Global Distribution of Column Satellite Aerosol Optical Depth to Surface PM2.5 Relationships
Round 1
Reviewer 1 Report
Dear authors,
I think this is an important study. This study provides a general picture on the estimated relationship between AOD vs PM2.5. However, there are still many points that need to be fixed before the paper will be published in RS journal. Much work is still need to be done. The paper is not focused. However i see a high potential in this publication. The results are interesting to my opinion.
First of all- the paper is not in the format of the journal. References must be numbered. Methods need to be separated from the Results section. Critical discussion of results is also needed.
Specific comments:
- Lines 127-128: "The secondary goal is to provide a guideline to the air quality community on the behavior of AOD-PM2.5 relationships in different parts of the world".
I think this is too strong and authors study does not respond tothis ambitious goal. In addition, using different satellite AOD retrievals the results can differ. And this need to be discussed and may be even one example shown in discussion. Yes, perhaps it wouldn't be too much different but still. In addition, using high resolution retrieval, the better match between AOD and PM2.5 is expected. Also higher noise level. I studied this impact and also other researchers. Below are several references. I would suggest that authors smooth this sentence to something like "provide an general view, insight, or something like that.
Chudnovsky, A. A., A. Kostinski, A. Lyapustin, and P. Koutrakis. 2013a. “Spatial Scales of Pollution from Variable Resolution Satellite Imaging.” Environmental Pollution 172: 131–138.
Chudnovsky, A., C. Tang, A. Lyapustin, Y. Wang, and J. Schwartz. 2013b. “A Critical Assessment of High Resolution Aerosol Optical Depth (AOD) Retrievals for Fine Particulate Matter (PM) Predictions.” Atmospheric Chemistry and Physics 13: 14581–14611.
(2019) A study of the impact of spatial resolution on the estimation of particle matter concentration from the aerosol optical depth retrieved from satellite observations, International Journal of Remote Sensing, 40:18, 7084-7112
2. Using 1 degree AOD data is excellent to provide a global view picture, however, not sufficient to study the correlation at the urban- sub urban scale. Authors mentioned this point in the manuscript. Showing several examples of this change can be useful.
3. Lines 150-153 (data fusion) should be better explained. Especially that the paper of Gupta is not published. I did not understand what authors did. I work with 1 degree and also with conventional MOD04. Does it mean that authors simply averaged all 10 km pixels within 1 degree pixel? May be even a short drawing/explanation can help. This point is critical for understanding
4. I think that the flow chart that explain the general methodology can be also useful. But authors need to decide.
5. Table 2- I did not find any 7 regions that authors mentioned in the table title. Seasonal statistics need to refer to different regions.
6. As I mentioned before, discussion is mandatory in this paper. Authors need to provide a general explanations to a reader what regions are can be better characterized, what regions/seasons provide poorer view, etc.
7. I see Figure 1 at the beginning and also Figure 1 as supplementary. Unfortunately I did not find anywhere across the text any reference to supplementary figure. Please clarify, use different letters, or else.
8. Figure 1 need to be revised- there are two panels. Authors need also overlay 7 boxes in the upper panel. Otherwise it is difficult to a reader moving eyes across the figure. These boxes also must be numbered.
9. Figure 2: number of stations and AOD/Pm2.5 pairs is different for 2019, lots of stations, but lower number of pairs. I would suggest for each box present the panel of different distributions or generate a map for each box with numbers. Otherwise it has no meaning. Global statistics without any reference to a studied box doesn't meet authors goal of providing a guide to air quality community. What message one can get from Figure 2 as a local manager?
9. Line 117: First paper using mixed effects model was:
HJ Lee, Y Liu, BA Coull, J Schwartz, P Koutrakis 2011 A novel calibration approach of MODIS AOD data to predict PM2. 5 concentrations 2011, 11(15)
Please give credit
10. Figure 1, lower. Is eleven sites the maximum of ground monitoring sites within 1 degree? I doubt. For example, MA, CT states, part that 1 degree can overlay contain at least 27 sites. The question if authors used sites that conduct daily measurements, sites that collect every 3 days or every 6 days. That must be clarified. Perhaps different statistics will be achieved. Again, authors need to provide a reader with a kind of a guide for each box, responses for each box. So, discussion or results need to be addressed for each and recommendations for each as well. Brief explanation also should be given why different regions have different R2, possible reasons for lower correlations.
11. It can be useful also to provide AOD vs AERONET AOD comparison for each box. If the retrieval biased, we cannot expect reasonable estimation of PM2.5.
Author Response
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Author Response File: 
Author Response.pdf
Reviewer 2 Report
Overall, the paper is easy to read and seems clear even for a non-expert in the field (like myself). I have only a few comments. First, based on the paper, I am still uncertain on the possibility of “replacement” of data from the ground monitors by the satellite remote sensing data. Many referred papers discuss AOD retrievals and its possible relation to PM2.5. However, what are the main spatial-temporal requirements for the satellite data to be applicable for the PM2.5 analysis? The “sub-km” (Line 65) resolution does not sound enough for city blocks – it should be ~10-100 meters. Can we do it with MODIS? Shall we monitor PM2.5 constantly? I believe yes, which this is not possible from polar-orbiting satellites, but rather from geostationary ones. We again return to the spatial resolution problem – what is the best one from GEO? These topics are not discussed. Monitors “cannot provide adequate coverage especially in regions that are not well populated” (line 50), but do we need to know PM2.5 in areas with low population?
Second, I have a strong objection versa Eq.(1). The authors refer to a paper from 2006 after after about 2 decades of the MODIS twins flying up there! Are there any recent (within 5 years) studies in the field? A paper by Chu et, 2016 does not really count because it considers the problem from the satellite remote sensing point of view (published in “Atmopshere”). I am talking about references to papers published, e.g., in Public Health Reports (https://journals.sagepub.com/home/phr) and similar. In References, the authors refer to atmopsheric/environment/aerosol journals; they did a rather poor job on analysis of the medical journals.
A proof-read would be good: “neon-meter” (line 32) “@ = aerosol mass density” (line 82) are just a few examples. Some terms, like “aerodynamic diameters”, would be good to briefly clarify. In line 55 “other independent sites” – it would be good to name a few.
But again, my comments should not be considered as negative, but rather as possible questions from a potential reader (not an expert in the field).
Author Response
Please see attached file
Author Response File: Author Response.pdf
Reviewer 3 Report
RemoteSensing-805963. Global Distribution of Column Satellite Aerosol Optical Depth to Surface PM2.5 Relationships
Christopher and Gupta.
The paper discusses the relationship between satellite aerosol optical depth and surface PM2.5 mass concentrations across the world. While the subject matter is of interest to air pollution research the paper is poorly written and of low quality. In the present form the paper is not suitable for publication.
Line 32. neon-meter should be nano-meter.
Line 50. Instead of most countries use many countries.
Line 59. .. vast number of population centers..
Line 82. The @ symbol should be ρ.
Line 110. The @ symbol is used again.
Line 160. GRIM should be GRIMM
Line 216. To other platforms.
Lines 217-219. Europe 60 to 713 is repeated.
Line 284. correlation has a peak frequency of approximately 0.2.
Line 288. Conducted.
Line 325. having more surface monitors.
Author Response
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Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
I have now only minor suggestions.
Figures 1a and 1b- Please provide title in the figure, or legend for AOD and number om pm2,5 sites. Authors do write this information in the figure caption however it will be useful to have it also in the figure- simplest to the reader (without eye travelling).
Figure 3- capture Please consider change to "Global distribution of AOD-PM2.5 relationship statistics at 1x1 degree" (I suggest to include "statistics" as otherwise it is not clear for my opinion).
What geographic areas exhibit the largest variability in correlation, slope, number of pairs- I see that Asia (China) is a very challenging region. I would like a bit more explanation from authors that highlight on some areas that need further analyses. May be a zoom in and some short discussion will be helpful to a reader to understand importance of authors findings,
Good Luck!
Author Response
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Author Response File: Author Response.pdf
Reviewer 3 Report
The revised paper is acceptable for publication.
Please check the caption on Figure 4, specifically the slope and intercept values in parenthesis against what is shown in the panels.
Author Response
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Author Response File: Author Response.pdf
