Dioxin-like Compounds In Agricultural Soils Near E-waste Recycling Sites From Taizhou Area, China: Chemical And Bioanalytical Characterization

摘要

The crude recycling of electronic and electric waste (e-waste) is now creating a new set of environmental problems especially in developing countries such as China. The present study aimed to characterize the dioxin-like compounds in Taizhou area, one of the largest e-waste recycling centers in China, using both chemical analysis and in vitro bioassay. Agricultural soil samples were screened for aryl hydrocarbon receptor (AhR) activity with EROD bioassay in H411E cells, and the concentrations of the target AhR agonists including polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs), polychlorinated biphenyls (PCBs) and polycyclic aromatic hydrocarbons (PAHs) were determined by instruments. The bioassay-derived TCDD equivalents (TEQ_(bio)) and the chemical-calculated TCDD equivalents (TEQ_(cal)) were then compared, and mass balance analysis was conducted to identify the contributors of the observed response. Raw soil extracts from all locations induced significant AhR activities, where the TEQ__(bio) ranged from 5.3 to 210 pg/g dry weight soil (pg/g dw). The total concentrations of 17 PCDD/Fs, 36 PCBs and 16 PAHs varied from 210 to 850 pg/g dw, 11 to 100 ng/g dw, and 330 to 20,000 ng/g dw, respectively. Profile characterization of the target analytes revealed that there were similar sources originating from the crude dismantling of electric power equipments and the open burning of e-waste. There was a significant relationship between TEQ_(cal) and TEQ_(bio) (r=0.99, p<0.05). Based on the mass balance analysis, PCDD/Fs, PCBs and PAHs could account for the observed AhR responses in vitro elicited by soil extracts, though their respective contributions varied depending on sample location. In this study, the combination of chemical analysis and bioanalytical measurements proved valuable for screening, identifying and prioritizing the causative agents within complex environmental matrices.