jp0c03984_si_002.pdf (3.42 MB)
Impact of Quantum Chemistry Parameter Choices and Cluster Distribution Model Settings on Modeled Atmospheric Particle Formation Rates
journal contribution
posted on 2020-07-03, 12:33 authored by Vitus Besel, Jakub Kubečka, Theo Kurtén, Hanna VehkamäkiWe
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.
History
Usage metrics
Categories
Keywords
ACDCcluster distribution dynamics modelAtmospheric Cluster Dynamics Codequantum chemistry input dataparticle formation rateQuantum Chemistry Parameter ChoicesCluster Distribution Model Settingscluster distribution dynamics simul...particle formation ratessymmetry numberModeled Atmospheric Particle Format...formation rate curve
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC