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Peer-Review Record

A Study on the Long-Term Variations in Mass Extinction Efficiency Using Visibility Data in South Korea

Remote Sens. 2022, 14(7), 1592; https://doi.org/10.3390/rs14071592
by Sohee Joo 1, Naghmeh Dehkhoda 1, Juseon Shin 1, Mi Eun Park 2, Juhyeon Sim 1 and Youngmin Noh 3,*
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Remote Sens. 2022, 14(7), 1592; https://doi.org/10.3390/rs14071592
Submission received: 2 March 2022 / Revised: 20 March 2022 / Accepted: 24 March 2022 / Published: 25 March 2022
(This article belongs to the Section Atmospheric Remote Sensing)

Round 1

Reviewer 1 Report

< General comments >

Generally, this study is very interesting to see the long-term trend in PM10, PM2.5, and mass extinction efficiency (Qe) values over South Korea. Since other factors such as hygroscopicity of aerosols, relative humidity, and other atmospheric compositions are related with the visibility and Qe, further research regarding them is required for a better understanding of the relationship between mass concentrations of PM and Qe in the future. This manuscript needs to be accepted after taking author’s response to the following specified comments.

 

< Specific comments >

- Line 13-14, Line 80-81: To my knowledge, this study doesn’t firstly attempt to analyze the long-term trends in Qe. For example, Cheng et al. (2013) analyzed and showed the trend of Qe over Yangtze River Delta cities during 2001-2011. So, please remove those sentences.

- Line 15: “between 2001 to 2020” → needed to be explained separately for PM10 and PM2.5 because the PM2.5 data is available since 2015.  

- Line 34: “aerosols play” → “aerosols can play”    

- Line 98: “confirmed” → “used”

- Line 102: “was 90%” → “was over 90%”

- Line 102: The relative humidity (RH) of 90 % is too high. Because of the high RH, hygroscopic effects of aerosols can not be neglected in the results of this paper. In case of Cheng et al. (2017)’s study, they selected data where RH was less than 40%. Please, explain the reason why you selected the high threshold value.

- Line 104: “website of the Korea Environment Corporation” → “Air Korea website”

- Line 106: Could you add exact definition of PM10 and PM2.5?

- Line 106-107: As far as I know, PM10 observations have been officially conducted since 1995 and gradually expanded till now. Is there any specific reason to analyze the trend of PM10 from 2001?

- Line 113-115: These sentences are unclear to me. What do you mean by that “if one of the four seasons had a smaller amount of data compared to the other seasons”? Do you mean that you removed three seasons since the other season has more data than the rest three seasons? Please, rephrase these sentences for clear explanation.

- Line 121-122: How did you determine the specific distance of 4km?

- Line 126-128: Are these sites from Air Korea or KMA? Please, add more information about these specified observation sites.

- Figure 1: (1) If possible, please add the location of the Taebaek Mountains since they are important for analysis as written in Line 203-210. (2) The colored dots in Figure 1 seem to indicate Air Korea observation sites, so please modify its caption accordingly. (3) In addition, can you add KMA observation sites into the Figure 1 as shown in Cheng et al. (2013, 2017)?

- Line 137: Remove “first” because it was used repeatedly.

- Line 139-140: Please, rephrase the sentence concisely.

- Line 142: (1) NO2 mixing ratios were used, but no explanation was found in the paper. Did you use NO2 data at the same Air Korea observation sites as used for PM concentrations? Please, add the detailed information of NO2 data to the manuscript. (2) This equation is very empirical based on several assumptions. For example, 0.02 can be used for large cities like Seoul but may not be applicable for Jeju Island. Additionally, Cheng et al. (2017) applied data when RH is less than 40%. So, please be aware of the limitation of this empirical equation and this can cause uncertainties in calculated values.

- Line 145: “Mm-1” → “Mm-1

- Line 146: “PM2.5 -10” → “PM2.5-10” (Please, remove the space)

- Line 208-209: Please, remove or change the sentence “Wonju had the highest annual average concentration of PM” because Seoul showed the highest annual average of PM10 in 2002 during the research period.

- Line 267: Table 4 looks broken. And does the “total” mean the average Qe of the eight observation sites for the entire research period?

- Line 331-343: How did you decide the range for low (19-21 or 9-11), moderate (69-71 or 29-31), and high (139-141 or 69-71) concentrations of PM10 or PM2.5? Please add the reference or reason why these numbers were chosen. Normally, low, moderate, and high PM indicate lower than 31, 31-80, and higher than 81 for PM10, lower than 15, 16-35, and higher than 36 for PM2.5, respectively, according to the Korea’s PM concentration standards.

- Line 346: Please, modify typo “€” into (e).

- Line 387: Remove “(Jung et al … 2003)”.

- Line 390: Remove “(Cheng…2017)”.

- Line 382: (1) Figure 8 can confuse readers because study area and methodology of each research are not the same. I recommend you modify this figure by including data obtained at same city or remove this figure and add a table including information of research domain for each previous study. (2) Why Cheng et al. (2013)’s data is found only in 2011? They analyzed Qe,2.5 from 2001 to 2011. Please, check and add the values to the manuscript.

 

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Initial review of “A Study on the long-term variations in mass extinction efficiency using
visibility data” by Sohee Joo, Naghmeh Dehkhoda, Juseon Shin, Mi Eun Park, Juhyeon Sim and
Youngmin Noh.
In this study, long-term trends in the mass extinction efficiency were investigated using
particle matter (PM) mass concentration and visibility data recorded from 2001 to 2020 at eight
different sites in Korea. The authors show interesting characteristics of the trends in the
relationship between PM concentration and mass extinction efficiency for each site through a
detailed statistical analysis and comparison with the results of previous studies. The results will
help understand the complex aerosol properties in Northeast Asia. This work is worth publishing
if the manuscript is to be revised.
Major Comments:
As the authors mentioned in the manuscript, optical aerosol properties such as visibility are
strongly affected by relative humidity through their hygroscopicity. Although the authors
excluded the data from the analysis when relative humidity was 90% or when the precipitation
and fog occurred, effect of particle growth remained even, when the relative humidity was less
than 90%.
The authors require to further explain the influence of relative humidity with regard to mass
extinction efficiency by indicating mean relative humidity or the rate of high humidity
conditions during the specified period used for analysis. I think it would be more useful to
discuss in the manuscript whether a similar trend of mass extinction efficiency can be seen
under low relative humidity (e.g., RH<50%).
Individual points:
Title:
Please consider adding the region or country name to the title.
L104-L116:
The authors should provide a brief review of observation methods for PM2.5, PM10, and visibility
in Korea, or include related references.
The description of temporal resolution of the original data for this analysis are required.
L157, eq. 2:
I believe the parameter bext should also have the subscript i, because bext is a different equation
between PM2.5, and PM10, as described in L147-148. How can Equation 1 be divided into two
for clarity?
L188, Table 1:
 g/m3=> g/m3
L267, Table 4:
Table 4 lists the broken layout in the PDF.
The value of 2006 in Qe10: 6.00 => 6.0
L323, Figure 6:
 There are sites where the Qe2.5 value increases sharply from late summer to early autumn. Can
the authors explain this main factor?
L313-342:
 Please clarify how you chose the threshold values for the categories of low, moderate, and
high concentrations of PM2.5 and PM10. Is the daily mean value used for this analysis? Although
the range in each category is narrow (3g/m3
 for PM2.5), is there a sufficient dataset available to
obtain yearly mean values?
L343, Figure 7:
 It seems that the variations in Qe2.5 for moderate and high concentrations in each city
increased after 2010. Is it possible to discuss the factors? I am interesting to consider changes in
the spatial scale of aerosol distributions, such as the increase in the local effect under haze
conditions.
L398, “from 0.04 to 0.23 (m2
/g)/mth”
The values of “0.04 (m2
/g)/mth” in the Conclusion section do not appear in the Results and
Discussion sections. Please add an explanation for “0.04 (m2
/g)/mth” to the manuscript. 

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

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