What is the cause(s) of positive ozone trends in three megacity clusters in eastern China during 2015&ndash;2020?

Hu, Tingting; Lin, Yu; Liu, Run; Xu, Yuepeng; Wang, Boguang; Zhang, Yuanhang; Liu, Shaw Chen

doi:https://doi.org/10.5194/egusphere-2023-1088

Preprints

https://doi.org/10.5194/egusphere-2023-1088

Preprints

13 Jun 2023

| 13 Jun 2023

What is the cause(s) of positive ozone trends in three megacity clusters in eastern China during 2015–2020?

Tingting Hu, Yu Lin, Run Liu, Yuepeng Xu, Boguang Wang, Yuanhang Zhang, and Shaw Chen Liu

Abstract. Due to a robust emission control policy, significant reductions in major air pollutants, such as PM_2.5, SO₂, NO₂, and CO, were observed in China between 2015 to 2020. On the other hand, during the same period, there was a notable increase in ozone (O₃) concentrations, making it a prominent air pollutant in eastern China. The annual mean concentration of maximum daily 8-hour average (MDA8) O₃ exhibited alarming linear trends of 2.4, 1.1, and 2.0 ppb yr^–1 in three megacity clusters: three-fold increase in the number of O₃-exceeding days, defined as MDA8 O₃ >75 ppb during the same period. Our analysis indicated that the upward trends in the annual mean concentration of MDA8 were primarily driven by the rise in consecutive O₃-exceeding days. Furthermore, from 2015 to 2017, there was a widespread expansion of high O₃ concentrations from urban centers to surrounding rural regions, resulting in a more uniform spatial distribution of O₃ after 2017. Lastly, we discovered a close association between O₃ episodes featuring four or more consecutive O₃-exceeding days and the position and strength of Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD). Additionally, there was a significant the West Pacific subtropical high (WPSH). The WPSH contributed to meteorological conditions characterized by clear skies, subsiding air motion, high vertical stability in the lower troposphere, increased solar radiation, and positive temperature anomaly at the surface. These favorable meteorological conditions greatly facilitated the formation of O₃. Thus, we propose that the worsening O₃ trends observed in BTH, YRD and PRD from 2015 to 2020 can be attributed to enhanced photochemical O₃ production resulting from an increased occurrence of meteorological conditions with high solar radiation and positive temperature anomalies under the influence of WPSH and tropical cyclones.

Received: 23 May 2023 – Discussion started: 13 Jun 2023

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Journal article(s) based on this preprint

05 Feb 2024

What caused large ozone variabilities in three megacity clusters in eastern China during 2015–2020?

Tingting Hu, Yu Lin, Run Liu, Yuepeng Xu, Shanshan Ouyang, Boguang Wang, Yuanhang Zhang, and Shaw Chen Liu

Atmos. Chem. Phys., 24, 1607–1626, https://doi.org/10.5194/acp-24-1607-2024,https://doi.org/10.5194/acp-24-1607-2024, 2024

Short summary

Tingting Hu, Yu Lin, Run Liu, Yuepeng Xu, Boguang Wang, Yuanhang Zhang, and Shaw Chen Liu

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2023-1088', Anonymous Referee #1, 22 Jul 2023

This paper analyzes the cause of 2015-2020 positive ozone trends in megacities in China. While the topic is important, the main conclusion of this study is not well supported by the analyses. In addition, the presentation, including the logic, word expression, and figure quality requires substantial improvement. I recommend at least a major revision before it can be re-considered to be published in ACP.
Main concern:

The authors emphasize the role of meteorology and diminish that of emission change as the key cause of the ozone rise between 2015-2020 in many places of the text, but in most places, there is no direct evidence to approve or disapprove, and the conclusions seem to be arbitrary, I list several questions related to this point below that need to be addressed.

(1) Line 166-167: Why is this simply attributed to weather system? (e.g. lines 166-168, 178-180, and many others).

(2) Line 177-180: For what reason it is “highly unlikely emission change”? It is not convincing to guess the cause simply based on the spatial pattern of ozone change. In addition, the ozone data used in this study is smoothed from observations in the TAP dataset, thus it may not reflect the true ozone change in the regions with no direct observation.

(3) The function of Section 3.2 is very confusing to me. The paper is about 2015-2020 trends, but here only the difference between 2015 and 2017 is analyzed. Even though the ozone difference between 2017 and 2015 is mostly driven by weather anomalies, the authors do not explain what weather system can sustain high ozone from 2017 to 2018-2020. Analyses of yearly differences cannot be simply applied to explain the 6-year trend.

(4) The authors list “ozone at high ozone stations unchanged while ozone at low ozone station increase” as a major finding (Line 235). If it is driven by weather, I wonder what weather system could selectively influence sites with different ozone levels. It more likely reflects chemical factors. This is a key concern.

(5) Line 210-223: VOCs emission change is not considered here. And again this is for difference between 2015 and 2017, it doesn’t explain the trend at all.

(6) Section 3.3 is not convincing as well. It should try to explain what weather system contributes to more ozone consecutive day from 2015 (as authors state that it drives the ozone increase), but figures are not helpful for this purpose. Figure 11 only shows that meteorological parameters can explain some of the ozone variability, Figures 12-13 show that WPSH can influence weather patterns, but is there any hint of an increasing influence of WPSH on consecutive ozone days? It might be useful to first clarify the weather patterns for consecutive ozone days, and explain what system can explain an increase in the frequency of such weather pattern during 2015-2020.
Other comments

Line 100, Before Table 1, please consider introducing the purpose for such classification.

Line 116: missing ppb

Line 158-160. It is quite unclear what the calculation stands for, and how it leads to the conclusion that. Please clarify. Please also carefully clarify the rationale of other formulas.

Figure 3: Should “episodes” be a better word compared to “days” for the y-axis, since the variables plotted are “days”?
The expression needs to be improved, and the use of words needs re-consideration. For example, what does “quasi-saturation” stand for? Please revise “Same as Figure 5 except for YRD” to “Same as Figure 5 but for YRD”. Please carefully check others.

Figure quality can be improved, by increasing resolution and avoiding contours on shadings if both represent the same variable (Figs 5-6)

Citation: https://doi.org/10.5194/egusphere-2023-1088-RC1
- AC1: 'Reply on RC1', Run Liu, 29 Sep 2023
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1088/egusphere-2023-1088-AC1-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2023-1088-AC1
RC2:
'Comment on egusphere-2023-1088', Anonymous Referee #2, 15 Aug 2023
The authors explore the potential mechanism driving the observed increase in surface Ozone during 2015-2020 over three megacity clusters in eastern China. Observational data for several pollutants from the Chinese National Environmental Ministry of Environmental Protection and Tracking Air Pollution in China dataset are analyzed in the paper to explore the trends in surface ozone over the study regions for the period of interest. Further, reanalysis data from ERA5, NCEP and NCAR are used to investigate the correlation between the evolving weather systems and the positive ozone trends. The study approach is mainly based on statistical analysis of observational data.

General comments:

The paper presents the meteorological conditions conducive to ozone formation (e.g., increased solar radiation) as potentially driving the positive ozone trends, rather than an increase in the anthropogenic emissions or a combination of both. While this is an important and interesting topic, some concerns need to be addressed in the paper before publication. The paper section structure, wording and logic, and the overall presentation can be further improved. More information needs to be included in the paper to further support the hypothesis that weather systems and changing meteorological conditions are responsible for observed increase in O3. Please consider the following suggestions:
List the processes (e.g., photochemistry) and precursors involved in the production of ozone, explicitly with tables and/or graphs (e.g., EKMA ozone isopleth diagram). Explicitly show the correlation (even if a weak correlation) between emissions of precursors (e.g., NOx, VOCs) and O₃ levels.

Compare the meteorological conditions to longer range time periods to clearly demonstrate that conditions have evolved towards increased ozone production. Comment on why these conditions have changed.

Include information on how land use/development was changed during the same period, to compare against the spatial expansion of high O₃ from urban centers to surrounding regions (past vs current).

Authors acknowledge that their results are mainly based on statistical correlations and further investigation into causal relationships is needed, perhaps with a use of a chemical/transport model. I agree and I’d like to emphasize that this topic is a great case for a model-based investigation, although it might be out of scope for the current manuscript. Model scenario simulations, with different input emissions and for various meteorological conditions, are crucial for further investigating this topic. All models have limitations, but their power and capability in investigating air quality and transport scenarios cannot be dismissed.

Specific comments:
Line 23: “These favorable meteorological conditions greatly facilitated the formation of O3” - suggests causal relationship, while only correlation is established in the paper…, please consider revising.
Line 37: “The concentrations of air pollutants SO₂, NOx, CO, PM10 and PM2.5 in China have been significantly reduced since 2013” – what about VOCs?
Figure 1,2,3,4: What caused the reduction in 2020? The Covid19 pandemic related closures and slowed down activities perhaps? You can see the same reduction in Figures 2, 3 and 4. Is this related to decreased emissions of precursors in 2019-2020 or changing meteorological conditions?
Line 85: “time interval of 1 h” do you mean a temporal resolution of 1 h, or your data is for only a 1 hour interval?
Line 93: “duration of O3 pollution,” please elaborate.

Line 93: “can be divided into consecutive O3-exceeding days with four or more days…” - please explain why this particular division was used?
Line 117: The decrease in 2020 suggests correlation with emissions…
Line 118: For completeness, please define “p” before use.
Line 127: “Is it due to changing O₃ photochemical processes or changing meteorological parameters?” – still the big question!
Line 137: How does this expansion correlate with the expansion of urban/industrial regions to not previously developed regions (perhaps industries were relocated to surrounding regions from urban centerers?)
Lines 141 to 144: Why compare the entire 2015-2020 period for high O₃ stations to the sub-period 2015-2017 for low O₃ stations?
Line 144: “quasi-saturation” – define.
Line 145: “approximately 100 ppb” - what are the instrumental/measurement limitations for these sites?
Line 147: “Did it have anything to do with the increase of consecutive O₃-exceeding days” – correlation!
Line 154: “expanded by about a factor of five from 2015 to 2017. ” - how did the land use/development change during this period?
Line 155: how big in area is the BTH box? How does it compare to the resolution of the data you analyzed?
Line 156: “66.42 ppb in2015 (31 days, Fig. 5a) to 69.44 in 2017 (62 days, Fig. 5b)” - comparing averages over different time periods (and number of days), how do you justify this comparison?
Line 159: Not clear what the equation represents. Consider labeling with variables and defining the equation prior to usage….
Line 162: “driven primarily by the increase of consecutive O3-exceeding days” – correlation!
Line 163: “a lion’s share…” – consider revising the wording!
Line 165: What do you mean by quasi-saturation? How does it work? What is the mechanism preventing further increase in concentrations? Related to measurement limitations at the stations?
Line 166: “suggested that there was a quasi-saturation of O₃ inside Beijing City, and an expansion of weather systems conducive to O₃ formation from Beijing toward the southwest of the BTH box during 2017” - So the weather systems conducive to O₃ formation were previously focused on urban centers and now it has expanded to surrounding regions?! Please comment.
Line 177: “Since it is highly unlikely” – please explain with data (e.g., emissions, land use/development) why it is highly unlikely!
Line 249: “into two groups” – why these two groups?
Line 327: include full forms in the section titles rather than acronyms.
Line 320-323: So, the increased ozone is due to reduction in removing processes (low advection and low mixing) while the production is the same and not increased?
Line 343: “… in the former” - do you mean O₃ exceeding days?
Please comment on your choice for compare the average conditions over (for example) 31 days for O₃ exceeding days to average over 152 clear days? What happens if you compare O₃ exceeding days to average over the entire period including both clear days and O₃ exceeding days?
Fig 12: what does the concentration in ppb in parentheses refer to? Figure details are not clear (e.g., isoline labels are hard to read, 5880 gpm is not even labeled)

Technical corrections:
I suggest using different markers in Figures 1,2, and 4, so that different curves are discernible on a grayscale (black and white) version of your manuscript.
Table 3, 4: write complete captions rather than “same as…”
Figures 5,6: complete the captions.
Line 478 and 492: hyperlinks don’t work, please check!
Citation: https://doi.org/10.5194/egusphere-2023-1088-RC2
- AC2: 'Reply on RC2', Run Liu, 29 Sep 2023
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1088/egusphere-2023-1088-AC2-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2023-1088-AC2

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2023-1088', Anonymous Referee #1, 22 Jul 2023

This paper analyzes the cause of 2015-2020 positive ozone trends in megacities in China. While the topic is important, the main conclusion of this study is not well supported by the analyses. In addition, the presentation, including the logic, word expression, and figure quality requires substantial improvement. I recommend at least a major revision before it can be re-considered to be published in ACP.
Main concern:

The authors emphasize the role of meteorology and diminish that of emission change as the key cause of the ozone rise between 2015-2020 in many places of the text, but in most places, there is no direct evidence to approve or disapprove, and the conclusions seem to be arbitrary, I list several questions related to this point below that need to be addressed.

(1) Line 166-167: Why is this simply attributed to weather system? (e.g. lines 166-168, 178-180, and many others).

(2) Line 177-180: For what reason it is “highly unlikely emission change”? It is not convincing to guess the cause simply based on the spatial pattern of ozone change. In addition, the ozone data used in this study is smoothed from observations in the TAP dataset, thus it may not reflect the true ozone change in the regions with no direct observation.

(3) The function of Section 3.2 is very confusing to me. The paper is about 2015-2020 trends, but here only the difference between 2015 and 2017 is analyzed. Even though the ozone difference between 2017 and 2015 is mostly driven by weather anomalies, the authors do not explain what weather system can sustain high ozone from 2017 to 2018-2020. Analyses of yearly differences cannot be simply applied to explain the 6-year trend.

(4) The authors list “ozone at high ozone stations unchanged while ozone at low ozone station increase” as a major finding (Line 235). If it is driven by weather, I wonder what weather system could selectively influence sites with different ozone levels. It more likely reflects chemical factors. This is a key concern.

(5) Line 210-223: VOCs emission change is not considered here. And again this is for difference between 2015 and 2017, it doesn’t explain the trend at all.

(6) Section 3.3 is not convincing as well. It should try to explain what weather system contributes to more ozone consecutive day from 2015 (as authors state that it drives the ozone increase), but figures are not helpful for this purpose. Figure 11 only shows that meteorological parameters can explain some of the ozone variability, Figures 12-13 show that WPSH can influence weather patterns, but is there any hint of an increasing influence of WPSH on consecutive ozone days? It might be useful to first clarify the weather patterns for consecutive ozone days, and explain what system can explain an increase in the frequency of such weather pattern during 2015-2020.
Other comments

Line 100, Before Table 1, please consider introducing the purpose for such classification.

Line 116: missing ppb

Line 158-160. It is quite unclear what the calculation stands for, and how it leads to the conclusion that. Please clarify. Please also carefully clarify the rationale of other formulas.

Figure 3: Should “episodes” be a better word compared to “days” for the y-axis, since the variables plotted are “days”?
The expression needs to be improved, and the use of words needs re-consideration. For example, what does “quasi-saturation” stand for? Please revise “Same as Figure 5 except for YRD” to “Same as Figure 5 but for YRD”. Please carefully check others.

Figure quality can be improved, by increasing resolution and avoiding contours on shadings if both represent the same variable (Figs 5-6)

Citation: https://doi.org/10.5194/egusphere-2023-1088-RC1
- AC1: 'Reply on RC1', Run Liu, 29 Sep 2023
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1088/egusphere-2023-1088-AC1-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2023-1088-AC1
RC2:
'Comment on egusphere-2023-1088', Anonymous Referee #2, 15 Aug 2023
The authors explore the potential mechanism driving the observed increase in surface Ozone during 2015-2020 over three megacity clusters in eastern China. Observational data for several pollutants from the Chinese National Environmental Ministry of Environmental Protection and Tracking Air Pollution in China dataset are analyzed in the paper to explore the trends in surface ozone over the study regions for the period of interest. Further, reanalysis data from ERA5, NCEP and NCAR are used to investigate the correlation between the evolving weather systems and the positive ozone trends. The study approach is mainly based on statistical analysis of observational data.

General comments:

The paper presents the meteorological conditions conducive to ozone formation (e.g., increased solar radiation) as potentially driving the positive ozone trends, rather than an increase in the anthropogenic emissions or a combination of both. While this is an important and interesting topic, some concerns need to be addressed in the paper before publication. The paper section structure, wording and logic, and the overall presentation can be further improved. More information needs to be included in the paper to further support the hypothesis that weather systems and changing meteorological conditions are responsible for observed increase in O3. Please consider the following suggestions:
List the processes (e.g., photochemistry) and precursors involved in the production of ozone, explicitly with tables and/or graphs (e.g., EKMA ozone isopleth diagram). Explicitly show the correlation (even if a weak correlation) between emissions of precursors (e.g., NOx, VOCs) and O₃ levels.

Compare the meteorological conditions to longer range time periods to clearly demonstrate that conditions have evolved towards increased ozone production. Comment on why these conditions have changed.

Include information on how land use/development was changed during the same period, to compare against the spatial expansion of high O₃ from urban centers to surrounding regions (past vs current).

Authors acknowledge that their results are mainly based on statistical correlations and further investigation into causal relationships is needed, perhaps with a use of a chemical/transport model. I agree and I’d like to emphasize that this topic is a great case for a model-based investigation, although it might be out of scope for the current manuscript. Model scenario simulations, with different input emissions and for various meteorological conditions, are crucial for further investigating this topic. All models have limitations, but their power and capability in investigating air quality and transport scenarios cannot be dismissed.

Specific comments:
Line 23: “These favorable meteorological conditions greatly facilitated the formation of O3” - suggests causal relationship, while only correlation is established in the paper…, please consider revising.
Line 37: “The concentrations of air pollutants SO₂, NOx, CO, PM10 and PM2.5 in China have been significantly reduced since 2013” – what about VOCs?
Figure 1,2,3,4: What caused the reduction in 2020? The Covid19 pandemic related closures and slowed down activities perhaps? You can see the same reduction in Figures 2, 3 and 4. Is this related to decreased emissions of precursors in 2019-2020 or changing meteorological conditions?
Line 85: “time interval of 1 h” do you mean a temporal resolution of 1 h, or your data is for only a 1 hour interval?
Line 93: “duration of O3 pollution,” please elaborate.

Line 93: “can be divided into consecutive O3-exceeding days with four or more days…” - please explain why this particular division was used?
Line 117: The decrease in 2020 suggests correlation with emissions…
Line 118: For completeness, please define “p” before use.
Line 127: “Is it due to changing O₃ photochemical processes or changing meteorological parameters?” – still the big question!
Line 137: How does this expansion correlate with the expansion of urban/industrial regions to not previously developed regions (perhaps industries were relocated to surrounding regions from urban centerers?)
Lines 141 to 144: Why compare the entire 2015-2020 period for high O₃ stations to the sub-period 2015-2017 for low O₃ stations?
Line 144: “quasi-saturation” – define.
Line 145: “approximately 100 ppb” - what are the instrumental/measurement limitations for these sites?
Line 147: “Did it have anything to do with the increase of consecutive O₃-exceeding days” – correlation!
Line 154: “expanded by about a factor of five from 2015 to 2017. ” - how did the land use/development change during this period?
Line 155: how big in area is the BTH box? How does it compare to the resolution of the data you analyzed?
Line 156: “66.42 ppb in2015 (31 days, Fig. 5a) to 69.44 in 2017 (62 days, Fig. 5b)” - comparing averages over different time periods (and number of days), how do you justify this comparison?
Line 159: Not clear what the equation represents. Consider labeling with variables and defining the equation prior to usage….
Line 162: “driven primarily by the increase of consecutive O3-exceeding days” – correlation!
Line 163: “a lion’s share…” – consider revising the wording!
Line 165: What do you mean by quasi-saturation? How does it work? What is the mechanism preventing further increase in concentrations? Related to measurement limitations at the stations?
Line 166: “suggested that there was a quasi-saturation of O₃ inside Beijing City, and an expansion of weather systems conducive to O₃ formation from Beijing toward the southwest of the BTH box during 2017” - So the weather systems conducive to O₃ formation were previously focused on urban centers and now it has expanded to surrounding regions?! Please comment.
Line 177: “Since it is highly unlikely” – please explain with data (e.g., emissions, land use/development) why it is highly unlikely!
Line 249: “into two groups” – why these two groups?
Line 327: include full forms in the section titles rather than acronyms.
Line 320-323: So, the increased ozone is due to reduction in removing processes (low advection and low mixing) while the production is the same and not increased?
Line 343: “… in the former” - do you mean O₃ exceeding days?
Please comment on your choice for compare the average conditions over (for example) 31 days for O₃ exceeding days to average over 152 clear days? What happens if you compare O₃ exceeding days to average over the entire period including both clear days and O₃ exceeding days?
Fig 12: what does the concentration in ppb in parentheses refer to? Figure details are not clear (e.g., isoline labels are hard to read, 5880 gpm is not even labeled)

Technical corrections:
I suggest using different markers in Figures 1,2, and 4, so that different curves are discernible on a grayscale (black and white) version of your manuscript.
Table 3, 4: write complete captions rather than “same as…”
Figures 5,6: complete the captions.
Line 478 and 492: hyperlinks don’t work, please check!
Citation: https://doi.org/10.5194/egusphere-2023-1088-RC2
- AC2: 'Reply on RC2', Run Liu, 29 Sep 2023
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1088/egusphere-2023-1088-AC2-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2023-1088-AC2

Peer review completion

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

AR by Run Liu on behalf of the Authors (29 Sep 2023) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (14 Oct 2023) by Jayanarayanan Kuttippurath

RR by Anonymous Referee #1 (29 Oct 2023)

Suggestions for revision or reasons for rejection

The revision has partly addressed my concerns. The clarity of sections 3.1 and 3.2 has been largely improved. However, Section 3.3 is still not convincing and does not show sufficient novelty to meet ACP standard. It may require another round of substantial revision. My comments are to the revision-tracked version.

I suggest use “variability” other than “trends” in the title and the text, because 2015-2020 are too short to derive statistically meaningful trends (only 6 data points). It also makes much more sense if the authors prefer to highlight meteorological conditions of 2017 and 2019 in their analysis.

Line 98: may rephrase to “some commonly-used methods are applied in this study.”

Line 140-146: It is not necessary that high ozone concentrations are at urban centers, as titration would be strong at urban centers which lead to lower ozone compared to suburban regions. Please provide clear information to support this statement.

Line 151: Has Figures 5 been introduced before? I suggest show raw site measurement instead of the gridded data because the later may introduced unrealistic smooths.

Line 206-207. Many other studies have suggested this hypothesis. Suggest remove “suggested by XXX”, instead just use them as references.

Line 208-209: I suggest tune down this statement. It is only a possible and partial cause.

Section 3.3: Could the title of 3.3 be something like “Causes of ozone expansion at low-concentration sites and saturation at high-concentration sites”. I am still not clear whether “saturation” is a precise word to describe the “ozone remained nearly constant”.

Line 225-262: Suggest shorten this part. It takes too long to start the discussion of meteorology as stated by the subtitle.

Line 285-294: It is still very difficult to understand what exactly explain the “saturation” at high-ozone sites. Why “This saturation effect was the result of enhanced rates of atmospheric dispersion, dry deposition and photochemical loss at high O3 concentrations”? Please clarify with data supported.

Line 294-305: Again, why this only causes ozone increase in low-ozone sites, but not at high-ozone sites? It looks like it is an important finding from the observations but no convincing reasons are provided.

My judgement is that the study does not add significant novelty to the meteorological cause of high ozone in 2017 and 2019, because the impact of tropical cyclone and subtropical high is well-known. This is can be seen in Sections 3.3.2-3.3.3 that the study cites and repeats many existing research. Please highlight what’s novel in this analysis. Why this happens in 2017 and 2019? Why this extends the ozone episodes? Can such weather pattern explain the observed ozone increase in low-ozone site and the saturation of high-ozone site?

Figure 2. I am confused about the y-axis title of Figure 2. Ozone days has lower than 20 ppbv of MDA8 ozone? Please check carefully.

Hide

RR by Anonymous Referee #2 (31 Oct 2023)

Suggestions for revision or reasons for rejection

• I couldn’t find any reference to Table R1 and Figures R1 to R3 (in Author’s response document) or the corresponding information in either the main manuscript or the supplement? Please include at least some of this information in the manuscript.

• Also, the following paragraph as added text in Author’s response doesn’t appear in Author’s tracked changes. I wonder why that is?
“Hu W. et al. (2023), in collaboration with this study, conducted a statistical analysis to assess processes that contribute to high O3 formation in PRD when TCs were present in the northwest Pacific. They investigated the impact of the distance between TCs in the northwest Pacific and PRD on the O3 concentration in the PRD from 2006 to 2020. They found that the large numbers of consecutive O3-exceeding days in 2017 and 2019 relative to 2015 were primarily attributable to the greater occurrence of downdrafts and stable atmospheric conditions brought about by mid-distance category TCs. This finding clearly establishes that changing frequency of mid-distance category TCs (i.e. changing meteorological conditions) is the cause of the increases in the numbers of consecutive O3-exceeding days as well as the higher O3 concentrations in PRD. Ongoing study by our research group further shows that the mid-distance category TCs are predominately those TCs with tracks starting around the southern Philippines and ending near Korea and/or Japan. Since TC tracks in northwestern Pacific are strongly controlled by WPSH, we conclude that both Philippines-to-Korea/Japan track TCs and corresponding distribution and intensity of WPSH contributed to the higher consecutive O3-exceeding days in PRD from 2015 to 2020.”

Hide

ED: Reconsider after major revisions (11 Nov 2023) by Jayanarayanan Kuttippurath

AR by Run Liu on behalf of the Authors (15 Nov 2023) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (22 Nov 2023) by Jayanarayanan Kuttippurath

RR by Anonymous Referee #1 (12 Dec 2023)

ED: Publish subject to technical corrections (16 Dec 2023) by Jayanarayanan Kuttippurath

AR by Run Liu on behalf of the Authors (17 Dec 2023) Manuscript

Journal article(s) based on this preprint

05 Feb 2024

What caused large ozone variabilities in three megacity clusters in eastern China during 2015–2020?

Tingting Hu, Yu Lin, Run Liu, Yuepeng Xu, Shanshan Ouyang, Boguang Wang, Yuanhang Zhang, and Shaw Chen Liu

Atmos. Chem. Phys., 24, 1607–1626, https://doi.org/10.5194/acp-24-1607-2024,https://doi.org/10.5194/acp-24-1607-2024, 2024

Short summary

Tingting Hu, Yu Lin, Run Liu, Yuepeng Xu, Boguang Wang, Yuanhang Zhang, and Shaw Chen Liu

Supplement

https://doi.org/10.5194/egusphere-2023-1088-supplement

Tingting Hu, Yu Lin, Run Liu, Yuepeng Xu, Boguang Wang, Yuanhang Zhang, and Shaw Chen Liu

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Month	HTML	PDF	XML	Total
Jun 2023	158	54	6	218
Jul 2023	50	12	4	66
Aug 2023	43	7	2	52
Sep 2023	30	10	6	46
Oct 2023	28	8	5	41
Nov 2023	15	7	1	23
Dec 2023	19	9	1	29
Jan 2024	16	4	0	20
Feb 2024	1	1	0	2
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.

Preprint (1973 KB)
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Short summary

We hypothesize that the cause of the worsening O₃ trends in the Beijing-Tianjin-Hebei region, the Yangtze River Delta, and Pearl River Delta from 2015 to 2020 is attributable to the increased occurrence of meteorological conditions of high solar radiation and positive temperature anomaly under the influence of West Pacific Subtropical High, tropical cyclones as well as mid-high latitude wave activities.


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