Perturbations of Aerosol Radiative Forcing on the Planetary Boundary Layer Thermal Dynamics in a Central China Megacity

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This study focuses on a megacity in China’s Central Plains and investigates the impact of aerosol radiative forcing on the thermodynamic and dynamic structure of the planetary boundary layer (PBL). Key meteorological variables—including wind speed, wind direction, temperature, and relative humidity—were analyzed across the 1000 to 800 hPa pressure levels by comparing ERA5 reanalysis data with multi-source ground-based observations. It was found that ERA5 performs well in simulating wind direction, while moderate consistency was observed for wind speed and temperature, with temperature discrepancies decreasing with altitude. This suggests enhanced thermal stability and vertical inhomogeneity in the lower PBL due to aerosol loading. Additionally, nighttime warming near the surface and cooling above 800 hPa were identified, and a positive correlation between the thermal dynamic (HD) index and PM₂.₅ concentration was observed. These findings further clarify the mechanisms of aerosol–PBL interactions and provide a scientific basis for applying reanalysis data over complex urban terrains.

 

The study addresses an important topic and is generally well designed. However, the results are preliminary, and the data presentation and analysis need improvement. More detailed methodology and stronger interpretation are required. Specific suggestions for revision are listed below:

 

1. The full meaning of “HD index” should be clearly defined upon its first appearance.

 

2. Given that the Zhengzhou station is located in the southwestern part of the main urban area, it is worth clarifying whether it is representative of the boundary layer structure across the entire city or the broader Central Plains urban agglomeration. Has the potential influence of the urban heat island effect or local topographic disturbances been considered?

 

3. This paper mainly takes Zhengzhou as the representative of the megacities in the Central Plains region, but it does not fully explain whether the observational data of this site (34.75°N, 113.62°E) can be generalized to the entire Central Plains urban agglomeration. It is suggested to supplement the similarities and differences between Zhengzhou and other core cities in the Central Plains (such as Luoyang and Kaifeng) in terms of aerosol emission characteristics (such as the proportion of industrial sources, PM₂.₅ composition), terrain and climatic conditions, and clarify the spatial representativeness of single-point observations.

 

 

4. The observation period spans from October to November 2024. The authors are encouraged to justify the choice of this time frame—does it adequately represent the typical boundary layer structure? Could there be seasonal biases?

 

5. There is a noticeable discrepancy in the temporal resolution among the datasets: 10-minute intervals for CFL-06L, sub-minute resolution for MP-3000A, and hourly data for ERA5. How were these data-sets temporally aligned? Which resampling or matching strategy was employed?

 

6. The use of cubic spline interpolation for matching ERA5 and lidar data warrants further justification. Was it validated as the most suitable method for this context? Have the authors compared its performance with linear or other interpolation techniques, particularly in terms of error characteristics at lower and upper altitudes?

 

7. The order of the references cited in the text is incorrect. For instance, [31, 32] are followed directly by [34, 35].

 

8. The titles of Figures 3 and 4 are exactly the same ("Wind rose diagrams comparing observed and ERA5-reanalyzed mean wind speeds across 16 directions at different pressure levels"), which leads to a problem of duplicate labeling and fails to distinguish the specific differences between the two figures.

 

9. There is inconsistency in the capitalization of some terms, such as 'planetary boundary layer (PBL)', which is sometimes written as 'Planetary Boundary Layer' and sometimes as 'planetary boundary layer' after its first appearance, lacking a uniform capitalization standard.

Author Response

1.The full meaning of “HD index” should be clearly defined upon its first appearance.

Thanks for the comment. I have added the definition of HD index in LINES 368-370 of the INTRODUCTION: “the Heating and surface Dimming Index (HD Index) - to assess the coupling strength between aerosols and the PBL.”

 

2.Given that the Zhengzhou station is located in the southwestern part of the main urban area, it is worth clarifying whether it is representative of the boundary layer structure across the entire city or the broader Central Plains urban agglomeration. Has the potential influence of the urban heat island effect or local topographic disturbances been considered?

 

Thank you for the valuable comment. The Zhengzhou station is a national basic meteorological observatory, whose site selection follows strict criteria aimed at ensuring the representativeness of the urban environment. It is located in the southwestern part of the main urban area but remains broadly representative of the city's boundary layer characteristics. This is because Zhengzhou lies in the Central Plains, with relatively flat terrain and no significant topographic obstructions nearby.

 

As for the potential influence of the urban heat island (UHI) effect, we acknowledge that UHI can indeed alter the boundary layer structures. However, this study specifically focuses on the perturbation of aerosol radiative forcing on the planetary boundary layer. The influence of UHI is beyond the scope of the current work and is not the primary factor considered in our analysis.

 

To clarify the spatial representativeness of the observational site, we have added a brief discussion on the differences among Zhengzhou and its neighboring cities, Luoyang and Kaifeng, in LINES 127-129 of the revised manuscript. This addition helps contextualize why Zhengzhou serves as a suitable representative megacity for this study. The revised text begins with: “Zhengzhou, as a representative megacity in the Central Plains, provides an ideal setting for exploring thermodynamic disturbances in the urban boundary layer through high-resolution observational data.”

 

3.This paper mainly takes Zhengzhou as the representative of the megacities in the Central Plains region, but it does not fully explain whether the observational data of this site (34.75°N, 113.62°E) can be generalized to the entire Central Plains urban agglomeration. It is suggested to supplement the similarities and differences between Zhengzhou and other core cities in the Central Plains (such as Luoyang and Kaifeng) in terms of aerosol emission characteristics (such as the proportion of industrial sources, PM₂.₅ composition), terrain and climatic conditions, and clarify the spatial representativeness of single-point observations.

 

Thank you for your thoughtful comment. We acknowledge the importance of clarifying the spatial representativeness of Zhengzhou as a representative megacity in the Central Plains urban agglomeration.

 

Zhengzhou, Luoyang, and Kaifeng all lie within the temperate monsoon climate zone; however, their geographical and emission characteristics differ. Zhengzhou is situated in the central plains with relatively flat terrain and minimal topographic disturbance, making it suitable for investigating the thermodynamic structure of the boundary layer. In contrast, Luoyang is adjacent to the Qinling Mountains to the west and surrounded by several hills and low mountains (e.g., Mang mountains, Song mountains, and Daimei Mountains), which exert significant topographic influences on local atmospheric circulation and boundary layer development. Therefore, Luoyang’s boundary layer dynamics are less comparable to those of Zhengzhou.

 

Kaifeng, although geographically closer to Zhengzhou and also located on the plains, has a smaller population and fewer industrial activities. As a result, its overall anthropogenic aerosol emissions, especially from industrial sources, are relatively lower than those of Zhengzhou.

 

Given Zhengzhou’s central location, relatively flat terrain, and substantial urban and industrial development, we consider it a suitable representative of Central Plains megacities for investigating aerosol–boundary layer interactions. To clarify the spatial representativeness of our observational site, we have added a brief comparison of regional city characteristics in LINES 146–149 of the revised manuscript: “Zhengzhou is densely populated and industrialized; Luoyang, located to the west, is characterized by more complex and mountainous terrain; while Kaifeng, to the east, lies on the flat Huang-Huai Plain but has a smaller population and lower level of industrial activity.”

Figure 1. Geographic locations and topographic features of Zhengzhou, Luoyang, and Kaifeng based on digital elevation model (DEM) data.

 

4.The observation period spans from October to November 2024. The authors are encouraged to justify the choice of this time frame—does it adequately represent the typical boundary layer structure? Could there be seasonal biases？

 

Thank you for your insightful comment. We have carefully considered the rationale behind the selection of the observation period from October to November 2024.

This period corresponds to late autumn and early winter, which is a seasonally sensitive window in the Central Plains region. During this time, meteorological conditions are conducive to the accumulation of aerosols, and haze episodes frequently occur due to weak atmospheric dispersion and a shallow boundary layer. These features provide a valuable opportunity to examine the perturbations of boundary layer thermal-dynamics under intensive aerosol loading.

 

In contrast, spring in this region is often influenced by dust storms, which involve different aerosol compositions and dynamic processes. Summer is characterized by frequent precipitation, which suppresses aerosol accumulation and makes persistent haze events less likely.

 

Therefore, the October–November period was selected as the most appropriate window to capture typical pollution-induced boundary layer disturbances under relatively stable meteorological conditions.

 

5.There is a noticeable discrepancy in the temporal resolution among the datasets: 10-minute intervals for CFL-06L, sub-minute resolution for MP-3000A, and hourly data for ERA5. How were these data-sets temporally aligned? Which resampling or matching strategy was employed?

 

Thank you for pointing this out. We acknowledge the temporal resolution differences among the various datasets used in this study and have taken appropriate steps to ensure temporal alignment for consistent analysis.

 

To address the discrepancy, we used a unified time base to synchronize all datasets. The high-frequency data from the MP-3000A microwave radiometer (with a sub-minute resolution, typically ~30 seconds) were first aggregated to 10-minute means to match the native temporal resolution of the CFL-06L wind profile radar. This step reduces high-frequency noise while retaining meaningful atmospheric variability within the boundary layer.

 

For the ERA5 reanalysis data, which are available at hourly intervals, we performed a temporal downscaling through linear interpolation to obtain values at 10-minute resolution. While this does not introduce new variability, it ensures time consistency when comparing or merging with the observational datasets. This interpolation is appropriate given the relatively smooth temporal evolution of large-scale ERA5 fields.

 

After these adjustments, all datasets were re-indexed to a common 10-minute temporal grid. This approach ensures temporal comparability across instruments while minimizing distortions to the original physical signals.

 

In addition, we note that ERA5 provides meteorological variables on isobaric surfaces, whereas the microwave radiometer and wind profiler radar use altitude-based vertical coordinates. Therefore, we applied appropriate vertical interpolation and coordinate conversion techniques to enable consistent spatial comparison.

 

A brief discussion of these data alignment procedures has been added to LINES 265-268 of the revised manuscript, starting with: “In actual analysis, on the one hand, interpolation and screening methods are firstly adopted to align different data in time. On the other hand, ERA5 provides wind field data with the isobaric surface as the vertical coordinate, while liDAR and micro-wave radiometer use height as the reference coordinate.”

 

6.The use of cubic spline interpolation for matching ERA5 and lidar data warrants further justification. Was it validated as the most suitable method for this context? Have the authors compared its performance with linear or other interpolation techniques, particularly in terms of error characteristics at lower and upper altitudes?

 

Thank you for this valuable comment. We fully agree that the choice of interpolation method can significantly influence the accuracy of vertical matching between datasets with differing resolutions, such as ERA5 reanalysis and lidar observations.

 

In our study, we employed cubic spline interpolation to align the ERA5 vertical profiles with the observation levels of the lidar. This choice was based on two main considerations. First, cubic spline interpolation offers a smooth and continuous approximation that minimizes curvature between nodes, which is beneficial for preserving the vertical structure of atmospheric variables (e.g., temperature, potential temperature) in stable boundary layers. This is particularly important for identifying inversion layers and assessing vertical gradients that define the planetary boundary layer.

 

Second, we conducted sensitivity tests comparing cubic spline interpolation with both linear and piecewise quadratic methods. While the differences in the mid-troposphere were generally small, cubic spline interpolation produced lower biases in the upper levels (above 2 km) and avoided artificial discontinuities near strong inversion layers in the lower troposphere. These features are crucial for our study, which focuses on the thermodynamic structure of the boundary layer.

 

Moreover, our approach is consistent with recent studies that performed vertical collocation between reanalysis datasets and ground-based remote sensing measurements using similar interpolation techniques (e.g., Wei et al., 2025; Cheynet et al., 2025; Wei et al., 2024). These works have demonstrated the effectiveness of cubic spline interpolation for preserving the physical continuity and minimizing interpolation errors, especially in complex terrain or heterogeneous vertical structures.

 

To support our methodological choice, we conducted pre-experiments comparing multiple interpolation schemes, including linear and piecewise methods. Based on both empirical performance and literature precedent, cubic spline interpolation was selected as the optimal method for this study [40,41].

 

A corresponding discussion and the two references have been added in LINES 319-321 of the revised manuscript, beginning with: “Through literature reference and pre-experiments with different interpolation methods, the optimal interpolation method was determined to be cubic spline interpolation [40,41].”

 

7.The order of the references cited in the text is incorrect. For instance, [31, 32] are followed directly by [34, 35].

 

We are sorry for this careless mistake. We have carefully rechecked and revised the citation order throughout the manuscript to ensure that all references now appear in correct numerical sequence and correspond accurately to the reference list.

 

8.The titles of Figures 3 and 4 are exactly the same ("Wind rose diagrams comparing observed and ERA5-reanalyzed mean wind speeds across 16 directions at different pressure levels"), which leads to a problem of duplicate labeling and fails to distinguish the specific differences between the two figures.

 

Thank you for the comment. You are absolutely right—this was an oversight on our part. The original figure captions for Figures 3 and 4 were indeed identical, which caused confusion regarding their distinct purposes. In the revised manuscript, we have corrected the captions to clearly reflect the specific content of each figure: Figure 3 now refers to wind rose diagrams (vector wind distribution), while Figure 4 presents directional scatter density plots. These revisions clarify the differences in visualization and highlight the complementary roles of the two figures in illustrating wind characteristics at different pressure levels.

 

The updated figure captions have been revised in LINES 422-423, 425-426 of the manuscript as follows:

 

“Figure 3. (a–e) Wind rose diagrams showing the frequency distribution of observed and ERA5 wind directions at different pressure levels (975-800 hPa).”

“Figure 4. Scatter density plots of 16 wind direction sectors comparing ERA5 and observations at different pressure levels (975–800 hPa).”

 

9.There is inconsistency in the capitalization of some terms, such as 'planetary boundary layer (PBL)', which is sometimes written as 'Planetary Boundary Layer' and sometimes as 'planetary boundary layer' after its first appearance, lacking a uniform capitalization standard.

 

Thank you for pointing this out. We have now thoroughly reviewed the manuscript to ensure that scientific terms are treated consistently. Specifically, we have adopted the standard academic convention: the full term “Planetary Boundary Layer (PBL)” is used upon first mention, and the abbreviation “PBL” is used in subsequent instances.

 

In addition, we have carefully checked the manuscript to ensure that capitalization follows standard usage rules. Inconsistent capitalization has been corrected, and non-proper nouns are no longer unnecessarily capitalized.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

This paper attempts to characterize aerosol atmospheric energy rerlationships in the atmospheric boundary layer. There is virtually no quantitative information about the urban aerosols used in the calculations.  The authors need to include PM2.5 mass or other concentration data (as a function of month--mean and max-min) to capture seasonal variation, and how these data were translated into optical properties.  Aerosols vary in their energy scattering or absorption properties depending on size and composition.  Unless these are specified by data or assumed the calculations and interpretation are ambiguous.  The assumption about aerosol concentration with height also needs to be stated since it is widely known that the concentration profile is non-uniform with height.  The spatial distribution aloft also ndeds to be discussed following the resolution of the ERA-5 model.

The ERA 5 model yields meteorological data on 30 x 30 grids. It's unclear if this includes the entire city or rural conditions in the surroundings.  The aerosol PM concentrations derive from only a single site--A comment about their representativeness is needed.

Until aerosol details are added or assumptions made about PM2.5 data applications, this paper must be considered incomplete

Author Response

 

1.This paper attempts to characterize aerosol atmospheric energy relationships in the atmospheric boundary layer. There is virtually no quantitative information about the urban aerosols used in the calculations. The authors need to include PM2.5 mass or other concentration data (as a function of month--mean and max-min) to capture seasonal variation, and how these data were translated into optical properties. Aerosols vary in their energy scattering or absorption properties depending on size and composition. Unless these are specified by data or assumed the calculations and interpretation are ambiguous. The assumption about aerosol concentration with height also needs to be stated since it is widely known that the concentration profile is non-uniform with height. The spatial distribution aloft also ndeds to be discussed following the resolution of the ERA-5 model.

 

Thank you for your valuable comment. We fully acknowledge the importance of including quantitative aerosol information, such as PM₂.₅ mass concentrations and optical properties, for a more precise interpretation of aerosol–boundary layer interactions.

 

Due to observational constraints during the study period, only surface-level PM₂.₅ data from national air quality monitoring stations in Zhengzhou were available. These data are now briefly described in the revised manuscript (Section 2.2.3), and while limited, they help contextualize the aerosol loading during the October–November 2024 period. However, detailed aerosol chemical composition, size distribution, or vertical profile data were not available, and no further measurements could be added retrospectively. Therefore, our analysis was designed to be exploratory in nature, focusing on the dynamic and thermodynamic signatures of aerosol effects as reflected in observation–reanalysis discrepancies, rather than on deriving radiative forcing magnitudes or energy budgets.

 

The corresponding text has been added in LINES 580-583 of the revised manuscript as follows:“During the study period, the monthly average PM₂.₅ concentration was 57.96 μg/m³ (based on daily values), with a maximum of 175 μg/m³ and a minimum of 9 μg/m³, indicating several distinct pollution episodes.”

 

To approximate the influence of aerosols on boundary layer structure, we followed a common practice in prior studies by assuming an exponential decay of aerosol concentration with altitude—a simplification often applied in data-sparse environments (e.g., Dang et al., 2019; Su et al., 2020). While this assumption may not capture all vertical variations, it provides a first-order framework to understand potential aerosol-induced perturbations. We have added a note in the revised manuscript to clarify this assumption and its limitations.

 

The primary objective of our study is to highlight the observable impacts of aerosols on PBL structure, using existing remote sensing and reanalysis datasets, and to propose diagnostic indices (e.g., the HD Index) that can be used in similar contexts. We believe this approach still provides meaningful insight into aerosol–PBL coupling, especially in regions where vertical aerosol measurements are scarce.

 

2.The ERA 5 model yields meteorological data on 30 x 30 grids. It's unclear if this includes the entire city or rural conditions in the surroundings. The aerosol PM concentrations derive from only a single site--A comment about their representativeness is needed.

 

Thank you for this important comment. We fully agree that the spatial representativeness of both ERA5 meteorological data and the ground-based aerosol measurements is an essential consideration.

 

Regarding the ERA5 data, the reanalysis is provided at a horizontal resolution of 0.25° x 0.25° (approximately 30 x 30 km), which indeed covers both urban and surrounding peri-urban/rural areas. In the case of Zhengzhou, this spatial coverage encompasses the main urban core as well as adjacent suburban zones. As noted in previous studies (e.g., Zhang et al., 2020), ERA5 grid cells over large cities tend to be dominated by the synoptic-scale background but still respond to regional-scale urban effects, especially under stagnant conditions when boundary layer processes are most relevant. We have clarified this coverage in the revised manuscript (Section 2.3).

 

As for the aerosol data, it is true that PM₂.₅ concentrations were obtained from a single national control site. However, this station is part of China’s standardized National Air Quality Monitoring Network and was selected based on strict siting criteria to represent the broader urban environment, minimizing interference from local point sources. Prior studies in Central Chinese megacities (e.g., Miao et al., 2019; Li et al., 2017) have shown that during pollution episodes, spatial variability of PM₂.₅ concentrations within a city is relatively low due to widespread atmospheric stability and pollutant accumulation. Therefore, while we acknowledge the limitation of single-site data, we believe the measurements are reasonably representative of urban aerosol conditions within the ERA5 grid cell during the study period. A note has been added in the revised manuscript to clarify this point.

 

Specifically, we have included the following clarification in LINES 235-240 of the manuscript:“The selected dataset in the experiment is sufficient to cover the cities and surrounding villages within the study area. ERA5 features a horizontal resolution of 0.25° × 0.25°, corresponding to approximately 30 km × 30 km at midlatitudes; through spatial interpolation, it effectively represents the meteorological conditions of nearby towns and villages. It also offers a temporal resolution of 1 hour and includes 41 pressure levels spanning from 1000 hPa to 1 hPa.”

 

3.Until aerosol details are added or assumptions made about PM2.5 data applications, this paper must be considered incomplete

 

Thank you for your important and critical comment. We fully understand your concern regarding the necessity of providing aerosol detail or clearly stated assumptions for the application of PM₂.₅ data.

 

The core objective of this study is to investigate the thermodynamic and dynamic perturbations of the planetary boundary layer (PBL) under high aerosol loading conditions, rather than to quantitatively model aerosol radiative forcing or retrieve aerosol optical properties. Given the data limitations during the observational period, detailed chemical speciation or size-resolved aerosol measurements were not available. As such, we have explicitly adopted and clarified in the revised manuscript a set of commonly used assumptions to support our analysis:

 

Surface PM₂.₅ mass concentration is treated as an indicator of aerosol loading, supported by its high correlation with thermodynamic disturbance indices (e.g., the HD Index);

 

An exponential decay profile with height is assumed for aerosol vertical distribution, consistent with standard practice in prior studies (e.g., Dang et al., 2019; Su et al., 2020), especially under stable stratification;

 

While a more detailed treatment of aerosol optical parameters would certainly strengthen the paper, we believe that the current framework still enables meaningful insights into aerosol–PBL interactions and complements existing literature on reanalysis evaluation in polluted environments.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The revised manuscript was a little improved in light of the former reviewer’s advice, seem to be okay. However, this paper may be accepted by the current journal on condition that the English should be corrected through the manuscript, for example, most of sentences using the active voice should be changed into the ones using the passive voice, the manuscript in the current form is not like a scientific paper, seem to be a typical style of Chinese-English description. It's very hard to read this revised paper for the readership in a traditional English.

Comments on the Quality of English Language

The manuscript in the current form is not like a scientific paper, seem to be a typical style of Chinese-English description. It's very hard to read this revised paper for the readership in a traditional English.

Author Response

1.This paper may be accepted by the current journal on condition that the English should be corrected through the manuscript, for example, most of sentences using the active voice should be changed into the ones using the passive voice, the manuscript in the current form is not like a scientific paper, seem to be a typical style of Chinese-English description. It's very hard to read this revised paper for the readership in a traditional English.

Thank you for your valuable suggestions on the article. We acknowledge the concern regarding the English writing style, particularly the excessive use of active voice and the overall readability of the manuscript. We sincerely apologize that we did not pay sufficient attention to the issue of voice usage in the previous version.

 

We sincerely apologize for the inconvenience caused by the current language presentation. In response, we have undertaken a comprehensive revision of the manuscript to improve its clarity, grammar, and conformity with scientific writing conventions. Specifically, we have revised many sentences from active to passive voice and refined expressions to enhance fluency and academic tone.

 

For example:

1. Lines 24-28:
   Original: “Focusing on a megacity in China’s Central Plains, this study examines the effects of aerosol–PBL interactions by comparing ERA5 reanalysis data with multi-source ground-based observations.”
   Revised: “In this study, the effects of aerosol–PBL interactions were examined over a megacity in China’s Central Plains by comparing ERA5 reanalysis data with multi-source ground-based observations. Key meteorological variables—including wind speed, wind direction, temperature, and relative humidity—were analyzed across pressure levels from 1000 to 800 hPa.”
2. Lines 328-331:
   Original: “This method accounts for actual variations in observed temperature and humidity profiles by incorporating virtual temperature into the hydrostatic balance equation.”
   Revised: “In this method, actual variations in observed temperature and humidity profiles are accounted for by incorporating virtual temperature into the hydrostatic balance equation.”
3. Lines 471-474:
   Original: “The scatter density plots reveal distinct clusters in the west-northwesterly to northwesterly (WNW–NW) and southerly (S–SSW) directions, suggesting greater diversity in upper-level wind patterns.”
   Revised: “In the scatter density plots, distinct clusters are observed in the west-northwesterly to northwesterly (WNW–NW) and southerly (S–SSW) sectors, indicating increased diversity in upper-level wind patterns.”

All revisions have been marked in red text in the manuscript for the reviewer’s convenience. Given the extensive number of changes, we have not enumerated each modification individually. In addition, we are in the process of completing a full language polish to ensure the manuscript meets the standards of professional scientific English. We sincerely appreciate the reviewer’s valuable comments, which have greatly contributed to improving the quality of our work.

Reviewer 2 Report

Comments and Suggestions for Authors

Modifications ard satisfactory.  Unfortunatelyt there are minimal aerosol data for improving the study.

 

Author Response

1.Unfortunately, there are minimal aerosol data for improving the study.

 

Thank you for your valuable comment. We fully acknowledge the importance of incorporating more comprehensive aerosol data—including vertical profiles, optical depth, and chemical composition—to improve the interpretation of aerosol–boundary layer (PBL) interactions.

 

Unfortunately, due to observational constraints during the study period, only surface-level PM_2.5 concentration data from national air quality monitoring stations in Zhengzhou were available. No vertically resolved aerosol measurements (e.g., lidar, aircraft, or satellite-derived profiles) or speciation data were collected concurrently, and retrospective acquisition was not feasible.

 

We have now clarified this limitation in the revised manuscript. In particular, a sentence has been added in the Discussion and Conclusion section (lines 662–663):

 

“However, a limitation of this study is the lack of vertically resolved aerosol observations to directly constrain aerosol–PBL interactions.”

 

Additionally, surface PM_2.5 statistics have been summarized in the revised Section 2.2.3 (lines 580–583):

 

“During the study period, the monthly average PM₂.₅ concentration was 57.96 μg/m³ (based on daily values), with a maximum of 175 μg/m³ and a minimum of 9 μg/m³, indicating several distinct pollution episodes.”

 

To approximate the vertical aerosol distribution, we adopted a widely used assumption of exponential decay with altitude, as is common in data-scarce regions. While this simplification cannot fully capture vertical heterogeneity, it offers a useful first-order estimate to support our diagnosis of aerosol-induced boundary layer perturbations. We have now noted this assumption and its limitations in the revised text.

 

Our primary aim is to explore the physical signals of aerosol radiative forcing as reflected in thermodynamic discrepancies between ERA5 reanalysis and remote-sensing observations, rather than to quantify detailed aerosol radiative budgets. Nonetheless, we agree that vertically resolved aerosol observations would greatly strengthen the analysis. Therefore, we plan to incorporate lidar, satellite retrievals, and high-resolution model simulations in future work to enhance the robustness and generalizability of our findings.

Author Response File: Author Response.docx

Round 3

Reviewer 1 Report

Comments and Suggestions for Authors

The 2^nd revised manuscript has been addressed by point-to-point and partially vague responses and was greatly improved and may be accepted by the journal of Sustainability in the current form.