the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A new steady-state gas/particle partitioning model of PAHs: Implication for the influence of the particulate proportion in emissions
Fu-Jie Zhu
Peng-Tuan Hu
Wan-Li Ma
Abstract. Gas/particle (G/P) partitioning is an important atmospheric process for semi-volatile organic compounds (SVOCs). However, the exact prediction of the G/P partitioning coefficients (KP) of polycyclic aromatic hydrocarbons (PAHs) was still a challenge. In this study, a new steady-state G/P partitioning model was established based on the level III multimedia fugacity model, with the introduction of the particulate proportion of PAHs in emission (ϕ0) particularly. Same with the previous steady-state model, three different domains with different G/P partitioning behavior can be divided by the threshold values of log KOA (octanol-air partitioning coefficient). The difference between the new steady-state model and previous G/P partitioning models was quite different in different domains. It was found that the deviation with the KP of PAHs from the equilibrium state was caused by both the gaseous and particulate interferences, in which ϕ0 determined the influence of the two interferences. Different forms of the new steady-state model were observed under different values of ϕ0. The comparison with log KP of PAHs between the prediction result of the new steady-state model and the monitored results from 11 cities in China indicated that the ϕ0 was an important factor for the G/P partitioning of PAHs. In addition, the new steady-state model also showed good performance for the prediction of log KP of PAHs with totally gaseous emission and PBDEs with totally particulate emission. Therefore, it can be concluded that the ϕ0 should be considered in the study of G/P partitioning of PAHs, which also provided a new insight for other SVOCs.
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Fu-Jie Zhu et al.
Status: open (until 06 Jun 2023)
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RC1: 'Comment on egusphere-2023-199', Anonymous Referee #1, 10 May 2023
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This paper presents a model which incorporates the extent of partitioning at emissions sources to explain observed non-equilibrium gas-particle partitioning trends for PAHs. Overall, I think the results are interesting and the paper highlights some interesting cases where the assumption of equilibrium partitioning at emissions is not valid – e.g. for coking when particles are being filtered out. I think that clarifying that this model is showing deviations from equilibrium Kp values rather than a “new” KP value could maybe help here – along with more emphasis on comparing the measured results with a null-hypothesis of phi-nought = KpCa (emissions are at equilbirum conditions is the default assumption in most fate and transport models) rather than setting arbitrary values.
- Abstract – I think parts of the abstract could be re-worded.
- Lines 21 – 23 – here it would be more clear to describe the domains you observed
- Lines 25-29, I think rather than a description of results the actual results could be given, as the current form seems a little vague.
- Lines 53-61 – Here and throughout the use of Kp throughout the manuscript is somewhat problematic, since Kp is an equilibrium constant but the model presented here is not at equilibrium. I think the authors should clarify the differences here, and use a different symbol (e.g. K’p) for non-equilbrium distribution between gas and particle. I also think fundamentally the equilibrium models and the non-equilibrium models are describing different things, so they are not directly comparable. In this section, the authors could expand on why in the real world assumptions of equilibrium are often not valid.
- Lines 108-109 – “it can be found…” This could be rephrased to be more direct e.g. “Four fluxes represented <XX% of overall mass transfer and were therefore removed from the system.” For instance from Fig. S1 it looks like gaseous wet deposition becomes somewhat important for e.g. DahA, making up a pretty large portion of the overall flux. Did you have some threshold you defined here?
- Line 120 – This looks like a derivation based on the fugacity capacity (Z value) – is that correct?
- Line 122– Again here I find the use of Kp I think this equation shows what you are doing – adjusting an equilibrium partition coefficient with a correction based on phi – rather than creating a new equilibrium rate constant. I think expressing this as a departure from equilibrium could also help the discussion elsewhere – for instance around Fig. 2,
- Equation 4 – You have simplified the equation such that it only depends on phi nought and kdeg but it also has a dependence on the parameters used to set-up the fugacity model. In particular, I would be interested to see what this looks like at different rain rates – the value you use (9.7e-5 m/h) from Mackay (2001) is going to vary substantially depending on location (presumably it was parameterized for a temperate climate like Ontario, Canada). Also, what about the assumed windspeed/ventilation coefficient – presumably, if you have little turnover the equilibrium assumption for G/P partitioning would get more accurate, whereas faster turnover would mean the initial G/P ratio would dominate.
- Line 197 – do you mean “deviation” here? Also, this is an interesting finding – are you assuming that degradation is only happening in the gas-phase?
- Line 235 – wouldn’t most modeling approaches show these to be mostly in the particle-phase anyways? I think the null-hypothesis here would be to assume equilibrium g/p partitioning at the emissions source rather than an arbitrary value?
- Line 246 – Ok here I see where this might apply! I think giving more examples like this makes sense and helps show where this model would be most useful – places where the emissions would not be at equilbirum (e.g. if they are at high temperatures, if the particles are being removed, etc.)
- Line 265-266 – what would be the equilibrium phi value for these compounds – is it close to 1? If so, then is this result telling us anything new?
- Implications – I think more could be done here showing how these limitations would impact the model. Could the authors run some sensitivity analyses?
Citation: https://doi.org/10.5194/egusphere-2023-199-RC1
Fu-Jie Zhu et al.
Fu-Jie Zhu et al.
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