Abstract
Abstract Air pollution by fine particles represents a severe environmental health-risk. The particle’s content of toxic compounds, such as polycyclic aromatic hydrocarbons (PAH), elemental carbon/soot or redox-active transition metals (e.g. Fe), is highly relevant for their toxicity. The particulate matter (PM) composition can be determined by chemical analysis of PM-loaded filter samples but no information on the mixing state of toxicants, i.e. the distribution of toxicants within the particle ensemble, is obtainable by this approach. The mixing state, however, is a crucial parameter to assess health effects as the toxicants may either be equally distributed over many particles (internally mixed) or could be highly concentrated within a small particle sub-population (externally mixed). In the latter case, the few particles with a very high concentration of toxicants can induce stronger cellular effects at the lung-deposition site. A new approach is based on single particle mass spectrometry (SPMS) but introduces a novel, tailored laser ionisation process. Aerosol particles are on-line sampled from the air and size-characterized by laser velocimetry. The organic coating of individual particles is desorbed by intense IR-laser pulses and subsequently the relevant toxicants (transition metals, PAH and soot) are ionized and MS-detected particle-by-particle, using a novel combined UV-laser ionization scheme (Schade et al. Anal., Chem. 2019; Passig et al. ACP 2022). The novel SPMS system offers the characterisation of the most relevant PM-toxicants (soot, metals, PAH) on a sized-resolved, single particle-basis and gives insight into their mixing state. First SPMS-ambient air monitoring results for PAH or metals show that, depending on conditions, the toxicants indeed either are concentrated on a very small fraction of the particle-ensemble or are rather uniformly distributed over all particles. Future application concepts of the new SPMS-technology in air monitoring and environmental health research are discussed.
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