Assessment of Soil Pollution Levels in North Nile Delta, by Integrating Contamination Indices, GIS, and Multivariate Modeling
, Enas E. Abd Elkhalek 1, Salah Elsayed 3, Rasha M. Abou Samra 4, Abdullah S. Alshammari 5, Farahat S. Moghanm 1, Kamal H. Shaltout 6, Saad A. M. Alamri 7 and Ebrahem M. Eid 7,8,*Round 1
Reviewer 1 Report
In the presented publication, the authors made an effort to estimate the risks of pollution of the north Nile delta with selected chemical elements using the analysis of pollution indexes and the GIS system. The subject matter is important to me and should be presented.
The work, however, after deeper study, shows a number of minor but also more serious shortcomings. I have tried to list the most important of them below:
- It is not clear at all why these particular four elements were taken into account. What does this choice result from? Are there any common sources of contamination with just these elements and not others? In the introductory part, it would be appropriate to include strong arguments in favor of choosing just these three metals and one non-metallic element.
- There is no explanation why samples were taken at the three levels. There are no soil characteristics of the sample, description and presentation of exemplary soil profiles, as well as calculations of the such key parameters as content of particle size fractions (especially the so-called floatable fraction), calculations regarding the content of organic matter as well as the pH of the tested soils at various depths. These parameters are important for the final interpretation of the results obtained. They also say a lot about the mobility of the chemical elements under study.
- Were the samples sieved? If so, through what size sieves? If not, please provide justification.
- The number "0" should be avoided in order to indicate that the concentration is below the limit of quantification of the method. The limits of quantification should be provided.
- The spatial distribution of Igeo (Fig. 4) would be more readable if the grouping of maps was by metals and not by levels. Then the reader would be much easier to judge the changes in the Igeo of a given element with depth.
- There is no detailed description of the presented maps and the observed differences in the concentrations of elements.
- Has the PLI index for the presented samples been calculated using the PLSR and MLR methods? Because it is not clear from the text (line 179-183).
- Table 7. should be corrected. Column 2 or 3 should be omitted as the information from Table 2. is repeated. The columns with the number of samples should be standardized. The percentage should be presented for all values or for none.
- Figure 5 is informative to a very limited extent. Should be replaced with the appropriate table.
In general, the purposes of the presented publication are unclear to me. If the article is to show the problem of pollution of the Nile Delta with the use of appropriate indices and the GIS method, there is no detailed analysis of the obtained results. There is no discussion of differences in index values, no field analysis of local increases or decreases in the tested concentrations. It is also not known why the authors made the effort to research soils on three levels, since practically no conclusions were drawn from it. There is also no analysis and an attempt to indicate specific causes (sources) of pollution, or accumulation, instead of general textbook theses.
On the other hand, if the work was to present the usefulness of statistical methods to study soil pollution, the work should be reformatted in this respect. Corrections should be shown between the calculated igeo index calculated in the traditional way with the PLI index and the PLI parameter predicted by the presented statistical methods. However, in this case, it is not very clear why include GIS information.
In general, I suggest rethinking the work and answering yourself the question of what the authors want to present specifically. This should be followed by the reformatting of the text, a more complete analysis of the obtained data and the formulation of adequate, more complete conclusions - especially since, in my opinion, the collected data allows for such an analysis.
Author Response
- 28. June 2021
Sustainability
Dear Reviewer #1,
Please find the revised manuscript titled ‘Assessment of soil pollution levels in North Nile Delta, by integrating contamination indices, GIS, and multivariate modeling’. Ms. Ref. No.: sustainability-1256613, authored by Mohamed E. Abowaly, Abdel-Aziz A. Belal, Enas E. Abd Elkhalek, Salah Elsayed, Rasha M. Abou Samra, Abdullah S. Alshammari, Farahat S. Moghanm, Kamal H. Shaltout, Saad A.M. Alamri, and Ebrahem M. Eid.
On behalf of my co-authors, I thank you very much for giving us the opportunity to revise our manuscript. We appreciate the positive and constructive comments and suggestions provided by the reviewers on our manuscript. We have carefully studied the reviewers’ comments and have made revisions that are tracked in the revised version of the manuscript. We have tried our best to revise our manuscript according to the reviewers’ comments. Please find attached the revised version of our manuscript, which we would like to submit for your kind consideration. Once again, we would like to express our great appreciation to you and the reviewers for the comments on our manuscript.
Please find below our detailed responses to each of the points raised.
---------------------------------------------------------------------------------------------------------------------
- It is not clear at all why these particular four elements were taken into account. What does this choice result from? Are there any common sources of contamination with just these elements and not others? In the introductory part, it would be appropriate to include strong arguments in favor of choosing just these three metals and one non-metallic element.
Response: We greatly appreciate your critical observations as well as your constructive and helpful comments. We hope that we could address your questions/comments by the explanations and revisions made in the manuscript. The study area is considered highly contaminated with heavy metals, especially the elements Cr, Co, B and Ni (Shaheen et al., 2019). The sources of these elements are the industrial drainage in the El Gharbia main drainage. We have added that in theintroduction section.
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- There is no explanation why samples were taken at the three levels. There are no soil characteristics of the sample, description and presentation of exemplary soil profiles, as well as calculations of the such key parameters as content of particle size fractions (especially the so-called floatable fraction), calculations regarding the content of organic matter as well as the pH of the tested soils at various depths. These parameters are important for the final interpretation of the results obtained. They also say a lot about the mobility of the chemical elements under study.
Response: The study area was classified into order Entisols, there are no morphological differences in the soil profiles, so soil samples were taken at the three levels. The type of soil is clay. We have added that in material and methods section.
Soil properties were determined using the prepared samples (pH, EC, Ca+2,Mg+2, K+, Na+, CO2-, HCO3-, Cl-, SO4-, OM %, CaCO3 %, P% and N%). And more details data for these parameters was added in supplementary file as Table S2.
|
Measured parameters |
Surface soil (0–30 cm) |
Subsurface soil (30–60 cm) |
Underground soil (60–100 cm) |
|||||||||
|
Min |
Max |
Mean |
SD |
Min |
Max |
Mean |
SD |
Min |
Max |
Mean |
SD |
|
|
pH |
8.0 |
8.7 |
8.5 |
0.2 |
8.1 |
9.0 |
8.6 |
0.2 |
8.2 |
9.0 |
8.7 |
0.2 |
|
EC (ds/m) |
0.3 |
1.9 |
0.7 |
0.3 |
0.2 |
2.1 |
0.8 |
0.4 |
0.2 |
1.7 |
0.8 |
0.4 |
|
Ca+2 |
0.5 |
4.8 |
1.6 |
0.6 |
0.8 |
4.0 |
1.6 |
0.6 |
0.7 |
3.0 |
1.6 |
0.6 |
|
Mg+2 |
3.3 |
9.6 |
5.5 |
1.5 |
1.1 |
7.7 |
4.7 |
1.7 |
2.3 |
10.2 |
4.7 |
2.3 |
|
K+ |
0.0 |
1.0 |
0.3 |
0.3 |
0.0 |
1.2 |
0.3 |
0.3 |
0.0 |
1.2 |
0.4 |
0.4 |
|
Na+ |
0.4 |
8.2 |
2.3 |
2.0 |
0.3 |
9.8 |
3.3 |
2.7 |
0.3 |
10.9 |
3.6 |
2.8 |
|
CO2- |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
|
HCO3 -- |
1.8 |
4.2 |
2.9 |
0.8 |
1.8 |
4.8 |
2.9 |
0.9 |
1.2 |
4.8 |
2.8 |
1.2 |
|
Cl- |
3.0 |
9.5 |
5.0 |
1.6 |
2.2 |
9.0 |
5.1 |
2.2 |
2.1 |
10.0 |
5.1 |
1.9 |
|
SO4-- |
0.1 |
10.7 |
1.7 |
1.6 |
0.1 |
12.0 |
2.0 |
2.2 |
0.1 |
8.2 |
2.4 |
2.4 |
|
OM % |
0.0 |
1.9 |
0.7 |
0.6 |
0.0 |
1.3 |
0.3 |
0.3 |
0.0 |
0.9 |
0.2 |
0.2 |
|
CaCO3 % |
0.5 |
45.5 |
9.4 |
9.5 |
0.5 |
40.0 |
7.5 |
8.5 |
0.8 |
13.0 |
6.6 |
3.8 |
|
P% |
0.8 |
30.8 |
11.3 |
8.0 |
1.8 |
27.9 |
13.8 |
7.6 |
0.7 |
22.8 |
11.4 |
6.5 |
|
N% |
2.2 |
5.8 |
2.9 |
0.9 |
2.3 |
16.1 |
3.6 |
3.1 |
2.2 |
5.2 |
2.9 |
0.8 |
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- Were the samples sieved? If so, through what size sieves? If not, please provide justification.
Response: The samples were composited, homogenized, air-dried at 25 to 35 °C, crushed, and sieved to 2 mm.
---------------------------------------------------------------------------------------------------------------------
- The number "0" should be avoided in order to indicate that the concentration is below the limit of quantification of the method. The limits of quantification should be provided.
Response: We mentioned that under every tables (0 value mean that is not detect (ND) and it is below the limit of quantification).
---------------------------------------------------------------------------------------------------------------------
- The spatial distribution of Igeo (Fig. 4) would be more readable if the grouping of maps was by metals and not by levels. Then the reader would be much easier to judge the changes in the Igeo of a given element with depth.
Response: We fully agree with reviewer and the grouping of maps was by metals was added. Old Figures 2, 3 & 4 was replaced by modified Figures 2, 3, 4 &5 in the manuscript.
---------------------------------------------------------------------------------------------------------------------
- There is no detailed description of the presented maps and the observed differences in the concentrations of elements.
Response: GIS is used to see only the distribution of the elements in different soil layers to give overview picture for the area of study and observed differences in the concentrations of elements was presented in different tables in manuscript.
---------------------------------------------------------------------------------------------------------------------
- Has the PLI index for the presented samples been calculated using the PLSR and MLR methods? Because it is not clear from the text (line 179-183).
Response: We have written the method for calculate the PLI under section 2.3.2. As explain below:
The PLI is a geometric average of impurity coefficients (Cif) that defines the contribution of all trace elements in a specific place [47]. Contamination factor (CF) was computed by dividing metal concentration by background value using the following equation [48]:
Pollution load index (PLI) is used to estimate elements concentrations in soils relative to the reference concentration and was calculated using the following equation [49]:
Where CF is the contamination factor and n is the number of metals.
We tested also PLSR and MLR methods as alternative approaches to predict the PLI based on four trace elements. The calculated values from above equations were related to predict values from PLSR and MLR to see the performance of the two models to estimate PLI (Tables 10 & 11 and Figures 6 &7).
---------------------------------------------------------------------------------------------------------------------
- Table 7. should be corrected. Column 2 or 3 should be omitted as the information from Table 2. is repeated. The columns with the number of samples should be standardized. The percentage should be presented for all values or for none.
Response: Table 7 was corrected, column 3 was removed and the percentage presented for all values or for none.
---------------------------------------------------------------------------------------------------------------------
- Figure 5 is informative to a very limited extent. Should be replaced with the appropriate table.
Response: Figure 5 was replaced by Table 8.
---------------------------------------------------------------------------------------------------------------------
In general, the purposes of the presented publication are unclear to me. If the article is to show the problem of pollution of the Nile Delta with the use of appropriate indices and the GIS method, there is no detailed analysis of the obtained results. There is no discussion of differences in index values, no field analysis of local increases or decreases in the tested concentrations. It is also not known why the authors made the effort to research soils on three levels, since practically no conclusions were drawn from it. There is also no analysis and an attempt to indicate specific causes (sources) of pollution, or accumulation, instead of general textbook theses.
Response: Two objectives of this study to show pollution of the Nile Delta by using Igeo and PLI indices and using GIS to see only the distribution of the elements in different soil layers to give overview picture for the area of study. In general, in this location about more than 95% of samples is contaminated to extremely contaminate in three layers according to I-geo and very highly polluted according to PLI. Detailed analysis of the obtained results can be shown in different tables such as Tables 4, 5 & 7 which showed that based on element concentration, Igeo value and PLI value the soil profiles are more polluted and in general no significant different between the three layers. Discussion of differences in index values, no field analysis of local increases or decreases in the tested concentrations. In Table 6 and 9 we presented the data of all field samples for 1geo and PLI, respectively and from the table the reader can see the change between the field but as we wrote in general that the study is very polluted. As well as we make highlight on the sentences which showed the difference in concentration elements between the field. The sources of these elements are the industrial drainage in the El Gharbia main drainage and we added that in manuscript.
---------------------------------------------------------------------------------------------------------------------
On the other hand, if the work was to present the usefulness of statistical methods to study soil pollution, the work should be reformatted in this respect. Corrections should be shown between the calculated igeo index calculated in the traditional way with the PLI index and the PLI parameter predicted by the presented statistical methods. However, in this case, it is not very clear why include GIS information.
Response: In this study statistical methods or new approaches such as PLSR and MLR techniques is the third objective in this work to predict PLI. PLSR and MLR techniques can combine data for a large number of trace elements more than one element such as Ni, Cr, Co and B as input data to predict single index such as PLI to enhance the prediction of a measured variable. Since the Igeo calculated from one element for different profiles, we cannot apply these methods to calculate Igeo. The calculated values of PLI from the traditional way were related to predict values from PLSR and MLR to see the performance of the two models to estimate PLI (Tables 10 & 11 and Figures 6 &7). GIS is other technique to see only the distribution of the elements in different soil layers to give overview picture for the area of study. New approaches such as PLSR and MLR and GIS are a valuable and applicable approach for soil water quality assessment with respect to heavy metals and shows special promise and unique insights for soil layers and to help decision and policy maker.
---------------------------------------------------------------------------------------------------------------------
I hope the explanation given above adequately addresses the reviewers’ comment. I would appreciate if the revised version of our manuscript would be considered for publication in Sustainability.
Sincerely,
Ebrahem M. Eid
[Kafrelsheikh University]
[Botany Department, Faculty of Science, Kafrelsheikh University, Kafr El-Sheikh 33516, Egypt]
[Phone number: 002010 22648840]
[Email address: [email protected]]
Reviewer 2 Report
This paper introdused an interesting approach to study and map soil contamination. I can see that this reseach has an high potential to be used in finding practical solutions for the problem.
Anyway, I have here two questions:
1) Mapping:
Why to use IDW in mapping, and not for eample Kriging? It would be nice to see the equation of IDW in the paper, as it easily leads to circulat 'hot spot' areas. Do the sampling points represent 'hot spots' or are they chosen to give a regional average?
2) PLI and linear models
I started to wonder what is the relationship of PLI and linear models. You have calculated PLI (page 16, lines 383-388. Then you have used linear models to predict PLI. On line 431 you say mathematical models can be used to calculate PLI, but linear models are easy way to do it. But how did you calculate the original PLI? More text on page 6 to explain PLI would be needed.
I would like to hear on line 60, that wahat kind of waste water is used in irrigation. Gray water? And from which sources?
Author Response
- 28. June 2021
Sustainability
Dear Reviewer #2,
Please find the revised manuscript titled ‘Assessment of soil pollution levels in North Nile Delta, by integrating contamination indices, GIS, and multivariate modeling’. Ms. Ref. No.: sustainability-1256613, authored by Mohamed E. Abowaly, Abdel-Aziz A. Belal, Enas E. Abd Elkhalek, Salah Elsayed, Rasha M. Abou Samra, Abdullah S. Alshammari, Farahat S. Moghanm, Kamal H. Shaltout, Saad A.M. Alamri, and Ebrahem M. Eid.
On behalf of my co-authors, I thank you very much for giving us the opportunity to revise our manuscript. We appreciate the positive and constructive comments and suggestions provided by the reviewers on our manuscript. We have carefully studied the reviewers’ comments and have made revisions that are tracked in the revised version of the manuscript. We have tried our best to revise our manuscript according to the reviewers’ comments. Please find attached the revised version of our manuscript, which we would like to submit for your kind consideration. Once again, we would like to express our great appreciation to you and the reviewers for the comments on our manuscript.
Please find below our detailed responses to each of the points raised.
---------------------------------------------------------------------------------------------------------------------
- Why to use IDW in mapping, and not for example Kriging?
Response: We greatly appreciate your critical observations as well as your constructive and helpful comments. We hope that we could address your questions/comments by the explanations and revisions made in the manuscript. The reason for using IDW in mapping is illustrated in lines 218 to 223. The advantage of using IDW in mapping of spatial distribution of heavy metals is that it is efficient. This interpolation method works better with equally distributed points. We have tested other algorithm such as Kriging, and the best algorithm was chosen based on different criteria such the root mean squared error and mean error. IDW and Ordinary kriging are the most popular spatial interpolation methods used in the field of environmental studies. In this study, the concentration of elements is not due to natural sources, but the presence of other sources such as agricultural and industrial drainage, which directly affects the concentration of elements in the soil, which varies based on the distance from the source, and therefore it is better to choose this IDW method.
---------------------------------------------------------------------------------------------------------------------
- It would be nice to see the equation of IDW in the paper, as it easily leads to circulate 'hot spot' areas.
Response: The equation of IDW was added with an explanation of its components under section 2.3.2. The Pollution Load Index (PLI).
---------------------------------------------------------------------------------------------------------------------
- Do the sampling points represent 'hot spots' or are they chosen to give a regional average?
Response: Sampling points represent regional average.
---------------------------------------------------------------------------------------------------------------------
2) PLI and linear models
I started to wonder what is the relationship of PLI and linear models. You have calculated PLI (page 16, lines 383-388. Then you have used linear models to predict PLI. On line 431 you say mathematical models can be used to calculate PLI, but linear models are easy way to do it. But how did you calculate the original PLI? More text on page 6 to explain PLI would be needed.
Response: PLI was calculated according to the equations under section 2.3.2. As explain below:
The PLI is a geometric average of impurity coefficients (Cif) that defines the contribution of all trace elements in a specific place [47]. Contamination factor (CF) was computed by dividing metal concentration by background value using the following equation [48]:
Pollution load index (PLI) is used to estimate elements concentrations in soils relative to the reference concentration and was calculated using the following equation [49]:
Where CF is the contamination factor and n is the number of metals.
We tested also PLSR and MLR methods as alternative approaches to predict the PLI based on four trace elements. The calculated values from above equations were related to predict values from PLSR and MLR to see the performance of the two models to estimate PLI (Tables 10 & 11 and Figures 6 &7).
---------------------------------------------------------------------------------------------------------------------
- I would like to hear on line 60, that what kind of waste water is used in irrigation. Gray water? And from which sources?
Response: Mixing agricultural and industrial drainages waste water from El Gharbia main drain (Kotchenr) with Nile water was used for irrigation in area of study.
---------------------------------------------------------------------------------------------------------------------
I hope the explanation given above adequately addresses the reviewers’ comment. I would appreciate if the revised version of our manuscript would be considered for publication in Sustainability.
Sincerely,
Ebrahem M. Eid
[Kafrelsheikh University]
[Botany Department, Faculty of Science, Kafrelsheikh University, Kafr El-Sheikh 33516, Egypt]
[Phone number: 002010 22648840]
[Email address: [email protected]]
Reviewer 3 Report
- The authors mention that they used IDW interpolation method to estimate and map the I-geo values for different elements throughout the study area. Why this specific algorithm was chosen among many others? Did the authors tested different algorithms and used the one with the better results? Which were the selection criteria for the interpolation algorithm?
- The interpolation of spatially highly variable parameters such as the concentration of trace elements and therefore of the respective pollution indices by using an interpolation algorithm and only 21 sampling points in a fairly large study area seems a highly uncertain approach. The authors should discuss about this issue in the manuscript and attempt to quantify or at least describe in a concise way the relevant uncertainty.
- The regression equations produced in the manuscript that describe the relationship between PLI and trace elements concentrations are site and time specific only or they can have a degree of generalization for different sites or sampling efforts? This is important because if the estimated equations have only local or sampling specific applicability then the value of this process is not so significant.
- The authors should also try to justify their approach by comparing their main findings with other similar studies from the international literature.
Author Response
- 28. June 2021
Sustainability
Dear Reviewer #3,
Please find the revised manuscript titled ‘Assessment of soil pollution levels in North Nile Delta, by integrating contamination indices, GIS, and multivariate modeling’. Ms. Ref. No.: sustainability-1256613, authored by Mohamed E. Abowaly, Abdel-Aziz A. Belal, Enas E. Abd Elkhalek, Salah Elsayed, Rasha M. Abou Samra, Abdullah S. Alshammari, Farahat S. Moghanm, Kamal H. Shaltout, Saad A.M. Alamri, and Ebrahem M. Eid.
On behalf of my co-authors, I thank you very much for giving us the opportunity to revise our manuscript. We appreciate the positive and constructive comments and suggestions provided by the reviewers on our manuscript. We have carefully studied the reviewers’ comments and have made revisions that are tracked in the revised version of the manuscript. We have tried our best to revise our manuscript according to the reviewers’ comments. Please find attached the revised version of our manuscript, which we would like to submit for your kind consideration. Once again, we would like to express our great appreciation to you and the reviewers for the comments on our manuscript.
Please find below our detailed responses to each of the points raised.
---------------------------------------------------------------------------------------------------------------------
- The authors mention that they used IDW interpolation method to estimate and map the I-geo values for different elements throughout the study area. Why this specific algorithm was chosen among many others? Did the authors tested different algorithms and used the one with the better results? Which were the selection criteria for the interpolation algorithm?
Response: We greatly appreciate your critical observations as well as your constructive and helpful comments. We hope that we could address your questions/comments by the explanations and revisions made in the manuscript. The reason for using IDW in mapping is illustrated in lines 218 to 223. The advantage of using IDW in mapping of spatial distribution of heavy metals is that it is efficient. This interpolation method works better with equally distributed points. IDW and Ordinary kriging are the most popular spatial interpolation methods used in the field of environmental studies. In this study, the concentration of elements is not due to natural sources, but the presence of other sources such as agricultural and industrial drainage, which directly affects the concentration of elements in the soil, which varies based on the distance from the source, and therefore it is better to choose this IDW method. We have tested other algorithm such as Kriging. And the best algorithm was chosen based on different criteria such the root mean squared error and mean error.
---------------------------------------------------------------------------------------------------------------------
- The interpolation of spatially highly variable parameters such as the concentration of trace elements and therefore of the respective pollution indices by using an interpolation algorithm and only 21 sampling points in a fairly large study area seems a highly uncertain approach. The authors should discuss about this issue in the manuscript and attempt to quantify or at least describe in a concise way the relevant uncertainty.
Response: Twenty one soil profiles were selected according to geomorphologic units in the study area to represent the different agricultural practices and soil samples were collected from different layers according to morphological variations. As each physiographic unit covers more than one profile, and therefore the degree of certainty in the distribution is great because it covers the physiographic units to a large extent. This paragraph was added under section 2.2. Soil Analysis.
---------------------------------------------------------------------------------------------------------------------
- The regression equations produced in the manuscript that describe the relationship between PLI and trace elements concentrations are site and time specific only or they can have a degree of generalization for different sites or sampling efforts? This is important because if the estimated equations have only local or sampling specific applicability then the value of this process is not so significant.
Response: We recommend in conclusion section, the future studies should evaluate both the PLSR and MLR models under different environmental conditions for different soils to test the stability of two models.
---------------------------------------------------------------------------------------------------------------------
- The authors should also try to justify their approach by comparing their main findings with other similar studies from the international literature.
Response: The manuscript was supported by the international literature.
---------------------------------------------------------------------------------------------------------------------
I hope the explanation given above adequately addresses the reviewers’ comment. I would appreciate if the revised version of our manuscript would be considered for publication in Sustainability.
Sincerely,
Ebrahem M. Eid
[Kafrelsheikh University]
[Botany Department, Faculty of Science, Kafrelsheikh University, Kafr El-Sheikh 33516, Egypt]
[Phone number: 002010 22648840]
[Email address: [email protected]]
Reviewer 4 Report
Authors are commended for a clear and well written paper analyzing results of field collected data regarding four trace elements in a critical agricultural area in the world with high health implications to people, agriculture, and the environment. The work both confirms other studies and outlines statistical techniques for future applications too. Hopefully results of this paper can supplement other works for building a case to address and mitigate an important health and environment issue.
My general comments are intended to improve the paper:
- Figure 1 would greatly benefit if overlaid on a base map (or an inset) to show where geographically the study area is located.
- In Figure 1 the title of the figure could be more descriptive since no legend was included.
- In addition to Figures 2, 3, and 4, it would have been informative to add another figure that superimposes the GIS layers for each trace element to spatially visualize the results for all three soil layers (integration of the surface, subsurface, and underground soil layers).
- In Line 171-175, the authors introduce the factor of 1.5 in Equation 1. Two questions:
- Why the factor 1.5 (and not 2 or 3 or 4)?
- Will that affect how a sample is classified in classification tables?
- In Lines 240-242 the variables CWCact and CWCave need to be checked, or defined, for consistency.
Author Response
- 28. June 2021
Sustainability
Dear Reviewer #4,
Please find the revised manuscript titled ‘Assessment of soil pollution levels in North Nile Delta, by integrating contamination indices, GIS, and multivariate modeling’. Ms. Ref. No.: sustainability-1256613, authored by Mohamed E. Abowaly, Abdel-Aziz A. Belal, Enas E. Abd Elkhalek, Salah Elsayed, Rasha M. Abou Samra, Abdullah S. Alshammari, Farahat S. Moghanm, Kamal H. Shaltout, Saad A.M. Alamri, and Ebrahem M. Eid.
On behalf of my co-authors, I thank you very much for giving us the opportunity to revise our manuscript. We appreciate the positive and constructive comments and suggestions provided by the reviewers on our manuscript. We have carefully studied the reviewers’ comments and have made revisions that are tracked in the revised version of the manuscript. We have tried our best to revise our manuscript according to the reviewers’ comments. Please find attached the revised version of our manuscript, which we would like to submit for your kind consideration. Once again, we would like to express our great appreciation to you and the reviewers for the comments on our manuscript.
Please find below our detailed responses to each of the points raised.
---------------------------------------------------------------------------------------------------------------------
Authors are commended for a clear and well written paper analyzing results of field collected data regarding four trace elements in a critical agricultural area in the world with high health implications to people, agriculture, and the environment. The work both confirms other studies and outlines statistical techniques for future applications too. Hopefully results of this paper can supplement other works for building a case to address and mitigate an important health and environment issue.
Response: We greatly appreciate your critical observations as well as your constructive and helpful comments. We hope that we could address your questions/comments by the explanations and revisions made in the manuscript. We believe that the manuscript is substantially improved after making the suggested revisions.
---------------------------------------------------------------------------------------------------------------------
My general comments are intended to improve the paper:
- Figure 1 would greatly benefit if overlaid on a base map (or an inset) to show where geographically the study area is located.
Response: Many thanks for this comment. The base map was added in Figure 1 and the study area is geographically located.
---------------------------------------------------------------------------------------------------------------------
- In Figure 1 the title of the figure could be more descriptive since no legend was included.
Response: Legend was added in Figure 1 as well as the title of the figure was improved.
---------------------------------------------------------------------------------------------------------------------
- In addition to Figures 2, 3, and 4, it would have been informative to add another figure that superimposes the GIS layers for each trace element to spatially visualize the results for all three soil layers (integration of the surface, subsurface, and underground soil layers).
Response: To judge the changes in the Igeo of a given element with depth or at different layers, the grouping of maps was modified by metal including three layers in one figure to be more readable to changes in three layers and to be easier for the reader.
---------------------------------------------------------------------------------------------------------------------
- In Line 171-175, the authors introduce the factor of 1.5 in Equation 1. Two questions: Why the factor 1.5 (and not 2 or 3 or 4)? Will that affect how a sample is classified in classification tables?
Response: Many thanks for this comment. The reason for using factor 1.5 is illustrated in lines 178, 179 and 1.5 is standard factor was used this equation according to Lu et al. [45]. As well as, it will not affect in calcification the samples. In general, in this location about 95% of samples is moderately contaminated to extremely contaminate in three layers according to I-geo and very highly polluted according to PLI.
---------------------------------------------------------------------------------------------------------------------
- In Lines 240-242 the variables CWCact and CWCave need to be checked, or defined, for consistency.
Response: Many thanks for this comment. The variables CWCact and CWCave were corrected to PLIact and PLIave.
---------------------------------------------------------------------------------------------------------------------
I hope the explanation given above adequately addresses the reviewers’ comment. I would appreciate if the revised version of our manuscript would be considered for publication in Sustainability.
Sincerely,
Ebrahem M. Eid
[Kafrelsheikh University]
[Botany Department, Faculty of Science, Kafrelsheikh University, Kafr El-Sheikh 33516, Egypt]
[Phone number: 002010 22648840]
[Email address: [email protected]]
Round 2
Reviewer 1 Report
Dear Authors
The publication has been corrected in many places, however, there are still a number of inaccuracies that, in my opinion, must be changed and reconsidered. The main ones that still stand out:
The text from line 322 to 361 is in many places incomprehensible, there are errors in the determinations of individual elements, as well as full of general statements about potential sources of contamination - in total common to all the elements. Hence one could describe it once or try to group it together. There are incomprehensible phrases such as: "positive geographical accumulation effect" or "Positive contamination". In general, this part of the text is to be reformatted and carefully checked for various errors, including linguistic errors.
"0" and "0.00" in the tables are still misleading to me. Despite the explanations below the tables, this type of nomenclature is not used to describe concentrations below the limit of quantification and should be changed.
I still do not understand the point of showing the spatial distribution of I-geo in this publication, if practically fig 2-5 are not discussed. In my opinion, the GIS analysis should either be removed or the effort to discuss of the obtained maps and draw conclusions should be made. If the authors, as it was possible to get the impression from their answer, plan to discuss the maps in another publication, maybe they should skip showing them in this paper.
Tab 6. – in my opinion, it should be included in supplementary materials, because it is too detailed, and the most important information is extracted from it and described in the text and other tables (min, max, average, degree of contamination).
Figures 6 and 7 should be described more fully in their caption, as well as the conclusions resulting from them should be described and discussed in more detail in the text. Both figures are now summarized in practically one sentence.
A clear comparison of the results of analyzes with the use of I-geo and PLI classification is, in my opinion, necessary (correlation, differences, etc.) and should be included in the conclusions.
Author Response
9. July 2021
Sustainability
Reviewer 1´s comments:
Response: We greatly appreciate your critical observations as well as your constructive and helpful comments. We hope that we could address your questions/comments by the explanations and revisions made in the manuscript.
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The text from line 322 to 361 is in many places incomprehensible, there are errors in the determinations of individual elements, as well as full of general statements about potential sources of contamination - in total common to all the elements. Hence one could describe it once or try to group it together. There are incomprehensible phrases such as: "positive geographical accumulation effect" or "Positive contamination". In general, this part of the text is to be reformatted and carefully checked for various errors, including linguistic errors.
Response: Many thanks for this comment. The text from 322 to 361 was revised and it was abbreviated to be clear to the reader.
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"0" and "0.00" in the tables are still misleading to me. Despite the explanations below the tables, this type of nomenclature is not used to describe concentrations below the limit of quantification and should be changed.
Response: Many thanks for this comment. 0 cannot use in the elements concentration that have not been read by the analytical instead of ND. Therefore, ND was used with the concentration of the elements, but with the pollution indicators, a zero number was set for the indefinite value. Since the value of I-geo and PLI calculated from Equations.---------------------------------------------------------------------------------------------------------------------
I still do not understand the point of showing the spatial distribution of I-geo in this publication, if practically fig 2-5 are not discussed. In my opinion, the GIS analysis should either be removed or the effort to discuss of the obtained maps and draw conclusions should be made. If the authors, as it was possible to get the impression from their answer, plan to discuss the maps in another publication, maybe they should skip showing them in this paper.
Response: Many thanks for this comment. The spatial distributions of I-geo are illustrated in lines (301-310). The GIS maps were kept since the other three reviewers are interested with GIS maps.
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Tab 6. – in my opinion, it should be included in supplementary materials, because it is too detailed, and the most important information is extracted from it and described in the text and other tables (min, max, average, degree of contamination).
Response: Table 6 has been moved to supplementary materials as Table S3.
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Figures 6 and 7 should be described more fully in their caption, as well as the conclusions resulting from them should be described and discussed in more detail in the text. Both figures are now summarized in practically one sentence.
Response: Many thanks for this comment. Figures 6 and 7 were described in more fully in their caption as well as the described and discussed of results with support by add additional sentences in results and discussion sections and also in conclusion section.
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A clear comparison of the results of analyzes with the use of I-geo and PLI classification is, in my opinion, necessary (correlation, differences, etc.) and should be included in the conclusions.
Response: We have already explained in details about the I-geo and PLI classification but to do statistical correlation and difference, may be is not interest since I-geo is specific for individual element and PLI was calculated from four elements. Any way more details about I-geo and PLI was written in conclusion section.
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I hope the explanation given above adequately addresses the reviewers’ comment. I would appreciate if the revised version of our manuscript would be considered for publication in Sustainability.
Sincerely,
Ebrahem M. Eid
[Kafrelsheikh University]
[Botany Department, Faculty of Science, Kafrelsheikh University, Kafr El-Sheikh 33516, Egypt]
[Phone number: 002010 22648840]
[Email address: [email protected]]
Reviewer 3 Report
The authors have addressed most of the reviewers' comments and the manuscript has been improved significantly.
Author Response
9. July 2021
Sustainability
Reviewer 3´s comments:
The authors have addressed most of the reviewers' comments and the manuscript has been improved significantly.
Response: Thanks so much Sir for your time and for this positive comment.
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I hope the explanation given above adequately addresses the reviewers’ comment. I would appreciate if the revised version of our manuscript would be considered for publication in Sustainability.
Sincerely,
Ebrahem M. Eid
[Kafrelsheikh University]
[Botany Department, Faculty of Science, Kafrelsheikh University, Kafr El-Sheikh 33516, Egypt]
[Phone number: 002010 22648840]
[Email address: [email protected]]
Round 3
Reviewer 1 Report
Dear Authors
I appreciate taking my comments into account. I encourage you to do more research on the topic presented
