AbstractsPhysics

Formation of aerosol particles from condensable vapors is a ubiquitous phenomenon in the atmosphere. Aerosols can affect regional and global climate, as well as visibility and human health. The work of this thesis contributes to the numerous efforts made to build understanding of atmospheric particle formation mechanisms. The focus is on the first molecular-level steps, where clustering of individual gas-phase molecules initiates the process, and the applied method is dynamic cluster population modeling. Sets of sub-2 nm molecular clusters are simulated in conditions relevant to the atmosphere or laboratory considering vapor production, external sinks for clusters and vapors, cluster collision and evaporation processes, and in some cases also ionization and recombination by generic ionizing species. Evaporation rates are calculated from the cluster formation free energies computed with quantum chemical methods. As sulfuric acid has been shown to be the key component in particle formation in most boundary layer locations, the majority of the work presented here concentrates on simulating sulfuric acid-containing clusters in the presence of potentially enhancing species, namely ammonia and amines. In laboratory experiments, these base compounds have been found to be capable of enhancing sulfuric acid driven particle formation to produce formation rates around the magnitude observed in the atmosphere. This result is reproduced by the cluster model. In this work, the performance of the modeling tools is validated against experimental data also by comparing simulated concentrations of charged sulfuric acid ammonia clusters to those measured with a mass spectrometer in a chamber experiment. Examination of clustering pathways in simulated sulfuric acid ammonia and sulfuric acid dimethylamine systems shows that the clustering mechanisms and the role of ions may be very different depending on the identity of the base. In addition to predictions related to cluster formation from different precursor vapors, the model is applied to study the effects of varying conditions on the qualitative behavior of a cluster population and quantities that have been deduced from measured cluster concentrations. It is demonstrated that the composition of the critical cluster corresponding to the maximum free energy along the growth pathway cannot be reliably determined from cluster formation rates by commonly used methods. Simulations performed using a simple model substance show that cluster growth rates determined from the fluxes between subsequent cluster sizes are likely to differ from the growth rates deduced from the time evolution of the concentrations as in experiments, with the difference depending on the properties of the substance as well as ambient conditions. Finally, the effect of hydration and base molecules on sulfuric acid diffusion measurement is assessed by mimicking an experimental setup. Applications of cluster population simulations are diverse, and the development of these types of modeling tools provides useful…