Design and Analysis of an Open-Pit Iron Mine Dust Pollution Evaluation Model Based on the AHP-FCE Method

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The study aims to facilitate a systematic and quantitative assessment of air pollution prevention by dust at a selected strip iron mine using an analytic hierarchy process (AHP) with a fuzzy comprehensive evaluation (FCE).

The site-specific data used in the AHP-FCE approach originate from a structured questionnaire. However, the dataset lacks relevant information, which hinders the evaluation of the analysis's correctness. Due to this fundamental flaw, the majority of the statements in Chapter 5 cannot be evaluated. In general, the uncertainty of the dataset of this type definitely does not allow for the presentation of statistical results with four digits of precision (Table 4). The same objection applies to the comprehensive score numbers (Table 5). Therefore, even such a simple error may indicate wrong analysis.

Additionally, the list of comprehensive risk prevention indicators (Fig. 1) lacks the depth of the strip mine, an important parameter that induces frequent temperature inversions in the atmospheric boundary layer.

In summary, the relevant information necessary to evaluate or compare the provided analysis is missing. I recommend appending the required information and resubmitting the manuscript

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

GENERAL COMMENT (Overall Assessment)

The manuscript addresses a relevant and important topic: the evaluation of dust pollution in open-pit mining environments using an AHP–FCE composite model. The work has clear practical value for environmental management and occupational health in mining operations. The paper is well intentioned, reasonably structured, and contains a complete set of computational outputs. The integration of multi-level indicators with a fuzzy evaluation framework shows potential for operational decision-making.

However, the manuscript requires substantial improvement in several major areas, including:
(1) clearer articulation of the scientific gap and methodological novelty,
(2) stronger justification and documentation of the indicator system and expert scoring process,
(3) more detailed and reproducible methodological procedures,
(4) deeper scientific interpretation of results, beyond descriptive reporting,
(5) explicit discussion of methodological limitations and practical implications, and
(6) significant refinement of the English language for clarity and precision.

With major revisions that enhance methodological rigor and analytical depth, the paper has potential to contribute meaningfully to the field.

 

1. ABSTRACT

Positive aspects:

• The Abstract clearly states the objective and general methodological approach.
• The AHP–FCE framework is correctly identified as the core analytical tool.

Critical points and line-specific issues:

• Lines 3–7: Background information is generic and does not identify a specific research gap or inadequacy in current models.
• Line 8: The jump to “30 tertiary indicators” is abrupt and lacks justification; readers are not informed about the theoretical or empirical basis for selecting them.
• Lines 10–13: The description of the fuzzy evaluation process is conceptual but lacks essential details such as data sources, sampling procedures, or the nature of expert input.
• Lines 15–20: Conclusions remain descriptive and do not quantify the model’s performance, nor do they explain how the framework enhances dust-control decision making.

Recommendation:

Revise the Abstract to:

• clearly state the scientific gap,
• justify the indicator framework,
• specify data origin and expert involvement,
• and end with a strong statement of practical impact.

 

2. INTRODUCTION

Positive aspects:

• Provides contextual justification for studying dust in open-pit mining.
• Cites a wide range of relevant studies.
• Establishes general importance of dust pollution assessment.

Critical points and line-specific issues:

• Lines 25–38: Overly general summary of dust pollution impacts, lacking connection to specific methodological challenges.
• Line 40: The claim of “unique characteristics” of mining dust is not supported by evidence or references; needs clarification or removal.
• Lines 48–59: Literature review lists studies without synthesizing their limitations or explaining how the present work differs.
• Lines 60–82: The research gap is not clearly articulated; the reader cannot determine what current models fail to achieve.
• Line 95: Introducing the hierarchical indicator system here is premature; it must follow a clear justification.
• Lines 100–116: The stated study aims are descriptive but do not emphasize scientific novelty or methodological contribution.

Recommendation:

Rewrite the Introduction to:

• explicitly identify the methodological gap,
• integrate literature into a critical synthesis,
• justify the AHP–FCE model’s use,
• and state the study’s contribution in a concise, impactful manner.

 

3. MATERIALS AND METHODS

Positive aspects:

• Mathematical formulation of AHP and FCE is correct.
• Hierarchical structure is clearly described.
• Fundamental equations are properly presented.

Critical points and line-specific issues:

• Lines 119–124: The number, expertise, and selection criteria of AHP evaluators are not reported. This severely undermines the reliability of the weighting process.
• Lines 130–141: The selection criteria for the 30 tertiary indicators lack theoretical, regulatory, or empirical justification.
• Line 144: Consistency Ratio (CR) values must be explicitly provided for each judgment matrix to validate AHP consistency.
• Lines 158–167: Mathematical steps are correct but should include a numerical example to demonstrate application.
• Lines 170–195: The manuscript does not specify the type, shape, or parameterization of fuzzy membership functions, nor the rationale for their selection.
• Line 201: The source of indicator scores (measurements vs. expert scoring) is not explicitly stated, hindering reproducibility.
• Lines 215–244: The absence of a methodological flowchart weakens structural clarity. Such diagrams are standard in AHP–FCE research.

Recommendation:

Provide detailed descriptions of expert profiles, indicator selection process, CR values, membership function design, numerical examples, and a complete methodological workflow diagram.

 

4. RESULTS AND DISCUSSION

Positive aspects:

• Tables comprehensively present the computed weights, membership degrees, and evaluation outcomes.
• The model outputs are well formatted and consistent.

Critical points and line-specific issues:

• Lines 248–259: Discussion simply repeats table values; lacks higher-level interpretation of why specific indicators have higher weights.
• Lines 260–273: Results are not linked to known dust-generation mechanisms, occupational exposure theory, or comparable studies.
• Line 280: The final evaluation category (“good”) is reported without benchmarking against standards, threshold values, or prior evaluations.
• Lines 290–315: The narrative remains descriptive rather than analytical; deeper mechanistic reasoning is needed.
• Line 316: No sensitivity analysis is provided to assess model robustness against changes in weights or membership assignments.
• Lines 330–360: Results are not translated into practical recommendations for dust-control technologies or management strategies.
• Line 365: Insufficient engagement with international literature on fuzzy multi-criteria environmental evaluation.

Recommendation:

Strengthen the Discussion by adding:

• mechanistic interpretation,
• contextual benchmarks,
• sensitivity analysis,
• operational recommendations,
• and comparative discussion with international literature.

 

5. CONCLUSIONS

Positive aspects:

• Conclusions reflect the framework’s general outcomes.
• The paper acknowledges the utility of AHP–FCE for multi-indicator evaluation.

Critical points and line-specific issues:

• Line 374: Conclusions are overly broad and lack scientific precision.
• Lines 380–394: No limitations are acknowledged (sample size, subjectivity, data source constraints).
• Lines 395–404: No actionable recommendations are provided for dust-mitigation practices in the mining context.
• Line 405: Absence of future research direction leaves the contribution incomplete.

Recommendation:

Revise Conclusions to incorporate:

• clear limitations,
• specific operational recommendations,
• and well-defined avenues for future research (e.g., integration with monitoring sensors, predictive modeling, real-time decision support systems).

Comments on the Quality of English Language

The English language in the manuscript is generally understandable; however, it requires substantial revision to meet the standards of a high-impact scientific journal. The text contains recurring issues in grammar, syntax, article usage, and sentence construction. Several sections include long, complex, or redundant sentences that hinder clarity, and transitions between ideas are sometimes abrupt or poorly connected. In addition, certain expressions appear to be literal translations and do not align with standard scientific phrasing.

A thorough, professional English-language editing is strongly recommended to improve:

• clarity and precision of technical descriptions,

• coherence and logical flow of paragraphs,

• consistency of terminology,

• and overall readability of the manuscript.

Such improvements will significantly enhance the scientific communication and presentation quality of the work.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf