the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 04 Apr 2025
Distinct aerosol populations and their vertical gradients in central Amazonia revealed by optical properties and cluster analysis
Abstract. In central Amazonia, aerosol sources, weather, and chemical processes create a highly variable aerosol population. The aerosols' optical properties, shaped by composition and size, determine sunlight interaction and the regional radiation budget. Previous studies observed differences in the particles' physical properties during smoke events and described their vertical gradients during clean periods. However, a complete characterization of these properties at two height levels considering both seasons is still missing. This study connects aerosol optical measurements from the Amazon Tall Tower Observatory (ATTO), at 60 and 325 m heights, to particle composition and sources, characterizing different aerosol populations, assessing their vertical gradients, and associating them with the influence of various emission sources and atmospheric processes. A seasonally segregated clustering method was applied to five years of optical data (2018–2023), allowing for the identification of periods with low biomass-burning impact, long-range transport (LRT) events, and regional pollution episodes. Aerosols from Saharan dust events showed the highest real and imaginary refractive index, along with a large inorganic mass fraction (around 26 %), which differs from typical Amazonian conditions. Furthermore, regional biomass-burning emissions during the dry season promoted elevated fine-mode particle concentrations (median 2250 cm-3), dominated by absorbing carbonaceous material. These particles also showed the maximum mass scattering efficiency, which was consistently higher at the 60 m height, underscoring the importance of vertical transport and aerosol aging processes. These results indicate that the clustering method can discriminate between aerosol populations and elucidate differences between particles of different sources and processes influencing the Amazonian atmosphere.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Atmospheric Chemistry and Physics.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.- Preprint
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2025-1078', Anonymous Referee #1, 02 May 2025
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RC2: 'Comment on egusphere-2025-1078', Anonymous Referee #2, 12 Aug 2025
Manuscript by Valiati et al. presents long-term in situ data (5 years) from atmospheric aerosol measurements at tall tower using state-of-the-art aerosol instrumentation in the Amazon region. The study provides a unique data set investigating changes in aerosols optical properties in combination with their chemical composition, vertical gradient and size distribution as well as aerosol origin.
From this perspective, I find this study suitable for publication in the ACP. I have only a few minor comments that would be worth to address.
- Fig. 2, matrix: Could you add to this Ångström matrix a classification scheme presented e.g. by Cappa et al. (2016) (in their Fig. 8d) for better orientation of possible aerosol composition? And can you provide a same matrix for 60 m data? Considering the different year-variations of SAE (Fig. 1a), certain changes could also be reflected in this image. It can be included in the supplement.
- The same eBC trend at both heights (60 vs. 325 m, Fig. 1c) is an interesting result. Some shorter time measurements on towers show that eBC concentrations usually decrease with height - e.g. Sun et al. (2020). The vertical distribution of other components in individual clusters is also similar (60 vs. 325 m, Fig. 4e), suggesting that atmospheric mixing at both levels is similar. Could this indicate that the mixed planetary boundary layer (PBL) is much higher than 325 m? Can you compare this with other studies where the concentration gradient changes with elevation?
- 167: „…and ρOrg calculated based on Kuwata et al.“ Please, provide average organic matter density + standard deviation you calculated for the measurement period.
- 170: you write: „Lastly, the scatter and linear regression between ACSM daily concentrations and SMPS-derived daily concentrations minus eBC indicate that the methodology could accurately represent ACSM aerosol concentrations at both heights.“ Can you prove this statement, for example with a graph in the supplement?
- Some parts of the manuscript are too long and should be shortened or moved to the supplement. An example is section 2.4. (Clustering procedure), but in general, I think the entire methodology could be shortened appropriately.
- Fig. 6: Can you add correlations of individual fits to scatter plots?
- References, l.607, Andreae et al. (2015): Citation to preprint is provided, please update with link to final article.
Refrences:
Cappa, C. D., Kolesar, K. R., Zhang, X., Atkinson, D. B., Pekour, M. S., Zaveri, R. A., Zelenyuk, A. and Zhang, Q.: Understanding the optical properties of ambient sub-and supermicron particulate matter: Results from the CARES 2010 field study in northern California, Atmos. Chem. Phys., 16(10), 6511–6535, doi:10.5194/acp-16-6511-2016, 2016.
Sun, T., Wu, C., Wu, D., Liu, B., Sun, J. Y., Mao, X., Yang, H., Deng, T., Song, L., Li, M., Li, Y. J. and Zhou, Z.: Time-resolved black carbon aerosol vertical distribution measurements using a 356-m meteorological tower in Shenzhen, Theor. Appl. Climatol., 140(3–4), 1263–1276, doi:10.1007/s00704-020-03168-6, 2020.
Citation: https://doi.org/10.5194/egusphere-2025-1078-RC2 -
AC1: 'Response to the referees' comments', Rafael Valiati, 15 Sep 2025
Response to reviewer comments on the manuscript "Distinct aerosol populations and their vertical gradients in central Amazonia revealed by optical properties and cluster analysis", submitted for publication at ACP.
Dear Editor, we would like to thank you and both reviewers for their valuable comments and useful suggestions for improving our manuscript. Attached, you can find answers and actions for each individual comment from the reviewers.
Responses to Reviewer #1 of the manuscript “Distinct aerosol populations and their vertical gradients in central Amazonia revealed by optical properties and cluster analysis” by Valiati et al., submitted for publication in Atmospheric Chemistry and Physics
Dear editor, we thank Reviewer #1 for the positive feedback and for recognizing the value of this manuscript, which utilizes an extensive dataset of atmospheric measurements from the ATTO site and is based on a sound methodology for aerosol characterization. The general and specific comments are addressed in detail in the attached response letter.
Responses to Reviewer #2 of the manuscript “Distinct aerosol populations and their vertical gradients in central Amazonia revealed by optical properties and cluster analysis” by Valiati et al., submitted for publication in Atmospheric Chemistry and Physics
Dear Editor, we would like to thank Reviewer #2 for the valuable comments and useful suggestions to improve our manuscript. Attached, you can find answers and actions for each individual comment.
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The manuscript titled “Distinct aerosol populations and their vertical gradients in central Amazonia revealed by optical properties and cluster analysis” by Valiati et al. presents multi-instrument datasets (optical, chemical, and size-resolved measurements) at two different heights and the application of clustering algorithm to characterize of Amazonian aerosol dynamics and sources. The study leverages five years of vertically resolved in-situ data (2018–2023) from the Amazon Tall Tower Observatory (ATTO), applying unsupervised machine learning (k-means clustering) to optical intensive parameters and black carbon concentrations. By stratifying observations seasonally and vertically (60 m and 325 m), the authors identify different aerosol populations associated with background conditions, long-range transport (LRT) events (e.g., Saharan dust and African biomass burning), and regional biomass-burning episodes. The methodology is well based in the literature, it extends the field by linking aerosol intensive properties to source and transformation processes and this study provide a valuable optical characterization of different aerosol populations at the analyzed site. The manuscript deserves publication since it is methodologically sound, comprehensive, and clearly written. However, I recommend minor revisions before acceptance.
General comments:
Specific comments:
Line 135: PNSDs measurements were performed using a TSI SMPS in the range between 10-400 nm. Why did you choose this range without considering a wider range which would allow you to characterize a more realistic accumulation mode (up to 500 – 800 nm, for example)? Considering a wider range in the PNSD data will provide very useful information for the aerosol population characterization.
Lines 166-170: Why did you consider only two inorganic species? What about the contribution of H2SO4 or NH4HSO4? Probably, you expect a negligible effect of this species, I recommend supporting this statement with previous publication in the same area.
Lines 169-171: The plots and regression coefficients of the comparison of ACSM and SMPS-derived mass concentration should be included in the manuscript (maybe in the supplement) to support the statement mentioned in these lines.
Lines 225-228: In the manuscript, it’s pointed out that the main driver of the aerosol population at this site is the dry/wet condition. Since it’s mentioned that the k-means clustering is applied to two different datasets: the dry and wet condition seasons. As a quality check for the input variables choice, have you tried to perform the clustering with k=2 for the whole dataset? According to this analysis, we expect that each cluster represents one of the main seasons. If this quality check is not satisfactory, I am a bit skeptical in the decision of the input variables of the algorithm. I’m curious to see a figure like Fig. S2b with the cluster frequency of each two cluster over it.
Line 460: “Section 3.5 Aerosol mass scattering efficiency”. In my opinion, I found that the last section (on aerosol mass scattering efficiency) reads somewhat independently of the earlier parts of the study. In the introduction of the manuscript all the optical parameters (SSA, refractive index, MSE, etc…) are presented at the same time showing their usefulness for characterizing aerosol population properties. If this section were more clearly related to the objectives of the document, the cohesion of the entire document would be improved. I recommend, for example, to clarify at the begging of this section the purpose of this analysis within the manuscript main goals.