Review Reports - Study on Spatial Changes in PM<sub>2.5</sub> before and after the COVID-19 Pandemic in Southwest China

Round 1

Reviewer 1 Report (Previous Reviewer 2)

The authors have answered most of my questions however, they need to state that vegetation is not fully covered and that the current study does not reflect the outcome after 2021.

Author Response

Dear Expert: Thank you for your valuable comments and would like to respond to your questions below:

The following answers are given to the question of vegetation selection: In this study, a normalized vegetation index was selected to represent vegetation change, which is a comprehensive indicator of vegetation coverage. In the study, the monthly MOD13A2 data was selected as one of the variables for model construction, which can represent the monthly vegetation coverage changes, thereby representing quarterly and annual vegetation changes.

For the results after 2021: the reason for not discussing after 2021 is the following two aspects: first, the time frame of this study includes the year, and after 2021, most cities in China have a low degree of epidemic control and have almost returned to the pre-epidemic development level; The second is that this paper was written from June 2022, when complete observation data for 2022 was lacking, so the results after 2021 were not discussed after comprehensive consideration.

Reviewer 2 Report (Previous Reviewer 1)

Some issues I concerned have been addressed by the authors. However, the innovation of this paper is still limited. Many related studies have discussed this topic before, and the necessity of this paper should be strengthened. Two issues I mentioned in first review have not been well clarified.

The discussion section needs to be further improved as follows:

1. The relationship between COVID-2019 and PM 2.5 should be considered.

2. The mechanism of PM2.5 spatiotemporal distribution feature should be analyzed.

Author Response

Dear Expert: Thank you for your valuable comments and would like to respond to your questions below:

For questions about the relationship between COVID-19 and PM2.5: On the one hand, it may be due to the misunderstanding caused by the content in lines 40~47 of the introduction, which is intended to prove the necessity of PM2.5 research in the context of COVID-19 events rather than to focus on its relationship; On the other hand, although the Chinese government will release COVID-19 infection data and case fatality rates in some cities, the southwest region is too large to obtain sufficient data, so the relationship between COVID-19 and PM2.5 is not specifically discussed due to data availability limitations.

Reviewer 3 Report (New Reviewer)

Manuscript Number; atmosphere-2243226

Title; Study on spatial changes in PM_2.5before and after the COVID-19 pandemic in Southwest China

Although the topic is of interest to the Scientific community, before consideration for publication, this paper should be improved. Authors should reconsider the main objective of the paper according to the content. They should try to revise the synthesis and emphasize the study's main findings and avoid long sentences. Furthermore, authors should avoid drawing risky conclusions.

Evaluation; Minor Revision.

1. Keywords; Must to revised; spelling and avoiding general and plural terms and multiple concepts (avoid, for example, 'and', 'of').

Unsuitable >>> control

2. In the main text, many numeric data are given with too many significant figures; 2 significant figures suffice, and 3 suffice in case the first significant figure is "1".

e.g., abstract 32.08, 26.52, and 28.60 μg/m³should be 32.1, 26.5, and 28.6 μg/m³

3. Line 102; 1.14 million KM² should be km²

4. Line 123-124; The time interval was 1 hour. Any abnormal data less than 2 μg/m³ and more than 200 μg/m³ were eliminated.

Please explain the criteria for the removal of some data.

5. All of the main text, typing errors, and subscripts (PM_2.5) should be checked.

6. Figures 6-9 need to improve. It is difficult to understand.

7. Conclusion; Final Considerations, please revise and combine them into only one section in the conclusion. The findings could be further developed, there is a lot of interesting data in the article.

Author Response

Evaluation; Minor Revision.

Dear Expert: Thank you for your valuable comments and would like to respond to your questions below:

Question1.Keywords; Must to revised; spelling and avoiding general and plural terms and multiple concepts (avoid, for example, 'and', 'of').。Unsuitable >>> control。

Answer: In the Keywords section, keywords with unknown meanings such as spatial change and post epidemic era have been removed. Now changed to: COVID-19 control, PM2.5 estimates, GTWR, AOD

Question 2.In the main text, many numeric data are given with too many significant figures; 2 significant figures suffice, and 3 suffice in case the first significant figure is "1". e.g., abstract 32.08, 26.52, and 28.60 μg/m3 should be 32.1, 26.5, and 28.6 μg/m3

Answer: The number of valid digits has been modified in the text，For example, for PM2.5, the effective digits have been changed to 1, while for AOD, NDVI, and other data, two digits have been reserved.

Question 3. Line 102; 1.14 million KM2 should be km2

Answer: Due to a previous oversight that overlooked formatting, it has now been revised.

Question 4. Line 123-124; The time interval was 1 hour. Any abnormal data less than 2 μg/m3 and more than 200 μg/m3 were eliminated. Please explain the criteria for the removal of some data.

Answer: Due to a previous oversight that overlooked formatting, it has now been revised.

Question 5. All of the main text, typing errors, and subscripts (PM2.5) should be checked.

Answer: Due to a previous oversight that overlooked formatting, it has now been revised.

Question 6. Figures 6-9 need to improve. It is difficult to understand.

Answer: Changes have been made in the figure section

Question 7. Conclusion; Final Considerations, please revise and combine them into only one section in the conclusion. The findings could be further developed, there is a lot of interesting data in the article.

Answer: Redescripted in the Conclusion section (lines 428-500)

Reviewer 4 Report (New Reviewer)

This study provided a geographically and temporally weighted regression (GTWR) model to invert the spatial distribution of PM2.5 by combining PM2.5 on-site monitoring data and related driving factors, then compared and analyzed the spatial changes before and after the COVID-19 pandemic. Results demonstrated the ability of GTWR model and accuracy. This study provided the decision-making basis for promoting atmospheric environment governance and formulating pollution prevention and control plans. This is an interesting topic, with a relatively well-written introduction and method section. The results were documented in a sufficiently well-written presentation. Through checking the whole content, the revised manuscript did make a significant revision, however, some important comments should be clarify in a more detailed way.

(1) The authors should check the unit of all the parameters used in the table, the pictures, and some sections, e.g., table 3, table 4. The unit was lost.

(2) In the pictures, e.g., figure 2 and figure 3, the sub-pictures have to be used and listed in a sequence. The title of the subpicutres should be used, e.g., (1) (2), otherwise, reviewers cannot clearly understand the details.

(3) In the section, 2.3.3 model validation. Seem like it is only the evaluation indices, instead of the validation details. Please revise that. Moreover, R2, MAE, and RMSE values were normally pointed out first or explained first.

(4) Compared to the existing findings mentioned in the conclusion, reviewer strongly suggests the authors provide a separate discussion section and note the limitation of this study and further considerations, e.g., which parameters were highly related to the daily/monthly/season PM2.5 variations.

Author Response

Dear Expert: Thank you for your valuable comments and would like to respond to your questions below:

Question 1. The authors should check the unit of all the parameters used in the table, the pictures, and some sections, e.g., table 3, table 4. The unit was lost.

Answer: The units in the text have been added and modified

Question 2. In the pictures, e.g., figure 2 and figure 3, the sub-pictures have to be used and listed in a sequence. The title of the subpicutres should be used, e.g., (1) (2), otherwise, reviewers cannot clearly understand the details.

Answer: The tables and figures in the text have been renumbered, for example, Figures 2 3 and 4 have been numbered with letters, and the lower right corner of Figures 5 and 7 has been distinguished by year and quarter

Question 3. In the section, 2.3.3 model validation. Seem like it is only the evaluation indices, instead of the validation details. Please revise that. Moreover, R2, MAE, and RMSE values were normally pointed out first or explained first.

Answer: For the model validation section, section 2.3.3 of the original text has been deleted and moved to section 3.2. In section 3.2, indicator explanations and result analysis have been performed

Question 4. Compared to the existing findings mentioned in the conclusion, reviewer strongly suggests the authors provide a separate discussion section and note the limitation of this study and further considerations, e.g., which parameters were highly related to the daily/monthly/season PM2.5 variations.

Answer: The conclusion is analyzed (Lines 428-500). The shortcomings of the article are discussed on line 476.

Author Response File: Author Response.docx

Round 2

Reviewer 3 Report (New Reviewer)

This revised version is suitable for publication.

This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.

Round 1

Reviewer 1 Report

Air pollution is a hot issue in the field of environment and epidemiology which has received more and more public concerns. And analyzing the relationship between air pollution and epidemics is crucial to human health. So, I believe that this problem selected by the authors of the present draft will attract lots of readers to follow. However, the innovation of this paper is limited, and some issues in the draft need to be addressed carefully before publication. I express my concerns as follows.

1. Introduction section

The significance and innovation of this study need to be further expressed.

Line 45-47: Some important literatures in term of this topic were neglected. I strongly suggest that authors conduct a completely review.

Line 74-75: meteorological influential factors of PM2.5 has been discussed by many studies. Please supplement sufficient references.

2. Materials and methods

Line 86: The necessity of choosing Southwest as study area should be strengthened.

Line 105: The data pretreatment needs to be strengthened. For example, what is the data fusion measure in this study? Data quality should be assessed before using.

Line 125: Why did the authors select GTWR model? I did not find any explanation. The suitability of GTWR in this study need to be clarified.

3. Results and discussion

Line 208: There are so many PM2.5 products globally. A precision comparison between this work and existing products should be supplemented.

Line 223: the data units in Figure 4 5 6 7 8 9 & table 1 were missed. Figure and table quality of the entire draft can be improved.

The discussion section needs to be further improved as follows:

1. The relationship between COVID-2019 and PM 2.5 should be considered.

2. The mechanism of PM2.5 spatiotemporal distribution feature should be analyzed.

Reviewer 2 Report

The authors of the entitled manuscript “Study on spatial changes in PM2.5 before and after the control of COVID-19 pandemic in Southwest China” presented an analysis of air quality changes in 2019, 2020 and 2021 covering the pandemic using remote sensing of particulate matter 2.5-micron om Southwest China. I found the topic is very relevant to the pandemic; however, I have the following points:

The authors mentioned in their manuscript that the data is before and after the pandemic, which is not accurate for after the pandemic as China till now is suffering from the pandemic. I think the authors need to address this point as it is the main concept of their study.
Figures 4, 7, 8 and 9: what is the purpose of this type of graph to present the data? It needs to be more straightforward for the readers to track the changes of PM2.5 during these periods for these cities.
The authors claim that they have addressed the meteorological, vegetation and topographic factors after the pandemic control from natural influencing factor 2021; however, based on my knowledge China imposed lookdowns in 2022, and I believe these types of lookdowns got a continuous impact started from 2020. Why is this point not considered?
I could not see any mention of vegetation outcomes in this study. However, it is mentioned in conclusion.
Did the author use their sensors or just outdoor sensors located as shown in Figure 1? What is the sensitivity of these sensors? Please provide more information about the sensors, such as brand and quality. Please add this in lines (108-119) under the “Data” section.
Figures 4 and 5 illustrate the PM2.5 concentration in southwest China. I would like the authors to expand the process used to obtain these graphs to benefit the readers.

General comments and corrections are required.

Under the Introduction section, line 45: what is the decrease? Please provide the ration.
Line 56: Please define AOD.
Line 273: it should be Table 3, not Table 1.
Please improve the PM and Units and Lines subscripts: Lines: 226 and 253.
Line 163 required some correction after [41, 42].

Overall, it is a good topic and covers a reasonable period of the pandemic; however, mentioning this study after the pandemic is not an accurate sentence for China, and they are still treating it as a pandemic till the end of 2022.

Reviewer 3 Report

The manuscript investigates the spatial and temporal variations in the PM2.5 concentration over Southwest China before, during, and after the COVID-19 lockdown using mathematical approach. However, the topic regarding effects of lockdown on the air quality is not interesting anymore. There is no new finding in the current manuscript. Furthermore, the entire manuscript looks like a plain report with no comparison for the model and pollution results with other studies. In particular, there is no citation throughout section 3. Unfortunately, a rejection is suggested.

Minor comments:

1. Correction is lines 68, 76, 163, 208, 223, 244, 273, 275, 289, 302, 312, 321, 338.

2. Numbering of figures is incorrect.

3. Letter “a” after year in three figures on pages 7-8.

4. Missing space between number and letter.

5. Missing reference 22 in line 60.

6. Missing citations in lines 71-76.

7. Independent variables are unclear in section 3.2.