An Integrated Workflow Assisted by In Silico Predictions To Expand the List of Priority Polycyclic Aromatic Compounds

The limited information in existing mass spectral libraries
hinders
an accurate understanding of the composition, behavior, and toxicity
of organic pollutants. In this study, a total of 350 polycyclic aromatic
compounds (PACs) in 9 categories were successfully identified in fine
particulate matter by gas chromatography high resolution mass spectrometry.
Using mass spectra and retention indexes predicted by in silico tools
as complementary information, the scope of chemical identification
was efficiently expanded by 27%. In addition, quantitative structure–activity
relationship models provided toxicity data for over 70% of PACs, facilitating
a comprehensive health risk assessment. On the basis of extensive
identification, the cumulative noncarcinogenic risk of PACs warranted
attention. Meanwhile, the carcinogenic risk of 53 individual analogues
was noteworthy. These findings suggest that there is a pressing need
for an updated list of priority PACs for routine monitoring and toxicological
research since legacy polycyclic aromatic hydrocarbons (PAHs) contributed
modestly to the overall abundance (18%) and carcinogenic risk (8%).
A toxicological priority index approach was applied for relative chemical
ranking considering the environmental occurrence, fate, toxicity,
and analytical availability. A list of 39 priority analogues was compiled,
which predominantly consisted of high-molecular-weight PAHs and alkyl
derivatives. These priority PACs further enhanced source interpretation,
and the highest carcinogenic risk was attributed to coal combustion.