Abstract
Background
Heavy metal pollution of aquatic systems is a global issue that has received considerable attention. Canonical correlation analysis (CCA), principal component analysis (PCA), and potential ecological risk index (PERI) have been applied to heavy metal data to trace potential factors, identify regional differences, and evaluate ecological risks. Sediment cores of 200 cm in depth were taken using a drilling platform at 10 sampling sites along the Xihe River, an urban river located in western Shenyang City, China. Then they were divided into 10 layers (20 cm each layer). The concentrations of the As, Cd, Cr, Cu, Hg, Ni, Pb and Zn were measured for each layer. Eight heavy metals, namely Pb, Zn, As, Cd, Cr, Cu, Ni, and Hg, were measured for each layer in this study.
Results
The average concentrations of the As, Cd, Cu, Hg, and Zn were significantly higher than their background values in soils in the region, and mainly gathered at 0–120 cm in depth in the upstream, 0–60 cm in the midstream, and 0–20 cm downstream. This indicated that these heavy metals were derived from the upstream areas where a large quantity of effluents from the wastewater treatment plants enter the river. Ni, Pb, and Cr were close or slightly higher than their background values. The decreasing order of the average concentration of Cd was upstream > midstream > downstream, so were Cr, Cu, Ni and Zn. The highest concentration of As was midstream, followed by upstream and then downstream, which was different to Cd. The potential factors of heavy metal pollution were Cd, Cu, Hg, Zn, and As, especially Cd and Hg with the high ecological risks. The ecological risk levels of all heavy metals were much higher in the upstream than the midstream and downstream.
Conclusions
Industrial discharge was the dominant source for eight heavy metals in the surveyed area, and rural domestic sewage has a stronger influence on the Hg pollution than industrial pollutants. These findings indicate that effective management strategies for sewage discharge should be developed to protect the environmental quality of urban rivers.
A New Receptor Model Based on the Alternating Trilinear Decomposition Followed by a Score Matrix Reconstruction for Source Apportionment of Ambient Particulate Matter
