Air pollution constitutes an environmental problem that it is known to cause many serious adverse effects on the cardiovascular and respiratory systems. The chemical characterization of particulate matter (PM) is key for a better understanding of the associations between chemistry and toxicological effects. In this work, the chemical composition and biological effects of fifteen PM10 air filter samples from three air quality stations in Catalonia with contrasting air quality backgrounds were investigated. Three-dimensional (3D) lung cancer cell cultures were exposed to these sample extracts, and cytotoxicity, reactive oxygen species (ROS) induction, metabolomics, and lipidomics were explored. The factor analysis method Multivariate Curve Resolution-Alternating Least-Squares (MCR-ALS) was employed for an integrated interpretation of the associations between chemical composition and biological effects, which could be related to urban traffic emission, biomass burning smoke, and secondary aerosols. In this pilot study, a novel strategy combining new approach methodologies and chemometrics provided new insights into the biomolecular changes in lung cells associated with different sources of air pollution. This approach can be applied in further research on air pollution toxicity to improve our understanding of the causality between chemistry and its effects.
Keywords: air pollution; chemometrics; data fusion; lipidomics; metabolomics; particulate matter; sources of pollution.