Spatiotemporal Evaluation of PM₁₀ Concentrations within the Greater Athens Area, Greece. Trends, Variability and Analysis of a 19 Years Data Series

Round 1

Reviewer 1 Report

Authors present in their manuscript a work about the spatiotemporal variation of PM10 during the last 19 years (2001-2018) at five different monitoring sites within the greater Athens area. Further, an interesting analysis has been performed to the time series applying sliding windows of different length. In my opinion, this part of the manuscript needs greater attention by the Authors. I think that this technique needs to be explained in depth and to give more clearness to the results obtained from. What’s are the advantages of this statistical technique? Also the analysis of the complex system entropy results very interesting in the field of environment pollution.

The topic of this manuscript is interesting and it falls in the scope of the Journal. However, this manuscript needs to make a minor revision before it could be accepted by Environments. Comments and suggestion are in the following:

Abstract: what are the key implications of the study? I suggest that the abstract should also include: why you do this study, why did you use this statistical technique and at last, what did you find in this way?

Introduction: paragraph from line 32 to line 51 is totally useless. It seems to be too academic, educational. The Reader of this paper probably will be a specialist of the argument. So this paragraph sounds to be redundant.

Section 2.2: The statistical analysis needs the support of massive samples, and I suggest that the authors provide (i.e in within the Table 1) the valid data for each station of PM10 used in this work.

Line 136-138. This sentence should be placed before, when Authors explain the first step in statistical analysis (window 32 points length and 32 step forward)

Fig.2 – Fig.3: Error bars should be considered in these figures (standard deviation or standard errors).

Fig.9: Caption of this figure could be more comprehensive. What are the whiskers? What are the red lines? And the red circles? Outliers? How have these outliers been selected?

Conclusion. As in the Abstract, but here with a more complete discussion, what are the key implications of the study? why you do this study, why did you use this statistical technique and at last, what did you find in this way?

Minor details

Besides the major points explained before, this Reviewer has a number of minor comments which are listed below. 

• Line 3. Replace “year” with “years”
• Line 15. “the spatiotemporal variation of the suspended particles concentrations and especially” in this work you treat only PM10. The sentence should be changed for only PM10.
• Line 79. “Initiated” could be replaced by “started”
• Line 113. “under the auspices” could be replaced by “within the organization of”
• Line 169. “kind2 should be replaced by “type”
• Line 170. As in line 169.
• Line 324. “as” should be deleted

Author Response

Rebuttal and Point-to-point Response

 

We would like to thank Reviewer's for the valuable time that they spent on the review of our manuscript. We took into serious consideration all issues raised and our manuscript was revised accordingly. We provide the following forms of our revised manuscript: 

(a) paper with all changes marked. 

Each change or add in text is yellow highlighted. The lines and Figures with double strikethrough were deleted and removed from the revised manuscript. 

The manuscript is entitled “PM10_3-Moustris-et-al-environments-template_v21_changes_marked.docx” and is in WORD format.

and 

(b) “clean” paper. 

This is entitled “PM10_3-Moustris-et-al-environments-template_v21.dot” and is in the MDPI’s dot format.

 

We additionally provide a pdf containing this rebuttal and point-point response to the reviewers. 

 

We believe that we responded to all issues raised by changing appropriately or presenting arguments and evidence to the comments to which we have a counter-opinion. 

 

Our revised manuscript was enhanced through this review process and for this reason we would like to thank all reviewers involved.

 

We hope that our responses are adequate. 

 

 

Reviewer #1: 

 

Comment 1:

Authors present in their manuscript a work about the spatiotemporal variation of PM10 during the last 19 years (2001-2018) at five different monitoring sites within the greater Athens area. Further, an interesting analysis has been performed to the time series applying sliding windows of different length. In my opinion, this part of the manuscript needs greater attention by the Authors. I think that this technique needs to be explained in depth and to give more clearness to the results obtained from. What’s are the advantages of this statistical technique? Also the analysis of the complex system entropy results very interesting in the field of environment pollution.

 

Reply 1:

We would like to thank the reviewer for this comment. We would like to inform you that the specific part of the manuscript was deleted and removed from the revised manuscript. We believe that the specific part of the manuscript would be better to be presented in a future paper including the specific analysis exclusively in a more detailed description.

 

Comment 2:

Abstract: what are the key implications of the study? I suggest that the abstract should also include: why you do this study, why did you use this statistical technique and at last, what did you find in this way?

 

Reply 2:

We would like to thank the reviewer for this comment and the chance that we have to clarify this issue. We respond directly to the above questions in reference to the reworded abstract of the revised manuscript.

Key implications: Investigation of seasonality, intraweek, intraday and spatial variations within the GAA and the existing trends through the examined period. 

Why you do this study: To investigate the impacts of the economic crisis and actions of the Greek state during the previous decade, on the PM₁₀ time series within the GAA.

Why did you use this statistical technique: To assist to future development of PM₁₀ forecasting models of hourly, daily, weekly, monthly and annual  horizon.

What did you find in this way? The results showed a significant decreasing trend of PM₁₀ concentrations at all examined stations. This may be due to economic and social reasons but also due to measures taken by the state so as to be harmonised with the European Directives concerning the protection of public health and the atmospheric environment of the European Union (EU) members. 

 

Key implications are also given in the conclusions section.

 

We hope that we respond adequately.

 

 

Comment 3:

Introduction: paragraph from line 32 to line 51 is totally useless. It seems to be too academic, educational. The Reader of this paper probably will be a specialist of the argument. So this paragraph sounds to be redundant.

 

Reply 3:

We thank the reviewer for this comment, as well. We started the Introduction section with this paragraph because it is customary to start with a briefly introduction, in our case for the particulate matters, for readers who maybe are not specialist of the specific argument. Despite that, the whole paragraph was deleted as requested. We hope that we responded adequately.

 

Comment 4:

Section 2.2: The statistical analysis needs the support of massive samples, and I suggest that the authors provide (i.e in within the Table 1) the valid data for each station of PM10 used in this work.

 

Reply 4:

We would like to thank the reviewer for his valuable comment. We also believe that a trustworthy statistical analysis needs the support of massive samples. In our case, the data completeness was from 77.2% (THR station) up to 89.2% (LYK station) and in any case more than 75.0% which is a threshold by the European Union for such statistical treatments concerning air pollution time series. The valid data for each one of the five examined monitoring stations was added in Table 1 as requested. 

Table 1. The characteristics of the examined air pollution monitoring stations within the GAA. Abbr stands for abbreviation and Alt for altitude a.s.I.

Monitoring Station	Longitude	Latitude	Abbr.	Alt. (m)	Characterisation	Data Completeness
Aristotelous	23°43'39''	37°59'16''	ARI	75	Urban- Traffic	85.8%
Lykovrissi	23°47'19''	38°04'04''	LYK	234	Suburban-Background	89.2%
Maroussi	23°47'14''	38°01'51''	MAR	170	Urban- Traffic	82.5%
Agia Paraskevi	23°49'09''	37°59'42''	AGP	290	Suburban- Background	88.7%
Thrakomakedones	23°45'29''	38°08'36''	THR	550	Suburban- Background	77.2%

 

Comment 5:

Line 136-138. This sentence should be placed before, when Authors explain the first step in statistical analysis (window 32 points length and 32 step forward.

 

Reply 5:

We would like to thank the reviewer for this comment. The specific part of the manuscript was deleted and removed from the revised manuscript.

 

Comment 6:

Fig.2 – Fig.3: Error bars should be considered in these figures (standard deviation or standard errors).

 

Reply 6:

We would like to thank the reviewer for this comment. Error bars (Standard Deviation) charts were added next to the initial bar charts with corresponding comments.

 

Comment 7:

Fig.9: Caption of this figure could be more comprehensive. What are the whiskers? What are the red lines? And the red circles? Outliers? How have these outliers been selected?

 

Reply 7:

We would like to thank the reviewer for this comment. The specific Figure 9 was deleted and removed from the revised manuscript.

 

Comment 8:

Conclusion. As in the Abstract, but here with a more complete discussion, what are the key implications of the study? why you do this study, why did you use this statistical technique and at last, what did you find in this way?

 

Reply 8:

We would like to thank the reviewer for this comment. We added some related comments in the Conclusions section (yellow highlighted).

 

Comment 9:

Line 3. Replace “year” with “years”

 

Reply 9:

Replaced as requested.

 

 

Comment 10:

Line 15. “the spatiotemporal variation of the suspended particles concentrations and especially” in this work you treat only PM10. The sentence should be changed for only PM10.

 

Reply 10:

Was changed as requested.

 

Comment 11:

Line 79. “Initiated” could be replaced by “started”

 

Reply 11:

Was replaced as requested.

 

Comment 12:

Line 113. “under the auspices” could be replaced by “within the organization of”

 

Reply 12:

Was replaced as requested.

 

Comment 13:

Line 169. “kind2 should be replaced by “type”

 

Reply 13:

Was replaced as requested.

 

Comment 14:

Line 170. As in line 169.

 

Reply 14:

Was replaced as requested.

 

Comment 15:

Line 324. “as” should be deleted

 

Reply 15:

Was deleted as requested.

Reviewer 2 Report

The manuscript presents a statistical analysis of trends in PM10 concentrations at 5 air quality monitoring sites in the greater Athens area. The data is of daily mean values over 18 years period (2001-2018). The analysis is done by simple descriptive statistics (trends in annual mean) and entropy analysis.

The authors show some interesting findings in the data (mainly a decreasing trend in annual averages over the study period and two distinct types of monthly behavior), and suggest some explanations for these behaviors, but do not provide compelling evidence to support their claims.

I do not see any justification for the entropy analysis, and it is not clear what conclusions are drawn from this analysis.

Another weakness of the manuscript is that the authors try to describe the long term and monthly trends in PM10, but barely describe the sources of PM10 emissions from within the region (other than road transport), sources outside the region (and particularly the role played by natural dust from North Africa and long-term transport from other regions) and the role of meteorology (atmospheric stability and winds).

Last, if the health effects of particulate matter are the main motivation for the study, why not focus on the smaller particles of PM2.5, which are known to be more harmful to human health?  

I recommend rejecting the manuscript. Below are some additional comments the authors might find helpful.

 

Additional comments:

1. The Introduction needs to be rewritten to make it more focused on the main topic of the paper, to describe what is already known in Greece and the region and what the paper has to add.
2. Line 32: PM is not restricted to ground level. Need to rephrase
3. The first paragraph (lines 32-51) is a collection of well-known statements (without any references!). I would suggest the authors to shorten it significantly and lead the reader to the relevant information to this paper.
4. Lines 48-51: not accurate. Most of health effects of PM is attributed to the smaller particles of PM2.5, PM1 and the submicron particles.
5. The second paragraph (lines 52-74) is also redundant and not related to the main research question of the paper. It would be sufficient to give a few sentences with references to the health effects of PM (e.g., World Health Organization, American Heart Association[1]) or leading review papers.
6. From the Introduction it is not clear what the goal of the paper is. What is the knowledge gap that the paper is addressing? Also, what is already known about PM10 levels in the East Mediterranean region?
7. Line 99: " The GAA basin is surrounding by…" change to "surrounded by"
8. Line 105: " sunny days are very common" please provide quantitative data with reference.
9. Line 107: " minimum monthly temperature is" is it the minimum monthly mean? Or mean of daily minimum by month? Please provide accurate description
10. Line 108: " the prevailing winds are south direction winds" is it southerly winds (i.e., coming from the south) or winds flowing to the south? Please use accurate terminology.
11. Lines 108-110: the sentence is not clear. Please rephrase
12. How complete is the data for each of the stations? In other words, how much of the data was missing? Did the authors augment the missing data?
13. Line 142: " The statistical tests are derived with R package". Please use correct reference to R language.
14. Section 2.1: Please add a description of the major emission sources in the region, apart from traffic. Are there any coal-powered power plants? Heavy industry? Waste burning? How much does natural dust contribute?
15. Line 183: "This claim is reinforced by the station's position within the GAA (Fig.1)." It is not clear how the coarse-scale map in Fig 1 supports this statement.
16. Reference 23 is missing
17. Some of the results are for the 2001-2018 period and some is for 2001-2010 (e.g., Fig 3 vs. Figs 4-9).
18. Line 293-296: Since the metro started working in 2000, and the data presented is from 2001, it is not clear what is the impact of the metro on the measurements in this analysis. The same is true for the new airport and the Attiki Odos highway, both of which started in 2001.
19. Line 295: CO2 is a greenhouse gas, and the reduction in its emissions is not relevant for PM. Do the authors have an estimate about the reductions in PM?
20. Lines 308-312: Please provide references to the statements in the paragraph.
21. Lines 313-315: again, please provide references to these statements.
22. A major factor that is often mentioned to have a major effect on traffic emissions is the improvements in vehicle technology. Can the authors address this issue? Is there any information about the changes in vehicle fleet in Greece over the period of 2000-2018?
23. Lines 339-341: units?
24. Lines 341-343: Where is the data for the number of exceedances from the daily mean PM of 50 ug/m3? Figure 8 shows annual mean.

 

[1] Brook, Robert D., et al. "Particulate matter air pollution and cardiovascular disease: an update to the scientific statement from the American Heart Association." Circulation 121.21 (2010): 2331-2378.

Author Response

Rebuttal and Point-to-point Response

 

We would like to thank Reviewer's for the valuable time that they spent on the review of our manuscript. We took into serious consideration all issues raised and our manuscript was revised accordingly. We provide the following forms of our revised manuscript: 

(a) paper with all changes marked. 

Each change or add in text is yellow highlighted. The lines and Figures with double strikethrough were deleted and removed from the revised manuscript. 

The manuscript is entitled “PM10_3-Moustris-et-al-environments-template_v21_changes_marked.docx” and is in WORD format.

and 

(b) “clean” paper. 

This is entitled “PM10_3-Moustris-et-al-environments-template_v21.dot” and is in the MDPI’s dot format.

 

We additionally provide a pdf containing this rebuttal and point-point response to the reviewers. 

 

We believe that we responded to all issues raised by changing appropriately or presenting arguments and evidence to the comments to which we have a counter-opinion. 

 

Our revised manuscript was enhanced through this review process and for this reason we would like to thank all reviewers involved.

 

We hope that our responses are adequate. 

 

 

 

Reviewer #2: 

 

Comment 1:

The manuscript presents a statistical analysis of trends in PM10 concentrations at 5 air quality monitoring sites in the greater Athens area. The data is of daily mean values over 18 years period (2001-2018). The analysis is done by simple descriptive statistics (trends in annual mean) and entropy analysis.

The authors show some interesting findings in the data (mainly a decreasing trend in annual averages over the study period and two distinct types of monthly behavior), and suggest some explanations for these behaviors, but do not provide compelling evidence to support their claims.

I do not see any justification for the entropy analysis, and it is not clear what conclusions are drawn from this analysis.

Another weakness of the manuscript is that the authors try to describe the long term and monthly trends in PM10, but barely describe the sources of PM10 emissions from within the region (other than road transport), sources outside the region (and particularly the role played by natural dust from North Africa and long-term transport from other regions) and the role of meteorology (atmospheric stability and winds).

Last, if the health effects of particulate matter are the main motivation for the study, why not focus on the smaller particles of PM2.5, which are known to be more harmful to human health?  

I recommend rejecting the manuscript. Below are some additional comments the authors might find helpful.

 

Reply 1:

General comments:

We would like to thank Reviewer for the valuable time that he/she spent on the review of our manuscript as well as for his/her constructive comments.   

New figures and comments were added in order to provide compelling evidence to support our claims and conclusions.

The entropy analysis was totally removed from the manuscript.

We believe that if we try to describe the sources of PM₁₀ emissions from within the region (other than road transport), sources outside the region (and particularly the role played by natural dust from North Africa and long-term transport from other regions) and the role of meteorology (atmospheric stability and winds), the size of the specific work would be such that it would make it prohibitive for possible publication. In addition, such an elaboration, which will be combined with the results of this work, is in the future research projects by the authors. In any case, some related comments were added accordingly.

Last, concerning the PM_2.5 concentrations we have to say that there is a limit number of such data. PM2.5 are monitored during the last years in a few locations but the most important is the the records are not so exploitable due to errors (e.g. mean daily PM2.5 concentration greater than PM10 mean daily concentration, etc.). 

 

Additional comments:

 

Comment 1:

The Introduction needs to be rewritten to make it more focused on the main topic of the paper, to describe what is already known in Greece and the region and what the paper has to add.

Reply 1:

The Introduction section was rewritten and some related changes took place.

 

Comment 2:

Line 32: PM is not restricted to ground level. Need to rephrase

Reply 2:

The whole paragraph deleted and removed. 

 

Comment 3:

The first paragraph (lines 32-51) is a collection of well-known statements (without any references!). I would suggest the authors to shorten it significantly and lead the reader to the relevant information to this paper.

Reply 3:

The whole paragraph deleted and removed.

 

Comment 4:

Lines 48-51: not accurate. Most of health effects of PM is attributed to the smaller particles of PM2.5, PM1 and the submicron particles.

Reply 4:

The whole paragraph deleted and removed.

 

Comment 5:

The second paragraph (lines 52-74) is also redundant and not related to the main research question of the paper. It would be sufficient to give a few sentences with references to the health effects of PM (e.g., World Health Organization, American Heart Association[1]) or leading review papers.

Reply 5:

We believe that the specific paragraph is a brief description in order to introduce the reader to PM and is related to the main research because highlights the danger of PM and the need to study their time series, especially in big urban environments such as the GAA. 

 

Comment 6:

From the Introduction it is not clear what the goal of the paper is. What is the knowledge gap that the paper is addressing? Also, what is already known about PM10 levels in the East Mediterranean region?

Reply 6:

Some relevant changes and additions were made in this direction.

 

Comment 7:

Line 99: " The GAA basin is surrounding by…" change to "surrounded by"

Reply 7:

Was replaced as requested.

 

Comment 8:

Line 105: " sunny days are very common" please provide quantitative data with reference.

Reply 8:

Quantitative data added as requested.

 

Comment 9:

Line 107: " minimum monthly temperature is" is it the minimum monthly mean? Or mean of daily minimum by month? Please provide accurate description

Reply 9:

An accurate description added as requested. It is the mean of daily minimum by month and the mean of daily maximum by month respectively. 

 

Comment 10:

Line 108: " the prevailing winds are south direction winds" is it southerly winds (i.e., coming from the south) or winds flowing to the south? Please use accurate terminology.

Reply 10:

In meteorology, the term "south direction winds" or “south winds” means winds that blow from south to north. An appropriate explanation added in brackets.

 

Comment 11:

Lines 108-110: the sentence is not clear. Please rephrase

Reply 11:

The sentence was rephrased accordingly.

 

Comment 12:

How complete is the data for each of the stations? In other words, how much of the data was missing? Did the authors augment the missing data?

Reply 12:

The completeness of data for each one of the five examined monitoring sites was added in Table 1. Furthermore, only the available data was used for the specific analysis. The filling of missing data is in our future work-plan with the application of artificial intelligence techniques.

 

Comment 13:

Line 142: " The statistical tests are derived with R package". Please use correct reference to R language.

Reply 13:

The whole paragraph and the statistical tests were deleted and removed from the manuscript.

 

Comment 14:

Section 2.1: Please add a description of the major emission sources in the region, apart from traffic. Are there any coal-powered power plants? Heavy industry? Waste burning? How much does natural dust contribute?

Reply 14:

A short relevant paragraph was added.

 

Comment 15:

Line 183: "This claim is reinforced by the station's position within the GAA (Fig.1)." It is not clear how the coarse-scale map in Fig 1 supports this statement.

Reply 15:

As we can see in Fig.1, LYK station is located within the urban environment of the GAA (the yellow line). THR and AGP stations are located on the outskirts of the GAA. Finally, the industry area is outside of the urban area (yellow line in Fig.1) on the west-southwest direction.

 

Comment 16:

Reference 23 is missing

Reply 16:

Reference 23 was replaced.

 

Comment 17:

Some of the results are for the 2001-2018 period and some is for 2001-2010 (e.g., Fig 3 vs. Figs 4-9).

Reply 17:

The error was inadvertent and corrected in all figures (2001-2018).

 

Comment 18:

Line 293-296: Since the metro started working in 2000, and the data presented is from 2001, it is not clear what is the impact of the metro on the measurements in this analysis. The same is true for the new airport and the Attiki Odos highway, both of which started in 2001.

Reply 18:

It is real that both metro and the new airport started in 2001. The effects of these new conditions were obviously not immediate. Air pollution was not automatically reduced by their operation, but gradually over time as shown in the figures. For example, the number of subway passengers has been gradually increasing over the years with a simultaneous decrease in traffic due to private cars.

 

Comment 19:

Line 295: CO2 is a greenhouse gas, and the reduction in its emissions is not relevant for PM. Do the authors have an estimate about the reductions in PM?

Reply 19:

Off course CO2 is a greenhouse gas, and the reduction in its emissions is not relevant for PM. On the other hand, when the reduction of CO2 is due to reduction of traffic, probably is conected with PM reduction. The aim of this work is to prove and investigate the reduction of PM10 within the GAA during the last two decades.

 

Comment 20:

Lines 308-312: Please provide references to the statements in the paragraph.

Reply 20:

Relevant reference was provided.

 

Comment 21:

Lines 313-315: again, please provide references to these statements

Reply 21:

Relevant reference was provided.

 

Comment 22:

A major factor that is often mentioned to have a major effect on traffic emissions is the improvements in vehicle technology. Can the authors address this issue? Is there any information about the changes in vehicle fleet in Greece over the period of 2000-2018?

Reply 22:

Unfortunately we do not have the ability to provide such data and information. The only we can say, based on personal experience and knowledge, is that in 1990-1991 there was a major replacement of the car fleet in Athens and in Greece in general, with the introduction of catalytic converters and the replacement of old vehicles. Then, as the standard of living increased, the replacement of old cars and the purchase of new ones was every 7 ~ 10 years. However, after the financial crisis, the sales of new cars decreased up to 70%, according to car sales companies in Greece. At the same time, due to the economic crisis, the use of vehicles was very limited.

 

Comment 23:

Lines 339-341: units?

Reply 23:

In lines 339-341 the corresponding numbers 2 and 5.5 are days of exceedances (no units) as indicated.

 

Comment 24:

Lines 341-343: Where is the data for the number of exceedances from the daily mean PM of 50 ug/m3? Figure 8 shows annual mean.

Reply 24:

The appropriate Figure was not inadvertently presented. The appropriate Figure was added to the revised document.

 

Reviewer 3 Report

This is an important paper because it examines the annual trends of PM10 in the metropolitan Athens area. The study is based on a 19-year concentration time series from five sites. The results highlight how air quality improved in Athens over the last two decades.  

The introduction contains some very rudimentary information about particle physics and particle health effects. I suggest that some of this information be deleted to make the introduction more concise.

The authors used unnecessarily sophisticated trends analysis methods. In fact, some of the figures, which I identify below, give little useful information. To assess annual trends, after controlling for day of the week, season, and weather variables, there are statistical approaches that are easier to use and actually provide results that are more robust.

The manuscript needs some editing. It is written clearly but has some grammatical errors.

A more detailed description of the measurement method is needed.

In figure 2, we can see the monthly concentrations. As the authors note, the sites that are near traffic present higher levels during the winter, while the sites located in the suburbs have higher concentrations during the summer. This figure suggests that the Athens area is impacted by local photochemical pollution as well as by transported particles from regional sources.

In figure 3, we can see the day of the week variability of concentrations. The authors report that they did not find a strong pattern. I do not know what test they used to arrive at this conclusion; however, a simple observation of the results indicates that there is a slight decrease of levels during the weekend. I suggest that the authors take another look at this issue.

I believe that most readers will not pay much attention to figures 4 and 5. There is no clear message; therefore, they add very little to the interpretation of the data. I suggest that this information go to the supplementary material. In lines 240 through 241, the authors report annual trends in micrograms per cubic meter. The trends should expressed in micrograms per cubic meter per year.

Similarly, figures 6 and 7 do not add much to the discussion, and they are not easy to interpret. These figures could go to the supplementary material.

The discussion should stress that much of PM10 in the metropolitan Athens area is affected by transport of pollution from regional sources. A correlation analysis among the sites could support this conclusion.

As I noted above, usually, when scientists study trends over a long periods they control for weather changes. As expected, during years with high winds or more rain PM10 levels go down. Consequently, many papers use regression models in which they control for the day of the week, season, and meteorological parameters. This is perhaps the best way to estimate trends since it controls for weather differences across the years.

Figure 8 shows big differences in trends among sites. It seems that the sites impacted more by traffic and local emissions exhibit more pronounced annual decreases. The authors should discuss these results in more detail.

Overall, despite my comments, the paper the manuscript presents important information that merits publication. It is important to show that there is a steady improvement of air quality in a large European city like Athens. As I said above, I am not sure the trend analysis methods that the authors used were necessary. In fact, the most important conclusions of the study came from the simple regression analysis.

I suggest major revisions prior to publication.

 

 

Comments for author File: Comments.pdf

Author Response

Rebuttal and Point-to-point Response

 

We would like to thank Reviewer's for the valuable time that they spent on the review of our manuscript. We took into serious consideration all issues raised and our manuscript was revised accordingly. We provide the following forms of our revised manuscript: 

(a) paper with all changes marked. 

Each change or add in text is yellow highlighted. The lines and Figures with double strikethrough were deleted and removed from the revised manuscript. 

The manuscript is entitled “PM10_3-Moustris-et-al-environments-template_v21_changes_marked.docx” and is in WORD format.

and 

(b) “clean” paper. 

This is entitled “PM10_3-Moustris-et-al-environments-template_v21.dot” and is in the MDPI’s dot format.

 

We additionally provide a pdf containing this rebuttal and point-point response to the reviewers. 

 

We believe that we responded to all issues raised by changing appropriately or presenting arguments and evidence to the comments to which we have a counter-opinion. 

 

Our revised manuscript was enhanced through this review process and for this reason we would like to thank all reviewers involved.

 

We hope that our responses are adequate. 

 

 

Reviewer #3: 

 

Comment 1:

The introduction contains some very rudimentary information about particle physics and particle health effects. I suggest that some of this information be deleted to make the introduction more concise.

Reply 1:

The specific paragraph of the introduction was deleted.

 

 

Comment 2:

The authors used unnecessarily sophisticated trends analysis methods. In fact, some of the figures, which I identify below, give little useful information. To assess annual trends, after controlling for day of the week, season, and weather variables, there are statistical approaches that are easier to use and actually provide results that are more robust.

Reply 2:

We would like to thank Reviewer for his/her valuable comment. The sophisticated trends analysis methods were totally removed from the revised manuscript.

 

Comment 3:

The manuscript needs some editing. It is written clearly but has some grammatical errors.

Reply 3:

We did our best and we tried to minimize the grammatical errors.

 

Comment 4:

A more detailed description of the measurement method is needed.

Reply 4:

In our opinion, a more detail description of the measurement method is not within the scope of the present work. For this reason, we provide a relevant reference for those who want to read more details.

 

Comment 5:

In figure 2, we can see the monthly concentrations. As the authors note, the sites that are near traffic present higher levels during the winter, while the sites located in the suburbs have higher concentrations during the summer. This figure suggests that the Athens area is impacted by local photochemical pollution as well as by transported particles from regional sources.

Reply 5:

We would like to thank Reviewer for his/her valuable comment. A relevant sentence was added in the specific paragraph.

 

Comment 6:

In figure 3, we can see the day of the week variability of concentrations. The authors report that they did not find a strong pattern. I do not know what test they used to arrive at this conclusion; however, a simple observation of the results indicates that there is a slight decrease of levels during the weekend. I suggest that the authors take another look at this issue.

Reply 6:

Observing Figure 2 we see that at during the weekend there is a relative increase of PM10 mean daily concentration in all stations and especially on Sunday. However, this increase is very small and may be due to the fact that the residents staying at home for many hours during the day, so they use the heating systems more hours than the working days. A relevant sentence was added in the revised manuscript.

 

Comment 7:

I believe that most readers will not pay much attention to figures 4 and 5. There is no clear message; therefore, they add very little to the interpretation of the data. I suggest that this information go to the supplementary material.

Reply 7:

Figures 4 and 5 deleted and removed from the revised manuscript. 

 

Comment 8:

In lines 240 through 241, the authors report annual trends in micrograms per cubic meter. The trends should expressed in micrograms per cubic meter per year.

Reply 8:

The specific lines were corrected as requested.

 

Comment 9:

Similarly, figures 6 and 7 do not add much to the discussion, and they are not easy to interpret. These figures could go to the supplementary material.

Reply 9:

Figures 6 and 7 deleted and removed from the revised manuscript.

 

Comment 10:

The discussion should stress that much of PM10 in the metropolitan Athens area is affected by transport of pollution from regional sources. A correlation analysis among the sites could support this conclusion.

Reply 10:

We would like to thank Reviewer for his/her valuable comment. A relevant correlation analysis took place and a short paragraph with a table was added in the revised manuscript.

Table 2. Correlation analysis among the five examined monitoring sites. Period 2001-2018.

N=2999 cases	AGP (SB)	ARI (UT)	LYK (SB)	MAR (UT)	THR (SB)
AGP (SB)	1.000	0.774	0.821	0.754	0.827
ARI (UT)	0.774	1.000	0.879	0.881	0.709
LYK (SB)	0.821	0.879	1.000	0.870	0.714
MAR (UT)	0.754	0.881	0.870	1.000	0.688
THR (SB)	0.827	0.709	0.714	0.688	1.000

 

 

Comment 11:

As I noted above, usually, when scientists study trends over a long periods they control for weather changes. As expected, during years with high winds or more rain PM10 levels go down. Consequently, many papers use regression models in which they control for the day of the week, season, and meteorological parameters. This is perhaps the best way to estimate trends since it controls for weather differences across the years.

Reply 11:

We would like to thank Reviewer for his/her valuable comment. This is a very interesting and important topic but at this time is not able to be done. First, we do not have the appropriate weather and meteorological data for the five examined locations. Second, as it can easily be understood, if we try to satisfy all Reviewers observations, comments and suggestions then the work will become very large and it will not be possible for publication. Once more, we would like to thank Reviewer for his/her comment. We would take it in consideration for a future work. At this time, we try to investigate the shape of PM10 time series trends and latter we will try to connect these results with meteorological, weather, ect.

 

 

Comment 12:

Figure 8 shows big differences in trends among sites. It seems that the sites impacted more by traffic and local emissions exhibit more pronounced annual decreases. The authors should discuss these results in more detail.

Reply 12:

A short related paragraph was added.

Round 2

Reviewer 2 Report

Comment to: "Spatiotemporal evaluation of PM10 concentrations within the greater Athens area, Greece. Trends, variability and analysis of a 19 years data series".

 

The authors made considerable changes to the manuscript, and yet the study does not appear to be sound. The conclusions made by the authors are very partial and do not account for other potential explanations to the findings. In addition, the authors should revise the language to improve readability.

Below are some specific comments that demonstrate the major concerns.

 

Specific comments:

1. Abstract: …"during the last 19 years" . For someone reading the paper a few years from now, this is meaningless. I suggest changing to "a nineteen years period".
2. A thorough language editing is needed. Few examples:
   2001. Line 59 "Regarding monitoring of PM10 within the greater Athens area (GAA), this initiated started on 2001."
   2002. Line 99: "The bulk of the industry, representing over 95% in power," what does "power" refer to? Power plants? Emissions? Businesses?
   2003. Line 100 "the industry area" should be "industrial area"
   2004. Line 155 is not clear.
   2005. Line 160: "and February are the most “cold” months of the year" Change to "coldest months"

 

3. Figure 1 is at very low quality. Please add a map with the location of residential areas in the GAA. If the authors do not have access to GIS software, Open Street Map can be used: https://www.openstreetmap.org/search?query=athens#map=11/37.9705/23.7634&layers=C
4. Line 153: "In any case, Figure 2 suggests that the GAA is impacted by local photochemical pollution as well as by transported particles from regional sources." Please explain how this conclusion is derived from Fig 2.
5. Line 153: the term "photochemical pollution" refers to secondary pollutants, and mainly ozone. If the authors suggest that some of the PM10 in Fig. 2 is secondary, this needs to be supported by evidence.
6. Line 157: "This is maybe due to the fact that during summer months the PM10 sources present a more “stable” behavior"… another explanation to this behavior is that the meteorology is very similar during the summer (in the east Mediterranean, ~80% of the days during the summer have very similar synoptic pattern – the etesian winds). In addition, on cold nights with clear skies during the winter there is often very strong thermal stability that captures air pollutants near the surface and results in very high concentrations. This is a well-known and documented phenomenon that the authors cannot ignore. Another possible explanation that the authors mention is the contribution of Saharan dust that occurs mainly during the winter, spring and fall. The authors claim that the Saharan dust occurs in Athens only in the spring. This is contrary to my knowledge (e.g., see https://www.hindawi.com/journals/amete/2012/828301/) . Please provide a reference to support this claim.
7. Line 178: "Only Sunday there is a relative increase of PM10 mean daily concentration in all stations. "  This is not supported by Fig 3a. At the ARI LYK and MAR sites the PM10 levels on Sunday are lower than the rest of the week. Please provide a quantitative measure of the change (in concentrations or %).  I think the authors are confusing Fig3a and Fig 3b. Moreover, the authors provide an explanation to the weekend behavior (increased residential heating on the weekends), without considering other potential causes like changes in traffic volumes, which is a common explanation for weekend changes in many studies from other cities. Do the authors have any data or evidence to exclude the option of traffic changes on weekends?  
8. The authors' conclusion in lines 181-185 ("This behaviour may lead to the conclusion that regardless of the characterization of the stations, regardless of the source of the fine-grained suspended particles, their constant level concentration in the atmosphere during working or not working days may be due to re-swing or reflow because of the prevailing meteorological conditions (wind, drought, etc.), even if this occurs under low pollution and light traffic.") is pure speculation and not supported by the measurements. If indeed the meteorology has such a strong impact on the measured concentrations in GAA that it eliminates the temporal difference in emissions (between weekdays/weekends), it would also eliminate differences between the traffic and background sites.
9. Line 207: "This maybe indicates that much of PM10 concentrations within the GAA are affected by dispersion of pollution from regional sources." Again speculation. The temporal correlation is also due to similar meteorological factors that have an impact on all sites in the same direction (increase/decrease in concentrations)
10. Line 249: "During the second period (2010-2018), the use of private vehicles as well as the fuel consumption for heating was reduced in a significant level due to the Greek economic crisis". Can this be supported by data about annual fuel consumption for traffic and heating? Even data at the national level can be useful.

 

Author Response

Rebuttal and Point-to-point Response

 

 

 

General Remarks 1:

The authors made considerable changes to the manuscript, and yet the study does not appear to be sound. The conclusions made by the authors are very partial and do not account for other potential explanations to the findings. In addition, the authors should revise the language to improve readability.

Reply 1:

We would like to thank Reviewer for his/her valuable remarks and for his/her effort in order our paper achieves a better scientific quality. We addressed all issues and responded adequately.

 

 

Comment 2:

Abstract: …"during the last 19 years". For someone reading the paper a few years from now, this is meaningless. I suggest changing to "a nineteen years period".

Reply 2:

We would like to thank the reviewer for this comment. The change was made as requested.

 

Comment 3:

A thorough language editing is needed. Few examples:

Line 59 "Regarding monitoring of PM10 within the greater Athens area (GAA), this initiated started on 2001."

Reply 3:

We would like to thank the reviewer for this comment. The change was made as requested.

 

Comment 4:

Line 99: "The bulk of the industry, representing over 95% in power," what does "power" refer to? Power plants? Emissions? Businesses?

Reply 4:

We would like to thank the reviewer for this comment. The change was made as requested.

 

Comment 5:

Line 100 "the industry area" should be "industrial area"

Reply 5:

We would like to thank the reviewer for this comment. The change was made as requested.

 

Comment 6:

Line 155 is not clear.

Reply 6:

We would like to thank the reviewer for this comment. A part of line 155 was deleted. So, we believe that line 155 is now clear as requested.

 

Comment 7:

Line 160: "and February are the most “cold” months of the year" Change to "coldest months"

Reply 7:

We would like to thank the reviewer for this comment. The change was made as requested.

 

Comment 8:

Figure 1 is at very low quality. Please add a map with the location of residential areas in the GAA. If the authors do not have access to GIS software, Open Street Map can be used: https://www.openstreetmap.org/search?query=athens#map=11/37.9705/23.7634&layers=C

Reply 8:

We would like to thank Reviewer for his/her valuable comment. We tried to use his/her suggestion but it was difficult to add a map with the location of residential areas in the GAA. The map suggested by the Reviewer does not give any significant information for the landscape of the GAA (at least for the zoom we need). We believe that the map we used was enough good in the context of this work. With Figure 1, we just want to show to the reader the landscape and the boundaries of the GAA, the location of the GAA in Greece as well as the position of the five examined monitoring stations within the GAA. We therefore believe that Figure 1 is quite satisfactory and gives the necessary information to the reader.

 

Comment 9:

Line 153: "In any case, Figure 2 suggests that the GAA is impacted by local photochemical pollution as well as by transported particles from regional sources." Please explain how this conclusion is derived from Fig 2.

Reply 9:

We would like to thank the reviewer for this comment. The whole sentence was deleted and removed. The specific sentence was added in the revised manuscript after the suggestion and the request by another Reviewer. 

 

Comment 10:

Line 153: the term "photochemical pollution" refers to secondary pollutants, and mainly ozone. If the authors suggest that some of the PM10 in Fig. 2 is secondary, this needs to be supported by evidence.

Reply 10:

We would like to thank the reviewer for this comment. The whole sentence was deleted and removed. The specific sentence was added in the revised manuscript after the suggestion and the request by another Reviewer. 

 

Comment 1:

Line 157: "This is maybe due to the fact that during summer months the PM10 sources present a more “stable” behavior"… another explanation to this behavior is that the meteorology is very similar during the summer (in the east Mediterranean, ~80% of the days during the summer have very similar synoptic pattern – the etesian winds). In addition, on cold nights with clear skies during the winter there is often very strong thermal stability that captures air pollutants near the surface and results in very high concentrations. This is a well-known and documented phenomenon that the authors cannot ignore. Another possible explanation that the authors mention is the contribution of Saharan dust that occurs mainly during the winter, spring and fall. The authors claim that the Saharan dust occurs in Athens only in the spring. This is contrary to my knowledge (e.g., see https://www.hindawi.com/journals/amete/2012/828301/) . Please provide a reference to support this claim.

Reply 11:

We would like to thank the reviewer for this valuable comment. We reformulated this paragraph, taking into account the remarks of the Reviewer, as follows:

“Concerning the standard deviation of the mean monthly PM₁₀ concentrations (Fig.2b) it can be observed that during summer months is lower than the winter months. This is maybe due to the fact that during summer months the PM₁₀ sources present a more “stable” behaviour than the winter months were the weather conditions determine oil consumption for heating purposes thus increasing or decreasing particulate emissions. Moreover, during summer the meteorological conditions are very stable, presenting a very similar synoptic pattern with no abrupt changes from day to day. In addition, on cold nights with clear skies during the winter there is often very strong thermal stability that captures air pollutants near the surface and results in very high concentrations. January and February are the coldest months of the year for the GAA. February for example, presents often great temperature differences and weather changes from day to day leading, according to our opinion, to great daily differences of oil and wood consumptions for heating purpose thus great daily differences to PM₁₀ emissions.”

 

Concerning the contribution of Saharan dust we reform the whole paragraph (lines 166-171) as follows, adding a new relevant reference:

“Finally, the high standard deviation during spring months (March, April and May) maybe is due to the Saharan dust event which is mainly occurs in Athens during spring period [16,17,18]. According to Dimitriou et al., the maximum probability of dust events, during the years 2018-2018, was detected in spring, when the dust transport pathways were also vertically extended [18]. Dust intrusions from the Sahara desert, mainly from areas in Egypt and Libya, were associated with daily PM10 episodes ([PM₁₀]>50μg/m³) during all seasons, mainly through back trajectories within the layer up to 1000m above ground level. Nevertheless, during spring the frequency of occurrence of the dust episodes was the highest and the dust pathways were vertically extended in comparison with the other seasons. The daily PM10 episodes in winter were mainly connected to northern air masses approaching from the Balkan Peninsula and North Greece [18]. The phenomenon is not observed so often in summer because in Greece strong north winds prevail, known as the “Etesians” or “Meltemia” [19,20].” 

 

New Reference added [18]

Dimitriou, K.; Grivas, G.; Liakakou, E.; Gerasopoulos, E.; Mihalopoulos, N. Assessing the contribution of regional sources to urban air pollution by applying 3D-PSCF modeling. Atmos. Res., 248, 2021, Article number 105187

 

Comment 12:

Line 178: "Only Sunday there is a relative increase of PM10 mean daily concentration in all stations. "  This is not supported by Fig 3a. At the ARI LYK and MAR sites the PM10 levels on Sunday are lower than the rest of the week. Please provide a quantitative measure of the change (in concentrations or %).  I think the authors are confusing Fig3a and Fig 3b. Moreover, the authors provide an explanation to the weekend behavior (increased residential heating on the weekends), without considering other potential causes like changes in traffic volumes, which is a common explanation for weekend changes in many studies from other cities. Do the authors have any data or evidence to exclude the option of traffic changes on weekends?  

Reply 12:

We would like to thank the reviewer for this valuable comment. We reformulated this paragraph, taking into account Reviewer’s comments as follows:

“Only, in urban traffic monitoring stations (ARI, LYK and MAR) a slight decrease of PM₁₀ mean daily concentration occurs during Sunday. However, this reduction is very small and may be is due to the changes in traffic volumes between working and not working days such as Sunday.”

 

Comment 13:

The authors' conclusion in lines 181-185 ("This behaviour may lead to the conclusion that regardless of the characterization of the stations, regardless of the source of the fine-grained suspended particles, their constant level concentration in the atmosphere during working or not working days may be due to re-swing or reflow because of the prevailing meteorological conditions (wind, drought, etc.), even if this occurs under low pollution and light traffic.") is pure speculation and not supported by the measurements. If indeed the meteorology has such a strong impact on the measured concentrations in GAA that it eliminates the temporal difference in emissions (between weekdays/weekends), it would also eliminate differences between the traffic and background sites.

Reply 13:

We would like to thank the reviewer for this valuable comment. The specific paragraph was deleted and removed. 

 

Comment 14:

Line 207: "This maybe indicates that much of PM10 concentrations within the GAA are affected by dispersion of pollution from regional sources." Again speculation. The temporal correlation is also due to similar meteorological factors that have an impact on all sites in the same direction (increase/decrease in concentrations)

Reply 14:

We would like to thank the reviewer for this valuable comment. The specific lines were deleted and removed. We would like also to inform Reviewer that Table 2 and the specific lines (207-209) were added after the recommendation of another Reviewer. 

 

Comment 15:

Line 249: "During the second period (2010-2018), the use of private vehicles as well as the fuel consumption for heating was reduced in a significant level due to the Greek economic crisis". Can this be supported by data about annual fuel consumption for traffic and heating? Even data at the national level can be useful.

Reply 15:

We would like to thank the reviewer for this comment. The specific sentence is supported by data at a national level concerning fuel consumption for traffic and heating (Figure 7). By this way, we reformed the specific sentence as follows:

“During the second period (2010-2018), the use of private vehicles as well as the fuel consumption for heating was reduced in a significant level (Fig.7) due to the Greek economic crisis [22].”

Round 3

Reviewer 2 Report

There are still language and style corrections that need to be addressed. I recomend accepting after style and language editing.

Author Response

Rebuttal and Point-to-point Response

 

 

 

General Remarks Reviewer 2:

There are still language and style corrections that need to be addressed. I recomend accepting after style and language editing.

 

Reply:

We would like to thank Reviewer for the time spent on reviewing our manuscript once more. Indeed, there we we scattered style problems that we have found and corrected. We made several language changes as well. In the manuscript entitled “PM10_3-Moustris-et-al-environments-template-R3-changes_marked”, the reviewer may find all deletions  as red strikethrough text and all insertions-corrections as highlighted text. We hope that we responded adequately.