Modification of Hybrid Receptor Model for Atmospheric Fine Particles (PM_2.5) in 2020 Daejeon, Korea, Using an ACERWT Model

Round 1

Reviewer 1 Report

The paper developed a hybrid receptor model with the combination of a positive matrix factorization (PMF), back trajectory, and Regional Emission Inventory in Asia (REAS), as well as Advanced Concentration Emission and Retention Time Weighted Trajectory (ACERWT). While the study is significant in tracing background areas with no specific emission sources, the presentation of results needs additional effort to improve the science. The results are not clear enough to substantiate why the method. 

Major flaws.

1. The biggest concern is receptor sampling location is limited (only one), which is located in the central region of Korea in the Daejeon Metropolitan region. The establishment of the model can perform well with other new locations (e.g., in China and sea). The data points from the same location in one year can not test the spatial generalizability of sources at all.
2. 3.1 Emission Inventory

Figure 3. The units of emissions are absent. 

In Figure 3, which metrics of air pollutants do you present? For three metrics of air pollutants (PM2.5, SOx, and NOx), at least 15 sub-figures are required to show the total emissions and sector emissions.

1. Regional Emission Inventory in Asia (REAS) version 3.2. Have you compared the dataset of Regional Emission Inventory in Asia (REAS) version 3.2 with other emission inventory including Transport and Chemical Evolution over the Pacific, TRACE-P; Intercontinental Chemical Transport Experiment-Phase, INTEX-B; Model Inter-Comparison Study for Asia, Hemispheric Transport of Air Pollution, HTAP; The Multi-resolution Emission Inventory for China (MEIC).
2. Figure 7 What is the unit for the y-axis?
3. Figure 8 What is the unit for the y-axis? If the unit is % of mass, the total contribution of eight sources in each season is lower than 50% of PM2.5 mass? What is the contribution of unresolved PM2.5 mass? The authors should depict that.
4. Figure 9. The authors should provide figures with high resolution. 

What is the unit for the y-axis? If the red color refers to the higher emissions of specific sources, it seems some source regions are located on the sea. The authors should depict that. The findings derived from Figure 9 seem against the purpose of the study, which aims to improve model performances to explain the contribution overestimation of background area with no specific emission sources, like the Yellow Sea in Korea. 

Minor issues.

Lines 38-39 incomplete sentence

 Moderate editing of English language required

Author Response

Please see the attachment.

Thank you for your reviews. We sincerely have reflected about all your opinions and updated our manuscript with point-by-point responses as below. We also highlighted the corrected part (blue color) in the revised manuscript. 

Author Response File: Author Response.pdf

Reviewer 2 Report

The topic of the work is interesting and current, perhaps the part on methods could be clearer and the results could be more explanatory.

Air pollution continues to have significant impacts on global health, particularly in urban areas.  Carbon monoxide, sulfur oxides, nitrogen oxides, ozone, benzene and atmospheric particulates represent the main pollutants found in the air, currently, the most damage to ecosystems is caused by O3, ammonia and nitrogen oxides (NOX). Tropospheric O3 and black carbon (BC), a constituent of PM, are examples of air pollutants that are short-lived climate forcers and that contribute directly to global warming. In recent decades, the development of knowledge on air pollution has attributed a growing role to atmospheric particulate matter as a polluting component of the air responsible for a significant negative impact on human health and the environment.

This study is undoubtedly of interest to readers because it increases knowledge, concerns a topic of great interest to the scientific community and aims to enhance model performance through the utilization of Advanced Concentration Emission and ACERWT which is integrated with positive matrix factorization (PMF) back trajectory, and Regional Emission Inventory in Asia (REAS).

 However, the work needs a general revision regarding:

- better explain the method and its applicability and benefits on a large scale

- make the results clearer:

- the authors should provide figures with high-resolution

- the units of emissions are absent

- the unit for the y-axis Fig. 7

- the unit for the y-axis 8

Minor editing of the English language required

Author Response

Please see the attachment.

Thank you for your reviews. We sincerely have reflected about all your opinions and updated our manuscript with point-by-point responses as below. We also highlighted the corrected part (blue color) in the revised manuscript. 

Author Response File: Author Response.pdf

Reviewer 3 Report

The research investigates the tendency of hybrid receptor models to overestimate background contributions, specifically focusing on the Yellow Sea in Korea. The study aims to enhance model performance through the utilization of Advanced Concentration Emission and ACERWT which is integrated with positive matrix factorization (PMF), back trajectory, and Regional Emission Inventory in Asia (REAS). The PMF identifies eight sources influencing PM2.5 pollution in Daejeon, Korea, with secondary sulfate being the dominant source. ACERWT reveals high contributions from China, Japan, and Korean regions, reducing the Yellow Sea's impact. Several regions, including eastern China, southern Taiwan, western Tokyo, and central Korea, show high contributions due to large-scale emission facilities.

RPaper is in the scope of journal and in interest of researchers. However, the paper has certain shortcomings that need to be addressed before publication. A broader perspective is missing - I would like to see more  global-wide analysis in introduction and while competing results. Figures are wrongly prepared lacking obvious things like axis units or legends and legends description. It is essential to elucidate the novelty of the study and discuss how this methodology can benefit a wider scientific audience. Additionally, attention should be given to the necessity of discussing uncertainties associated with measurements used in the study.

Please double read paper and correct errors 

Author Response

Please see the attachment.

Thank you for your reviews. We sincerely have reflected about all your opinions and updated our manuscript with point-by-point responses as below. We also highlighted the corrected part (blue color) in the revised manuscript.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

accept

Minor editing of English language required

Author Response

Dear Editor,

We are resubmitting a manuscript, entitling " Modification of hybrid receptor model for atmospheric fine particles (PM_2.5) in 2020 Daejeon, Korea, using an ACERWT model”. We found the reviewers’ and editor’s comments to be constructive and helpful as we revised our manuscript. We sincerely believe that our manuscript has been significantly improved. Please find the attached point-by-point response for more details.

Thank you very much for reconsidering this manuscript.

Sincerely,

Jin-seok Han, Ph.D.

Associate Professor

Department of Environmental Engineering,

Anyang University.

Tel: +82-31-463-1292, cell phone: +82-10-8703-2671

E-mail: [email protected] or [email protected]

Thank you for your reviews. This paper was proofread in English to editage(https://app.editage.co.kr/?type=individual). Fig shows editing certificate.

Author Response File: Author Response.pdf