Number Concentration, Size Distribution, and Lung-Deposited Surface Area of Airborne Particles in Three Urban Areas of Colombia

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Dear Editor(s) and Authors,

please find my comments in the attached file.

Comments for author File: Comments.pdf

Author Response

Comments Reviewer #1

 

General Comments

 

While particle size distribution and LDSA measurements are very common in the so called developed countries (e.g., Europe, USA, Canada) they are sparse in South America, despite the increasing industrialization and urbanization, resulting in human exposure to potentially degraded air quality and to recognized health risk pollutants, like UFPs. The importance of this study is that it provides additional information on the size and number of airborne particles, going a step further than PM mass fraction measurements (i.e., PM10 and/or PM2.5) that are already conducted in the country. This can increase the awareness of the authorities and of the public leading to more detailed studies of air quality, identification of polluted areas and targeted pollution mitigation

strategies.

 

However, this study has one main limitation, related to the short term observations, which in the extreme case span over 4 days at one location. Therefore the findings of this study cannot be generalized, neither treated as representative at each location. They can be used for increasing the awareness in order to lead to further investigations in terms of both extended measuring periods and of additional instrumentation. The authors mention some of the limitations in their introduction but not clearly the limited measuring periods and the fact that their observations cannot be considered characteristic/indicative of each location. Despite this limitation, I suggest the publication of this paper to the journal of atmosphere after a major revision, recognizing the scope of this paper to pose a foundation for further and more detailed research.

 

We appreciate the reviewer’s comments and the recognition of our work as a foundation for fuerther studies. We have adjusted the manuscript in the sense the reviewer has suggested.

 

Specific major comments

 

1) Introduction (lines 115 118): This approach will not only provide a deeper understanding of the aerosol dynamics in urban and suburban areas and the impact of PM on human health, but also will establish a foundation for implementing more effective air quality monitoring and control strategies in the country. According to my opinion this sentence is misleading and should be rephrased.

 

We agree with the reviewer. We have edited the sentence accordingly, which. Now reads: “This study estimates, for the first time, PNSD, PNC, and LDSA in three cities in Colombia: Bogotá, Cali, and Palmira. Due to the availability and operation of the sampling device, observations were limited to a few days, especially in Cali, so the results of this study are indicative and not generalized to the cities. Nevertheless, this approach provides insights into a preliminary understanding of the aerosol dynamics in urban and suburban areas in Colombia and contributes to understanding potential health implications of PM exposure. We also emphasize that these results can increase the awareness of society and government leading to new research studies and the need to continuously monitoring PM number in addition to mass.”

 

In more details, for obtaining a deeper understanding on aerosol dynamics, the authors need more data, not only for longer periods of time, but also data related to different aerosol properties/characteristics combined with meteorological patterns, sources location and activity observations. This is not something that the current study can offer, due to the understandable limitations that the authors mention in the introduction (see also my comment #2 for more details on how to improve the discussion section).

We appreciate the reviewer’s comment regarding the need for more comprehensive data to deepen the understanding of aerosol dynamics. We fully agree that a longer monitoring period and the inclusion of additional aerosol properties would significantly enhance the analysis.

However, due to logistical and resource constraints, partially because of the COVID-19 pandemic, it was not feasible to extend the monitoring duration or to perform all measurements continually throughout the entire period. 

The campaign conducted in Cali, for example, was limited to a four-day period. Although relatively short, this timeframe was selected to provide an initial approximation of aerosol behavior in the city, and to offer a starting point for future, more extended studies.

We have clarified these limitations in the manuscript, which. Now reads: “Although the monitoring campaigns were conducted over a relatively short period, especially in Cali, the selected timeframe aimed to provide an initial approximation of aerosol dynamics in the cities. Due to logistical constraints, it was not possible to extend the monitoring duration or to conduct all measurements consistently across the entire period. The manuscript includes recommendations for future research on this topic.” The authors hope this exploratory study will serve as a foundation for more detailed investigations in subsequent work.

 

In a similar manner, in order to understand deeper the impact of PM on human health the authors should ideally correlate the measured size distributions together with the PM number and LDSA concentrations to actual health related data obtained contemporary with their measurements. Alternatively, the authors could try to relate the concentration levels of their observations (e.g., LDSA, UFP number concentrations) to existing literature medical data for specific impacts. The discussion in section 4.1 offers generic and well known information about the impacts of elevated UFP/LDSA concentration and the way that is now written makes this section more suitable for the introduction (see more details in my comment #3 below).

 

We agree with the reviewer that correlating LDSA and size distributions with health outcomes would greatly enhance the relevance of the study. However, due to the limited duration of the campaigns and lack of access to real-time health data for the same period, this analysis could not be performed within the scope of this work. Nonetheless, we have highlighted this as a recommended direction for future research.

 

The second part of the question was resolved and answered in comment number 3) Section 4.1.

 

Based on the above I suggest to rephrase the sentence in lines 115-118 emphasizing on the scope of this study, which is to pose a preliminary research, a foundation as the authors call it that will pave the way for more detailed research in the country. There is no need to mention something that their study (and data) cannot support (i.e., deeper understanding of aerosol dynamics and impacts on human health).

We thank the reviewer for this valuable suggestion. We agree that the sentence in lines 115–118 should be revised to better reflect the scope and limitations of our study. As recommended, we have rephrased the statement to emphasize that this work constitutes a preliminary investigation intended to serve as a foundation for more comprehensive research on aerosol dynamics in Colombia. 

The revised sentence now reads in Lines 130–135:

“This approach will provide insights into the aerosol dynamics in urban and suburban areas and contribute to understanding potential health implications of PM exposure. It is worth mentioning that this is the first time that this type of measurement has been conducted in the country, so several difficulties had to be overcome and resources optimized to achieve the results.”

We have also moved the general information about UFP and LDSA impacts on health to the introduction.

 

2) Discussion (section 4):

 

The discussion as it is written now contains some comparisons with other studies/observations and some speculation on the potential causes/factors that affect the UFP and LDSA concentrations in this study. As it is now written is quite difficult to follow. The discussion could benefit if:

 

1. i) The authors segregate, group and discuss in different paragraphs the comparisons with other studies/locations based on their main characteristics (e.g., urban traffic, background, industrial). This can be done for instance by grouping together all other studies conducted in urban traffic sites and compare with the observations conducted in the urban traffic site of this study. In a similar manner, the authors could select (or even add new) studies at different urban background locations and compare with their observations in the two urban background stations of Cali and San Cristobal.

 

The suggestion of the reviewer is very interesting and well-intended. We agree that grouping the sites by type could help compare our results with those from other studies. However, the classification of sites in the different studies is not so straightforward. In Latin American cities, for example, land use is usually mixed. Residential and industrial areas are not so well separated, and urban background sites may actually have a strong influence of road traffic and even industrial emissions. This precludes a neat comparison by site type.

 

1. ii) It can be beneficial for this discussion to select for comparison other studies from locations that have similarities to the measuring sites of this work. For instance the authors compare their findings in terms of UFP number concentrations in Palmira and Cali with studies from Los Condes (Chile) and from New Dehli (India), without mentioning which of the two cities is more similar in terms of population, traffic patterns, etc. Another example is the high LDSA concentration

observed in San Cristóbal, which is related with Barcelona, without further discussing any similarities or differences between the two cities (e.g., which city has more traffic, what is the average age of the car, bus, truck fleet in each city, if there is public transportation and how systematically is used by the dwellers, etc).

 

In the case of UFP, we have edited the sentence, which now reads: “Kumar et al. [54] reported UFPs concentrations ranging from 8,020 cm-³ in Los Condes (Chile) to an extreme 3 × 10⁵ cm-³ in New Delhi (India), and links the high levels to urban growth and expanding road traffic. Average UFPs levels in this study range between 7,800 in Bogotá - Las Ferias and 28,400 cm-3 in Cali. Bogota’s urban characteristics are similar to Santiago, which is reflected in UFPs levels as well as in annual average PM2.5 concentrations, namely 16 µg m-3 in Bogotá and 22 µg m-3 in Chile. Industrial and agro-industrial activities, which emit gases that can increase secondary particle formation, may explain the higher UFPs levels measured in Cali and Palmira.”

 

We have also rephrased the sentence about LDSA comparison, which now reads: “The high LDSA values observed in San Cristóbal (200 µm2/cm3) surpass those recorded in other urban areas worldwide by a large margin. Reche et al. [64] reported LDSA concentrations of 37 ± 26 µm2/cm3 in Barcelona, while Kuuluvainen et al. [65] observed values between 12 µm2/cm3 in park areas and up to 94 µm2/cm3 at traffic sites. Population density and annual average PM2.5 in Bogotá (16,000 inhab/km2 and 16 µg m-³) are similar to Barcelona’s (16,000 inhab/km2 and 17 µg m-³). The observed peaks in LDSA concentrations during working hours and the decline on weekends align with patterns reported in urban environments.      Fung et al. [62], for example, reported diurnal cycles with peak concentrations at the same hours, reinforcing the influence of traffic patterns on UFPs levels. Nevertheless, the unexpectedly high LDSA levels in San Cristóbal are worthy of further research. One important factor may be related to the fact that San Cristóbal site is located at the base of the Eastern hills of the city, an area with a higher density of vegetation. Biogenic emissions from this area might create condensation nuclei for UFPs formation.”

 

iii) Regarding the factors that may explain the observations of this study, I suggest a distinct paragraph in which the authors may refer to well known global observations, like for instance that near roads with intense traffic one will observe high concentrations of UFPs, while near agricultural or mining sites one will also observe elevated concentrations of coarse particles. For these claims the authors may use the literature that they already cite, but also some books related to air quality and atmospheric observations. In this paragraph it should be evident that based on the current measurements conducted by the authors one cannot be 100% sure that these are the true causes that affect the observable UFP and LDSA concentrations but here the authors may add to the discussion by mentioning which methods/instrumentation (in addition to long term measurements) may employ for supporting their arguments. For example, if the authors assume that

UFP concentrations in Bogotá, Palmira and Cali are driven by traffic, industrial emission and long range transport then they can discuss with which methods in a future work they could distinguish the importance and contribution of each source. This will deepen the discussion and for sure serve the cause of this publication to act as a foundation for further and more detailed surveys/studies.

 

We appreciate the reviewer’s insightful suggestion. We also acknowledge the limitations of our study in definitively attributing observed concentrations to specific sources, particularly given the short monitoring period and the absence of source apportionment techniques. Therefore, we have included a discussion of future approaches that could strengthen source attribution in follow-up studies. As suggested, we have added a new paragraph in the discussion section:

“Although our findings point to traffic-related emissions, agriculture and industrial activities as relevant contributors to the observed UFPs and LDSA concentrations, we acknowledge that, based on the short-term measurements, these attributions cannot be confirmed with certainty. Nevertheless, the spatial patterns observed, such as higher LDSA and UFPs levels near traffic corridors, are consistent with the evidence presented worldwide. To strengthen source attribution in future research, it would be valuable to incorporate observations for new particle formation from complementing devices in order to characterize physical and chemical characteristics of the aerosols. The inclusion of tracer species (e.g., black carbon for traffic, potassium for biomass burning, sulfates for secondary aerosols) could further improve spatial resolution. Integrating these approaches with long-term datasets would allow for a more robust understanding of the sources driving LDSA and UFPs exposure in urban environments like Bogotá, Cali, and Palmira.”

 

3) Section 4.1 Influence of size and LDSA Distribution on Health : The way that this section is now written presents the existing knowledge on the topic, without adding any significant or site specific new information. The authors can maintain most of this information but in this case this section suits better in the introduction. It would really improve this part of the discussion if the authors can use available literature from other locations for associating their observations with potential health effects. For instance from a quick literature search I found in the review of Zhang et al. (2024) studies associating long term exposure to UFPs with increased disease burden, which are reported together with the associated hazard ratios. In a similar manner, Bergmann et al. (2023) report mortality and hospitalization rates associated with UFP concentrations in Denmark. The authors perhaps can find more studies relating UFP and/or LDSA concentrations with hospitalization and/or mortality/morbidity rates and could use their findings in order to estimate qualitatively (or just compare) the health hazard for the locations they observed.

We thank the reviewer for this valuable comment and the constructive suggestions. We agree that the current version of the section primarily summarizes existing knowledge and lacks site-specific interpretation. In response, we have moved most of the general background information to the introduction, as suggested, and revised the discussion section to strengthen the connection between our observations and potential health implications.

Following the reviewer’s recommendation, we have incorporated references to relevant studies from the literature, including the work of Zhang et al. (2024) and Bergmann et al. (2023), which report hazard ratios and health outcomes associated with long-term exposure to UFPs. Additionally, we have included qualitative comparisons between the LDSA and UFP concentration levels observed in our study and those reported in peer-reviewedthe literature, to provide a broader context for the potential health risks in the sampled locations.

These changes aim to improve the scientific value of the discussion and align our findings more closely with established health impact assessments.

 

4) Conclusions (lines 541-544): This exploratory work identified various particle formation processes, which must be understood in order to control not only primary sources but also secondary formation processes. In this regard, the work should be complemented with other devices other than the ELPI+, such as the Scanning Mobility Particle Sizer (SMPS). I find quite misleading the phrase identified various particle formation processes , since the authors can only speculate about the origins and formation processes of the particles they measured. More specifically the technique/instrumentation that they used can measure only specific physical characteristics of the sampled aerosols (i.e., the particle size distribution) and based on that only, one cannot be sure about the origins and formation processes of the studied particles. This sentence needs rephrasing in order to be aligned with the work conducted. For example the authors may refer to the differences in the size distributions and number concentrations that they measured as well as to the

temporal variabilities that they observed at each site and emphasize on the fact that further research should include long-term measurements conducted with more than one aerosol instruments in order to characterize both the physical and the chemical properties of the aerosols at these locations in an attempt to identify the origins and evolution of the particles encountered and of the human exposure on those particles, as well as the associated potential health impacts. Following the same path of thinking, the SMPS alone cannot provide the necessary information for fully characterizing the aerosol over the study locations and for better understanding its dynamics. Perhaps the authors can be more generic here (i.e. in the conclusions section) and just mention that an array of instruments will be necessary in order to fully characterize the air quality, its drivers and the potential health impacts at the specific locations.

 

Specific minor comments

 

1) Introduction (line 69): Kalaiarasan et al. [14] observed that nucleation-mode particles dominated indoors It would be helpful for the reader if the authors mention the size range of the nucleation-mode particles. For example: Kalaiarasan et al. [14] observed that nucleation-mode particles (i.e., < X nm) dominated indoors

 

We thank the reviewer for this helpful suggestion. As recommended, we have revised the sentence in the introduction (line 69) to include the size range of nucleation-mode particles. It now reads: “Kalaiarasan et al. [14] observed that nucleation-mode particles (6–30 nm) dominated indoors.”

 

2) Introduction (lines 74-76): Leinonen et al. [15] found that particle size and concentration distribution changed depending on environmental and meteorological conditions, encompassing nucleation, Aitken, and accumulation modes. Similar as above, it would be helpful for the reader if the authors provide the size ranges of Aitken and accumulation mode particles.

 

We appreciate the reviewer’s suggestion. In response, we have updated the sentence in the introduction (lines 76–80) to include the particle size ranges for the Aitken and accumulation modes. The revised sentence now reads: “Leinonen et al. [15] found that particle size and concentration distributions varied depending on environmental and meteorological conditions, encompassing nucleation (<20 nm), Aitken (20–100 nm), and accumulation (>100 nm) modes, based on their geometric mean diameters.”

 

3) Introduction (lines 121-123): Although it would have been ideal, it wasn't possible to characterize PM simultaneously in all three cities, and not all measurements could be performed in all of them. The manuscript includes recommendations for future research. The authors in this sentence present one limitation of their research. However, they should also refer the limitation of short-term observations. In addition, they should raise the attention that perhaps their time-limited data set cannot be generalized, considered indicative of the observations at the study locations.

 

We thank the reviewer for this important observation. In response, we have revised the sentence in the introduction (lines 121–123) to explicitly acknowledge the limitation of the short-term monitoring period and its implications. The updated text now reads: “ This study estimates, for the first time, PNSD, PNC, and LDSA in three cities in Colombia: Bogotá, Cali, and Palmira. Due to the availability and operation of the sampling device, observations were limited to a few days, especially in Cali, so the results of this study are indicative and not generalized to the cities. Nevertheless, this approach provides insights into a preliminary understanding of the aerosol dynamics in urban and suburban areas in Colombia and contributes to understanding potential health implications of PM exposure. We also emphasize that these results can increase the awareness of society and government leading to new research studies and the need to continuously monitoring PM number in addition to mass.”

4) Section 2.2 (Table 2): This table is from the Dekati ELPI+ manual if I am not mistaken. If so, please correct the citation under Table 2 in order to properly cite it.

 

Thank you for your observation. You are right, the information presented in Table 2 was taken from the Dekati ELPI+ manual. We have revised the citation accordingly to properly credit the source under Table 2 in the revised manuscript.

 

5) Section 2.3: The authors provide in this section the equations used for calculating the LDSA based on the number size distribution measured by the ELPI+. If I am not mistaken, the authors employ the conversion factors (found in Table 2) that relate the measured current (I) of each ELPI+ stage for calculating the number concentration of particles (N) at the respective stage. Then by employing equation 2 and 3 calculate the surface area of the particles and by applying the alveolar deposition efficiency (n; see equation 1) they estimate the LDSA. While in principle this does not seem wrong, I have a couple of questions. The particle number concentration (N) at each stage of the ELPI+ is directly associated by the electrical current (I) measured at each stage (Lepistö et al., 2020): , where Q stands for the flow rate, e for the elementary charge, while Pn denotes the charger efficiency function. The latter, assuming spherical particles, depends on the particles mobility diameter (Järvinen et al., 2014). On the other hand, the midpoint cut-off point of each stage of the ELPI+ refers to aerodynamic diameter (Dia , as the authors correctly report). The relationship between the midpoint aerodynamic diameter of each ELPI+ stage and the mobility diameter of the particles charged and then deposited in that stage includes the particles effective density.

 

1. a) Which were the midpoint aerodynamic diameters of each stage? Table 2 shows only stage numbers (1 to 14) but without the cut-off points.

We thank the reviewer for this important observation. Following the suggestion, we have now added the midpoint aerodynamic diameters for each stage, along with the cut-off points, in the revised version of Table 2. This additional information provides a clearer understanding of the size ranges associated with each stage of the impactor.

1. b) Which effective density of the particles did the authors used? If they used the unit density, then they should mention it in this section.

Thank you for the suggestion. Regarding question (a): the Cutting Diameter (Di (µm)) has been added to Table 2 of the Conversion Vectors, along with the Aerodynamic Diameter used. These values are based on the Impactor Properties provided by the ELPI+ equipment manufacturer. Additionally, In response to question (b) the impactor properties, including a flow rate of 10 L/min, a density of 1 g/cm³, and a dilution factor of 1, were also considered.

 

Lepistö et al. (2020), provide conversion factors for calculating the LDSA at different regions of the human respiratory system (i.e., alveolar, tracheobronchial, upper airways) directly from the measured current of the ELPI+ device for particles of unit density, as well as of other particle effective densities (see Table S2 in the supplement in Lepistö et al., 2020). Perhaps the authors can perform a quick comparison between their estimated alveolar LDSA and the one derived when using the conversion factors found in Lepistö et al. (2020) assuming unit density. They can also directly use conversion factors (i.e., to convert current at each stage to LDSA) assuming different

densities in order to perform a sensitivity analysis for the alveolar LDSA. I am not suggesting that they should follow the above, but it is just an idea that can have a positive impact to the paper. Especially since the authors speculate about the chemical composition of the particles they sampled (e.g., dust at coarse particles, carbonaceous emissions for the fine ones, etc).

 

Thank you for your suggestion and for providing the bibliographic reference. We have added, in the supplementary material, the LDSA graphs calculated using our methodology for the different deposition profiles: ET1 (anterior nasal passage), ET2 (posterior nasal passage, pharynx, and larynx), BB (bronchial), bb (bronchiolar), and AI (alveolar–interstitial). Additionally, we performed calculations following the methodology proposed by Lepistö et al. (2020), which directly applies conversion factors (i.e., to convert the current at each stage into LDSA), to highlight the main differences between the approaches.

 

6) Based on the collected data, did the authors observed any new particle formation event? If yes, then I believe that this (or these) event(s) should be reported and analyzed individually.

 

Thanks for this suggestion. We are not certain about having observed new particle formation events, because of the resolution limitations of the measurement instrument. Future studies will need complementary techniques to unambiguously measure new particle formation events, such as SMPS instruments.

 

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The study contains an assessment of the amount and dynamics of dust pollution in the atmosphere of several cities in Colombia. The work demonstrates data obtained by a new method using an electric low-pressure impactor (ELPI+). In general, the work contains interesting data that can be used as reference materials for further more detailed and extensive studies. But the work requires corrections:
1. Throughout the work, there is an unclear symbol denoting the concentration of dust particles. Please correct this. Check the applicability of units of measurement for all indicators and bring them to international standards.
2. The introduction is written quite well. I would recommend adding some experience in assessing the cyto- and genotoxicity of dust of different dimensions so that your work is designed for a larger audience and problem.
3. In some places, designate references as: [21-25]. Line 53, 102 and other.

4. I consider the main problem of the work to be the small number of days of observations and their fragmentation in time. Since your study is very limited in the time of sampling from the air, I suggest adding a section on the limitations of the study that could affect the results of the work. Obviously, there is not enough data to discuss the daily, weekly and other dynamics of dust pollution. When comparing studies conducted at different times, one should also be careful in judgments. Since dust pollution of agglomerations is a very dynamic object of study in time and space.
5. For what reason were different heights of dust study chosen? Different heights for study give completely different results, there are recommendations that determine the height of the sensor at 10 m to exclude surface turbulence. Obviously, it is necessary to add the height of the dust sensor in all cases. And this fact should be written down in the limitations.
6. In Figure 1, it is necessary to add a coordinate grid. Figure 1 should have an increased resolution.
7. When interpreting the reasons for the ratio of different fractions, it should be remembered that they have different transport capabilities, which increase from the coarse to the ultrafine fraction. Coarse fractions indicate a local source. This should be borne in mind when discussing the results.
8. For clarity, it is better to present data from one city in adjacent columns of the diagram (for example, in Figure 2).
9. Are the data averaged over several days or other options presented in Figures 3 and 9? Please clarify this.
10. What correlation was used (Spearman, Pearson?). Was the data checked for normality beforehand? This should be added to Section 2.
11. There is no information on how the meteorological data were obtained. What equipment? This should be added to Section 2. It is also necessary to add the measurement errors of the ELPI+ device.
12. In the conclusions, you refer to previous studies of dust in Colombia carried out using other methods. I suggest comparing this data with your results and discussing this.

The work requires additions and corrections before revision. Good luck to the authors!

Author Response

Comments Reviewer #2

 

The study contains an assessment of the amount and dynamics of dust pollution in the atmosphere of several cities in Colombia. The work demonstrates data obtained by a new method using an electric low-pressure impactor (ELPI+). In general, the work contains interesting data that can be used as reference materials for further more detailed and extensive studies. But the work requires corrections:

 

1. Throughout the work, there is an unclear symbol denoting the concentration of dust particles. Please correct this. Check the applicability of units of measurement for all indicators and bring them to international standards.

 

We have removed the symbol #, as suggested by the reviewer. Particle concentration are now expressed in cm^-3 units.

 

2. The introduction is written quite well. I would recommend adding some experience in assessing the cyto- and genotoxicity of dust of different dimensions so that your work is designed for a larger audience and problem.

 

Thank you very much for your positive evaluation of the introduction and for your valuable suggestion. In response, we have incorporated a new paragraph that discusses recent research addressing the cytotoxicity and genotoxicity of particulate matter of different dimensions. Specifically, the paragraph highlights findings from Faruqui et al. (2024), Yan et al. (2023), and Moreno-Ríos (2022), which demonstrate the effects of PM_2.5 and ultrafine particles on human alveolar epithelial cells. The main mechanisms identified include oxidative stress, apoptosis, inflammatory responses, DNA damage, and potential neurotoxicity associated with particle exposure. 

 

3. In some places, designate references as: [21-25]. Line 53, 102 and other.

 

We thank the reviewer for the observation. The suggested formatting of reference ranges (e.g., [21–25]) has been applied throughout the manuscript, including lines 53, 102, and other relevant locations.

 

4. I consider the main problem of the work to be the small number of days of observations and their fragmentation in time. Since your study is very limited in the time of sampling from the air, I suggest adding a section on the limitations of the study that could affect the results of the work. Obviously, there is not enough data to discuss the daily, weekly and other dynamics of dust pollution. When comparing studies conducted at different times, one should also be careful in judgments. Since dust pollution of agglomerations is a very dynamic object of study in time and space.

We thank the reviewer for highlighting this important aspect. We fully agree that the limited duration and temporal fragmentation of the monitoring campaigns represent a significant limitation of our study. As explained in our response to the first reviewer, logistical and resource constraints, partially exacerbated by the COVID-19 pandemic, restricted our ability to extend the monitoring periods or to ensure continuous, long-term sampling. 

The campaign conducted in Cali, for example, was limited to a four-day period. Although relatively short, this timeframe was selected to provide an initial approximation of aerosol behavior in the city, and to offer a starting point for future, more extended studies.

 

We recognize that the limited temporal coverage does not allow for a comprehensive analysis of daily, weekly, or seasonal variability in PM_2.5 concentrations. Consequently, we have added in the manuscript outlining these limitations. In particular, we note that comparisons between different campaigns must be interpreted cautiously, given the dynamic nature of dust pollution in urban environments, both spatially and temporally.

We have clarified these limitations in the manuscript as: “Although the monitoring campaigns were conducted over a relatively short period, especially in Cali, the selected timeframe aimed to provide an initial approximation of aerosol dynamics in the cities. Due to logistical constraints, it was not possible to extend the monitoring duration or to conduct all measurements consistently across the entire period. The manuscript includes recommendations for future research on this topic.” The authors hope this exploratory study will serve as a foundation for more detailed investigations in subsequent work.

 

5. For what reason were different heights of dust study chosen? Different heights for study give completely different results, there are recommendations that determine the height of the sensor at 10 m to exclude surface turbulence. Obviously, it is necessary to add the height of the dust sensor in all cases. And this fact should be written down in the limitations.

 

We thank the reviewer for this important observation regarding the sensor heights. We have clarified in the manuscript the specific heights at which the dust sensors were installed in each city. 

We fully agree that sensor height can influence measured concentrations due to effects such as surface turbulence and vertical variability in particle distribution. As the reviewer correctly points out, standard guidelines recommend positioning sensors at around 10 meters to minimize surface effects. However, the different heights used in our study were determined primarily by logistical and security constraints specific to each monitoring site, such as the availability of secure structures for instrument installation.

We have updated the methodology section to include this information and have explicitly noted in the limitations section that variations in sensor height may introduce variability when comparing results between locations. We appreciate the reviewer’s insight, which has helped us improve the transparency and robustness of the study.

 

6. In Figure 1, it is necessary to add a coordinate grid. Figure 1 should have an increased resolution.

 

We appreciate the reviewer’s suggestion. In response, we have added a coordinate grid to Figure 1 and increased its resolution to improve clarity and readability.

 

7. When interpreting the reasons for the ratio of different fractions, it should be remembered that they have different transport capabilities, which increase from the coarse to the ultrafine fraction. Coarse fractions indicate a local source. This should be borne in mind when discussing the results.

 

8. For clarity, it is better to present data from one city in adjacent columns of the diagram (for example, in Figure 2).

 

We thank the reviewer for this helpful suggestion. Figure 2 has been reorganized so that the data from each city are now presented in adjacent columns, improving clarity and comparison across sites.

 

9. Are the data averaged over several days or other options presented in Figures 3 and 9? Please clarify this.

 

We thank the reviewer for the observation. The data presented in Figures 3 and 9 represent average values over the monitoring days for each site. To clarify this, we have updated the x-axis label from 'hourly' to 'diel cycle' to better reflect the temporal averaging across a 24-hour period. 

 

10. What correlation was used (Spearman, Pearson?). Was the data checked for normality beforehand? This should be added to Section 2.

 

Thank you for your question. The question was answered and added to Section 2.2 as “Additionally, the normal distribution of the data was calculated with the Shapiro-Wilk test to indicate whether the distribution of the data is nonparametric (NIST, 2012). Also, The Spearman correlation coefficient was selected due to the data distribution, to assess the relationship between meteorological parameters and PNCs.”

 

11. There is no information on how the meteorological data were obtained. What equipment? This should be added to Section 2. It is also necessary to add the measurement errors of the ELPI+ device.

 

We appreciate the reviewer’s insightful comment. In response, we have expanded Section 2 to provide additional details regarding the source and handling of the meteorological data. The revised text now reads as follows:

"Meteorological data for Bogotá were obtained from the official Bogotá air quality monitoring network, which systematically records atmospheric variables relevant to air quality and meteorological assessments. For the municipality of Palmira, meteorological measurements were sourced from the Universidad Nacional de Colombia, specifically from a monitoring site established and operated by the institution, where data collection began approximately one year prior to the start of the study period. In the case of Cali, meteorological data were provided by the Sistema de Vigilancia de la Calidad del Aire de Cali, managed by the Departamento Administrativo de Gestión del Medio Ambiente (DAGMA). Since these data are not publicly available, a formal request was submitted. In response, the data corresponding to a single monitoring station, operated by the Universidad del Valle (Univalle), were made available and subsequently used for the analysis. The data are processed in hourly averages according to the monitoring periods of each campaign for subsequent correlation analysis."

Furthermore, we have clarified that meteorological data were obtained from established monitoring networks that utilize standard equipment for environmental monitoring, such as automatic weather stations equipped, although the specific models and calibration information were not disclosed by the respective institutions.

In response to the error comment, we have added information regarding the evaluation of the ELPI+ measurement performance. The added information read: “At the beginning of the campaigns in Bogotá, the ELPI+ device was compared against a reference Scanning Mobility Particle Sizer (SMPS) to assess measurement uncertainty. The comparison indicated that the ELPI+ tends to overestimate particle number concentrations (PNC) when Stage 1 is included, while better agreement was observed when excluding it. Specifically, the relative root mean square error (rms) between the PNC measured by the ELPI+ (excluding Stage 1) and the SMPS was 414.3 cm^-3.”

Unfortunately, for subsequent campaigns in Palmira and Cali, it was not possible to perform similar intercomparisons due to the unavailability of a reference SMPS instrument during the measurement periods.

 

12. In the conclusions, you refer to previous studies of dust in Colombia carried out using other methods. I suggest comparing this data with your results and discussing this.

 

The work requires additions and corrections before revision. Good luck to the authors!

 

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The authors studied particulate concentration in Colombia is paper because few data about PM concentration in Columbia. It is important to recognize the pollution situation for understanding the health effect of particulate. However, some information may not be clear. The reviewer requests that the authors add or revise the following information for publication.

1. Does Columbia have any environmental standard(s) or guideline(s) related to particulate matter? If yes, please show us it (them) in the manuscript and compare your results with the standard(s). It is useful to understand the pollution situation of Columbia.
2. Line 117-118: The authors write “…but also will establish a foundation for implementing more effective air quality monitoring and control strategies in the country.” The reviewer didn’t find any information in this manuscript about the above description. Can the authors add some information?
3. Table 1: Monitoring period at Cali is different from other cities. Is it reasonable to compare the data of Cali with the data of other cities? Please add some explanation.
4. Table 1 and Line 228-229: The authors wrote “This similarity in concentration values suggests a contribution from a common source, mobile and stationary sources.”, and Palmira is an industrial zone and San Cristobal is a background zone. Why are the values almost the same?
5. Figure 2: UFP in Cali is the highest although Cali is an urban background zone. Why is the value highest? The authors must make the definition of zone classification clear.
6. Figure 3: Please make clear how to draw the solid lines. Is it an average value of each-day measurement?
7. Line 353-355: The authors explain the relationship between particles and meteorological variables (MVs). The reviewer can’t understand why the authors say the relationship between CP and MVs are weaker than the relationship between FP and UFPs, and MVs. Figure 7 shows some MVs have the stronger relationship with CP. The authors have to describe the results carefully.
8. Page 11: The authors discussed the LDSA distribution with aurodynamic diameter, although they show the measurement results as UFP, FP and CP. The readers may be confused with the description of the results based on diameter. The reviewer recommends the authors to add the discussion on the 3-categorical results briefly.
9. Line 396-397 and Figure 9: The authors showed the higher peak in the morning. The reviewer wonders why the peak in the afternoon or evening is lower than in the morning. Is traffic not related to commuting?
10. Discussion: The authors mentioned the potential risks of the elevated UFP. The reviewer agrees with the authors qualitatively. However, this study was conducted based on quantitative measurements. The authors have to mention the risk and/or measurement results quantitatively. Are there any reference values such as NOAEL in Columbia? If yes, the authors have to compare your results with some reference value. If no, the authors have to show the reasons why your results should be useful for quantitative discussion. Also, please review the entire discussion.

Author Response

Comments Reviewer #3

 

The authors studied particulate concentration in Colombia is paper because few data about PM concentration in Columbia. It is important to recognize the pollution situation for understanding the health effect of particulate. However, some information may not be clear. The reviewer requests that the authors add or revise the following information for publication.

 

Does Columbia have any environmental standard(s) or guideline(s) related to particulate matter? If yes, please show us it (them) in the manuscript and compare your results with the standard(s). It is useful to understand the pollution situation of Columbia.

 

We thank the reviewer for this valuable suggestion. In response, Colombia has established environmental air quality standards for criteria pollutants. The 24-hour average limit for PM_2.5 is set at 50 µg/m³, and the annual average limit is 25 µg/m³.

However, we would like to highlight that, currently, Colombia does not have specific standards or guidelines for ultrafine particles (UFP; particles with aerodynamic diameters below 100 nm), which are the primary focus of our study through the measurement of Lung-Deposited Surface Area (LDSA). Therefore, while PM_2.5 mass concentration comparisons are useful for contextualizing general air quality, they do not fully capture the health-related implications associated with exposure to UFP, which this study aims to address.

We appreciate the reviewer’s comment, which helped us improve the clarity and completeness of our manuscript.

 

Line 117-118: The authors write “…but also will establish a foundation for implementing more effective air quality monitoring and control strategies in the country.” The reviewer didn’t find any information in this manuscript about the above description. Can the authors add some information?

 

We appreciate the reviewer’s observation. We have revised the sentence to better reflect the purpose of the manuscript. The intention of the study is not to serve as a foundation for implementing air quality control strategies, but rather to contribute to the understanding of aerosol dynamics and their potential health implications in urban and suburban environments. Accordingly, the sentence has been modified to: “This approach will provide insights into the aerosol dynamics in urban and suburban areas and contribute to understanding potential health implications of PM exposure.”

 

Table 1: Monitoring period at Cali is different from other cities. Is it reasonable to compare the data of Cali with the data of other cities? Please add some explanation.

 

We appreciate the reviewer’s observation regarding the differences in monitoring periods between Cali and the other cities. We agree that the temporal and even geographical  mismatch could limit direct comparability of the datasets.

However, the objective of our study is not to conduct a direct comparative analysis between the cities, but rather to provide an individual description of the particle characteristics observed in each location during the respective monitoring periods. Each city’s data is treated independently, focusing on the site-specific conditions and temporal context.

We have added a clarification in the manuscript to explicitly state that comparisons across cities are limited, and that the study aims primarily to describe and characterize the particle metrics observed during each campaign.

The revised sentence now read as: “This section presents the descriptive results for PNC and PSD for the three cities (Bogotá, Palmira, and Cali), along with the influence of meteorological parameters. It is important to note that the monitoring periods for each city were different; therefore, the data are presented independently for each site, and direct comparisons between cities are limited”

We thank the reviewer for highlighting the need to better frame this point in the manuscript.

 

Table 1 and Line 228-229: The authors wrote “This similarity in concentration values suggests a contribution from a common source, mobile and stationary sources.”, and Palmira is an industrial zone and San Cristobal is a background zone. Why are the values almost the same?

 

We thank the reviewer for this important observation. In response, we have reworded the relevant paragraph to better reflect the variability among the sites and to avoid suggesting that the FP concentrations were identical across different urban contexts.

Specifically, we now describe the FP concentrations as exhibiting "moderate variability" rather than "similarity," and we acknowledge that while the values fall within a relatively narrow range, differences in emission profiles between the sites (e.g., industrial activities in Palmira versus urban background conditions in San Cristóbal) are expected.

This revision has been incorporated into the manuscript to more accurately characterize the findings and to reflect the potential influence of different local sources on FP levels. We thank the reviewer for helping us improve the clarity and precision of the interpretation.

 

Figure 2: UFP in Cali is the highest although Cali is an urban background zone. Why is the value highest? The authors must make the definition of zone classification clear.

 

We thank the reviewer for this valuable observation. In response, we clarify that the zone classification for each monitoring site, including Cali, was assigned by the respective environmental authority and was not determined independently by the authors.

Although the site in Cali is officially classified as an urban background zone, the immediate surroundings include major avenues, areas with parked vehicles, and nearby industrial activities, which may contribute to the elevated UFP concentrations observed.

We have updated the manuscript to make this distinction clearer, noting that while the official classification reflects a broader urban planning category, local conditions can significantly influence aerosol characteristics.

We appreciate the reviewer’s comment, which allowed us to improve the transparency and contextualization of the study.

 

Figure 3: Please make clear how to draw the solid lines. Is it an average value of each-day measurement?

 

We thank the reviewer for the comment. The solid lines in Figure 3 represent the average values calculated for each hour of the day, based on all available daily measurements during the sampling period. We have made this explicit in the figure caption to avoid ambiguity.

 

Line 353-355: The authors explain the relationship between particles and meteorological variables (MVs). The reviewer can’t understand why the authors say the relationship between CP and MVs are weaker than the relationship between FP and UFPs, and MVs. Figure 7 shows some MVs have the stronger relationship with CP. The authors have to describe the results carefully.

 

We thank the reviewer for pointing out this inconsistency. Upon revisiting the results, we agree that the original statement did not accurately reflect the correlations observed between coarse particles (CP) and certain meteorological variables (MVs), particularly in Palmira. We have revised the paragraph accordingly to clarify that, although CPs generally show weaker correlations in some sites, in Palmira, strong correlations were indeed observed between CP and temperature (−0.74), relative humidity (0.78), and wind speed (0.57). The revised text now presents a more careful and site-specific interpretation of the results.

Page 11: The authors discussed the LDSA distribution with aurodynamic diameter, although they show the measurement results as UFP, FP and CP. The readers may be confused with the description of the results based on diameter. The reviewer recommends the authors to add the discussion on the 3-categorical results briefly.

 

We thank the reviewer for this helpful observation. To address the potential confusion regarding the LDSA distribution by aerodynamic diameter versus particle categories, we have added a paragraph in the discussion that explicitly summarizes the results using the three commonly used size classes: UFP, FP, and CP. The updated paragraph clarifies that, across all cities, LDSA was primarily dominated by particles in the fine mode, with contributions ranging from 67.5% to 90.2%, followed by UFPs and CPs. This addition helps bridge the interpretation between diameter-based results and categorical classification, as suggested.

 

Line 396-397 and Figure 9: The authors showed the higher peak in the morning. The reviewer wonders why the peak in the afternoon or evening is lower than in the morning. Is traffic not related to commuting?

 

We thank the reviewer for the insightful question. In response, we have clarified in the manuscript that both morning and evening rush hours influence FP patterns, as reflected in the observed peaks.

However, the morning peaks tend to be higher than those in the evening, which is consistent with previous studies and can be attributed to several factors. These include cooler atmospheric conditions and lower boundary layer heights in the morning, which enhance pollutant accumulation near the surface, and a more intense and simultaneous traffic demand during the start of the working day.

We have incorporated this explanation into the manuscript to better address the reviewer’s comment and to enhance the interpretation of the diurnal concentration profiles.

 

Discussion: The authors mentioned the potential risks of the elevated UFP. The reviewer agrees with the authors qualitatively. However, this study was conducted based on quantitative measurements. The authors have to mention the risk and/or measurement results quantitatively. Are there any reference values such as NOAEL in Columbia? If yes, the authors have to compare your results with some reference value. If no, the authors have to show the reasons why your results should be useful for quantitative discussion. Also, please review the entire discussion.

 

We sincerely thank the reviewer for this important comment. We agree that strengthening the quantitative interpretation of potential risks associated with UFP exposure improves the manuscript.

Specifically, we clarify that Colombia currently does not have established reference values such as NOAELs or specific regulatory thresholds for ultrafine particles (UFPs). National air quality standards focus on criteria pollutants (PM_2.5, PM₁₀, etc.) and are based on mass concentrations, not particle number concentration (PNC) or lung-deposited surface area (LDSA).

To address this limitation, we contextualized our findings using international studies. For example, epidemiological studies have associated short-term health effects, including increased COPD mortality and asthma hospitalizations, with UFP concentrations exceeding 5000 particles/cm³. In our study, measured UFP concentrations frequently reached or exceeded this threshold across monitoring sites.

Additionally, we discuss the relevance of LDSA measurements, highlighting that elevated LDSA values—particularly in traffic-impacted areas—could increase pulmonary and systemic health risks through mechanisms such as oxidative stress and inflammation, as supported by recent toxicological studies. LDSA values recorded in our campaigns (20–80 µm²/cm³) fall within ranges associated with increased health risk in the literature.

We have thoroughly reviewed and revised the discussion to integrate these quantitative links, offering a more robust scientific interpretation even in the absence of national standards. We thank the reviewer for encouraging us to strengthen this important aspect of the manuscript.

 

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript has been improved substantially and my comments were adequately answered.

Reviewer 2 Report

Comments and Suggestions for Authors

The article looks much better in its current form. The authors have done a great job and taken into account all the comments of the reviewer. I believe that the article can be accepted in this form.

Perhaps there is a need to add several references to studies of different dust sources and their toxicity, which will probably differ due to the different fractional composition of the produced dust and their toxicity. In your case, you are more likely to receive an integral indicator from all sources. But this recommendation is solely at the discretion of the authors.