Underestimated heavy metal pollution of the Minjiang River, SE China: Evidence from spatial and seasonal monitoring of suspended-load sediments

Fan, Jiayu; Jian, Xing; Shang, Fei; Zhang, Wei; Zhang, Shuo; Fu, Hanjing

doi:10.1016/j.scitotenv.2020.142586

Cited by 63 publications

(26 citation statements)

References 82 publications

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“…The emission and pollution types of heavy metals in different rivers are different. The research results show that the discharges of heavy metals from the Minjiang River are related to the types of sediments and hydrological characteristics [59].…”

Section: Source Identification Of Heavy Metals and Nutrient Elementsmentioning

confidence: 95%

“…By using cluster analysis (CA) to generate a dendrogram (Figure 6), the Ganjiang River Basin was divided into four statistically significant clusters (Figure 7). Among them, 15% of the sampling points of CA1 (12,13,14,16,17,18,19,20,31,59,72,74,76,82,94) were in the area and were mainly located in Lushui and the middle reaches of the main stream of the Ganjiang River (Figure 1). In CA2 (1,4,5,8,10,21,23,24,25,28,29,30,32,33,34,35,36,39,40,43,45,47,50,51,52,53,54,55,56,57,58,60...…”

Section: Cluster Analysismentioning

confidence: 99%

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Spatial Distribution Characteristics and Risk Assessment of Nutrient Elements and Heavy Metals in the Ganjiang River Basin

Chu

Wang

et al. 2021

Water

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The pollution of water bodies by nutrients and heavy metals can lead to a loss of biodiversity, environmental degradation, and harm to human health. During the two-month monitoring period (e.g., December 2019 to January 2020), variables such as trace metals (e.g., Cu, Zn, As, and Cr), nutrients (e.g., NH4+-N, TN, and TP), water temperature, pH value, dissolved oxygen (DO), chemical oxygen demand (COD) and five-day biochemical oxygen demand (BOD5) were measured at 102 monitoring points in the main stream and tributaries of the Ganjiang River in the Poyang Lake Basin. A variety of multivariate statistical techniques, including cluster analysis (CA), principal component analysis (PCA), and correlation analysis, were used to conduct risk assessments and source analyses of the nutrient elements and heavy metals in the Ganjiang River system. The results show that although the Ganjiang River Basin is polluted by human activities, its water chemistry characteristics and trace metal and nutrient elements concentrations were better than the national standards. Through principal component analysis, the water pollution sources could be divided into urban sewage, agricultural activities, industrial activities, and the sources of industrial activities and transportation activities. The comprehensive risks of noncarcinogens (Hc) and comprehensive risks of carcinogens (Rc) for adults and children due to drinking water indicated that the risk from drinking water for the children in the basin was greater than that for adults, and that the Hc for adults and children was acceptable. However, the Rc for adults and children was slightly higher than the acceptable values. This study provides a reference for the fine control of the environmental water pollution sources in the Ganjiang river basin and health risk assessments in the basin, which are of great significance for improving the environmental water quality standards in the river basin and for reducing the risk of carcinogenesis.

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Section: Source Identification Of Heavy Metals and Nutrient Elementsmentioning

confidence: 95%

Section: Cluster Analysismentioning

confidence: 99%

Spatial Distribution Characteristics and Risk Assessment of Nutrient Elements and Heavy Metals in the Ganjiang River Basin

Chu

Wang

et al. 2021

Water

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“…As in other contaminated river systems (Hilscherova et al 2007;Hürkamp et al 2009;Schulz-Zunkel and Krueger 2009), it is assumed that the heavy metal-laden sediments of the Innerste River were transported downstream and repeatedly redistributed during flooding events and intense rainfall (Du Laing et al 2009;Ponting et al 2021). According to Fan et al (2021), mining and other industrial activities in upstream areas will result in higher heavy metal concentrations compared to downstream areas. Lower metal levels in the latter can be attributed to dilution effects from inflow of unpolluted waters (Luo et al 2020).…”

Section: Heavy Metals In Floodplain Soilsmentioning

confidence: 99%

Heavy metal concentrations in floodplain soils of the Innerste River and in leaves of wild blackberries (Rubus fruticosus L. agg.) growing within and outside the floodplain: the legacy of historical mining activities in the Harz Mountains (Germany)

Steingräber

Ludolphy

Metz

et al. 2021

Environ Sci Pollut Res

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We studied heavy metal levels in floodplain soils of the Innerste River in northern Germany and in the leaves of wild blackberries (Rubus fruticosus L. agg.) growing within and in adjacent areas outside the river floodplain. Heavy metal contamination of the Innerste floodplain is a legacy of historical metal ore mining, processing, and smelting in the Harz Mountains. The heavy metal (Cd, Pb, Zn, Cu, Ni, and Cr) contents of previously studied soil samples from eleven floodplain sites along the Innerste River were re-analyzed statistically, and the levels of these metals in blackberry leaves were determined at five sites. Mean concentrations in the floodplain soils were elevated by factors of 4.59 to 28.5 for Cd, 13.03 to 158.21 for Pb, 5.66 to 45.83 for Zn, and 1.1–14.81 for Cu relative to the precautionary limits for soils stipulated by the German Federal Soil Protection and Contaminated Sites Ordinance. Cadmium, Pb, Zn, Cu, and Ni levels in floodplain soils decreased markedly downstream, as did the concentrations of Cd, Zn, and Ni in the leaves of blackberries from within the floodplain. Levels of Cd, Pb, and Zn in leaves of blackberries from within the floodplain significantly exceeded those of specimens from outside the floodplain. The findings of our study highlight the potential of wild blackberry as a biomonitor of soil pollution by Cd, Pb, and Zn and corroborate the massive heavy metal contamination of floodplain soils along the Innerste River observed in previous studies.

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“…Metal contamination in urban aquatic ecosystems originates from various anthropogenic activities related to industrialization and urbanization, such as industrial/domestic wastewater, runoff/gas emissions and solid-waste disposal. Sediments receive metal contaminations from the overlying water column (dissolved and particulate forms) and act as a source/sink of metals in aquatic ecosystems (Fan et al, 2020;Ge et al, 2021). Many studies have reported metal pollutions and sources in aquatic ecosystems worldwide, such as Dongting Lake in China (Long et al, 2020), Mediterranean coast in Egypt (Keshta et al, 2020) and Lake Wigry in Poland (Kostka & Leśniak, 2020).…”

Section: Introductionmentioning

confidence: 99%

Integrated source-risk and uncertainty assessment for metals contamination in sediments of an urban river system in eastern China

Xia

Niu²,

et al. 2021

CATENA

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Integrated source apportionment and risk assessment of metals is of great importance for contamination source control and remediation at the regional watershed scale. To identify metal sources and source-specific ecological risks, sediments were collected in the Wen-Rui Tang urban watershed for metal analysis. Risk assessment showed considerable and extremely high risk for Cu and Cd with large spatial variation. Positive matrix factorization model extracted three main sources with reasonable prediction efficacy for metal concentrations. Due to different toxicity coefficients for various metals, the low concentration contribution of source factor 2 (27.2%) contributed 83.7% of total risk, while a high concentration loading for factor 3 (40.8%) only contributed 4.6% to total risk. Predicted source-specific risk was similar to determined risk level for Cr, Ni and Pb; however, Cu and Cd were predicted with decreased risk, while Zn had increased risk. Triangular fuzzy number (TFN) coupled with stochastic simulation showed elevated trend in risk simulation for Cd and Cu when compared with determined risk. The uncertainties for risk evaluation appear to result from spatial variations in metal concentrations. Source apportionment and specific-risk assessment results suggest that different strategies may be required to address mitigation of elevated metal concentrations versus ecological risk.

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Underestimated heavy metal pollution of the Minjiang River, SE China: Evidence from spatial and seasonal monitoring of suspended-load sediments

Cited by 63 publications

References 82 publications

Spatial Distribution Characteristics and Risk Assessment of Nutrient Elements and Heavy Metals in the Ganjiang River Basin

Spatial Distribution Characteristics and Risk Assessment of Nutrient Elements and Heavy Metals in the Ganjiang River Basin

Heavy metal concentrations in floodplain soils of the Innerste River and in leaves of wild blackberries (Rubus fruticosus L. agg.) growing within and outside the floodplain: the legacy of historical mining activities in the Harz Mountains (Germany)

Integrated source-risk and uncertainty assessment for metals contamination in sediments of an urban river system in eastern China

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