Spatiotemporal distribution and dynamic modeling of atmospheric gaseous polycyclic aromatic hydrocarbons in a rapidly urbanizing city: Nanjing, China.

Multiple studies have evaluated the concentration and lung cancer risk of polycyclic aromatic hydrocarbons (PAHs). However, the monitoring and dynamic modeling of PAHs with a high resolution were relatively insufficient. We investigated the spatiotemporal distribution of gaseous PAH concentrations using passive air samplers with high sampling density in an industrial city of Nanjing, China (January and October 2015) and found that the gaseous PAH concentrations in western Nanjing were higher than those in eastern Nanjing, mainly because of emission source distribution and wind action. There were notable seasonal changes in PAH concentrations: winter > autumn > spring > summer. We developed an atmospheric PAH dynamic model with a high resolution of 1 km2 based on the advection-diffusion equation and coupled with an emissions inventory and atmospheric transportation processes. Acenaphthene was selected as a proxy for gaseous PAHs. The modeled acenaphthene concentrations were similar to the concentrations measured. Moreover, we used the model to identify the impact of meteorological factors on gaseous PAHs via scenario analysis and found that a narrow-range temperature change and even heavy rainfall may not significantly affect atmospheric gaseous PAH concentrations, whereas the wind played an important part in transferring PAHs and changing their geographic distribution.