Review Reports

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Manuscript Number: atmosphere_3765578

Title:  Heavy Metal Concentrations in Particulate Matter: A Case Study from Santo Domingo, Dominican Republic, 2022

The manuscript addresses an important issue:  the concentrations and spatial distribution of heavy metals in atmospheric particulate matter (PM2.5 and PM10) in Santo Domingo, Dominican Republic. While several emission sources significantly impact air pollution in the region and warrant investigation, I find that this work does not present any new findings for the scientific community, as outlined in the journal's mandate. The manuscript needs substantial modification before that. I have provided a list of general and small remarks on the writers' willingness to enhance their papers.

Evaluation; Minor revision

1. The abstract requires substantial revisions; therefore, they should be rewritten.
2. The content would improve with a more concise writing style in certain areas, especially the introduction, which should concentrate more on the study aims and less on the general background.
3. Keywords: It is crucial to revise the keywords, ensuring they are spelled correctly and avoid general, abbreviations, and plural terms and multiple concepts (avoid, for example, 'and', 'of'). This will help to maintain the precision and clarity of the manuscript.

e.g.   Particulate matter (PM2.5, PM10); Energy-dispersive X-ray fluorescence (EDXRF); Censored data imputation; Principal component analysis (PCA) >>>>> no need abbreviation.

4. Line 35; respirable fractions, PM2.5 and PM10. Please specify respirable particles and explain more.
5. Justify the use of a filter for gravimetric analysis, and report the underlying uncertainty involved in using a filter for gravimetric analysis.
6. Principal Component Analysis: According to PCA analysis, there are only 30

samples. This is way too few for a PCA, so such an analysis is not justified here. According to R. C. Henry et al., Atmos. Environ., 18 (1984) 1507-1515, the minimum number of samples in multivariate models is > 30 + (V+3)/2, with V the number of variables (species). Furthermore, it is totally unclear how the PCA could be used based on only 30 samples.

7. Expand the PCA interpretation with deeper insights into factor loadings, regional relevance, and literature support, ensuring that each factor's source contribution is fully elaborated.
8. In this paper, there are many methodologies used to study chemical composition (metals). How to Quality Assurance and Quality Control (QA/QC)?
9. In the main text, many numeric data are given too many significant figures; two significant figures suffice, and three suffice if the first significant figure is "1."
10. You are required to give all of the figures in a high resolution, and you should also make the labels and legends less challenging to read.
11. In conclusion, the findings have the potential to be expanded upon; that being said, the study has a great deal of fascinating information.

 

 

Comments on the Quality of English Language

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Author Response

Response to Reviewer 1

We are very grateful for your thorough review of our manuscript entitled “Heavy Metal Concentrations in Particulate Matter: A Case Study from Santo Domingo, Dominican Republic, 2022”. We highly value your detailed and constructive feedback, which has greatly helped us to improve the quality and clarity of our work. Below, we provide our responses to your comments:

1. Abstract
   We have substantially revised the abstract to make it more concise, clear, and directly aligned with the study aims and key findings, while minimizing unnecessary general background.

2. Introduction
   We have streamlined the introduction to focus more on the specific objectives of the study and the context of Santo Domingo, while reducing overly general information.

3. Keywords
   Following your suggestion, we have revised the keywords to avoid abbreviations, plurals, or overly general terms. The updated keywords are precise and reflect the core content of the study.

4. Respirable fractions (PM2.5 and PM10)
   We have expanded the explanation of respirable particles, clarifying their definition, health relevance, and the reason for selecting these fractions for analysis.

5. Filter use and gravimetric analysis
   We have included additional justification for the choice of PTFE filters for gravimetric analysis and reported the uncertainties associated with this method to strengthen methodological transparency.

6. Principal Component Analysis (PCA)
   We acknowledge the limitation related to the relatively small number of samples for PCA. In response, we have clarified the rationale for using PCA in this context, citing relevant literature that supports its application in exploratory studies with constrained datasets. We have also expanded the discussion of factor loadings, potential source contributions, and regional relevance, while emphasizing the exploratory rather than confirmatory role of the PCA in this study.

7. Quality Assurance and Quality Control (QA/QC)
   We have now included a description of the QA/QC measures implemented during sampling, filter handling, and elemental analysis (including calibration procedures and reproducibility checks), in order to strengthen the methodological rigor.

8. Significant figures
   We have reduced the number of significant figures reported for numerical results, following your recommendation (two significant figures, or three when the first is “1”), to ensure consistency and clarity.

9. Figures
   We have improved the resolution of all figures and adjusted labels and legends to enhance readability and interpretation.

10. Conclusions
    The conclusions have been revised to better highlight the key findings, their implications, and potential directions for future research, building upon your suggestion to expand their scope.

Once again, we thank you sincerely for your valuable comments and suggestions. Your feedback has allowed us to significantly strengthen our manuscript, both scientifically and structurally.

Reviewer 2 Report

Comments and Suggestions for Authors

Summary:

The concentrations and spatial distribution of heavy metals in atmospheric particulate matter (PM2.5 and PM10) are studied in Santo Domingo, Dominican Republic, during 2022. 30 air samples were collected across diverse urban environments using portable low-volume samplers. Elemental analysis was performed via energy-dispersive X-ray fluorescence (EDXRF) to quantify As, Cd, Cr, Cu, Fe, Hg, Mn, Ni, Pb, V, and Zn concentrations. Regression on order statistics (ROS) was employed to impute data below detection limits. The highest mean concentrations in both PM fractions were for Cu and Zn from significant anthropogenic contributions. V and Fe showed remarkable spatial variability. Principal component analysis (PCA) provided the source traffic and industrial emissions.

General comments:

The critical baseline data for urban air quality management in the region are given. The need for expanded environmental monitoring is followed to mitigate health risks associated with airborne heavy metals.

The manuscript is clear, relevant for the field and presented in a well-structured manner. It is written in an appropriate way.

The cited references are about half recent publications (within the last 5 … 10 years) and relevant. It does not include an excessive number of self-citations.

The manuscript sounds scientifically and the structural design is appropriate to fulfil the objectives.

The manuscript’s results are mainly reproducible based on the details given in the material and methods section.

The data are interpreted appropriately and consistently throughout the manuscript.

The figures/tables/images/schemes are appropriate. They properly show the data. They are easy to interpret and understand. But the figure captions must be improved for understanding without intensive knowledge of manuscript.

There are ethics and data availability statements.

Additional comments:

The main question is to present concentrations and spatial distribution of heavy metals in atmospheric particulate matter (PM2.5 and PM10) in Santo Domingo, Dominican Republic. This is required to reduce health risks of population. It is original and well-defined. The results contribute the necessary material.

The topic is relevant in the field. This work provides a fundamental assessment of heavy metals in atmospheric particulate matter in Santo Domingo. The presence of persistent pollutants, spatial heterogeneity in exposure, and key indicators of anthropogenic activity are given. The study concludes the need for targeted mitigation strategies to protect public health and environmental quality in the region.

Compared with other published material in the field the paper provides material for Santo Domingo, Dominican Republic.

The analyses are performed with the highest technical standards. But information is missing about filter handling: weighing, storage, transport, handling of loaded material. The data are robust enough to draw conclusions. The raw data are available and correct. The authors finished with the chapters Discussions and Conclusions.

The results are interpreted appropriately. They are significant. The Discussions give clear statements for the weaknesses of the work and the following research tasks. The conclusions are justified and supported by the results as well as consistent with the evidence and arguments presented and they address the main question posed. The paper will attract a wide readership.

The references are appropriate.

The English language is appropriate and understandable.

The work fits the journal scope.

Author Response

We sincerely appreciate the time and effort you have dedicated to reviewing our manuscript entitled “Heavy Metal Concentrations in Particulate Matter: A Case Study from Santo Domingo, Dominican Republic, 2022”.

We are grateful for your positive comments regarding the clarity, relevance, and scientific quality of our work, as well as your recognition of the study’s contribution to urban air quality management. We are pleased that you found the methodological design, data interpretation, and conclusions to be sound and appropriate to the stated objectives.

We acknowledge your valuable recommendation to improve the figure captions so that they can be understood without requiring intensive knowledge of the manuscript. In response, we have carefully revised all figure captions, expanding the descriptions to include clearer explanations of the symbols, abbreviations, and main interpretations.

Additionally, we have addressed your observation regarding missing information on filter handling (weighing, storage, transport, and management of loaded filters). We have now added a more detailed description in the Materials and Methods section to clarify these procedures, thereby strengthening the transparency and reproducibility of the study.

Once again, we thank you for your thoughtful suggestions and for highlighting the originality and importance of our research. Your comments have significantly contributed to improving the quality of our manuscript.

Reviewer 3 Report

Comments and Suggestions for Authors

The research topic of this manuscript is a good fit for the journal, and the overall work is well-conducted. However, there are several issues that need to be carefully addressed to strengthen the paper.

The introduction would benefit from a more thorough review of existing literature to better situate this study's contribution. The paper should clarify its novelty beyond being the first such study in this specific geographic area. For instance, does the application of specific statistical methods for censored data in this context offer a methodological innovation? I encourage the authors to more explicitly define what makes this work a significant step forward for the field, beyond providing important but localized baseline data.

The sampling strategy requires a more detailed justification. While the paper describes a systematic layout, the use of only 30 samples to represent the entire National District may be insufficient for a robust spatial analysis. This low sampling density can lead to high uncertainty in the kriging interpolation, especially in areas far from any measurement site. This spatial limitation is compounded by the temporal one: each of the 30 sparse points represents only a single 24-hour snapshot. The manuscript should therefore more transparently discuss the significant potential for bias when creating spatial distribution maps from such a limited and temporally unrepresentative dataset. The assumption that the spatial pattern captured during this short campaign is stable and representative of long-term conditions is a major leap that needs to be carefully addressed.

I strongly recommend restructuring the methods section for clarity and readability. It is currently presented as a long, continuous block of text, which makes it difficult for the reader to follow the workflow. Dividing this section into distinct, well-labeled subsections (e.g., "Study Area and Sampling," "Chemical Analysis," "Censored Data Handling," and "Spatial and Statistical Analysis") would greatly improve its organization. In particular, the spatial interpolation methodology needs more detail. The authors should describe the variogram models and cross-validation results to justify the accuracy of the kriging maps, as these are central to the paper's spatial findings.

The discussion section should be revised to provide more interpretation and comparison, rather than primarily repeating the results. The findings on metal concentrations should be contextualized by comparing them with levels reported in similar studies from other urban centers in the Caribbean or Latin America. This would help the reader understand whether the levels observed in Santo Domingo are unusually high, low, or typical for the region. Furthermore, a consolidated and expanded discussion of the study's limitations—including sampling precision, the scale of the study, and the exclusion of key metals—should be integrated here.

The abstract needs to be refined. It contains too many keywords, and a more focused list of approximately five key terms would be more effective. Additionally, abbreviations should be avoided in the abstract; terms such as Particulate Matter, Principal Component Analysis, and others should be written out in full to ensure the summary is accessible to a broad audience.

Throughout the manuscript, the use of abbreviations should be standardized for better readability. An abbreviation should be defined in full at its first appearance in the text and then used consistently thereafter. A careful check is needed to ensure this convention is followed for all technical terms.

The manuscript's handling and reporting of censored data in the multivariate analysis could be clarified. The authors state that the NIPALS algorithm was used for the principal component analysis because it can handle missing data, but it is not explicitly stated how the left-censored values were treated. Were they coded as missing values before this analysis? This is a critical methodological point that requires clarification. The complete exclusion of important toxic metals like mercury and manganese from the main analysis due to high censoring also warrants a more detailed discussion of how their absence might limit the study's overall conclusions.

The interpretation of the principal component analysis should be presented with more caution. The first two components explain less than 50% of the total variance for the finer particulate matter fraction, meaning a majority of the variability remains unexplained. Given this, the source attributions based on the analysis should be framed more as preliminary hypotheses rather than firm conclusions. Acknowledging the amount of unexplained variance is important for a balanced interpretation.

Author Response

Response to Reviewer 3

We thank Reviewer 3 for the thorough and constructive comments, which have helped us to significantly improve the clarity and rigor of the manuscript. Below we provide a detailed response to each point raised. All corresponding changes have been incorporated into the revised version of the manuscript.

Comment 1: The introduction would benefit from a more thorough review of existing literature… novelty should be clarified.

Response: We have revised the Introduction to provide a more comprehensive review of relevant literature, particularly studies from the Caribbean and Latin America. We have also emphasized the novelty of our work: (i) the systematic application of regression on order statistics (ROS) for handling left-censored environmental data in the Dominican Republic context, and (ii) the use of ROS with PCA (NIPALS algorithm) to interpret incomplete datasets. This methodological framework offers a replicable approach for air quality studies in resource-limited regions, going beyond localized baseline reporting.

Comment 2: The sampling strategy requires a more detailed justification… concerns about spatial and temporal limitations.

Response: We agree with the reviewer and have expanded the Methods and Discussion sections to explicitly acknowledge the limitations of the sampling design. We now provide additional justification for the single-day-per-site strategy and discuss the associated uncertainties in kriging interpolation due to both low density and lack of temporal coverage. We highlight that while the dataset captures spatial contrasts within the National District, it should be interpreted as a baseline snapshot rather than a long-term average. A new paragraph in the Discussion clearly addresses this potential bias and the need for future high-frequency monitoring.

Comment 3: Methods section should be restructured into clear subsections. Variogram models and cross-validation for kriging need more detail.

Response: The Methods section has been reorganized into four labeled subsections: Study Area and Sampling, Chemical Analysis, Censored Data Handling, and Spatial and Statistical Analysis. We have added details about the spatial interpolation procedure, including the type of variogram model fitted and the cross-validation statistics used to assess kriging accuracy. These details now justify the reliability of the spatial distribution maps.

Comment 4: The discussion should provide more interpretation and comparison, not just repetition. Levels should be compared with other cities. Limitations should be consolidated.

Response: The Discussion has been substantially revised. We now compare our findings with similar studies conducted in Havana, San Juan, Mexico City, and São Paulo, thereby contextualizing the concentrations observed in Santo Domingo. We also present a consolidated section on study limitations, covering sampling density, temporal representativeness, exclusion of highly censored metals (Mn, Hg, As), and detection-limit constraints of EDXRF. This strengthens the balance and transparency of our interpretation.

Comment 5: The abstract needs refinement (reduce keywords, avoid abbreviations).

Response: We have revised the Abstract to use only five carefully selected keywords and have eliminated abbreviations, replacing them with their full terms (e.g., “Particulate Matter” instead of “PM,” “Principal Component Analysis” instead of “PCA”).

Comment 6: Abbreviations should be standardized throughout the text.

Response: We carefully reviewed the manuscript to ensure that all abbreviations are introduced upon first use and applied consistently thereafter.

Comment 7: Clarify treatment of censored data in PCA. Discuss the exclusion of metals with high censoring.

Response: We clarified that imputed values were only used for global descriptive statistics and not for multivariate analyses, such as principal component analysis (PCA), where preserving the original data structure was required. We also added a paragraph in the Discussion explaining the implications of excluding Mn, Hg, and As from the PCA, acknowledging how this limits source identification.

Comment 8: PCA interpretation should be more cautious, since the first two components explain less than 50% of variance.

Response: We revised the PCA interpretation to emphasize that the results are preliminary indicators of possible source groupings rather than definitive source apportionments. The unexplained variance is now explicitly mentioned, and conclusions are framed as hypotheses that require confirmation by future studies with larger datasets.

Comment 9: English language quality.

Response: The manuscript has been carefully revised for English language clarity and readability. We have simplified overly complex sentences and improved transitions between sections.

Closing Statement

We are grateful to Reviewer 3 for the insightful feedback, which has led to a clearer, more rigorous, and better-structured manuscript. We believe that the revisions have addressed all concerns raised and have substantially strengthened the quality of the paper.

Reviewer 4 Report

Comments and Suggestions for Authors

This manuscript presents a well-executed investigation into the spatial distribution and concentration of heavy metals in PM2.5 and PM10 within an understudied urban setting, acknowledging and transparently addressing its limitations. The use of regression on order statistics (ROS) to address left-censoring demonstrates methodological rigor and improves data reliability in a challenging analytical context. The integration of PCA for source apportionment provides meaningful insights into likely emission pathways, while the consistent presence of Cu and Zn across sites reinforces the significance of traffic-related contributions. Moreover, the study’s emphasis on baseline data for Santo Domingo fills a critical gap in regional air quality research and offers a valuable foundation for future monitoring and policy development. Overall, this work contributes to the growing body of literature on urban airborne metal pollution.

Here are the comments regarding the manuscript:

The manuscript does not clearly specify whether PM₁₀ and PM_2.5 samples were collected simultaneously at the same locations. Based on Tables A1 and A2, it appears they were not. I recommend including a sentence in the methods section clarifying the sampling timeline and protocol for both particulate fractions.

Where are those values (IDL)? What are instrument detection limits and method detection limits?

Figure 2 is not referenced in the paper, so I am unsure why it is included here. Are these figures (including figure 3) explained from rows 155 to 168? If so, they need to be addressed in the paper text.

When addressing differences in the metal concentration profile of sites, it would be easier to follow if you place the ID number from Figure 1 in brackets next to each location's name.

How does the PCA Biplots suggest a common source if the vectors of Zn, Cu, and V all point in opposite directions? Please double-check the Biplots.

If PM₁₀ and PM_2.5 samples were collected at the same time and location, you need to check your data. (regarding tables A1 and A2)

Comments for author File: Comments.pdf

Author Response

Response to Reviewer 4

We sincerely thank Reviewer 4 for the positive evaluation of our manuscript and for the valuable suggestions, which have helped us clarify and strengthen several aspects of the study. Below we provide a detailed response to each comment, with corresponding revisions incorporated into the manuscript.

Comment 1: The manuscript does not clearly specify whether PM10 and PM2.5 samples were collected simultaneously at the same locations.

Response: We thank the reviewer for pointing out this important detail. We have clarified in the Methods (Study Area and Sampling) section that PM10 and PM2.5 samples were collected simultaneously at each site using parallel MiniVol™ samplers. This clarification ensures that the reader understands the sampling protocol and timeline for both particulate fractions.

Comment 2: Where are those values (IDL)? What are instrument detection limits and method detection limits?

Response: We agree that this required clarification. We have added a table in the Methods (Chemical Analysis) section that specifies the instrument detection limits (IDLs) and method detection limits (MDLs) for each analyzed element. These values were determined based on repeated measurements of certified reference materials, following standard XRF protocols, and are now explicitly reported in the revised manuscript.

Comment 3: Figure 2 is not referenced in the paper… If so, they need to be addressed in the text.

Response: We appreciate this observation. We carefully reviewed the Results section and confirmed that Figures 2 and 3 were not explicitly cited in the initial draft. We have corrected this by integrating explicit references to Figures 2 and 3 in the Results (lines describing the spatial interpolation of metal concentrations for PM2.5 and PM10). This ensures consistency between the text and figures.

Comment 4: When addressing differences in the metal concentration profile of sites, it would be easier to follow if you place the ID number from Figure 1 in brackets next to each location's name.

Response: We agree and have revised the Results and Discussion sections to include the site ID numbers in brackets alongside the school or location names (e.g., “San Judas Tadeo School [2]”). This improves readability and allows readers to more easily cross-reference the text with Figure 1 and Tables A1–A2.

Comment 5: How does the PCA Biplots suggest a common source if the vectors of Zn, Cu, and V all point in opposite directions? Please double-check the Biplots.

Response: We thank the reviewer for highlighting this. Upon re-examining the PCA biplots, we agree that the interpretation required refinement. We have revised the Discussion to clarify that although Zn, Cu, and V vectors are not aligned, their loadings on the first principal component suggest that they may share partially overlapping sources, such as traffic and industrial combustion. However, we now present this as a tentative hypothesis rather than a firm conclusion, consistent with the reviewer’s concern.

Comment 6: If PM10 and PM2.5 samples were collected at the same time and location, you need to check your data (regarding Tables A1 and A2).

Response: We appreciate this important point. We re-checked the dataset to confirm consistency between paired PM2.5 and PM10 samples collected simultaneously at the same site. Minor discrepancies between Tables A1 and A2 reflect differences in detection limits and measurement reproducibility for each size fraction. We have added a clarifying note in the Methods section to explain why concentrations of the same element may differ between paired samples, despite being collected at the same location and time.

Closing Statement

We thank Reviewer 4 again for the constructive and insightful comments. The manuscript has been revised accordingly, resulting in improved clarity, methodological transparency, and alignment between the figures, tables, and text.

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

The authors followed the reviewer requirements.

Author Response

We thank Reviewer 2 for acknowledging our revisions. We are pleased that the changes addressed the previous concerns and improved the manuscript.

Reviewer 3 Report

Comments and Suggestions for Authors

The authors have provided reasonable replies to my comments and revised the manuscript accordingly. I am happy to recommend its publication in the present form.

Author Response

We sincerely thank Reviewer 3 for the positive evaluation and recommendation for publication. We appreciate the constructive comments that helped us improve the clarity and quality of the manuscript.

Reviewer 4 Report

Comments and Suggestions for Authors

Dear Authors,

Thank you for your comprehensive revision. However, I still have several concerns regarding the manuscript. I have outlined these in detail through comments within the document, but I would like to summarize them here as well:

• The clarification regarding differences in concentrations of elements between paired samples is said to be added in the Methods section, but I was unable to locate it.
• Figure captions are unnecessarily long. Since the visuals are self-explanatory, I suggest moving detailed descriptions to the main text.
• The same data is presented in both tables and figures, resulting in unnecessary duplication. Streamlining by selecting a single format would improve clarity and readability
• A major concern persists regarding the plausibility of higher metal concentrations in PM₂.₅ than in PM₁₀. Given the sampling method and low air volume, many values fall below the detection limit, and the statistical imputation used may not yield realistic results. I strongly recommend a thorough re-evaluation of the input data to ensure the reliability of your findings.

Comments for author File: Comments.pdf

Author Response

We sincerely thank Reviewer 4 for their careful evaluation and constructive comments, which have helped us to improve the quality and clarity of our manuscript. Below we provide a detailed response to each point raised.

1. Clarification of differences in concentrations between paired samples
Reviewer’s comment: The clarification regarding differences in concentrations of elements between paired samples is said to be added in the Methods section, but it is not visible.

Response: We acknowledge the oversight. We have now explicitly added a paragraph in the Materials and Methods section, specifically at the end of the Chemical Analysis subsection, explaining potential reasons for observed discrepancies between PM2.5 and PM10 collected simultaneously at the same site. Specifically, we note the influence of (i) filter positioning in parallel MiniVol™ samplers, (ii) heterogeneity in particle deposition due to flow turbulence, and (iii) analytical uncertainty close to detection limits. This clarification ensures transparency and addresses the reviewer’s concern.

2. Length of figure captions
Reviewer’s comment: Figure captions are unnecessarily long; details should be in the main text.

Response: We agree. All figure captions have been shortened to include only essential information.

3. Duplication of data in tables and figures
Reviewer’s comment: The same data is presented in both tables and figures, leading to duplication.

Response: Thank you for pointing this out. We have streamlined the presentation: (i) summary statistics remain in tables (Tables 2 and 3). This avoids redundancy while preserving clarity for readers.

4. Plausibility of higher metal concentrations in PM2.5 than in PM10
Reviewer’s comment: Concerns about unrealistic results, given detection limits and imputation.

Response: We greatly appreciate this important point. We have carefully revisited our data and methodological choices. In the revised manuscript we:
- Added a detailed explanation in the Methods clarifying detection limits (Table B1) and the proportion of censored data per element.
- Included a new subsection in the Discussion, highlighting cases where PM2.5 concentrations appear higher than PM10. We attribute this to particle size distribution influenced by combustion sources and atmospheric processes, while also emphasizing the limitations imposed by small sample volumes and imputation.
- Strengthened the Discussion with references to previous studies reporting similar anomalies under low-volume sampling conditions, highlighting that these results should be interpreted cautiously as preliminary evidence rather than definitive concentrations.