Measurement report: Comprehensive Seasonal Study of the Composition and Sources of Submicron Aerosol during the JULIAC Campaign in Germany

Liu, Lu; Hohaus, Thorsten; Hofzumahaus, Andreas; Holland, Frank; Fuchs, Hendrik; Tillmann, Ralf; Bohn, Birger; Andres, Stefanie; Tan, Zhaofeng; Rohrer, Franz; Karydis, Vlassis A.; Vardhan, Vaishali; Franke, Philipp; Lange, Anne C.; Novelli, Anna; Winter, Benjamin; Cho, Changmin; Gensch, Iulia; Wedel, Sergej; Wahner, Andreas; Kiendler-Scharr, Astrid

doi:https://doi.org/10.5194/egusphere-2025-3074

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https://doi.org/10.5194/egusphere-2025-3074

Preprints

18 Jul 2025

| 18 Jul 2025

Measurement report: Comprehensive Seasonal Study of the Composition and Sources of Submicron Aerosol during the JULIAC Campaign in Germany

Lu Liu, Thorsten Hohaus, Andreas Hofzumahaus, Frank Holland, Hendrik Fuchs, Ralf Tillmann, Birger Bohn, Stefanie Andres, Zhaofeng Tan, Franz Rohrer, Vlassis A. Karydis, Vaishali Vardhan, Philipp Franke, Anne C. Lange, Anna Novelli, Benjamin Winter, Changmin Cho, Iulia Gensch, Sergej Wedel, Andreas Wahner, and Astrid Kiendler-Scharr

Abstract. The seasonal variations of aerosol sources and their atmospheric evolution are investigated using observations from the year-long JULIAC campaign (January–November 2019) in Jülich, Germany. Non-refractory submicron aerosol components were continuously measured alongside oxidants (OH, O₃, NO₃), trace gases, and meteorological conditions. Organic aerosols (OA) dominated the aerosol composition throughout the year (39–58 %), with secondary formation being the major source. OA, including organic nitrate and organosulfur, peaked during a summer heatwave event due to enhanced daytime and nighttime secondary OA formation driven by elevated concentrations of atmospheric oxidants. Changes in the OA composition during the heatwave suggest shifts in the formation pathways, where isoprene may play an important role. Biomass-burning, mainly wildfires and anthropogenic activities (e.g., heating, industry), is the dominant primary OA source (45–83 %), which may grow in influence due to climate change and the expected energy transition. Air masses containing OA from regional transport from marine and wildfire sources are identified through source apportionment. Analysis and modeling prove this method to be more reliable than traditional tracer-based methods. Regional transport to this study site typically shows a cleansing effect on the aerosol concentration, except in winter. Furthermore, seasonal variations in the effects of regional transport are seen, where identical transport pathways led to different influences on aerosol properties, driven by seasonal differences in biogenic and anthropogenic emissions. This study enhances understanding of seasonal variation in submicron aerosol properties in response to their sources, atmospheric evolution, and transport.

How to cite. Liu, L., Hohaus, T., Hofzumahaus, A., Holland, F., Fuchs, H., Tillmann, R., Bohn, B., Andres, S., Tan, Z., Rohrer, F., Karydis, V. A., Vardhan, V., Franke, P., Lange, A. C., Novelli, A., Winter, B., Cho, C., Gensch, I., Wedel, S., Wahner, A., and Kiendler-Scharr, A.: Measurement report: Comprehensive Seasonal Study of the Composition and Sources of Submicron Aerosol during the JULIAC Campaign in Germany, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-3074, 2025.

Received: 28 Jun 2025 – Discussion started: 18 Jul 2025

Competing interests: At least one of the (co-)authors is a member of the editorial board of Atmospheric Chemistry and Physics.

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Status: final response (author comments only)

RC1:
'Comment on egusphere-2025-3074', Anonymous Referee #1, 11 Aug 2025
General comments
This study investigates the seasonal composition, sources, and formation mechanisms of submicron aerosols in the Jülich region of Germany based on the JULIAC observation campaign, with a focus on the secondary formation processes of organic aerosols, the influence of regional transport, and the impact of heatwave events on aerosol properties. This study provides important insights into the seasonal variations of aerosols and their environmental effects in the study area. However, some aspects require further clarification or improvement to enhance the scientific rigor and readability of the paper.

Specific comments
Line 78-83: The first sentence of this paragraph mentions that “long-term regional transport affects atmospheric conditions as well as aerosol properties”, but the subsequent text only focuses on MSA without directly explaining how “regional transport” specifically influences MSA or aerosol characteristics. It is recommended to add one or two sentences clarifying the direct relationship between regional transport and the distribution or concentration of MSA.

This study employs both 24-hour and 72-hour backward trajectories. Please explain the rationale behind using trajectories of different durations.

Line 199-205: The methodology for estimating liquid water content using the ISORROPIA-II model requires further refinement. Please clarify whether the model operates in forward or backward mode, and elaborate on the impact of missing gaseous pollutants (such as HCl, HNO₃, HNO₂, SO₂, and NH₃) on the model’s performance, along with an assessment of the associated uncertainties. For example, this may affect the conclusions in line 286-288.

Section 2.2 “Instrumentation” and Table 1 describe auxiliary instruments (e.g., SMPS, CPC) and report total particle volume/number concentrations, but these data are scarcely discussed in later sections. Please either incorporate relevant analysis or consider removing redundant information for better focus.

Line 298-309: Although the author mentioned the proportion falling under condition II when pH <0, it should be noted that a non-negligible portion of winter, summer, and autumn data still falls within condition I. The authors pointed out that the organic sulfur calculation method has limited reliability under low pH or high ammonium nitrate conditions (Figure 4), but they do not discuss the potential impact of the resulting errors on the conclusions. It is recommended to supplement the uncertainty analysis or include comparative validation results with other methods.

Line 330-332: LO-OOA and MO-OOA are defined by oxidation degree, while NO-OOA is categorized by time. Could there be potential overlaps between NO-OOA and the other two subtypes? Additionally, is NO-OOA also resolved during daytime? It would be better to provide diurnal variation plot to clarify day-night differences, and supplement the discussion with a comparison of their mass spectral signatures to better distinguish these components.

Line 352-354: A comparative analysis of NO-OOA and biomass burning tracers across different seasons would help clarify their potential sources and interactions.

Figure 7 demonstrates good correlations between NO-OOA and both C₂H₄O₂ and CO, it would be valuable to examine whether these relationships vary seasonally.

Line 390: The word “for” should be deleted.

Line 402-405: It would be better to incorporate meteorological data (particularly wind direction/speed) to better identify the sugar factory’s contribution. Additionally, could the relative contributions of the two distinct BBOA sources be further differentiated and quantified?

Line 422: Please clarify why O_x wasn’t employed for this particular analysis.

Line 427: The preceding dot before (Liu et al., 2024) should be removed.

Line 437-441: Quantitative comparison of diurnal and seasonal variations in LO-OOA, MO-OOA, NO-OOA contributions would strengthen the analysis.

Line 504: Would this methodological bias might occur across other seasons?

Figure 10 suggests that both Mean Cluster 1 and Mean Cluster 2 exhibit marine influences, yet no marine source contribution is identified. Please clarify why marine sources are not reflected in the apportionment results? And additionally, what about the percentage distribution of air masses from different trajectory directions

Line 519-520: The fire spots and trajectory plots suggest influences from local European fires, yet the analysis primarily emphasizes Russian contributions. Could you clarify why other regional fire impacts (e.g., from Europe) were not addressed

Line 525: How does the mass spectral signature of BBOA at this time differ from other periods? There should be distinguishable features between relatively fresh and aged BBOA

Figure 12: The air mass trajectories indicate marine influences across all seasons, yet MSA-OA contributions are only identified under marine air masses in spring/summer source apportionment results, not in autumn/winter. Additionally, please clarify whether PMF was run separately for each season or as a consolidated dataset in “PMF analysis” section in the main text.

Section 4.1.3 provides a relatively weak analysis of the regional transport factor. It is recommended to incorporate other statistical methods (such as Potential Source Contribution Function, PSCF) for supplementary validation.

Line 603-608: The relationship between increased ALWC and organic sulfur formation during heatwaves requires more direct data support (e.g., SO₂ concentration, aqueous-phase reaction rates).

The terms “organosulfur” and “organosulfates” are used interchangeably in the text and should be standardized (note that “organosulfur” should be a broader term encompassing organic sulfur compounds and organosulfates).

In lines 283 and 323, "ALWC" can be used directly since it has already been defined earlier.
Citation: https://doi.org/10.5194/egusphere-2025-3074-RC1
RC2:
'Comment on egusphere-2025-3074', Anonymous Referee #2, 12 Aug 2025
This manuscript provides an analysis of the seasonal variability, sources, and formation mechanisms of submicron aerosols in the Jülich region of Germany, based on measurements from the JULIAC campaign. Particular attention is given to secondary organic aerosol formation and its influence from characteristic events during the measurement period, such as regional transport episodes and heatwave conditions. The paper is generally well written and could be considered for publication once the following concerns are addressed.
Specific comments:
Line 41. The direct and indirect effects are not described. Please add a brief description of radiation and cloud interactions.

Line 45. The statement “playing a key role in altering the environmental impact of aerosols”. Please specify how these impacts are altered.

Line 71. Correct the reference “Liu et al. (Liu et al., 2024)”

Section 2.2. “Instrumentation”: The manuscript does not specify the instrument models used and does not describe the calibration protocols, for example, those applied to the PTR-ToF-MS during the field campaign. Please include them.

Section 2.5 “Trajectory model”: Specify the altitude at which the back trajectories were calculated.

Line 245: Please ensure consistent formatting of “O_x”.

Line 261: Space between “America” and “(Kiendler-Scharr”

Line 263-266: The authors report high organic-nitrate fractions during summer (62%), yet the cited comparative studies are from spring, and the authors’ springtime results are considerably lower (14%). Please provide comparable references from summer or justify why springtime observations are directly comparable; otherwise, consider rephrasing the comparison.

Line 274: The reported organosulfur concentrations (summer up to 6 µg/m³; autumn up to 2 µg/m³) do not match the values shown in Figure 3. Please verify and correct the text or the figure to ensure consistency.

Line 273: Space between “heating” and “(Liu et al., 2024)”.

Lines 304, 313, and 315: The citation of Schueneman et al. (2021) should be corrected.

Line 388: Space between “of” and “R²”.

Line 399 – 409: The attribution of BBOA emissions to the sugar factory is unclear. Is there a specific reason why the factory operates only in autumn? It would be useful to also assess other potential influences, such as meteorological parameters (e.g., wind direction and speed).

Please ensure consistent use of the term “VOC” or “VOCs” throughout the manuscript.

Line 515-528: Please consider whether wildfire plumes from other European countries (e.g., Poland, where numerous hotspots were detected) may have contributed to the aerosol population.

Is the O:C ratio different between autumn BBOA sources (residential heating, sugar factory) and aged BBOA from regional wildfire plumes (e.g., Russia region)? This comparison could reveal important differences in oxidation state between local and transported BBOA in spring and autumn.

Figures S3-S6: The x-axis labels in the diurnal variability plot appear overcrowded. please adjust the spacing or format to improve them.

Table S6: “Sulfate” is repeated in the caption, and the volume/surface columns are somewhat confusing. Please clarify.
Citation: https://doi.org/10.5194/egusphere-2025-3074-RC2
RC3:
'Comment on egusphere-2025-3074', Anonymous Referee #3, 17 Aug 2025
This work describes the aerosol composition during one-year measurements at a semi-rural area in Germany. The results provide interesting insights of the contribution of secondary organic aerosol sources to the organic aerosol and highlighted the presence of organic nitrate species. However, some modifications and technical corrections should be considered before publishing this work. Additionally, I consider the number of figures in the main text should be reduced, however I let it to the editor consideration.
Section 2.2 introduce the different instrumentation deployed and later the agreement time between the trajectory arrival and the detection time of the instruments is highlighted. However, details of data acquisition resolution and other technical details for the mass spectrometry techniques are not provided (e.g., collection efficiency for organics in AMS, conditions in the drift tube and E/N for PTRMS). I suggest the authors add a table in the supplement with the technical information.

In lines 248 to 250, the correlations of higher O/C ratios with increases Ox concentrations are highlighted only during summer. However, in Figure 2 a similar observation is reported during the spring period. This observation requires further discussion.

In Lines 267 and 268 the role of NO3 chemistry is highlighted to contribute to OA production during all the seasons, specially during the night. What is the role of other parameters measured (e.g., temperature and RH) into this observation as seasonal variations are also reported in Figure 3.

In lines 301 to 303, the authors highlight that organosulfur calculations can be affected by environmental parameters such as acidity. During the one-year calculations, the fragmentation method seems to be feasibly. I wonder about the applicability of this methodology during the heatwave period, where environmental conditions and chemistry is enhanced. Could the authors provide information on this? Could that have an impact into the organic and inorganic nitrate?

Technical details:
Line 19: Define the acronym JULIAC.
Lines 73 and 74 should be merged with the main goals introduced in lines 94 to 97.
Lines 101-102: “aimed to explore annual variations of and source contributions to oxidant concentrations”. This sentence is not clear.
Line 111: delete the and before submicron aerosol.
Line 143: replace made by reported.
Line 175: replace aerosol organics concentrations by organic aerosol concentrations.
In line 180, the use of prior factors from literature were used to constrain PMF analysis was mentioned. Can the authors provide further details of the additional constrains considered.
Line 193: What is the resolution of the GDAS used for the HYSPLIT model.
Line 202: The acronyms for RH and T are defined here but used since before. Introduce the abbreviations before and homogenize the text accordingly.
Modify the colors in right panel of Figure 6, as differences between the seasons are not clear.
Line 421: replace secondary organic aerosol by SOA
Line 525: replace primary organic aerosol and secondary organic aerosol by POA and SOA.
526: delete organic aerosol, the acronym was defined before.
Lines 569: “In this study, a decrease in monoterpene concentrations is observed during a heatwave event, with the average levels dropping to 60% of the pre-heatwave values (Figure 13).” The decrease of monoterpene concentrations is not clear in Figure 13 as values are lower than 0.3 ppb. The authors should consider displaying this profile on the right axes.
Citation: https://doi.org/10.5194/egusphere-2025-3074-RC3

Supplement

https://doi.org/10.5194/egusphere-2025-3074-supplement

Data sets

Replication data for Aerosol chemical composition and aerosol source apportionment (PMF) for the JULIAC 2019 campaign Lu Liu https://data.fz-juelich.de/dataset.xhtml?persistentId=doi:10.26165/JUELICH-DATA/TPPXNL

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Short summary

We measured air particles at a rural site in Germany over a year to understand how their sources and properties change with the seasons. Particles from natural sources peaked in summer, especially during heatwaves, while those from burning activities like residential heating and wildfires dominated in colder months. Winds carrying air from other regions also influenced particle levels. These findings link air quality to climate change and energy transitions.


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