Bioparticle Sources, Dispersion, and Influencing Factors in Rural Environmental Air

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

line15-31: Could the authors clarify how the "portable bioaerosol detector" was calibrated or validated before field deployment?

line94-110: The description of the study site is detailed, but could the authors elaborate on how generalizable these findings are to other rural settings?

line111-121: Please specify the criteria used to select the final sampling points within the 81 grids.

line187-202: While temperature is compared, humidity differences between hot and cold weather conditions were not discussed. Could this be a confounding factor?

line264-278: The RDA analysis is informative. Have the authors conducted any sensitivity analysis to check robustness of environmental variables?

line410-429: The use of CFU/m³ for Enterobacteriaceae is appropriate. However, were molecular methods (e.g., qPCR) considered to confirm identification?

line454-468: The conclusion is comprehensive, but could the authors briefly comment on policy implications or mitigation strategies for local governments?

line469-475: Future directions are mentioned. Would the authors consider integrating a real-time rural bioaerosol surveillance system?

discussion/conclustion: Please expand the discussion on the interaction between outdoor bioaerosols and indoor environments, and elaborate on its significance. Additionally, discuss the limitations of conventional culture-based and impaction methods for bioaerosol measurement, and suggest directions for future research. The following references may be helpful.
https://doi.org/10.4209/aaqr.210231

Author Response

1. line15-31: Could the authors clarify how the "portable bioaerosol detector" was calibrated or validated before field deployment?
2. RE) Thanks to the reviewers' advice. This biological aerosol detector only needs to be powered on for 30 seconds before use, and it will automatically calibrate. After calibration, it can conduct real-time data collection and recording. We also perform routine maintenance on the device when it is not in use. We have added relevant content in the abstract and materials and methods section.

Potential bioaerosol sources including livestock farming areas, composting sites, garbage dumps, and sewage treatment facilities were investigated using a calibrated portable bioaerosol detector to collect and analyze the dispersion of bioaerosol particles. (Line 19 to 21).

The equipment will automatically calibrate after being powered on for 30 seconds. (Line 137 to 138).

In the actual air environment, cigarette particles, paper dust, pollen, kaolin, etc. will also produce intrinsic fluorescence, so in the process of use, the instrument should try to avoid inhaling these fluorescence interferences in order to reduce the false alarm rate. We regularly maintain it. For example, the dust filter is cleaned once a week, and the filter is replaced every 2-3 months. The replacement frequency can be adjusted according to the usage and environment to ensure data accuracy.  (Line 148 to 153).

2. line94-110: The description of the study site is detailed, but could the authors elaborate on how generalizable these findings are to other rural settings?
3. RE) Thanks to the experts' advice, we selected a village in western Hohhot, Inner Mongolia. It has typical northwestern region village features and common rural bioaerosol sources like livestock areas and compost sites. Thus, the findings can be extended to other northwestern region villages. We've added this to the "Description of the study sites" in the revised manuscript.

Thus, the research conclusions obtained for this village may be applicable to similar villages in other regions. (Line 97 to 99).

3. line111-121: Please specify the criteria used to select the final sampling points within the 81 grids.
4. RE) Thanks to the reviewers' advice. We sampled bio-particles in areas with obvious livestock farming areas, composting sites, garbage dumps, dry toilet and sewage treatment facilities across 81 grids. Also, each of the 81 grids was split into 25 sub-grids. In each sub-grid, we picked a spot without the above risk sources to collect the local environmental background value. We added this to the revised manuscript.

We sampled bio-particles in areas with obvious livestock farming areas, composting sites, garbage dumps, dry toilet and sewage treatment facilities across 81 grids. Also, each of the 81 grids was split into 25 sub-grids. In each sub-grid, we picked a spot without the above risk sources to collect the local environmental background value. (Line 113 to 117).

4. line187-202: While temperature is compared, humidity differences between hot and cold weather conditions were not discussed. Could this be a confounding factor?
5. RE) Thanks to the reviewers' advice. In the revised manuscript, we added information on the possible effects of humidity.

While we focused on temperature differences, we acknowledge that humidity levels also varied between these conditions (Table 1). Analysis in Fig. 3a reveals a minimal difference in the mean concentration of biological particles between the hot and cold weather conditions. However, humidity levels were significantly higher during the cold weather conditions. This higher humidity may have contributed to the increased bioparticle concentrations we observed under cold conditions, as high humidity can promote the survival of certain microorganisms and affect particle aggregation. (Line 215 to 222).

5. line264-278: The RDA analysis is informative. Have the authors conducted any sensitivity analysis to check robustness of environmental variables?
6. RE) We appreciate the reviewer's suggestion to conduct a sensitivity analysis. While we recognize the value of such analyses in model validation, we have chosen not to perform one at this stage due to the exploratory nature of our study and concerns about overfitting.

Our primary goal with the RDA was to identify potential relationships between environmental variables and bioparticle concentrations, rather than to build a predictive model. Given the relatively large number of environmental variables considered in relation to our sample size, we are concerned that a sensitivity analysis could lead to overfitting, where the model is optimized to fit the specific data set but does not generalize well to other situations. Therefore, we did not perform a sensitivity analysis.

6. line410-429: The use of CFU/m³ for Enterobacteriaceae is appropriate. However, were molecular methods (e.g., qPCR) considered to confirm identification?
7. RE) Thanks to the reviewers' advice. We used McConkey agar in the Anderson sampler. As a selective medium, it only allows Enterobacteriaceae bacteria to grow. Thus, we can confirm that all grown bacteria belong to Enterobacteriaceae.
8. line454-468: The conclusion is comprehensive, but could the authors briefly comment on policy implications or mitigation strategies for local governments?
9. RE) Thanks to the reviewers' advice, we added relevant content to the end of the revised manuscript.

Based on our findings, we recommend that local governments consider the following policy implications and mitigation strategies: (1) Implement zoning regulations to ensure adequate separation between livestock farming areas and residential areas, minimizing exposure to bioparticles. (2) Establish mandatory composting programs for livestock waste to reduce bioparticle emissions from agricultural sources, a key finding of our study. (3) Launch public health education campaigns to inform residents about the risks of bioparticles and promote practices such as proper ventilation and hand hygiene. (4) Expand air quality monitoring programs to include bioparticles, providing a more comprehensive assessment of air quality in rural areas.  (Line 504 to 512).

8. line469-475: Future directions are mentioned. Would the authors consider integrating a real-time rural bioaerosol surveillance system?
9. RE) Thanks to the reviewers' advice, we added relevant content to the end of the revised manuscript.

Future research should address limitations in measurement techniques and potential interference from non-biological organic compounds. While conventional methods may underestimate bioaerosol concentrations, fluorescent monitors are prone to interference from sources like solid fuel burning and secondary organic particles (Yang et al., 2023). Therefore, we recommend employing advanced analytical techniques such as PCR and metagenomics to differentiate biological from non-biological particles and developing real-time sensors less susceptible to interference. Integrating multiple measurement methods will provide a more comprehensive understanding of bioaerosol dynamics. (Line 513 to 520).

9. discussion/conclustion: Please expand the discussion on the interaction between outdoor bioaerosols and indoor environments, and elaborate on its significance. Additionally, discuss the limitations of conventional culture-based and impaction methods for bioaerosol measurement, and suggest directions for future research. The following references may be helpful. https://doi.org/10.4209/aaqr.210231
10. RE) Thanks to the reviewers' advice, in the revised manuscript, we further discussed the interaction between outdoor bioaerosols and indoor environments, and the limitations of traditional culture and impaction methods for bioaerosol measurement. We also proposed future research directions at the end of the article.

This is primarily because outdoor bioaerosols can infiltrate into indoor spaces through ventilation systems, open windows, and other pathways, increasing the overall indoor bioaerosol load (Yang et al., 2023). This is particularly evident in rural areas where homes may be in close proximity to agricultural bioaerosol sources. Infiltration of outdoor bioaerosols can exacerbate indoor air quality problems and increase health risks for building occupants, especially vulnerable groups such as children and the elderly. (Line481 to 487).

Future research should address limitations in measurement techniques and potential interference from non-biological organic compounds. While conventional methods may underestimate bioaerosol concentrations, fluorescent monitors are prone to interference from sources like solid fuel burning and secondary organic particles (Yang et al., 2023). Therefore, we recommend employing advanced analytical techniques such as PCR and metagenomics to differentiate biological from non-biological particles and developing real-time sensors less susceptible to interference. Integrating multiple measurement methods will provide a more comprehensive understanding of bioaerosol dynamics. (Line 513 to 520).

References：

Yang, J., Seo, J., Jee, Y., Kim, Y., Sohn, J., 2023. Composition Analysis of Airborne Microbiota in Outdoor and Indoor Based on Dust Separated by Micro-sized and Nano-sized. Aerosol air qual. res. 23(7), 1-13. https://doi.org/10.4209/aaqr.210231.

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors It is interesting work, but more statistical assessment is required (significance testing for the comparisons of particle numbers, as well as clarification of methods - averaging time of sampling, inlet size range of the instrument used, fluorescence wavelengths used - fluorescent particle monitors are prone to interference from non-biological organic compounds (could the big rise during cold weather reflect solid fuel burning?) The increase in particle count under hazy conditions also suggests to me that interference by secondary organic particles is a possibility. Comments on the Quality of English Language It is interesting work, but more statistical assessment is required (significance testing for the comparisons of particle numbers, as well as clarification of methods - averaging time of sampling, inlet size range of the instrument used, fluorescence wavelengths used - fluorescent particle monitors are prone to interference from non-biological organic compounds (could the big rise during cold weather reflect solid fuel burning?) The increase in particle count under hazy conditions also suggests to me that interference by secondary organic particles is a possibility.

Author Response

1. This study is interesting because the authors collected some data from a village in China on atmospheric bioparticles and tried to enhance our understanding of the characteristics and transport patterns of bioparticles with reference to temperature, relative humidity, atmospheric pressure, wind speed, wind direction, UV, and other particulate matter. They also recorded the weather conditions. They used a new type of real-time bioaerosol monitor that uses Mie scattering and ultraviolet-induced fluorescence (UV-LIF) methods to characterize bioaerosols.
2. RE) We sincerely appreciate the reviewer's insightful comments. We have thoroughly examined each of them and crafted responses accordingly. Please find our specific responses to the comments below.
3. Introduction, lines 84 – 92: Please clearly outline the study's objectives and omit the risk assessment and awareness-raising issues, as they were not documented in the article.
4. RE) Thanks to the reviewers' advice, in the revised manuscript's Introduction, we omitted risk assessment and awareness-raising issues and clearly outlined the research objectives. The specific revisions are as follows.

Therefore, the objective of this study was to investigate the sources and dispersion patterns of bioparticles in a rural environment under different weather conditions. We aimed to identify the key environmental factors influencing bioparticle concentrations and to characterize the presence of Enterobacteriaceae, a group of bacteria with potential health implications. This research will contribute to a better understanding of bio-aerosol dynamics in rural areas and provide a scientific basis for future air quality monitoring and management strategies. (Line 84 to 90).

3. Figure 1: Why was the Andersen sampler operated in only nine square grids?
4. RE) Thanks to the reviewers' question. Why did we choose nine grids in the village for sampling with the Andersen six-stage sampler? Because the initial measurements from the portable bioaerosol detector showed they represented areas at the highest potential risk for Enterobacteriaceae pollution. These areas had diverse land uses, including residential zones near livestock farming and waste disposal sites. Due to resource limits, the Andersen sampler was only used in these nine grids. We've added this to the revision.

To determine Enterobacteriaceae concentrations and analyze their escape pathways, we selected nine square grids within the village for sampling with an Andersen six-stage impact sampler. These grids were chosen because they represented areas with the highest potential risk of Enterobacteriaceae contamination, based on preliminary measurements with the portable bioaerosol alarm, and included a range of land uses, including residential areas near livestock farming and waste disposal sites. While the Andersen sampler measurements were limited to these nine grids due to resource constraints, the portable bioaerosol alarm was used to provide a broader picture of bioparticle concentrations across the entire study area. (Line 118 to 126).

4. Table 1, row 1: What do you mean by ‘Air Quality’? Is this the total mass concentration of particulate matter? How was this measured, and how was the mass data calculated?
5. RE) Thanks to the reviewers' advice. Air quality refers to AQI (Air Quality Index). The AQI values in this study were determined by the weather forecast at the time. We have noted this in the revised manuscript in the Table 1. Summary of environmental conditions.

Air quality refers to AQI (Air Quality Index). The AQI values in this study were determined by the weather forecast at the time. (Line 132 to 134).

5. Section 2.3: How many samples were collected, and for what durations? Please include this information in the table and figures. How many BM3001 samplers were utilized? How many times was sampling repeated within individual grids? How did the authors ensure that bioparticles remained consistent during their movement between grids, and how were repeated samples comparable when not collected simultaneously? What was the sampling height for BM3001?
6. RE) Thanks to the reviewers' question. For each sampling session, we use one device to collect data from about 2500 locations, with each location sampled for 30 seconds. The value for each location is determined by the mean of multiple measurements. To maintain consistency in bioparticle movement between grids, we keep the daily sampling sequence consistent. The BM3001 bioaerosol alarm was positioned at a height of 1.5 meters above the ground, which corresponds to the average breathing height of an adult. We have added relevant content in the revised manuscript.

A total of approximately 2500 samples were collected across the 81 grids using a BM3001 bioaerosol alarm. Each sampling event lasted for 30 seconds. This device records data every 2 seconds on average. The concentration at each sampling site was determined by averaging 15 data points. To minimize the impact of temporal variations in bioparticle concentration across multiple sampling sites, we maintained a consistent sampling sequence daily. The BM3001 bioaerosol alarm was positioned at a sampling height of 1.5 meters above the ground, which corresponds to the average breathing height of an adult. (Line 153 to 160).

6. Lines 132 – 139: Please provide references for studies that validated this bioaerosol sampler or utilized it in field studies. If the manual for this sampler is available online, please provide the link.
7. RE) Thanks to the reviewers' advice. As the BM3001 Bio-aerosol Alarms is newly launched, no scholars have published relevant articles on it yet. However, there are cases of it being used to assess bio-safety in public places. For reference, please visit: https://www.htnova.com/portal/case/detail/id/222/type/1/aid/7/l/zh-cn.html.
8. Lines 193, 195, and 202: Please convert the data into numbers per cubic meter of air. Additionally, make this conversion for other similar values throughout the entire manuscript.
9. RE) Thanks to the reviewers' advice. We have carefully considered the suggestion to convert the units from particles/L to particles/m³. However, after thorough deliberation, we have decided to retain the original units of particles/L. Here are the reasons:

While we recognize that particles/m³ is a commonly used unit for indicating the concentration of particles in air, we have decided to keep the original unit of particles/L. Converting from particles/L to particles/m³ (1 particles/L = 1000 particles/m³) would result in much larger numerical values. This could create an impression of extremely high concentrations, which might be misleading and cause unnecessary concern. Using the original unit of particles/L provides a more intuitive understanding of the actual concentration levels.

Moreover, retaining particles/L ensures that the data presentation aligns with the methodology and instrumentation used in the study. We believe that keeping our original units offers a clear and accurate representation of our data while still allowing for easy comparison with other studies. We hope the reviewer understands our rationale.

8. Lines 379 – 389: Can these reproductions occur during the brief sampling period in the air? Please provide a suitable reference to support your statements in this paragraph.
9. RE) We thank the reviewers for their insightful comments. While significant microbial reproduction is unlikely during the short duration of air sampling, we acknowledge that the reproductive potential within source environments (such as livestock manure and waste) influences the overall bioparticle load in the air. Under favorable conditions like high temperature and humidity, microorganisms can rapidly proliferate, leading to an increase in bioparticle concentrations over time. This point has been addressed in the manuscript.

Bacteria engage in swift metabolism and division under nutrient-rich, warm, and humid conditions, whereas the germination and growth of fungal spores depends on suitable humidity and the presence of organic matter (Nguyen et al., 2021; Piecková, 2012; Wang and Levin, 2009). As a result, microorganisms proliferate rapidly under favorable conditions such as high temperatures and high humidity, leading to an increase in the concentration of biological particles over time (Line 413 to 419).

9. Figure 8: This figure is intriguing, but given the limited data collected from nine grids in the village, these findings may not be reliable. Please provide more information in the methods section to justify the statistical rigor of your sample size.
10. RE) Thanking the reviewers for their advice. To determine Enterobacteriaceae concentrations and analyze their escape pathways, we selected nine square grids within the village for sampling with an Andersen six-stage impact sampler. We acknowledge that the Enterobacteriaceae sampling was limited to nine grids due to resource constraints. However, these grids were strategically selected to represent areas with the highest potential risk of Enterobacteriaceae contamination, based on preliminary measurements with the portable bioaerosol alarm, and to include a range of land uses, including residential areas near livestock farming and waste disposal sites. While this limited sample size restricts the statistical power of our analysis, we believe that the detailed analysis of these representative grids provides valuable insights into potential Enterobacteriaceae escape pathways. We have also added to this section in the Material Methods section.

To determine Enterobacteriaceae concentrations and analyze their escape pathways, we selected nine square grids within the village for sampling with an Andersen six-stage impact sampler. These grids were chosen because they represented areas with the highest potential risk of Enterobacteriaceae contamination, based on preliminary measurements with the portable bioaerosol alarm, and included a range of land uses, including residential areas near livestock farming and waste disposal sites. While the Andersen sampler measurements were limited to these nine grids due to resource constraints, the portable bioaerosol alarm was used to provide a broader picture of bioparticle concentrations across the entire study area. (Line 118 to 126).

Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

This study is interesting because the authors collected some data from a village in China on atmospheric bioparticles and tried to enhance our understanding of the characteristics and transport patterns of bioparticles with reference to temperature, relative humidity, atmospheric pressure, wind speed, wind direction, UV, and other particulate matter. They also recorded the weather conditions. They used a new type of real-time bioaerosol monitor that uses Mie scattering and ultraviolet-induced fluorescence (UV-LIF) methods to characterize bioaerosols.

Introduction, lines 84 – 92: Please clearly outline the study's objectives and omit the risk assessment and awareness-raising issues, as they were not documented in the article.

Figure 1: Why was the Andersen sampler operated in only nine square grids?

Table 1, row 1: What do you mean by ‘Air Quality’? Is this the total mass concentration of particulate matter? How was this measured, and how was the mass data calculated?

Section 2.3: How many samples were collected, and for what durations? Please include this information in the table and figures. How many BM3001 samplers were utilized? How many times was sampling repeated within individual grids? How did the authors ensure that bioparticles remained consistent during their movement between grids, and how were repeated samples comparable when not collected simultaneously? What was the sampling height for BM3001?

Lines 132 – 139: Please provide references for studies that validated this bioaerosol sampler or utilized it in field studies. If the manual for this sampler is available online, please provide the link.

Lines 193, 195, and 202: Please convert the data into numbers per cubic meter of air. Additionally, make this conversion for other similar values throughout the entire manuscript.

Lines 379 – 389: Can these reproductions occur during the brief sampling period in the air? Please provide a suitable reference to support your statements in this paragraph.

Figure 8: This figure is intriguing, but given the limited data collected from nine grids in the village, these findings may not be reliable. Please provide more information in the methods section to justify the statistical rigor of your sample size.

 

Author Response

1. It is interesting work, but more statistical assessment is required (significance testing for the comparisons of particle numbers, as well as clarification of methods - averaging time of sampling, inlet size range of the instrument used, fluorescence wavelengths used - fluorescent particle monitors are prone to interference from non-biological organic compounds (could the big rise during cold weather reflect solid fuel burning?) The increase in particle count under hazy conditions also suggests to me that interference by secondary organic particles is a possibility.
2. RE) We thank the reviewer for their valuable suggestions. We have added further details regarding the sampler to the revised manuscript. However, given the considerable natural variability observed in our bioparticle concentration data, we have prioritized descriptive statistics, effect sizes, and visual representations to highlight meaningful trends and practical implications for human exposure. We believe this approach is more informative for this exploratory study.

We also acknowledge the potential for interference from particles released during wood or coal burning in cold weather, which could trigger the BM3001's fluorescence detector. While we lack specific data to quantify the contribution of these non-biological sources, we recognize their potential influence on our results. Future studies should consider techniques such as PCR and metagenomics for a more comprehensive assessment of bioaerosol composition. We have added a discussion of these points to the Conclusions and Prospects section of the manuscript.

The instrument has an inlet size range of 0.5-10 μm and uses an excitation wavelength of 400 nm. (Line 141 to 142).

In the actual air environment, cigarette particles, paper dust, pollen, kaolin, etc. will also produce intrinsic fluorescence, so in the process of use, the instrument should try to avoid inhaling these fluorescence interferences in order to reduce the false alarm rate. (Line 148 to 151).

A total of approximately 2500 samples were collected across the 81 grids using a BM3001 bioaerosol alarm. Each sampling event lasted for 30 seconds. This device records data every 2 seconds on average. The concentration at each sampling site was determined by averaging 15 data points. To minimize the impact of temporal variations in bioparticle concentration across multiple sampling sites, we maintained a consistent sampling sequence daily. The BM3001 bioaerosol alarm was positioned at a sampling height of 1.5 meters above the ground, which corresponds to the average breathing height of an adult. (Line 153 to 160).

Future research should address limitations in measurement techniques and potential interference from non-biological organic compounds. While conventional methods may underestimate bioaerosol concentrations, fluorescent monitors are prone to interference from sources like solid fuel burning and secondary organic particles. Therefore, we recommend employing advanced analytical techniques such as PCR and metagenomics to differentiate biological from non-biological particles and developing real-time sensors less susceptible to interference. Integrating multiple measurement methods will provide a more comprehensive understanding of bioaerosol dynamics. (Line 513 to 520).

Author Response File: Author Response.docx

Round 2

Reviewer 3 Report

Comments and Suggestions for Authors

The authors have adequately addressed the previous critiques. However, some minor changes are still needed. Please provide more information on the DJI Mini 3 drone, as the current explanation of its photographic methods used to identify the 111 risk point sources in the selected village is unclear. This section requires further description and explanation. Additionally, I believe that the data should be presented in cubic meter units to facilitate easier comparison with other published studies and standards.

Author Response

Point-to-point responses:

Re manuscript: aerobiology-3576818

Title: Bioparticle Sources, Dispersion, and Influencing Factors in Rural Environmental Air

The replies to the reviewers’ comments are detailed below in BLUE. All changes can be viewed in the attached document with the BLUE font.

 

COMMENTS FROM THE EDITOR AND/OR REVIEWERS

Reviewer #4:

1. The authors have adequately addressed the previous critiques. However, some minor changes are still needed. Please provide more information on the DJI Mini 3 drone, as the current explanation of its photographic methods used to identify the 111 risk point sources in the selected village is unclear. This section requires further description and explanation. Additionally, I believe that the data should be presented in cubic meter units to facilitate easier comparison with other published studies and standards.
2. RE) Thank you for the reviewers' suggestions. In this study, the DJI MINI 3 drone was used for high-altitude photography to obtain top-down images, analyzing the distribution of village houses and road layouts. Field surveys were the main method for identifying and marking risk spots on these images, so the drone served an auxiliary role. We've revised the manuscript to clarify this.

Regarding units, after careful discussion, we initially tried cubic meter units but decided to retain the original particles per liter unit. Converting to particles per cubic meter (1 particle/L = 1000 particles/m³) would magnify the numerical values, potentially misleading readers into thinking the concentrations were extremely high and causing unnecessary worry. Using particles per liter offers a more direct view of actual concentration levels and aligns with our methods and instruments. We believe this choice ensures clear data presentation and easier comparison with other studies. We hope the reviewers understand our reasoning.

Exploit the DJI MINI 3 drone to carry out high-altitude photographic tasks, ob-taining top-down images. Analyze the distribution of village houses and the layout of roads. Conduct field investigations to identify and mark risk spots on the top-down images. This determines the risk sources in a typical village for subsequent data analysis and figure plotting. (Line 111 to 115).

Author Response File: Author Response.docx