Spatiotemporal Analysis of NO₂ Production Using TROPOMI Time-Series Images and Google Earth Engine in a Middle Eastern Country

Round 1

Reviewer 1 Report

Please refer to the attached file.

Comments for author File: Comments.pdf

Author Response

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Author Response File: Author Response.docx

Reviewer 2 Report

Review of “Spatiotemporal Analysis of NO2 Production Using TROPOMI Time-Series Images and Google Earth Engine in a Middle Eastern Country”

In this manuscript, the authors conduct comparisons for TROPOMI NO₂ retrievals against ground observations over the Iran area on a monthly sence. TROPOMI data is from the google GEE platform. This is the main reason the title ‘TROPOMI Time-Series Images and Google Earth Engine’ comes from. Given the quality of the manuscript, I shall recommend a major revision before its publication.

 

 

General comment:

In order to meet publication standards, the format, e.g., equation, reference, bulletin, font size et. al, of the manuscript should be improved.

 

On the science side, the main weakness of the current manuscript is all the comparison is on a monthly scale. Actually, quite a lot of literature has conducted evaluations of TROPOMI NO₂ on a daily scale, such as Judd (2020). The author shall clarify the reason for their choice of the comparison time scale.

 

Specific comments:

 

1. Section 2.2, a more detailed description of the ground data should be included. Specifically, what is the uncertainty of the ground observation? What is the sampling frequency of the measurement? What procedures are made to process the ground data on the monthly scale? What method is applied to collocate the TROPOMI with ground observation in both space and time?

 

2. Section 2.3, the resampling method of CEE should be introduced more clearly since it processed the main data source used in this research. What criterion is used in the resampling, nearest neighborhood, reverse distance, or area weight?
3.  
4. Figure 4, more discussion should be present. Why does the data cluster into two categories in spring and summer? Is the unit of the Y-axis correct?

 

5. Equation 1, the i shall be subscript?

 

6. Statistics in Section 3.1 does not match statistics shown in the figure 4

 

7. Section 3.2, What is the definition of your seasons? It will be better to clarify in the text

 

8. Figure 7, how is the R² is calculated, comparing the observation with regression? trend analysis should be conducted instead of a naïve linear regression since the NO₂ variation shall be greatly impacted by the season

 

Judd, L. M., Al-Saadi, J. A., Szykman, J. J., Valin, L. C., Janz, S. J., Kowalewski, M. G., ... & Williams, D. (2020). Evaluating Sentinel-5P TROPOMI tropospheric NO 2 column densities with airborne and Pandora spectrometers near New York City and Long Island Sound. Atmospheric measurement techniques, 13(11), 6113-6140.

 

Comments for author File: Comments.pdf

Author Response

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Author Response File: Author Response.docx

Reviewer 3 Report

This paper is about the use of Sentinel 5p product from ESA to estimate the NO2 concentrations over Iran. Validation with ground based-measurements has been carried out in a consistent way

The work is well written and well structured. It is one of the first clear example about processing Sentinel 5p form the GEE repository that allow users to spend very little time about retrieving NO2 data without any problem of misinterpretation of the results. On the other hand, good efforts has been put in the validation with the in situ data. 

Results showed acceptable correlation between ground measurements and satellite observations. The aim of the work focused on the understating some KPI about NO2 levels over the Country. These KPIs were population density, and industrial activities. Results are quite convincing and clearly confirm that NO2 is a direct consequence of anthropogenic activities on the ground.  

For the scientific point of view this work does not show any relevant and new insights when compared to previous work. The only new thing of this work is the fact that it uses the freely available GEE platform to retrieve different typology of data from open source 

Conclusions are well done and cover all the aspect treated in the paper and highlight the main scope of their work. References are well chosen and appropriate with the text.

The only suggestion I have to the authors is to indicate as “pollution class” the “class” in Table 6. In addition, in Figure 9 I would clearly indicate what is the correlation (between population and NO2 concentration etc.).

Finally, I suggest this paper for publication and accept it with minor corrections.

Author Response

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Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

The authors have revised the manuscript following the comments from the initial review.

Reviewer 2 Report

The author has addressed my comment. I shall recommend an accept.