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Peer-Review Record

Characteristics of Aerosol Extinction Hygroscopic Growth in the Typical Coastal City of Qingdao, China

Remote Sens. 2022, 14(24), 6288; https://doi.org/10.3390/rs14246288
by Nana Liu 1,2, Shengcheng Cui 1,2,3,*, Tao Luo 1,2,3, Shunping Chen 1,4, Kaixuan Yang 1,4, Xuebin Ma 1,4, Gang Sun 1,2 and Xuebin Li 1,2,3
Reviewer 1:
Remote Sens. 2022, 14(24), 6288; https://doi.org/10.3390/rs14246288
Submission received: 4 November 2022 / Revised: 6 December 2022 / Accepted: 7 December 2022 / Published: 12 December 2022
(This article belongs to the Section Atmospheric Remote Sensing)

Round 1

Reviewer 1 Report

This paper addresses an important problem - hygroscopic growth (HG) on the aerosol extinction – for coastal environment. The authors propose an improved retrieval algorithm for aerosol extinction HG factor by taking aerosol type and particle number concentration into account. With long-term field measurements in Qingdao, the authors use an aerosol backward trajectory tracing model to classify the aerosol types into land source, sea source, and/or the mixed. Finally, the HG characteristics of different aerosols types under different seasons were obtained.

Overall, the article is well organized and is in good presentation. However, there are some minor issues needing to be improved: 

 

1.     The title seems to be more suitable as “Characteristics of aerosol extinction hygroscopic growth in the typical coastal city of Qingdao, China”;

2.     Page 1, the abstract needs to be rewritten to highlight the work with some necessary quantitative results obtained using the proposed algorithm.

3.     Give full spellings for all the terminologies at their first appearance, e.g., GDAS, MODIS,...,

while some abbreviations (e.g., PNC) are redefined;

4.     In Subsection 2.1.1, technical specifications of different instruments are suggested to be listed in one table, including measurement range, resolution, accuracy, sampling frequency, and so on;

5.     In Table 3, the authors should give detail values or ranges for both RMSE and R2, to explain which value or range for the classification for aerosol type in different season is rational and correct;

6.     Page 9, “pure Marine,…”should be “pure marine, …”;

7.     Page 10, “… in the analyze of HGFext…”, analyze -> analysis;

 

8.     Page 13, Figure 8 b1 and c1 -> Figure 8 (b1) and (c1), FIG. 8 b1 -> Figure 8(b1); Please check the full text.

Author Response

Please see the attachment!

Author Response File: Author Response.doc

Reviewer 2 Report

 

The manuscript is written well and it can be accepted after a moderate revision. I have few specific comments as listed below which may improve the scientific contents of the manuscript.

General Comments:

1. Diurnal feature of AOD along with the visibility data is found to be missing in the manuscript. It is one of the important parameters to explain the variability data. Temporal asymmetry in aerosol optical characteristics is strongly significant in clean (high-altitude, remote, continental and coastal) sites. Authors should elaborate more on this section with relevant recent works reported elsewhere.

2. Can you explain how the visibility varied during the day with aerosol particle number concentration or with other available aerosol optical parameters ?

Specific Comments:

1. Line no. 139: Please used a proper reference instead of using ‘Chwala’s research’.

2. Line no. 165-166: The sentence, ‘It is one of the most…products.’ can be remove as you have describe similar description in the previous sentence. Please mention temporal and spatial resolution of data what you have used in the manuscript. The same can be updated for other data sources.

3. Line no. 184-188: Do you meant RH > 50% for δext,wet in relevant to Equations 1 and 2 ? Please elaborate it.

4. Line no. 293-295: Since you have spectral AOD values, you can estimate Angstrom Exponent (AE). You can also examine the three aerosol types from the AOD vs AE scatter plot.

5. Line no. 300-302: The mixing aerosol types can be explained from the AOD vs AE scattered plot.

6. Figure 2: Diurnal feature of visibility data is found maximum during ~ 12:00 - 22:00 LTC and after that it start falling in the Figure 2. Is this pattern same for other months ? From this study you can see diurnal asymmetry/symmetry of visibility data.

7. Figures 4, 7 and 8 : Apparently, there is lack of observational data during 2020-05. Please mention it in the text.

Author Response

Please see the attachment!

Author Response File: Author Response.doc

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