Long-term O<sub>3</sub>–precursor relationships in Hong Kong: field observation and model simulation

Wang, Yu; Wang, Hao; Guo, Hai; Lyu, Xiaopu; Cheng, Hairong; Ling, Zhenhao; Louie, Peter K. K.; Simpson, Isobel J.; Meinardi, Simone; Blake, Donald R.

doi:https://doi.org/10.5194/acp-17-10919-2017

Articles | Volume 17, issue 18

https://doi.org/10.5194/acp-17-10919-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/acp-17-10919-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 17, issue 18

Research article

|

15 Sep 2017

Research article |

| 15 Sep 2017

Long-term O₃–precursor relationships in Hong Kong: field observation and model simulation

Yu Wang, Hao Wang, Hai Guo, Xiaopu Lyu, Hairong Cheng, Zhenhao Ling, Peter K. K. Louie, Isobel J. Simpson, Simone Meinardi, and Donald R. Blake

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Final revised paper (published on 15 Sep 2017)
Supplement to the final revised paper
Preprint (discussion started on 14 Mar 2017)
Supplement to the preprint

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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RC1: 'Review of" Long term O3-precursor relationships in Hong Kong: Field observation and model simulation" by Wang et al.,', Anonymous Referee #1, 24 Apr 2017
- AC1: 'Responses to reviewers' comments', Hai GUO, 21 Jun 2017
RC2: 'Review', Anonymous Referee #2, 08 May 2017
- AC2: 'Responses to reviewers' comments', Hai GUO, 21 Jun 2017

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Hai GUO on behalf of the Authors (21 Jun 2017) Author's response Manuscript

ED: Referee Nomination & Report Request started (23 Jun 2017) by Andreas Hofzumahaus

RR by Anonymous Referee #2 (14 Jul 2017)

Suggestions for revision or reasons for rejection

The quality of the paper has improved significantly. However there are still a few issues which the authors want to address before publication in ACP. Here I only repeat my initial questions and include additional comments ("New"):

Major issues:

1) In most figures intra- and inter-annual variations are significantly larger than the 2005-2014 trend. For instance, the O3 trend shows the highest increase from 2005-2014 (0.67 ppb/yr) in autumn (Fig. 3). However, this trend is only determined by 3 "outlier" months of the years 2012, 2013, 2014. These 3 months are just 10% of this specific data set. Another example is Fig. 5 which shows very large scatter in O3 data for the autumn season. Also, for instance Fig. S10 about the annual trends of VOC/NOx ratios is largely determined by the last two years. The question is: how robust are all the trends shown in this paper?

New:
I want to state that the term "outliers" I used in my initial comment does not refer to any characteristics of this data, which could be regarded as "bad" data, and I understand that the data shown in box-whisker plots consists of a larger data set. This is why I put the term "outlier" in brackets. My statement focused on the fact that these few years at the end of the reporting period 2005-2014 completely determine the statistical trend and one should be cautious to deduce a trend and this should be mentioned in the text. Looking into the VOCs/NOx ratio time series (previously S10, now S17), for instance, it seems that there has been some significant variability. For instance the years 2009, 2011, and 2012 show significantly enhanced VOCs/NOx ratio. Assuming the year 2015, just following the 2005-2014 time series, would show any values comparable to those seen in 2009, 2011 and 2012, the trend analysis would yield a completely different results. The similar comment would refer to O3 time series (now S1). The authors should make the point why they believe that such variability could be excluded for future years and that their trend analysis is justified in this sense.

Other comments:

Page 4 L13-14:
How was the accuracy of 1-7% determined?

New:
I assume that a "measured mixing ratio" would ultimately depend on the weekly span checks and calibration. What makes a "measured mixing ratio" different from an "actual mixing ratio"?

Page 5 L25-29:
The authors only measured 21 VOCs. What assumptions did the authors have on other VOCs not measured, but needed as an input for MCM?

New:
The authors should include their comment specifically with respect to MCM in their manuscript.

Page 7, L16:
With regard to the precursors NOx, total VOCs and CO did the authors calculate arithmetic means or medians? Would there be differences?

New:
I primarily referred to O3 precursors, not O3 itself. I doubt that the number of data determines, whether data ensembles are distributed normally or not. Rather it is an intrinsic characteristic of the specific data ensemble. The authors should mention in the manuscript that they used arithmetic means in order to compare with other studies. Unfortunately, it does not make the use of arithmetic means more correct, the more studies have used this quantity.

Page 12 L11:
I was just wondering if the definition of daytime (0700-1900 LT) is valid regardless what season is concerned.

New:
The authors should include their answer in the manuscript.

Page 21, L17:
"...increased emissions of alkenes from traffic related sources". Is this due to enhanced alkene emissions from changes in the composition of the traffic fleet or from increased traffic volume? If it is the latter, then emissions of aromatic compounds would also increase.

New:
The authors should include their answer in the manuscript.

Page 21, L20-21:
Diesel driven vehicles emit significantly less VOCs than gasoline driven vehicles. In other words was the DCV program a significant contribution to the overall traffic related alkene emissions?

New:
The authors should include their answer in the manuscript.

Page 21, L26-28:
Why would the AVOC (alkane) contribution to O3 formation not increase with increasing alkane levels in 2005-2013?

New:
The authors should include their answer in the manuscript.

Page 22, L6-7:
The authors state that 90% of isoprene was emitted from biogenic sources, while traffic sources were less than 5%. From what sources did the remaining 5% isoprene come from?

New:
The authors should include their answer in the manuscript.

Referee Report: PDF

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ED: Reconsider after minor revisions (Editor review) (14 Jul 2017) by Andreas Hofzumahaus

AR by Hai GUO on behalf of the Authors (24 Jul 2017) Author's response Manuscript

ED: Publish as is (16 Aug 2017) by Andreas Hofzumahaus

AR by Hai GUO on behalf of the Authors (17 Aug 2017)

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Short summary

Though the Hong Kong government has made great efforts toward a reduction in emissions, ambient O₃ levels have presented an increasing trend in the past decade. Data analysis and model simulations indicated that the locally produced O₃ in Hong Kong varied by seasons, while regional transport from the PRD region made a substantial contribution to ambient O₃ in Hong Kong and even increased in autumn. This long-term study has important implications for other Chinese cities to reduce O₃ pollution.

Long-term O3–precursor relationships in Hong Kong: field observation and model simulation

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Interactive discussion

Peer-review completion

Long-term O₃–precursor relationships in Hong Kong: field observation and model simulation