This manuscript describes a series of modeling experiments performed in CESM2 to test the importance of newly elucidated pathways in biogenic volatile organic compound (VOC) chemistry to the formation of secondary organic aerosol (SOA), and the resulting changes in that SOA under past and future climate scenarios. Specifically, the authors implement a number of new peroxy radical (RO2) reaction pathways in the model's chemical mechanism, some of which do not form SOA but compete with SOA-forming pathways (for isoprene) and some of which have SOA-forming capabilities of their own (isomerization and RO2 + RO2 chemistry, especially from monoterpenes). Using parameters from the literature for these new pathways, they authors find that monoterpene-RO2 isomerization is a hugely important pathway, accounting for nearly half of monoterpene-derived SOA. They also find that the effect on SOA of changes in biogenic VOC emissions from preindustrial to present to future conditions overwhelm the effects of changing chemistry (via temperature-dependent reaction rates and changing bimolecular RO2 reaction partners) and thermodynamics (gas-particle partitioning), and will likely cause increased in biogenic SOA in a warmer future climate.

The results of this study are certainly important and useful, and worthy of publication following some clarification as described below. I'm also very impressed by the clarity of the writing. The edits made to the model and mechanism are extensive, but I felt they were clearly enough laid out and walked through that I was never lost. The step-by step discussion of modeling results is excellent; in particular the paragraph on separating chemistry from emissions (L 551-565) does an exceptional job of explaining the experimental setup and highlighting the important results in a concise and clear manner. I think the finding that the change from PD to F is completely due to emissions -- and in fact that chemistry & thermodynamics would lead to a decrease in SOA with BVOC emissions held constant -- is an important one that should be highlighted in the abstract! 

My main concern is that a lot of the mechanistically-specific conclusions (that monoterpene isomerization is hugely important to SOA formation; that RO2 + RO2 chemistry is not) seem based on the particular parameters the authors chose out of many highly uncertain ones, and this uncertainty is not satisfactorily expressed in the places where quantitative conclusions about the contributions of these pathways are noted. While some of these uncertainties are discussed in the methods section, they are then glossed over in places like the abstract and conclusions where headline numbers about the importance of isomerization, e.g., are reported. In particular, I *don't* think it's worth highlighting quantitatively in the abstract the very precise fraction of monoterpene SOA formed by isomerization (44-46%), which makes it look like the uncertainty range on this is tiny when in fact the parameterization that went into it is highly uncertain. 

I write more detail below on the specific elements of uncertainty (or at least the specific parameters that seem highly uncertain) that come to mind, but overall I think the magnitudes of these compounding uncertainties in reaction rates, yields, and simplifying parameterizations (e.g. lumping of all terpenes and treating them like a-pinene) merit more discussion -- for example, how big a range could the isomerization fraction of monoterpene SOA actually span given the uncertainty on parameters like its rate, its SOA yield, the isomerize-able fraction (especially given the lumping of all terpenes into a-pinene), the low volatility and photorecalcitrance of its products? Not that you need to do more simulations testing all this -- just some back-of-the-envelope type analysis to temper the conclusions would be useful, I think.

- L174-175 --> but ISOP makes SOA mostly through heterogeneous reactivity (IEPOX uptake being a reactive process), not volatility, so isn't that problematic? Not suggesting that you fully revise the isoprene SOA scheme here, but has there been any previous assessment you can point to here of the errors introduced by treating IEPOX SOA as a volatility-driven process, and/or can you speculate on how that would influence your findings about PI vs PD vs F for isoprene SOA?

- L177-179 --> lumping of MTERP RO2s seems problematic given their very different structures; they'll likely have very different reaction pathways and balances between fragmentation vs functionalization. It's fine if the existing mechanism is tuned to get this right given the distribution of monoterpenes, but will that distribution change under preindustrial or future scenarios, and what influence would that have?

- L182-183 isn't that work by Pye et al just for a-pinene? Do these rates and yields hold across MTERPs, and if not, how much uncertainty is introduced from your treatment here?

- L188-195 the isom pathway seems extremely poorly constrained and heavily oversimplified; is there any constraint on the high SOAG yields and subsequent SOA production from this pathway? Does that match any ambient or chamber observations? And is there any information at all informing the implementation of an equivalent rate and product yield for BCARY? I'm glad you acknowledge the uncertainties here, but later in the results section (e.g. L 313-321) it sounds like it's taken as fact, since you're describing the huge impact of isomerization-derived SOA there without any mention of the high uncertainty.

- Table 2 --> it appears that these added RO2 + RO2 reactions in Part 2 consume gas-phase RO2s that weren't part of the VBS scheme, which is contrary to how this mechanism's previous VBS chemistry seems to work, in that none of the reactions in Table 1 consume the gas-phase compounds implicated in the reactions (i.e. the reactions of precursors with OH still have the precursor and OH on the right side of the equation, so they effectively don't consume it, and the reactions of VBS compounds with HO2 & NO don't consume those either). Does the newly-added consumption of gas-phase RO2 in your scheme influence gas-phase chemical outcomes (I'm especially thinking of oxidant recycling) in places where this chemistry happens abundantly? I wouldn't be surprised, for example, if this consumption of RO2 in, say, the Amazon leads to somewhat lower HOx levels there...

- Also in Table 2 - Is it known that the reactions of MTERP/BCARY RO2's with CH3O2 and CH3CO3 make no SOA? (And ISOPRO2 + CH3O2/CH3CO3, for that matter, though that seems less likely anyway). And if that's known known experimentally, why is that assumed? Presumably these RO2-RO2 reactions could lead to a small fraction of accretion products (at least for the RO2 + CH3O2 reactions) -- the equivalent accretion products do show up as an appreciable chunk of the total in some locations in Mayhew et al (https://acp.copernicus.org/articles/25/17027/2025/, Fig 12, bottom, "sesquiterpenes + small VOCs" & "monoterpenes + small VOCs"). Even for the branching of these RO2 + RO2 reactions to non-accretion alkoxy radicals, some moderate-volatility products could be produced (especially for BCARY), for which volatilities could at least be estimated. Could you at least provide an estimate of what fraction of the mono-/sesquiterpenes go down these pathways to give the reader a sense of the uncertainty here? 

- Speaking of the branching to non-accretion products -- am I correct in interpreting the 0.04 SOAG0 yield from all the BCARYO2VBS + RO2 reactions as an attempt to represent just the accretion product, meaning that there's an assumed SOA yield of zero from non-accretion pathways? Again, this seems unlikely for the non-accretion pathways from sesquiterpenes and even monoterpenes, which leave you with more-oxygenated C10 and C15 compounds than you started with and could easily form compounds with low-enough volatility to contribute to SOA. Overall it seems this representation is likely to underestimate SOA from RO2 + RO2 pathways if it only accounts for accretion products, and with a fixed yield of 4%, despite mounting evidence that yields increase with molecular size (Berndt et al., 2018, DOI 10.1002/anie.201710989; Franzon, 2023, DOI 10.1021/acs.jpca.3c01890; Frandsen et al., 2025, DOI 10.1021/acsearthspacechem.4c00355). The justification for this fixed 4% number (L 222-224) needs to be stronger.

- I assume "SOAG0" is a single compound with a fixed effective molar mass; if that's the case, surely the 0.04 molar yield of SOAG0 represents a fixed mass yield of this SOA compound from each of the RO2 + RO2 reactions, but that's not the same as saying that the reactions have the same dimer yields; a BCARYO2 + BCARYO2 dimer would have 30 carbons compared to a MTERPO2 + ISOPRO2 dimer's 15. So doesn't this method of fixing the yield at 0.04 SOAG0 skew the product formation, such that lighter precursors effectively have higher molar SOA yields? This is compounded by the fact that the C30 BCARYO2 + BCARYO2 dimer should be less volatile than the C15 MTERPO2 + ISOPRO2 dimer, and so should have a higher propensity to form SOA. You acknowledge this on L226-229, but it seems like it would be reasonable to estimate the volatilities of these dimers and correctly apportion them into volatility bins rather than just putting them all in the same extremely-low-volatility bin together. 

- The overall sense here is that many compounding factors are making the SOA yield parameterizations from this RO2+RO2 chemistry hugely uncertain and likely a low estimate, and as with the isomerization chemistry discussed above, I think that merits more mention of this uncertainty later on when large claims are made (e.g. L 575-576 in the conclusions that "The RO2 + RO2 reactions contribute moderately to the MTERP RO2 fate but make a minor contribution to the MTERP SOA formation" -- I think it's worth stating right in that sentence that this is perhaps only because the estimated SOA yields from RO2 + RO2 are quite low.

- L 224-225 it's unclear what's meant by "these two"

- Table 3 - are the ISOP-RO2s not allowed to cross react with other ISOP-RO2s? Presumably this pathway could be important in some high-isoprene-emission locations, and would lead to a small yield of accretion products with sufficiently low volatility to contribute to SOA? 

- L 261-262 does the implementation of this photorecalcitrant fraction in just the lowest-volatility bin and not spread out across the bins -- which seems based in convenience rather than any physical or chemical characteristics of that volatility bin -- potentially bias your results toward overemphasizing the importance of the lowest volatility bin, which just happens to be where you've put a lot of the new isomerization and RO2+RO2 SOA? How large could this effect be?

- L 284 "reduced future anthropogenic emissions" of what? A priori it seems directly counter to the high CO2 stated in the previous sentence. Reduced emissions of NOx? How is that compatible with increased CO2 that likely comes from fossil fuel combustion?

- L 403-406 - the introduction of new ISOPRO2 reactions that compete with the SOA-forming pathways and decrease overall isoprene-derived SOA brings up an important point: were the original SOA yields from ISOPRO2's HO2 and NO pathways based exclusively on chamber experimental results, or were they at all tuned in order to match ambient observations of isoprene-derived SOA? Because if it's the latter, then adding new pathways that compete with those old ones means you should artificially bump up the SOA yields to compensate; otherwise, you're now biased low on isoprene SOA formation relative to the previous tuning. If it's the former, keeping those old SOA yields should be okay -- but you're really only getting the decrease because you've assumed zero SOA formation from the newly added isomerization and RO2 + RO2 pathways for isoprene, which is likely not correct (e.g. Berndt et al 2025 for SOA formation from isomerization, Mayhew et al 2025 for the contribution of isoprene RO2 + isoprene RO2 accretion products to SOA).

This manuscript investigates the role of expanded biogenic RO₂ chemistry in secondary organic aerosol (SOA) formation using CESM2.2, with a particular focus on monoterpene RO₂ isomerization and RO₂ + RO₂ accretion pathways under pre-industrial, present-day, and future conditions. The study addresses an important and timely problem: current global models generally represent biogenic SOA formation using highly simplified chemistry, while recent laboratory and modeling studies indicate that autoxidation and accretion chemistry may substantially affect SOA formation and its response to changing climate and anthropogenic emissions. The implementation of these pathways in a global chemistry–climate model, together with the comparison across PI, PD, and F conditions, has the potential to provide useful insight into the drivers of biogenic SOA burden and its future evolution.

Overall, I find the manuscript scientifically interesting and potentially suitable for publication. I consider this study a strong and potentially valuable contribution to the field. However, the manuscript currently lacks important methodological detail, and several aspects of the model formulation and interpretation require further clarification and discussion before the main conclusions can be fully evaluated. I therefore recommend publication after the authors address the points below.

1. Lines 182-187: The implementation "MTERPO2VBS → 0.5 SOAG0" simplifies the downstream chemistry described in Pye et al. (2019). In the original mechanism (their Fig. 1 and SI Fig. S2), the fate of first-generation C₁₀H₁₇O₇-RO₂ is NOx-dependent: reaction with HO₂ produces very low-volatility hydroperoxides (C* ≈ 7.3 × 10⁻³ μg m⁻³ for the major products), while reaction with NO yields a mix of organic nitrates with C* ≈ 0.1–0.4 μg m⁻³ and alkoxy radicals (~87.5%) that largely decompose to more volatile fragments. Collapsing these pathways into a single 50% SOAG0 yield loses the NOx sensitivity of post-isomerization HOM-RO₂ termination and product volatility, and may overestimate SOA formation under relatively high-NO conditions. This is particularly relevant given that one of the paper's central results concerns the PI→PD→F trend in isomerization-derived SOA, and the NO-related chemical environment differs substantially across these periods, with anthropogenic NO emissions peaking at PD. The reported increase in the isomerization contribution from 38% (PI) to 44% (PD) to 51% (F) could therefore be sensitive to this simplification.

I recommend that the authors expand Section 2.2 to explicitly explain this simplification, including which pathways from Pye et al. (2019) are lumped together, why the 50% value was chosen as representative, and how this differs from the original mechanism. Specific references to the source of each parameter — for example, Pye et al. (2019) SI Table S1 for the 22% APINCO2 branching and SI Table S2 for the 0.5 branching ratio — would help readers verify the linkage. A qualitative discussion of how this simplification might bias the PI→PD→F trend would also strengthen the paper.

2. Lines 234-236: The reactions of MTERP-RO₂ with NO₃, CH₃O₂, and CH₃CO₃ are incorporated in the modified VBS as additional loss pathways that do not produce SOAG. Given that the VBS treatment represents SOA-forming potential through effective yields assigned to first-generation RO₂ pathways, it is unclear why these additional channels are assumed to have no downstream SOA-forming potential. In particular, recent work by Kang et al. (2025) provides experimental evidence that highly oxygenated alkoxy radicals formed during α-pinene oxidation can undergo isomerization with a branching ratio of approximately 50%, regenerating RO₂ and propagating HOM formation. Thus, treating these additional MTERP-RO₂ loss pathways as zero-SOAG channels may neglect potentially relevant alkoxy–peroxy contributions to SOA formation.

I recommend that the authors clarify the rationale for treating the reactions in Table 2 part 3 as zero-SOAG pathways. Because the relative importance of these pathways may vary across PI, PD, and F chemical environments, a brief qualitative discussion of the resulting uncertainty in the reported SOA trends would be helpful.

3. Lines 255–270: To mimic the photo-recalcitrant fraction observed in laboratory studies, the authors turn off the photolysis of SOA in the lowest volatility bin (SOAG0). However, this choice ties photo-recalcitrance to volatility, whereas laboratory studies typically report photo-recalcitrant fractions based on bulk or precursor-specific SOA behavior rather than volatility-resolved measurements (e.g., O'Brien and Kroll, 2019; Zawadowicz et al., 2020). Highly oxidized, low-volatility products formed via autoxidation can contain photolabile functional groups, including carbonyls and hydroperoxides, suggesting that the relationship between volatility and photo-recalcitrance is not straightforward.

This choice may also have implications for the reported PI→PD→F trend. Because the contribution of isomerization, which feeds directly into SOAG0, increases from 38% in PI to 44% in PD and 51% in F, a growing fraction of MTERP SOA is produced through a pathway assigned zero photolytic loss. This treatment could contribute to the simulated future increase in isomerization-derived SOA. I recommend that the authors clarify the physical rationale for tying photo-recalcitrance to volatility and discuss qualitatively how this assumption might affect the reported PI→PD→F trend.

4. Lines 271–291: The description of the simulation setup, particularly for the PI and F experiments, lacks sufficient detail to fully evaluate and reproduce the results. In the current form, it is unclear how the authors set up the CESM simulations. Several key choices should be clarified:

• CESM component configuration: It is not specified whether the simulations use an atmosphere–land configuration with prescribed SST and sea ice, such as an F-compset, or a fully coupled configuration, such as a B-compset. The reference to SST data for each period suggests that prescribed-ocean boundary conditions may have been used, but this should be stated explicitly. This distinction is important for interpreting the reported temperature changes, such as the +5.9 K increase from PD to F, as either an internally generated coupled climate response or an atmospheric response constrained by prescribed boundary conditions.
• Source and temporal treatment of SST and sea-ice forcing: If SST and sea ice were prescribed, please identify the source of the PI, PD, and F fields and explain how they were constructed, for example, whether they were taken from a parent CESM2/CMIP6 coupled simulation under SSP5-8.5 and whether climatological or time-varying boundary conditions were applied. The sources and temporal treatment of CO₂, anthropogenic and natural emissions, and land-use forcing should also be specified.
• Please also clarify whether the 10-year simulations represent repeated time-slice forcing or transient integrations.

5. Lines 281–285: The future analysis is based solely on SSP5-8.5, which combines very strong warming and CO₂ increases with declining anthropogenic air pollutant emissions. Because both temperature-driven BVOC emission changes and changes in NO emissions strongly influence the simulated SOA response, the choice of future scenario is important for interpreting the reported PD→F changes. Please clarify the rationale for selecting SSP5-8.5 as the only future scenario.

6. Figures 6, 11, and 12: The dotted regions are described as statistically significant at the 0.05 level, but the statistical testing procedure is not provided. Please specify the test used, the sample basis for the test (e.g., annual means from the 10-year simulations), and any other information needed to interpret the dotted regions.

7. Lines 317–318 and 332–334: Xu et al. (2022) is the most directly comparable prior global modeling study of monoterpene-derived RO₂ autoxidation and RO₂ + RO₂ chemistry, yet the comparison in Section 3.1 is limited to brief qualitative statements. Given that the present work follows Xu et al. in testing fast and slow RO₂ + RO₂ reaction-rate combinations, a more quantitative comparison of the globally averaged MTERP-RO₂ fate partitioning between the two studies, where the diagnostics are comparable, would substantially strengthen the paper.

8. Section 3.2: The attribution of PI→PD and PD→F changes in SOA burden focuses on BVOC emissions, RO₂ fate, and gas–particle partitioning, but changes in SOA removal and lifetime may also be important. This is particularly relevant because SOA photolysis is modified in this study and because wet scavenging may change substantially under different climate conditions. I recommend that the authors provide a quantitative SOA loss budget for PI, PD, and F, separating at least photolytic loss, wet deposition, and dry deposition, together with any other relevant modeled losses. Corresponding changes in SOA lifetime would help support the attribution of the reported burden trends. If possible, these diagnostics should be provided separately for MTERP SOA, ISOP SOA, and total BVOC + OH SOA.

9. The manuscript attributes part of the PD→F change in SOA burden to temperature-driven changes in gas–particle partitioning, but the thermodynamic parameters governing this response are not specified. I recommend that the authors (1) report the enthalpy of vaporization (ΔH_vap) values used for each volatility bin and the basis for these choices, and (2) briefly discuss how the assumed ΔH_vap influences the gas–particle partitioning response in the PD→F simulation and the interpretation of the reported +113% SOA increase.

References

Pye, H. O. T., D’Ambro, E. L., Lee, B. H., Schobesberger, S., Takeuchi, M., Zhao, Y., Lopez-Hilfiker, F., Liu, J., Shilling, J. E., Xing, J., Mathur, R., Middlebrook, A. M., Liao, J., Welti, A., Graus, M., Warneke, C., de Gouw, J. A., Holloway, J. S., Ryerson, T. B., Pollack, I. B. and Thornton, J. A.: Anthropogenic enhancements to production of highly oxygenated molecules from autoxidation, Proc. Natl. Acad. Sci. U. S. A., 116(14), 6641–6646, 2019.

Kang, S., Wildt, J., Pullinen, I., Vereecken, L., Wu, C., Wahner, A., Zorn, S. R. and Mentel, T. F.: Formation of highly oxygenated organic molecules from α -pinene photooxidation: evidence for the importance of highly oxygenated alkoxy radicals, Atmos. Chem. Phys., 25(22), 15715–15740, 2025.

O’Brien, R. E. and Kroll, J. H.: Photolytic aging of secondary organic aerosol: Evidence for a substantial photo-recalcitrant fraction, J. Phys. Chem. Lett., 10(14), 4003–4009, 2019.

Zawadowicz, M. A., Lee, B. H., Shrivastava, M., Zelenyuk, A., Zaveri, R. A., Flynn, C., Thornton, J. A. and Shilling, J. E.: Photolysis controls atmospheric budgets of biogenic secondary organic aerosol, Environ. Sci. Technol., 54(7), 3861–3870, 2020.

This manuscript incorporates an expanded biogenic RO₂ chemical mechanism into CESM2 to investigate the atmospheric fate of biogenic RO₂ and its role in biogenic SOA formation across pre-industrial, present-day, and future climate scenarios. Although uncertainties remain regarding the parameterizations of RO₂ isomerization and RO₂ + RO₂ accretion, there is significant scientific interest in how the detailed biogenic RO₂ chemistry can improve our understanding of the biogenic SOA burden and its temperature-driven evolution in a warming climate. The results highlight the critical role of monoterpene RO₂ isomerization in biogenic SOA formation, which accounts for nearly half of monoterpene SOA. Furthermore, the model suggests an increase in biogenic SOA under the SSP5-8.5 scenario, driven primarily by elevated biogenic VOC emissions. Overall, this manuscript is well-written and within the scope of ACP. I recommend it for publication after the authors address the comments below.

1. Table 1: The table indicates that APIN, BPIN, LIMON, and MYRC are assigned identical SOA yield in the model. However, previous studies have demonstrated that the SOA yield of LIMON is generally higher than that of other terpenes (Pye et al., 2010). I recommend that the authors clarify the rationale for this uniform treatment, as applying a single yield across these distinct species may lead to an underestimation of terpene-derived SOA.

2. Line 171: The manuscript states that OH-initiated pathways account for 59% of total biogenic SOA in CAM6-chem. This high overall fraction is likely driven by isoprene, whose SOA formation is predominantly OH-initiated. In contrast, for terpene-derived SOA, the contribution from ozonolysis is crucial (Hallquist et al., 2009). Please clarify how the absence of ozonolysis-derived RO₂ might affect the simulations of terpene-derived RO₂ and subsequent SOA formation.

3. Line 174-175: The majority of isoprene-derived SOA forms from the heterogeneous reactions, such as the heterogeneous uptake of IEPOX (Marais et al., 2016). By omitting these heterogeneous processes, the model may have biases in the atmospheric fate of ISOP-RO₂. I recommend that the authors clarify how the absence of these pathways might impact ISOP-RO₂ and isoprene-derived SOA.

4. Line 263: Although turning off the photolysis of SOA in the lowest volatility bin may reproduce the observed photo-recalcitrant fraction in laboratory experiments, this approach may lead to an overestimation in the SOA formed from RO₂ isomerization, given that this specific reaction exclusively forms SOAG0. I recommend that the authors discuss the potential for this overestimation and its implications, particularly regarding projected future changes in the biogenic SOA burden.

5. Line 278-280: The manuscript currently lacks sufficient detail in the setup of the pre-industrial (PI) and future (F) experiments. The authors should provide a more comprehensive description of these scenarios, particularly clarifying the prescribed or online-calculated inventories used for anthropogenic, open biomass burning, and biogenic emissions across the PI, present-day (PD), and F experiments.

6. Line 285: The authors utilize the SSP5-8.5 scenario to project the future evolution of biogenic RO₂ and SOA. However, a recent study suggests this extremely high fossil-fuel emission pathway is increasingly viewed as implausible (Hausfather and Peters, 2020). It would be more appropriate for the authors to explicitly regard their SSP5-8.5 results as an upper-bound sensitivity test. Furthermore, I recommend that the authors consider including an additional simulation under a more moderate pathway (such as SSP2-4.5) to provide a more realistic projection of future biogenic SOA burdens.

7. Line 290: Please specify the exact simulation periods for the PI, PD, and F experiments.

8. Line 424: The text notes that the NEW simulations predict a decrease relative to the BASE scenario over tropical forest regions. However, the underlying drivers for this change are not discussed. I recommend that the authors add a brief explanation of this regional decrease.

9. Line 425-428: As acknowledged in the text, the simulation results are highly dependent on the parameterizations for the biogenic RO₂ chemical mechanism, which is highly uncertain. It would strengthen the manuscript to provide a summary of the SOA yields, reaction rate constants, and branching ratios from various laboratory studies, and then to evaluate the extent to which the uncertainties in these specific parameters impact the modeled biogenic RO₂ and SOA.

10. Line 467-469: It would be beneficial to clarify the range of estimated future BVOC emissions in the selected scenario, and then evaluate the extent to which the uncertainties in these future BVOC emission estimates might affect the projected biogenic SOA burden.

11. Line 471-476: I recommend adding a figure for the global distributions of changes in the VOC emissions from anthropogenic and biomass burning sources from PI to PD and from PD to F in the supplementary, which would better support the authors' discussion about the shifts in OH and HO₂ concentrations.

12. Figures 11 and 12: Please clarify in the figure captions how the differences are calculated (e.g., whether they represent PD minus PI and F minus PD, respectively).

13. Line 537-539: The manuscript currently attributes the increase in SOA from RO₂ isomerization solely to the reduced evaporation of low volatility products. However, the increase is likely driven not only by this volatility effect, but also because the higher temperature kinetically favors the RO₂ isomerization pathways themselves, as illustrated in Figure 1. I recommend that the authors explicitly highlight that by incorporating detailed biogenic RO₂ chemistry, the modeled biogenic SOA formation becomes more sensitive to temperature changes than estimated by previous simplified schemes.

References

Hallquist, M., Wenger, J. C., Baltensperger, U., Rudich, Y., Simpson, D., Claeys, M., Dommen, J., Donahue, N. M., George, C., Goldstein, A. H., Hamilton, J. F., Herrmann, H., Hoffmann, T., Iinuma, Y., Jang, M., Jenkin, M. E., Jimenez, J. L., Kiendler-Scharr, A., Maenhaut, W., McFiggans, G., Mentel, T. F., Monod, A., Prévôt, A. S. H., Seinfeld, J. H., Surratt, J. D., Szmigielski, R., and Wildt, J.: The formation, properties and impact of secondary organic aerosol: current and emerging issues, Atmos. Chem. Phys., 9, 5155-5236, https://doi.org/10.5194/acp-9-5155-2009, 2009.

Hausfather, Z., and Peters, G. P.: Emissions - the 'business as usual' story is misleading, Nature, 577, 618-620, https://doi.org/10.1038/d41586-020-00177-3, 2020.

Marais, E. A., Jacob, D. J., Jimenez, J. L., Campuzano-Jost, P., Day, D. A., Hu, W., Krechmer, J., Zhu, L., Kim, P. S., Miller, C. C., Fisher, J. A., Travis, K., Yu, K., Hanisco, T. F., Wolfe, G. M., Arkinson, H. L., Pye, H. O. T., Froyd, K. D., Liao, J., and McNeill, V. F.: Aqueous-phase mechanism for secondary organic aerosol formation from isoprene: application to the southeast United States and co-benefit of SO₂ emission controls, Atmos. Chem. Phys., 16, 1603-1618, https://doi.org/10.5194/acp-16-1603-2016, 2016.

Pye, H. O. T., Chan, A. W. H., Barkley, M. P., and Seinfeld, J. H.: Global modeling of organic aerosol: the importance of reactive nitrogen (NO_x and NO₃), Atmos. Chem. Phys., 10, 11261-11276, https://doi.org/10.5194/acp-10-11261-2010, 2010.