Assessment of Tropospheric Concentrations of NO2 from the TROPOMI/Sentinel-5 Precursor for the Estimation of Long-Term Exposure to Surface NO2 over South Korea
Round 1
Reviewer 1 Report
Review of “Assessment of Tropospheric Concentrations of NO2 from the TROPOMI/Sentinel-5 Precursor for the Estimation of Long-term Exposure to Surface NO2 over South Korea” by Jeong and Hong (2021)
The manuscript by Jeong and Hong (2021) evaluates the spatiotemporal comparison of tropospheric nitrogen dioxide (NO2) retrieved by TROPOspheric Monitoring Instrument (TROPOMI) and in situ measurements from the South Korea operated by the Korean Ministry of Environment (SKE) network in South Korea. This analysis was conducted for the year 2019. The methods of this study also converted vertical column density (VCD) values of NO2 from TROPOMI to surface-level values using a chemical transport model. These derived surface values were also compared to the spatiotemporal trends and magnitudes of surface measurements. The results of this study show that TROPOMI VCD NO2 values are highly correlated with urban in situ data and moderately correlated with rural stations. Surface-level NO2 values derived from TROPOMI VCDs also displayed moderate correlation within situ observations, with a low bias comparable presented in other recent studies. The article is generally well-written, detailed, and organized. I think a discussion of how this study expands upon the current state-of-the-science and improves our ability to apply satellite remote-sensing in air quality studies would greatly improve the overall manuscript. Overall, I would recommend this article to be published in Remote Sensing after addressing the minor and major comments suggested here.
Minor Comments
1. Line 48-49. References to air quality studies using land-use regression (LUR) models are needed after this sentence.
2. Line 90. Figure 2 is referenced before Fig. 1. The order of these figures should be switched.
3. Line 94. Do the authors mean “quantitative” instead of “qualitative”?
4. Line 100. What do the authors mean by unique? Do they refer to it being the sole instrument onboard Sentinel-5 Precursor (S5p)? Or do they wish to emphasize how TROPOMI is different/unique from other space-borne sensors?
5. Line 204-206. Lower surface KME NO2 concentrations at the TROPOMI overpass time could also be due to boundary layer development throughout the day.
6. Line 308. This should be KME and not KMA.
7. Figure 5 and 8. The statistics presented in the figure insets are difficult to read.
Major Comments
1. TROPOMI data. The authors evaluate TROPOMI data over South Korea for the entire year of 2019. Do the authors use TROPOMI data at a consistent spatial resolution for the entire year? Or
do they switch to the higher spatial resolution product which began in August 2019? How does this impact the results of the study?
2. Line 216-223. Do the weekday/weekend trends in NO2 observed by TROPOMI agree with the KME data? Are the fractional reductions of NO2 observed by TROPOMI similar to the KME data?
3. Surface NO2 calculation. The authors apply CAMS vertical profiles of NO2 (spatial resolution of 80 km (0.75° × 0.75°)) to derive surface concentrations of NO2 using TROPOMI column retrievals. More description of how this was done is needed. Do the authors sample the model at the overpass time of TROPOMI? Or are daily-averaged vertical profiles applied? Given CAMS has coarse spatial resolution, can the vertical distributions of NO2 in the model, especially in the lower troposphere, be expected to be accurate? Models at very coarse spatial resolution will have difficulty to accurately simulate lower tropospheric NO2 near source regions, along the urban/rural interface, near complex topography or coastlines, etc. The authors need to discuss this in more detail and provide reasoning for not applying a higher spatial resolution model to provide vertical profiles of NO2.
4. Line 332-341. The authors should expand upon this analysis to show how TROPOMI surface derived NO2 concentrations compared to in situ data at a monthly or seasonal scale. Does the intercomparison show seasonal differences? The authors should expand upon this part of the analysis which potentially could increase the overall impact of this research.
5. Overall relevance and impact of the study. The authors should add a section to the conclusion section of the article to discuss the overall relevance and impact of the study? Explaining to the readers how this research advances our understanding of satellite remote-sensing of tropospheric and surface-level NO2 would greatly improve the impact of this study. Also, how does this research improve our ability to use satellite retrievals in air quality studies? What are the next steps that need to be done? A discussion such as this is needed at the end of the manuscript.
Author Response
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Author Response File: 
Author Response.docx
Reviewer 2 Report
Tropospheric nitrogen dioxide (NO2) is an important gaseous pollutant in the atmosphere, and an important precursor of tropospheric ozone and aerosols. Satellite measurement is an important method to provide large-scale air pollutants, including aerosols and trace gases. This paper uses reanalysis meteorological data, surface observation data, products of satellites, makes analyses column NO2 conc. and surface NO2 conc., and their correlation in South Korea. The paper shows various data of NO2 conc., important to understand NO2 spatial-temporal distribution and NO2 emission. On a whole, it is relatively well written and straightforward.
Author Response
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Author Response File: Author Response.docx
Reviewer 3 Report
Review of the manuscript: “Assessment of Tropospheric Concentrations of NO2 from the TROPOMI/Sentinel-5 Precursor for the Estimation of Long-term Exposure to Surface NO2 over South Korea”
The manuscript deals with the comparison between satellite-based TROPOMI NO2 products and in situ observations in South Korea. The paper is clearly written but it requires a few clarifications. I recommend publication after addressing the following comments:
- You could add the following references in your introduction:
Cooper et al 2020 Environ. Res. Lett. 15 104013
Goldberg, D. L., Anenberg, S. C., Kerr, G. H., Mohegh, A., Lu, Z., & Streets, D. G. (2021). TROPOMI NO2 in the United States: A detailed look at the annual averages, weekly cycles, effects of temperature, and correlation with surface NO2 concentrations. Earth's Future, 9, e2020EF001665. https://doi.org/10.1029/2020EF001665
- L94 For qualitative assessment: you mean here quantitative?
- L117 “…we used offline reprocessed level-2 NO2 data (version 1.3.2) from 2019”: can you specify the exact period of study?
- L220-221 “whereas it was relatively small at Danyang and Gwangyang in spite of the strong emission sources nearby” is this sign of the fact that the emission here are not dominated by traffic and they are mostly related to industrial emission?
- Figure 5. It seems that you compare individual data from in situ measurements to TROPOMI finely gridded (0.05 deg): What type of gridding did you use (oversampling?)? Did you consider spatially averaging in situ data within the grid pixel before the comparison especially for Fig.5b? And anyway how does the result/correlation changes when changing the gridding size?
- Sect. 3.3. How do you calculate the tropospheric column CEAC4 ? How do you derive the tropopause level? Did you apply the TROPOMI averaging kernels before integrating? Please clarify.
- L308 and following: You could compare your results also to Cooper et al. 2020. They have employed a few more corrections that bring the satellite-based values of the surface concentration closer to the in situ measurements.
Author Response
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Author Response File: Author Response.docx
Reviewer 4 Report
Comments:
- L38 and L40. Please include specific references. “references therein”? L48, 58, 62, etc.
- L50-51. Avoid excessive use of text inside a parenthesis. I suggest removing parentheses.
Author Response
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Author Response File: Author Response.docx
