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Simulating Non-Equilibrium Dynamics of Atmospheric Multicomponent Clusters

Periodic Reporting for period 2 - DAMOCLES (Simulating Non-Equilibrium Dynamics of Atmospheric Multicomponent Clusters)

Reporting period: 2017-12-01 to 2019-05-31

The aim of DAMOCLES is to achieve a comprehensive understanding of atmospheric nanocluster and ice crystal formation based on fundamental physico-chemical principles
Formation of aerosol particles and ice crystals in the atmosphere affects weather, climate and air quality. These formation processes are poorly understood and are one of the major uncertainties in predicting climate change.
Extracting accurate molecular level information from state of the art experiments is vital for sound model developments. Chemical ionization mass spectrometers can, unlike any other instruments, detect the elemental composition of many of the smallest clusters at low atmospheric concentrations. However, the charging process and energetic collisions inside the instrument change the composition of the clusters. Our objective is build an accurate model for the fate of clusters inside mass spectrometers, which will vastly improve the amount and quality of information that can be drawn from mass spectrometric measurements in atmospheric science and elsewhere.
We will use a wide palette of theoretical and computer simulation methods to build particle formation models with genuine predictive capacity. We also aim to produce reliable model for ice crystal formation. This will lead to improved predictions of aerosol concentrations and size distributions, leading to improved air quality forecasting, more accurate estimates of aerosol indirect climate forcing and other aerosol-cloud-climate interactions.
We have developed a statistical model for cluster fragmentation in the mass spectrometric instrument that is able to reproduce experimental extent of fragmentation without any semi-empirical fitting parameters.

We have discovered new classes of molecular species that efficiently form cluster with sulphuric acid, and also excluded the potential of an arrays of molecules to participate in the first stages of atmospheric particle formation.

We have developed physically consistent methodology for simulating ice crystal formation, and achieved one of the first molecular -level matches between theory and experiments in ice nucleation
We will further develop models to describe cluster that are not in equilibrium, especially concerning cluster evaporation rates. We aim to connect detected cluster mass spectra to the original neutral molecules and molecular clusters in the atmosphere by accounting for the charging and fragmentation processes occurring in the detection instrument. We will predict size distributions and formation rates atmospheric clusters as a function of temperature and vapour concentrations using a combination of theoretical and experimental information.
We will produce models that can predict ice nucleation on various seed particle types in real atmospheric conditions.