ABSTRACT: Dynamic linear models (DLM) and seasonal trend decomposition (STL) using local regression, or LOESS, were used to analyze the 50‐year time series of suspended sediment concentrations for the Yadkin River, measured at the U.S. Geological Survey station at Yadkin College, North Carolina. A DLM with constant trend, seasonality, and a log10 streamflow regressor provided the best model to predict monthly mean log10 suspended sediment concentrations, based on the forecast log likelihood. Using DLM, there was evidence (odds approximately 69:1) that the log10 streamflow versus log10 suspended sediment concentration relationship has changed, with an approximate 20 percent increase in the log10 streamflow coefficient over the period 1981 to 1996. However, sediment concentrations in the Yadkin River have decreased during the decade of the 1990s, which has been accompanied by a concomitant increase in streamflow variability. Although STL has been shown to be a versatile trend analysis technique, DLM is shown to be more suitable for discovery and inference of structural changes (trends) in the model coefficient describing the relationship between flow and sediment concentration. 相似文献
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Journal of Material Cycles and Waste Management - Bio-drying has been proved to be a promising method for treatment of MSW (municipal solid waste) and sewage sludge due to its high energy... 相似文献
Environmental Science and Pollution Research - The concentrations of major and trace elements in the sediments from the Four River inlets of Dongting Lake were analysed. The results show that the... 相似文献
Environmental Science and Pollution Research - For effective photocatalytic pollutant degradation on bismuth tungstate (Bi2WO6), it is vital to enhance the photogenerated charge separation and the... 相似文献
Characterization of the typical petroleum pollutants, polycyclic aromatic hydrocarbons (PAHs) and n-alkanes, and indigenous microbial community structure and function in historically contaminated soil at petrol stations is critical. Five soil samples were collected from a petrol station in Beijing, China. The concentrations of 16 PAHs and 31 n-alkanes were measured by gas chromatography-mass spectrometry. The total concentrations of PAHs and n-alkanes ranged from 973 ± 55 to 2667 ± 183 μg/kg and 6.40 ± 0.38 to 8.65 ± 0.59 mg/kg (dry weight), respectively, which increased with depth. According to the observed molecular indices, PAHs and n-alkanes originated mostly from petroleum-related sources. The levels of ΣPAHs and the total toxic benzo[a]pyrene equivalent (ranging from 6.41 to 72.54 μg/kg) might exert adverse biological effects. Shotgun metagenomic sequencing was employed to investigate the indigenous microbial community structure and function. The results revealed that Proteobacteria and Actinobacteria were the most abundant phyla, and Nocardioides and Microbacterium were the important genera. Based on COG and KEGG annotations, the highly abundant functional classes were identified, and these functions were involved in allowing microorganisms to adapt to the pressure from contaminants. Five petroleum hydrocarbon degradation-related genes were annotated, revealing the distribution of degrading microorganisms. This work facilitates the understanding of the composition, source, and potential ecological impacts of residual PAHs and n-alkanes in historically contaminated soil.
