Fraction distribution and risk assessment of heavy metals in sediments of Moshui Lake

Abstract

To examine the status and risk of heavy metal pollution in urban lakes, in China, the distribution of several heavy metals (e.g., Cr, Cu, Ni, Pb, Zn) in the sediment of Moshui Lake, Hangyang District, Wuhan City, was characterized. The process of rapid urbanization and industrialization of the district was also studied to find out its relationship with the metal accumulation profile in the sediment. It was found that the total concentration of heavy metals in the sediment was higher than the severe effect level (SEL), at all sampling sites, except those in the riparian zone. The Cr and Cu maximum concentrations were 1,780 and 1,250 mg/kg, approximately 16 and 11 times as much as the SEL values, and they appeared as deep as 32 cm in one sample. The carbonate and exchangeable fractions of Zn were more than 50% of the total Zn content, resulting in very high risk according to the Risk Assessment Code (RAC). For Cu and Ni, a medium RAC value was found for carbonate and exchangeable fractions of 11%-20%. As sensitive indicators of contaminants in aquatic systems, heavy metals in the sediment reflect the outcome of regional urbanization, industrialization, and environmental management. With rapid urbanization, sedimentary Pb and Zn concentrations increased. The experimental results showed that high sedimentary heavy metal concentrations had resulted from rapid urbanization and industrialization, which would absolutely lead to substantial aquatic environmental decline in urban lakes.

Risk assessment of metals in road-deposited sediment along an urban–rural gradient

“…The earliest studies conducted to investigate metal contamination associated with RDS focused on comparison among land uses in one city or among different cities (Lau and Stenstrom, 2005;Lu et al, 2009). In recent years, a variety of methods have been introduced to investigate the metal risk associated with RDS posed to water, soil or river sediments, with traditional methods including the (1) geoaccumulation index (I geo ), (2) enrichment factor (EF), (3) Nemerow synthetic pollution index (PI N ) and (4) potential ecological risk index (RI) (Buccolieri et al, 2006;Cheng et al, 2007;Liu et al, 2008;Shi et al, 2010;Wei and Yang, 2010). The applicability of these traditional assessment methods to the risks associated with metals in RDS is still unclear.…”

Pollution Assessment and Sources Identification of Heavy Metals in Surface Sediments from the Nantaizi Lake, Middle China

“…Besides, there is significant correlation in As and Cr, which shows that they are closely related. factors with different main components based on displaying original data to the maximum [16].Urban inland lake waters has reflected that lake waters are polluted by heavy metals, of which contents and sources have recorded influence of human activity and natural change on environment [17]. Pollution source of heavy pollution can be divided into main source and secondary source according to sources.…”

“…Pollution source of heavy pollution can be divided into main source and secondary source according to sources. Based on PCA, by simplifying and extracting original variables factors, independent heavy metal elements can be combined to form a new variable, so as to judge and analyze heavy metal sources in water environment sediments [16]. Therefore, PCA has been implemented for characteristics values of heavy metals of 6 sample sites of Nantaizi Lake water system.…”

Characterization of Heavy Metal Contamination from their Spatial Distributions in Sediment of an Urban Lake of Hanoi, Vietnam

“…The world averages for sediment (Bowen, 1979) and the values for the surface sediments of Lake Teganuma and Moshui Lake, urban lakes in Japan and China, respectively, with similar geographical characteristics to Ho Tay (e.g., surface area: 6.5 km 2 and 3.14 km 2 ; average depth: 0.86 m and 1.2 m for Lake Teganuma and Moshui Lake, respectively) Chiyo, 2004;Liu et al, 2008) are also listed for comparison. In general, metal contents in the surface sediment at each station decreased in the following order: S4 > S2 > S1 > S3.…”