Ground-Level Particulate Matter (PM2.5) Concentration Mapping in the Central and South Zones of Peninsular Malaysia Using a Geostatistical Approach
, Firdaus Mohamad Hamzah 2,3,*, Lam Kuok Choy 4, R. Azizah 3, Lilis Sulistyorini 3, Ririh Yudhastuti 3, Khuliyah Chandraning Diyanah 3, Retno Adriyani 3 and Mohd Talib Latif 3,5Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsNice work! it must be also be useful!
As mentioned the interpolation methods 28
are beneficial and could be extended for the investigation of air pollution distributions in other regions of Peninsular Malaysia. Give at least an example.
what about other regions? conditions? on my opinion the interpolation should be open and demonstrated to have a more larger utility - valueability
This will raise also the readers' interest and enlarge the possibility of quotations.
Describe the method of measuring data of all stations! and if it is not a general/international method, indicate the differences to CEN for example or other legislation (EPA for ex). Only maxim admitted values are indicated. The used data must be technically accepted not only locally!
Author Response
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Reviewer 2 Report
Comments and Suggestions for AuthorsThe reviewed manuscript deals with relationship between humanity and the environment.. This topic seems to stay relevant as long as people continue to pollution and change environmental. It is very important to look for ways to improve the situation. Small particles are very dangerous for the population of almost anywhere on the planet.
The methods used and the results obtained seem adequate. Many areas of the manuscript need improvement.
1. Introduction section is incomplete. It should include four key components: motivation, literature survey, contributions, and the organization of paper. The literature review should contain references that would allow to adequately and fully evaluate your contribution. The number and content of references to studies dedicated to the study area seems to be insufficient. References to other works are accompanied by a fairly brief explanation. Based on this, it is not always clear why this link is given. It seems unnecessary to provide a definition of the term kriging at this point. Please modify this section accordingly.
2. Why was this period chosen in your study (2019-2020)?
3. Line 115-134: This paragraph contains a lot of information that, strictly speaking, is not important for the purpose at hand. There is no information on landscapes, relief, climate, sources of pollutant emissions, etc. Please provide this information in the text of the article.
4. You claim that the 2019 results were heavily impacted by the bushfire and covid in 2020. Why wasn't a different time period chosen for comparison in this case?
5. Fig.2. For what year of measurements were the diagrams made?
6. Line 348-349: It is not clear why this statement was made. Please give more detailed information.
7. Line 349-352: What does this information tell us? How can this be used for forecasting? What are the potential reasons for this? Why is Moran's test needed further if it is not used anywhere else in the work? Please correct this moment.
8. For what reason was it decided to split the data into two zones to construct semi-variograms? Please clarify.
9. Line 372-377: How do these statements apply to your work? Please clarify.
10. Line 460-464: What conclusions about the causes can be drawn/assumed?
Author Response
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Reviewer 3 Report
Comments and Suggestions for AuthorsThe article is generally well-written and on-topic. However, some additional work is needed to fill in the gaps
Line 34 please add references proving that statement.
The paper is generally well-written and aligns with the journal's theme. It addresses an important topic and validity of the research findings.
Please include wider comparison of simlara studies especially showing the use of similar methods and data as you. Please comment in the introduction and refere to some modern studies in this field like Danek et al.'s research published in Scientific Reports The influence of meteorological factors and terrain on air pollution concentration and migration: a geostatistical case study from Krakow, Poland were GWR, Local Moran and Getis-Ord were examined for PM studies.
Please also provide the references for sentence in line 44. Introduction in general should be more detailed.
Line 97 – please describe different parameters
Please add information about type of sensors (reference measurements? Automatic? Manual? What’s the accuracy and uncertainties related to them?)
Please refer to WMO guidelines about the air pollution communication.
What are the sources of PMx in this region?
Are the box plots the best trend representation? Maybe other technique can be added as well that will show the long-term trend.
Comments on the Quality of English LanguageMajor correction needed, english minor correction
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Round 2
Reviewer 2 Report
Comments and Suggestions for AuthorsWhy is it necessary to refer to an article aimed at clarifying the correlation between other pollutants and PM 2.5. Line 46-49.
The introduction (line 68-103) lacks a summary of why these methods of geostatistics and spatial analysis were chosen. Successful use of these methods in studies of air pollution by other authors.
The central zone of what area is the purpose of the study (lines (104-106)?
The question of years of study concerns the idea of whether a given data set is relevant to propose models for a given area. In this case, your data will be applicable for similar situations (Covid, emissions from fires, in general, these are excesses in long-term observations). Extreme situations leading to a serious (non-typical) change in the volume of emitted pollutants seriously affect the resulting interpolation models and the Moran's l index.
Please provide data on the terrain in the characteristics of the study area.
Are there other natural or anthropogenic prerequisites for such a division? The number of stations as an important division criterion seems difficult to perceive.
Unfortunately, it may not be clear to readers how you calculated the performance of a particular kriging model. Please try to add this information.
Author Response
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Reviewer 3 Report
Comments and Suggestions for AuthorsThe authors satisfactorily addressed my comments and made improvements to the article. A few minor additional corrections – I would like the sources of PMx pollutants to be indicated more quantitatively rather than generically. It is obvious that vehicular traffic, industrial activity, and biomass burning are sources essentially for most cities; however, the contribution of individual components can vary significantly depending on the country and location.
Regarding the representation of trends, a box plot is certainly a good tool. However, for analyzing trends themselves, trend decomposition methods can be used. Nevertheless, this is not a critical step, and if the authors believe that the box plot is sufficient, then it's okay.
The paper can be published as it is or after minor changes
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