the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Uncertainties in the effects of organic aerosol coatings on polycyclic aromatic hydrocarbon concentrations and their estimated health effects
Abstract. We utilized the CAM5 model to examine how different degradation approaches for particle-bound Polycyclic Aromatic Hydrocarbons (PAHs) affect the spatial distribution of benzo(a)pyrene (BaP). Three approaches were evaluated: NOA (no OA coatings), Shielded (where viscous OA coatings protect PAHs from oxidation), and ROI-T (where OA coatings influence PAHs through reactive oxygen intermediates related to temperature). Our findings indicate that the seasonal variation of BaP is influenced by emissions, deposition, and degradation approaches. All simulations predict higher population-weighted global average (PWGA) fresh BaP concentrations during December-January-February (DJF) compared to June-July-August (JJA), primarily due to increased emissions from household activities, less efficient wet removal, and unfavourable winter conditions. The Shielded and ROI-T approaches show that viscous OA coatings significantly inhibit BaP oxidation, leading to PWGA fresh BaP concentrations two to six times higher in DJF than in NOA. The Shielded approach predicts the highest PWGA fresh BaP concentration of 1.3 ng m-3 in DJF, with 90 % of BaP protected from oxidation. In contrast, the ROI-T approach forecasts lower concentrations in mid-to-low latitudes. Model evaluations indicate the Shielded method performs best, with a normalized mean bias within ±20 %. The incremental lifetime cancer risk ranges from 0.6 to 2 deaths per 100,000 persons based on fresh BaP exposure. Overall, the human health risks from fresh and oxidized PAHs are comparable, underscoring the importance of including both forms in risk assessments and highlighting the critical role of accurate degradation approaches in PAH modelling.
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Status: open (until 23 Dec 2024)
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RC1: 'Comment on egusphere-2024-3269', Anonymous Referee #1, 27 Nov 2024
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General comments
This study uses the CAM5 model to investigate the impact of particle-bound PAH degradation approaches on the spatial distribution of BaP and its lung cancer risk, considering the presence or absence of OA coatings. Three representative PAH degradation approaches are implemented. Though PAH modeling and discussion about different degradation schemes are not novel, especially when PAH modeling using the CAM model was already published, it’s still fresh to see the simulated oxidized BaP concentrations being compared with measurements. In general, it’s well-written and of high scientific quality. This manuscript can be published after addressing the following issues.
Specific comments
This study tries to show the uncertainty from different BaP degradation schemes, but what are the criteria for selecting the degradation schemes to quantify the uncertainty range? There are other schemes such as Poschl et al. 2001 which should be even faster, so why is it not chosen? Also, for uncertainty study, it would also be nice to have a no reaction scheme for comparison.
Section 2.3 introduces several BaP degradation schemes mostly using text. However, it’s not clear for the readers to understand those schemes. In the Supplement, expressions/equations of those schemes can be given. (1) For NOA, give the expression of LH mechanism and k. (2) For the Shielded scheme and the ROI-T scheme, use tables to summarize the different reaction expressions. It would be even better if the intercomparison of reaction rate k could be clearly seen through the summary.
L78-79 It seems that ppLFER is good for anthropogenically impacted areas but Junge-Pankow is good for remote areas. So why do you choose ppLFER in the end? Have you tested their differences in your model?
When discussing the role of emission and meteorology in influencing BaP level and distribution, cited references are used. However, those references use different emission inventories and meteorological inputs, so results from those references can’t be directly used. It would be more straightforward to use this model’s inputs for analysis.
Technical comments
L33 Explain the abbreviation of OA.
L35 Not only related to temperature but also relative humidity.
L36 The influence missed meteorology (transport and other meteo conditions) which you also explained later.
L84 Explain the abbreviation of OH, NO3.
L122 Lung cancer risk part is not mentioned in section 3, which is important.
L135 suburban background site.
L158 Delete “organic aerosols” as OA is already explained earlier.
L164 Delete “hydroxyl radicals” as OH should be explained earlier.
L190 How does the model decide if the coating is thicker than 20 nm?
L194-195 How does temperature influence the reaction rates? I only see that RH plays a role.
L210 The explanation of the Shielded scheme is not complete. Since it’s not easy to explain it in one sentence in the brackets, it’s better not to explain it at all. Section 2.3 has explained it well.
L214 Which are the two simulation years?
L226 GFED4 is already widely used by all kinds of models replacing GFED3. So why is GFED3 still used in the simulation? Does it influence the results?
L238 Does n equal to 8? If yes, just use 8.
L240 What does “1 to 16” mean?
Section 2.7 What are the values of CSF and SUS or how are they calculated? For LADD calculation, what’s the value of inhalation rate, exposure duration and body weight?
L271 How is PWGA calculated?
L276 Use PWGA as it’s explained earlier.
L280 Should be “lighting” not “lightning”.
L279 Shen et al. 2013 used a different BaP emission inventory. Instead of citing the emission results from the literature, it’s better to calculate them from the model’s emission inventory, which is more convincing.
Figure 1 Unit is missing in the color bar.
L301 Does OH really have the same trait as ozone here?
L308 Temperature, humidity and emissions can be plotted, instead of citing references as references may not use the same inputs.
L337 Can you show the chemical reaction and reaction rate for producing oxidized-BaP?
L389 Since NMB for the background sites is -18%, could downgrading the background sites improve model performance?
Figure 5. Why are China and Europe chosen to be shown? No explanation in the text.
L419 Use NMB.
L427 Calculate the emission instead of citing a reference that uses another inventory.
L455-457 Site description should be moved to site introduction part.
Figure 7: Model results may also have error bars as observations?
L478 Why “however”?
L508 “selected”.
L590 “effect”.
Citation: https://doi.org/10.5194/egusphere-2024-3269-RC1
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