, and the prediction of aerosols over the lakes.
Response: We thank the reviewer for the comprehensive comments, suggestions, and criticisms. We have made major revisions to the manuscript, and have detailed our responses below.
1. Line 30: “One calibration flight was conducted at GLSM over land”. What is calibrated? Please clarify.
Response: We have changed the terminology of this mission. This mission was designed as an intercomparison among the drone used to measure windspeed, the drone with the AirDROPS package, and the tower with the wind sensor on it.
2. Introduction: Information regarding how bioaerosols are produced over the lake is needed in the introduction for a better understanding of the manuscript. What are the physicochemical characteristics (e.g., composition, size) of the aerosols produced?
Response: We have added two new paragraphs to the introduction regarding aerosolization processes, and have also expanded the introduction to included information on red tides in oceans. Additional references have also been added.
3. Line 99: The samples were collected 10 m above the water surface. Why 10 m? How do aerosols transport over the lake once emitted? What was the vertical distribution of the aerosols? Have the authors tried to collect samples at different heights and compare the results?
Response: The sampling height was chosen to minimize the effects of propwash on aerosolization from the lake surface. Below this height, the propwash from the drone could generate visible aerosols from the lake surface. The question about vertical distribution of aerosols above the lake surface is an excellent one, and certainly is an interest of ours for future work. We have added a section to the discussion to address this, and also have referenced previous work by the corresponding author to compare simultaneous measurements of microbes collected between a UAS and a USV.
4. Lines 109-114: The weight of the payload can significantly affect the flight time of the UAV. What were the weights of the impinging device and OPC?
How were the pumps powered, by UAV power supply or external power supply? Why a flow rate of 0.6 L/min was used? Was there any solvent/glue applied inside the impinger prior to sampling? What are the collection efficiencies of particles at different sizes (e.g., 0.3-10 microns)?
Response: Excellent questions. Thank you for bringing these missing details to our attention. We have added additional details to the methods section of the manuscript to address all of these points.
5. Line 118: “The inlet was located 330 mm above the horizontal plane”. Depending on the position of the inlet, air sampling can be significantly affected by UAV downwash. Compared to gaseous species, aerosols may be subject to a greater impact due to their size. Please discuss the effects of UAV disturbance on aerosol sampling in this study.
Response: The inlets were designed to be free of propeller downwash. We have added additional language and numerous references to address this salient point, largely motivated by the work by De Wekker and colleagues to understand appropriate distances above rotary wing aircraft to limit influences of propwash. The work by the corresponding author highlighted in Nolan et al. allows shows the use of a similar mount design but for a sonic anemometer above the same airframe.
6. Line 120: OPC records size in the range of 0.3-10 microns. Again, what are the sizes of HAB-related aerosols do you expect? Any literature references can be cited?
Response: Thank you for bringing this important detail to our attention. We have added additional information regarding the sizes of cells expected, at least for Microcystis spp. (1-7 um).
7. Figure 3: What is the meaning of the numbers at the left top corner of each sub-figure (e.g., 1251, 1825, 3887, 3976)? Is “7 um” in the left bottom corner of each sub-figure the scale for the particle size? Please clarify in the caption. What about the image of abiotic particles? Please provide an example for comparison.
Response: The figure has been modified to address these issues, and the legend has been updated to clarify the scale bar.
8. Lines 149-150: “One mL of the impinged liquid sample was spun twice at 3,000 x gravity for five minutes”. Again, was there any solvent applied inside the impinger prior to sampling? If so, what was the solvent? If not, why there was liquid in the impinger?
Response: We have added additional language regarding the impinger. The impinger contained 2.5mL of sterile water which was added immediately prior to each sampling mission. Air samples were impinged in the fluid with a very high efficiency, as previously described by Powers et al. 2018.
9. Lines 161-162: “The objects counted in the red channel were considered to be biotic in origin, regardless of fluorescence level”. The OPC detects particles greater than 0.3 microns. What is the smallest size of the particle that can be observed by the Cytometer?
Response: The smallest size we looked for was 0.2 microns radius in the flow cytometer. The largest size was 8.9 micron radius.
10. Lines 167-168: “the average of the total BF obj/mL for the zero red channel runs were assigned to a discrete size bin.” What about the size distribution of the biotic objects in the samples? This information is not present in the current manuscript. Can it be estimated from the results of the Cytometer?
Response: We have added a new figure that shows the size distribution ranges of the biotic objects from 0.2 microns to 8.9 microns. The biotic objects in that size range were all larger than 1.5 microns with the majority of the objects being between 2.8 and 5.6 microns radius. Since this range falls within the bin sizes of the OPC we were able to compare object counts and particle counts.
11. Lines 207-208: “Drone-based wind velocity measurements were derived from a 3DR Solo quadrotor using the model-based wind estimation technique described in (González-Rocha et al, 2019; 2020).17,18”. First of all, the numbering of the references is wrong. Please check all the references to make sure they are correctly cited.
Reference 19 “Application of multirotor sUAS wind profiling for resolving microscale flows in complex environments” is still in preparation. Please provide this reference for review. Otherwise, please provide data to validate the results from UAV-based wind measurements presented in this study.
Response: Thank you for bringing the reference issues to our attention. This was likely the result of merging multiple Zotero libraries. The references have been updated. Attached please find a copy of the manuscript, which is currently in review for the same issue of the same journal.
12. Figure 6: What is the diurnal time series of biotic objects over the two lakes? Please provide a similar figure as Figure 6.
Response: We have added data to Table 1, and have generated a new Figure 7 that shows the distribution of biotic objects across different size bins.
13. Lines 263-264: “During our sampling throughout the day. the windspeed increased by 2 to 3 times the morning speed (Figure 7)”. Wrong figure. Do you mean Figure 5?
Response: Correct. This has been updated. Thank you for catching this error.
14. Lines 265-267 and elsewhere: Based on the wind information, the authors claimed that the sources of the collected particles were from the lakes. How can the authors be sure that the particles are produced solely from the lake? Although the dominant wind directions were off the lake, land-lake interactions such as lake breeze (land-lake air recirculation) can transport land-origin particles over the lake to be detected. Please discuss the influence of land-origin particles on the current results.
Response: This is a very important point. We have added an additional paragraph to the discussion to address that we can only speculate on the origin of the particles, and acknowledge that background sources upwind of the lakes could have produced particles. We have offered future ideas for experiments to address this.
15. Lines 270-271: “An association between object concentrations and particle counts was not observed (Figure 8).”
What do you mean by the unit of the object number (#/mL R1) in Figure 8? Why object number is much higher than the OPC number? Is it because that OPC data unit is #/mL air and the unit of Cytometer data is #/mL liquid? Please clarify.
Response: We have moved these data into Table 1, and have provided a new figure (Figure 7) that shows the distribution of biotic objects across different size bins.
16. Lines 273-274: “Impinger samples were also analyzed for a suite of cyanotoxins using LC-MS/MS, but no cyanotoxins were detected in any of the samples.” The authors also collected water samples over Lake Erie. What is the typical concentration of MCs and nodularin cyanotoxins in the surface water of Lake Erie at the sampling site?
Response: We have added a few sentences regarding the concentrations of toxins in the water at GLSM. This was the subject of paper (Hanlon et al., 2022) just published by the corresponding author in Frontiers.
17. Figure 9 Prediction: The prediction was based on the data from August 5 on GLSM. Can the prediction be applied to the data collected on the other day (i.e., August 6)? Also, can the prediction be applied to the data collected over Lake Erie? According to Lines 306-322 and Figures 6-8, there were significant differences between aerosols produced over GLSM and Lake Erie. It seems that the prediction might only be suitable for a specific day at a specific cite (e.g., GLSM) and height (e.g., 10 m) under some specific weather conditions (e.g., fine weather, onshore winds). If so, what’s the point of generating this prediction equation?
Response: We changed the model to better utilize our collected data by using the neural network feature of JMP to train a model with data from two different days of sampling. Using data from both days that was excluded from the model training we were able to verify the results of a model that works on multiple days at GLSM. In the future it would be good to collect data from our site again and test the model with that data set, unfortunately we only had data from August 5th and 6th to work with at the time, but the goal is to make a general model that can be applied to GLSM in any conditions.
18. Lines 283-290 and Figure 10: This paragraph shows the calibration and validation of OPC measurement. The information of this paragraph is disconnected from previous ones. I suggest the authors move this paragraph to the earlier part of the manuscript or to the supporting information.
Response: We moved this paragraph to better fit in with the surrounding paragraphs.
19. Lines 317-318: “Lake Erie, however, would be more likely to produce larger numbers of aerosols from wave breaking and bubble-bursting due to the larger size and depth”. Isn’t this conflict with the information shown in Figures 6 and 7?
Response: We added this line and the reference attached to highlight how the size of a lake can influence the ways in which lake aerosols are produced. It is not meant to imply we should necessarily see more particles.
20. Lines 350-351: “Higher windspeeds may decrease total particle counts above a lake, but also drive aerosol production closer to the lake surface.” Any sample collection at the surface to support this statement?
Response: We added this line and the attached references to explain why our data may not line up perfectly with our expectations, but still is in line with other experimental results.
Round 2
Revised manuscript submitted on 30 ஆகஸ்ட் 2022![](https://www.rsc-cdn.org/pubs-core/2022.0.147/content/NewImages/icon-letter.png)
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12-Sep-2022
Dear Professor Schmale III:
Manuscript ID: EA-ART-05-2022-000055.R1
TITLE: Drone-Based Particle Monitoring Above Two Harmful Algal Blooms (HABs) in the USA
Thank you for your submission to Environmental Science: Atmospheres, published by the Royal Society of Chemistry. I sent your manuscript to reviewers and I have now received their reports which are copied below.
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Associate Editor, Environmental Science: Atmospheres
Environmental Science: Atmospheres is accompanied by companion journals Environmental Science: Nano, Environmental Science: Processes and Impacts, and Environmental Science: Water Research; publishing high-impact work across all aspects of environmental science and engineering. Find out more at: http://rsc.li/envsci
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Reviewer 1
Title: Drone-Based Particle Monitoring Above Two Harmful Algal Blooms (HABs) at Grand Lake St Marys and Lake Erie, Ohio, USA
This manuscript describes the use of a drone-based particle monitoring system for the evaluation of algal blooms airborne particle emissions over freshwater.
Most of the comments and suggestions provided by the different reviewers have been addressed in the new version of the manuscript. However, there are still some small issues to be clarified and / or considered by the authors before its publication in Environmental Science: Atmospheres.
Line 305. Injection volume is too large for the selected column. Please check.
Line 308. Use ng/mL or similar instead of ppt in the text.
Line 368. Avoid the use of abbreviations on the section titles.
Line 437. Add space between 3.91 and µm.
Lines 452-456. The number of samples us
ed for model development should be clarified in the text.
Reviewer 2
I appreciate the time and effort that the authors put into both revising the manuscript and replying to my comments. The authors have sufficiently addressed my comments, especially for those concerns regarding aerosol sampling methodology, the origin and the size of the aerosol sampled, and the influence of the UAV on aerosol sampling. I only have some minor comments about the revised model prediction:
The authors used JMP Pro (with JMP neural network) to generate model prediction equations.
a. Please add a sentence to briefly introduce JMP Pro and JMP neural network.
b. How were the training and testing datasets selected? Were they selected randomly, or they were selected based on some rules? Please also add the distribution of the training and testing datasets in Figure 8 to show that the training data can well represent the range of the testing data (although it seems so in Figure 8).
c. For the prediction equations, what are H1, H2, H3, and THETA1? Please define them in the manuscript.
d. Please reduce the number of significant digits for the coefficients used in the prediction equations. For example, for one of the coefficients 0.256505072493476, do you really need so many significant digits?
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September 13, 2022
Editor, Environmental Science: Atmospheres themed collection on UAS in atmospheric science
Dear Editor,
Attached please find our revised manuscript EA-ART-05-2022-000055R2 titled ‘Drone-Based Particle Monitoring Above Two Harmful Algal Blooms (HABs) in the USA’ to be considered for publication in Environmental Sciences: Atmospheres as part of the themed collection on UAS in atmospheric science. The revised manuscript and associated materials have been uploaded through the online manuscript submission and peer review system. Changes have been ‘tracked’ in MS Word. A separate file containing our detailed responses to the two reviewers has also been included following this letter.
We have addressed all of the suggested revisions. We look forward to having our paper published in Environmental Science: Atmospheres.
Sincerely,
David G. Schmale III, Ph.D.
Referee: 1
This manuscript describes the use of a drone-based particle monitoring system for the evaluation of algal blooms airborne particle emissions over freshwater. Most of the comments and suggestions provided by the different reviewers have been addressed in the new version of the manuscript. However, there are still some small issues to be clarified and / or considered by the authors before its publication in Environmental Science: Atmospheres.
Response: We thank the reviewers for taking the time to take a second look at the manuscript. Your comments have been helpful in improving the work and we appreciate your dedication to the success of this paper. Below we address specific concerns regarding the second round of reviewer comments.
Line 305. Injection volume is too large for the selected column. Please check.
Line 308. Use ng/mL or similar instead of ppt in the text.
Response: We have changed the wording of the entire methods 2.5 section to address both of these issues.
Line 368. Avoid the use of abbreviations on the section titles.
Response: We changed OPC to Optical Particle Counter to avoid abbreviations in the section title.
Line 437. Add space between 3.91 and µm.
Response: We added the space between 3.91 and µm.
Lines 452-456. The number of samples used for model development should be clarified in the text.
Response: We added the number of samples to the text in the section explaining the model and we describe how the portion used for training the model and the portion withheld for validation is determined.
Referee: 2
I appreciate the time and effort that the authors put into both revising the manuscript and replying to my comments. The authors have sufficiently addressed my comments, especially for those concerns regarding aerosol sampling methodology, the origin and the size of the aerosol sampled, and the influence of the UAV on aerosol sampling. I only have some minor comments about the revised model prediction:
Response: We thank the reviewers for taking the time to take a second look at the manuscript. Your comments have been helpful in improving the work and we appreciate your dedication to the success of this paper.
The authors used JMP Pro (with JMP neural network) to generate model prediction equations. a. Please add a sentence to briefly introduce JMP Pro and JMP neural network.
Response: We added a definition of JMP and the neural network modeling to section 2.10 of the methods. We also added some additional references for the neural network modeling.
b. How were the training and testing datasets selected? Were they selected randomly, or they were selected based on some rules? Please also add the distribution of the training and testing datasets in Figure 8 to show that the training data can well represent the range of the testing data (although it seems so in Figure 8).
Response: This has been expanded upon in section 2.10 of the methods. The figure represents a random selection of 2/3 of the data to train the model and to illustrate this we have included a separate run of the model.
c. For the prediction equations, what are H1, H2, H3, and THETA1? Please define them in the manuscript.
Response: The H1, H2, H3, and THETA1 terms have been explained in section 2.10 when discussing how the hidden nodes equations are created during the modeling.
d. Please reduce the number of significant digits for the coefficients used in the prediction equations. For example, for one of the coefficients 0.256505072493476, do you really need so many significant digits?
Response: We reduced the equation to include fewer significant digits to increase the readability of the equations.
Round 3
Revised manuscript submitted on 14 செப்டம்பர் 2022![](https://www.rsc-cdn.org/pubs-core/2022.0.147/content/NewImages/icon-letter.png)
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16-Sep-2022
Dear Professor Schmale III:
Manuscript ID: EA-ART-05-2022-000055.R2
TITLE: Drone-Based Particle Monitoring Above Two Harmful Algal Blooms (HABs) in the USA
Thank you for submitting your revised manuscript to Environmental Science: Atmospheres. I am pleased to accept your manuscript for publication in its current form.
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Dr Lin Wang
Associate Editor, Environmental Science: Atmospheres
Environmental Science: Atmospheres is accompanied by companion journals Environmental Science: Nano, Environmental Science: Processes and Impacts, and Environmental Science: Water Research; publishing high-impact work across all aspects of environmental science and engineering. Find out more at: http://rsc.li/envsci
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