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Article
Peer-Review Record

The Impact of Sustained Exposure to Air Pollutant on the Mental Health: Evidence from China

Sustainability 2022, 14(11), 6693; https://doi.org/10.3390/su14116693
by Jin Sun, Chuntian Lu and Jinchen Xie *
Reviewer 1:
Reviewer 2: Anonymous
Reviewer 3: Anonymous
Sustainability 2022, 14(11), 6693; https://doi.org/10.3390/su14116693
Submission received: 10 April 2022 / Revised: 20 May 2022 / Accepted: 25 May 2022 / Published: 30 May 2022
(This article belongs to the Special Issue Air Pollution and Environmental Sustainability)

Round 1

Reviewer 1 Report

Dear Authors,

I advise to re-write the paper and re-submit it again. You have valuable data, but further explanation about the data and the statistical treatment is needed. The paper is not very readable and there are many English errors and other flaws.

 Some comments:

- All acronyms must the presented the first time they appear such as you write for “Hierarchical Linear Models (HLM)”. It does not happen with RD, BMI, OLS, …  

- Line 24 – “This paper finds that a 10- 24 μg/m3 increase in air pollutant concentrations leads to 4.9-unit decrease in the mental health.” Is this true in all PM10 concentration range? Is it a linear decrease? I don´t believe.

- Line 28 – refer which coefficient. There are many..

- Line 29 - female instead of felame

- References are indicated simultaneously by numbers and by “author name, year”. Choose one reference system.

- Line 92 -“The results of the RD regression indicate that a 100 μg/m3 rise in air pollutants (PM10) would lead to a 49-unit significant decrease in mental health”. This decrease is different from the above one mentioned. Why?

- you don´t explain why the data is split in north and south according to the river. Is that river an important pollution factor?

- Figure 1 – you have a mixture of more and less polluted cities in both regions (N and S), although more cities more polluted are in the N region. Why that boundary?

- Why didn’t you run the statistical analysis clustering the data according to the pollution PM10 concentrations for eg.? Surely better and precise conclusions would be drawn…

- I think the population and the samples must be better described. Is this sample representative?

- Are you sure that covid did not influence your data? It represents 20% of your years range, and probably, people were held at home all days and nights...

 

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

A follow-up of the statistical data for the years 2020-2022 would be interesting takeing into account the pandemic situation. Does the situations was mantained on both sides of the river or something has changed?

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 3 Report

The manuscript merits publication to Sustainability if the authors take into consideration some remarks:

  • The legend in the graphics is not perfectly noticeable - needs to be improved (eg increasing size);
  • For a better understanding of the text, a list of abbreviations is needed (eg: RD, CESD, CFPS);
  • Do not forget to use the underwritten text, eg.: M10, NO2, SO2, O3

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

Dear authors,

I am satisfied with your answers to my concerns and with the new information and statistical tests you added to the manuscript. Now I recommend it to be published, only after some minor revision.

Some recommendations:

Line 24 (and in more 6 other places)

-         When indicating cubic meter, the “3” should be superscript.

Line 36

- the table of Abbreviations and Acronyms should be called Acronyms only.

- in this table, there is no need to indicate PM10, NO2, SO2 and O3. I think everyone knows.

- normally in this type of lists, the acronyms are indicated following the alphabetic order.

Line 128 (and in other line)

- you refer NO2 as nitrogen dioxides (and it should be nitrogen dioxide, not in plural)

Lines 135 and 161

- These sections are both in the Methods section and there are some results presented here. They should be moved to the Results section as well as the sentences about the corresponding analysis.

Line 159 table 1

- The end of PM10, SO2, NO2 and O3 should be written as subscript.

- All means should have the corresponding standard deviation to assess their precision, that is, the values in the columns “Mean in southern group” “Mean in northern group” and “Mean difference” should have after “+- stdev value”.

Line 202 Table 2

- All means should have the corresponding standard deviation to assess their precision, that is, the values in the columns “Mean in southern group” “Mean in northern group” and “Mean difference” should have after “+- stdev value”.

Line 216

-         Please refer the statistical tests performed to compare means.

Line 290 table 3

-         It is presented “SI” and this acronym is not in the Acronym table.

Line 307

– Figure should be written singular.

Line 470

-         SEM should be replaced by structural equation modeling because it appears only here in the manuscript.

Line 471

-         Don’t you think you have more interesting conclusions to added in this section?

Author Response

 

Thank you for your comments on the manuscript, and I really appreciate your acknowledgment of our revision. We have addressed the details you raised, and in new manuscripts, use the 'tracking' .

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