W6 PM Environmental Changes in Response to China's Economic Expansion
Wednesday, 16 November 2005: 1:50 PM - 5:30 PM in 324-326

(TAO-1117-105000) Source apportionment of polycyclic aromatic hydrocarbons in multimedia environment based on diagnostic ratios.

Tao, S¹, Zhang, X¹, Liu, W, Xu, F¹, ¹ Laboratory for Earth Surface Processes, College of Environmental Sciences, Peking University, Beijing, China

ABSTRACT- A fugacity model was applied to evaluate changes of polycyclic aromatic hydrocarbon (PAH) ratios in a virtual environment to test a hypothesis that most PAH ratios vary significantly due to differential transport from sources to receptors in a multimedia environment. Linear relationships between media concentrations and emission were identified for all PAH species in all media and were quantified by Source to Receptor Ratios (RSR). However, RSR values of two species in a PAH ratio differed significantly due to differential transportation from source to receptors. Consequentially, PAH ratios changed remarkably from source to bulk media including air. A Rectification Factors (RF) was defined as a ratio of the two RSR values of the paired species for a specific PAH ratio in a given media, which can be applied to account for such changes in source diagnostic in multimedia environment. For the virtual environment studies, RF values varied from 0.28 (BaP/BghiP in sediment) to 2.00 (FLA/PYR in sediment). The PAH ratio changes were further verified based on the field data collected from Tianjin. It was demonstrated that a multimedia verification can indicate the directions of the PAH ratio changes from the emission sources to the surface soils. As the results of a sensitivity analysis, it was shown that PAH ratios with low molecular size species were less stable and the most influential parameters affecting PAH ratios are those controlling dry-precipitation, air-surface diffusion, degradation in air and air-vegetation partitioning. As demonstrated by Monte-Carlo simulation, the total uncertainties of PAH ratios ranged from one to two third orders of magnitude, of which 35% to 50% were due to spatial and temporal variabilities.

Key words: PAHs, source apportionment, diagnostic ratio, multimedia modeling