Unraveling the chemical structures and sources of biomass-derived organic aerosols through a year-long offline analysis in Hyyti&auml;l&auml;, Finland

Sun, Qianzhe; Zhou, Ruichen; Ohata, Sho; Shirota, Chiaki; Petäjä, Tuukka; Ylivinkka, Ilona; Ahonen, Lauri; Kulmala, Markku; Mochida, Michihiro

doi:10.5194/egusphere-2026-1023

Preprints

https://doi.org/10.5194/egusphere-2026-1023

Preprints

16 Mar 2026

| 16 Mar 2026

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

Unraveling the chemical structures and sources of biomass-derived organic aerosols through a year-long offline analysis in Hyytiälä, Finland

Qianzhe Sun, Ruichen Zhou, Sho Ohata, Chiaki Shirota, Tuukka Petäjä, Ilona Ylivinkka, Lauri Ahonen, Markku Kulmala, and Michihiro Mochida

Abstract. Biomass-burning OA (BBOA) and biogenic secondary OA (BSOA), both originating from biomass but from different pathways, still lack comprehensive and quantitative understanding, which limits assessments of their environmental impacts. In this study, source-resolved OAs including BBOA and BSOA in a European boreal forest were characterized by the offline use of an aerosol mass spectrometer (AMS), with improved chemical resolution offered by polarity-based fractionation. OA extract solutions were prepared according to polarity as high-polarity water-soluble organic matter, humic-like substances, and water-insoluble organic matter, and their abundances and chemical structures were analyzed by off-line high-resolution AMS analysis. Quantitative analysis revealed an annual OA concentration of 1.24 ± 0.75 µg m⁻³, with lower concentrations in winter and higher in summer. A 5-factor source apportionment solution was obtained from positive matrix factorization (PMF) of the mass spectra of the three fractions. CHN-family ions were found to be indicative of BBOA, whereas C₅H₈O₅⁺, C₅H₆O⁺, and C₈H₉O₄⁺ were identified as potential tracers for BSOA; they lead the identification of BBOA- and BSOA-like factors. CROA factor, related to aged fossil fuel combustion and aged biomass material combustion, was also identified. Different PMF factors exhibited differences in water solubility, with relatively water-insoluble characteristics of compounds containing CROA aromatic structures. This study highlights the usefulness of polarity-resolved factor analysis in understanding diverse OA sources and opens the door for the characterization of climate- and air-quality-related properties of BBOA and BSOA.

Received: 24 Feb 2026 – Discussion started: 16 Mar 2026

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.

Download & links

Preprint (PDF, 2155 KB)

Supplement (1478 KB)

Download & links

Qianzhe Sun, Ruichen Zhou, Sho Ohata, Chiaki Shirota, Tuukka Petäjä, Ilona Ylivinkka, Lauri Ahonen, Markku Kulmala, and Michihiro Mochida

Status: open (until 27 Apr 2026)

Post a comment Subscribe to comment alert

RC1:
'Comment on egusphere-2026-1023', Anonymous Referee #1, 27 Mar 2026 reply
Sun et al. present a year-long offline HR-ToF-AMS study of polarity-resolved organic aerosol fractions from Hyytiälä, with PMF used to distinguish BBOA-like, BSOA-like, CROA, MO-OOA, and HOA components. The study is novel and potentially valuable because the polarity-based fractionation appears to provide additional chemical resolution beyond conventional online AMS-PMF approaches, particularly for separating biomass-burning and biogenic influences. The manuscript is generally well done, and I believe it is suitable for publication after minor revision.
My comments are mainly related to clarification, figure presentation, and several points where the interpretation could be made easier to follow.
Low concentrations and uncertainty (Lines 225–226)

The winter concentrations of the three OA fractions are quite small (HP-WSOM 0.13, HULIS 0.31, and WISOM 0.17 µg m⁻³). Please clarify the associated uncertainty for such low values, ideally in relative terms or in comparison with the uncertainty of total OA. This would help the reader assess the robustness of the seasonal interpretation.

Source-region discussion could be more specific (Lines 236–240; Fig. 3)

The discussion of the PSCF results remains somewhat broad. The text states that air masses passed over Scandinavia and other parts of Europe, but from Fig. 3 the western-European influence does not appear equally clear for both events. Please specify more precisely which parts of Europe are implicated for P1 and P2. In addition, the map readability in Fig. 3 should be improved because the current figure is difficult to interpret.

Figure numbering / SI cross-reference inconsistency

Please carefully check the figure numbering throughout the manuscript and Supplement. In the Methods, all sample trajectories are said to be shown in Figure S4 (Lines 180–181), and the PMF stability analysis is also said to be shown in Figure S4 (Lines 193–194). Later, in the Results, the backward trajectory analysis is instead referred to as Fig. S6 (Line 242). This is confusing and should be corrected throughout the manuscript and SI.

Clarify relation to previous SVOOA/LVOOA terminology (Lines 244–245 and Section 3.2.1)

Since earlier Hyytiälä studies identified SVOOA/LVOOA, it would be useful to briefly explain for readers how these previously reported factors relate to the MO-OOA terminology adopted here. This would make it easier to place the current results in the context of previous source-apportionment work at the site.

PMF factor selection and apparent typo (Lines 270–272; Fig. 4 caption)

Please comment briefly on whether a six-factor or higher-factor solution was examined and why it was not retained. Also, there appears to be a typo in the description of the four-factor solution: it is written as “MO-OOA, BSOA-like factor, BSOA-like factor, and HOA,” where one of the repeated BSOA-like entries is presumably intended to be BBOA-like. The same duplication appears in the Fig. 4 caption (“MO-OOA, BSOA-like, BSOA-like, CROA, and HOA”). Please correct this in both the main text and figure caption.

Paragraph logic around HOA/BSOA-like discussion (Lines 292–296)

The paragraph beginning with HOA is somewhat awkward because the section is focused on the BSOA-like factor. I suggest restructuring it so that the paragraph starts from the BSOA-like behavior and then introduces HOA as a secondary observation. As written, the logic is somewhat difficult to follow.

Figure guidance for the BSOA-like tracer discussion (Lines 297–307)

In the paragraph discussing the selected BSOA-related fragment ions, it would help the reader if the relevant figure reference were given at the start of the paragraph. At present, the text discusses the ions first and only later says that the results are shown in Fig. 5b. Since the previous paragraph already refers to Fig. 6, this section becomes harder to follow than necessary.

Seasonality of C₅H₆O⁺ / tracer discussion (Line 314)

Since C₅H₆O⁺ is presented as a particularly source-specific tracer for the BSOA-like factor, please comment more explicitly on its seasonal behavior in the main text. That would further strengthen the interpretation.

Tree species / regional vegetation context (Line 335)

When using the lodgepole pine AMS spectrum and discussing MBO emissions from coniferous trees such as pines, please clarify whether this is representative of the dominant tree species in the region surrounding the site.

P1 and P2 should be labeled more consistently (Line 341 and related figures)

P1 and P2 are introduced clearly in Fig. 2 and in the text, but it would help the reader if these periods were identified consistently throughout all relevant time-series figures, especially where their interpretation is discussed later.

Sulfate associated with BBOA-like periods (Lines 347, 354–355)

The co-variation between nss-SO₄²⁻ and the BBOA-like factor is interesting, but the interpretation remains somewhat underdeveloped. Since the reported correlation is only moderate (r = 0.45), please discuss more explicitly what processes or source regions might explain this association and how selective this relationship really is relative to the other PMF factors.

Formatting consistency (Line 371 and elsewhere)

Please check the formatting of m/z and ion notation throughout the manuscript for consistency.

CROA interpretation / other combustion sources (Line 394)

The discussion of CROA is interesting. In addition to aged fossil-fuel emissions and aged biomass-combustion material, could the authors briefly comment on whether coal combustion may also contribute to this aromatic factor, or explain why that possibility is unlikely in this setting?

Interesting polarity/solubility anomalies (Lines 451, 455, 490)

There are a few periods in the later polarity-distribution discussion that appear noteworthy, including elevated MO-OOA in the water-insoluble fraction in late July, the small winter increase in BSOA-like material, and the behavior of HP-WSOM during the same period. Please comment on whether these features reflect genuine compositional changes or could partly result from factor mixing/rotational ambiguity and larger uncertainty under low-concentration conditions.

Overall, I find the study novel and suitable for ACP after these mainly clarifying and presentation-related revisions.

Reply
Citation: https://doi.org/10.5194/egusphere-2026-1023-RC1
RC2: 'Comment on egusphere-2026-1023', Anonymous Referee #2, 09 Apr 2026 reply

The author performed a year-long offline analysis of PM1 filter samples collected at SMEAR II, Hyytiälä. The samples were fractionated by polarity into HP-WSOM, HULIS, and WISOM, followed by HR-AMS measurements and PMF analysis. Five factors were resolved, including MO-OOA, BBOA-like, BSOA-like, CROA, and HOA. The polarity-based fractionation improved source separation of OA, particularly between BBOA and BSOA, and provided additional insights into solubility and seasonality of different OA components. AMS CHN-family ions are identified as potential markers of BBOA, which can be an important complement to more conventional BBOA indicators such as levoglucosan-related fragments. The dataset is promising, and the link between OA factor composition and polarity is interesting. I think the manuscript could be suitable for ACP after major revision.
1. Section 1, lines 80-83: The AMS fragment ions m/z 60 (C₂H₄O₂⁺) and m/z 73 (C₃H₅O₂⁺) are commonly associated with levoglucosan and have been widely used as markers of fresh BBOA in previous studies. Although the diagnostic value of these two ions is weaker for aged BBOA, they are still important reference markers and should be acknowledged in the introduction.
2. Section 2.2, lines 126-129: Please clarify the extraction conditions in more detail. Was the extraction bottle capped and sealed during sonication? Was the sonication done in an ice bath or under other temperature-controlled conditions?
3. Section 2.2, lines 131-135: Please provide more details on the SPE procedure. Was the SPE cartridge conditioned and equilibrated before sample loading? Why was the aqueous extract acidified to pH 2 before SPE? Were the filter extraction and SPE procedures performed in the dark? What was the approximate duration of the full extraction and SPE workflow? Prolonged light exposure could potentially alter the OA composition through photooxidation.
Please justify the definitions of the two eluted fractions. Why is the first portion assigned as high polarity-WSOM and the retained portion as HULIS? A brief explanation supported by relevant literature would be helpful.
4. Section 2.3: Please clarify whether blanks were analyzed, for example, by subjecting a blank filter to the same extraction, SPE, and AMS workflow as that used for the ambient samples. These blank measurements can provide background OM concentrations and AMS mass spectra and would help readers estimate potential contaminations from filter material and sample-processing steps. These data are particularly important when examining low-concentration samples.
5. Section 2.4, lines 181-182: Please justify the use of 10-day back trajectories. Although HYSPLIT can be run over this duration, trajectory uncertainty increases with transport time, which may affect the interpretation of the trajectory and PSCF results. Most receptor-oriented trajectory studies usually use shorter durations (e.g., 48-120 h) for source-region analysis. Please explain why a 10-day duration is used in this study.
6. Section 2.5: Please clarify the PMF input and preprocessing in more detail. How many variables were included? Were UMR data, HR data, or both used? Only organic ions or also any inorganic species were included? Please also describe any pretreatment applied to the error matrix before PMF, such as downweighing of noisy ions or CO₂⁺-related ions.
7. Section 2.5, lines 191-192: The author states that "HP-WSOM, HULIS, WISOM, and WSOM were processed together." If these four datasets were merged into a single PMF input matrix, please describe exactly how this was done. Were the matrices combined vertically or horizontally? These two approaches can lead to different types of PMF solutions and provide different scientific information.
Well, based on the PMF results shown in Figure 4, it appears that the datasets may have been combined vertically. If that is correct, please state this explicitly in the Methods section. The author should also briefly discuss why a "vertical combination" approach was used in this PMF analysis.
In addition, I’m curious about the PMF results that could be obtained if the input matrices were combined horizontally. In that setup, distinct MS profiles for the HP, HULIS, and WISOM fractions can be resolved for each PMF factor.
8. Section 3.1.3, lines 243: The author states that "The backward trajectory analysis (Fig. S6) reveals the possibility of long-range transport for P1." This interpretation would benefit from more careful justification. With a 10-day trajectory length, the older portions of the trajectories are subject to large uncertainties, and longer trajectories typically span much broader spatial domains. These factors may bias the PSCF analysis towards emphasizing remote source regions.
9. Section 3.2.3: When evaluating whether an AMS fragment ion can serve as a marker for BSOA, it’s better to consider not only its correlations with the factor and external references, but also its relative abundance in the factor MS profile. I encourage the author to also report the relative abundances of the proposed marker ions (e.g., C₅H₆O⁺, C₇H₉O₃⁺, and C₉H₁₃O₄⁺) in the factor MS.
10. Section 3.3.3, line 467-470: When interpreting seasonality and source influences, both the absolute concentration and the fractional contribution of WISOM should be considered. Although the fractional contribution of WISOM increased (Figure 12), the absolute concentration of WISOM was lower in winter (Figure 2). The statement "This seasonality likely reflects increased inputs of fossil fuel-derived aerosols in winter" may need more careful justification.
Minor points:
1. Line 22: Please spell out CROA at its first occurrence.
2. Line 65: Change "isolated by using SPE" to "isolated using SPE".
3. Lines 75-77: This sentence doesn't make sense to me. I think fragmentation in AMS breaks molecules into smaller ions, which leads to loss of much of the original molecular structure and therefore reduces molecular specificity.
4. General comment on terminology: Throughout the manuscript, the authors use terms such as "chemical structural information" and "chemical structures" to describe the information obtained from AMS. In my view, this wording may be somewhat too strong. AMS provides valuable information on elemental composition, fragment ion patterns, and broad chemical composition, but it does not directly resolve molecular structures in a strict sense. I suggest using more cautious language, such as "chemical composition" and "chemical information".
5. Table S2: Please specify in the table note which instrument was used to determine the WSOM, HULIS, and HP-WSOM concentrations.
6. Line 139: Please provide the manufacturer and model information for the gas exchange device.
7. Please check the figure numbering and cross-references throughout the manuscript and supplement.
Line 181: The sample trajectories are cited as Figure S4, but they appear in Figure S7.
Line 242: The back trajectories are cited as Figure S6, but they appear in Figure S8.
Line 219: "Fig. 2a" should be changed to "Fig. 2"
8. The section numbering skips from 3.1.1 to 3.1.3.
9. Figure 4 caption repeats BSOA-like and omits BBOA-like.
10. Line 316: "BBOA" should be corrected to "BSOA".
11. Figure 5b: Please clarify how the correlations were calculated. Were they based on the summed concentrations across HP-WSOM, HULIS, and WISOM?
12. Figure 6: In the figure caption, please clarify that the correlations are of different types. Some are based on mass spectral similarity and others are based on time series relationships.
13. Line 338: How were nss-K⁺ and nss-SO₄^2- calculated?
14. Figure 11: It may be helpful to add a summary panel showing the seasonal average contributions of the factors.

Reply

Citation: https://doi.org/10.5194/egusphere-2026-1023-RC2
RC3:
'Comment on egusphere-2026-1023', Anonymous Referee #3, 14 Apr 2026 reply
The authors utilized an offline aerosol mass spectrometer coupled with pre-separation of organic aerosols into three groups of substances based on water solubility and polarity. The authors further analyzed the organic aerosol samples collected in Hyytiälä over one year, followed by PMF analysis, aiming to distinguish the composition and factors of biomass burning aerosols and biogenic organic aerosols. Overall, the offline HR-AMS analysis method coupled with pre-separation of OA is novel, and I recommend publication of this paper in ACP after major revision.
Major comments:
Please provide more details on the analysis method in the Method section. For example, how were the one-year aerosol samples stored? Were any background measurements taken, and are the results presented background-subtracted?

WISOM was extracted using several organic solvents, which could contribute fragmentation ions in the following AMS measurement. Could the authors comment on whether these organic solvents could contribute signals to the five PMF factors? Similarly, in the extraction of WSOM, were the HCl and methanol removed before the OA was analyzed by AMS? How can we evaluate the effect of these solvents on the AMS mass spectraand the resulted PMF factors?

A nebulizer was used to generate aerosols. Please add more details on the nebulizer, e.g., operation flow rate and inlet pressure. Since the compounds in OA may have different volatilities, will there be potential loss of semi-volatile compounds in the setup or different efficiencies in generating the aerosols? Could the authors comment on the effect of size-dependent transmission efficiency of AMS on the quantification of aerosols generated from the nebulizer? Why did the authors generate aerosols using compressed air and then transfer to Ar?

The calculation of SPE extraction efficiency: Does the mass concentration in μg m⁻³ in Table S2 refer to the concentration of the organic matters in the aqueous solution or in the aerosols? If it is the concentration in aerosols, how was the extraction efficiency estimated? More detailed information would be helpful.

Minor comments:
Please add the full name of CROA in the abstract.

The abbreviation for "OAs" is duplicated in lines 30 and 39.

Line 57: What do the "additional tools" refer to?

Line 71: What does "each fraction" refer to?

Section 3.1.2 is missing.Section 3.1.3: it would be helpful to add a sentence to summarize the possible OA sources of P1 and P2.

Is the quantification of OA based on V-mode or W-mode AMS results? Are the mass spectra used for PMF analysis based on V-mode or W-mode results? Please clarify.

Line 232: What is the PSCF analysis? Similar comment on line 234: “DMPS measurement”. Please add more information on them to the Method section. Additionally, why did the authors choose the 75th percentile instead of the 90th or 60th percentile in the PSCF analysis?

Line 273: A potential typo: two “BSOA-like factors” in the four-factor solution. Or is it one BSOA-like factor and one BBOA-like factor?

Line 294-296: Not sure I agree with the interpretation, because the concentrations of most PMF factors increased in P2.

Figure 10: The y-axis scaling cuts off some prominent peaks. Either use broken axes or state the scaling explicitly in the caption.

Reply
Citation: https://doi.org/10.5194/egusphere-2026-1023-RC3
RC4: 'Comment on egusphere-2026-1023', Anonymous Referee #4, 15 Apr 2026 reply

Comments are attached.

Reply

Citation: https://doi.org/10.5194/egusphere-2026-1023-RC4

Qianzhe Sun, Ruichen Zhou, Sho Ohata, Chiaki Shirota, Tuukka Petäjä, Ilona Ylivinkka, Lauri Ahonen, Markku Kulmala, and Michihiro Mochida

Supplement

https://doi.org/10.5194/egusphere-2026-1023-supplement

Qianzhe Sun, Ruichen Zhou, Sho Ohata, Chiaki Shirota, Tuukka Petäjä, Ilona Ylivinkka, Lauri Ahonen, Markku Kulmala, and Michihiro Mochida

Viewed

Total article views: 215 (including HTML, PDF, and XML)

HTML	PDF	XML	Total	Supplement	BibTeX	EndNote
139	67	9	215	30	8	17

HTML: 139
PDF: 67
XML: 9
Total: 215
Supplement: 30
BibTeX: 8
EndNote: 17

Views and downloads (calculated since 16 Mar 2026)

Month	HTML	PDF	XML	Total
Mar 2026	103	58	9	170
Apr 2026	36	9	0	45

Cumulative views and downloads (calculated since 16 Mar 2026)

Month	HTML	PDF	XML	Total
Mar 2026	103	58	9	170
Apr 2026	36	9	0	45

Viewed (geographical distribution)

Total article views: 216 (including HTML, PDF, and XML) Thereof 216 with geography defined and 0 with unknown origin.

Country	#	Views	%

Latest update: 25 Apr 2026

Short summary

Source identification of atmospheric aerosols is crucial for understanding their properties and resulting environmental impacts. By mass spectrometry for aerosol samples, organic aerosols in a European boreal forest were apportioned to five source-related types based on chemical structure, highlighting the importance of biomass-originated organics. Polarity-based fractionation advanced source apportionment, which is expected to improve the capability of property analysis for organic aerosols.


Total:	0
HTML:	0
PDF:	0
XML:	0