Multiphase kinetics of molecular diffusion, phase transitions and chemical reactions in liquid, semi-solid and glassy organic aerosols
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Abstract
Atmospheric aerosols play a key role in climate, air quality and public health. Aerosol particles enable the formation of clouds and precipitation and can cause adverse health effects upon inhalation, which is of high interest to the general public. Secondary organic aerosols (SOA) constitute a large and abundant subclass of atmospheric particles, but their formation rates and properties are difficult to describe with current models. In this study, kinetic multi-layer models of gas-particle interactions and aerosol surface and bulk chemistry (KM-GAP, KM-SUB) have been developed and applied to elucidate the multiphase chemical kinetics of molecular diffusion, phase transitions and chemical reactions in liquid, semi-solid and glassy organic aerosols.
For the efficient characterization and comparison of different systems, conditions, and studies of gas uptake by aerosol and cloud particles, a comprehensive kinetic framework and classification scheme was developed. According to this framework, reaction systems can be associated with one of two major kinetic regimes (reaction-diffusion or mass transfer regime), each of which comprises four distinct limiting cases, characterised by the dominant reaction location and a single rate-limiting process (chemical reaction, bulk diffusion, gas-phase diffusion or mass accommodation). For the treatment of SOA formation, the kinetic framework was extended to incorporate gas phase reactions and related to molecular corridors, which are ensemble pathways describing the chemical evolution and volatility of organic aerosol components as a function of molar mass and oxygen-to-carbon ratio.
A novel computational method (Monte-Carlo genetic algorithm, MCGA) was developed for efficient, automated and unbiased optimization of kinetic model parameters to multiple experimental data sets. The MCGA approach utilizes a sequence of heuristic and deterministic optimization methods to contain the solution of an inverse modelling problem and to explore the space of solutions with similar model output. The method was successfully applied to several reaction systems of practical relevance, including the oligomerisation of proteins, heterogeneous reactions of HOX radicals, chemical ageing of organic aerosols and production of reactive oxygen species (ROS) in human lung lining fluid.
Model calculations show that mass transport by diffusion can be significantly retarded in organic particles exhibiting a semi-solid or glassy phase state. Simulation along characteristic trajectories of atmospheric updraft show that organic aerosol can persist long enough in glassy states and solid/liquid core-shell morphologies to let heterogeneous ice nucleation in the deposition and immersion mode prevail over homogeneous ice nucleation. The predominant cloud formation pathway is strongly dependent on temperature, updraft velocity, particle size and chemical composition.
The kinetic modelling and optimization tools were used to analyse a large data set of ozone uptake by the unsaturated SOA surrogate shikimic acid. Characteristic diffusion and reaction rate coefficients were derived from the experimental data and are consistent with earlier assessments of ozone and water diffusivity in SOA. The model revealed a surface oxidation mechanism involving long-lived reactive oxygen intermediates (ROIs). The ROIs appear to enable ozone destruction through an effective self-reaction mechanism, which may be of general relevance for atmospheric aerosols.
A radioactive tracer technique was applied to quantify the amount of nitrogen containing compounds incorporated into the particle phase of SOA from the monoterpene α-pinene, an important atmospheric SOA precursor. The kinetic experiments in a flow reactor show organic nitrate mass fractions of up to 40% and close correlations with SOA particle numbers, suggesting that organic nitrates may play an important role in the nucleation and growth of atmospheric nanoparticles.