the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 08 Apr 2024
Cluster Dynamics-based Parameterization for Sulfuric Acid-Dimethylamine Nucleation: Comparison and Selection through Box- and Three-Dimensional- Modeling
Abstract. Clustering of gaseous sulfuric acid (SA) enhanced by dimethylamine (DMA) is a major mechanism for new particle formation (NPF) in polluted atmospheres. However, uncertainty remains regarding the SA-DMA nucleation parameterization that reasonably represents cluster dynamics and is applicable across various atmospheric conditions. This uncertainty hinders accurate three-dimensional (3-D) modeling of NPF and subsequent assessment of its environmental and climatic impacts. Here we extensively compare different cluster dynamics-based parameterizations for SA-DMA nucleation and identify the most reliable one through a combination of box-model simulations, 3-D modeling, and in-situ observations. Results show that the parameterization derived from Atmospheric Cluster Dynamic Code (ACDC) simulations, incorporating the latest theoretical insights (DLPNO-CCSD(T)/aug-cc-pVTZ//ωB97X-D/6-311++G(3df,3pd) level of theory) and adequate representation of cluster dynamics, exhibits dependable performance in 3-D NPF simulation for both winter and summer conditions in Beijing and shows promise for application in diverse atmospheric conditions. Another ACDC-derived parameterization, replacing the level of theory with RI-CC2/aug-cc-pV(T+d)Z//M06-2X/6–311++G(3df,3pd), also performs well in NPF modeling at relatively low temperatures around 280 K but exhibits limitations at higher temperatures due to inappropriate representation of SA-DMA cluster thermodynamics. Additionally, a previously reported parameterization incorporating simplifications is applicable for simulating NPF in polluted atmospheres but tends to overestimate particle formation rates under conditions of elevated temperature (> ~300 K) and low condensation sink (< ~3×10-3 s-1). Our findings highlight the applicability of the new ACDC-derived parameterization, which couples the latest SA-DMA nucleation theory and holistic cluster dynamics, in 3-D NPF modeling. The ACDC-derived parameterization framework provides valuable reference for developing parameterizations for other nucleation systems.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2024-642', Anonymous Referee #2, 25 Apr 2024
General comments:
The work conducts comprehensive comparison of different cluster dynamics-based parameterizations for SA-DMA nucleation by integrating box-model simulations, 3-D modeling, and in-situ observations. It is found that ACDC_DB performs well in modeling 3-D NPF for both winter and summer in Beijing and shows promise for application in various atmospheric environments. Furthermore, ACDC_RM_SF0.5 exhibits effective applicability at ~280 K, but has limitations in predicting J1.4 at elevated T. While Dynamic_Sim is applicable for simulating NPF in polluted atmospheres but makes significant overestimation of J1.4 under conditions of high T and low CS.The topic discussed in this paper is highly meaningful for developing parameterizations for various nucleation systems. The reported results are clearly presented and are relevant to the scope of Atmos. Chem. Phys. I recommend publication of this manuscript after consideration of the following comments.
Specific comments:
1) Lines 94-95: Please explain briefly the reason for considering such three simplifications within Dynamics_Sim.
2) Line 281: To make a clear understanding among readers, it would be better to provide the concept of the chemical initial and boundary conditions in WRF-Chem/R2D-VBS simulations.
3) Figure 6C: It can be noted that ACDC_DB and Dynamic_Sim also exhibit an underestimation of averaged PNSDs in the 2-100 nm range in comparison to observation. Can the authors account for the cause of this phenomenon？Technical corrections:
1) Lines 143-144: “n and m represent the number of SA and DMA molecules in a cluster” should be “m and n represent the number of SA and DMA molecules in a cluster”.
2) Lines 465 and 482: “ACDC_RM” should be “ACDC_RM_SF0.5”.
3) Supporting Information, lines 37 and 38: “A: ΔG = 13.5 kcal/mol; B: ΔG = 12.9 kcal/mol” should be “A: ΔG = -13.5 kcal/mol; B: ΔG = -12.9 kcal/mol”. -
CC1: 'Comment on egusphere-2024-642', Tinja Olenius, 26 Apr 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-642/egusphere-2024-642-CC1-supplement.pdf
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RC2: 'Comment on egusphere-2024-642', Anonymous Referee #1, 03 Jun 2024
This manuscript compared the simulations of new particle formation rate from sulfuric acid (H2SO4) and dimethylamine (DMA) by different molecular cluster kinetics modeling under various conditions (e.g., different T and CS) and aims to find applicable parameterizations for 3-D NPF modeling in Beijing. The provided results indicated that: ACDC_DB, an ACDC derived parameterization, incorporated into WRF-Chem/R2D-VBS model can effectively reproduce particle formation rates and PNSDs evolution for both winter and summer in Beijing. The content of this paper is useful for developing parameterizations aiming at predicting or simulating NPF in urban areas. The manuscript is well written and the topic fits the scope of Atmos. Chem. Phys. I recommend publication of this manuscript after responding the following comments.
Specific comments:
- The authors should clarify the advantage or difference of the parameterizations developed using ACDC to the one used in Dynamic_Sim. On the words, why the authors developed ACDC based parameterizations rather than making iteration on the base of Dynamic_Sim in L173-176 and in the introduction part. Moreover, except for making comparison with Dynamic_Sim, what’s the consideration of setting the ACDC_BC coupling with three simplifications?
- The look-up table approach has its limitation due to the ignorance of the explicit interactions of clusters with gas phase precursors and pre-existing particles. The author should add some discussion about the disadvantage of the applied look-up table approach and discuss about the possible conditions that may lead to the biased simulation results.
- In Figure S8, it seems to me that ACDC_RM_SF0.5 overestimate the formation rate by a factor of 2 at 293K, please check the simulation results or discuss the possible reasons. Would this influence the 3D model simulations during summer, leading to the overestimation of J1.4? Moreover, Figure S8 also indicated that ACDC_DB and Dynamic_Sim overestimate the formation rate more at 293K compared with at 278K, would this be the reason of the overestimation during summer?
Technical comments:
- L90-91: check the reference
- Lines 465 and 482: “ACDC_RM” should be “ACDC_RM_SF0.5”
- Line 476-478 and other parts in section 3.1: I suggest using “overestimate” and “underestimate” instead of “applicable “and “suitable “, since the discussion in section 3.1 is the evaluation of different simplifications on the molded J1.4 for ADCD_RM and ACDC_DB.
- Line 525: Replace the comma of ‘ACDC_RM show higher concentrations,’ with period.
Citation: https://doi.org/10.5194/egusphere-2024-642-RC2
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