The authors integrate high-level quantum chemical calculations with Atmospheric Cluster Dynamics Code simulations to systematically investigate how HNO₃ influences HIO₃–HIO₂ nucleation across the troposphere. The results reveal that HNO₃ can undergo a functional transition from a nucleation catalyst in the warm marine boundary layer (MBL) to a core structural component of nucleating clusters in the cold upper troposphere (UT). This conclusion is particularly important given declining global sulfur emissions, rising marine iodine emissions, and the well-recognized significance of upper tropospheric new particle formation for the global cloud condensation nuclei budget. The manuscript is clearly written and employs state-of-the-art computational methodologies for atmospheric cluster nucleation research, while its altitude-resolved mechanistic analysis provides a valuable, novel perspective to the field. Overall, this work is logically structured and easy to follow, with a topic that aligns closely with the scope of Atmospheric Chemistry and Physics. I recommend this work for publication following the adequate addressing of the comments below.

Scientific issues:

1. 2(b) shows boundary clusters determined at 228, 248, 268, and 288 K. However, the ACDC simulations in this work cover a temperature range of 204–288 K (Fig. 4a), yet boundary clusters are not provided for the remaining temperatures. Boundary clusters should be provided for all the studied temperatures.
2. The introduction briefly notes that HNO₃ stabilizes sulfuric acid-based clusters, without explicitly extending this established behavior to iodine oxoacid systems. A clear logical bridge is missing: if HNO₃ enhances sulfuric acid nucleation via hydrogen bonding and proton transfer, it is reasonable to hypothesize a stabilizing effect in iodine oxoacid systems, given their ability to form hydrogen bond and halogen bond networks. Adding this analogy would strengthen the motivation for investigating HNO₃ in iodine-driven nucleation, making the hypothesis less speculative and better grounded in existing knowledge.
3. In Section 2.1, the cluster composition is defined as (HNO₃)_x(HIO₃)_y(HIO₂)_z with 1 ≤ x ≤ 3, but no justification is provided for limiting the number of HNO₃ molecules to three. This arbitrary cutoff lacks chemical or kinetic rationale. A brief explanation (e.g., thermodynamic or kinetic stability) should be added to clarify this constraint.
4. In Section 2.3, the kinetic criterion βc/∑γ > 1 defines stable clusters, but the monomer concentration c is not clearly specified. Given that HNO₃, HIO₃, and HIO₂ concentrations differ by orders of magnitude, an ambiguous c undermines the criterion. Please clarify whether c refers to the dominant precursor concentration or an equivalent concentration.
5. A previous study has shown that HIO₃–HIO₂–DMA nucleation (Atmos. Chem. Phys., 24, 5823–5835, 2024) plays an important role in the marine boundary layer. This nucleation mechanism is also relevant to the Zhejiang and Mace Head cases, where DMA is abundant. To better illustrate the practical atmospheric significance of the proposed HIO₃–HIO₂–HNO₃ nucleation pathway, a direct comparison with the well-documented HIO₃–HIO₂–DMA nucleation mechanism should be included.
6. The conclusion links Arctic NPF enhancement to anthropogenic nitrogen emissions but does not explain how elevated HNO₃ interacts with iodine species under the cold, low condensation sink Arctic conditions. This weakens the causal link. Additional environmental and mechanistic context should be provided.

Technical issues:

Lines 19. The “nucleation” in “200-fold enhancement in nucleation” should be “in the cluster formation rate”.

Line 48. The “proton transfer-driven electrostatic interactions” should be changed to “proton-transfer driven electrostatic interactions”.

Line 165 Inconsistent unit notation: “molecules/cm³” appears here whereas the rest of the manuscript uses “molecules cm⁻³”.

Line 196. The “minimizes scavenging of nascent clusters This enhancement…” should be changed to “minimizes scavenging of nascent clusters. This enhancement…”

Line 209. The caption refers to “Heatmaps of (a) cluster formation rates” but only one panel is labelled.

Line 329. The “solidifying HIO₃’s role as a UT nucleation core component” should be changed to “solidifying HNO₃’s role as a UT nucleation core component”.

Line 540. The reference Jones et al. (Atmos. Chem. Phys., 2014, 14, 11843–11851) is listed but not cited in the main text.

Lines 590-595. The two references “Li, J., Ning, A., Liu, L., and Zhang, X. … 2024a” and “Li, J., Ning, A., Liu, L., and Zhang, X. … 2024b” are identical references with the same title, journal, DOI.

Zhang et al. investigates the effect of nitric acid (HNO₃) on the clustering of iodic acid (HIO₃) and iodous acid (HIO₂). The (HIO₃)_n(HIO₂)_m cluster structures are taken from previous work by the same group, and the current investigation feels like a natural extension. 

The cluster configurations are sampled using well-established protocols and state-of-the-art quantum chemical methods. The calculated thermochemistry is used in the atmospheric cluster dynamics code (ACDC) to simulate new particle formation (NPF) rates. Specifically, the authors simulate NPF at Zhejiang, Mace Head, Greenland and in the upper troposphere. The overall finding is that nitric acid contributes to the cluster formation in all regions. I find the altitude analysis performed in this manuscript particularly interesting and extremely well carried out. This is good inspiration for other work in the field.

I only have minor issues with the justification of the applied methods. I.e. how much can we trust that the methods are giving reliable results, without backing up the accuracy of the methods. I acknowledge that the sensitivity tests alleviate some of this concern, but it does not give the full picture.

Overall, the paper is interesting, well-written and advances our understanding of NPF in the marine environment. I believe it is a good fit for ACP and recommend publication after the following comments have been addressed.

Comments

Line 72: “… with detailed procedures provided in the Supporting Information” 

I would appreciate that the sampling details are also included in the methods. Hence, integrate the “Multi-step cluster conformational search method” from the SI to the methods section as this will make it more transparent whether one can trust the found structures.

In addition, the applied UFF forcefield cannot handle bond breaking. Did the authors sample the cluster structures using ionic monomers to simulate bond breaking (see Kubečka et al., https://doi.org/10.1021/acs.jpca.9b03853).

Only selecting the lowest 100 cluster configurations based on PM7 could lead to the global minimum cluster being missed (see Kurfman et al., https://doi.org/10.1021/acs.jpca.1c00872). Could the authors comment on this aspect?

Line 74: “All identified low-energy cluster conformations were rigorously optimized and subjected to frequency analysis using the Gaussian 09 package (Frisch et al., 2009) at the ωB97X-D/6-311++G(3df,3pd) (for H, O, N) + aug-cc-pVTZ-PP with ECP28MDF (for I) level of theory”

I am missing some justification to why the ωB97X-D functional and why the 6-311++G(3df,3pd) basis set was used. There exist many benchmarks that advocate this level of theory, but without a proper reference it may seem like an arbitrary choice.

Line 80, equation (1): I am missing some specification on how the spin-orbit coupling SOC was calculated. Could the authors please elaborate. 

In addition, I believe it was Khanniche et al. (10.1016/j.comptc.2016.09.010, https://doi.org/10.1021/acsearthspacechem.6b00010) and Engsvang et al. (https://doi.org/10.1021/acsomega.4c01235) that suggested that SOC is important for iodine species in the atmosphere. It might be worth to explicitly acknowledging the previous foundational work in the manuscript.

Line 83: “… DLPNO-CCSD(T)/aug-cc-pVTZ (for H, O, and N) + aug-cc-pVTZ-PP with ECP28MDF (for I) level of theory with TightPNO and TightSCF settings.”

Engsvang et al. (https://doi.org/10.1021/acsomega.4c01235) demonstrated that relativistic effects are important to include in the Hamiltonian. Even a simple scalar relativistic method such as ZORA was found to lead to a difference. Without relativistic correction the calculated binding energies likely lead to too stable clusters. The authors should comment on this aspect.

Line 108-111: Please mention the explicit boundary conditions in the main text. Setting the boundary clusters as clusters consisting of only six molecules could lead to artefacts in the ACDC simulations, giving too high cluster formation rates (see Besel et al., https://doi.org/10.1021/acs.jpca.0c03984). Too small boundary cluster will yield too high cluster formation rates. This aspect should be elaborated in the manuscript.

Section 3.1 and figure 1: I do not see what Figure 1 is contributing with to the present study. It is simple chemistry to identify the donor/acceptor groups in molecules. No need for electrostatic potential maps for doing this. Please remove this part.

Instead it would be much more informative to include some of the cluster structures which are hidden in the SI.

Line 152: “Six-molecule clusters with an acid-to-base ratio of 1:1 (HNO₃ and HIO₃ as acids, HIO₂ as base) exhibit the lowest Gibbs free energies of formation (ΔG). This 1:1 stoichiometry preference is consistent across all cluster sizes (Figure S2).”

The 1:1 acid-to-base ratio is general finding in cluster formation studies. This was originally found by Olenius et al. (https://doi.org/10.1063/1.4819024) and generalized by Elm et al. (https://doi.org/10.1021/acs.jpca.7b08962). This finding should be put into context with previous work, as it is not a unique finding discovered here.

Line 165: “Although HNO₃-containing clusters require a higher cboundary than HIO₃–HIO₂ clusters, ambient HNO₃ concentrations (10⁸–10¹¹ molecules/cm³), spanning clean polar regions to polluted coastal environments”

Could you add a reference here for HNO₃ reaching 10⁸ molecules cm^-3 in clean polar regions?

Line 174: I do not understand figure 2(b). How can clusters that do not include HNO₃ depend on its concentration for c_boundary?

Line 206: “Given the ppb-level HNO₃ concentrations observed in the UT, this enhanced sensitivity underscores the amplified importance of HNO₃ in iodine oxoacid nucleation at high altitudes.”

Do you have a reference for HNO₃ reaching 1 ppb in the UT?

Line 223: “HIO₃ concentration was set to 1×10⁷ molecules cm^-3 in the MBL (coastal emission hotspot) (Sipilä et al., 2016) and reduced by one order of magnitude in the FT. Due to limited field constraints on HIO3 at high altitudes, its concentration was held constant above the FT.”

I am a bit concerned that the iodine oxoacid concentrations might be a bit too high in the UT. Has it actually been proven that iodine oxoacids can be transported to the upper troposphere or just been inferred? From the cited work (Twohy et al., 2002; Randel et al., 2010; Williamson et al., 2019), I only find mention of convective clouds, but not that they can transport iodine. Would iodine species formed in the lower troposphere not quite rapidly form particles and thereby be scavenged before being transported to the upper troposphere?

Line 315: “Both HNO₃-HIO₃-HIO₂ and HIO₃-HIO₂ mechanisms are consistent with the upper limit of field-observed cluster formation rates.”

In figure 6(a) and 6(b) it is seen that both mechanisms actually exceed the observed upper limit. I suspect this could be related to too strongly binding clusters. As mentioned under methods above this could originate either from the boundary conditions or the applied quantum chemical methods. This aspect should be further commented on. 

Line 344: I commend the authors for making a section on the potential uncertainties in the quantum chemical results and applied concentration. However, based on previous benchmarks, it should be explicitly stated that it is more likely that the applied methods are yielding too low free energies. Hence, the +1 kcal/mol scenario is probably the most likely.