Quantifying Topography-Dependent Ultrafine Particle Exposure from Diesel Emissions in Appalachia Using Traffic Counts as a Surrogate Measure

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The article studies an approach to estimate ultrafine particulate matter (UFP) concentrations from heavy diesel truck traffic emissions in different topographical regions.

In the introduction section please check line 96 which is subsection 1.2.

 Furthermore, a comparison table with particulate matter air quality standards for PM2.5, PM10 (NAAQS) could enhance the characterization of these particulate matter and UFP with the indication/comparison of the particle size.

The historical data such as average concentrated values of particulate matter in these locations will provide an evolution of these emissions and could indicate the need to increase or provide mitigation measures. Please provide if possible historical data of particulate emissions in these locations.

 Please check line 136 which corresponds to subsection 1.3. and the following subsections accordingly.

In Materials and Methods subsection 2.5 about Statistical Analysis and Data Processing, in line 420, please provide in the article the descriptive statistics used to examine UFP concentration distribution over several sites.

In addition, please provide an explanation of the relationship between variables in Figure 1,2 and 3.

In the discussion section please indicate a possible mitigation measure according to results obtained. This section should discuss the results and how they can be interpreted in perspective of previous studies and of the working hypotheses. The findings and their implications should be discussed in the broadest context possible and limitations of the work highlighted. Future research directions may also be mentioned. This section may be combined with Results.

Best regards

Comments on the Quality of English Language

The english language could be improved.

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Diesel engines emit ultrafine particles (<0.1 μm) that pose serious health risks, especially from heavy‐duty trucks. While most traffic‐pollution studies focus on urban settings, this work examines how Morgantown’s steep topography affects UFP concentrations near roadways. A linear relationship between truck count and UFP levels was proposed, indicating that truck count can serve as a surrogate for estimating lung dose across varied terrain.

The literature review is thorough and well‐contextualized; however, the data analysis requires significant improvement. In particular, the linear regression in Figure 4 yields an R² of only 0.1591, indicating that a simple linear model is wrong for these data. I therefore recommend this paper be rejected.

 

Additional comments:

1. The authors are advised to re-evaluate their choice of fitting model, as the current linear regression fails to adequately capture the trend in the scatter data. Given the low R² value, alternative modeling approaches such as non-linear or multivariate regressions should be considered to better represent the data. Any revised model should be supported with appropriate statistical justification, including residual analysis, goodness-of-fit metrics, and relevant diagnostic plots. In addition, the Results section should be updated to reflect the outcomes of the new model, with a clear discussion on how the revised analysis impacts the interpretation of the findings.

 

2. A satellite map image of the Brockway and Beechurst locations in West Virginia should be included to clearly illustrate their geographic features and traffic patterns, rather than relying solely on textual descriptions.

 

3. Wind and Weather Conditions. The manuscript should clarify the experimental site’s ventilation regime, ideally by reporting mean wind speed or an estimated air-exchange rate. Ultrafine oil particles (15.4 nm) behave as stable aerosols in quiescent air, remaining suspended for at least nine hours under Stokes‐law settling conditions (You et al., 2021, https://doi.org/10.1016/j.buildenv.2021.108239). Based on this, three ventilation scenarios can be anticipated: High Ventilation: In an open environment with sufficient air convection, UFP concentration will track the 15-min truck count closely, as emissions outpace losses. Moderate Ventilation: With intermediate airflow, a dynamic equilibrium forms between UFP generation and removal, yielding a near-constant concentration over the sampling period. Low Ventilation: In a confined area (e.g., encircled by tall buildings), poor air exchange leads to progressive UFP accumulation regardless of truck traffic.

Author Response

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Reviewer 3 Report

Comments and Suggestions for Authors

In this work, the authors demonstrated the “Developing a Simplified Method of Measuring Ultrafine Particulate Matter Dose Concentrations for Diesel Emissions” In this study,

 Diesel particulate matter, primarily ultrafine particles (UFP), defined as particles smaller than 0.1 μm, are released by diesel-powered vehicles, especially those used in heavy-duty hauling, and are linked to serious health hazards. While much of the existing research on traffic-related air pollution focuses on urban environments, limited attention has been paid to how complex the topography influences the concentration of UFPs, particularly in areas with significant truck traffic. With a focus on Morgantown, West Virginia, an area distinguished by steep topography, this study investigates how travel over two different terrain conditions affect UFP concentrations close to roadways. Specifically, we sought to determine if truck count can be used as a surrogate allowing for varying topography for the concentration of UFPs. This study shows that “TRUCK COUNT” does result in a linear relationship and yields a possible surrogate measure of lung dose of UFP number concentration. Thus, I would like to recommend this work be published in the world-famous Journal of “Applied Sciences”. Some minor revisions have been made to refine the manuscript's overall structure.

Comments

1. The title should be revised to better reflect the study's focus on topography, suggesting: "Quantifying Topography-Dependent Ultrafine Particle Exposure from Diesel Emissions Using Traffic Counts as a Surrogate Measure"
2. The (Abstract Page 1) needs to include specific numerical results (R²=0.6035, 30% alveolar deposition rate) and clarify that truck counts serve as a validated rather than possible surrogate for UFP exposure
3. The introduction should be restructured to: Highlight the novelty of using truck counts in complex terrain earlier, Reduce redundancy in health risk discussions, Incorporate 3-4 recent references (2022-2024) on UFP monitoring
4. Methods section requires clarification on: How loading conditions were determined from truck direction Justification for the 15-minute sampling interval Calibration procedures for all instruments
5. Some sentences are overly long or complex (e.g., Page 3, paragraph 2). Consider breaking them down for readability.
6. Define abbreviations like "UNGD" (Page 3) and "MPPD" (Page 12) at first use for broader accessibility.

 

7. Results should better address: Confounding factors affecting Beechurst's weaker correlation Clinical significance of the 30% alveolar deposition finding Statistical uncertainty measures for all reported values
8. The discussion needs: Direct comparisons with similar urban vs. mountainous UFP studies A dedicated limitations subsection addressing: “ Short 6-day sampling period” “Single-city focus” Lack of weather data incorporation Reduced repetition of health risk information
9. The authors must discuss the basics of their work by discussing the latest work.  some up-to-date references regarding air pollution and environmental health concerns such as org/10.1016/j.mssp.2023.107534, doi.org/10.1016/j.jscs.2023.101753, and 10.1016/j.heliyon.2024.e27378,
10. Ref [7] (Kwon) cited 3x for same UFP properties, Ref [3] (Ali) cited 2x for lung penetration, Ref [46] (Stahlhofen) cited 2x for deposition model Needs more 2020-2024 citations (only ~20% current), Some refs missing journal names (33,35)
11. Figures require improvement for clarity: Ensure all text is legible at 100% magnification Standardize formatting of scientific notation (PM₂.₅, μm) Bold and properly position all captions Adjust label sizes for better readability. (Pages 11-14 Figures) Scientific notation (e.g., p12 "0.1µm" → "0.1 μm")
12. All abbreviations (UNGD, MPPD, etc.) must be defined at first use and used consistently thereafter.
13. The manuscript requires thorough proofreading for: Grammatical errors (e.g., affect/effects) Consistent terminology (e.g., "Beechurst Avenue") Proper unit formatting throughout
14. The health risk discussion should be consolidated into one focused section rather than being repeated in abstract, introduction, and discussion.
15. The methods should include more details about: Site selection criteria Quality control measures Data processing procedures.
16. Overall structure needs tightening by: Removing excessive line breaks Ensuring logical flow between sections Maintaining consistent heading styles Aligning with journal formatting guidelines

Author Response

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Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

Thank you for addressing my earlier comments and adding Figure 7 to account for increased emissions over hilly terrain. This revised manuscript represents a substantial improvement over the previous submission. Pending minor edits, this paper is recommended for publication.

I remain concerned, however, that the statement on lines 578–584“the lower correlation coefficient but still parallel slopes” is not statistically meaningful given the very low R² at the Beechurst site; under such conditions any slope will fit that dataset with similar R² value, so this claim should be revised or further justified.

I also note that Figure 8 is neither referenced nor discussed in the main text. The caption alone does not suffice; please introduce this figure in the Results or Discussion section and explain why it was included, the inverse relationship between particle size and number concentration, and the positive correlation between truck speed and ultrafine-particle concentrations.

Finally, the Methods section should be expanded to describe the AI-based video analysis mentioned in passing. Please specify the model or algorithm used, outline the training and validation procedures, and present performance metrics (e.g., accuracy or precision) that demonstrate the reliability of the automated vehicle counts and speed measurements.

Author Response

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