A Monte Carlo approach to study the effect of ions on the nucleation of sulfuric acid–water clusters

Dan Krog*, Martin B. Enghoff, Christoph Köhn

*Corresponding author for this work

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The nucleation of sulfuric acid–water clusters is a significant contribution to the formation of aerosols as precursors of cloud condensation nuclei (CCN). Depending on the temperature, there is an interplay between the clustering of particles and their evaporation controlling the efficiency of cluster growth. For typical temperatures in the atmosphere, the evaporation of (Formula presented.) clusters is more efficient than the clustering of the first, small clusters, and thus their growth is dampened at its early stages. Since the evaporation rates of small clusters containing an (Formula presented.) ion are much smaller than for purely neutral sulfuric acid clusters, they can serve as a central body for the further attachment of (Formula presented.) molecules. We here present an innovative Monte Carlo model to study the growth of aqueous sulfuric acid clusters around central ions. Unlike classical thermodynamic nucleation theory or kinetic models, this model allows to trace individual particles and thus to determine properties for each individual particle. As a benchmarking case, we have performed simulations at (Formula presented.) a relative humidity of 50% with dipole and ion concentrations of (Formula presented.) and (Formula presented.). We discuss the runtime of our simulations and present the velocity distribution of ionic clusters, the size distribution of the clusters as well as the formation rate of clusters with radii (Formula presented.). Simulations give reasonable velocity and size distributions and there is a good agreement of the formation rates with previous results, including the relevance of ions for the initial growth of sulfuric acid–water clusters. Conclusively, we present a computational method which allows studying detailed particle properties during the growth of aerosols as a precursor of CCN.

Original languageEnglish
JournalJournal of Computational Chemistry
Issue number13
Pages (from-to)1250-1262
Publication statusPublished - 2023


  • Effect of ions
  • High-performance computing
  • Monte Carlo simulation
  • Nucleation of sulfuric acid–water clusters
  • Octree


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