The Chinese Gridded Industrial Pollutants Emission and Residue Model (ChnGIPERM) was used to investigate potential fractionation effects and atmospheric transport of polychlorinated biphenyls (PCBs) derived from single-source emissions in China. Modeling the indicative PCBs (CB28, CB101, CB153, and CB180) revealed spatiotemporal trends in atmospheric transport, gas/particle partitioning, and primary and secondary fractionation effects. These included the inference that the Westerlies and East Asian monsoons affect atmospheric transport patterns of PCBs by influencing the atmospheric transport time (ATT). In this study, dispersion pathways with long ATTs in winter tended to have short ones in summer and vice versa. The modeled partitioning of PCB congeners between gas and particles was mainly controlled by temperature, which can further influence the ATT. The potential for primary and secondary fractionation was explored by means of numerical simulations with single-source emissions. Within ChnGIPERM, these phenomena were mainly controlled by the temperature and soil organic carbon content. The secondary fractionation of PCBs is a slow process, with model results suggesting a timescale of several decades.
Environmental Science and Pollution Research - Sediment, composed of a complex assemblage of minerals, controls the fate and behaviour of P in aqueous environments and affects trophic status. In... 相似文献
Environmental Science and Pollution Research - To understand the influence of Cd on atrazine (ATZ) degradation in aqueous solution, the degradation of different initial levels of ATZ (0.1, 0.5,... 相似文献
Environmental Science and Pollution Research - Sulfate radical?based advanced oxidation processes have received considerable attentions in the remediation of organic pollutants due to their... 相似文献
The plateau lakes of Yunnan are important both ecologically and economically in China. Nevertheless, the human impact on water quality in these lakes has become increasingly highlighted. The water quality of 10 plateau lakes was monitored regularly over the period of 2000 through 2004 for 24 parameters. Multivariate statistical techniques, including cluster analysis (CA), factor analysis (FA), and principal component analysis (PCA), were employed to better interpret information about the water quality and its pollution sources. No obvious data reduction from CA/FA was found because three principal components (PCs) needed 14 variables to explain 85.01% of the total variance. However, three latent factors accounted for pollution mainly from the following sources: agricultural activities, residential activities and anthropogenic-toxic pollution from industrial effluents, or other special activities. Box-whiskers plots were employed to visually interpret the spatiotemporal variations of water quality variables, which were highly correlated with three PCs. Three types of water quality (i.e., low-, medium-, and high-polluted lakes) were determined through CA based on the similarity of water quality variables. Our results may provide helpful information for the authorities to effectively manage the water quality and make sound policies. 相似文献
