Here, we aim to determine the distribution, ecological risk and sources of heavy metals and metalloids in the surface sediments of the Xiangjiang River, Hunan Province, China. Sixty-four surface sediment samples were collected in 16 sites of the Xiangjiang River, and the concentrations of ten heavy metals and metalloids (Mn, Zn, Cr, V, Pb, Cu, As, Ni, Co, and Cd) in the sediment samples were investigated using an inductively coupled plasma mass spectrometer (ICP-MS) and an atomic fluorescence spectrophotometer (AFS), respectively. The results showed that the mean concentrations of the ten heavy metals and metalloids in the sediment samples followed the order Mn > Zn > Cr > V > Pb > Cu > As ≈ Ni >Co > Cd. The geoaccumulation index (I geo), enrichment factor (EF), modified degree of contamination (mCd), and potential ecological risk index (RI) revealed that Cd, followed by Pb, Zn, and Cu, caused severely contaminated and posed very highly potential ecological risk in the Xiangjiang River, especially in Shuikoushan of Hengyang, Xiawan of Zhuzhou, and Yijiawan of Xiangtan. The Pearson's correlation coefficient (PCC) analysis, principal component analysis (PCA), and hierarchical cluster analysis (HCA) indicated that the ten heavy metals and metalloids in the sampling sediments of the Xiangjiang River were classified into three groups: (1) Cd, Pb, Zn, and Cu which possibly originated from Shuikoushan, Xiawan, and Yijiawan clustering Pb-Zn mining and smelting industries; (2) Co, V, Ni, Cr, and Al from natural resources; and (3) Mn and As. Therefore, our results suggest that anthropogenic activities, especially mining and smelting, have caused severe contamination of Cd, Pb, Zn, and Cu and posed very high potential ecological risk in the Xiangjiang River.

Heavy metals and metalloids in the surface sediments of the Xiangjiang River, Hunan, China: distribution, contamination, and ecological risk assessment

Phosphogypsum as a soil fertilizer: Ecotoxicity of amended soil and elutriates to bacteria, invertebrates, algae and plants

Urinary metabolites of organophosphate esters in children in South China: Concentrations, profiles and estimated daily intake.

Sediment samples from the coastal area of Asaluyeh harbor were collected during autumn and spring 2015. The acid-volatile sulfide (AVS) and simultaneously extracted metals (SEMs) were measured to assess the sediment quality and potential ecological risks. The average concentrations (and relative standard deviation (RSD)) of AVS in the industrial sediments were 12.32 μmol/g (36.91) and 6.34 μmol/g (80.05) in autumn and spring, respectively, while in the urban area, these values were 0.44 μmol/g (123.50) and 0.31 μmol/g (160.0) in autumn and spring, respectively. The average concentrations of SEM (and RSD) in the industrial sediments were 15.02 μmol/g (14.38) and 12.34 μmol/g (20.65) in autumn and spring, respectively, while in the urban area, these values were 1.10 μmol/g (43.03) and 1.06 μmol/g (55.59) in autumn and spring, respectively. Zn was the predominant component (34.25–86.24 %) of SEM, while the corresponding value for Cd, much more toxic ingredient, was less than 1 %. Some of the coastal sediments in the harbor of Asaluyeh (20 and 47 % in autumn and spring, respectively) had expected adverse biological effects based on the suggested criterion by United States Environmental Protection Agency (USEPA), while most stations (80 and 53 % in autumn and spring, respectively) had uncertain adverse effects.

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Assessment of sediment quality based on acid-volatile sulfide and simultaneously extracted metals in heavily industrialized area of Asaluyeh, Persian Gulf: concentrations, spatial distributions, and sediment bioavailability/toxicity

Trace metals (Cd, Cr, Cu, Ni and Pb) concentrations in benthic sediments were analyzed through multi-step fractionation scheme to assess the levels and sources of contamination in estuarine, riverine and freshwater ecosystems in Niger Delta (Nigeria). The degree of contamination was assessed using the individual contamination factors (ICF) and global contamination factor (GCF). Multivariate statistical approaches including principal component analysis (PCA), cluster analysis and correlation test were employed to evaluate the interrelationships and associated sources of contamination. The spatial distribution of metal concentrations followed the pattern Pb>Cu>Cr>Cd>Ni. Ecological risk index by ICF showed significant potential mobility and bioavailability for Cu, Cu and Ni. The ICF contamination trend in the benthic sediments at all studied sites was Cu>Cr>Ni>Cd>Pb. The principal component and agglomerative clustering analyses indicate that trace metals contamination in the ecosystems was influenced by multiple pollution sources.

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Source Evaluation and Trace Metal Contamination in Benthic Sediments from Equatorial Ecosystems Using Multivariate Statistical Techniques.

Sediments from 14 stations in the Foshan Waterway, a river crossing the industrial district of Guangdong Province, South China, were sampled and subsequently analyzed. The 14 stations were selected for the pollution discharging features of the river, such as the hydrology, the distribution of pollution sources, and the locations of wastewater outlets. The ecological risks were assessed, and the pollution sources were identified to provide valuable information for environmental impact assessment and pollution control. The spatial variability was high and the range were (in milligrams per kilogram dry weight): Pb, 46.0~382.8; Cu, 33.7~ 482.3; Zn, 62.2~1,568.7; Ni, 28.5~130.7; Cr, 34.7~1,656.1; Cd, 0.50~8.53; Hg, 0.02~8.27; and As, 5.77~66.09. The evaluation results of enrichment factor and potential ecological risk index indicate that the metal pollution in the surface and bottom sediments were severely polluted and could pose serious threat to the ecosystem in most stations. Although the hazard levels of the trace element differed among the stations, Hg was the most serious pollutant in all stations. The results of principal component analysis (PCA) show that the discharge of industrial wastewater is the most important polluting factor whereas domestic sewage, which contains a large amount of organic substances, accelerates metal deposition. And potential pollution sources were identified by the way of integrating the analysis results of PCA and data gained from the local government. Therefore, the conclusion is drawn that Foshan Waterway is seriously polluted with trace elements, both in the surface sediment (0 to 20 cm) and the bottom sediments (21 to 50 cm) are contaminated.

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Ecological Risks Assessment and Pollution Source Identification of Trace Elements in Contaminated Sediments from the Pearl River Delta, China

The spatial variability of acid-volatile sulfide (AVS) and its influential factors were studied through regression analysis to explain the spatial distribution of AVS and to predict the variability of metal availability under changing conditions simply and effectively. The AVS equation is used to derive oxidation-reduction potential (Eh), sulfate-reducing bacteria (SRB), organic carbon (OC), and total sulfur (TS). The relationships of these variables with AVS were then analyzed. Moreover, their effect on AVS was quantified through linear regression (LR) and principal component regression (PCR). These two regression equations were analyzed using a histogram of residual values and by comparing mean relative error (MRE) and root-mean-square error (RMSE) values. LR (Model 1) and PCR (Model 2) models were established as well. The MRE and RMSE values in the PCR model were 21.9 and 25.9%, respectively. In terms of these values, the PCR model is more accurate than the LR model. Furthermore, its predictive results were more reasonable. In conclusion, the PCR model can be used to predict the AVS concentrations based on the OC, Eh, SRB, and TS values. This model simplifies and facilitates the evaluation of metal toxicity under field conditions and can thus be used to manage sediments contaminated with metals.

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A Field Study of Factors that Affect Acid-Volatile Sulfide Concentrations

The information mining of biological monitoring data is important for environment monitoring and accessment. Although Shannon-Wiener diversity index (SWI) has beenwidely used to explain the results of aquatic biologicalmonitoring previously, it runs into problems in heavily polluted rivers. In this paper, a representative heavily polluted river has been selected, and the samples of sediment, pore water, phytoplankton, zooplankton, and zoobenthoswere collected and analyzed, with a view to providing theoretical basis for biological data analysis in heavy polluted area. SWI, themultivariate analysis (combined by twomultivariate analysis methods: cluster and Non-matricMulti-dimentional Scaling analysis) were used to analyze biological data of phytoplankton, zooplankton, and zoobenthos, with the results of the physical and chemical monitoring and assessment as reference. The results show that the results of SWI cannot effectively reflect the difference of pollution status of various stations in the heavily polluted river; despite the presence of some problems, multivariate analysismethod ismore suitable than SWI as far as information mining of biologicalmonitoring in the heavily polluted river is concerned.

The information mining of biological monitoring data in a heavily polluted river: The comparison between shannon-wiener diversityindex and the multivariate analysis

Yan-Mao Wen

Papers

Ecological Risks Assessment and Pollution Source Identification of Trace Elements in Contaminated Sediments from the Pearl River Delta, China

A Field Study of Factors that Affect Acid-Volatile Sulfide Concentrations

The information mining of biological monitoring data in a heavily polluted river: The comparison between shannon-wiener diversityindex and the multivariate analysis