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

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:

1. 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.
2. 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.
3. 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.
4. 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.