the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 07 Mar 2024
Quantifying the diurnal variation of atmospheric NO2 from observations of the Geostationary Environment Monitoring Spectrometer (GEMS)
Abstract. The Geostationary Environment Monitoring Spectrometer (GEMS) over Asia is the first geostationary Earth orbit instrument in the virtual constellation of sensors for atmospheric chemistry and composition air quality research and applications. For the first time, the hourly observations enable studies of diurnal variation of several important trace gas and aerosol pollutants including nitrogen dioxide (NO2) which is the focus of this work. NO2 is a regulated pollutant and an indicator of anthropogenic emissions in addition to being involved in tropospheric ozone chemistry and particulate matter formation. We present new quantitative measures of NO2 tropospheric column diurnal variation which can be greater than 50 % of the column amount especially in polluted environments. The NO2 distribution is seen to change hourly and can be quite different from what would be seen by a once-a-day low Earth orbit satellite observation. We use GEMS data in combination with TROPOMI satellite and Pandora ground-based remote sensing measurements and MUSICAv0 3D chemical transport model analysis to examine the NO2 diurnal variation in January and June 2023 over Northeast Asia and Seoul, South Korea, study regions to distinguish the different emissions, chemistry, and meteorological processes that drive the variation. Understanding the relative importance of these processes will be important for including pollutant diurnal variation in models aimed at determining true pollutant exposure levels for air quality studies. The work presented here also provides a path for investigating similar NO2 diurnal cycles in the new TEMPO data over North America, and later over Europe with S-4.
-
Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
-
Preprint
(15784 KB)
-
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(15784 KB) - Metadata XML
- BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-570', Anonymous Referee #1, 25 Mar 2024
This study investigates diurnal changes in tropospheric NO2 over northeast Asia and the Seoul metropolitan area, as observed by the geostationary GEMS satellite instrument. The authors attempted to quantify the diurnal changes in GEMS NO2 using two metrics: the cumulative absolute changes in tropospheric NO2 over a day, as well as normalized hourly deviations from local afternoon NO2 values. Diurnal cycles in GEMS tropospheric NO2 for January and June 2023 are compared with ground-based Pandora observations. The authors also conducted model simulations, and discussed the impacts of emissions, chemistry, and meteorology on NO2 over the study area. GEMS, as the first dedicated atmospheric composition instrument in the GEO orbit, is expected to provide valuable insights into the diurnal changes in the emissions and photochemical processes of important air pollutants. This study represents one of the earlier efforts to understand the diurnal changes in GEMS NO2 data, and the results should be of interest to the atmospheric composition and air quality research community. On the other hand, while the paper attempts to combine satellite and ground-based remote sensing measurements with model, the two parts (sections 3-4 and section 5) are only loosely connected. I would recommend major revisions before the paper can be accepted for publication in Atmos. Chem. Phys.
Specific comments:
As mentioned by the authors, GEMS NO2 retrievals have some known issues and there are improvements that are being implemented. Can the authors use the new version NO2 product for their analysis? At the very least, the authors should demonstrate that with the anticipated changes in the new GEMS product, the major conclusions of the paper would still stand.
Figure 1: Can the authors comment more on the gradient around 130E? Would the gradient disappear if the authors use the same number of samples across the entire domain? Are the areas east of 130E mainly sampled in the morning? If so, would one expect the mean NO2 for those areas to be higher, as compared with the case with a full daytime sample? In other words, should one expect that the areas just west of 130E to have smaller NO2 than those to the east, due to sampling differences?
Section 2.4: can the authors comment on the diurnal changes in the GEMS a priori profiles used in retrievals? How do they compare with the MUSICA simulations in this study?
Figure 3: there appear to be some horizontal (east-west) stripes in the GEMS tropospheric NO2 over the ocean, can the authors comment on those?
Line 180: are the absolute changes calculated based on two consecutive hourly observations? If there is a gap between two observations, how is that handled?
Figure 5: can the authors comment on the features (hot spots) that can be seen over the oceans (e.g., east of Philippines).
Lines 252-255 (and Figure 8): some of the day-to-day changes can also be caused by synoptic weather conditions. Do the MUSICA simulations show similar day-to-day changes in NO2?
Figures 7 and 8: maybe add Pandora time series to Figures 7c and 8c?
Section 5: this section appears to be only loose connected to the previous sections and the comparisons between GEMS and model simulations are largely qualitative. Can the authors sample MUSICA simulations using GEMS observation time and cloud filter? Also, can the authors apply the GEMS diurnal change metrics (as discussed in section 3.2) to the model simulations and make comparisons of those metrics between GEMS and MUSICA? Additionally, I’d strongly suggest that the authors use MUSICA simulated NO2 profiles as a priori to estimate air mass factor for GEMS NO2 – this would allow more consistent, quantitative comparisons.
Citation: https://doi.org/10.5194/egusphere-2024-570-RC1 -
AC1: 'Reply on RC1', D. P. Edwards, 24 May 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-570/egusphere-2024-570-AC1-supplement.pdf
-
AC1: 'Reply on RC1', D. P. Edwards, 24 May 2024
-
RC2: 'Comment on egusphere-2024-570', Anonymous Referee #2, 07 Apr 2024
Edwards et al. present observations of diurnal variations in NO2 from GEMS, one of the geostationary satellites measuring the NO2 column at an hourly time scale. The authors quantify the diurnal variation using two metrics: the sum of absolute changes in the NO2 column over the day and the absolute deviation of the day’s hourly observed NO2 relative to the observation at TROPOMI overpass time. The authors also utilize TROPOMI and Pandora measurements to help interpret the NO2 diurnal variation observed in the GEMS observations. The manuscript is well-written but requires some clarification on the context, such as the connections between satellite observations and modeling analysis. I suggest major revisions before publication in ACP.
- I suggest adding the equations to describe the matrices used to quantify NO2 diurnal variations. It is very hard to understand what exactly is defined as the “monthly average absolute change” in the figures.
- It is worth more discussion on the uncertainty in the GEMS NO2 column observations. What are the uncertainty levels of the hourly, daily, and monthly NO2 column measurements? Is the NO2 diurnal variation described in the paper sensitive to the measurement uncertainty?
- I can’t follow the modeling method section and Section 5. How does the model compare against the GEMS observations? Is the model capturing the diurnal variations observed in the GEMS? If the model is biased, how do you utilize the model to gain a process-level understanding of the observed NO2 diurnal variation?
- The introduction section provides a detailed discussion of the satellite's capability of observing the NO2 column, but the result section delves directly into the diurnal variation in the NO2 column. I suggest restructuring the introduction section to highlight the significance of this study.
- Figure 2: I don’t think this figure is necessary for the main manuscript, you can move it to the supplement.
- Figure 9 and section 4: the comparison of the NO2 column between GEMS and other measurements at SEOUL-YN raises concerns about possible bias in GEMS measurement. Why there is a much steeper gradient in the observed NO2 column between 12 and 13 local times from GEMS? Why is it?
- Following Figure 9, I wonder if the authors can point out and focus on regions where GEMS can provide more reliable NO2 column observations.
- Section 5: This part seems barely connected to other sections. More discussion is needed to strengthen the connections between sections.
Citation: https://doi.org/10.5194/egusphere-2024-570-RC2 -
AC2: 'Reply on RC2', D. P. Edwards, 24 May 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-570/egusphere-2024-570-AC2-supplement.pdf
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-570', Anonymous Referee #1, 25 Mar 2024
This study investigates diurnal changes in tropospheric NO2 over northeast Asia and the Seoul metropolitan area, as observed by the geostationary GEMS satellite instrument. The authors attempted to quantify the diurnal changes in GEMS NO2 using two metrics: the cumulative absolute changes in tropospheric NO2 over a day, as well as normalized hourly deviations from local afternoon NO2 values. Diurnal cycles in GEMS tropospheric NO2 for January and June 2023 are compared with ground-based Pandora observations. The authors also conducted model simulations, and discussed the impacts of emissions, chemistry, and meteorology on NO2 over the study area. GEMS, as the first dedicated atmospheric composition instrument in the GEO orbit, is expected to provide valuable insights into the diurnal changes in the emissions and photochemical processes of important air pollutants. This study represents one of the earlier efforts to understand the diurnal changes in GEMS NO2 data, and the results should be of interest to the atmospheric composition and air quality research community. On the other hand, while the paper attempts to combine satellite and ground-based remote sensing measurements with model, the two parts (sections 3-4 and section 5) are only loosely connected. I would recommend major revisions before the paper can be accepted for publication in Atmos. Chem. Phys.
Specific comments:
As mentioned by the authors, GEMS NO2 retrievals have some known issues and there are improvements that are being implemented. Can the authors use the new version NO2 product for their analysis? At the very least, the authors should demonstrate that with the anticipated changes in the new GEMS product, the major conclusions of the paper would still stand.
Figure 1: Can the authors comment more on the gradient around 130E? Would the gradient disappear if the authors use the same number of samples across the entire domain? Are the areas east of 130E mainly sampled in the morning? If so, would one expect the mean NO2 for those areas to be higher, as compared with the case with a full daytime sample? In other words, should one expect that the areas just west of 130E to have smaller NO2 than those to the east, due to sampling differences?
Section 2.4: can the authors comment on the diurnal changes in the GEMS a priori profiles used in retrievals? How do they compare with the MUSICA simulations in this study?
Figure 3: there appear to be some horizontal (east-west) stripes in the GEMS tropospheric NO2 over the ocean, can the authors comment on those?
Line 180: are the absolute changes calculated based on two consecutive hourly observations? If there is a gap between two observations, how is that handled?
Figure 5: can the authors comment on the features (hot spots) that can be seen over the oceans (e.g., east of Philippines).
Lines 252-255 (and Figure 8): some of the day-to-day changes can also be caused by synoptic weather conditions. Do the MUSICA simulations show similar day-to-day changes in NO2?
Figures 7 and 8: maybe add Pandora time series to Figures 7c and 8c?
Section 5: this section appears to be only loose connected to the previous sections and the comparisons between GEMS and model simulations are largely qualitative. Can the authors sample MUSICA simulations using GEMS observation time and cloud filter? Also, can the authors apply the GEMS diurnal change metrics (as discussed in section 3.2) to the model simulations and make comparisons of those metrics between GEMS and MUSICA? Additionally, I’d strongly suggest that the authors use MUSICA simulated NO2 profiles as a priori to estimate air mass factor for GEMS NO2 – this would allow more consistent, quantitative comparisons.
Citation: https://doi.org/10.5194/egusphere-2024-570-RC1 -
AC1: 'Reply on RC1', D. P. Edwards, 24 May 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-570/egusphere-2024-570-AC1-supplement.pdf
-
AC1: 'Reply on RC1', D. P. Edwards, 24 May 2024
-
RC2: 'Comment on egusphere-2024-570', Anonymous Referee #2, 07 Apr 2024
Edwards et al. present observations of diurnal variations in NO2 from GEMS, one of the geostationary satellites measuring the NO2 column at an hourly time scale. The authors quantify the diurnal variation using two metrics: the sum of absolute changes in the NO2 column over the day and the absolute deviation of the day’s hourly observed NO2 relative to the observation at TROPOMI overpass time. The authors also utilize TROPOMI and Pandora measurements to help interpret the NO2 diurnal variation observed in the GEMS observations. The manuscript is well-written but requires some clarification on the context, such as the connections between satellite observations and modeling analysis. I suggest major revisions before publication in ACP.
- I suggest adding the equations to describe the matrices used to quantify NO2 diurnal variations. It is very hard to understand what exactly is defined as the “monthly average absolute change” in the figures.
- It is worth more discussion on the uncertainty in the GEMS NO2 column observations. What are the uncertainty levels of the hourly, daily, and monthly NO2 column measurements? Is the NO2 diurnal variation described in the paper sensitive to the measurement uncertainty?
- I can’t follow the modeling method section and Section 5. How does the model compare against the GEMS observations? Is the model capturing the diurnal variations observed in the GEMS? If the model is biased, how do you utilize the model to gain a process-level understanding of the observed NO2 diurnal variation?
- The introduction section provides a detailed discussion of the satellite's capability of observing the NO2 column, but the result section delves directly into the diurnal variation in the NO2 column. I suggest restructuring the introduction section to highlight the significance of this study.
- Figure 2: I don’t think this figure is necessary for the main manuscript, you can move it to the supplement.
- Figure 9 and section 4: the comparison of the NO2 column between GEMS and other measurements at SEOUL-YN raises concerns about possible bias in GEMS measurement. Why there is a much steeper gradient in the observed NO2 column between 12 and 13 local times from GEMS? Why is it?
- Following Figure 9, I wonder if the authors can point out and focus on regions where GEMS can provide more reliable NO2 column observations.
- Section 5: This part seems barely connected to other sections. More discussion is needed to strengthen the connections between sections.
Citation: https://doi.org/10.5194/egusphere-2024-570-RC2 -
AC2: 'Reply on RC2', D. P. Edwards, 24 May 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-570/egusphere-2024-570-AC2-supplement.pdf
Peer review completion
Journal article(s) based on this preprint
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 487 | 164 | 28 | 679 | 19 | 15 |
- HTML: 487
- PDF: 164
- XML: 28
- Total: 679
- BibTeX: 19
- EndNote: 15
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
Cited
Sara Martínez-Alonso
Duseong S. Jo
Ivan Ortega
Louisa K. Emmons
John J. Orlando
Helen M. Worden
Jhoon Kim
Hanlim Lee
Junsung Park
Hyunkee Hong
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(15784 KB) - Metadata XML