Semi-volatile organic compounds in fine particulate matter on a tropical island in the South China Sea

Measurements of hazardous semi-volatile organic compounds (SVOCs) in remote tropical regions are rare. In this study, polycyclic aromatic compounds (PACs) [including polycyclic aromatic hydrocarbons (PAHs), nitrated PAHs (NPAHs), and oxygenated PAHs (OPAHs)], organophosphate esters (OPEs), and phthalic acid esters (PAEs) were measured in fine particulate matter (PM2.5) at Yongxing Island in the South China Sea (SCS). The concentrations of PACs (median = 53.5 pg/m(3)) were substantially low compared with previous measurements. The concentration weighted trajectory (CWT) model showed that the eastern and southern China was the main source region of PAC, occurring largely during the northeast (NE) monsoon. The PM2.5 showed remarkably high concentrations of OPEs (median = 3231 pg/m(3)) and moderate concentrations of PAEs (13,013 pg/m(3)). Some Southeast Asian countries were largely responsible for their higher concentrations, driven by the tropical SCS monsoons. We found significant atmospheric loss of the SVOCs, which is an explanation for the low concentrations of PACs. Enhanced formation of N/OPAHs originated from tropical regions was also observed. The positive matrix factorization model was applied to apportion the SVOC sources. The results, as well as correlation analyses of the SVOC concentrations, further indicate insignificant local sources and enhanced atmospheric reactions on this island.

Automated summary

Measurements of hazardous semi-volatile organic compounds (SVOCs) in fine particulate matter (PM2.5) at Yongxing Island in the South China Sea showed low concentrations of polycyclic aromatic compounds (PACs), largely influenced by Southeast Asian countries and southern China. The atmospheric loss of SVOCs and enhanced formation of N/OPAHs from tropical regions were significant factors for the low PAC concentrations. Enhanced atmospheric reactions and insignificant local sources were further indicated through results and correlation analyses.