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The growth of freshly formed aerosol particles can be the bottleneck in their survival to cloud condensation nuclei. It is therefore crucial to understand how particles grow in the atmosphere. Insufficient experimental data has impeded a profound understanding of nano-particle growth under atmospheric conditions. Here we study nano-particle growth in the CLOUD (Cosmics Leaving OUtdoors Droplets) chamber, starting from the formation of molecular clusters. We present measured growth rates at sub-3 nm sizes with different atmospherically relevant concentrations of sulphuric acid, water, ammonia and dimethylamine. We find that atmospheric ions and small acid-base clusters, which are not generally accounted for in the measurement of sulphuric acid vapour, can participate in the growth process, leading to enhanced growth rates. The availability of compounds capable of stabilizing sulphuric acid clusters governs the magnitude of these effects and thus the exact growth mechanism. We bring these observations into a coherent framework and discuss their significance in the atmosphere.

Kinetics of collision-sticking processes between vapor molecules and clusters of low-volatility compounds govern the initial steps of atmospheric new particle formation. Conventional non-interacting hard-sphere models underestimate the collision rate by neglecting long-range attractive forces, and the commonly adopted assumption that every collision leads to the formation of a stable cluster (unit mass accommodation coefficient) is questionable for small clusters, especially at elevated temperatures. Here, we present a generally applicable analytical interacting hard-sphere model for evaluating collision rates between molecules and clusters, accounting for long-range attractive forces. In the model, the collision cross section is calculated based on an effective molecule–cluster potential, derived using Hamaker's approach. Applied to collisions of sulfuric acid or dimethylamine with neutral bisulfate–dimethylammonium clusters composed of 1–32 dimers, our new model predicts collision rates 2–3 times higher than the non-interacting model for small clusters, while decaying asymptotically to the non-interacting limit as cluster size increases, in excellent agreement with a collision-rate-theory atomistic molecular dynamics simulation approach. Additionally, we calculated sticking rates and mass accommodation coefficients (MACs) using atomistic molecular dynamics collision simulations. For sulfuric acid, a MAC ≈1 is observed for collisions with all cluster sizes at temperatures between 200 and 400 K. For dimethylamine, we find that MACs decrease with increasing temperature and decreasing cluster size. At low temperatures, the MAC ≈1 assumption is generally valid, but at elevated temperatures MACs can drop below 0.2 for small clusters. [ABSTRACT FROM AUTHOR]

The formation of atmospheric aerosol particles from condensable gases is a dominant source of particulate matter in the boundary layer, but the mechanism is still ambiguous. During the clustering process, precursors with different reactivities can induce various chemical reactions in addition to the formation of hydrogen bonds. However, the clustering mechanism involving chemical reactions is rarely considered in most of the nucleation process models. Oxocarboxylic acids are common compositions of secondary organic aerosol, but the role of oxocarboxylic acids in secondary organic aerosol formation is still not fully understood. In this paper, glyoxylic acid, the simplest and the most abundant atmospheric oxocarboxylic acid, has been selected as a representative example of oxocarboxylic acids in order to study the clustering mechanism involving hydration reactions using density functional theory combined with the Atmospheric Clusters Dynamic Code. The hydration reaction of glyoxylic acid can occur either in the gas phase or during the clustering process. Under atmospheric conditions, the total conversion ratio of glyoxylic acid to its hydration reaction product (2,2-dihydroxyacetic acid) in both gas phase and clusters can be up to 85%, and the product can further participate in the clustering process. The differences in cluster structures and properties induced by the hydration reaction lead to significant differences in cluster formation rates and pathways at relatively low temperatures. [ABSTRACT FROM AUTHOR]

Ion-dipole collisions can facilitate the formation of atmospheric aerosol particles, and play an important role in their detection in chemical ionization mass spectrometers. Conventionally, analytical models, or simple parametrizations, have been used to calculate rate coefficients of ion-dipole collisions in the gas phase. Such models, however, neglect the atomistic structure and charge distribution of the collision partners. To determine the accuracy and applicability of these approaches at atmospheric conditions, we calculated collision cross sections and rate coefficients from all-atom molecular dynamics collision trajectories, sampling the relevant range of impact parameters and relative velocities, and from a central field model using an effective attractive interaction fitted to the long-range potential of mean force between the collision partners. We considered collisions between various atmospherically relevant molecular ions and dipoles, as well as charged and neutral dipolar clusters. Based on the good agreement between collision cross sections and rate coefficients obtained from molecular dynamics trajectories and a generalized central field model, we conclude that the effective interactions between the collision partners are isotropic to a high degree, and the model is able to capture the relevant physico-chemical properties of the systems. In addition, when the potential of mean force is recalculated at the respective temperatures, the central field model exhibits the correct temperature dependence of the collision process. The classical parametrization by Su and Chesnavich [J. Chem. Phys., 76, 5183-5185, 1982], which combines a central field model with simplified trajectory simulations, is able to predict the collision rate coefficients and their temperature dependence quite well for molecular systems, but the agreement worsens for systems containing clusters. Based on our results, we propose the combination of potential of mean force calculation and central field model as a viable and elegant alternative to brute force sampling of individual collision trajectories over a large range of impact parameters and relative velocities. [ABSTRACT FROM AUTHOR]