Analysis and Characterization of the Behavior of Air Pollutants and Their Relationship with Climate Variability in the Main Industrial Zones of Hidalgo State, México

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The current study examines the behavior of air pollutants and their relationship with climate variability in the industrial zones of Hidalgo State, Mexico, from 2016 to 2023. The study focuses on six pollutants (PM10, PM2.5, SO2, NO2, O3, and CO) and climate variables (precipitation, temperature, and evaporation) across six regions with industrial parks. ​

Key findings:

1. Pollutant Behavior: Zones 2 and 3 are the most polluted, with annual averages exceeding Mexican and WHO limits for PM10, PM2.5, and NO2. ​ Zone 2 recorded over 1,000 days exceeding PM10 limits, 96 days for PM2.5, and 11 days for SO2. Pollutant concentrations were highest in spring and winter and lowest in summer and autumn, correlating inversely with precipitation. ​
2. Climate Variables: Precipitation showed a negative trend across all zones, indicating future reductions, which could hinder pollutant dispersion. ​ Maximum and average temperatures showed positive trends, suggesting future increases, while minimum temperatures showed mixed trends. ​ Evaporation increased in some zones and decreased in others. ​
3. Correlations: Precipitation negatively correlated with all pollutants, while maximum temperature and evaporation showed positive correlations with PM10, PM2.5, and O3. Minimum temperature negatively correlated with PM10, PM2.5, NO2, and CO. ​
4. Health Impacts: High pollutant concentrations, especially in Zone 2, pose significant health risks, including respiratory and cardiovascular diseases, mental health issues, and increased mortality. ​
5. Industrial Impact: The high pollution levels in Zones 2 and 3 are linked to industrial activities, including the operation of a thermal power station and a refinery, which contribute to 90% of Hidalgo's atmospheric emissions. ​ Efforts to reduce fuel oil consumption have led to decreases in SO2 and CO levels, but other pollutants remain high. ​
6. Future Trends: Pollutant concentrations are expected to decrease in some zones, possibly due to compliance with regulations. ​ However, climate changes, such as reduced precipitation and increased temperatures, may exacerbate pollution levels.

 

Comments

1. Though well written, the studies English needs to be edited a bit more for extra clarity, because at times it is hard to follow what the authors are trying to convey.
2. Though the authors utilize an impressive amount of longitudinal data, their use of only correlations makes it hard to draw any definite conclusions on what is happening in their study area. I would therefore suggest that the authors reframe this paper as an examination of the long-term trends in the study area.
3. In addition, in my opinion I do not think that the authors can prove that the industrial parks are the sole sources of the pollutants that they are measuring. I would therefore reframe the study as saying that they used sensors adjacent to industrial parks and tone down the language as regards the industrial parks being the main sources of pollution, especially given the proximity of the study area to Mexico City.
4. Furthermore, given that the study area is rather small, I would urge the authors to justify why they present climate variable trends for each zone. Is it possible that climate variable trends would differ between the zones? And if that is the case, why would this be observed- is influenced by the region’s topography for example?
5. For Figure 3, I would suggest that the authors modify this graph to have individual bars for each of the pollutants.
6. In the Discussion, Lines 403-424 are an exact repeat of Lines 374-395. These lines have to be deleted and the paragraphs are re-written accordingly.

Comments on the Quality of English Language

Please see my main comments above.

Author Response

Comments Reviewer 1

Thank you for highlighting the main contributions of our research. Below, we respond to each of your comments. The modifications made to our manuscript are available in track changes format, highlighted in red. Likewise, this document responds to each of your comments.

Comments

1. Though well written, the studies English needs to be edited a bit more for extra clarity, because at times it is hard to follow what the authors are trying to convey.

Response 1: Thank you for your comments. We have reviewed the entire manuscript and made corrections to clarify the ideas.

2. Though the authors utilize an impressive amount of longitudinal data, their use of only correlations makes it hard to draw any definite conclusions on what is happening in their study area. I would therefore suggest that the authors reframe this paper as an examination of the long-term trends in the study area.

Response 2: Thank you for your suggestions. We have revised the wording in the manuscript to clarify our proposal and avoid confusion. However, our work not only provides long-term trend analysis but also characterizes the behavior of various pollutants and climatic variables, as well as their relationships.

3. In addition, in my opinion I do not think that the authors can prove that the industrial parks are the sole sources of the pollutants that they are measuring. I would therefore reframe the study as saying that they used sensors adjacent to industrial parks and tone down the language as regards the industrial parks being the main sources of pollution, especially given the proximity of the study area to Mexico City.

Response 3: Thank you very much for your comment. We have revised the document's wording to incorporate the reviewer's suggestions. Consequently, we discuss that industrial parks are not the only sources of atmospheric pollutants. This information can be found in lines 421-428.

4. Furthermore, given that the study area is rather small, I would urge the authors to justify why they present climate variable trends for each zone. Is it possible that climate variable trends would differ between the zones? And if that is the case, why would this be observed- is influenced by the region’s topography for example?

Response 4: Thank you very much for your comment. Regarding the size of the study area, it is not as small as it seemed. The maximum distance between stations can reach 100 kilometers, prompting the proposal of six small analysis areas. Likewise, each pollutant station has at least one nearby weather station that helps to describe the behavior of climatic variables. Moreover, we decided to obtain as much information as possible, since regional climate can vary due to factors such as topography, proximity to urban centers, atmospheric conditions, among others. Therefore, it is essential to note that the stations are located at altitudes ranging from 2,000 to 2,800 meters above sea level. This change in terrain meant we could not assume that the climates of each small area were the same, which justifies the number of weather stations proposed for each area. To illustrate this situation, a column indicating the elevation of each weather station was added to Table B1 in the appendices (line 528), as well as a sentence indicating the altitude of the study area was added to its description (lines 118-120).

5. For Figure 3, I would suggest that the authors modify this graph to have individual bars for each of the pollutants.

Response 5: Thank you very much for your suggestion. We have modified Figure 3 as suggested. This change can be seen in line 280.

6. In the Discussion, Lines 403-424 are an exact repeat of Lines 374-395. These lines have to be deleted and the paragraphs are re-written accordingly.

Response 6: Thank you for your correction. We have removed the duplicate text and carefully read through the manuscript to avoid such errors.

 

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

This work collects air pollutant concentration data from various sites in Mexico, aiming to investigate the variation of pollutants and to assess local air quality in six different industrial zones. It also attempts to use meteorological observations to explore the climatic effects of these variables. While the objective of this study is valuable, the work fails to achieve its stated goal. I have several concerns regarding both the presentation and the validity of the conclusions. My specific comments are as follows:

1. The abstract is not precise. Firstly, SO₂ is generally not considered a greenhouse gas; I suggest the authors replace the expression ‘greenhouse gases’ with ‘air pollutants’ . Secondly, the conclusion is questionable. A simple correlation coefficient is insufficient to claim that the presence of pollutants alters climatic conditions. Although the general idea is recognized in the scientific community, it would be more appropriate to state that air pollutants are influenced by meteorological factors (e.g., precipitation leads to wet deposition, which reduces aerosol concentrations).
2. Although the authors introduce a substantial amount of climate change background, much of it is not directly related to the study. Instead, the introduction should include more references to previous research on how meteorological factors affect the distribution of air pollutants, or conversely, how air pollutants can influence climate.
3. Line 109, please clarify what “98.2 O” refers to.
4. The discussion of pollutant behavior is questionable. For example, the authors state that PM10 in Zones 2 and 3 tends to increase; however, such a conclusion requires appropriate trend fitting. From the statistics in Table 3, Zone 5 also shows an increasing tendency. Moreover, the changing rates for Zones 2 and 3 do not pass the 95% confidence level, making such conclusions inappropriate. Similar issues appear elsewhere, for instance, the claim that ‘zones with the lowest average concentrations were Zones 1, 4, and 6’ does not hold true for all years.
5. Line 228–229. Why are there gaps in PM2.5 for some zones? In particular, Zone 2, which shows the highest PM10 in most years, has many missing PM2.5 data points. This significantly weakens the study.
6. Line 231: This conclusion cannot be drawn from the presented results.
7. Line 235 and Figure 2(d). Why does the NOM limit (gray dashed line) not correspond to 0.02 ppm?
8. Lines 236–237. It is interesting that Zone 5 shows a sharp decrease in ozone. Is there any possible explanation for this phenomenon?
9. The discussion of Figure 3 is also questionable. Given the substantial missing PM2.5 data, how can the conclusions about exceedance days be justified?
10. Lines 269–277. Why is Zone 5 not discussed in this section? As noted, the pollutant variations in Zone 5 are distinct.
11. Lines 281–282. This conclusion is inconsistent with the discussion in the previous section.
12. Tables 3 and 4. The Z-values and Sen’s slopes appear to be incorrect. The Sen’s slope for Zone 6 (mentioned in the discussion) is missing in both tables. Please carefully check all table values. Also, it should read ‘Zone 3,’ ‘Zone 4,’ etc., rather than ‘Zona 3,’ ‘Zona 4’.
13. Figure 5. The presentation format differs from previous figures. Why was the subplot arrangement changed from “variable-based” to “zone-based”? The analytical approach does not seem to justify this change.
14. Figure 6. The figure resolution is low and difficult to interpret. In addition, the number of decimal places is inconsistent throughout the manuscript. I recommend improving the figure resolution, enlarging the fonts, and ensuring consistency in decimal formatting.
15. Lines 377–395 and 404–425. These two passages are nearly identical. The authors should carefully revise the manuscript to eliminate repetitive discussion.
16. Lines 514–515. This conclusion is not supported by the results presented in this study.
17. Table B1. Please ensure that the number of decimal digits is consistent across all values.

Author Response

Comments Reviewer 2

Thank you for your feedback; it has significantly enhanced our manuscript. The modifications made to our manuscript are available in track changes format, highlighted in red. Likewise, this document responds to each of your comments.

Comments:

1. The abstract is not precise. Firstly, SO₂ is generally not considered a greenhouse gas; I suggest the authors replace the expression ‘greenhouse gases’ with ‘air pollutants’ . Secondly, the conclusion is questionable. A simple correlation coefficient is insufficient to claim that the presence of pollutants alters climatic conditions. Although the general idea is recognized in the scientific community, it would be more appropriate to state that air pollutants are influenced by meteorological factors (e.g., precipitation leads to wet deposition, which reduces aerosol concentrations).

Response 1: Thank you for your suggestions. We have modified the abstract by changing the word 'greenhouse gases' to 'air pollutants'. Furthermore, the conclusion has been modified as suggested. These modifications are found on lines 16-34.

2. Although the authors introduce a substantial amount of climate change background, much of it is not directly related to the study. Instead, the introduction should include more references to previous research on how meteorological factors affect the distribution of air pollutants, or conversely, how air pollutants can influence climate.

Response 2: Thank you for your comment. A paragraph describing how climate change can affect air pollutant concentrations has been added to the introduction. This modification can be found in lines 61-69.

Recent changes in local and regional climates have been identified as potentially degrading air quality through altered wind patterns (ventilation and dispersion), temperature, and precipitation [17,18,20]. Moreover, the occurrence of extreme events, potentiated by regional climate change, such as more frequent and prolonged drought and increased temperatures, can directly affect air pollutant concentrations [23]. Similarly, the combination of changing weather patterns and altered atmospheric chemistry can promote the formation and accumulation of atmospheric air pollutants, resulting in a phenomenon known as the climate penalty [24-26]

3. Line 109, please clarify what “98.2 O” refers to.

Response 3: Thank you very much for your correction. We have changed the nomenclature to correctly define the coordinate. The modification is on line 116.

4. The discussion of pollutant behavior is questionable. For example, the authors state that PM10 in Zones 2 and 3 tends to increase; however, such a conclusion requires appropriate trend fitting. From the statistics in Table 3, Zone 5 also shows an increasing tendency. Moreover, the changing rates for Zones 2 and 3 do not pass the 95% confidence level, making such conclusions inappropriate. Similar issues appear elsewhere, for instance, the claim that ‘zones with the lowest average concentrations were Zones 1, 4, and 6’ does not hold true for all years.

Response 4: Thank you very much for your suggestions. We have modified the wording of the results to clarify the behavior of the annual averages. These modifications can be seen in lines 230-238.

5. Line 228–229. Why are there gaps in PM2.5 for some zones? In particular, Zone 2, which shows the highest PM10 in most years, has many missing PM2.5 data points. This significantly weakens the study.

Response 5: Thank you for your comment. We understand your point of view. However, the information was taken from the official Mexican website for monitoring pollutants. This website does not specify the reason for the missing data in the time series for this pollutant. It could be due to an error in the measurements or sensors, or because the concentration of this pollutant has not been recorded. This situation was highlighted in lines 478-482 and as future work (lines 509-511).

6. Line 231: This conclusion cannot be drawn from the presented results.

Response 6: Thank you very much for your suggestions. We have modified the wording of the line mentioned, replacing it with the following paragraph located in lines 241-243.

Meanwhile, for SO₂ (Figure 2c), Zone 2 had the highest values (>0.006 ppm), whereas Zone 4 had the lowest values in more than 60% of the years.

7. Line 235 and Figure 2(d). Why does the NOM limit (gray dashed line) not correspond to 0.02 ppm?

Response 7: Thank you very much for your comment. We have modified the information as you mentioned. The actual value is 0.021 and not 0.020 as shown in the text. You can see this change in line 247.

8. Lines 236–237. It is interesting that Zone 5 shows a sharp decrease in ozone. Is there any possible explanation for this phenomenon?

Response 8: Thank you very much for your suggestions. The reduction in tropospheric O₃ may be due to the reduction in NO₂ present in the same area (Figure 2d). This situation arises because tropospheric ozone (O₃) concentrations depend on photochemical reactions with certain precursor pollutants, such as nitrogen oxides (NO₂ and NO).

In our document, we highlight a possible relationship between NO₂ and O₃ pollutants, in which reductions in O₃ coincide with reductions in NO₂, starting in 2020. This information can be found in lines 249-251 and 409-413.

9. The discussion of Figure 3 is also questionable. Given the substantial missing PM2.5 data, how can the conclusions about exceedance days be justified?

Response 9: Thank you very much for your comment. We understand your point of view. However, Figure 3 describes the number of days in the time series that exceed the NOM limits. This data could increase if we had the complete series, but even with the gaps, many days with this behavior are shown.

10. Lines 269–277. Why is Zone 5 not discussed in this section? As noted, the pollutant variations in Zone 5 are distinct.

Response 10: Thank you very much for your comment. We have added information about Zone 5 in lines 291-292.

Finally, Zone 5 showed the lowest PM_2.5 level in autumn across all time series, around 10 μg/?³.

11. Lines 281–282. This conclusion is inconsistent with the discussion in the previous section.

Response 11: Thank you very much for your observation. We have modified the text in the previous lines referring to trends to avoid any confusion. You can see this in lines 296-298.

12. Tables 3 and 4. The Z-values and Sen’s slopes appear to be incorrect. The Sen’s slope for Zone 6 (mentioned in the discussion) is missing in both tables. Please carefully check all table values. Also, it should read ‘Zone 3,’ ‘Zone 4,’ etc., rather than ‘Zona 3,’ ‘Zona 4’.

Response 12: Thank you very much for your comment. We have corrected the errors in Tables 3 and 4 by adding missing information and correcting incorrect wording. You can see these changes in lines 313 and 351.

13. Figure 5. The presentation format differs from previous figures. Why was the subplot arrangement changed from “variable-based” to “zone-based”? The analytical approach does not seem to justify this change.

Response 13: Thank you very much for your observation. In the field of atmospheric sciences, to understand the behavior of the climate in each location, it is necessary to describe the time-series averages (a minimum of 30 years). The graph combining this information is known as a climogram. The WMO recommends this approach for defining a location's characteristics, which is why we have chosen to present the information in this manner [43]. If we modified the graph, we would have comparisons of the variables for each zone, which is not what we want to highlight in Figure 5.

14. Figure 6. The figure resolution is low and difficult to interpret. In addition, the number of decimal places is inconsistent throughout the manuscript. I recommend improving the figure resolution, enlarging the fonts, and ensuring consistency in decimal formatting.

Response 14: Thank you very much for your suggestions. Figure 6 has been modified as you suggested. Moreover, the decimal format has been standardized in the figure and text. You can see this modification in line 381.

15. Lines 377–395 and 404–425. These two passages are nearly identical. The authors should carefully revise the manuscript to eliminate repetitive discussion.

Response 15: Thank you very much for your correction. We have removed the duplicate text and carefully reviewed the manuscript to avoid such errors in the future.

16. Lines 514–515. This conclusion is not supported by the results presented in this study.

Response 16: Thank you very much for your comment. We have revised these lines to avoid inconsistencies with our results. The modification can be found in lines 505 and 508.

17. Table B1. Please ensure that the number of decimal digits is consistent across all values.

Response 17: Thank you very much for your suggestions. We have standardized the number of decimal places across the entire table. This modification is observed in line 528.

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

I have no further comments for the authors. Thank you for addressing my concerns.

Reviewer 2 Report

Comments and Suggestions for Authors

My concerns have been addressed in this revised version, and I believe the manuscript can be accepted.