Using a pattern recognition approach to link inorganic chemical fingerprints of ambient PM sub(2.5-0.1) with in vitro biological effects

Atmospheric fine particulates act as prime vehicles for the transport of toxic chemicals into the human respiratory system on a daily basis and adverse human health effects do exist. By examining toxicological differences and chemical composition of ambient fine particles using a novel experimental design and chemometric approach, the present work examines the hypothesis: that it is not clear whether there are significant differences in public health risk from exposure to fine particles in a rural location compared to those in urban locations. In the present study, an investigation into the inorganic chemical characteristics and biological effects of PM sub(2.5-0.1) on human lung epithelial cell line A549 has been performed. Biological responses were evaluated by in vitro tests using equivalent masses of PM sub(2.5-0.1) samples, collected during different seasons at urban and rural locations in Cork, Ireland. The relationship between the biological responses and the chemical composition of the samples were investigated using Principal Component Analysis followed by Partial Least Squares regression analysis. The PM sub(2.5-0.1) samples collected at three contrasting sites in Cork demonstrated the ability to generate reactive oxygen species upon exposure irrespective of season. However, the magnitude of generation was somewhat higher for samples collected in the urban sites, compared to those generated by rural samples. Similarly, metals such as Cu and Mn were found to be present in larger quantities in the urban-based composite samples compared to those for their rural counterparts. The induction of interleukin 6 determined in this study followed a very similar seasonal trend to the measured concentrations of potassium ions in the PM sub(2.5-0.1) samples to which the A549 cells were exposed. The current study provides further support that identifying important chemical components and their sources, with subsequent targeted emission controls, which will likely prove to be a more cost-effective strategy for mitigating toxicity and protecting human health, than current approaches which depend on uncharacterized total particle mass, especially when sophisticated pattern recognition techniques are employed to assess limited airborne datasets.