Polycyclic Aromatic Hydrocarbons in the Marine Atmosphere from the Western Pacific to the Southern Ocean: Spatial Variability, Gas/Particle Partitioning, and Source Apportionment.
Xue ZhangZi-Feng ZhangXianming ZhangFu-Jie ZhuYi-Fan LiMinghong CaiRoland KallenbornPublished in: Environmental science & technology (2022)
The spatial variability of polycyclic aromatic hydrocarbons (PAHs) in the marine atmosphere contributes to the understanding of the global sources, fate, and impact of this contaminant. Few studies conducted to measure PAHs in the oceanic atmosphere have covered a large scale, especially in the Southern Ocean. In this study, high-volume air samples were taken along a cross-section from China to Antarctica and analyzed for gaseous and particulate PAHs. The data revealed the spatial distribution, gas-particle partitioning, and source contributions of PAHs in the Pacific, Indian, and Southern Oceans. The median concentration (gaseous + particulate) of ∑ 24 PAHs was 3900 pg/m 3 in the Pacific Ocean, 2000 pg/m 3 in the Indian Ocean, and 1200 pg/m 3 in the Southern Ocean. A clear latitudinal gradient was observed for airborne PAHs from the western Pacific to the Southern Ocean. Back trajectories (BTs) analysis showed that air masses predominantly originated from populated land had significantly higher concentrations of PAHs than those from the oceans or Antarctic continents/islands. The air mass origins and temperature have significant influences on the gas-particle partitioning of PAHs. Source analysis by positive matrix factorization (PMF) showed that the highest contribution to PAHs was from coal combustion emissions (52%), followed by engine combustion emissions (27%) and wood combustion emissions (21%). A higher contribution of PAHs from wood combustion was found in the eastern coastal region of Australia. In contrast, engine combustion emissions primarily influenced the sites in Southeast Asia.
Keyphrases
- polycyclic aromatic hydrocarbons
- heavy metals
- particulate matter
- municipal solid waste
- health risk assessment
- sewage sludge
- human health
- climate change
- magnetic resonance imaging
- risk assessment
- depressive symptoms
- drinking water
- air pollution
- computed tomography
- contrast enhanced
- machine learning
- artificial intelligence
- health risk
- cell wall