RESUMEN
The real-time detection of the mixing states of polycyclic aromatic hydrocarbons (PAHs) and nitro-PAHs in ambient particles is of great significance for analyzing the source, aging process, and health effects of PAHs and nitro-PAHs; yet there is still few effective technology to achieve this type of detection. In this study, 11 types of PAH and nitro-PAH standard samples were analyzed using a high performance-single particle aerosol mass spectrometer (HP-SPAMS) in lab studies. The identification principles 'parent ions' and 'mass-to-charge (m/z) = 77' of each compound were obtained in this study. It was found that different laser energies did not affect the identification of the parent ions. The comparative experiments of ambient atmospheric particles, cooking and biomass burning emitted particles with and without the addition of PAHs were conducted and ruled out the interferences from primary and secondary organics on the identification of PAHs. Besides, the reliability of the characteristic ions extraction method was evaluated through the comparative study of similarity algorithm and deep learning algorithm. In addition, the real PAH-containing particles from vehicle exhaust emissions and ambient particles were also analyzed. This study improves the ability of single particle mass spectrometry technology to detect PAHs and nitro-PAHs, and HP-SPAMS was superior to SPAMS for detecting single particles containing PAHs and nitro-PAHs. This study provides support for subsequent ambient observations to identify the characteristic spectrum of single particles containing PAHs and nitro-PAHs.