Assessing the Impact of Natural and Anthropogenic Pollution on Air Quality in the Russian Far East

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript uses ground-based and satellite observational data on the composition of the atmosphere containing major air pollutants (NO₂, SO₂, CO, O₃, PM) and analyses were performed in a three-dimensional WRF-Chem numerical model. The impact of forest fires and transboundary transport of pollutants from China on air quality in the Russian Far East was demonstrated. The work is very valuable and interesting, with elements of novelty. Minor inaccuracies are listed below:

INTRODUCTION. Clearly state the novelty of your research.

Lines 83-89; The last sentence is unnecessary. Remove it.

ABBREVIATIONS (e.g. line 196 and others). Explain the abbreviation/symbol the first time you use it. Even if the acronym is familiar to you, it may not be clear to readers. Review the entire manuscript and fill this in.

Fig. 4. Describe the left Y-axes (parameter + unit) in detail for greater clarity.

Fig. 9-12. The information that the data is observed without units is confusing. You should write that it is the AQI (air quality index). All graphs must have labelled axes (parameter + unit) for greater clarity.

Author Response                                         

First of all, we are thankful to the reviewer for carefully reading the manuscript and for the valuable comments on its structure and content. Without any doubt, they will help to improve the quality of the manuscript and the perception of the text by the readers. We tried to take into account most of the reviewer’s comments. New/changed text in the corrected manuscript highlighted my green colour.

General Comments:

I think this is worthwhile research/work I would like to see it published. I also think there is a case here for air quality in the region to be receiving more attention.

But, I also found the write-up frustrating. Maybe just my opinion, but the paper would benefit significantly from a rethink about where detail and discussion focus, and a rewrite to reflect this.

Recommending Accept BUT subject to a major rewrite.

Major Comments/Concerns:

1. I personally found the Abstract frustrating. I would like to have seen more detail on exactly what was done and what the outcomes/findings. For example, the nature of the study/analysis does not appear to be clearly defined and the outcomes are very vague. You say ‘Evaluation of two current factors in the future state air quality reports are suggested…’ but don’t say what the two factors are… There are also some specific minor issues below, but I think the abstract needs work, maybe a rewrite highlighting a few key findings and their consequences, and something about the scope of required future work?

We rearranged and shortened the abstract to make it more logical and precise in the relation of the works done

1. No detail of the ground-based monitoring anywhere in the main text...  

We added explanatory text about ground-based meteorological observations to 3.1 and about ground-based observation data of atmospheric pollutants to 3.2. We did not put this text as an extra section in a chapter 2

1. Results, Line 166: Maybe you could say something about how Fig 4 was produced in the Methods before starting the Results with ‘According to the analysis of Fig. 4b’ or at the very least linking to relevant sections of the Supporting Information? Absolutely huge jump here, and it is again frustrating because we have a lot of detail regarding the WRF-Chem model inputs (which I think is mostly other people’s work?), then nothing on local data sources, or how the data was analysed. What was compared to what to generate Figure 4? I am guessing/hoping the work is good, but I honestly have no idea because I am missing even an indication of the care and attention that went into data analysis, which I think is the work you are actually reporting the results of?

We changed section 3.1 by adding information on the observation data and how the Fig.4 was produced. Also we re-structurized this section to make it more coherent and logical - starting from air temperature analysis and ending on the wind direction. Finally, we added a few sentences related to the additional potential cause for the observations-model data differences. Also we redraw Fig.4 making it a bit easier for a reader to understand.

1. There is some (again I am guessing) good quality analysis of meteorological parameters (e.g. wind speed, direction, air temperature, etc) in the results, but you only provide detailed discussion of CO (Figure 9 and related text) and nothing like Fig 4 and the scope of analysis of the Meteorological data. Then, there re is one figure showing examples for other species later. Given that your focus is air pollution impact, I would have expected more on the comparison of model and measurements of other air pollution data, especially as you highlight O3 and NO2 in the results and NO2 in the abstract? Either that or more of an effort to join up weather conditions and pollution events in the region or to identify the parameters that would allow you quickly extrapolate to your findings to larger datasets, longer time periods?    

This is a fair comment, thank you.

We did not plot anything like Fig.4 for the chemical species, since we analysed only correlation between the modelled and observed data (since the observed data were available as Air Quality Index and can not be transformed to the mixing ratio directly). Therefore we decided to keep correlation coefficient values for chemical species directly in a text.

We extended Fig.9 adding also plots for other species and provided the analysis of these plots in the text before the FIg.9. In addition, we extended a bit the analysis of the correspondence between pollutant mixing ratio in January 2023 (Fig.12).

1. In the Introduction, line 67 onwards: You say ‘The main contributors to air pollution in the city are identified as local sources such as machinery manufacturing, energy production, transportation, and others. Nevertheless, reports [8-14] do not provide information (including quantitative assessments) regarding the potential contribution of forest fires and transboundary transport from China to the air quality of the Amur Region.’ You also go on to say ‘The aim of this study is to assess the potential contribution of forest fires and transboundary transport of pollutants to ground-level air pollution in selected regions of the Russian Far East, using three-dimensional numerical modeling in conjunction with measurement data.’ So, I was expected you to make some comment in either the results or conclusions regarding on how much of the in-city pollution is likely from city/urban source and how much is external? I appreciate you are only looking at very short abouts of data, but the process used to select those periods has hopefully told you something about how representative they were? Anything on either might help the case for and focus of further work?

Thank you for the comment. In general from the chosen cases (Jul 2015 and Jan 2023) it is not easy to determine the contribution of local anthropogenic sources in, for example, Amur Region to air pollution. In the first case a significant contribution from wildfires, mainly in the north of Amur Region, overcovers other sources of pollutants. But we added discussions about possible effects of domestic anthropogenic emission sources on the air quality in Amur Region in January 2023.

Also, some minor comments, technical and/or practical, but these are not comprehensive as I think attention should focus on the above major concerns at this stage: 

1. Abstract, line 22: Maybe change ‘…how two mentioned phenomena…’ to ‘how the two mentioned phenomena’ or think about specifically name the phenomena?

We complemented this phrase with the following explanation:

“how two mentioned phenomena - wild fires and transboundary pollution - could influence air quality”

1. Abstract, line 25 and after: ‘The model performance…’ which model? Guessing WRF-Chem or some model you built with your three data sets? Likewise, your go on to say ‘By using numerical modelling potential cases…’ Is this using outputs from WRF-Chem, or is this some combination of that and local air quality data? It is really unclear what actual local measurements you have… 

You wrote “Abstract, line 25 and after: ‘The model performance…’ which model?”. But in the sentence above of the original abstract we wrote “In the current study the ground- and satellite-based observation data of the particular pollutant atmospheric composition (NO2, CO, SO2, O3, aerosols) together with 3-D numerical modelling (WRF-Chem) were applied to demonstrate”. We think that it is straightforward which model we are talking about in the particular sentence.

You wrote “Likewise, your go on to say ‘By using numerical modelling potential cases…’ Is this using outputs from WRF-Chem, or is this some combination of that and local air quality data? It is really unclear what actual local measurements you have… “ . You are correct. These are results of WRF-Chem modelling. If we talk in the manuscript about measurements data we used a phrase “measurements or observations data”. When we talk about modelling data - we always mean WRF-Chem output, because it is the only model described in the Abstract/Data and Methods. But we agree that the particular sentence was unreal. We changed it in the following way - “The potential cases of the air quality change in Amur region and surrounding territories caused by seasonal wildfires in the northern Amur region, Zabaykalsky Krai, and the Republic of Yakutia (July 2015) and transboundary pollution from Northeastern China (January 2023) were demonstrated by WRF-Chem modelling.”.

1. Introduction, line 54: I think ‘gathers’ is not the right word? Did you mean ‘generates’ or ‘produces’ or do you mean it is it a ‘vector, funnelling pollution into the region’ ?

Here we wanted to say that there are relatively large anthropogenic sources on the territory of the Heilongjiang province. We corrected the word ‘gathers’ with a word ‘concentrates’. So now it looks like this - “For example, Heilongjiang province which is on the Russian-Chinese border, concentrates relatively large sources of anthropogenic pollutants…”

1. Methods, line 95: what do you mean by ‘The correctness of the investigation periods was also verified…’ The quality of the measurement data or that the selected periods were representative forest fire-dominated and anthropogenic-dominated time periods?

Here we meant the second - “that the selected periods were representative forest fire-dominated and anthropogenic-dominated time periods”. We added a brief explanatory phrase to the text.

1. (Methods, Table 1: Guessing this will be on one page in final draft?)

Yes

1. Methods, Paragraph starting line 140: Maybe say that is in from EDGAR in first sentence? I know it is currently start half way into paragraph and in Figures but when dealing with multiple data sets/models/sources of information it is important to be clear where you are using model outputs and where you are using measurements.

Agree, we mentioned in the first sentence that the data is based on EDGAR inventory.

1. Methods, line 154: Might be on safer ground with this time but specifically, is this ‘biomass burning’ generally or ‘identified biomass burning emission sources’? Maybe I am wrong/confused but I thought FINN used satellite data? However, the data looks like points than the ‘smears’ I would have associated with a satellite image of an actual forest-fire? Maybe outside the scope of this paper but it leads me to wonder how that data was handled/processed.

Yes, indeed, satellite data are used to produce FINN dataset. But FINN is emission data, not concentration. Therefore the data look like points (sources). In the original text we wrote “.. emissions of NO₂ (a), CO (b), and BC (c) from biomass burning, based on the FINNv2.5 database..”.

1. Results, Fig 4: what is the correlation coefficient? Guessing it is conventional Pearson R.

Yes, you are right. This is a Pearson correlation coefficient. We added the corresponding explanation to the Fig.4 caption.

Reviewer 2 Report

Comments and Suggestions for Authors

Review Report on “Investigating of the potential factors influencing air quality in the Far East of Russia”

The aim of this study is to assess the potential contribution of forest fires and transboundary transport of pollutants to ground-level air pollution in selected regions of the Far East of Russia. For this purpose, WRF-Chem model with surface meteorological and satellite data is used.

This study is a valuable contribution to the body of knowledge aimed at understanding how to quantify the contributions of meteorological chemical formation, and horizontal transport to air quality during winter (January)and summer (July)in different regions of the Far East Russia using WRF-Chem model.

The manuscript is a comprehensive paper concerning the implications of forest fire emissions on air quality in the study region. However, the presented study has some shortcomings. Accurate discussions on the performance of model results depend on eliminating these deficiencies. These are shown below.

Finally, I believe that the paper by Nerobelov et al. can be accepted for publication in the journal after the major revision, including the questions and discrepancies discussed below.

MAJOR POINTS

1. Abstract: The abstract is very long and extremely confusing. It's difficult to follow, so it should be shortened.
2. Keywords: "Forest fire" or "forest fire emissions" can be added to the keywords. There is no need to repeat the “modeling”.
3. Introduction: It would be appropriate to provide more detailed information on emission sources in the research region. Furthermore, information on forest fires affecting the Amur region needs to be explained in detail.
4. Table 1 appears messy. This table should be prepared in a more organized manner.
5. Results and Discussion: The authors should explain why they used 2023 data at the beginning of the results section. Otherwise, confusion arises.
6. Section 3.1 was written in an extremely confusing order. It would be beneficial to rewrite this section more fluently, paying attention to the logical order.
7. Evaluation of the WRF-Chem model against surface temperature, wind speed and wind direction observations in the region during July and January 2015 reveals that there is no close agreement between the modeled and observed values. For example, in Figure 4, inconsistencies in temperature, wind speed and wind direction are clearly seen. The reason for this discrepancy needs to be better explained.
8. 5: The authors suggest that forest fires may have contributed to the underestimation of air temperature in Figure 5. Explaining this result through the interaction of SW radiation with the mechanism of air temperature reduction during biomass burning is meaningless due to the scale difference and is a very forced explanation. Instead, a more plausible explanation could be that model configurations, such as the use of high-resolution meteorological data, IC/BC, chemical schemes for some physical processes related to fire emissions, etc., may affect forecasting ability.
9. Conclusion section: The opening paragraph of this section should be rewritten to reflect the purpose of the study. This creates confusion.

MINOR POINTS:

1. Abstract: Lines 23-25: Jan>January; Jul>July.

2.Fig.1: The blue circles and numbers do not match.

Review Report on “Investigating of the potential factors influencing air quality in the Far East of Russia”

The aim of this study is to assess the potential contribution of forest fires and transboundary transport of pollutants to ground-level air pollution in selected regions of the Far East of Russia. For this purpose, WRF-Chem model with surface meteorological and satellite data is used.

This study is a valuable contribution to the body of knowledge aimed at understanding how to quantify the contributions of meteorological chemical formation, and horizontal transport to air quality during winter (January)and summer (July)in different regions of the Far East Russia using WRF-Chem model.

The manuscript is a comprehensive paper concerning the implications of forest fire emissions on air quality in the study region. However, the presented study has some shortcomings. Accurate discussions on the performance of model results depend on eliminating these deficiencies. These are shown below.

Finally, I believe that the paper by Nerobelov et al. can be accepted for publication in the journal after the major revision, including the questions and discrepancies discussed below.

MAJOR POINTS

1. Abstract: The abstract is very long and extremely confusing. It's difficult to follow, so it should be shortened.
2. Keywords: "Forest fire" or "forest fire emissions" can be added to the keywords. There is no need to repeat the “modeling”.
3. Introduction: It would be appropriate to provide more detailed information on emission sources in the research region. Furthermore, information on forest fires affecting the Amur region needs to be explained in detail.
4. Table 1 appears messy. This table should be prepared in a more organized manner.
5. Results and Discussion: The authors should explain why they used 2023 data at the beginning of the results section. Otherwise, confusion arises.
6. Section 3.1 was written in an extremely confusing order. It would be beneficial to rewrite this section more fluently, paying attention to the logical order.
7. Evaluation of the WRF-Chem model against surface temperature, wind speed and wind direction observations in the region during July and January 2015 reveals that there is no close agreement between the modeled and observed values. For example, in Figure 4, inconsistencies in temperature, wind speed and wind direction are clearly seen. The reason for this discrepancy needs to be better explained.
8. 5: The authors suggest that forest fires may have contributed to the underestimation of air temperature in Figure 5. Explaining this result through the interaction of SW radiation with the mechanism of air temperature reduction during biomass burning is meaningless due to the scale difference and is a very forced explanation. Instead, a more plausible explanation could be that model configurations, such as the use of high-resolution meteorological data, IC/BC, chemical schemes for some physical processes related to fire emissions, etc., may affect forecasting ability.
9. Conclusion section: The opening paragraph of this section should be rewritten to reflect the purpose of the study. This creates confusion.

MINOR POINTS:

1. Abstract: Lines 23-25: Jan>January; Jul>July.

      2.Fig.1: The blue circles and numbers do not match.

Author Response

First of all, we are thankful to the reviewer for carefully reading the manuscript and for the valuable comments on its structure and content. Without any doubt, they will help to improve the quality of the manuscript and the perception of the text by the readers. We tried to take into account most of the reviewer’s comments. New/changed text in the corrected manuscript highlighted my green colour.

The aim of this study is to assess the potential contribution of forest fires and transboundary transport of pollutants to ground-level air pollution in selected regions of the Far East of Russia. For this purpose, WRF-Chem model with surface meteorological and satellite data is used.

This study is a valuable contribution to the body of knowledge aimed at understanding how to quantify the contributions of meteorological chemical formation, and horizontal transport to air quality during winter (January)and summer (July)in different regions of the Far East Russia using WRF-Chem model.

The manuscript is a comprehensive paper concerning the implications of forest fire emissions on air quality in the study region. However, the presented study has some shortcomings. Accurate discussions on the performance of model results depend on eliminating these deficiencies. These are shown below.

Finally, I believe that the paper by Nerobelov et al. can be accepted for publication in the journal after the major revision, including the questions and discrepancies discussed below.

MAJOR POINTS

1. Abstract: The abstract is very long and extremely confusing. It's difficult to follow, so it should be shortened.

We tried to make the abstract more clearer and logical by reducing and rearranging its parts.

1. Keywords: "Forest fire" or "forest fire emissions" can be added to the keywords. There is no need to repeat the “modeling”.

Thank you. We added a keyword “Wildfires” and removed “Modelling”

1. Introduction: It would be appropriate to provide more detailed information on emission sources in the research region. Furthermore, information on forest fires affecting the Amur region needs to be explained in detail.

We added a bit more information about pollutant sources on the territory of interest. Also we provided information regarding wildfires in the Russian Far East to the Introduction.

1. Table 1 appears messy. This table should be prepared in a more organized manner.

In similar studies this structure is usually used to briefly describe the main experiment settings. We are not sure if it is possible to reorganize the table making it clearer. But we tried to make it visually more understandable by adding “borders” to the lines and columns and using bold text.

1. Results and Discussion: The authors should explain why they used 2023 data at the beginning of the results section. Otherwise, confusion arises.

This information was provided in Section “2. Materials and methods” of the original manuscript - “Based on the analysis conducted (Appendix 1, A1) of satellite and ground-based measurement data, two periods were selected for further investigation of air pollution in the Amur Region: July 2015, corresponding to forest fires in the Russian Far East confirmed in Dynamics of Forest Fires in the Russian Far East [16] and January 2023, representing anthropogenic air pollution. The correctness of the investigation periods was also verified by the analysis of synoptic conditions on the territory of Russian Far East and Northeastern China (Appendix 1, A2).”

1. Section 3.1 was written in an extremely confusing order. It would be beneficial to rewrite this section more fluently, paying attention to the logical order.

Thank you, we tried to rewrite this section, making the analysis of air temperature, wind speed and direction more straightforward and going step by step.

1. Evaluation of the WRF-Chem model against surface temperature, wind speed and wind direction observations in the region during July and January 2015 reveals that there is no close agreement between the modeled and observed values. For example, in Figure 4, inconsistencies in temperature, wind speed and wind direction are clearly seen. The reason for this discrepancy needs to be better explained.

We added one possible explanation for the differences between observed and modelled meteorological parameters. Also, regarding the air temperature we added the following text to the manuscript - “Taking into account that on the territory of interest near-surface air temperature amplitude during both months is up to 15-20 deg C, the modelled air temperature bias (0.5-2deg) and STD (2-5deg) still provide the possibility to reproduce daily and monthly air temperature variation.”. Also in the original version of the manuscript there was the following text which also is attributed to the possible differences between observed and modelled near-surface wind - “It should be noted that the observational wind speed and direction data represent 10-minute averages, each of which includes several hundred individual measurements. In contrast, the results of the numerical experiment represent values corresponding to the model time step, which in our case is 2 minutes. This factor may influence the comparison between modeled and observed data, since averaging hundreds of measurements over 10 minutes is expected to smooth out wind gusts that can still appear in the two-minute model outputs.”.

1. The authors suggest that forest fires may have contributed to the underestimation of air temperature in Figure 5. Explaining this result through the interaction of SW radiation with the mechanism of air temperature reduction during biomass burning is meaningless due to the scale difference and is a very forced explanation. Instead, a more plausible explanation could be that model configurations, such as the use of high-resolution meteorological data, IC/BC, chemical schemes for some physical processes related to fire emissions, etc., may affect forecasting ability.

The resolution of the numerical experiment with WRF-Chem in the current study is 24 km when the resolution of ERA5 reanalysis is 0.25deg (~25 km), therefore they are comparable in relation to the resolutions. On top of that, even though ERA5 produces only parameters characterizing atmospheric state, the ERA5 itself is calculated as a part of global circulation model (IFS) which considers aerosol radiative effect on atmospheric radiation as well.

However, according to [https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation-TheIFSanddataassimilation] and [https://www.ecmwf.int/en/elibrary/79697-ifs-documentation-cy41r2-part-iv-physical-processes] in the current setup of the IFS model used to produce ERA5 reanalysis (CY41R2), climatological aerosol data were used in the radiation scheme which definitely can not reproduce local time specific aerosol radiative effect due to wildfires. However, the aerosol effect should be taken into account to ERA5 via the assimilation of observation data, such as the radiance measured by satellites [https://www.ecmwf.int/en/elibrary/79695-ifs-documentation-cy41r2-part-i-observations]. Therefore, this local modelled phenomenon (the impact of time and region specific biomass-burning aerosols on near-surface air temperature) is either not presented in the ERA5 reanalysis data or it is represented wrongly in WRF-Chem. The last could be related to the inaccuracies in biogenic emission data used, modelling of direct aerosol effect or aerosol field which is prognostically estimated in the case of WRF-Chem. We added this information to the manuscript and changed Conclusion/Abstract correspondingly.

1. Conclusion section: The opening paragraph of this section should be rewritten to reflect the purpose of the study. This creates confusion.

We separated the first sentence of the Conclusion and tried to explain the study aim clearer.

MINOR POINTS:

1.Abstract: Lines 23-25: Jan>January; Jul>July.

Corrected

2.Fig.1: The blue circles and numbers do not match.

Probably it was not clear from the caption, but the numbers and circles should not match. Numbers depict regions in focus ( 1 - Republic of Sakha (Yakutia), 2 - Amur Region, 3 - Zabaykalsky Krai (Russia), 4 - Heilongjiang Province (China)) and the circles represent observation stations used to validate the model. We added an explanation to the caption.

Reviewer 3 Report

Comments and Suggestions for Authors

REVIEW COMMENTS:

Title: Investigating of the potential factors influencing air quality in the Far East of Russia

In my opinion, the paper is well-structured, and the findings are significant, there is some of room for improvements for this article. Here are some suggestions to improve the paper:

1. The title can be improved that summarizes the paper's core investigation. My recommendation would be “Assessing the impact of wildfires and transboundary pollution on air quality in the Russian Far East”
2. The abstract should be more precise. Include quantitative statements that highlight the finding. Especially for the sentences in line 33-35 “According to the modelling, in both cases NO₂ concentrations higher than state standards were registered when the concentrations of other pollutants fit the norms.”
3. Is there any sensitivity analysis has been done for this study? Including the missing values or reanalysis for the data set.
4. In line 188-189, please include more discussion regarding this statement “Future studies should therefore consider using simulated data in the form of averages rather than instantaneous values.”

Author Response

First of all, we are thankful to the reviewer for carefully reading the manuscript and for the valuable comments on its structure and content. Without any doubt, they will help to improve the quality of the manuscript and the perception of the text by the readers. We tried to take into account most of the reviewer’s comments. New/changed text in the corrected manuscript highlighted my green colour.

In my opinion, the paper is well-structured, and the findings are significant, there is some of room for improvements for this article. Here are some suggestions to improve the paper:

1. The title can be improved that summarizes the paper's core investigation. My recommendation would be “Assessing the impact of wildfires and transboundary pollution on air quality in the Russian Far East”

Thank you for the suggestion. We changed the manuscript name to “Assessing the impact of natural and anthropogenic pollution on air quality in the Russian Far East”

1. The abstract should be more precise. Include quantitative statements that highlight the finding. Especially for the sentences in line 33-35 “According to the modelling, in both cases NO₂ concentrations higher than state standards were registered when the concentrations of other pollutants fit the norms.”

We rearranged and shortened the abstract to make it more logical and precise in the relation of the works done

1. Is there any sensitivity analysis has been done for this study? Including the missing values or reanalysis for the data set.

At the current moment there was no sensitivity analysis carried out for the particular region/weather conditions. The observed datasets were used as they were available. However, no significant gaps were found for the particular period/region of investigation. For the future investigations we consider an option of making sensitivity tests, thank you for the comment!

1. In line 188-189, please include more discussion regarding this statement “Future studies should therefore consider using simulated data in the form of averages rather than instantaneous values.”

This statement is discussed (justified) in the text before - “It should be noted that the observational wind speed and direction data represent 10-minute averages, each of which includes several hundred individual measurements. In contrast, the results of the numerical experiment represent values corresponding to the model time step, which in our case is 2 minutes. This factor may influence the comparison between modeled and observed data, since averaging hundreds of measurements over 10 minutes is expected to smooth out wind gusts that can still appear in the two-minute model outputs”. Frankly speaking we do not know what else we could add to this. We reformed the statement to make it more clear.

Reviewer 4 Report

Comments and Suggestions for Authors

Requested review of Manuscript ID climate-3956791 ‘Investigating of the potential factors influencing air quality in the Far East of Russia’

General Comments:

I think this is worthwhile research/work I would like to see it published. I also think there is a case here for air quality in the region to be receiving more attention.

But, I also found the write-up frustrating. Maybe just my opinion, but the paper would benefit significantly from a rethink about where detail and discussion focus, and a rewrite to reflect this.

Recommending Accept BUT subject to a major rewrite.

Major Comments/Concerns:

1. I personally found the Abstract frustrating. I would like to have seen more detail on exactly what was done and what the outcomes/findings. For example, the nature of the study/analysis does not appear to be clearly defined and the outcomes are very vague. You say ‘Evaluation of two current factors in the future state air quality reports are suggested…’ but don’t say what the two factors are… There are also some specific minor issues below, but I think the abstract needs work, maybe a rewrite highlighting a few key findings and their consequences, and something about the scope of required future work?
2. No detail of the ground-based monitoring anywhere in the main text...   
3. Results, Line 166: Maybe you could say something about how Fig 4 was produced in the Methods before starting the Results with ‘According to the analysis of Fig. 4b’ or at the very least linking to relevant sections of the Supporting Information? Absolutely huge jump here, and it is again frustrating because we have a lot of detail regarding the WRF-Chem model inputs (which I think is mostly other people’s work?), then nothing on local data sources, or how the data was analysed. What was compared to what to generate Figure 4? I am guessing/hoping the work is good, but I honestly have no idea because I am missing even an indication of the care and attention that went into data analysis, which I think is the work you are actually reporting the results of?
4. There is some (again I am guessing) good quality analysis of meteorological parameters (e.g. wind speed, direction, air temperature, etc) in the results, but you only provide detailed discussion of CO (Figure 9 and related text) and nothing like Fig 4 and the scope of analysis of the Meteorological data. Then, there re is one figure showing examples for other species later. Given that your focus is air pollution impact, I would have expected more on the comparison of model and measurements of other air pollution data, especially as you highlight O3 and NO2 in the results and NO2 in the abstract? Either that or more of an effort to join up weather conditions and pollution events in the region or to identify the parameters that would allow you quickly extrapolate to your findings to larger datasets, longer time periods?     
5. In the Introduction, line 67 onwards: You say ‘The main contributors to air pollution in the city are identified as local sources such as machinery manufacturing, energy production, transportation, and others. Nevertheless, reports [8-14] do not provide information (including quantitative assessments) regarding the potential contribution of forest fires and transboundary transport from China to the air quality of the Amur Region.’ You also go on to say ‘The aim of this study is to assess the potential contribution of forest fires and transboundary transport of pollutants to ground-level air pollution in selected regions of the Russian Far East, using three-dimensional numerical modeling in conjunction with measurement data.’ So, I was expected you to make some comment in either the results or conclusions regarding on how much of the in-city pollution is likely from city/urban source and how much is external? I appreciate you are only looking at very short abouts of data, but the process used to select those periods has hopefully told you something about how representative they were? Anything on either might help the case for and focus of further work?

Also, some minor comments, technical and/or practical, but these are not comprehensive as I think attention should focus on the above major concerns at this stage:  

5. Abstract, line 22: Maybe change ‘…how two mentioned phenomena…’ to ‘how the two mentioned phenomena’ or think about specifically name the phenomena?
6. Abstract, line 25 and after: ‘The model performance…’ which model? Guessing WRF-Chem or some model you built with your three data sets? Likewise, your go on to say ‘By using numerical modelling potential cases…’ Is this using outputs from WRF-Chem, or is this some combination of that and local air quality data? It is really unclear what actual local measurements you have…  
7. Introduction, line 54: I think ‘gathers’ is not the right word? Did you mean ‘generates’ or ‘produces’ or do you mean it is it a ‘vector, funnelling pollution into the region’ ?
8. Methods, line 95: what do you mean by ‘The correctness of the investigation periods was also verified…’ The quality of the measurement data or that the selected periods were representative forest fire-dominated and anthropogenic-dominated time periods?
9. (Methods, Table 1: Guessing this will be on one page in final draft?)
10. Methods, Paragraph starting line 140: Maybe say that is in from EDGAR in first sentence? I know it is currently start half way into paragraph and in Figures but when dealing with multiple data sets/models/sources of information it is important to be clear where you are using model outputs and where you are using measurements.
11. Methods, line 154: Might be on safer ground with this time but specifically, is this ‘biomass burning’ generally or ‘identified biomass burning emission sources’? Maybe I am wrong/confused but I thought FINN used satellite data? However, the data looks like points than the ‘smears’ I would have associated with a satellite image of an actual forest-fire? Maybe outside the scope of this paper but it leads me to wonder how that data was handled/processed.
12. Results, Fig 4: what is the correlation coefficient? Guessing it is conventional Pearson R.

Author Response

First of all, we are thankful to the reviewer for carefully reading the manuscript and for the valuable comments on its structure and content. Without any doubt, they will help to improve the quality of the manuscript and the perception of the text by the readers. We tried to take into account most of the reviewer’s comments. New/changed text in the corrected manuscript highlighted my green colour.

General Comments:

I think this is worthwhile research/work I would like to see it published. I also think there is a case here for air quality in the region to be receiving more attention.

But, I also found the write-up frustrating. Maybe just my opinion, but the paper would benefit significantly from a rethink about where detail and discussion focus, and a rewrite to reflect this.

Recommending Accept BUT subject to a major rewrite.

Major Comments/Concerns:

1. I personally found the Abstract frustrating. I would like to have seen more detail on exactly what was done and what the outcomes/findings. For example, the nature of the study/analysis does not appear to be clearly defined and the outcomes are very vague. You say ‘Evaluation of two current factors in the future state air quality reports are suggested…’ but don’t say what the two factors are… There are also some specific minor issues below, but I think the abstract needs work, maybe a rewrite highlighting a few key findings and their consequences, and something about the scope of required future work?

We rearranged and shortened the abstract to make it more logical and precise in the relation of the works done

1. No detail of the ground-based monitoring anywhere in the main text...  

We added explanatory text about ground-based meteorological observations to 3.1 and about ground-based observation data of atmospheric pollutants to 3.2. We did not put this text as an extra section in a chapter 2

1. Results, Line 166: Maybe you could say something about how Fig 4 was produced in the Methods before starting the Results with ‘According to the analysis of Fig. 4b’ or at the very least linking to relevant sections of the Supporting Information? Absolutely huge jump here, and it is again frustrating because we have a lot of detail regarding the WRF-Chem model inputs (which I think is mostly other people’s work?), then nothing on local data sources, or how the data was analysed. What was compared to what to generate Figure 4? I am guessing/hoping the work is good, but I honestly have no idea because I am missing even an indication of the care and attention that went into data analysis, which I think is the work you are actually reporting the results of?

We changed section 3.1 by adding information on the observation data and how the Fig.4 was produced. Also we re-structurized this section to make it more coherent and logical - starting from air temperature analysis and ending on the wind direction. Finally, we added a few sentences related to the additional potential cause for the observations-model data differences. Also we redraw Fig.4 making it a bit easier for a reader to understand.

1. There is some (again I am guessing) good quality analysis of meteorological parameters (e.g. wind speed, direction, air temperature, etc) in the results, but you only provide detailed discussion of CO (Figure 9 and related text) and nothing like Fig 4 and the scope of analysis of the Meteorological data. Then, there re is one figure showing examples for other species later. Given that your focus is air pollution impact, I would have expected more on the comparison of model and measurements of other air pollution data, especially as you highlight O3 and NO2 in the results and NO2 in the abstract? Either that or more of an effort to join up weather conditions and pollution events in the region or to identify the parameters that would allow you quickly extrapolate to your findings to larger datasets, longer time periods?    

This is a fair comment, thank you.

We did not plot anything like Fig.4 for the chemical species, since we analysed only correlation between the modelled and observed data (since the observed data were available as Air Quality Index and can not be transformed to the mixing ratio directly). Therefore we decided to keep correlation coefficient values for chemical species directly in a text.

We extended Fig.9 adding also plots for other species and provided the analysis of these plots in the text before the FIg.9. In addition, we extended a bit the analysis of the correspondence between pollutant mixing ratio in January 2023 (Fig.12).

1. In the Introduction, line 67 onwards: You say ‘The main contributors to air pollution in the city are identified as local sources such as machinery manufacturing, energy production, transportation, and others. Nevertheless, reports [8-14] do not provide information (including quantitative assessments) regarding the potential contribution of forest fires and transboundary transport from China to the air quality of the Amur Region.’ You also go on to say ‘The aim of this study is to assess the potential contribution of forest fires and transboundary transport of pollutants to ground-level air pollution in selected regions of the Russian Far East, using three-dimensional numerical modeling in conjunction with measurement data.’ So, I was expected you to make some comment in either the results or conclusions regarding on how much of the in-city pollution is likely from city/urban source and how much is external? I appreciate you are only looking at very short abouts of data, but the process used to select those periods has hopefully told you something about how representative they were? Anything on either might help the case for and focus of further work?

Thank you for the comment. In general from the chosen cases (Jul 2015 and Jan 2023) it is not easy to determine the contribution of local anthropogenic sources in, for example, Amur Region to air pollution. In the first case a significant contribution from wildfires, mainly in the north of Amur Region, overcovers other sources of pollutants. But we added discussions about possible effects of domestic anthropogenic emission sources on the air quality in Amur Region in January 2023.

Also, some minor comments, technical and/or practical, but these are not comprehensive as I think attention should focus on the above major concerns at this stage: 

1. Abstract, line 22: Maybe change ‘…how two mentioned phenomena…’ to ‘how the two mentioned phenomena’ or think about specifically name the phenomena?

We complemented this phrase with the following explanation:

“how two mentioned phenomena - wild fires and transboundary pollution - could influence air quality”

1. Abstract, line 25 and after: ‘The model performance…’ which model? Guessing WRF-Chem or some model you built with your three data sets? Likewise, your go on to say ‘By using numerical modelling potential cases…’ Is this using outputs from WRF-Chem, or is this some combination of that and local air quality data? It is really unclear what actual local measurements you have… 

You wrote “Abstract, line 25 and after: ‘The model performance…’ which model?”. But in the sentence above of the original abstract we wrote “In the current study the ground- and satellite-based observation data of the particular pollutant atmospheric composition (NO2, CO, SO2, O3, aerosols) together with 3-D numerical modelling (WRF-Chem) were applied to demonstrate”. We think that it is straightforward which model we are talking about in the particular sentence.

You wrote “Likewise, your go on to say ‘By using numerical modelling potential cases…’ Is this using outputs from WRF-Chem, or is this some combination of that and local air quality data? It is really unclear what actual local measurements you have… “ . You are correct. These are results of WRF-Chem modelling. If we talk in the manuscript about measurements data we used a phrase “measurements or observations data”. When we talk about modelling data - we always mean WRF-Chem output, because it is the only model described in the Abstract/Data and Methods. But we agree that the particular sentence was unreal. We changed it in the following way - “The potential cases of the air quality change in Amur region and surrounding territories caused by seasonal wildfires in the northern Amur region, Zabaykalsky Krai, and the Republic of Yakutia (July 2015) and transboundary pollution from Northeastern China (January 2023) were demonstrated by WRF-Chem modelling.”.

1. Introduction, line 54: I think ‘gathers’ is not the right word? Did you mean ‘generates’ or ‘produces’ or do you mean it is it a ‘vector, funnelling pollution into the region’ ?

Here we wanted to say that there are relatively large anthropogenic sources on the territory of the Heilongjiang province. We corrected the word ‘gathers’ with a word ‘concentrates’. So now it looks like this - “For example, Heilongjiang province which is on the Russian-Chinese border, concentrates relatively large sources of anthropogenic pollutants…”

1. Methods, line 95: what do you mean by ‘The correctness of the investigation periods was also verified…’ The quality of the measurement data or that the selected periods were representative forest fire-dominated and anthropogenic-dominated time periods?

Here we meant the second - “that the selected periods were representative forest fire-dominated and anthropogenic-dominated time periods”. We added a brief explanatory phrase to the text.

1. (Methods, Table 1: Guessing this will be on one page in final draft?)

Yes

1. Methods, Paragraph starting line 140: Maybe say that is in from EDGAR in first sentence? I know it is currently start half way into paragraph and in Figures but when dealing with multiple data sets/models/sources of information it is important to be clear where you are using model outputs and where you are using measurements.

Agree, we mentioned in the first sentence that the data is based on EDGAR inventory.

1. Methods, line 154: Might be on safer ground with this time but specifically, is this ‘biomass burning’ generally or ‘identified biomass burning emission sources’? Maybe I am wrong/confused but I thought FINN used satellite data? However, the data looks like points than the ‘smears’ I would have associated with a satellite image of an actual forest-fire? Maybe outside the scope of this paper but it leads me to wonder how that data was handled/processed.

Yes, indeed, satellite data are used to produce FINN dataset. But FINN is emission data, not concentration. Therefore the data look like points (sources). In the original text we wrote “.. emissions of NO₂ (a), CO (b), and BC (c) from biomass burning, based on the FINNv2.5 database..”.

1. Results, Fig 4: what is the correlation coefficient? Guessing it is conventional Pearson R.

Yes, you are right. This is a Pearson correlation coefficient. We added the corresponding explanation to the Fig.4 caption.

Round 2

Reviewer 4 Report

Comments and Suggestions for Authors

I still find reading this paper hard work. While the authors have done a lot to improve the structure, it still feels strangely weighted if as the title suggests it is an assessment of the “impact of natural and anthropogenic pollution on air quality in the Russian Far East”.

I also can’t help wishing they have taken a little more time to reflect on the balance of reported work.

That said, I think most of my major comments have been sufficiently addressed.

Few very minor comments below, but nothing major.

Recommending editors accept once these are done to their satisfaction.

1. Chemical species names are inconsistently formatted in new sections. For example, authors using both NO2 and NO₂ in abstract. This should be standardised throughout paper.
2. I think I understand based on my reading of your response but “The District itself concentrates on its territory a broad variety of the sources of air pollutants” is hard to follow. Maybe think about rewording?
3. Figure and Table locations need to be tidied, particularly Table 1 and Figures 8 and 12.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf