Influence of anthropogenic pollution on the molecular composition of organic aerosols over a forest site in the Qinling Mountains region of central China

Zhang, Xin; Li, Lijuan; Li, Jianjun; Lin, Yue; Cheng, Yan; Wang, Rui; Xing, Shuyan; Zhu, Chongshu; Cao, Junji; Han, Yuemei

doi:10.5194/egusphere-2025-519

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https://doi.org/10.5194/egusphere-2025-519

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21 Feb 2025

| 21 Feb 2025

Influence of anthropogenic pollution on the molecular composition of organic aerosols over a forest site in the Qinling Mountains region of central China

Xin Zhang, Lijuan Li, Jianjun Li, Yue Lin, Yan Cheng, Rui Wang, Shuyan Xing, Chongshu Zhu, Junji Cao, and Yuemei Han

Abstract. Biogenic organic aerosols interacting with anthropogenic pollutants lead to large uncertainties in aerosol properties and impacts, yet the underlying mechanisms remain to be fully elucidated. To explore the anthropogenic–biogenic interactions in the Qinling Mountains region of central China, we investigated the molecular composition of organic aerosols in atmospheric PM_2.5 at a forest site in summer and winter of 2021/2022, using ultrahigh performance liquid chromatography coupled with Orbitrap mass spectrometry. Organic species were more abundant and chemically diverse in winter compared with those in summer, as revealed by their higher numbers and peak area intensities. The molecular characteristics of organic species exhibited distinct seasonal variabilities, with higher peak-area-weighted mean values of molecular weight and oxidation state but lower unsaturation degree in summer, possibly associated with more biogenic emissions and intense photochemical processes. A variety of organic tracer species were identified in the two seasons, among which the biogenic ones were relatively more abundant in summer, contrasting with the substantial increase of anthropogenic ones in winter. A higher ambient relative humidity, except for heavy precipitation, usually promoted the production of nitrogen- and sulfur-containing organic species by involving more anthropogenic pollutants. The synergistic effects of meteorology and anthropogenic pollution greatly affected the organic aerosol production in this forest atmosphere, thereby altering their molecular composition and related properties under different environmental conditions. The combined set of results herein provides direct evidence for the anthropogenic perturbations on air quality, atmospheric chemistry, and associated climate impacts in the Qinling Mountains region.

Received: 04 Feb 2025 – Discussion started: 21 Feb 2025

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Journal article(s) based on this preprint

28 Nov 2025

Influence of anthropogenic pollution on the molecular composition of organic aerosols over a forest site in the Qinling Mountains region of central China

Xin Zhang, Lijuan Li, Jianjun Li, Yue Lin, Yan Cheng, Rui Wang, Shuyan Xing, Chongshu Zhu, Junji Cao, and Yuemei Han

Atmos. Chem. Phys., 25, 17139–17158, https://doi.org/10.5194/acp-25-17139-2025,https://doi.org/10.5194/acp-25-17139-2025, 2025

Short summary

Xin Zhang, Lijuan Li, Jianjun Li, Yue Lin, Yan Cheng, Rui Wang, Shuyan Xing, Chongshu Zhu, Junji Cao, and Yuemei Han

Interactive discussion

Status: closed

RC1: 'Comment on egusphere-2025-519', Anonymous Referee #1, 22 May 2025

In this study, Zhang et al. report an extensive molecular characterisation of organic aerosol in particulate matter (PM_2.5) from a forest site in the Qinling mountains, China, and investigated the influence of anthropogenic pollution on the aerosol composition. For this they sampled 33 filter samples in summer and wintertime, used liquid extraction and measured the extracts with an ultrahigh-performance liquid chromatography coupled to high-resolution Orbitrap mass spectrometry. With a non-target analysis known and unknown compounds were detected and identified. The combination of molecular fingerprints, air quality measurements, meteorological data as well as back-trajectories enables detailed interpretation of origin and transformation pathways of the sampled aerosol. Tracer species confirm the interpretation of more influence from biogenic precursors in summer and a more diverse and largely anthropogenic influenced composition in winter.

The authors have combined their comprehensive results and have produced a detailed characterization of the molecular composition of organic aerosol. The manuscript has a good structure, meaningful illustrations and is written clear and precise. The work is worth to be published in “Atmospheric Chemistry and Physics” with some minor comments.
Comments

L84: Delete “city” in “[…] 50 km southwest of the megacity city Xi’an, as shown […]”.

L102: Have the authors considered that ultrasonication can influence the chemical composition due to free radical production? (Miljevic et al., 2014)

L142: Calculating HYSPLIT trajectories at 34.06° N, 108.34° E, 500 m height above ground level result in a height of 1885 m above sea level, since the height of the cell grid is already 1385 m. Can the authors comment on why they used 500 m height above ground level?

L205: Can the compounds also have different transmission efficiencies in the mass spectrometer? And is therefore not just an effect of different ionization efficiencies?

L206: Can the authors clarify what they mean with “technical limitations”?

The lack of authentic standards (and the fact that many compounds in ambient PM are not even precisely characterized) does not allow a quantitative approach on such a highly complex composition, independent of the analytical devices used. For example Ma et al. (2022) and Evans et al. (2024) showed that semi-quantification is possible but with great uncertainties.

Figure 3: The legend is not optimally visible in panel b. Since the legends applies to all panels, maybe a central positioning above would be easier to see (compare with the legend of Fig. 4).

Figure 5: In the caption the authors explain “ […] dashed lines inside boxes […]”, but the lines are solid.

Can the authors explain why they show box plots and violin plots? Since the data is not bimodal distributed, the reader can hardly get any additional information from both plots.

L311: The comparison of tracer species was only made based on the sum formula? Have the authors considered fragmentation spectra to identify compounds with databases to get a higher level of confidence (e.g. aerosolomics (Thoma et al. (2022)) or the mzCloud database)?

L336: Have fragmentation experiments carried out to validate the assignment of the compound classes? The functional groups of organosulfates (m/z 96.9601 (HSO₄^–) and m/z 79.9573 (SO₃^–)) as well as nitrate groups (m/z 61.9883 (NO₃^–)) are very strongly represented in the fragmentation spectra and a clear indicator for organosulfates and nitrooxy organosulfates.
References

Miljevic, B., Hedayat, F., Stevanovic, S., Fairfull-Smith, K. E., Bottle, S. E., and Ristovski, Z. D. (2014). To Sonicate or Not to Sonicate PM Filters: Reactive Oxygen Species Generation Upon Ultrasonic Irradiation. Aerosol Science and Technology, 48(12), 1276–1284. https://doi.org/10.1080/02786826.2014.981330
Jialiang Ma, Florian Ungeheuer, Feixue Zheng, Wei Du, Yonghong Wang, Jing Cai, Ying Zhou, Chao Yan, Yongchun Liu, Markku Kulmala, Kaspar R. Daellenbach, and Alexander L. Vogel (2022). Nontarget Screening Exhibits a Seasonal Cycle of PM2.5 Organic Aerosol Coposition in Bejing. Environmental Science & Technology, 56 (11), 7017-7028. https://doi.org/10.1021/acs.analchem.4c00819
Rhianna L. Evans, Daniel J. Bryant, Aristeidis Voliotis, Dawei Hu, HuiHui Wu, Sara Aisyah Syafira, Osayomwanbor E. Oghama, Gordon McFiggans, Jacqueline F. Hamilton, and Andrew R. Rickard (2024). A Semi-Quantitative Approach to Nontarget Compositional Analysis of Complex Samples. Analytical Chemistry. 96 (46), 18349-18358. https://doi.org/10.1021/acs.analchem.4c00819
Thoma, M., Bachmeier, F., Gottwald, F. L., Simon, M., and Vogel, A. L. (2022). Mass spectrometry-based Aerosolomics: a new approach to resolve sources, composition, and partitioning of secondary organic aerosol, Atmos. Meas. Tech., 15, 7137–7154. https://doi.org/10.5194/amt-15-7137-2022

Citation: https://doi.org/10.5194/egusphere-2025-519-RC1
RC2:
'Comment on egusphere-2025-519', Anonymous Referee #2, 08 Jun 2025
This manuscript presents observational evidence of the seasonal variability in organic aerosol composition. However, the research approach—combining seasonal sampling with high-resolution mass spectrometry—has been widely reported in previous studies. The study does not clearly provide novel mechanistic insights or substantial advancements in the understanding of anthropogenic–biogenic interactions. As such, the conclusions drawn lack originality and scientific novelty. I regret to conclude that the manuscript, in its current form, does not meet the publication standards of the journal. My main concerns are as follows:
Line 305: this interpretation lacks strong causal linkage, as biogenic emissions—particularly monoterpene-derived secondary organic aerosols (SOA)—also predominantly fall within the C₆–C₁₁ range. Therefore, the contribution from biogenic precursors should not be overlooked when interpreting the molecular composition in this carbon number range.

Lines 365-370: here only discuss the seasonal variation of molecules identified under the ESI⁻ mode using VK diagrams, while omitting the analysis of VK characteristics of compounds detected in the ESI⁺ mode. This incomplete treatment results in a weak logical connection between the data presented and the conclusions drawn, leading to a lack of coherence in the overall interpretation. Given that ESI⁺ typically captures a distinct subset of organic compounds—often including important nitrogen- and sulfur-containing species—its exclusion leaves a significant gap in the discussion. I recommend the authors include a comparative analysis of VK diagrams under both ionization modes to ensure a more comprehensive and balanced understanding of the seasonal dynamics of organic aerosol composition.

Lines 395-410: The conclusions regarding the influence of relative humidity on the molecular characteristics of organic species are solely based on compounds identified under the ESI⁻ mode. This raises concerns about the completeness of the analysis, as ESI⁻ and ESI⁺ modes often detect different classes of organic compounds with distinct physicochemical properties. Relying only on ESI⁻ data may lead to a biased or incomplete understanding of humidity-driven processes. A more balanced interpretation should incorporate results from both ionization modes to better capture the full range of organic species affected by relative humidity.

Lines 450-475: The authors primarily rely on positive and negative correlations with gaseous and particulate pollutants, as well as SOR, NOR, and Ox, to infer their influence on the chemical composition of organic aerosols. However, the correlation-based analysis lacks mechanistic support, making the conclusions less convincing. Furthermore, the discussion remains rather superficial and does not adequately elucidate the underlying interactions between pollutants and organic aerosol formation. It is recommended that the authors incorporate mechanistic insights from previous literature to strengthen the scientific basis and credibility of their conclusions.
Citation: https://doi.org/10.5194/egusphere-2025-519-RC2
AC1: 'Responses to Referees' Comments on egusphere-2025-519', Yuemei Han, 20 Jul 2025

Please find enclosed the authors' responses to two referees' comments on our manuscript (egusphere-2025-519) .
A copy of the manuscript and supplement with all the changes and other minor corrections tracked is also attached at the end for reference.

Citation: https://doi.org/10.5194/egusphere-2025-519-AC1

Interactive discussion

Status: closed

RC1: 'Comment on egusphere-2025-519', Anonymous Referee #1, 22 May 2025

In this study, Zhang et al. report an extensive molecular characterisation of organic aerosol in particulate matter (PM_2.5) from a forest site in the Qinling mountains, China, and investigated the influence of anthropogenic pollution on the aerosol composition. For this they sampled 33 filter samples in summer and wintertime, used liquid extraction and measured the extracts with an ultrahigh-performance liquid chromatography coupled to high-resolution Orbitrap mass spectrometry. With a non-target analysis known and unknown compounds were detected and identified. The combination of molecular fingerprints, air quality measurements, meteorological data as well as back-trajectories enables detailed interpretation of origin and transformation pathways of the sampled aerosol. Tracer species confirm the interpretation of more influence from biogenic precursors in summer and a more diverse and largely anthropogenic influenced composition in winter.

The authors have combined their comprehensive results and have produced a detailed characterization of the molecular composition of organic aerosol. The manuscript has a good structure, meaningful illustrations and is written clear and precise. The work is worth to be published in “Atmospheric Chemistry and Physics” with some minor comments.
Comments

L84: Delete “city” in “[…] 50 km southwest of the megacity city Xi’an, as shown […]”.

L102: Have the authors considered that ultrasonication can influence the chemical composition due to free radical production? (Miljevic et al., 2014)

L142: Calculating HYSPLIT trajectories at 34.06° N, 108.34° E, 500 m height above ground level result in a height of 1885 m above sea level, since the height of the cell grid is already 1385 m. Can the authors comment on why they used 500 m height above ground level?

L205: Can the compounds also have different transmission efficiencies in the mass spectrometer? And is therefore not just an effect of different ionization efficiencies?

L206: Can the authors clarify what they mean with “technical limitations”?

The lack of authentic standards (and the fact that many compounds in ambient PM are not even precisely characterized) does not allow a quantitative approach on such a highly complex composition, independent of the analytical devices used. For example Ma et al. (2022) and Evans et al. (2024) showed that semi-quantification is possible but with great uncertainties.

Figure 3: The legend is not optimally visible in panel b. Since the legends applies to all panels, maybe a central positioning above would be easier to see (compare with the legend of Fig. 4).

Figure 5: In the caption the authors explain “ […] dashed lines inside boxes […]”, but the lines are solid.

Can the authors explain why they show box plots and violin plots? Since the data is not bimodal distributed, the reader can hardly get any additional information from both plots.

L311: The comparison of tracer species was only made based on the sum formula? Have the authors considered fragmentation spectra to identify compounds with databases to get a higher level of confidence (e.g. aerosolomics (Thoma et al. (2022)) or the mzCloud database)?

L336: Have fragmentation experiments carried out to validate the assignment of the compound classes? The functional groups of organosulfates (m/z 96.9601 (HSO₄^–) and m/z 79.9573 (SO₃^–)) as well as nitrate groups (m/z 61.9883 (NO₃^–)) are very strongly represented in the fragmentation spectra and a clear indicator for organosulfates and nitrooxy organosulfates.
References

Miljevic, B., Hedayat, F., Stevanovic, S., Fairfull-Smith, K. E., Bottle, S. E., and Ristovski, Z. D. (2014). To Sonicate or Not to Sonicate PM Filters: Reactive Oxygen Species Generation Upon Ultrasonic Irradiation. Aerosol Science and Technology, 48(12), 1276–1284. https://doi.org/10.1080/02786826.2014.981330
Jialiang Ma, Florian Ungeheuer, Feixue Zheng, Wei Du, Yonghong Wang, Jing Cai, Ying Zhou, Chao Yan, Yongchun Liu, Markku Kulmala, Kaspar R. Daellenbach, and Alexander L. Vogel (2022). Nontarget Screening Exhibits a Seasonal Cycle of PM2.5 Organic Aerosol Coposition in Bejing. Environmental Science & Technology, 56 (11), 7017-7028. https://doi.org/10.1021/acs.analchem.4c00819
Rhianna L. Evans, Daniel J. Bryant, Aristeidis Voliotis, Dawei Hu, HuiHui Wu, Sara Aisyah Syafira, Osayomwanbor E. Oghama, Gordon McFiggans, Jacqueline F. Hamilton, and Andrew R. Rickard (2024). A Semi-Quantitative Approach to Nontarget Compositional Analysis of Complex Samples. Analytical Chemistry. 96 (46), 18349-18358. https://doi.org/10.1021/acs.analchem.4c00819
Thoma, M., Bachmeier, F., Gottwald, F. L., Simon, M., and Vogel, A. L. (2022). Mass spectrometry-based Aerosolomics: a new approach to resolve sources, composition, and partitioning of secondary organic aerosol, Atmos. Meas. Tech., 15, 7137–7154. https://doi.org/10.5194/amt-15-7137-2022

Citation: https://doi.org/10.5194/egusphere-2025-519-RC1
RC2:
'Comment on egusphere-2025-519', Anonymous Referee #2, 08 Jun 2025
This manuscript presents observational evidence of the seasonal variability in organic aerosol composition. However, the research approach—combining seasonal sampling with high-resolution mass spectrometry—has been widely reported in previous studies. The study does not clearly provide novel mechanistic insights or substantial advancements in the understanding of anthropogenic–biogenic interactions. As such, the conclusions drawn lack originality and scientific novelty. I regret to conclude that the manuscript, in its current form, does not meet the publication standards of the journal. My main concerns are as follows:
Line 305: this interpretation lacks strong causal linkage, as biogenic emissions—particularly monoterpene-derived secondary organic aerosols (SOA)—also predominantly fall within the C₆–C₁₁ range. Therefore, the contribution from biogenic precursors should not be overlooked when interpreting the molecular composition in this carbon number range.

Lines 365-370: here only discuss the seasonal variation of molecules identified under the ESI⁻ mode using VK diagrams, while omitting the analysis of VK characteristics of compounds detected in the ESI⁺ mode. This incomplete treatment results in a weak logical connection between the data presented and the conclusions drawn, leading to a lack of coherence in the overall interpretation. Given that ESI⁺ typically captures a distinct subset of organic compounds—often including important nitrogen- and sulfur-containing species—its exclusion leaves a significant gap in the discussion. I recommend the authors include a comparative analysis of VK diagrams under both ionization modes to ensure a more comprehensive and balanced understanding of the seasonal dynamics of organic aerosol composition.

Lines 395-410: The conclusions regarding the influence of relative humidity on the molecular characteristics of organic species are solely based on compounds identified under the ESI⁻ mode. This raises concerns about the completeness of the analysis, as ESI⁻ and ESI⁺ modes often detect different classes of organic compounds with distinct physicochemical properties. Relying only on ESI⁻ data may lead to a biased or incomplete understanding of humidity-driven processes. A more balanced interpretation should incorporate results from both ionization modes to better capture the full range of organic species affected by relative humidity.

Lines 450-475: The authors primarily rely on positive and negative correlations with gaseous and particulate pollutants, as well as SOR, NOR, and Ox, to infer their influence on the chemical composition of organic aerosols. However, the correlation-based analysis lacks mechanistic support, making the conclusions less convincing. Furthermore, the discussion remains rather superficial and does not adequately elucidate the underlying interactions between pollutants and organic aerosol formation. It is recommended that the authors incorporate mechanistic insights from previous literature to strengthen the scientific basis and credibility of their conclusions.
Citation: https://doi.org/10.5194/egusphere-2025-519-RC2
AC1: 'Responses to Referees' Comments on egusphere-2025-519', Yuemei Han, 20 Jul 2025

Please find enclosed the authors' responses to two referees' comments on our manuscript (egusphere-2025-519) .
A copy of the manuscript and supplement with all the changes and other minor corrections tracked is also attached at the end for reference.

Citation: https://doi.org/10.5194/egusphere-2025-519-AC1

Peer review completion

AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload

AR by Yuemei Han on behalf of the Authors (20 Jul 2025) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (29 Jul 2025) by Dara Salcedo

RR by Anonymous Referee #2 (11 Aug 2025)

Suggestions for revision or reasons for rejection

This manuscript presents observational evidence of the seasonal variability in organic aerosol composition. However, it is important to note that the electrospray Ionization interface that couples the UPLC and Orbitrap MS is known for its varying ionization efficiencies across different compounds. The sensitivity of this technique can vary substantially by orders of magnitude, depending on the compound structure, functional group, and the characteristics of the sample matrix. Consequently, the signal intensity in an ESI spectrum does not necessarily serve as a direct and reliable indicator of compound abundance. This variability poses challenges in accurately correlating ESI+ and ESI- ion abundances with the actual abundance of the compounds in a given sample. The high-resolution spectra offered by the Orbitrap MS only provide elemental composition information about the molecules. It is a major leap to connect this data to molecular identities, and discussions regarding functional groups or chemical details could be subjected to large uncertainties. Overall, I perceive this manuscript as lacking of scientific rigor, with conclusions and findings that are short of specificity and novelty.
This study employs a characterization approach based on exact mass formulae in combination with literature references. While high-resolution mass spectrometry offers clear advantages in molecular formula determination, its application to a highly complex mixture such as that investigated here—comprising a large number of compounds with varying degrees of oxidation—presents significant challenges and uncertainties. These include, but are not limited to, mass spectral data processing strategies (e.g., background and noise subtraction), adduct formation and identification, charge state determination, accurate mass measurements, elemental composition assignments, and complex data-dependent acquisition setups. In the present manuscript, structural elucidation relies solely on high-resolution mass spectra without MS/MS (including MS² and MS³) validation for standards and key compounds in field samples, and without the provision of chromatograms, mass spectra, or MS/MS spectra for the main tracer species. These omissions limit the robustness and verifiability of the reported conclusions. Addressing these concerns would require substantial additional experimental work, including targeted MS/MS validation and supplementary analyses, which appear to go beyond the scope of a standard revision. In light of this, I believe the manuscript, in its current form, is not yet suitable for publication in the journal.

1.Majority of discussions in this work are based on the variation or comparison of different compound categories, while the ionization efficiency of different organic compounds varied a lot. I wonder if the authors consider or evaluate the influence of varied ionization efficiency of different compounds. How much the variations of molecular characterization across different seasons are caused by the changing of ionization efficiency?

2.Line 375-380: In Figure 8b, the authors present example results for two days—August 30 (summer) and January 26 (winter)—in ESI- mode. However, the rationale for selecting these specific days is not clearly explained. Are these days representative in terms of meteorological conditions, pollution levels, or biogenic emissions? Without a clear justification, it is difficult to assess whether the observed seasonal differences can be generalized. The authors should clarify the criteria used for day selection and explain how these examples reflect the broader trends discussed in Figure 8c.

3.Lines 507–512 and Lines 336–339: The comparison of tracer species and the identification of clear indicators for organosulfates and nitrooxy organosulfates are noted. However, in HR-MS methods as the one used in this study, several structures proposed by the software can be associated with each formula and confusing and challenging decisions should be made for structural elucidation when hundreds if not thousands of compounds are present in the sample. Although these techniques can provide important information, I believe challenges are still presents when using these analytical techniques and special care should be used when interpreting data and elucidating structure from HR mass spectra. Therefore, additional analysis (e.g. MS/MS) should be conducted!

Hide

ED: Reconsider after major revisions (21 Aug 2025) by Dara Salcedo

AR by Yuemei Han on behalf of the Authors (26 Sep 2025) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (30 Sep 2025) by Dara Salcedo

RR by Anonymous Referee #3 (17 Oct 2025)

Suggestions for revision or reasons for rejection

Reviewer Comment:
This study describes a detailed molecular characterization of PM2.5 sampled from a forest site in the Qinling Mountains, China. Ambient filter samples collected during summer and winter were analyzed by ultrahigh-performance liquid chromatography and high-resolution Orbitrap mass spectrometry followed by a non-target analysis with a focus on the seasonal variability of the organic aerosol composition. Furthermore, air quality measurements, meteorological data, and back-trajectory analyses were integrated to draw detailed conclusions on aerosol origin and chemical transformation pathways. The authors conclude that chemical composition variation indicates a stronger influence from biogenic precursors in summer, contrasting with a more diverse, largely anthropogenic influenced composition in winter.
Combining non-target screening with filter samples from different seasons to investigate differences in organic aerosol composition is a widely used approach leading to already known basic results regarding anthropogenic–biogenic interactions. Orbitrap MS data provides exact mass of measured compounds from which molecular formulae can be derived using a software-based approach. To further confirm the identity of tracer compounds unfortunately only a literature review was carried out while a combination with fragmentation spectra (MS2) and retention time comparison with well-known biogenic and anthropogenic standards would have provided a significantly greater certainty regarding compound identification. Additionally, using electrospray ionization introduces ionization efficiency variations for compounds of different classes and chemical functionalities preventing from direct correlation of compound abundance by comparing measured signal intensities, especially if both polarity modes (ESI- and ESI+) are used.
Although the study has certain methodological weaknesses and does not provide any new fundamental scientific insights, it nevertheless provides a certain overview of the chemical composition of PM2.5 aerosols at Qinling Mountain Station, which contributes to the general understanding of this region and encourages further studies. The manuscript is well written and structured with interesting illustrations that support the results. In general, this study is publishable and fits the thematic focus of ACP and could either be published as Research article or also maybe as Measurement report after addressing some minor comments:

L66: Can you define and describe this specific area (anthropogenic–biogenic intersection zones) more precisely? Why is this zone of special interest regarding aerosol chemical composition?

Figure 1. (b, c): Can you include the origin of the mass concentrations in the caption. On which type of measurements is this data based?

L101: It is rather unusual to provide extraction solvent related information in a weight mass unit. Could you translate here mass into volume?

L102: Ultrasonication is no optimal method for filter extraction as it is known that the harsh conditions in the liquid phase due to free radical formation can lead to substantial changes in the chemical composition. Although cooling might reduce the impact, it will also reduce the extraction efficiency of the solvent mixture and therefore influence the extracted compound composition. Did you compare filter extraction by ultrasonication and orbital shaking for your specific samples?

Literature:
Riesz P, Berdahl D, Christman CL. Free radical generation by ultrasound in aqueous and nonaqueous solutions. Environ Health Perspect. 1985 Dec; 64:233-52. doi: 10.1289/ehp.8564233
Miljevic, B., Hedayat, F., Stevanovic, S., Fairfull-Smith, K. E., Bottle, S. E., & Ristovski, Z. D. (2014). To Sonicate or Not to Sonicate PM Filters: Reactive Oxygen Species Generation Upon Ultrasonic Irradiation. Aerosol Science and Technology, 48(12), 1276–1284. https://doi.org/10.1080/02786826.2014.981330

L118: Why not include phosphorus as element in the data processing? Anthropogenic compounds such as flame retardants often include phosphate groups (e.g. Tricresyl Phosphate). Chlorine may also be worth including due to its use in pesticides, provided this is relevant to the sampling region.
Could you rerun the MZmine data processing including the mentioned elements and give some feedback if you can see relevant compounds, especially when the wind is coming from the city region.

L129: This method for determining the PM mass concentration is highly uncertain. If possible mass concentrations should be based on measurement data like measured particle number size distributions (PNSD).

L257: You should substantiate this statement by mentioning known biogenic emission tracers as MBTCA and pinic acid in the text if found in the data.

Overall, to address the shortcomings of the compound identification (no measured standards and no analyzed fragmentation patterns) you should include the compound identification level system of Schymanski et. al. 2014 stating the level of identification confidence in the manuscript.

Literature:
Identifying Small Molecules via High Resolution Mass Spectrometry: Communicating Confidence
Emma L. Schymanski, Junho Jeon, Rebekka Gulde, Kathrin Fenner, Matthias Ruff, Heinz P. Singer, and Juliane Hollender; Environmental Science & Technology 2014 48 (4), 2097-2098; DOI:10.1021/es5002105

L308: You should discuss this more in detail as all three groups CHOS, CHON and CHONS are influenced by anthropogenic emissions. CHOS and CHON don’t show any difference between summer and winter - why does the CHONS subgroup (especially in ESI-)?

L496: Delete during.

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ED: Publish subject to minor revisions (review by editor) (17 Oct 2025) by Dara Salcedo

AR by Yuemei Han on behalf of the Authors (04 Nov 2025) Author's response Author's tracked changes Manuscript

ED: Publish as is (07 Nov 2025) by Dara Salcedo

AR by Yuemei Han on behalf of the Authors (08 Nov 2025) Manuscript

Journal article(s) based on this preprint

28 Nov 2025

Influence of anthropogenic pollution on the molecular composition of organic aerosols over a forest site in the Qinling Mountains region of central China

Xin Zhang, Lijuan Li, Jianjun Li, Yue Lin, Yan Cheng, Rui Wang, Shuyan Xing, Chongshu Zhu, Junji Cao, and Yuemei Han

Atmos. Chem. Phys., 25, 17139–17158, https://doi.org/10.5194/acp-25-17139-2025,https://doi.org/10.5194/acp-25-17139-2025, 2025

Short summary

Xin Zhang, Lijuan Li, Jianjun Li, Yue Lin, Yan Cheng, Rui Wang, Shuyan Xing, Chongshu Zhu, Junji Cao, and Yuemei Han

Supplement

https://doi.org/10.5194/egusphere-2025-519-supplement

Xin Zhang, Lijuan Li, Jianjun Li, Yue Lin, Yan Cheng, Rui Wang, Shuyan Xing, Chongshu Zhu, Junji Cao, and Yuemei Han

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The influence of anthropogenic pollution on atmospheric organic composition was studied to explore the chemical processes of anthropogenic–biogenic interactions in the Qinling Mountains region of central China using advanced Orbitrap mass spectrometry. Organic molecular species exhibited distinct seasonal variabilities and were more abundant and chemically diverse in winter. Anthropogenic pollution played key roles in altering their composition and related properties under various conditions.


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