A Decadal-Scale Perspective on <em>PM</em><sub>10</sub> Composition and its Variability Drivers at the Alpine High-Altitude Research Station Jungfraujoch

Weng, Julian; Hao, Yufang; Brem, Benjamin T.; Cui, Tianqu; Khare, Peeyush; Dada, Lubna; Daellenbach, Kaspar R.; Darfeuil, Sophie; Uzu, Gaëlle; Jaffrezo, Jean-Luc; Steinbacher, Martin; Reimann, Stefan; Gkraikou, Thaleia; Oikonomou, Konstantina; Sciare, Jean; Collaud Coen, Martine; Mohr, Claudia; Prévôt, Andre S. H.; Gysel-Beer, Martin; El Haddad, Imad; Winiger, Patrik

doi:10.5194/egusphere-2026-3660

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https://doi.org/10.5194/egusphere-2026-3660

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07 Jul 2026

| 07 Jul 2026

Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).

A Decadal-Scale Perspective on PM₁₀ Composition and its Variability Drivers at the Alpine High-Altitude Research Station Jungfraujoch

Julian Weng, Yufang Hao, Benjamin T. Brem, Tianqu Cui, Peeyush Khare, Lubna Dada, Kaspar R. Daellenbach, Sophie Darfeuil, Gaëlle Uzu, Jean-Luc Jaffrezo, Martin Steinbacher, Stefan Reimann, Thaleia Gkraikou, Konstantina Oikonomou, Jean Sciare, Martine Collaud Coen, Claudia Mohr, Andre S. H. Prévôt, Martin Gysel-Beer, Imad El Haddad, and Patrik Winiger

Abstract. Atmospheric aerosols in the free troposphere (FT) exert a disproportionate influence on climate forcing yet remain poorly constrained. Here, we present an 11-year (2011–2021) characterization of PM₁₀ chemical composition at the High Altitude Research Station Jungfraujoch (3580 m above sea level), capturing both FT conditions and episodic planetary boundary layer intrusions (PBLi). We integrate long-term measurements of organic aerosol (OA), elemental carbon, sulfate, crustal elements, trace metals, and bulk and molecular-level organic composition with gas-phase observations and proxies for atmospheric transport and oxidative capacity to quantify the drivers of aerosol loading and composition. The concentrations of primary aerosol species, including metals and elemental carbon, are strongly controlled by episodic PBL-to-FT transport (2-3-fold seasonal amplitude, e.g. 0.15 to 0.3 ng m^-3 for Pb). Secondary species, including sulfate and OA, also reflect PBLi impact, but their formation requires sustained oxidative processing, for which the atmospheric humidity ratio (ω) acts as a key control. OA exhibits the strongest seasonal amplitude (10-fold, 0.1 to 1 μg m^-3), additionally reflecting enhanced biogenic emission intensities in the PBL. This is accompanied by a systematic shift in C₉ and C₁₀ compounds, likely related to seasonal maxima in monoterpene emissions. Together, these results demonstrate that FT aerosol is governed by a dynamic interplay between episodic PBL-FT transport, source emission intensities and oxidative processing. This dataset constrains their relative contributions, and provides decade-scale observational benchmarks for improving the representation of transport and aging in atmospheric models, with implications for reducing uncertainties in climate forcing.

How to cite. Weng, J., Hao, Y., Brem, B. T., Cui, T., Khare, P., Dada, L., Daellenbach, K. R., Darfeuil, S., Uzu, G., Jaffrezo, J.-L., Steinbacher, M., Reimann, S., Gkraikou, T., Oikonomou, K., Sciare, J., Collaud Coen, M., Mohr, C., Prévôt, A. S. H., Gysel-Beer, M., El Haddad, I., and Winiger, P.: A Decadal-Scale Perspective on PM₁₀ Composition and its Variability Drivers at the Alpine High-Altitude Research Station Jungfraujoch, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2026-3660, 2026.

Received: 22 Jun 2026 – Discussion started: 07 Jul 2026

Competing interests: The authors declare that they have no conflict of interest. Part of the funding was provided via a WeMakeIt Science-485 Booster crowdfunding campaign, including contributions from Digitel AG and Camfil GmbH. The funders had no involvement in the study design, data collection, analysis, interpretation, or manuscript preparation.

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.

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'Comment on egusphere-2026-3660', Anonymous Referee #1, 11 Aug 2026 reply
Review of A Decadal-Scale Perspective on PM10 Composition and its Variability Drivers at the Alpine High-Altitude Research Station Jungfraujoch
Julian Weng et al.
This is an interesting and well-written manuscript. The introduction is particularly strong, providing a clear rationale and effectively framing the research question. The paper is carefully written throughout, with a logical organization. Overall, I found the hypothesis of using specific tracers at a mountain site [i.e. NOy/CO for PBLi and w for atmospheric oxidative capacity] to demonstrate and quantify that the influence of the PBL allows for elevated aerosol concentration, while atmospheric oxidative capacity governs the composition of these episodes (in gas and aerosol phase), an interesting and innovative approach. At this point, I believe this paper need further work to clearly demonstrate this approach (additional statistics, etc). The major and minor comments provided below are intended to further strengthen the manuscript and improve its clarity, rigor, and overall impact.
Major comments and questions:
The description of the inlet at JFJ must clarified. The paper cited (Weingartner et al., 1999) only considered particle below 750 nm. Additionally, the paper looked at number concentration (not mass) of aerosol, and said all assumptions were based on calculation in the submicron sizes. Thus, the “losses below 5%” is not appropriate when considering online mass concentration of PM10. Instead, I would strongly encourage the authors to deeply consider losses in the system using computational or experimental (if available) methods.   Here is an example to consider:

Von der Weiden, S-L., F. Drewnick, and S. J. A. M. T. Borrmann. "Particle Loss Calculator–a new software tool for the assessment of the performance of aerosol inlet systems." Atmospheric Measurement Techniques 2, no. 2 (2009): 479-494.
Has an experimental validation of the JFJ inlet been conducted (like these examples:https://www.tandfonline.com/doi/full/10.1080/02786826.2019.1602718#d1e1040 or https://www.osti.gov/servlets/purl/2375529)?
This is especially concerning as later (line 154) it is suggested that negligible number of accumulation (N90) particles is found in the Free Troposphere at JFJ. This is inconsistent with many other mountain sites, which commonly find coarse mode (especially dust) aerosols in the free troposphere.   A few examples are provided below.
Shen, M., Qi, W., Liu, Y., Zhang, Y., Dai, W., Li, L., Guo, X., Cao, Y., Jiang, Y., Wang, Q., Li, S., Wang, Q., and Li, J.: Measurement report: Observational insights into the impact of dust transport on atmospheric dicarboxylic acids in ground region and free troposphere, Atmos. Chem. Phys., 25, 16147–16165, https://doi.org/10.5194/acp-25-16147-2025, 2025.
Betsy, K. B., and Sanjay Kumar Mehta. "Characteristics of dust aerosols within the atmospheric boundary layer and free troposphere over a tropical coastal station." Meteorology and Atmospheric Physics 137, no. 3 (2025): 27.
Tsai, F., Chien, Y.C., Chen, W.N., Notaro, M., Chen, H.Y., Lin, N.H., Hsu, P.C. and Lin, Y.C., 2025. Source and transport of dust to the North Pacific: Observations and analysis from a high mountain. Journal of Geophysical Research: Atmospheres, 130(6), p.e2024JD042415.
Additionally, particle loss may impact the conclusion in line 216 that “on an annual basis, cumulative fine and coarse mode aerosol masses are of comparable magnitude”
This mass comparison depends upon the assumption that aerosol transmission losses are not size dependent, which is most likely incorrect.
Line 99 states that there were 249 composite samples. Yet, if a sample was taken daily for 10 years, we would expect ~3600 filters. The paper suggest that composites include 4 days of filters. Thus, this reviewer expects approximately 900 composite filters. Why are there only 249?

Eliminating times with Saharah dust conditions does specifically eliminate the unique meteorological conditions that allow for this source region. This bias in the dataset should be acknowledged.

Line 78, how has the contribution of local primary emissions changed over the last decade as tourist visits have increased?

How will potential increasing amounts of wildfire smoke sampled at JFJ impact the atmospheric oxidative capacity, as captured by the humidity ratio? Potentially the CO/CO2 ratio could be used to identify smoke influence. Does the role of smoke impact Figure 9b?

Generally, this paper requires more rigor to justify the conclusions. Here are a few examples, where further analysis/statistics could be used to demonstrate the results.
For figure 3b (plot of CO vs. NOy/CO), there is no clear relationship between the plotted variables, potentially suggestion that CO does not impact the ratio, as the variability (i.e. measurement range observed) in the two variables (NOy and CO) are significantly different

Line 268. Is this moderate decrease in CO at high humidity ratio statistically significant?

Generally, the statements pertaining to plots 3b and 3c are speculative and need to be more carefully considered and evaluated.

Throughout the paper statements such as “correlate well” need to be backed by statistics.

It is unclear to this reviewer if any relationships are found in Figure 3b and 3c.

In a similar vein, on line 300 and 311, please define “correlate”/ “correlation” with a statistical value.

It is also important to quantify term including “strongest dependence”, “moderate sensitivity”, “not correlated”, and “stronger correlation” in lines 313-319.

Line 339, define using statistics “increase systematically”

This review does not agree yet agree with the statement in line 413 “results emerges with clarity”.

Minor comment:
Figure 3b and 3c: Consider starting the y-axis at 60 ppb for CO and 35 ppb for O₃. This adjustment would improve the readability of the plots by reducing the amount of unused white space and emphasizing the variability in the data.
Figure 3, 4, 6, and 7 – Consider a different more distinct color bar. It is difficult to differentiate blue and purple, which is the most commonly used colors on all plots.

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Short summary

Long-term observations at the Jungfraujoch High Altitude Research Station show that, alongside air mass transport, sustained oxidative processing shaped by atmospheric water vapor plays a central role in driving aerosol loading and composition. Combining detailed aerosol chemical characterization with process-level insights, we provide important observational benchmarks for improving atmospheric model performance in the remote free troposphere, where uncertainties remain particularly high.


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A Decadal-Scale Perspective on PM10 Composition and its Variability Drivers at the Alpine High-Altitude Research Station Jungfraujoch

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