PCLM-D-25-00337

City-scale calibration of a low-cost PM2.5 network for regulatory-compliant air-quality assessment

PLOS Climate

Dear Dr. Gautam,

Thank you for submitting your manuscript to PLOS Climate. After careful consideration, we feel that it has merit but does not fully meet PLOS Climate’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Dec 04 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at climate@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pclm/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

• A rebuttal letter that responds to each point raised by the editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
• A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
• An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

We look forward to receiving your revised manuscript.

Kind regards,

Jingyu Wang

Academic Editor

PLOS Climate

Journal Requirements:

1. Please include a complete copy of PLOS’ questionnaire on inclusivity in global research in your revised manuscript. Our policy for research in this area aims to improve transparency in the reporting of research performed outside of researchers’ own country or community. The policy applies to researchers who have travelled to a different country to conduct research, research with Indigenous populations or their lands, and research on cultural artefacts. The questionnaire can also be requested at the journal’s discretion for any other submissions, even if these conditions are not met.  Please find more information on the policy and a link to download a blank copy of the questionnaire here: https://journals.plos.org/climate/s/best-practices-in-research-reporting. Please upload a completed version of your questionnaire as Supporting Information when you resubmit your manuscript.

2. In your Methods section, please provide additional information regarding the permits you obtained for the work. Please ensure you have included the full name of the authority that approved the field site access and, if no permits were required, a brief statement explaining why.

3. Please note that PLOS Climate has specific guidelines on code sharing for submissions in which author-generated code underpins the findings in the manuscript. In these cases, we expect all author-generated code to be made available without restrictions upon publication of the work. Please review our guidelines at https://journals.plos.org/climate/s/materials-and-software-sharing#loc-sharing-code and ensure that your code is shared in a way that follows best practice and facilitates reproducibility and reuse.

If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Does this manuscript meet PLOS Climate’s publication criteria?>

Reviewer #1: Yes

Reviewer #2: Partly

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2. Has the statistical analysis been performed appropriately and rigorously?-->?>

Reviewer #1: Yes

Reviewer #2: Yes

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3. Have the authors made all data underlying the findings in their manuscript fully available (please refer to the Data Availability Statement at the start of the manuscript PDF file)??>

The PLOS Data policy

Reviewer #1: Yes

Reviewer #2: No

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4. Is the manuscript presented in an intelligible fashion and written in standard English??>

Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: The article presents a solid, original, and timely study on the calibration of a low-cost sensor (LCS) network for urban PM₂.₅ monitoring in Bucharest, Romania.

The approach seeks to align the measurements of the InfoAer network with European Union regulatory standards, enabling the identification of air-quality limit exceedances with high spatial resolution.

The work has high applied value, contributing to the strengthening of environmental surveillance and the formulation of public policies based on reliable and cost-effective data.

1. Relevance and timeliness

The topic is critical for urban environmental management. The validation of low-cost sensors expands the spatial coverage of monitoring systems and democratizes access to information on air pollution.

2. Clear and reproducible methodology

The two-stage calibration design—local model development and cross-validation—is robust and replicable.

The use of Multiple Linear Regression (MLR), although simple, ensures transparency and ease of implementation for municipal or academic users.

3. Rigorous quality control

European criteria for data completeness, outlier exclusion, and environmental condition control (relative humidity and temperature) are applied.

This guarantees database consistency and traceability of the results.

4. Potential for regional extension

Although focused on Bucharest, the methodological approach could be transferred to other European and Latin American cities with emerging PM₂.₅ urban sensor networks.

5. Limitations of the linear model

The use of MLR assumes strictly linear relationships between predictors and PM₂.₅, which may underestimate non-linear behaviors under extreme humidity or temperature conditions.

It is recommended to explore hybrid or non-linear approaches (e.g., Random Forest, XGBoost, or physics-based statistical models).

6. Restricted spatial validation

Validation is limited to eight co-located groups within the same city.

Including cross-validation with other urban or peri-urban sites would help evaluate the transferability of the model.

7. Lack of uncertainty analysis

The study does not include explicit quantification of expanded uncertainty or relative error against the 25% limit required by EU Directive 2008/50/EC.

8. Descriptive focus of the discussion

The discussion mainly characterizes spatial and temporal patterns but could be enriched by including correlations between the observations and socioeconomic or public-health variables.

Recommendations for policy-oriented enhancement

To ensure that the study effectively supports environmental and urban health policies, it is recommended to complement the calibration model with an integrated geo-epidemiological and geophysical approach, linking pollution with territorial and health determinants.

These actions could enhance the utility of the InfoAer system and its replicability in other cities.

a) Incorporate a Digital Elevation Model (DEM)

Integrating a high-resolution DEM (e.g., SRTM or urban LiDAR) would allow modeling the influence of local topography on pollutant dispersion.

In Bucharest, small elevation differences may create micro-zones of accumulation or differential ventilation, affecting sensor representativeness.

b) Analyze prevailing winds and their interaction with topography

Wind direction and speed should be included as predictive or control variables.

Bucharest exhibits wind patterns channeled by the Dâmbovița River basin, which condition the dispersion of aerosols and trace gases.

Including these vectors would improve dynamic modeling and enable hourly or seasonal projections of pollution risk.

c) Geological and emission-source mapping

Overlay geological and land-use layers to identify quarries, mills, industrial facilities, or aggregate plants as potential sources of coarse and fine particulate emissions.

This mapping would facilitate spatial attribution of emissions and support the design of mitigation or buffer zones.

d) Integration of health and epidemiological information

Link the calibrated PM₂.₅ data with medical consultations and hospital admissions related to respiratory diseases, including:

Asthma

Chronic Obstructive Pulmonary Disease (COPD)

Lung cancer

Acute respiratory infections

This approach would enable the creation of correlation maps between pollution and health outcomes, useful for public policy, hospital planning, and preventive campaigns.

It would also facilitate the evaluation of environmental interventions based on morbidity indicators.

e) Development of an integrated geospatial visualization platform

Implement an interactive geospatial dashboard that combines layers of air pollution, topography, wind, and public-health data.

Such a system would support multi-sectoral decision-making (health, environment, transport, urban planning) and strengthen public communication on air-quality risks.

Minor graphical limitations

The figures are clear but could benefit from a standardized color scale and a consistent legend across all maps to improve comparative interpretation.

Recommendation

The manuscript meets PLOS Climate’s publication criteria for scientific rigor, methodological soundness, and ethical transparency. The conclusions are well supported by the data, and the research is directly relevant to climate, health, and environmental governance.

Recommendation: Accept with minor revisions, specifically:

• Provide open access to the dataset.

• Add a concise uncertainty analysis.

• Expand the discussion of topographic and meteorological influences.

• Optionally, highlight how calibrated LCS networks could inform public-health surveillance and urban air-quality policy.

Upon addressing these minor points, the manuscript will constitute an excellent contribution to the field of environmental monitoring and policy-oriented climate science.

Reviewer #2: Reviewer Comments

Summary

This manuscript presents a calibration and performance evaluation of a low-cost sensor (LCS) network (InfoAer) for PM₂.₅ monitoring in Bucharest, Romania. Forty-four Clarity Node-S sensors were assessed against reference data from the National Environmental Protection Agency (NEPA). The study developed multiple seasonal calibration models incorporating meteorological and chemical variables (temperature, relative humidity, and NO₂) and demonstrated that post-calibration data provided a more accurate representation of air quality conditions and regulatory exceedances.

The study is timely and relevant to PLOS Climate readers, given the increasing interest in low-cost air quality monitoring for climate-health interactions, urban air pollution management, and citizen science. However, some methodological details, interpretive depth, and contextualization within climate and policy frameworks require clarification and strengthening.

Comments

1. Scientific Significance and Novelty

The manuscript provides important insights into the performance of LCS networks under varying meteorological conditions, but its scientific novelty is only implicitly stated.

Formatting: Replace “�” with the correct symbol “≤” and ensure consistent units (µm, µg m⁻³).

Line 14–15: “network 14” appears to be a formatting or numbering artifact; clarify or delete.

Line 27–28: Define what is meant by “optimal calibration model” — was optimization based on lowest RMSE or highest R²?

Introduction.

The introduction is well-researched and comprehensive, presenting a logical progression from the global problem of air pollution to the specific issue of low-cost sensor calibration. The flow of ideas is strong, and the topic is timely and relevant for Climate readers. However, the writing can be improved for clarity, conciseness, and coherence, especially by reducing redundancy, enhancing transitions, and tightening sentence structures. Some minor stylistic, grammatical, and formatting errors should also be corrected.

Comments

1. Opening Paragraph

Strengths: The introduction begins with a compelling global context and cites credible data from a 2024 report.

Comment

i. The first paragraph is dense and slightly repetitive. It mentions both global and regional impacts of air pollution but could flow more smoothly by linking global patterns to European examples.

ii. The phrase “be pollution” in line 46, is a typographical error; should be “by pollution”.

iii. The section on uncertainty in epidemiological studies could be condensed to maintain focus on data limitations rather than health uncertainty, which is tangential.

Provides strong justification for the study by referencing Romania’s historical challenges and recent improvements in monitoring capacity.

Overly long sentences obscure the main message.

The tone is bureaucratic (“CGMB Decision No. 201/30.03.2022”) — details like this are better summarized or moved to Methods.

The flow from regulatory issues to infrastructure improvements and need for calibration could be made more direct.

Study Area Description (Section a)

I. The section reads like a figure caption rather than narrative text, with excessive reference to figure components and map colors.

II. Overly detailed discussion of figure symbols (e.g., “red lines,” “gray lines,” “green boxes”) is unnecessary in the text and should remain in the figure caption.

III. Sentences such as “The following sections provide detailed descriptions…” are meta-discursive and not needed in a published paper.

Comments

1. Improve readability and structure

The writing is heavy with long, multi-clause sentences and frequent use of nested parentheses. Break these into shorter, clear sentences to improve readability.

Introduce subheadings within the section (e.g., “Calibration Methodology,” “Model Development,” “Seasonal Adjustment,” “Model Validation,” “Discussion of Results”) to help readers follow the workflow.

Clearly distinguish between methodological description and discussion of results. Currently, methods and interpretations are intermixed, which confuses readers about what was done versus what was found.

a) Model Validation

Ensure numerical results are contextualized (e.g., what level of R² indicates “excellent” in this context?).

Use consistent units and notation (μg m⁻³ should be formatted consistently).

(b) Site Anomalies

Avoid redundancy: the discussion of “systematic underestimation,” “possible bias,” and “local meteorological influences” could be integrated into one cohesive paragraph.

(c) EU/WHO Compliance

This subsection is informative and policy-relevant but too long for a results section.

Move part of the detailed explanation of SDG targets and WHO rationale to the Introduction or Discussion section to maintain focus here on findings (e.g., exceedance frequencies, implications for Bucharest’s air quality).

Improve readability by separating statistical findings from interpretation.

For example:

Paragraph 1: Calibration effect on exceedance counts.

Paragraph 2: Comparison to EU and WHO standards.

Paragraph 3: Implications for public health and policy.

(d) Spatial and Seasonal Variations

The interpretation of spatial and seasonal patterns is strong but could be condensed to emphasize key messages.

Simplify complex sentences. For instance:

“The observed spatial distribution patterns suggest that air pollution in Bucharest is primarily caused by vehicular emissions and regional aerosol transport…”

could be simplified to

“Spatial trends indicate that vehicular emissions and regional aerosol transport are the dominant pollution sources, with peripheral heating activities intensifying winter concentrations.”

Avoid excessive parenthetical expressions, they interrupt flow. Use short sentences instead.

Replace technical jargon where possible:

e.g., “parameterization phase” → “model training phase.”

Ensure consistent terminology for the same concept: “cluster,” “co-location cluster,” “station,” and “site” are sometimes used interchangeably; clarify distinctions early.

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what does this mean? ). If published, this will include your full peer review and any attached files.

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Reviewer #1: Yes:  Carlos Barboza Pizard

Reviewer #2: No

**********

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PCLM-D-25-00337R1

City-scale calibration of a low-cost PM₂.₅ network for regulatory-compliant air-quality assessment

PLOS Climate

Dear Dr. Gautam,

Thank you for submitting your manuscript to PLOS Climate. After careful consideration, we feel that it has merit but does not fully meet PLOS Climate’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Jan 14 2026 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at climate@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pclm/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

• A letter that responds to each point raised by the editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
• A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
• An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

We look forward to receiving your revised manuscript.

Kind regards,

Jingyu Wang

Academic Editor

PLOS Climate

Journal Requirements:

1. Please include a complete copy of PLOS’ questionnaire on inclusivity in global research in your revised manuscript. Our policy for research in this area aims to improve transparency in the reporting of research performed outside of researchers’ own country or community. The policy applies to researchers who have travelled to a different country to conduct research, research with Indigenous populations or their lands, and research on cultural artefacts. The questionnaire can also be requested at the journal’s discretion for any other submissions, even if these conditions are not met.  Please find more information on the policy and a link to download a blank copy of the questionnaire here: https://journals.plos.org/climate/s/best-practices-in-research-reporting. Please upload a completed version of your questionnaire as Supporting Information when you resubmit your manuscript.

2. In your Methods section, please provide additional information regarding the permits you obtained for the work. Please ensure you have included the full name of the authority that approved the field site access and, if no permits were required, a brief statement explaining why.

3. Please note that PLOS Climate has specific guidelines on code sharing for submissions in which author-generated code underpins the findings in the manuscript. In these cases, we expect all author-generated code to be made available without restrictions upon publication of the work. Please review our guidelines at https://journals.plos.org/climate/s/materials-and-software-sharing#loc-sharing-code and ensure that your code is shared in a way that follows best practice and facilitates reproducibility and reuse.

If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise.

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments (if provided):

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

publication criteria?>

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?-->?>

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available (please refer to the Data Availability Statement at the start of the manuscript PDF file)??>

The PLOS Data policy

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English??>

Reviewer #1: Yes

Reviewer #2: Yes

**********

Reviewer #1: In summary, and based on the most recent review, I would like to frame my comments by comparatively evaluating the studies presented and the revisions undertaken:

Relevance and timeliness of the study

Original observation

The topic was considered highly relevant for urban environmental management, with clear applied value in aligning low-cost sensor (LCS) networks with European Union regulatory standards. It was recommended that the framing related to public policy and health be strengthened.

Response in the revised version (R1)

The revised version explicitly expands the political and regulatory context by incorporating the Sustainable Development Goals (SDGs 11.6.2 and 3.9.1) and strengthening links with WHO and EU standards.

The introduction has been reorganised so that regulatory and health-related motivations precede the technical description, which improves the manuscript’s relevance for environmental governance.

Assessment: Comment fully addressed and improved.

R1 presents a clearer and more robust argument regarding the scientific and policy relevance of the study.

Clarity and reproducibility of the methodology

Original observation

The methodology was solid, but greater clarity was recommended in:

documentation of the data flow,

operational criteria for seasonal partitioning,

the overall reproducibility of the analytical process.

Changes in R1

Inclusion of a table of acronyms, improved documentation of the data flow and data sources (InfoAer, RNMCA, OSM).

A more precise explanation of the two-stage calibration process:

model comparison within each cluster,

selection of cluster B23 as the reference site and cross-validation.

The dataset is now included as Supplementary Material, which substantially enhances reproducibility.

Persistent weaknesses

The operational definition of “dry” and “humid” periods remains implicit.

No code or pseudocode is provided to enable exact replication of the analysis.

Assessment

Partially resolved, with clear improvements:

Reproducibility is now adequate for PLOS Climate, although further strengthening would still be beneficial.

Rigorous quality control

Original observation

The QA/QC procedures complied with European criteria, but the reviewer requested:

explicit treatment of uncertainty,

clear regulatory performance benchmarks,

deeper discussion of anomalous clusters.

Changes in R1

Explicit incorporation of the Joint Research Centre (JRC) performance thresholds (R² > 0.9 equivalent to reference-grade; R² > 0.75 adequate for supplementary monitoring).

More detailed interpretation of problematic clusters (B9, B16, B20), linking their behaviour to microenvironmental conditions or representativeness issues.

Expanded physical explanation of the negative bias observed in LCS measurements.

Unresolved aspects

Expanded uncertainty is not quantified, as required by Directive 2008/50/EC.

No confidence intervals or temporal autocorrelation analyses are provided.

Assessment: Significant improvements, but the absence of a formal uncertainty analysis remains the main methodological limitation.

Potential for regional extension

Original observation

The approach was considered transferable to other European or Latin American cities.

Changes in R1

This aspect is maintained and explained with greater clarity in the discussion.

Assessment: Properly maintained and clarified.

Limitations of the linear model (MLR)

Original reviewer observation

It was noted that strictly linear relationships may fail under non-linear atmospheric conditions. The reviewer recommended exploring or at least comparing with non-linear approaches (RF, XGBoost, etc.).

Changes in R1

A clearer justification for using MLR is provided.

The physical interpretation of the model coefficients is improved.

The limitations in inter-city transferability are more explicitly acknowledged.

Remaining gaps

No comparison with non-linear models is included.

No alternative model is presented, even in supplementary material.

Assessment: Partially addressed.

The conceptual discussion is stronger, but the technical limitation remains unchanged.

Restricted spatial validation

Original observation

It was recommended that validation be extended beyond Bucharest’s urban clusters.

Changes in R1

The logic of the validation scheme is clarified.

The discussion of problematic clusters is more transparent.

The need for inter-urban validation is acknowledged in the conclusions.

Assessment: Not resolved, though it is now adequately discussed.

Lack of formal uncertainty analysis

Original observation

The reviewer requested expanded uncertainty quantification relative to the 25% threshold required by the EU.

In R1

This analysis is still not provided.

Assessment: Comment not addressed.

This is the most serious outstanding omission.

Predominantly descriptive discussion

Original observation

It was recommended that the discussion be enriched with socioeconomic, health-related and land-use variables.

Changes in R1

Slight expansion of attribution to residential heating and traffic.

Explicit mention of land-use regression models as future work.

No integration of socioeconomic or health data.

Assessment: Partially addressed, with modest improvements.

Structured summary of R1’s response to reviewer comments

Reviewer comment Addressed? Evaluation

Relevance and policy framing Yes Significantly improved

Methodological clarity Partial Improved documentation; some details still missing

Quality control Partial Better justification; uncertainty still lacking

Regional extension Yes Clarified

Limitations of the linear model Partial Better discussion; no alternative models

Spatial validation Partial Acknowledged; no additional validation

Uncertainty analysis No Entirely absent

Enriched discussion Partial Slight improvement

Overall assessment of the revised version (R1)

The revised manuscript shows clear, substantive and verifiable improvements in:

clarity and organisation,

methodological transparency,

alignment with regulatory frameworks,

physical interpretation of sensor behaviour,

data documentation and calibration workflow.

However, two critical weaknesses persist:

The absence of a formal uncertainty analysis, which is indispensable for regulatory interpretation.

The lack of comparison with non-linear approaches, which limits methodological robustness.

Despite these weaknesses, the manuscript remains scientifically solid, relevant and useful for urban environmental governance.

Editorial recommendation

Accept with minor revisions, specifically:

Include a concise uncertainty analysis (expanded uncertainty, relative error or confidence intervals).

Provide a clear justification for not including non-linear models, or include at least a minimal comparison in the supplementary material.

Specify the operational definition of dry and humid periods.

Add a brief mention of the potential public-health applications of the calibrated data.

Reviewer #2: The authors have addressed all comments

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what does this mean? ). If published, this will include your full peer review and any attached files.

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Reviewer #1: Yes:  Carlos Barboza Pizard

Reviewer #2: No

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

City-scale calibration of a low-cost PM₂.₅ network for regulatory-compliant air-quality assessment

PCLM-D-25-00337R2

Dear Dr. Gautam,

We are pleased to inform you that your manuscript 'City-scale calibration of a low-cost PM₂.₅ network for regulatory-compliant air-quality assessment' has been provisionally accepted for publication in PLOS Climate.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow-up email from a member of our team.

Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.

IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they'll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact climate@plos.org.

Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Climate.

Best regards,

Jingyu Wang

Academic Editor

PLOS Climate

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Additional Editor Comments (if provided):

Reviewer Comments (if any, and for reference):

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: All comments have been addressed

**********

publication criteria?>

Reviewer #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?-->?>

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available (please refer to the Data Availability Statement at the start of the manuscript PDF file)??>

The PLOS Data policy

Reviewer #1: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English??>

Reviewer #1: Yes

**********

Reviewer #1: The manuscript represents a substantially improved version compared to previous review rounds. The current version (R2) demonstrates a clear and consistent effort to address reviewer comments, particularly those related to methodological rigour, analytical transparency, and alignment with European regulatory frameworks.

From both a scientific and editorial perspective, the work is robust, relevant, and timely for the readership of PLOS Climate, offering clear applied value for urban environmental management and regulatory interpretation of low-cost sensor data.

Key issues addressed in the latest revision

Uncertainty analysis (previously critical issue)

The inclusion of confidence intervals through bootstrap resampling, together with explicit reporting of performance metrics (R², RMSE, MBE) and their associated uncertainty ranges, constitutes a substantial improvement.

This addition adequately responds to the requirements of Directive 2008/50/EC and the recommendations of the Joint Research Centre, significantly strengthening the regulatory interpretability of the results.

Methodological clarity and reproducibility

The two-stage calibration framework is now clearly described and reproducible. The inclusion of the dataset as supplementary material, together with improved documentation of data flow and quality control criteria, markedly enhances the transparency of the study.

Justification of the statistical approach (MLR)

Although non-linear models are not implemented, the current version provides a technically and regulatorily sound justification for the use of multiple linear regression, emphasising transparency, physical interpretability, and compatibility with regulatory frameworks. This is acceptable given the stated objectives of the study.

Discussion of limitations and scope

Limitations related to restricted spatial validation and inter-urban transferability are now explicitly acknowledged and discussed in a balanced manner, without undermining the validity of the conclusions or leading to overinterpretation.

Suggested minor improvements

To further enhance the editorial quality of the manuscript, the following minor refinements are suggested:

Operational definition of dry and humid periods

While implicitly understandable, a brief explicit definition (e.g. climatological or month-based criteria) would improve methodological clarity.

Editorial language polishing

A light stylistic revision is recommended to shorten some lengthy sentences and reduce redundancy, particularly in the Discussion section.

Strengthening the public health linkage

A brief additional mention of the implications of calibrated data for population exposure assessment would further reinforce the applied relevance of the study.

Editorial recommendation

In light of the scientific quality achieved, the satisfactory resolution of previously critical issues, and the minor nature of the remaining suggestions, the recommendation is:

Accept the manuscript, or accept with minor editorial revisions.

The manuscript meets the required scientific and editorial standards and represents a valuable contribution to the literature on urban environmental monitoring and evidence-based environmental governance.

**********

what does this mean? ). If published, this will include your full peer review and any attached files.

Do you want your identity to be public for this peer review? If you choose “no”, your identity will remain anonymous but your review may still be made public.

For information about this choice, including consent withdrawal, please see our Privacy Policy

Reviewer #1: Yes:  Carlos Barboza Pizard

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