Spatial Variation of PM₁₀ and PM_2.5 in Residential Indoor Environments in Municipalities Across Mexico City

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Review of Atmosphere 3832182 Spatial variation of PM10 and PM2.5

Lines 17 and 18. Missing word in both lines. Insert “was” twice. It would also be helpful to state if the “averages” here were arithmetic or geometric means or something else. It would be helpful to provide 95% confidence intervals and whether the differences between indoors vs outdoors was statistically significant.

The abstract is missing a conclusion, which might be something like “adequate indoor ventilation is needed to ensure indoor levels are less than outdoor levels and meet WHO indoor and outdoor air quality guidelines.”

Line 29. This perhaps might be an overstatement, because other health problems are also significant concerns, e.g., pandemics, obesity, departure from science in establishing policy, etc. Perhaps it would be best to say that air pollution is “one of” the most crucial public health problems.

Line 34. This is not a complete list of adverse health effects from PM 2.5, so perhaps it is best to add “and other health problems” to the end of this sentence.

Line 54. The meaning of “contingency” is not clear here. I think the authors mean “emergency” or exceedances. The English could be improved here and throughout the paper. This reviewer stopped editing the English at this point in the paper.

Line 95. Spell out “TSP”

Line 128, specify whether this is the arithmetic or geometric mean.

Line 265. It would be helpful to also reference the WHO air quality guidelines, which apply to both indoor and outdoor levels. See: https://www.who.int/news-room/feature-stories/detail/what-are-the-who-air-quality-guidelines

Line 279. It would be helpful to state what exactly is meant by “poor ventilation”

Line 466. Did an IRB determine this study was exempt?

Somewhere in this paper, the authors might reference some outdoor events that may lead to far higher levels, such as wildfires.

Thank you for the opportunity to review this paper.

Comments on the Quality of English Language

English needs minor improvement throughout

Author Response

Comments and Suggestions for Authors

Review of Atmosphere 3832182 Spatial variation of PM10 and PM2.5

1. Lines 17 and 18. Missing word in both lines. Insert “was” twice. It would also be helpful to state if the “averages” here were arithmetic or geometric means or something else. It would be helpful to provide 95% confidence intervals and whether the differences between indoors vs outdoors was statistically significant.

A: Arithmetic averages

2. The abstract is missing a conclusion, which might be something like “adequate indoor ventilation is needed to ensure indoor levels are less than outdoor levels and meet WHO indoor and outdoor air quality guidelines.”

A: Corrected, we include your suggestion.

3. Line 29. This perhaps might be an overstatement, because other health problems are also significant concerns, e.g., pandemics, obesity, departure from science in establishing policy, etc. Perhaps it would be best to say that air pollution is “one of” the most crucial public health problems.

A: Corrected

4. Line 34. This is not a complete list of adverse health effects from PM 2.5, so perhaps it is best to add “and other health problems” to the end of this sentence.

Corrected

5. Line 54. The meaning of “contingency” is not clear here. I think the authors mean “emergency” or exceedances. The English could be improved here and throughout the paper. This reviewer stopped editing the English at this point in the paper.

A: Now says

This is of great relevance since, when environmental air quality standards are exceeded,

6. Line 95. Spell out “TSP”

A: Corrected: Yes, it stands for total suspended particles, but it was eliminated as we did not report TSP data.

7. Line 128, specify whether this is the arithmetic or geometric mean.

A: Corrected: Arithmetic mean

8. Line 265. It would be helpful to also reference the WHO air quality guidelines, which apply to both indoor and outdoor levels. See: https://www.who.int/news-room/feature-stories/detail/what-are-the-who-air-quality-guidelines

A: Corrected:

Considering that 24-hour Mexico NAAQS of 41 µg m^-3 (NOM-025-SSA1-2021), refers to ambient air quality, it will be used as a reference to establish parameters for analyzing variations in concentrations within houses.

The paragraph was modified as follows, including your suggestions.

While the NAAQS value applies to ambient air, it is used here as a benchmark to assess household air quality. The World Health Organization [47] recommends an annual 24-hour PM₂.₅ limit of 15.0 µg m⁻³ for ambient air and a 25.0 µg m⁻³ 24-hour value for combustion-derived indoor pollutants [48]. Indoor PM₂.₅ concentrations are strongly influenced by the use of solid fuels and low-efficiency stoves for cooking, heating, and lighting, which can produce high emissions from incomplete combustion [49-50].

References:

2. WHO global air quality guidelines: particulate matter (‎PM2.5 and PM10)‎, ozone, nitrogen dioxide, sulfur dioxide and carbon monoxide (2021). https://www.who.int/publications/i/item/9789240034228 accessed 14 August 2025.
3. WHO guidelines for indoor air quality: selected pollutants. Bonn: World Health Organization; 2010 (http://www.euro.who.int/__data/assets/pdf_file/0009/128169/e94535.pdf, accessed 17 July 2014) accessed 14 August 2025.

• Gordon, S.B.; Bruce, N.G.; Grigg, J.; Hibberd, P.L.; Kurmi, O.P.; Lam, K.B.; Mortimer, K.; Asante, K.P.; Balakrishnan, K.; Balmes, J.; et al. Respiratory risks from household air pollution in low and middle income countries. Lancet Respir. Med. 2014, 2, 823–860. https://doi.org/10.1016/S2213-2600(14)70168-7

 

9. Line 279. It would be helpful to state what exactly is meant by “poor ventilation”

A: Corrected 

The results indicate that Álvaro Obregón registered the highest outdoor PM₁₀ levels. In contrast, municipalities such as Azcapotzalco, Coyoacán, Cuauhtémoc, Milpa Alta (MA), and Tlalpan reported continuous indoor activities combined with poor ventilation, often with all windows closed, which resulted in substantially higher maximum indoor concentrations compared to outdoor measurements.

Line 466. Did an IRB determine this study was exempt?

It was not necessary, as we worked on air quality indoors, we did not work with inhabitants.

10. Somewhere in this paper, the authors might reference some outdoor events that may lead to far higher levels, such as wildfires.

A: During the study, we focused on air quality indoors, and no important wildfires were reported, as the one that occurred in 2019.

 

Thank you for the opportunity to review this paper.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Dear Authors,

 

I have reviewed your manuscript titled: ” Spatial variation of PM10 and PM2.5 in residential indoor environments in municipalities across Mexico City” and concluded that it is an interesting review dealing with a topic that is relevant for the readership of the journal Atmosphere. I think this work is suitable and in the scope of the Journal Atmosphere. However, some issues need to be addressed.

 

1. I suggest rewriting the title, e.g., Residential Exposure to PM10 and PM2.5: A Spatial Perspective from Mexico City Municipalities.
2. In the introduction section, in the last paragraph, add a few more sentences about the goals of this work.
3. While correlation is reported (R = 0.97), the section does not include other important metrics such as RMSE, MAE, mean bias, or Bland-Altman analysis, which would help to characterize agreement between instruments better.
4. It is unclear whether the performance during the brief period of 17 days is representative of longer-term behavior or different seasons.
5. The analysis focuses on maximum concentrations, but does not clarify whether these spikes were sustained or brief. Averages, standard deviations, or time-series plots would help contextualize the exposure risk.
6. Were housing characteristics (e.g., building materials, floor type, ventilation design) taken into account when analyzing PM differences between homes?
7. The data suggests correlations (e.g., more occupants = higher PM2.5), but no statistical tests (e.g., regression, ANOVA) are reported to confirm significance or control for confounders like ventilation or house size. Were any statistical tests performed to determine whether the differences in PM2.5 concentrations based on cooking type or occupancy are significant?
8. Given the small sample size (n = 27), how confident are you in the generalizability of the observed trends? Do you plan to expand the sample in future studies?

Author Response

Dear Authors,

 

I have reviewed your manuscript titled: ”Spatial variation of PM10 and PM2.5 in residential indoor environments in municipalities across Mexico City” and concluded that it is an interesting review dealing with a topic that is relevant for the readership of the journal Atmosphere. I think this work is suitable and in the scope of the Journal Atmosphere. However, some issues need to be addressed.

 

1. I suggest rewriting the title, e.g., Residential Exposure to PM10 and PM2.5: A Spatial Perspective from Mexico City Municipalities.

A: Thank you for your suggestion, but we consider that our title reflects our work,

 

1. In the introduction section, in the last paragraph, add a few more sentences about the goals of this work.

Lines were included as reviewer 1 suggested

Adequate indoor ventilation is needed to ensure indoor levels are less than outdoor levels and meet WHO indoor and outdoor air quality guidelines

 

1. While correlation is reported (R = 0.97), the section does not include other important metrics such as RMSE, MAE, mean bias, or Bland-Altman analysis, which would help to characterize agreement between instruments better.

A: The suggested metrics are determined and commented. A Bland-ALtman analysis was added, finding an average underestimation of 1.8 µg/m³ for the OPC-equipment, and higher differences for higher concentrations.

 

1. It is unclear whether the performance during the brief period of 17 days is representative of longer-term behavior or different seasons.

A: The period of the study was longer; the study took one and a half years. In addition, the study was conducted indoors, so different seasons would not affect the indoor measurements, as the temperature variability indoors is low.

 

1. The analysis focuses on maximum concentrations, but does not clarify whether these spikes were sustained or brief. Averages, standard deviations, or time-series plots would help contextualize the exposure risk.

A: We reported average concentrations as stated in the following sentence:

The performance comparisons' results were based on a 24-hour average of PM_2.5 concentrations from August 19 to September 6, 2022.  

We also used time series as shown if Figure 2

Figure 3 shows the Box and whisker plots that include the basic statistics, as well as figures 4 and 5 that the corresponding distributions.

 

1. Were housing characteristics (e.g., building materials, floor type, ventilation design) taken into account when analyzing PM differences between homes?

A: Yes, but unfortunately, not all collaborators filled out the questionnaire to analyze this information, and some did not answer all the questions. An ANOVA and k-means clustering analysis was added to address the influence of the housing characteristics. No significant influence for these factors was found, however, neither on PM fraction concentrations nor on their ratios. We assume that the relatively low number of houses included in the questionnaire, as well as the large number of observed housing characteristics, were responsible for the fact that the conclusions were not significant (although some tendencies were observed).

 

1. The data suggests correlations (e.g., more occupants = higher PM2.5), but no statistical tests (e.g., regression, ANOVA) are reported to confirm significance or control for confounders like ventilation or house size. Were any statistical tests performed to determine whether the differences in PM2.5 concentrations based on cooking type or occupancy are significant?

• Although this was not the main objective of the study, an ANOVA and k-means analysis were added. However, the number of houses was not sufficient to draw final conclusions. We will definitely take into account your comment in future research and will design a more comprehensive study to be able to draw firmer conclusions.

 

1. Given the small sample size (n = 27), how confident are you in the generalizability of the observed trends? Do you plan to expand the sample in future studies?

A: We have 47 houses, but the questionnaire was answered by only 27. We definitely will extend the number of samples in future research.

 

Submission Date

06 August 2025

Date of this review

11 Aug 2025 22:45:20

Reviewer 3 Report

Comments and Suggestions for Authors

1. Title and abstract are fine.
2. Keywords do not accurately represent the overall characteristics of the entire paper.
3. Improve the coherence in the introduction.
4. The methodology and materials require more detail for the reader.
5. Why the Particles Plus model 8301-AQM and 8302-AQM particle counters?
6. Narrow time frame (August–September 2022). This may not capture seasonal variability in indoor–outdoor PM relationships.
7. Why was each home monitored for only seven days? This bounds the ability to simplify findings to long-term indoor air quality.
8. What are the reasons to validate OPC devices against BAM monitors?
9. While the study links higher indoor PM2.5 to cooking and cleaning, it lacks a detailed chemical characterisation to confirm contributions from specific sources.
10. Although relative humidity data and temperature were considered, the study does not fully integrate broader meteorological variables (e.g., wind speed, atmospheric pressure) that could influence dispersion and infiltration.
11. This study does not include direct health measurement data, which limits public health.
12. Ventilation type and rate?
13. More advanced statistical modelling (e.g., mixed-effects regression accounting for household clustering) could improve robustness and control for confounding factors.
14. The conclusion needs to link with the objectives.
15. Replace outdated references with the latest ones.
16. Improve the flow of information and sentence structure of the whole paper.

Comments on the Quality of English Language

The English could be improved to convey the research more clearly.

Author Response

Comments and Suggestions for Authors

1. Title and abstract are fine.
2. Keywords do not accurately represent the overall characteristics of the entire paper.

A: Some keywords were added

1. Improve the coherence in the introduction.

A: There were corrections included in the introduction.

1. The methodology and materials require more detail for the reader.

A: The methodology was corrected.

Particles Plus model 8301-AQM and 8302-AQM optical particle counters (OPCs) were used to measure concentrations of five particulate matter fractions: PM_0.5, PM₁, PM_2.5, PM_5, and PM₁₀. The monitors were programmed for continuous measurements indoors and outdoors in each home, 24 hours a day, seven days a week. The devices operate using a light-scattering detection system capable of sizing particles from 0.3 to 25 μm. In addition, they feature sensors for ambient temperature and relative humidity, as well as long-term data storage.

The Particles Plus OPCs were selected due to their combination of portability, affordability, and high temporal resolution, which allows simultaneous measurement of air quality in multiple locations. Their ability to record measurements at minute- or second-level intervals enables the capture of rapid fluctuations in PM concentrations throughout the day, providing insights into short-term exposure peaks that fixed-site monitors may miss [25-26]. Furthermore, these instruments facilitate the identification of indoor pollution hotspots, characterization of pollutant sources, complement fixed-site monitoring networks, and enable personal exposure assessments. Their ease of use also allowed active citizen participation in air quality monitoring in Mexico City, fostering environmental awareness and engagement [27].

The Particles Plus monitors were installed in 38 homes for seven consecutive days, primarily in living rooms and kitchens, covering all 16 municipalities of Mexico City. Participants maintained a diary of daily activities and completed a questionnaire documenting home characteristics, including flooring type, wall materials, proximity of windows to busy streets, number of inhabitants, and the presence of pets.

Given that low-cost OPCs may exhibit specific limitations in particle detection, performance comparisons were conducted to ensure data reliability [28]. Two levels of calibration were applied [29]: (1) direct comparison of the OPCs with reference-grade monitors and (2) co-location of the OPCs with reference equipment. The reference system was a beta attenuation monitor (BAM), which collects particles on a filter via a controlled airflow over a defined period for precise mass determination.

1. Why the Particles Plus model 8301-AQM and 8302-AQM particle counters?

A: The Particles Plus OPCs were selected due to their combination of portability, affordability, and high temporal resolution, which allows simultaneous measurement of air quality in multiple locations. Their ability to record measurements at minute- or second-level intervals enables the capture of rapid fluctuations in PM concentrations throughout the day, providing insights into short-term exposure peaks that fixed-site monitors may miss [25-26]. Furthermore, these instruments facilitate the identification of indoor pollution hotspots, characterization of pollutant sources, complement fixed-site monitoring networks, and enable personal exposure assessments. Their ease of use also allowed active citizen participation in air quality monitoring in Mexico City, fostering environmental awareness and engagement [27].

 

1. Narrow time frame (August–September 2022). This may not capture seasonal variability in indoor–outdoor PM relationships.

A: The comparison between OPC and BAM was conducted during this period, but the measurement indoors took more than a year and a half.

 

1. Why was each home monitored for only seven days? This bounds the ability to simplify findings to long-term indoor air quality.

A: The restricted time period per house was due to the fact that some volunteers did not want the responsibility to look after an instrument, in addition, for most of them, it was challenging to record all the activities carried out to associate them with PM concentrations. Some of them did not keep a diary of their activities, limiting the conclusions we could draw to this respect.

In addition, we wanted to evaluate the variability in the different municipalities and not just those of a single family.

 

1. What are the reasons to validate OPC devices against BAM monitors?

A: For the performance evaluation of the OPC,

This means to compare the results of a “low-cost” monitor against a reference method.

 

1. While the study links higher indoor PM2.5 to cooking and cleaning, it lacks a detailed chemical characterisation to confirm contributions from specific sources.

We did not do chemical characterization as the instruments that we used are optical counters, which means that they do not collect samples for further chemical analysis. This would be a very interesting point of view (several of the cowriters have a background in chemistry), but was out of the scope of this research.

The influence of prevailing meteorological conditions and variations in outdoor sources was evident. For most residences, outdoor PM₂.₅ concentrations were below the Mexican National Ambient Air Quality Standard (NAAQS) of 41.0 µg m⁻³ [43] for 24-hour averages, although exceedances occurred in a few locations. The highest outdoor concentrations were recorded in Xochimilco, Tláhuac, Iztapalapa, and Venustiano Carranza (VC). These elevated values may be attributed to dust emissions from bare soils, unpaved roads, and resuspension from traffic, consistent with findings from other urban environments [44-45]. In Xochimilco and Tláhuac, ongoing building construction and the presence of stored construction materials likely contributed to dust generation. Additionally, poorly maintained structures with deteriorating paint, and the presence of livestock in rural household areas, may further increase PM₂.₅ emissions [46].

While the NAAQS value applies to ambient air, it is used here as a benchmark to assess household air quality. The World Health Organization [47] recommends an annual 24-hour PM₂.₅ limit of 15.0 µg m⁻³ for ambient air and a 25.0 µg m⁻³ 24-hour value for combustion-derived indoor pollutants [48]. Indoor PM₂.₅ concentrations are strongly influenced by the use of solid fuels and low-efficiency stoves for cooking, heating, and lighting, which can produce high emissions from incomplete combustion [49-50].

 

1. Although relative humidity data and temperature were considered, the study does not fully integrate broader meteorological variables (e.g., wind speed, atmospheric pressure) that could influence dispersion and infiltration.

A: We could consider your comments for future research. The atmospheric pressure is also reported in the OPC, but we did not include it in the results, as these values were relatively constant most of the time.

 

1. This study does not include direct health measurement data, which limits public health.

A: This is true, but also out of the scope of the paper, but we want to measure PM concentrations to assess the risk inside the houses. We will take in consideration for future work.

 

1. Ventilation type and rate?

A: In Mexico, it is not common to have ventilation systems at home, just windows, and indeed, we did not measure any rate at all, but it could be considered in future measurements.

 

1. More advanced statistical modelling (e.g., mixed-effects regression accounting for household clustering) could improve robustness and control for confounding factors.

A: ANOVA and k-means clustering were included. Confounding factors related to domestic characteristics and habits did not influence the PM fraction concentrations and ratios. Although fractions (and to a minor degree concentrations) were found to be significantly different indoors than outdoors, the only significant confounding factor was found to be the location of the house. In a future study, this can be addressed if more low-cost monitors become available. In this study, the study of the dependence on geographical location and surrounding conditions was not the main objective.

 

1. The conclusion needs to link with the objectives.

 

A: Conclusions were modified to include your comments.

Monitoring indoor particulate matter using real-time instruments is essential for assessing health risks and designing effective prevention strategies. Optical particle counters (OPCs) provide a practical solution for continuous indoor air quality monitoring, enabling the evaluation of population exposure in spatial-temporal studies across urban areas.

This study examined the relationship and spatial variation of indoor and outdoor PM of different sizes in 38 houses across 16 municipalities in Mexico City. The performance of the OPC was evaluated against a beta attenuation monitor (BAM), showing a slight underestimation by the OPC compared to the reference instrument.

Indoor/outdoor PM relationships were analyzed to determine the influence of outdoor air on indoor air quality. The results indicate that outdoor PM levels significantly affect indoor concentrations, particularly in homes located near busy roads. On average, indoor PM_2.5 concentrations were 2 to 5 times higher than outdoor levels, primarily due to cooking, cleaning activities, smoking, and the number of occupants. Maintaining proper ventilation during cooking is recommended to reduce exposure to cooking-related aerosols.

Furthermore, the PM₁ fraction represented more than 60% of PM_2.5, suggesting that this fine fraction could be considered for inclusion in the National Ambient Air Quality Standards in Mexico.

Addressing indoor air pollution requires the active involvement of communities and individuals, supported by public education and behavior change initiatives. Understanding the sources of indoor pollutants is essential for developing effective control strategies. Engaging residents in reporting their household activities can help link behaviors with indoor air quality, promoting awareness and encouraging proactive measures. The collaborative use of OPCs can empower households to reduce exposure, thereby improving both individual and collective knowledge of indoor air pollution.

 

 

1. Replace outdated references with the latest ones.

Corrected,

A: More recent references were included in the paper.

 

1. Improve the flow of information and sentence structure of the whole paper.

Corrected

A: The information and sentences were modified throughout the paper to improve the information flow

 

 

Comments on the Quality of English Language

The English could be improved to convey the research more clearly.

A: The English was improved throughout the paper.

 

Reviewer 4 Report

Comments and Suggestions for Authors

This study provides valuable insights into the dynamics of indoor and outdoor PM pollution in Mexico City. Although the methodology is robust and the findings are significant, some sections require clarification and expansion. While the paper aligns with the scope of Atmosphere, it requires revisions to improve clarity and depth.

1. The title of the paper is 'Spatial Variation of ….', but I could not find any charts or textual descriptions relating to spatial distribution in the main body of the text.
2. The literature review is somewhat one-sided, lacking a critical comparison of previous research methods and in-depth arguments justifying the choice of Mexico City as a case study. It is recommended that local policy background information be added, such as Mexican indoor air quality standards, and that citations from similar Latin American research be included.
3. Lines 42-44: I don't understand the significance of this passage.
4. The chapter titles are in the wrong order.
5. Lines 217-222: The number of significant digits after the decimal point is inconsistent.
6. Materials and Methods:

• The OPC systematically underestimates PM2.5, but the results do not specify how to correct this bias, e.g. by providing a calibration formula. This may lead to distorted comparisons between indoor and outdoor concentrations.
• It is unclear whether sampling was conducted in the same season and whether seasonal biases exist.
• The reasons for choosing “kitchen and living room” as monitoring points are unclear, as is the availability of bedroom data.
• There is no description of the socio-economic background of the sample households, which may affect the generalizability of the results.
• The sample size is insufficient, with an average of only two to three households per district. The sampling method (random or stratified) is not specified, which casts doubt on the generalizability of the conclusions.
• Confounding variables such as building age, ventilation frequency, and cleaning habits were neither controlled for nor properly collected through questionnaires.

7. Results & Discussion

• Abstract reports indoor PM2.5 as 22.4 μg/m³, but Figure 11 shows 24.2 μg/m³.
• The discussion on why outdoor concentrations are sometimes higher than indoor concentrations in certain households is not in-depth enough and should be analyzed further in conjunction with geographical location and ventilation conditions.
• There is also a lack of discussion on sources of error, such as systematic bias in OPC at low concentrations.
• The discussion of the policy implications of the results is also superficial. It is recommended that a comparative analysis of existing indoor air quality standards in Mexico City be added.

8. Conclusion: In the absence of health data, the statement that 'PM1 particles account for 60% of PM2.5' (line 445) is insufficient to justify their inclusion in the standard. Please exercise caution when making policy recommendations.

Author Response

1. Open Review

Comments and Suggestions for Authors

This study provides valuable insights into the dynamics of indoor and outdoor PM pollution in Mexico City. Although the methodology is robust and the findings are significant, some sections require clarification and expansion. While the paper aligns with the scope of Atmosphere, it requires revisions to improve clarity and depth.

 

The title of the paper is 'Spatial Variation of ….', but I could not find any charts or textual descriptions relating to spatial distribution in the main body of the text.

 

We generated a map, but the information is not optimal, as some houses are quite close together, and the geographical spread of the houses might not be sufficient to cover the entire area of Mexico City, considering the high number of inhabitants. We decided not to include the map we generated. On the other hand, there is a section on what we observed on this topic.

3.5 Spatial Variations in indoor and outdoor PM₁₀ concentrations across Mexico City municipalities

Figure 10 compares the maximum indoor and outdoor PM₁₀ concentrations recorded across Mexico City. The results indicate that Álvaro Obregón registered the highest outdoor PM₁₀ levels. In contrast, municipalities such as Azcapotzalco, Coyoacán, Cuauhtémoc, Milpa Alta (MA), and Tlalpan reported continuous indoor activities combined with poor ventilation, often with all windows closed, which resulted in substantially higher maximum indoor concentrations compared to outdoor measurements.

Coyoacán and Benito Juárez, located in the city center, recorded the lowest maximum PM₁₀ concentrations both indoors and outdoors. Conversely, Tlalpan, Tláhuac, and Venustiano Carranza, situated in the southern and eastern parts of the city, showed the highest PM₁₀ concentrations, likely influenced by a combination of outdoor sources (e.g., traffic, unpaved roads, soil erosion) and indoor sources (e.g., cooking, dust resuspension).

Overall, more than 70% of the sampled homes registered high indoor PM₁₀ levels. The lowest concentrations were found in Tlalpan, Coyoacán, Iztacalco (IZTAC), and Cuajimalpa, where residents spent less time indoors and reported fewer indoor activities in their logbooks. This finding highlights the strong influence of human activities and ventilation practices on indoor particulate matter levels, consistent with previous research on indoor–outdoor PM dynamics in urban environments [51-53].

 

The literature review is somewhat one-sided, lacking a critical comparison of previous research methods and in-depth arguments justifying the choice of Mexico City as a case study. It is recommended that local policy background information be added, such as Mexican indoor air quality standards, and that citations from similar Latin American research be included.

It has been corrected, and more recent references were added to improve the paper.

Unfortunately, in Mexico, there are no quality standards for indoors; therefore, we consider that this information is important as it can help establish the regulations and control strategies to improve the quality of life indoors and outdoors.

Additionally, Mexico City has the best Air Quality Network in Mexico, which includes at least 2 monitoring sites in each municipality, in comparison to other important cities that may have less than 10 monitoring sites for the whole city, even though they are bigger than Mexico City.

 

Lines 42-44: I don't understand the significance of this passage.

As some of the volunteers to measure PM in their house have smokers, we believe that it is important to point out the risk of smoking inside the house due to the increase not just in PM but also in other substances that are toxic to those living in the house, not only for the smoker.

 

The chapter titles are in the wrong order.

Lines 217-222: The number of significant digits after the decimal point is inconsistent.

Corrected, the number of decimals was homogenized. Ratios were converted to percentages, with one significant digit after the decimal point. Only the R² value is maintained with 2 significant digits, as otherwise it would lack significance.

 

Materials and Methods:

The OPC systematically underestimates PM2.5, but the results do not specify how to correct this bias, e.g. by providing a calibration formula. This may lead to distorted comparisons between indoor and outdoor concentrations.

 

Two levels of calibration were applied [29]: (1) direct comparison of the OPCs with reference-grade monitors and (2) co-location of the OPCs with reference equipment. The reference system was a beta attenuation monitor (BAM), which collects particles on a filter via a controlled airflow over a defined period for precise mass determination.

We performed the validation of the OPC, and we found that it underestimated the PM2.5 at low concentrations, less than 5.0 µg/m³, but it has been shown that indoors, these concentrations are higher.

In 2.6% of the occasions, the OPC overestimated the concentration between 2.0 and 5.0 µg m^-3, and in 0.5% of the measurements with concentrations greater than 5 µg m^-3.

BAM measurements exhibited slightly higher mean and median values than the OPC. The frequency distribution of concentrations was similar, though the OPC had a higher percentage of lower concentrations. Specifically, 51–58% of OPC measurements were below 10.0 µg m⁻³, 29–31% were between 10.1 and 20.0 µg m⁻³, 3–6% were between 30.0 and 39.9 µg m⁻³, and less than 3% exceeded 40 µg m⁻³.

Figure 4 shows histograms of hourly measurements for BAM and OPC, and Figure 5 presents the histogram of differences between the two instruments. Analysis revealed that 56.6% of differences fell between −2.0 and 2.0 µg m⁻³, indicating good agreement. OPC overestimated concentrations by 2.0–5.0 µg m⁻³ in 2.6% of cases and by more than 5.0 µg m⁻³ in 0.5% of measurements. Underestimations were more frequent, with 33.4% of measurements between 2.0 – 5.0 µg m⁻³ and 6.9% exceeding 5.0 µg m⁻³.

 

It is unclear whether sampling was conducted in the same season and whether seasonal biases exist.

As we showed in the results, indoors, high levels of PM are due to cooking or cleaning activities, and the season does not show a difference.

 

The reasons for choosing “kitchen and living room” as monitoring points are unclear, as is the availability of bedroom data.

As the Optical counters measure every 4 minutes, and they were programmed to measure 24/7, it could bother the volunteers to have the noise during the night. We prefer to leave the monitors in living rooms as this is where people spend most of their time. Additionally, the kitchen represents an important source of particles.

 

There is no description of the socio-economic background of the sample households, which may affect the generalizability of the results.

The reason to include all municipalities in Mexico City was to account for these variations; in addition, the questionnaire helps to see these differences.

Figure 9 compares maximum indoor and outdoor PM_2.5 concentrations in Mexico City. The municipalities in central Mexico City - Benito Juarez, BJ, and Coyoacan, COY, generally exhibited the lowest maximum indoor and outdoor PM_2.5 concentrations.

In contrast, municipalities located in the eastern and southern regions of the city—Tlalpan (TLAL), Tláhuac (TLAH), Xochimilco (XOCH), Iztapalapa (IZTAP), and Azcapotzalco (AZC)—recorded maximum indoor levels two to three times higher than outdoor levels. This pattern was consistent with activity logbooks, which documented frequent indoor activities such as cooking, cleaning, and the use of combustion-based heating throughout the day. Only a few houses in Álvaro Obregón (AO), Tláhuac (TLAH), and Cuajimalpa (CUAJ) registered higher maximum concentrations outdoors than indoors. These exceptions may be linked to proximity to industrial zones, construction sites, and major roads with heavy vehicular traffic, which elevate outdoor PM₂.₅ levels.

 

The sample size is insufficient, with an average of only two to three households per district. The sampling method (random or stratified) is not specified, which casts doubt on the generalizability of the conclusions.

 

A total of 81867 indoor records and 79087 outdoor records were available in our study after assessing the quality and validity of the monitoring information. Although we only analyzed 38 homes, we think the monitoring information is sufficient to draw conclusions on the significance of the differences between indoor and outdoor concentrations and ratios, as well as to detect that the location of the households is the most important factor in the PM pollutant concentration and ratio differences. The sampling considered volunteers willing to take part in the study and place a particle monitor in their homes. The sampling method was random in the sense that there was no pattern in the selection of domestic habits and characteristics, nor in the location of the homes of the participants in the study.

 

Confounding variables such as building age, ventilation frequency, and cleaning habits were neither controlled for nor properly collected through questionnaires.

 

As the study depended on volunteers, willing to measure the PM concentrations in their real life environment, it was not possible, neither useful to control the confounding factors.  When volunteers agreed to participate, we tried not to disturb their habits; in fact, this was to measure the real emissions every day, without changes. One of our objectives was to evaluate whether indoor PM concentrations were higher than outdoors, which is what the study was able to draw conclusions on.

 

Results & Discussion

Abstract reports indoor PM2.5 as 22.4 μg/m³, but Figure 11 shows 24.2 μg/m³.

 

Thank you, it was a mistake, now it is corrected to 24.2 μg/m³.

 

The discussion on why outdoor concentrations are sometimes higher than indoor concentrations in certain households is not in-depth enough and should be analyzed further in conjunction with geographical location and ventilation conditions.

Figure 10 compares the maximum indoor and outdoor PM₁₀ concentrations recorded across Mexico City. The results indicate that Álvaro Obregón registered the highest outdoor PM₁₀ levels. In contrast, municipalities such as Azcapotzalco, Coyoacán, Cuauhtémoc, Milpa Alta (MA), and Tlalpan reported continuous indoor activities combined with poor ventilation, often with all windows closed, which resulted in substantially higher maximum indoor concentrations compared to outdoor measurements.

Coyoacán and Benito Juárez, located in the city center, recorded the lowest maximum PM₁₀ concentrations both indoors and outdoors. Conversely, Tlalpan, Tláhuac, and Venustiano Carranza, situated in the southern and eastern parts of the city, showed the highest PM₁₀ concentrations, likely influenced by a combination of outdoor sources (e.g., traffic, unpaved roads, soil erosion) and indoor sources (e.g., cooking, dust resuspension).

Overall, more than 70% of the sampled homes registered high indoor PM₁₀ levels. The lowest concentrations were found in Tlalpan, Coyoacán, Iztacalco (IZTAC), and Cuajimalpa, where residents spent less time indoors and reported fewer indoor activities in their logbooks. This finding highlights the strong influence of human activities and ventilation practices on indoor particulate matter levels, consistent with previous research on indoor–outdoor PM dynamics in urban environments [51-53].

The PM_2.5/PM₁₀ ratio results showed that dust resuspension dominates most days, primarily associated with unpaved roads with intense vehicular traffic, areas with eroded soils, and construction processes near houses.

The results indicated that 70% of the ratios were ≤ 0.40, 19% were 0.41–0.59, and 1% were ≥ 0.6, confirming that resuspension processes dominate most areas [54]. Significant activities impacting the PM_2.5/PM₁₀ ratio outdoors include woodworking or painting services, cement industries, paved and unpaved roads with high traffic, construction activities, and landfills.

The findings of this study are consistent with previously reported PM_2.5/PM₁₀ ratios: 0.5–0.9 across more than 60 European cities [55], 0.6–0.75 in Central Italy [56], 0.58 indoors and 0.49 outdoors in Nicosia, Cyprus [57], and 0.6–0.66 in Brazilian cities [58].

 

 

There is also a lack of discussion on sources of error, such as systematic bias in OPC at low concentrations.

We performed the validation of the OPC, and we found that it underestimated the PM2.5 at low concentrations, less than 5.0 µg/m³, but it has been shown that indoors, these concentrations are higher.

In 2.6% of the occasions, the OPC overestimated the concentration between 2.0 and 5.0 µg m^-3, and in 0.5% of the measurements with concentrations greater than 5 µg m^-3.

BAM measurements exhibited slightly higher mean and median values than the OPC. The frequency distribution of concentrations was similar, though the OPC had a higher percentage of lower concentrations. Specifically, 51–58% of OPC measurements were below 10.0 µg m⁻³, 29–31% were between 10.1 and 20.0 µg m⁻³, 3–6% were between 30.0 and 39.9 µg m⁻³, and less than 3% exceeded 40 µg m⁻³.

Figure 4 shows histograms of hourly measurements for BAM and OPC, and Figure 5 presents the histogram of differences between the two instruments. Analysis revealed that 56.6% of differences fell between −2.0 and 2.0 µg m⁻³, indicating good agreement. OPC overestimated concentrations by 2.0–5.0 µg m⁻³ in 2.6% of cases and by more than 5.0 µg m⁻³ in 0.5% of measurements. Underestimations were more frequent, with 33.4% of measurements between 2.0 – 5.0 µg m⁻³ and 6.9% exceeding 5.0 µg m⁻³.

 

The discussion of the policy implications of the results is also superficial. It is recommended that a comparative analysis of existing indoor air quality standards in Mexico City be added.

 

Although the 24-hour air quality standard was not exceeded, the inhabitants were exposed to very high short-term concentrations of PM_2.5. Acute exposure of this nature, even for short periods, has been linked to increased risks of respiratory symptoms, cardiovascular stress, and exacerbation of asthma [65-66]. This underscores the importance of considering not only compliance with daily or annual standards but also short-term peak events, which may disproportionately affect vulnerable populations such as children, older adults, and individuals with pre-existing health conditions [67].

Moreover, these findings raise important considerations for public health recommendations during air quality contingencies. Advisories encouraging residents to remain indoors may not always reduce exposure if indoor sources, such as smoking, cooking, or combustion-related accidents, generate concentrations exceeding those outdoors [68]. Thus, effective mitigation strategies should emphasize source control indoors, adequate ventilation, and the use of cleaner cooking and heating technologies.

 

Conclusion: In the absence of health data, the statement that 'PM1 particles account for 60% of PM2.5' (line 445) is insufficient to justify their inclusion in the standard. Please exercise caution when making policy recommendations.

 

Furthermore, the PM₁ fraction represented more than 60% of PM_2.5, suggesting that this fine fraction could be considered for inclusion in the National Ambient Air Quality Standards in Mexico.

Addressing indoor air pollution requires the active involvement of communities and individuals, supported by public education and behavior change initiatives. Understanding the sources of indoor pollutants is essential for developing effective control strategies. Engaging residents in reporting their household activities can help link behaviors with indoor air quality, promoting awareness and encouraging proactive measures. The collaborative use of OPCs can empower households to reduce exposure, thereby improving both individual and collective knowledge of indoor air pollution.

 

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

Dear authors,

Since almoust all suggestions have been implemented I am suggesting to accept your paper.

Best regards

Reviewer 4 Report

Comments and Suggestions for Authors

5. Conclusions->4. Conclusions