Abstract. Understanding new particle formation and growth is important because of the
strong impact of these processes on climate and air quality. Measurements to
elucidate the main new particle formation mechanisms are essential; however,
these mechanisms have to be implemented in models to estimate their impact
on the regional and global scale. Parameterizations are computationally
cheap ways of implementing nucleation schemes in models, but they have their
limitations, as they do not necessarily include all relevant parameters.
Process models using sophisticated nucleation schemes can be useful for the
generation of look-up tables in large-scale models or for the analysis of
individual new particle formation events. In addition, some other important
properties can be derived from a process model that implicitly calculates
the evolution of the full aerosol size distribution, e.g., the particle
growth rates. Within this study, a model (SANTIAGO – Sulfuric acid Ammonia
NucleaTIon And GrOwth model) is constructed that simulates new particle
formation starting from the monomer of sulfuric acid up to a particle size
of several hundred nanometers. The smallest sulfuric acid clusters
containing one to four acid molecules and a varying amount of base (ammonia)
are allowed to evaporate in the model, whereas growth beyond the pentamer
(five sulfuric acid molecules) is assumed to be entirely collision-controlled. The
main goal of the present study is to derive appropriate thermodynamic data
needed to calculate the cluster evaporation rates as a function of
temperature. These data are derived numerically from CLOUD (Cosmics Leaving
OUtdoor Droplets) chamber new particle formation rates for neutral sulfuric
acid–water–ammonia nucleation at temperatures between 208 and 292 K. The
numeric methods include an optimization scheme to derive the best estimates
for the thermodynamic data (dH and dS) and a Monte Carlo method to derive
their probability density functions. The derived data are compared to
literature values. Using different data sets for dH and dS in SANTIAGO
detailed comparison between model results and measured CLOUD new particle
formation rates is discussed.