Supervised Machine Learning Approaches for Predicting Key Pollutants and for the Sustainable Enhancement of Urban Air Quality: A Systematic Review

Round 1

Reviewer 1 Report

The authors have chosen very interesting topic, however, this review has certain limitations which make this article weak and requires major revision. The comments are as below:

1. Modify the title of manuscript keeping in view about objectives of paper.

2. In abstract, the authors should highlight the importance of frequently employed methods in air quality in real-world and how it helps in society.

3. In the section Introduction, add the importance of other qualitative tools which can be used in air quality other than ML. Moreover, in the end of Introduction, add the motivation of the study and mention the objectives of this review.

4. In the section "Related Works", add the application of these models to city planning and industrial planning too.

5. Details of other models in air quality assessment and prediction are required.

6. How these models help in climate change and air pollution mitigation?

7. How these methods are tuning with Sustainable Development Goals?

8. Conclusion should be focused towards air quality and climate change mitigation and in coherence with SDGs.

English Language should be checked properly, particularly grammar and punctuations.

Author Response

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Author Response File: Author Response.docx

Reviewer 2 Report

This study provides a comprehensive review of recent advancements in air quality research, focusing on the application of supervised learning algorithms. The manuscript discusses the identification of key pollutants and highlights the prominence of specific ML techniques in addressing air quality concerns. The study aims to contribute to proactive and sustainable strategies for combating urban air pollution and enhancing global air quality overall. However, the format of the manuscript is confusing, with many grammatical errors in English. In addition, the structure of the manuscript is also confusing, and the authors should consider categorizing and analyzing the papers according to the types of pollutants studied in different papers on the basis of distinguishing modeling methods when reviewing them. At the same time, the authors can also make quantitative comparisons of the prediction accuracy and computational resource overhead of different models to deepen the research depth of the study. Overall, the manuscript has the following problems with detail:

Formatting:

1.     The chemical abbreviation for carbon monoxide in Line 14 of the abstract should be "CO, not CO₂";

2.     In Line 60, "un section 2" should be "in section 2".

3.     In the heading of Line 134, "assessment" should be "Assessment";

4.     In Line 146, "urban quality" should be "urban air quality";

5.     In Line 150, "wit" should be "with";

6.     In Line 354, the heading of Section 4.3.4 is not spaced as it should be from the paragraph above and below;

7.     The font and font size of the content in Lines 370 through 374 are significantly inconsistent with the rest of the manuscript;

8.     Is the number in front of each reference mark in the first column of Table 1 on Page 14 a line number? Why does it appear inside the table?

9.     The content of Lines 441 and 442 should belong to the same paragraph, so why are the authors subparagraphing here?

10.  The content of Lines 504 and 505 should also belong to the same paragraph, so why did the authors make another subparagraph?

11.  The numerical subscripts in the chemical formulas of all pollutants in the manuscript are not given in subscript format.

Content:

1.     What occupancy rate is meant by "examines the prediction of occupancy" in Line 86?

2.  What is the relationship between "hospital admissions" and "Acute Respiratory Infections" in the third column of the first row of Table 1?

The authors still need to polish the English writing of this manuscript because there are many obvious grammar errors.

Author Response

Please see the attachment

Author Response File: Author Response.docx

Reviewer 3 Report

The objectives of the study are clearly articulated in a well-defined manner. The overall structure of the manuscript is well organized, with a comprehensive description of the methods used. The authors have effectively presented the objectives they intend to achieve with this article, therefore it can be published in its current form.

Dear Authors, I have reviewed your paper titled " Supervised learning in Assessing Urban Air Quality review" and I appreciate the significance of the topic, which is of general interest. The objectives of the study are clearly articulated in a well-defined manner. The overall structure of the manuscript is well organized, with a comprehensive description of the methods used and a clear presentation of the results, therefore it can be published in its current form.

Author Response

Please see the attachment

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

The authors have significantly answer the questions and I agree with their justifications and answers. They have also confirmed that they added all required matter in the manuscript.

Author Response

Thank you very much for taking the time to review this manuscript I wanted to express my sincere gratitude for your thoughtful and constructive comments on my paper. Your insights and suggestions played a pivotal role in improving the quality of the manuscript, and I am pleased to inform you that your recommendations have been carefully incorporated into the latest revisions.

I appreciate the time and effort you dedicated to reviewing my work and am thrilled to learn that the revisions were sufficient for the approval of the paper. Your expertise and feedback were invaluable throughout this process, and I am grateful for the opportunity to benefit from your insights.

I look forward to any additional guidance you may have in the future and hope that this paper contributes positively to the field. Thank you once again for your time, support, and commitment to advancing academic excellence

Reviewer 2 Report

The authors have carefully reviewed the entire text and corrected formatting and content issues from the first edition. In addition, the manuscript has been made more comprehensive and clearer by the author's polishing of the manuscript. In summary, the content of the manuscript has been greatly improved compared to the first edition. Therefore, I recommend receiving the manuscript for publication.

However, before the manuscript is published, the authors need to be aware of the inconsistency between the fonts in Table 1 and the fonts in the text.

Author Response

I wanted to express my sincere appreciation for your thorough review of our manuscript and for acknowledging the improvements made in the revised edition. Your insightful comments were incredibly helpful, and we are delighted to inform you that we have carefully addressed the formatting and content issues mentioned in the first edition.

The manuscript has undergone a meticulous revision process to enhance its comprehensiveness and clarity. We believe that the changes made contribute significantly to the overall quality of the paper.

Regarding the inconsistency between the fonts in Table 1 and the text, we have duly noted your observation. I am pleased to confirm that this issue has been rectified, and the fonts are now consistent throughout the manuscript.

We are grateful for your guidance and appreciate the time and effort you invested in reviewing our work. Your recommendation for publication is invaluable to us, and we look forward to the opportunity to contribute to the field