the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 13 Jul 2026
Cross-phase partitioning of sulfur-nitrogen ratios and aerosol mixing-state evolution based on single-particle observations
Abstract. Understanding sulfur-nitrogen partitioning is essential for predicting secondary aerosol formation and mixing-state evolution, yet the mechanisms governing its cross-phase coupling remain poorly constrained. Here, we integrate single-particle mass spectrometry (SPA-MS) with air-pollutant and meteorological observations from two regional emission-control periods. We define three sulfur-to-nitrogen ratio metrics in the gas (gSNR), particle (pSNR), and number-based (nSNR) domains, and use causal inference and interpretable machine learning to identify their linkages and environmental drivers. The results reveal a stepwise propagation from precursor composition to particle chemistry and then to population mixing-state evolution. Although gSNR sets the first-order constraint on sulfur-nitrogen partitioning, the aerosol response is strongly particle-type dependent, with more pronounced sulfate enrichment in black-carbon-containing and organic-rich particles than in BC-free particles. Relative humidity (RH) emerges as the primary regulator of this coupling by modulating aerosol liquid water and phase transitions. Under dry conditions, the three SNR metrics diverge and aerosols remain largely externally mixed; under humid conditions, the metrics converge and aerosols evolve toward a more internally mixed state. Our results support the inclusion of RH- and particle-type-dependent parameterizations of cross-phase coupling and chemical heterogeneity in air-quality models.
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Status: open (until 24 Aug 2026)
- RC1: 'Comment on egusphere-2026-3360', Anonymous Referee #2, 30 Jul 2026 reply
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RC2: 'Comment on egusphere-2026-3360', Anonymous Referee #1, 31 Jul 2026
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This manuscript presents an interesting particle-resolved investigation of sulfur–nitrogen ratio metrics and aerosol mixing state evolution based on single-particle mass spectrometer observations during both normal and emission-control periods. By introducing sulfur-to-nitrogen ratio metrics and combining causal inference with interpretable machine learning, the authors provide a framework for exploring the relationships among precursor composition, particle chemistry, and aerosol mixing-state evolution. Overall, the manuscript is well organized and clearly written. I have several comments and suggestions that should be addressed before the manuscript can be considered for publication.
Major comments:
The authors state in the Methods that both pSNR and κeff are relative indicators derived from semi-quantitative SPA-MS measurements and several simplifying assumptions. However, these parameters are subsequently used as quantitative evidence of particle aging, hygroscopicity, and broader atmospheric implications throughout the Results and Discussion. The manuscript would therefore benefit from a discussion of how the assumptions underlying the derivation of pSNR and κeff (e.g., relative ionization efficiency, matrix effects, and the adopted mixing rule) may influence their interpretation. In particular, it would be helpful to discuss the robustness of the reported trends to these assumptions. A simple sensitivity analysis of the κeff calculation would further strengthen confidence in the reported trends. This is especially important for the relatively small changes in κeff, where it remains unclear whether the observed differences exceed the uncertainty associated with the underlying assumptions.
Minor comments:
- Section 2.1: Please specify the measurement size range of the SPA-MS
- Line 56: should be “mixing-state diversity”?
- Line 352-353: there appears to be a grammatical issue in the phrase “… photo-induced the formation of reactive oxygen species (ROS)”
- Section 3.3: The opening summary (Lines 412–416) presents a generalized aging framework, whereas the subsequent discussion highlights distinct aging behaviors among OC-rich, BC-containing, and BC-free particles. Although the authors acknowledge that the proposed aging pathways are strongly composition-dependent (Lines 416–417), this distinction could be reflected more consistently throughout the discussion.
- The interpretation of Figure 4 would benefit from further clarification. As the proposed Stage I and Stage II pathways are inferred from population-level comparisons under different atmospheric conditions rather than direct observations of continuous particle evolution, I suggest explicitly describing Figure 4 as a conceptual aging framework in both the main text and the figure caption. It would also be helpful to clarify that the arrows represent inferred relationships between particle populations, rather than the temporal evolution of the same particles or air masses.
- The manuscript occasionally extrapolates the results to cloud activation, visibility, and climate impacts (e.g., Lines 444–446) in the Results and Discussions. Since these impacts are not directly measured or evaluated in this study, I suggest moving this discussion to the implications section rather than the Results and Discussion. In addition, please include references to support the discussion in Lines 444–446.
Citation: https://doi.org/10.5194/egusphere-2026-3360-RC2
Data sets
Datasets for cross-phase sulfur–nitrogen partitioning and aerosol mixing-state evolution in an urban atmosphere Yuan Dai https://doi.org/10.6084/m9.figshare.32618274
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- 1
Dai et al. presents an interesting study of atmospheric chemistry and potential chemical evolution of sulfur- and nitrogen-containing particles. The authors define sulfur-to-nitrogen ratios in the gas, particles and number-based domains, and use causal inference and interpretable machine learning to identify their linkages and environmental drivers. They found that the aerosol response is strongly particle-type dependent and relative humidity emerges as the primary regulator of the particle behaviors. Overall, the manuscript is well presented and analyzed, and the results are useful for parameterization of cross-phase coupling and chemical heterogeneity in air-quality models. I have a few general comments for the manuscript as shown below.
Comment 1: The particle-phase sulfur-to-nitrogen ratio (pSNR) is derived from the relative peak areas of sulfate and nitrate ions measured by SPA-MS. Because the ionization and detection efficiencies of these species may differ and may also be affected by particle composition and matrix effects, further clarification is needed regarding the interpretation of pSNR. In particular, can pSNR be regarded as an absolute chemical ratio, and how robust are comparisons among different particle types and environmental conditions?
Comment 2: The distinction between fresh-like and aged-like particles is important for the interpretation of particle aging. However, CN-containing particles may persist after atmospheric processing, whereas sulfate- and nitrate-rich particles may originate from source mixing or rapid secondary formation. Please clarify whether the “-CN” and “-sec” categories represent actual particle ages or operational compositional states.
Comment 3: The RH-dependent analysis is potentially important, but the selected RH thresholds appear to be related mainly to literature-reported deliquescence points of ammonium nitrate, ammonium sulfate, and their mixtures. Ambient particles contain complex mixtures of organics, black carbon, salts, and other components that may modify their phase behavior. Were particle phase states directly measured, and how should the RH regimes be physically interpreted?
Comment 4: The manuscript uses a directed acyclic graph to interpret the relationship among gSNR, pSNR, and nSNR. However, causal discovery based on observational data relies on assumptions such as causal sufficiency, faithfulness, and the absence of important unmeasured confounders. Please clarify the interpretation and limitations of the inferred gSNR → pSNR → nSNR pathway.
Comment 5: The manuscript suggests that air-quality models should consider RH- and particle-type-dependent sulfur-nitrogen partitioning. This implication is potentially valuable, but the observations were obtained at a single urban site during four relatively short episodes. Please clarify which modeling processes may be informed by the results and avoid implying that the identified RH ranges can be directly used as universal parameterizations.