Multi-Scale Analysis of PM2.5 Concentrations in the Yangtze River Economic Belt: Investigating the Combined Impact of Natural and Human Factors
Chaitanya Pande
Round 1
Reviewer 1 Report
In this article, the authors used a spatial analysis method to reveal the spatial and temporal characteristics of PM2.5 and its spatial clustering patterns using a geographic information system (GIS) platform, combined with 13 remote sensing and statistical data from 2000 to 2020. The results show that PM2.5 concentrations exhibit significant spatial agglomeration characteristics, and most urban clusters are highly polluted areas. In addition, the variation of PM2.5 concentration is influenced by seven factors together, including secondary industry, urban built-up area, population density, annual precipitation and NDVI. Here are some suggestions for the authors to improve this manuscript.
1. The spatial and temporal variation of natural and human factors is also to be shown.
2. Many studies used the observed PM2.5 data released by the Chinese Ministry of Environmental Protection, while this study used the grid PM2.5 data. It is recommended that the authors verify the gridded data against the observed data to ensure the reliability of the data. In addition, it should also be pointed out how the grid PM2.5 data used in the study were generated?
3. In section 2.3, the author mentions spatial spillover effects. Could the author provide additional information on spatial spillover effects and their related research applications?
4. In section 2.3.1, the author mentions the model selection process and testing process. Could you provide more detailed explanations in the methodology section?
5. In section 2.3.4, the author mentions that the model selection process consists of three steps. Could the author explain the reasons for choosing spatial econometric models and the criteria and basis for selecting SPLM, SPDM, and SPEM models?
6. In section 2.3.5, the author mentions the use of the P.D.E. method to decompose the local effects, spillover effects, and total effects of each factor. Could you provide more detailed explanations about the P.D.E. method and explain how to interpret these effects?
7. Regarding the spatial distribution map in Figure 7, could further discussion be provided on the reasons for the formation of this spatial distribution, such as geographic factors, population distribution, or differences in economic activities?
8. In section 3.3.1, likelihood ratio estimation (LR) and Wald statistic are used as two indicators to evaluate SPDM. Could you explain the reasons for choosing these two indicators?
9. In section 3.3.2, it is mentioned that PM2.5 concentration exhibits significant positive spatial spillover effects, and the reduction of PM2.5 concentration in one city will significantly influence the PM2.5 concentration in other cities through geographical correlation. Does the term "correlation influence" refer to the mutual influence between different cities? Could the author provide an explanation based on physical mechanisms and include relevant references?
10. Subsection 4.1 of the article states that urban sprawl reduces PM2.5 concentrations in the study area. The authors are requested to provide a more detailed explanation of this observation.
11. Why do natural factors and anthropogenic factors have a more diverse impact on PM2.5 concentration in YRDUA and YRMUA, while in CCUA they are primarily influenced by anthropogenic factors?
Author Response
Dear editor and reviewers, Thank you very much for handling and reviewing the submission, which is very much appreciated. The comments and suggestions are very helpful for revising and improving the manuscript. All comments have been carefully studied. Responses/explanations have been provided. Revisions have been made and all modified content is highlighted in red colour. The main corrections in the paper and the responses to the comments are as followings. We hope they can meet your requirements. Please see the attachment.Author Response File: 
Author Response.docx
Reviewer 2 Report
Paper is interesting, I have accepted the article with major revision. Details comments attached in PDF file .
Comments for author File: 
Comments.pdf
Author Response
Dear editor and reviewers, Thank you very much for handling and reviewing the submission, which is very much appreciated. The comments and suggestions are very helpful for revising and improving the manuscript. All comments have been carefully studied. Responses/explanations have been provided. Revisions have been made and all modified content is highlighted in red colour. The main corrections in the paper and the responses to the comments are as followings. We hope they can meet your requirements. Please see the attachment.Author Response File: Author Response.docx
Round 2
Reviewer 1 Report
We thank the authors for their acceptance of the review comments and for their positive response.
However, there is still a reserved issue concerning the precision of the PM2.5 data.
I suggest that the authors download the PM2.5 data provided by the Ministry of Ecological Protection of China in the study area. Then, compare the observed data with the gridded data and calculate the precision of the particulate matter data in the study area instead of using the R2 from References.
The results can be displayed in a probability density scatter plot.
Author Response
Dear editor and reviewers,
Thank you very much for handling and reviewing the submission, which is very much appreciated. The comments and suggestions are very helpful for revising and improving the manuscript. All comments have been carefully studied. Responses/explanations have been provided. Revisions have been made and all modified content is highlighted in red colour. The main corrections in the paper and the responses to the comments are as followings. We hope they can meet your requirements. Please see the attachment.
Author Response File: Author Response.docx
Reviewer 2 Report
I have accepted the article for publication..
Author Response
Thank you for your recognition and support, it is very encouraging to us.
