A modelling methodology to predict the range of organic components expected to condense to atmospheric aerosol: Sensitivities to fundamental properties and routes for reduced complexity parameterisations

Atmospheric aerosol particles are an important yet uncertain component of climate change and air quality. Influencing climate directly by the scattering and absorption of solar radiation and indirectly through their role as cloud condensation nuclei, their radiatively important properties are determined by the chemical composition, mass loading, mixing state and size distribution, as are their impacts on human health. Mechanistic understanding and knowledge of individual compounds involved in the chemical evolution of aerosol particles is far from complete. A full chemical analysis of the organic component of atmospheric aerosols is not available. Whilst explicit hydrocarbon oxidation mechanisms that track many thousands of degradation products of volatile organic compounds (VOC) have been developed, aerosol schemes in large-scale models neglect the majority of chemical components predicted to occur in the organic mixture and will continue to do so in the future. This is a result of prohibitive computational expense of explicit mechanisms which must be avoided via a reduction in complexity (numerical, chemical or both). Reduction mechanisms that neglect compositional information are widely used to derive those parameters deemed important for climatic and health impacts. However, it is possible to make detailed predictions of the range of organic components expected to condense to atmospheric aerosol by combining a gas/particle partitioning model with a detailed gas phase chemical mechanism. Provided they are of sufficient skill, these predictions can be used as the basis for process and composition complexity reduction whilst retaining mechanistic understanding. Here we present development of compound selection methodologies that combine detailed gas phase mechanisms, pure component vapour pressure calculations, thermodynamic properties and a gas/aerosol partition model. As an example, we combine the methodology with the master chemical mechanism (MCM) to simulate anthropogenically dominated and biogenically dominated scenarios at a chosen field site. Sensitivities to composition dependent properties are explored whilst we investigate the distribution of potential condensing compounds for use in a reduced complexity framework for calculating equilibrium vapour pressures above an aqueous solution in large scale schemes.