This manuscript addresses an interesting and important topic. Measuring PM_2.5 exposure in transport microenvironments using citizen science fills a knowledge gap where official monitoring data are unavailable. The low-cost sensor validation and emphasis on public participation are strengths. However, there are several methodological, statistical, and interpretational issues that should be addressed before publication 

1. Study design needs stronger description: The manuscript should address the following details to become more representative. 
1.  How were sampling days selected? 
2. Were weather conditions recorded? 
3. Were traffic intensity and ventilation operation considered? 
2. Line 133-135: Indicate which figures in the SI are related to this analysis in the format of SI Figure X. Also, fix every PM2.5 to PM_2.5.
3. Line 138-140: Please include scatter plots and/or time series comparison showing the relationship between the AirBeam 3 and the reference TEOM measurements before and after the calibration, with the regression line, regression equation, R^2 etc. A visual representation would help readers assess the agreement between the two instruments and identify any systematic bias or outliers. 
4. Line 142-149: This paragraph is difficult to follow because it combines multiple statistical analyses in a single paragraph without clearly explaining the purpose of each method. The manuscript should explicitly state the objective of each analysis and how they complement one another. 
5. Line 152-155: Since Airbeam records mapping data. It would be useful to show the transient data and display it on a map. 
6. Line 157-166: Please provide a detailed log of each field measurement (preferably in the Supplementary Material), including the sampling date, time, route, tunnel section, duration, enter/exit time, and other relevant metadata.
7. Line 168-174: Please indicate which figure or table corresponds to the analysis described in this section. More generally, throughout the manuscript, every major analysis should reference the corresponding figure or table (e.g., Figure X or Table Y). 
8. Line 168-173: Explain ANOVA testing. 
9. Artificial division into Phase A and Phase B: the division of tunnel measurements into two equal halves appears arbitrary. Instead, try to change points statistically. 
10. Explain the quality-control criteria.

Comments and Suggestions for Authors

The title, in its current form, is not particularly appealing. It might be more effective to remove the full stop and use “in Madrid” instead.

The literature review is strongly focused on the existing state of knowledge in Madrid, and the research gap to be addressed by the study is clearly identified.

This study evaluated the performance of low-cost sensors (LCS) for monitoring PM2.5 in urban transport microenvironments, including road tunnels and metro systems. The study highlights the potential of LCS and citizen-based monitoring to assess exposure and support air quality surveillance in transport environments. The study also highlights potentially elevated PM2.5 concentrations in heavily trafficked urban tunnels and metro environments, which may pose health risks, particularly for susceptible populations. The authors recommend systematic PM2.5 monitoring in tunnels, metro platforms, and train carriages, with publicly available data and the implementation of corrective measures when pollutant concentrations exceed relevant thresholds.

The division into paragraphs is clear and well structured.

Some recommendations and comments are provided:

1. Lines 113, 115, and 118: The references to the citations appear to be missing, as “n.d.” is reported. Please check and provide the appropriate references.
2. Line 124: How is cPM2.5 defined? It would be useful to provide its definition at its first occurrence. If it refers to PM2.5 concentration, clarification is needed because “PM2.5 concentration” is used instead in Lines 217–218. Do these terms refer to different quantities? The term “mean cPM2.5 concentration” is also used in Lines 249–250. Please clarify the distinction between these terms.
3. Line 181: A full stop appears to be missing.
4. It might be appropriate to move the section on public health implications, currently included in the Discussion section, to an earlier position, closer to the literature review. This section contains several references to previous studies and could therefore be more effectively integrated into the background and state-of-the-art discussion.
5. Tables 1 and 2: These tables could potentially be converted into graphical representations, which might provide a clearer visualization of the correlation between the LCS measurements and the reference values.
6. The number of figures is relatively limited. Consider including additional graphical representations of the results. It might also be useful to plot the reference measurements alongside the LCS measurements to facilitate a direct comparison.
7. Where are the reference monitoring stations located? Please provide information on their location and, if relevant, their proximity to the measurement sites.
8. Sensor performance over time: How do you assess the potential degradation or drift of the sensors over time? What methodology is used to evaluate the long-term reliability and stability of the system under study?
9. It would be useful to include a dedicated section describing the specific characteristics of the sensors used in the study. Providing detailed information on the instrumentation used as the validation basis could strengthen the interpretation and reliability of the validation results.
10. Figure 2: The x-axis is missing. Since the x-axis represents the time variable, this should be explicitly indicated. Alternatively, considering that the measurements were performed during a journey, would it be more appropriate to express the x-axis in terms of distance travelled rather than time?

Comments for Editors

The manuscript addresses a relevant and timely topic, namely the use of low-cost sensors to assess PM2.5 exposure in urban transport microenvironments. The study is potentially valuable, particularly because it combines sensor validation with measurements in road tunnels and metro environments and involves citizen participation.

Overall, the manuscript is clearly structured and the research gap is well presented. However, I believe that some aspects should be clarified or strengthened before publication. In particular, further details on the sensors and reference instrumentation, the definition and use of cPM2.5, the location and characteristics of the reference stations, and the assessment of sensor stability and potential degradation over time would improve the scientific robustness of the manuscript. The presentation of the results could also be enhanced through additional figures and a clearer comparison between LCS and reference measurements. Therefore, I believe that the manuscript has merit but requires major revisions before it can be considered for publication.