the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 17 Jun 2025
Measurement report: Molecular Insights into Organic Aerosol Sources and Formation at a Regional Background Site in South China
Abstract. Organic aerosols (OA) in fine particulate matter (PM) significantly impact air quality, climate, and human health. Understanding their chemical composition and quantifying their sources are crucial for assessing their formation and human-related effects. In this study, we examined OA at a background site in South China, analyzing from bulk to molecular levels, utilizing a high‐resolution time‐of‐flight aerosol mass spectrometer (AMS), a thermal-desorption aerosol gas-chromatograph-mass spectrometer (TAG-MS), and an electrospray ionization high‐resolution orbitrap mass spectrometer (HR‐MS). Our findings indicate that low-oxidized and more-oxidized oxygenated OA (LO-OOA1 and MO-OOA) comprised over 70 % of the OA mass. Biomass burning and gas-phase secondary OA (gas-pSOA) were the primary sources of LO-OOA1, while the high-oxidization degree of MO-OOA was mainly due to isoprene-derived SOA. HR-MS analysis revealed that oxidation processes significantly increased the accumulation of CHO compounds, and human-biological interactions enhanced the diversity of CHON compounds. Using a constrained non-negative matrix factorization method on offline HR-MS data, we identified differences in molecular associations between OA origins. Overall, our results underscore the prominent impact of anthropogenic emissions and their photo-oxidation on ambient OA, emphasizing the need for local emission reduction and regional cooperation to control OA in areas with low PM pollution but high O3 levels.
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RC1: 'Comment on egusphere-2025-2264', Anonymous Referee #1, 04 Jul 2025
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This manuscript presents a comprehensive investigation of organic aerosol (OA) composition, sources, and oxidative evolution in Hong Kong, utilizing a combination of high-resolution analytical techniques, including HR-AMS, TAG-TOF-MS, and HPLC-HR-MS. The authors demonstrate that during the COVID-19 lockdown period, low-oxidation OA was primarily influenced by biomass burning and gas-phase secondary organic aerosol (gas-pSOA), largely driven by air mass transport from mainland China. In contrast, high-oxidation OA was dominated by secondary inorganic aerosols (SIA), gas-pSOA, and biogenic SOA, with isoprene-derived SOA identified as the major contributor. HR-MS results indicate that CHO and CHON compounds dominated the OA composition, contributing over 60% of signal intensity and more than 40% of molecular formulas. Constrained-NMF analysis suggests that atmospheric oxidation promoted CHO accumulation, while nitrogen-related reactions increased molecular diversity. Overall, this study offers valuable insights into the molecular complexity and transformation of OA under different atmospheric conditions. I recommend publication after minor revision. However, several specific aspects require clarification or improvement prior to acceptance:
- Line 20：This is an interesting and innovative approach to source apportionment at the molecular level. The authors applied a constrained NMF model to offline HR-MS data to investigate molecular differences among various OA sources. However, the specific differences identified between these sources are not clearly presented. It is recommended that the authors elaborate on the key distinguishing features—such as dominant compound classes, oxidation levels, or representative molecular formulas—that characterize each OA source.
- Lines 175-180：The authors suggest that LO-OOA1 is more influenced by anthropogenic photochemical processes involving VOCs and NOx, while MO-OOA is primarily linked to biogenic SOA formation through ozone oxidation. However, the distinction between their "primary nature" and "secondary formation pathways" remains somewhat ambiguous. Could the authors clarify how LO-OOA1 is considered to have a more primary character despite its apparent link to secondary photochemical reactions?
- Lines 179：The authors state that MO-OOA shows good correlations with O₃ and biogenic SOA tracers. Could the authors provide the specific correlation coefficients (e.g., r values) and p-values to quantitatively support this statement, particularly for the relationship between MO-OOA and O3?Including these statistical details in the main text or supplementary figures would enhance the transparency and robustness of the analysis. The same places that need to be modified are in Lines 198 and 215.
- The x-axis in Figure 2a seems to be incorrect, and the symbol/icon used in Figure 3 is unclear. Please revise it to improve clarity and readability.
- Lines 235-238: The authors state that SIA contributed the most to MO-OOA (38%), yet also suggest that highly oxidized organics in MO-OOA might not be primarily related to SIA processes. This appears somewhat contradictory. Could the authors clarify how they reconcile the high SIA contribution with the conclusion that MO-OOA is more closely linked to biogenic SOA processes?
- Line 370-375: The authors note that the contribution of gas-pSOA estimated by the constrained-NMF method was 1.4 times higher than that from the tracer-based PMF model, while the SIA contribution was significantly lower. Could the authors clarify how they addressed this discrepancy, and whether any compound misclassification between SIA-related and gas-pSOA-related species may have biased the NMF results?
Citation: https://doi.org/10.5194/egusphere-2025-2264-RC1
Data sets
Molecular Insights into Organic Aerosol Sources and Formation at a Regional Background Site in South China [Data set] H. Jiang et al. https://zenodo.org/records/15675889
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