Spaceborne tropospheric nitrogen dioxide (NO<sub>2</sub>) observations from 2005–2020 over the Yangtze River Delta (YRD), China: variabilities, implications, and drivers

Yin, Hao; Sun, Youwen; Notholt, Justus; Palm, Mathias; Liu, Cheng

doi:https://doi.org/10.5194/acp-22-4167-2022

Articles | Volume 22, issue 6

https://doi.org/10.5194/acp-22-4167-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-22-4167-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 22, issue 6

Research article

|

31 Mar 2022

Research article |

| 31 Mar 2022

Spaceborne tropospheric nitrogen dioxide (NO₂) observations from 2005–2020 over the Yangtze River Delta (YRD), China: variabilities, implications, and drivers

Hao Yin, Youwen Sun, Justus Notholt, Mathias Palm, and Cheng Liu

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Final revised paper (published on 31 Mar 2022)
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RC1:
'Comment on acp-2021-1089', Anonymous Referee #1, 28 Jan 2022
This manuscript investigates the long-term variabilities of tropospheric NO₂ VCDs from 2005-2020 using OMI satellite data product over the Yangtze River Delta (YRD), one of the most densely populated and highly industrialized city clusters in China. The authors also quantify the contributions of meteorology and anthropogenic emissions to the long-term variabilities of tropospheric NO₂ VCDs in the major megacities over YRD. They conclude that the inter-annual variabilities of tropospheric NO₂ VCDs from 2005 to 2020 over the YRD can be divided into two stages, i.e., an overall increasing trend from 2005 to 2011 and an overall decreasing trend from 2011 to 2020.This is an interesting study and the majority of the work are creative. This manuscript is well written, structured and analyzed convincingly, and its topic fits well within the scope of ACP. I think that this manuscript can improve our knowledge with respect to long-term evolutions of economic and social development, anthropogenic emission over the YRD, and could be of interest to the general atmospheric science community. Minor revisions are recommended.

General comments:

Please provide more detailed descriptions about the YRD region, such as the population, number of cities, area of the region, etc, over Zhejiang, Anhui and Jiangsu Province. This would help the reader understand the reason that YRD region is one of the most densely populated and highly industrialized city clusters in China.

In section 3.3 and Figure 5, the authors state that “For each city, the CNMEC ground level NO₂ measurements nearest to the OMI ground grid were included for comparison.” In each city, there are a number of CNMEC ground stations. However, the authors present comparisons of satellite and ground-based observations for each city. Whether the authors averaged all observed values or some other method? The authors should state the detailed of this process in section 6.

Detailed comments:

The phrase “tropospheric NO₂ VCDs” is too cumbersome in this manuscript, and please change it to a simple symbol, such as “Tro_NO₂” or similar.

Please include a figure about the monthly average of surface temperature in main cities over YRD in the supplement, same as figure S6.

Line 37, “... inter annual ...” should be “... inter-annual ...”.

Line 41, “… which cause …” should be “… which causes …”.

Line 58, “… biogeochemical reaction …” should be “… the biogeochemical reactions …”

Line 85, “the rapid developing regions” should be “the rapidly developing regions”.

Line 102, “polices” should be “policies”.

Line 259, “Except ...” should be “Except for ...”.

Line 346, “agreements” should be “agreement”.

Line 352, “characterized” should be “is characterized”

Line 395, “bellow” should be “below”.

Line 465, “relative” should be “relatively”.

The usage of “emission” and “emissions” is sometimes misleading, please use it consistently.

Please add the units for each meteorological parameter in table 2.

I cannot list all technical errors as above. I thus suggest that the authors should check all grammatical errors throughout the manuscript and correct accordingly.

Please check the format of each reference and make sure it follows the ACP format.
Citation: https://doi.org/10.5194/acp-2021-1089-RC1
- AC1: 'Reply on RC1', Youwen Sun, 01 Mar 2022
  
  Response to Referee #1:
  Thanks very much for your comments, suggestions and recommendation with respect to improve this paper. The responses to all your comments are listed below.
  This manuscript investigates the long-term variabilities of tropospheric NO₂ VCDs from 2005-2020 using OMI satellite data product over the Yangtze River Delta (YRD), one of the most densely populated and highly industrialized city clusters in China. The authors also quantify the contributions of meteorology and anthropogenic emissions to the long-term variabilities of tropospheric NO₂ VCDs in the major megacities over YRD. They conclude that the inter-annual variabilities of tropospheric NO₂ VCDs from 2005 to 2020 over the YRD can be divided into two stages, i.e., an overall increasing trend from 2005 to 2011 and an overall decreasing trend from 2011 to 2020.This is an interesting study and the majority of the work are creative. This manuscript is well written, structured and analyzed convincingly, and its topic fits well within the scope of ACP. I think that this manuscript can improve our knowledge with respect to long-term evolutions of economic and social development, anthropogenic emission over the YRD, and could be of interest to the general atmospheric science community. Minor revisions are recommended.
  Response: All your comments listed below have been addressed. Please check the point by point response as follows.
  General comments:
  Comment [1]: Please provide more detailed descriptions about the YRD region, such as the population, number of cities, area of the region, etc, over Zhejiang, Anhui and Jiangsu Province. This would help the reader understand the reason that YRD region is one of the most densely populated and highly industrialized city clusters in China.
  Response: Thanks for your suggestion. In our revised version, we have added content to Table1 including the detailed descriptions of each province over the YRD region. Please check the marked up file for details.
  Comment [2]: In section 3.3 and Figure 5, the authors state that “For each city, the CNMEC ground level NO₂ measurements nearest to the OMI ground grid were included for comparison.” In each city, there are a number of CNMEC ground stations. However, the authors present comparisons of satellite and ground-based observations for each city. Whether the authors averaged all observed values or some other method? The authors should state the detailed of this process in section 6.
  Response: Thanks for your suggestion. In this study, ground level NO₂ concentrations were taken as the average of all CNMEC stations in each city. The Tro_NO₂ values were taken as the average of all OMI observed grids within the scope of each city. We have modified the corresponding content in Line 330-332, section 3.3. Please check the marked up file for details.
  Detailed comments:
  Comment [1]: The phrase “tropospheric NO₂ VCDs” is too cumbersome in this manuscript, and please change it to a simple symbol, such as “Tro_NO₂” or similar.
  Response: Done, we changed “ tropospheric NO₂ VCDs” to “NO₂ VCD_trop”. Please check the marked up file for details.
  Comment [2]: Please include a figure about the monthly average of surface temperature in main cities over YRD in the supplement, same as figure S6.
  Response: Thanks for your suggestion. We have added figure S9 including the monthly average of surface temperature in main cities over YRD in the supplement. Please check the marked up file for details.
  Comment [3]: Line 37, “... inter annual ...” should be “... inter-annual ...”.
  Response: Done. Please check the marked up file for details.
  Comment [4]: Line 41, “… which cause …” should be “… which causes …”.
  Response: Done. Please check the marked up file for details.
  Comment [5]: Line 58, “… biogeochemical reaction …” should be “… the biogeochemical reactions …”
  Response: Done. Please check the marked up file for details.
  Comment [6]: Line 85, “the rapid developing regions” should be “the rapidly developing regions”.
  Response: Done. Please check the marked up file for details.
  Comment [7]: Line 102, “polices” should be “policies”.
  Response: Done. Please check the marked up file for details.
  Comment [8]: Line 259, “Except ...” should be “Except for ...”.
  Response: Done. Please check the marked up file for details.
  Comment [9]: Line 346, “agreements” should be “agreement”.
  Response: Done. Please check the marked up file for details.
  Comment [10]: Line 352, “characterized” should be “is characterized”
  Response: Done. Please check the marked up file for details.
  Comment [11]: Line 395, “bellow” should be “below”.
  Response: Done. Please check the marked up file for details.
  Comment [12]: Line 465, “relative” should be “relatively”.
  Response: Done. Please check the marked up file for details.
  Comment [13]: The usage of “emission” and “emissions” is sometimes misleading, please use it consistently.
  Response: Done. Please check the marked up file for details.
  Comment [14]: Please add the units for each meteorological parameter in table 2.
  Response: Done. Please check table 3 in revised version.
  Comment [15]: I cannot list all technical errors as above. I thus suggest that the authors should check all grammatical errors throughout the manuscript and correct accordingly.
  Response: Done. Please check the marked up file for details.
  Comment [16]: Please check the format of each reference and make sure it follows the ACP format.
  Response: Done. Please check the marked up file for details.
  
  Citation: https://doi.org/10.5194/acp-2021-1089-AC1
RC2:
'Comment on acp-2021-1089', Anonymous Referee #2, 23 Feb 2022
Yin et al., present a comprehensive study to look insight to the NOx trend from 2005 to 2020 over the Yangtze River Delta China by using the OMI space borne observations. Observations revealed that the NOx experienced an upward and downward trend during 2005-2020, with a threshold of 2011. And they applied the multiple linear regression model to understand the role of anthropogenic emissions and meteorological factor in NOx level. Model results showed that the seasonal change is mainly attributed to meteorological factor and the long-term trend of NOx is attributed to emissions. Overall, the dataset and analysis make sense and the topic is with the scope of ACP, I only have some minor comments to be addressed.

Section 4.1, could you please provide more information about which two or three meteorological factors influence the level of NOx more significantly and conduct more discussions about the reasons in the main text?

Inspired by the text in Line 422-423, I suggest the authors supply two figures (same as Figure 2 and 3 but from 2011-2019) in SI to take a look at the influence of COVID-19 to the NOx trend from 2011-2020.

I can understand the motivation of using the GDP data in the discussions, while it seems that the GDP cannot be a perfect explanation for the trend of NOx emission, so I believe Figure 8 is not so important and can be moved to SI. By the way, I encourage the authors to collect some information about the motor vehicle emissions and major industrial emissions data in this region and analysis the NOx trend with these emissions.

Line 271-273, please check the decrement of Anhui and the total YRD, as the data values are the same, may be a typo.

Figure S2, NO2 change to subscript.
Citation: https://doi.org/10.5194/acp-2021-1089-RC2
- AC2: 'Reply on RC2', Youwen Sun, 01 Mar 2022
  
  Response to Referee #2:
  Thanks very much for your comments, suggestions and recommendation with respect to improve this paper. The responses to all your comments are listed below.
  Yin et al., present a comprehensive study to look insight to the NO_x trend from 2005 to 2020 over the Yangtze River Delta China by using the OMI space borne observations. Observations revealed that the NO_x experienced an upward and downward trend during 2005-2020, with a threshold of 2011. And they applied the multiple linear regression model to understand the role of anthropogenic emissions and meteorological factor in NO_x level. Model results showed that the seasonal change is mainly attributed to meteorological factor and the long-term trend of NO_x is attributed to emissions. Overall, the dataset and analysis make sense and the topic is with the scope of ACP, I only have some minor comments to be addressed.
  Response: All your comments listed below have been addressed. Please check the point by point response as follows.
  
  General comments:
  Comment [1]: Section 4.1, could you please provide more information about which two or three meteorological factors influence the level of NO_x more significantly and conduct more discussions about the reasons in the main text?
  Response: Thanks for your suggestions. We have provided more information about which two or three meteorological factors influence the level of NO_x more significantly and conduct more discussions about the reasons in the main text. As shown in Figure S2, the vast majorities of meteorological contributions over all megacities are from temperature and additional minor contributions over some cities such as Nanjing, Shanghai, and Suzhou are attributed to relative humidity, pressure, or surface incoming shortwave flux (SWGDN) (Agudelo–Castaneda et al., 2014;Parra et al., 2009). Significant negative correlations between temperature and NO₂ VCD_trop are observed in all megacities (Figure S3, Table 5). Higher temperature tends to decrease NO₂ VCD_trop and vice versa. This is because higher temperature conditions could accelerate the chemical reaction that destructs NO₂ in the troposphere (Pearce et al., 2011;Yin et al., 2021). In addition, surface pressure shows high positive and both surface relative humidity and SWGDN show negative correlations with NO₂ VCD_trop, but their contribution levels are much lower than the temperature. All other meteorological variables only have weak correlations with NO₂ VCD_trop (Table 5) . Please check the marked up file for details.
  
  Comment [2]: Inspired by the text in Line 422-423, I suggest the authors supply two figures (same as Figure 2 and 3 but from 2011-2019) in SI to take a look at the influence of COVID-19 to the NO_x trend from 2011-2020.
  Response: Thanks for your suggestions. We have added this two figures in supplement information (Figure S5 and Figure S6). We also obtained the same conclusion as that from Figure 6, indicating the drivers of seasonal cycles of NO₂ VCD_trop deduced above are consistent over years. Please check the marked up file for details.
  
  Comment [3]: I can understand the motivation of using the GDP data in the discussions, while it seems that the GDP cannot be a perfect explanation for the trend of NO_x emission, so I believe Figure 8 is not so important and can be moved to SI. By the way, I encourage the authors to collect some information about the motor vehicle emissions and major industrial emissions data in this region and analysis the NO_x trend with these emissions.
  Response: Thanks for your suggestions. We have moved Figure 8 to supplement information (Figure S11). In Figure S12, we further analyzed the variabilities of NO_x emissions over the YRD region from 2008 to 2017 by category provided by the MEIC inventory, including motor vehicle emissions, major industrial emissions, resident emissions and power emissions (http://meicmodel.org, last accessed: February 25, 2022) (Li et al., 2017;Zheng et al., 2018). The results show that the decreases in NO₂ VCD_trop over the YRD during 2011 to 2013 are attributed to the reductions of industrial and power emissions, during 2013 to 2014 are mainly attributed to the reductions of motor vehicle emissions and power emissions, and after 2014 are attributed to the reductions of motor vehicle emissions, power emissions and industrial emissions. We have added the corresponding content to line 370-380. Please check the marked up file for details.
  
  Comment [4]: Line 271-273, please check the decrement of Anhui and the total YRD, as the data values are the same, may be a typo.
  Response: Thanks for your reminder. We have revised this mistake in the correspond content. The total decrements over Anhui in 2020 relative to 2011 is (4.82 ± 0.35)´10¹⁵molecule/m² (43.26 ± 3.07) % (Line 266-267). Please check the marked up file for details.
  
  Comment [5]: Figure S2, NO₂ change to subscript.
  Response: Thanks for your reminder. We have modified the figure in supplement. Please check the marked up file for details.
  Reference
  Agudelo–Castaneda, D. M., Calesso Teixeira, E., and Norte Pereira, F.: Time–series analysis of surface ozone and nitrogen oxides concentrations in an urban area at Brazil, Atmospheric Pollution Research, 5, 411-420, https://doi.org/10.5094/APR.2014.048, 2014.
  Li, M., Liu, H., Geng, G., Hong, C., Liu, F., Song, Y., Tong, D., Zheng, B., Cui, H., Man, H., Zhang, Q., and He, K.: Anthropogenic emission inventories in China: a review, Natl Sci Rev, 4, 834-866, 10.1093/nsr/nwx150, 2017.
  Parra, M. A., Elustondo, D., Bermejo, R., and Santamaría, J. M.: Ambient air levels of volatile organic compounds (VOC) and nitrogen dioxide (NO2) in a medium size city in Northern Spain, Sci Total Environ, 407, 999-1009, https://doi.org/10.1016/j.scitotenv.2008.10.032, 2009.
  Pearce, J. L., Beringer, J., Nicholls, N., Hyndman, R. J., and Tapper, N. J.: Quantifying the influence of local meteorology on air quality using generalized additive models, Atmos Environ, 45, 1328-1336, https://doi.org/10.1016/j.atmosenv.2010.11.051, 2011.
  Yin, H., Liu, C., Hu, Q., Liu, T., Wang, S., Gao, M., Xu, S., Zhang, C., and Su, W.: Opposite impact of emission reduction during the COVID-19 lockdown period on the surface concentrations of PM2.5 and O3 in Wuhan, China, Environmental Pollution, 289, 117899, https://doi.org/10.1016/j.envpol.2021.117899, 2021.
  Zheng, B., Tong, D., Li, M., Liu, F., Hong, C., Geng, G., Li, H., Li, X., Peng, L., Qi, J., Yan, L., Zhang, Y., Zhao, H., Zheng, Y., He, K., and Zhang, Q.: Trends in China's anthropogenic emissions since 2010 as the consequence of clean air actions, Atmos. Chem. Phys., 18, 14095-14111, 10.5194/acp-18-14095-2018, 2018.
  
  Citation: https://doi.org/10.5194/acp-2021-1089-AC2

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

AR by Youwen Sun on behalf of the Authors (01 Mar 2022) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (01 Mar 2022) by Bryan N. Duncan

RR by Anonymous Referee #1 (07 Mar 2022)

RR by Anonymous Referee #2 (11 Mar 2022)

ED: Publish as is (11 Mar 2022) by Bryan N. Duncan

AR by Youwen Sun on behalf of the Authors (11 Mar 2022) Manuscript

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Short summary

In this study, we quantity the long-term variabilities and the underlying drivers of NO₂ from 2005 to 2020 over the Yangtze River Delta (YRD), one of the most densely populated and highly industrialized city clusters in China. We reveal the significant effect of the Action Plan on the Prevention and Control of Air Pollution since 2013 adopted by the Chinese government to reduce NO_x pollution. Our study can improve the understanding of pollution control measures on a regional scale.

Spaceborne tropospheric nitrogen dioxide (NO2) observations from 2005–2020 over the Yangtze River Delta (YRD), China: variabilities, implications, and drivers

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Spaceborne tropospheric nitrogen dioxide (NO₂) observations from 2005–2020 over the Yangtze River Delta (YRD), China: variabilities, implications, and drivers