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https://doi.org/10.5194/egusphere-2026-4216
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/egusphere-2026-4216
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
28 Jul 2026
| 28 Jul 2026
Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
A multi-site climatology of aerosol mixing state from hygroscopicity measurements
Abstract. We present an expanded, size-resolved observational climatology of aerosol mixing state inferred from hygroscopicity measurements. Using κ-PDFs from long-term and campaign-based HTDMA observations at eight sites spanning urban, continental, coastal, marine environments, we infer the aerosol mixing state index χ across multiple particle sizes and four seasons. Building on a previously evaluated κ-to-χ framework, we synthesize these datasets to characterize spatial, seasonal, and size-dependent variability in aerosol mixing state, with attention to retrieval limitations and site-dependent. We find that continental and accumulation-mode aerosol populations generally exhibit consistently higher χ, whereas marine and urban-influenced sites tend to be more externally mixed and show greater variability. Across most sites, χ increases with particle size, consistent with the stronger atmospheric aging of accumulation-mode particles. The use of Dα-Dγ diagnostics provides insight into the processes controlling the observed variability in χ. These results provide observational constraints on the size dependence, seasonal variability, and environmental controls of aerosol mixing state, and establish benchmarks for evaluating mixing-state assumptions in aerosol models relevant to cloud activation and radiative effects.
How to cite. Liu, Y., Zhou, S., Wang, J., and Riemer, N.: A multi-site climatology of aerosol mixing state from hygroscopicity measurements, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2026-4216, 2026.
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Status: open (until 08 Sep 2026)
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
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- RC1: 'Comment on egusphere-2026-4216', Anonymous Referee #1, 11 Aug 2026 reply
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RC2: 'Comment on egusphere-2026-4216', Anonymous Referee #2, 13 Aug 2026
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The manuscript presents a multi-site analysis of aerosol mixing state inferred from size-resolved HTDMA hygroscopicity measurements. The compilation of observations from different environments is potentially valuable, and the attempt to provide observational constraints on aerosol mixing state is relevant to Atmospheric Chemistry and Physics. The manuscript is generally well organized and the analysis provides useful information on the size and seasonal dependence of hygroscopicity-derived mixing state. However, several methodological and interpretational issues currently limit the robustness and generality of the conclusions. I therefore recommend major revision.
Major comments
- The use of the term “climatology” appears stronger than warranted by the temporal coverage of the datasets. The eight sites were sampled during substantially different periods, ranging from several years at MHD and SGP to approximately one year at several locations and only November 2016 and May–June 2017 at BJIAP. CRG also lacks a complete annual cycle. Consequently, site differences, seasonal variability, interannual variability, and long-term changes in aerosol composition are intrinsically mixed together. The present dataset therefore represents a useful multi-site synthesis, but its ability to establish a coherent climatology is limited.
- The retrieved χ is fundamentally conditional on the assumed binary LH–MH representation of aerosol composition. Real atmospheric particles contain complex mixtures of organics, sulfate, nitrate, ammonium, black carbon, sea salt, dust, and other components, and chemically distinct particles can exhibit similar hygroscopicities. Therefore, a κ distribution does not uniquely constrain chemical composition or chemical mixing state. Several parts of the manuscript appear to interpret the hygroscopicity-derived χ as though it were equivalent to a composition-resolved aerosol mixing-state metric, which requires greater caution.
- A major concern is the comparability of χ among different environments. Continental and coastal sites use κMH = 0.65, whereas ENA and MHD use κMH = 1.5. The manuscript explicitly states that values retrieved at ENA and MHD are not directly comparable with those obtained using κMH = 0.65 because of the different end-member assumptions. Nevertheless, the Abstract and Conclusions compare marine, urban, and continental environments and conclude that marine aerosol tends to be more externally mixed and more variable. This creates an important inconsistency between the methodological limitations acknowledged by the authors and the cross-environment conclusions drawn from the results.
- The datasets are not fully harmonized in terms of instruments, data-processing procedures, particle sizes, and original products. Five datasets are derived from ARM processed HTDMA data, BJIAP growth factors are converted to κ using κ-Köhler theory, and MHD and HACPL κ-PDFs are reconstructed from previously published distributions. These methodological differences may influence the width and shape of κ-PDFs and consequently propagate into Dα, Dγ, and χ. This issue is particularly relevant because the major conclusions are based on relatively subtle differences among sites and particle sizes.
- The uncertainty of the retrieved χ values is insufficiently characterized in the present study. Although previous work is cited for sensitivity and uncertainty analyses, the uncertainties associated with measured growth factors, κ conversion, κ-PDF construction, end-member assumptions, and differences among datasets are not quantitatively represented in the cross-site comparison. This is especially important for marine aerosol, where the authors acknowledge that the binary framework becomes more approximate.
- Several mechanistic interpretations go beyond what can be directly established from the HTDMA observations. Seasonal and size-dependent variations are attributed to nitrate formation, biomass burning, long-range transport, cloud processing, monsoon circulation, fresh anthropogenic emissions, and sea-spray contributions. These mechanisms are physically plausible, but they are not independently constrained by chemical composition, source apportionment, trajectory analysis, or other supporting observations in the present study. The Dα–Dγ analysis itself is also derived mathematically from the same κ-PDF and therefore provides a useful decomposition of χ rather than an independent constraint on atmospheric processes.
- The interpretation of increasing χ with particle size primarily as evidence of stronger atmospheric aging appears somewhat oversimplified. Aging is one plausible explanation, but size-dependent source distributions, condensational growth, coagulation, cloud processing, and selective removal can also modify the mixing state of different particle sizes. Moreover, fixed particle diameters do not necessarily correspond to the same aerosol mode across all environments.
- The implications for CCN and aerosol optical properties are stronger than directly demonstrated by the analysis. No CCN activation calculation is performed using the observed distributions, and the effect of mixing state on CCN depends on supersaturation, number-size distribution, and the full hygroscopicity distribution. Similarly, a high hygroscopicity-derived χ for accumulation-mode particles does not necessarily imply that internal-mixing assumptions introduce only small errors in aerosol optical calculations, particularly for absorbing aerosols such as black carbon, where coating state, refractive index, and particle morphology can strongly affect absorption.
- The manuscript presents the derived χ distributions as potential benchmarks for aerosol models, but the observational and model quantities are not necessarily equivalent. Composition-resolved models generally calculate mixing state from species mass fractions, whereas χ in this study is inferred from hygroscopicity under a binary LH–MH assumption. Therefore, the extent to which the reported χ can serve as a quantitative benchmark for model-derived composition-based mixing-state metrics requires careful interpretation.
Minor comments
- The Abstract contains an incomplete phrase: “with attention to retrieval limitations and site-dependent.”
- The statement that HTDMA instruments “operate continuously” appears too general considering that several datasets used here are campaign-based or contain incomplete seasonal coverage.
- The description of κLH = 0 as a nearly non-hygroscopic “carbonaceous” end-member is somewhat simplified because carbonaceous aerosol can span a substantial range of hygroscopicity depending on composition and atmospheric aging.
- The term “spatial variability” may overstate the spatial representativeness of only eight geographically sparse sites. “Cross-site variability” may better reflect the observational evidence.
- The manuscript occasionally uses “interannual variability” when discussing sites with approximately one year of observations. Such terminology is not appropriate where multiple years are unavailable.
- Several statements use words such as “significantly” or “significant” even though no formal statistical significance test is presented.
- Narrow κ-PDFs are occasionally interpreted as evidence of chemically homogeneous aerosol populations. Chemically different particles may have similar κ values, so hygroscopic homogeneity does not necessarily imply chemical homogeneity.
- Similarly, multimodal κ-PDFs do not uniquely identify distinct source populations. Different modes are consistent with multiple particle types, but hygroscopicity alone does not uniquely identify their sources.
- The number of observations represented by each boxplot in Figure 3 is not provided. Given the strongly unequal sampling among sites and seasons, this information is important for interpreting the distributions.
- The manuscript contains several typographical and grammatical issues, including “observational constratins,” “drwan from the literature,” “variablity,” “compare to,” “aeorsol,” and “particles populations,” and would benefit from careful language editing.
Citation: https://doi.org/10.5194/egusphere-2026-4216-RC2
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Yicen Liu
Department of Civil and Environmental Engineering, Grainger College of Engineering, University of Illinois Urbana-Champaign, Urbana, IL, USA
Shengqian Zhou
Department of Energy, Environmental, and Chemical Engineering, Washington University in St. Louis, St. Louis, MO, USA
Jian Wang
Department of Energy, Environmental, and Chemical Engineering, Washington University in St. Louis, St. Louis, MO, USA
Department of Climate, Meteorology, and Atmospheric Science, University of Illinois Urbana-Champaign, Urbana, IL, USA
Short summary
Airborne particles contain different chemicals, and their distribution among particles influences cloud formation and climate. Given limited long-term evidence, we combined measurements from eight locations to examine changes across particle sizes, seasons, and environments. Larger particles were more similar in composition, while smaller particles and those influenced by urban or marine air varied more. The results provide observational benchmarks for improving atmospheric and climate models.
Airborne particles contain different chemicals, and their distribution among particles...
This study investigates the seasonal and size-dependent variability of the aerosol mixing state index (χ) based on hygroscopicity parameter probability distributions from multiple sites, and establishes a climatological dataset of aerosol mixing state. The authors find that ambient aerosol populations generally tend toward internal mixing rather than the external mixing limit. Overall, the study is built upon a promising methodological framework and reports interesting observational findings. However, the depth of the analysis needs to be strengthened before the manuscript can be accepted for publication.
Several specific aspects warrant further improvement:
Specific technical and interpretative concerns:
Line 70: At the marine-influenced sites, κMH is set to 1.5 to represent highly hygroscopic species such as sea salt. A sensitivity test using alternative κMH values would help quantify the robustness of the retrieved χ values and should be included.
Line 165: The interpretation of χ variations at sites such as SGP, CRG, HOU, and EPC requires more detailed explanation. In particular, for urban and coastal urban sites that are persistently influenced by anthropogenic emissions (including fresh primary organic aerosol and black carbon), it is not immediately intuitive why the aerosol population remains relatively internally mixed throughout the year. The authors should elaborate on the underlying mechanisms—e.g., rapid coagulation, condensation of secondary species, or regional aging and add appropriate references.