Impact of Quantum Chemistry Parameter Choices and Cluster Distribution Model Settings on Modeled Atmospheric Particle...

We tested the influence of various parameters on the new particle formation rate predicted for the sulfuric acid-ammonia system using quantum chemistry and cluster distribution dynamics simulations, in our case, Atmospheric Cluster Dynamics Code (ACDC). We found that consistent consideration of the rotational symmetry number of monomers (sulfuric acid and ammonia molecules, and bisulfate and ammonium ions) leads to a significant rise in the predicted particle formation rate, whereas inclusion of the rotational symmetry number of the clusters only changes the results slightly, and only in conditions where charged clusters dominate the particle formation rate. This is because most of the clusters stable enough to participate in new particle formation have a rotational symmetry number of 1, and few exceptions to this rule are positively charged clusters. In contrast, the application of the quasi-harmonic correction for low-frequency vibrational modes tends to generally decrease predicted new particle formation rates and also significantly alters the slope of the formation rate curve plotted against the sulfuric acid concentration, which is a typical convention in atmospheric aerosol science. The impact of the maximum size of the clusters explicitly included in the simulations depends on the simulated conditions. The errors arising from a limited set of clusters are higher for higher evaporation rates, and thus tend to increase with temperature. Similarly, the errors tend to be higher for lower vapor concentrations. The boundary conditions for outgrowing clusters (that are counted as formed particles) have only a small influence on the results, provided that the definition is chemically reasonable and that the set of simulated clusters is sufficiently large. A comparison with data from the Cosmics Leaving OUtdoor Droplets (CLOUD) chamber and a cluster distribution dynamics model using older quantum chemistry input data shows improved agreement when using our new input data and the proposed combination of symmetry and quasi-harmonic corrections.