the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 17 Oct 2023
Rapid Iodine Oxoacids Nucleation Enhanced by Dimethylamine in Broad Marine Regions
Haotian Zu
Yiqun Lu
Abstract. Recent experiment (He et al, 2021, Science) revealed a vital nucleation process of iodic acid (HIO3) and iodous acid (HIO2) under the marine boundary layer conditions. However, HIO3-HIO2 nucleation cannot effectively derive the observed rapid new particle formation (NPF) in broad marine regions. Dimethylamine (DMA) is a promising basic precursor to enhance nucleation considering its strong ability to stabilize acidic clusters and the wide distribution in marine atmosphere, while its role in HIO3-HIO2 nucleation remains unrevealed. Hence, a method combining quantum chemical calculations and Atmospheric Cluster Dynamics Code (ACDC) simulations was utilized to study the HIO3-HIO2-DMA nucleation process. We found that DMA can compete with HIO2 to accept the proton from HIO3 as a basic precursor in the most stable configurations of HIO3-HIO2-DMA clusters. DMA can significantly enhance the cluster formation rates of HIO3-HIO2 kinetically for more than 103-fold in regions with abundant amine and scarce iodine based on combined factors of high nucleation ability and high concentration of DMA. Furthermore, the iodine oxoacids nucleation enhanced by DMA may explain the sources of rapid NPF events under different conditions corresponding to multiple ocean regions, which can provide important inspirations to understand the frequent and intensive NPF events in broad marine regions.
- Preprint
(2110 KB) - Metadata XML
-
Supplement
(546 KB) - BibTeX
- EndNote
Haotian Zu et al.
Status: open (extended)
-
RC1: 'Comment on egusphere-2023-1774', Jonas Elm, 24 Oct 2023
reply
General Comments:
Zu et al. investigate the influence of dimethylamine (DMA) on HIO3-HIO2 cluster formation using quantum chemical methods and atmospheric cluster dynamics simulations. This is an excellent and natural extension of the previous studies on iodine oxoacids by the same group.
A funneling approach is used to identify the cluster configurations lowest in free energy. The final cluster structures are calculated using density functional theory (ωB97X-D/6-311++G (3df,3pd)) and the single point energy is calculated using RI-CC2/aug-cc-pVTZ calculations. The calculated thermochemistry is applied as input to the atmospheric cluster dynamics code (ACDC) to simulate new particle formation rates in various marine regions (Mace Head, Zhejiang and Aboa). The main finding is that the HIO3-HIO2 cluster formation rates does not correspond to the NPF observations, but DMA enhance the cluster formation rate by several orders of magnitude, thereby increasing the agreement between the modelling and the observations.
I only have some minor quarrels with the applied methodology. The cluster formation simulations are very sensitive to the quantum chemical data, so some sensitivity runs should be performed to see how robust the conclusions are to the applied level of theory. In addition, the influence of other nucleation precursors (SA, MSA, multiple bases, ect) should be further discussed in the manuscript to emphasize that the HIO3-HIO2-DMA mechanism is not the only explanation for the gap between theory and measurements. However, the authors do not need to carry out the actual calculations, just discuss the potential importance of other species.
Overall, I believe the chosen systems and current study at hand is an interesting addition to the literature. The manuscript is easy to follow and the topic falls within the scope of ACP.
Specific Comments:
Introduction: I am missing some introduction to what we, in general, know about cluster formation from previous quantum chemical studies. Please put the current study into context of the whole field and not just iodine studies. What vapours have previously been studied and found important and what are the main findings of previous work?
Line 38: How high are the HIO3 and HIO2 concentrations measured at Mace Head? Please state the concentrations here as well.
Line 73-74: ”Firstly, the ABCluster program (Zhang and Dolg, 2015) was performed to generate up to 120000 initial isomer structures using the artificial bee algorithm.”
Where does the number 120000 come from? Is this the ABCluster population value (SN) times the number of generations? Some more information on the ABCluster parameters would be a useful addition.
Line 75-91: I am missing some comments on the accuracy of the applied configurational sampling methodology and the applied quantum chemical methods.
- Only saving 1000 local minima from the ABCluster search sounds a bit low. How certain are the authors that they have located the global minimum?
- As the UFF forcefield cannot handle bond breaking a more diverse pool of clusters is usually desirable. This is usually done by performing ABCluster runs with ionic monomers as well (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?
- How accurate are the RI-CC2/aug-cc-pVTZ calculations? The leading terms in the CC2 equations are MP2-like, at the cost of N5. Hence, you could get accurate DLPNO-CCSD(T)/aug-cc-pVTZ calculations at essentially the same computational cost.
- The authors admit that previous agreement with experiments is caused by random cancellation of errors. Our previous work has shown (Schmitz et al., https://doi.org/10.1021/acsomega.0c00436) that RI-CC2/aug-cc-pVTZ is severely overbinding, i.e. yielding too negative binding energies, thus leading to too stable clusters. Where is the remaining error cancellation coming from? All missing effects in the simulations (hydration, ionic effects, anharmonicity, potential inadequate sampling, ect …) would make the clusters more stable and hence make the current results agree less with experiments.
- ACDC simulations are extremely sensitive to the applied QC methods, and we can essentially get whatever we want by tweaking the level of theory. Hence, some further information on how we can trust the results is warranted. How robust are the conclusions to the applied level of theory? I suggest the authors test if the ωB97X-D/6-311++G(3df,3pd) calculations without RI-CC2 are yielding the same conclusions. Hence, this would not require additional calculations, but vastly improve the reliability of the study.
Line 113-115: Please also mention the boundary conditions here in the main text. Setting the boundary clusters as clusters consisting of only six molecules could lead to artefacts in the ACDC simulations, thereby yielding too high cluster formation rates (see Besel et al., https://doi.org/10.1021/acs.jpca.0c03984). For some acid-base systems the “critical cluster” is already found within the initial 2x2 cluster system, however this depend on the given base (https://doi.org/10.1021/acs.jpca.3c00068). Overall, I am not entirely convinced that the boundary conditions are adequate in the current study and might yield too high cluster formation rates. Please elaborate on this aspect.
Line 118-132: 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.
Line 137: “… , which proves the prediction of electrostatic potential analysis”
Please remove.
Line 143: “… and HIO2 can also act as a stabilizing base in the neutral nucleation process of HIO3-HIO2” and “Hence, the participation of DMA may potentially lead to a competition between two basic molecules for proton transfer reaction.”
I am not completely comfortable calling iodous acid a base (in the Brøndsted-Lowry acid-base formalism). I agree that the HIO2 show peculiar proton transfer dynamics, but I would refrain from calling it a base. I guess it is technically amphoteric.
Line 153-154: “… which possesses relatively stronger basicity than HIO2 in the process of proton transfer.”
What is the gas-phase basicity and pKa values of DMA and HIO2 respectively?
Line 180: What is the absolute cluster formation rate for the conditions given in Figure 3? How does this compare to the conventional SA-DMA system?
Line 201-202: “… and the HIO3-HIO2-DMA ternary nucleation is critical in explaining the missing sources of new particles especially in the place where the concentrations of HIO2 and DMA are similar.”
I would be careful stating that the HIO3-HIO2-DMA mechanism is the “critical” missing link. It might contribute, but other mechanisms might also be important. Some discussion on the potential other species (SA, MSA, multibases, water, ect) that might contribute to cluster formation in marine environments would be a welcome addition to the manuscript.
Line 204-205: “This is the first time that a combined influence of multiple bases has been discovered in the nucleation process driven by HIO3, …”
Again, I am not comfortable calling HIO3-HIO2-DMA a “two”-base system. Please remove this sentence.
Line 215: I really like Figure 4. It is an excellent way to show at what conditions the different pathways dominate.
Line 231: “The J of HIO3-HIO2-DMA and HIO3-HIO2 in Mace Head are shown …”
To avoid misinterpreting this as actual measurements at Mace Head, please specify that these are simulations of conditions corresponding to Mace Head.
Section 3.3 – cluster formation rates: I understand the rationale behind Figure 5. However, I believe it would be worth to more clearly state in the text that this is just a mechanism, potentially one out of many, that increases the rates such that they match the observations. The measurements are essentially the sum of all possible nucleation pathways. This means that all possible nucleating precursor vapours contribute to the measured J-value. For instance, how would the results be influenced if your simulations included water, sulfuric acid or base synergy such as having both ammonia and DMA present? All these factors would yield clusters lower in free energy, increasing the cluster formation rates, and hence push the agreement further away from the observations.
Line 293-295: “However, considering the conditions of humidity in oceanic atmosphere and the complexity of marine NPF events, future research should investigate the role of water molecules and other crucial precursors to establish a comprehensive multi-component nucleation mechanism in the marine atmosphere.”
I believe this is a very important point, that should be mentioned and discussed much earlier and not just as an outline.
Technical corrections:
Line 12: derive -> drive
Line 13: broad marine regions -> various? marine regions
Line 51: Quelever -> Quéléver
Line 86: Kuerten should be Kürten.
Line 176: Kurten -> Kurtén. Please check the spelling of all Finnish authors in the references as many umlauts are missing.
Citation: https://doi.org/10.5194/egusphere-2023-1774-RC1
Haotian Zu et al.
Haotian Zu et al.
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 224 | 49 | 11 | 284 | 16 | 4 | 6 |
- HTML: 224
- PDF: 49
- XML: 11
- Total: 284
- Supplement: 16
- BibTeX: 4
- EndNote: 6
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1