Investigation of the evolution of atmospheric particles with integration of the stochastic particle-resolved model PartMC-MOSAIC and atmospheric measurements

Atmospheric aerosols are known to have strong impacts on human health, visibility and the climate system. They originate directly from either anthropogenic or natural emission, or can be also formed through gas- particle conversion processes. Aerosol particles in the atmosphere often represent a complex mixture of a wide variety of species, and the mixing state can change during the evolution of particles in the ambient environment, leading to significantly different effects on the climate system compared to freshly emitted condition. With the recently-developed particle-resolved model PartMC-MOSAIC, the mixing state and other physico-chemical properties of individual aerosol particles can be tracked as the particles undergo aerosol aging processes. However, existing PartMC-MOSAIC applications have mainly been based on idealized scenarios, and a link to real atmospheric measurement has not yet been established. In this thesis, we extend the capability of PartMC-MOSAIC and apply the model framework to three distinct scenarios with different environmental conditions to investigate the physical and chemical aging of aerosols in those environments. The first study is to investigate the evolution of particle mixing state and cloud condensation nuclei (CCN) activation properties in a ship plume. Comparisons of our results with observations from the QUANTIFY Study in 2007 in the English channel and the Gulf of Biscay showed that the model was able to reproduce the observed evolution of total number concentration and the vanishing of the nucleation mode consisting of sulfate particles. Further process analysis revealed that during the first hour after emission, dilution reduced the total number concentration by four orders of magnitude, while coagulation reduced it by an additional order of magnitude. Neglecting coagulation resulted in an overprediction of more than one order of magnitude in the number concentration of particles smaller than 40 nm at a plume age of 100 s. Coagulation also significantly altered the mixing state of the particles, leading to a continuum of internal mixtures of sulfate and black carbon. The impact of condensation on CCN concentrations depended on the supersaturation threshold at which CCN activity was evaluated. Nucleation was observed to have a limited impact on the CCN concentration in the ship plume we studied, but was sensitive to formation rates of secondary aerosol. For the second study we adapted PartMC to represent the aerosol evolution in an aerosol chamber, with the intention to use the model as a tool to interpret and guide chamber experiments in the future. We added chamber-specific processes to our model formulation such as wall loss due to particle diffusion and sedimentation, and dilution effects due to sampling. We also implemented a treatment of fractal particles to account for the morphology of agglomerates and its impact on aerosol dynamics. We verified the model with published results of self-similar size distributions, and validated the model using experimental data from an aerosol chamber. To this end we developed a fitting optimization approach to determine the best-estimate values for the wall loss parameters based on minimizing the l2-norm of the model errors of the number distribution. Obtaining the best fit required taking into account the non-spherical structure of the particle agglomerates. Our third study focuses on the implementation of volatility basis set (VBS) framework in PartMC-MOSAIC to investigate the chemical aging of organic aerosols in the atmosphere. The updated PartMC-MOSAIC model framework was used to simulate the evolution of aerosols in air trajectories initialized from CARES field campaign conducted in California in June 2010. The simulation results were compared with aircraft measurement data during the campaign. PartMC-MOSAIC was able to produce gas and aerosol concentrations at similar levels compared to the observation data. Moreover, the simulation with VBS enabled produced consistently more secondary organic aerosols (SOA). The investigation of particle mixing state revealed that the impact of VBS framework on particle mixing state is sensitive to the daylight exposure time