Distribution, contamination and source identification of heavy metals in bed sediments from the lower reaches of the Xiangjiang River in Hunan province, China

Fang, Xiaohong; Peng, Bo; Wang, Xin; Song, Zhaoliang; Zhou, Dai; Wang, Aiqin; Qin, Zhilian; Tan, Changyin

doi:10.1016/j.scitotenv.2019.06.330

Cited by 140 publications

(39 citation statements)

References 53 publications

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“…At the upstream of the surveyed area, there are many companies producing Zn, Pb, As, and alloys as well as other companies that carry out comprehensive recovery of Cu, Au, Ag, Bi, Te, Cd, In, and other rare metals. In this work, eight target heavy metals (Cd, As, Pb, Zn, Cu, Ni, Cr, and Co) were chosen for evaluation after examining the actual situation of the study area and consulting literatures on heavy metals in the Xiangjiang River [21,25,28].…”

Section: Study Area and Sample Collectionmentioning

confidence: 99%

“…Unfortunately, the Xiangjiang River has become one of the most seriously heavy metal-polluted rivers in China over the past few decades because of the wastewater discharge from mining and metallurgical industries carrying heavy metals [23]. Although many researchers have studied heavy metal pollution in the Xiangjiang River [24][25][26], a systematic study is still lacking to associate the sediment with the distribution, characteristics, risk assessment, possible sources, and impact of heavy metals.…”

Section: Introductionmentioning

confidence: 99%

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Risk assessment of heavy metals in the surface sediment at the drinking water source of the Xiangjiang River in South China

et al. 2020

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Background: The Xiangjiang River is an important drinking water resource for the Hunan Province of China. It is crucial to ascertain the pollution status, influencing factors, ecological risks, and possible sources of heavy metals in the sediments of the Xiangjiang River. Sediment is both a source and a sink of heavy metals in aquatic ecosystems. In this study, surface sediment was collected from the Zhuzhou Reach of the Xiangjiang River and eight heavy metals were investigated. Results:In all sediment samples, all eight heavy metals were detected and their average concentration fell in the order of Zn > Pb > As > Cu > Cr > Ni > Cd > Co. Assessment shows extremely serious Cd pollution and a very high potential ecological risk from Cd. According to correlation analysis and principal component analysis (PCA), As, Cu, Ni, Pb, and Zn originate from industrial wastewater and mineral smelting activities, whereas Co, Cr, and Ni come from natural sources. Redundancy analysis (RDA) reveals that the organic matter content and the particle size of the sediment have a certain influence on the enrichment of heavy metals. Conclusion:Among all eight examined heavy metals in the surveyed area, the content of Zn, Pb, and As is the highest, and that of Cd and Co is the lowest. Despite a low level of absolute content, the Cd in sediment already renders a high ecological risk and thus calls for urgent attention. Anthropogenic activities are the main source of heavy metals in the sediment. The distribution of heavy metals may also be influenced by sediment properties. The results provide guidance for controlling heavy metal pollution and protecting drinking water sources in the Xiangjiang River.

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Section: Study Area and Sample Collectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Risk assessment of heavy metals in the surface sediment at the drinking water source of the Xiangjiang River in South China

et al. 2020

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“…The calculated EF factor values of most samples are lower than 2 ( Figure 3), which indicates the minimal enrichment of these heavy metals in soils [28]. Several extremely abnormal EF values occur in soil profile T5, exactly at the depth where abnormal heavy metal concentrations appear ( Figure 2), which can be attributed to the absorption by iron-manganese oxides.…”

Section: Enrichment Of Heavy Metalsmentioning

confidence: 94%

“…where M represents heavy metal concentrations and S refers to soil samples. Based on the EF values, the enrichment of heavy metals can be categorized into five grades: minimal enrichment (EF ≤ 2); moderate enrichment (2 < EF < 5); significant enrichment (5 ≤ EF < 20); high enrichment (20 ≤ EF < 40); and extremely high enrichment (EF ≥ 40) [28].…”

Section: Data Treatmentmentioning

confidence: 99%

“…Principal component analysis (PCA) is an important multivariate analysis method applied to identify the sources of soil heavy metals [54]. The prerequisite of the application of PCA is to pass the Kaiser-Meyer-Olkin (KMO) and Bartlett's sphericity tests: the KMO measure should be higher than 0.5 and Bartlett's sphericity test should be significant (P < 0.001) [28,55,56]. The KMO value equals 0.61 and Bartlett's sphericity test is significant (P = 0) in this study, indicating that PCA is applicable to the analysis of these soil samples.…”

Section: Principal Component Analysis For Heavy Metalsmentioning

confidence: 99%

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Vertical Distribution and Controlling Factors Exploration of Sc, V, Co, Ni, Mo and Ba in Six Soil Profiles of The Mun River Basin, Northeast Thailand

Zhou

Han

Liu

et al. 2020

IJERPH

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Exploring the enrichment and controlling factors of heavy metals in soils is essential because heavy metals can cause severe soil contamination and threaten human health when they are excessively enriched in soils. Soil samples (total 103) from six soil profiles (T1 to T6) in the Mun River Basin, Northeast Thailand, were collected for the analyses of the content of heavy metals, including Sc, V, Co, Ni, Mo, Ba. The average contents of soil heavy metals decrease in the following order: Ba, V, Ni, Sc, Co, and Mo (T1, T3, T4 and T5); Ni, V, Ba, Co, Sc, Mo, and Ba (T2); Ba, V, Sc, Ni, Mo, and Co (T6). An enrichment factor (EF) and geoaccumulation index were calculated to assess the degree of heavy metal contamination in the soils. The EFs of these heavy metals in most samples range from 0 to 1.5, which reveals that most heavy metals are slightly enriched. Geoaccumulation indexes show that only the topsoil of T1 and T2 is slightly contaminated by Ba, Sc, Ni, and V. Soil organic carbon (SOC), soil pH and soil texture are significantly positively correlated with most heavy metals, except for a negative correlation between soil pH and Mo content. In conclusion, the influence of heavy metals on soils in the study area is slight and SOC, soil pH, soil texture dominate the behavior of heavy metals.

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Modeling transmission of hexavalent chromium concentration and its health cost with a water quality analysis simulation program

Chen

Tseng

Chen

2021

Water Environment Research

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In this study the Water Quality Analysis Simulation Program (WASP7) was used to evaluate the transmission of hexavalent chromium (Cr(VI)) contamination in a water-sediment system and its flux into cultivated soils. The agricultural areas adjacent to the Wu River in Taiwan were taken as the study area, as these soils were found to be heavily polluted with Cr(VI) concentrations of 3,271-16,799 μg/kg. It was found that the rates of accumulation of Cr(VI) are affected by the distance from the source of 10 −6 in Changhua county (downstream). More worryingly, young children had a threefold greater risk of gastric cancer than adults. The values of statistical life-years (VSLYs) were US$6.2-10 million for rice, US$42-60 million for corn, and US$360-580 million for other vegetables, respectively, each year. It is critical that techniques other than source reduction are used to reduce health costs associated with human exposure to Cr(VI), such as chemical oxidation or ion-exchange treatment to remove Cr(VI) from factory wastewaters, prior to their discharge into rivers.

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Distribution, contamination and source identification of heavy metals in bed sediments from the lower reaches of the Xiangjiang River in Hunan province, China

Cited by 140 publications

References 53 publications

Risk assessment of heavy metals in the surface sediment at the drinking water source of the Xiangjiang River in South China

Risk assessment of heavy metals in the surface sediment at the drinking water source of the Xiangjiang River in South China

Vertical Distribution and Controlling Factors Exploration of Sc, V, Co, Ni, Mo and Ba in Six Soil Profiles of The Mun River Basin, Northeast Thailand

Modeling transmission of hexavalent chromium concentration and its health cost with a water quality analysis simulation program

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