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Peer-Review Record

Urban Air Quality Assessment by Fusing Spatial and Temporal Data from Multiple Study Sources Using Refined Estimation Methods

ISPRS Int. J. Geo-Inf. 2022, 11(6), 330; https://doi.org/10.3390/ijgi11060330
by Lirong Chen 1,2,*, Junyi Wang 3, Hui Wang 1,4 and Tiancheng Jin 5
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3: Anonymous
Reviewer 4: Anonymous
ISPRS Int. J. Geo-Inf. 2022, 11(6), 330; https://doi.org/10.3390/ijgi11060330
Submission received: 4 April 2022 / Revised: 24 May 2022 / Accepted: 27 May 2022 / Published: 31 May 2022

Round 1

Reviewer 1 Report

Please see the attached file.

Comments for author File: Comments.pdf

Author Response

Dear Reviewer,

Thanks for your comments. Please see the attached file for my responses.

Best regards.

Author Response File: Author Response.pdf

Reviewer 2 Report

In my opinion, the content of the paper is not clearly described making it practically incompressible. The introduction lacks of fundamental research and technological findings on the urban air quality assessment at high spatial resolution. Currently, the issue of capturing the spatial variability of air pollution at urban/street scale is addressed by mobile and opportunistic monitoring based on low cost air quality sensors. Previous research works, mentioned in the introduction, are not described clearly. The objective is not clear, the methodology is described very badly. I strongly suggest the authors to rewrite the paper, re-design the research, clarify some fundamental concepts on high resolution air quality assessment and the methods can be used, so that the reader can appreciate the research results  obtained

Author Response

Dear Reviewer,

Thank you for your valuable suggestions. We have tried our best to revise the paper.

Best regards.

Reviewer 3 Report

Overall, this is a solid manuscript that describes an incremental step in data analysis to improve the estimation of air quality in an urban area. Note that I am not an expert on the numerical and computation methods used in the study, so my comments below focus on the input to the model and then the subsequent analysis of the output.

Line 18: change the word “law.” Maybe observation?
Line 18-22: this complex sentence is too cumbersome. Split into at least two component ideas.
Line 36: insert “among” between “are” and “the.”
Line 61: need to clarify what you mean by “the coupling effects between multiple factors.”
Line 81: give an example of the purported “nonlinear association.”
Line 96: again, avoid the use of the word “law.”
Line 103: you have alluded to “attributes” and “factors” several times, but you should first define these more explicitly and also give some examples.
Line 119-120: this is the information that I asked for in the above comment. You should move this important information into the introduction.
Line 129-132: is this just one location? Or multiple met stations? In either case, should add to Figure 1.
Line 149: 38 what? Types of POIs?
Line 156-162: Land use type data are derived from image data. Explain why it is beneficial to have both datasets.
Line 192: “grid cells” should replace “grids.”
Line 218-221: First, the grammar here is hard to follow. The word “temporal” is used repeatedly and appears redundantly. Second, while Figure 3 helps, more information is necessary about the procedure. You should mathematically express the procedure using equations.
Line 229 (Figure 9): If I understand your model, the m x n window is 3 km on a side. In panel B, the underlaying data would typically not be a 1 km grid, correct? Or, is the underlaying data first averaged/interpolated to 1 km and then averaged with the 3 x 3 window? This representation would be better if the grid in B was not 1 x 1 km, as is typically the case with your data.
Line 230: I agree that 1.5 km is reasonable, but why is a 15-min walk relevant? I would instead talk about mixing and transport times of air pollutants. 
Line 242: How are missing data treated?
Line 245 (Table 1): Why do the POI data changed with hour? I would assume they are fixed. If they can vary, give some examples of this when you introduce POIs at line 147.
Line 259: missing figure number in parentheses. 
Line 313 (Figure 5): Again, while I like the visualization, this should also be described mathematically with equations.
Line 374-375: Only even values are given, and the max is at 6, not 7.
Line 455: Figure number is not correct. Maybe Figure 8, not 3.10?
Line 455-458: while I agree this is a plausible explanation, it is conjecture and would require further experimentation to prove. Add some cautionary language to this statement.
Line 462 (Figure 8): need a more descriptive figure caption.
Line 465: Discuss what might cause the hotspot just southwest of the center of the map.
Line 471-472: need to give citations to the previous research findings.
Line 498 (Figure 9): correct missing parenthesis and again improve figure caption text to be more descriptive.

Author Response

Dear Reviewer,

Thanks for your comments. Please see the attached file for our responses.

Best regards.

Author Response File: Author Response.pdf

Reviewer 4 Report

I have carefully reviewed the paper entitled “Urban air quality assessment by fusing spatial and temporal data from multiple study sources using refined estimation methods”. To start with, I am satisfied that the manuscript contains original material and has the potential to make an interesting contribution in the field. However, before I recommend its publication, the authors should carry out the following revisions:

1) The novelty of the manuscript should be highlighted better. What are the key new insights that this paper reports? Likewise, the conclusions section should be improved.

Does the proposed air quality model have any limitations? 

2) Also, other small mistakes should be corrected, for example:

 

In line 26,397,398,401: format 2 as superscript

In line 38: format 2 as superscript in both NO2 and SO2

In lines :111-116. Scale 1km*1km is not microscopic when we want to estimate air quality, especially in urban environments. Rewrite this sentence

In line 125,130: “a time granularity of one hour" Are they average hourly values?

PM2.5 index, PM10 index, NO2 index, are calculated by hourly average values; Please indicate.

In line 156: “FROM-GLC-seg”. Is that right? Add a reference.

In lines 188-190: Did you test with a smaller grid? It would be interesting to check the model in a smaller grid.

In line 259: Add Fig. number

In line 455: Correct figure number

In line 465: Correct the time (12:00 pm)

In line 561: Delete “6. Patents”

In lines 562,563: Delete those lines

 

Author Response

Dear Reviewer,

Thanks for your comments. Please see the attached file for our responses.

Best regards.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Dear Authors,

I'm satisfied with the changes and corrections you made on the manuscript

Reviewer 2 Report

The paper has serious weaknesses. The minor revisions the authors have made cannot be sufficient for addressing them. The paper needs to be re-designed in the concept and in the methodology. 

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