Whilst general policy objectives to reduce airborne particulate matter (PM) health effects are to reduce exposure to PM as a whole, emerging evidence suggests that more detailed metrics associating impacts with different aerosol components might be needed. Since it is impossible to conduct toxicological screening on all possible molecular species expected to occur in aerosol, in this study we perform a proof-of-concept evaluation on the information retrieved from in silico toxicological predictions, in which a subset (N = 104) of secondary organic aerosol (SOA) compounds were screened for their mutagenicity potential. An extensive database search showed that experimental data are available for 13 % of the compounds, while reliable predictions were obtained for 82 %. A multivariate statistical analysis of the compounds based on their physico-chemical, structural, and mechanistic properties showed that 80 % of the compounds predicted as mutagenic were grouped into six clusters, three of which (five-membered lactones from monoterpene oxidation, oxygenated multifunctional compounds from substituted benzene oxidation, and hydroperoxides from several precursors) represent new candidate groups of compounds for future toxicological screenings. These results demonstrate that coupling model-generated compositions to in silico toxicological screening might enable more comprehensive exploration of the mutagenic potential of specific SOA components. 1 Introduction Ambient air pollution was ranked as the seventh highest risk factor for human health (Lim et al., 2012), being responsible for almost 3 billion deaths per year globally. Evidence for air pollution impacts on life expectancy and for cardiovascular and respiratory illnesses has grown considerably in the last 2 decades (Beelen et al., 2014), and the ongoing global demographic and societal changes (ageing, urbanization) are projected to exacerbate atmospheric pollution health effects. Evidence from both short-and long-term epidemiological effects of particulate matter with particle diameters below 10 or 2.5 µm (PM 10 or PM 2.5 , respectively) is robust, with a range of possible policies aiming to mitigate PM health effects reflected by the possible sources from which PM arises. Since at least the early 2000s, metrics for PM chemical composition and sources have been incorporated along with PM 10 , PM 2.5 , or PM 0.1 (ultrafine) in epidemiological studies. Recently, black carbon (BC), which is a proxy for primary combustion particles, was associated with an increased risk of mortality 2 times greater than for total PM (Janssen et al., 2011). Recent findings highlight the fact that more detailed air quality metrics may be valuable in evaluating health risks by specifically distinguishing between, for example, black carbon, secondary organic aerosols, and inorganic aerosols (Cassee et al., 2013). A study in London, UK suggested that certain particle components might be more important to specific diseases (Atkinson et al., 2010), with some toxicological studies suggesting p...