Search

Organic aerosol is a highly complex mixture of ∼104to 105unique compounds all possessing their own set of physico-chemical properties such as saturation vapour pressure and hygroscopicity. Most of these properties have not been experimentally measured and so must be estimated, resulting in large uncertainties in their predicted gas-particle partitioning and subsequent effect on human health and the climate. Dicarboxylic acids (DCAs) have been used extensively to represent oxidised organic aerosol due to their ubiquity in the atmosphere and commercial availability. Pure component saturation vapour pressures have been obtained by different techniques to enable accurate treatment of their partitioning in atmospheric models. However, an understanding of the synergistic interactions between molecules in multi-component droplets containing DCAs under atmospherically relevant conditions remains limited, relying on group contribution models to estimate physicochemical properties such as activity coefficients in complex organic multicomponent matrices. In this work, a method for extracting activity coefficients of organic species in binary organic component droplets has been developed for investigating the effect of matrix character (such as functionality and molecular weight) on component volatility. Droplets containing a compound of interest and a low-volatility organic liquid are suspended in an electro-dynamic balance for hours to days and the evaporation rate is estimated as the droplet evolves in composition. Comparison with a liquid-like evaporation model allows for the extraction of experimental activity coefficients for a range of mole fractions. Activity coefficients extracted from simple binary organic systems have been compared to and have shown good agreement with an activity coefficient estimator, Aerosol Inorganic–Organic Mixtures Functional groups Activity Coefficients (AIOMFAC). The activity coefficients of a range of DCAs dissolved in a mixed-component organic droplet have also been measured and compared to AIOMFAC. The changes in DCA activity coefficient with evolving composition from experiments mostly show reasonable agreement with AIOMFAC for all systems investigated. This showcases the ability of AIOMFAC to predict activities for multi-organic systems containing no water.