Heavy metal contamination in surface runoff sediments of the urban area of Vilnius, Lithuania

Ignatavičius, Gytautas; Valskys, Vaidotas; Bulskaya, Ina; Paliulis, Dainius; Zigmontienė, Aušra; Satkūnas, Jonas

doi:10.3176/earth.2017.04

Cited by 18 publications

(14 citation statements)

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“…Using the PCA technique, 15 variables were reduced to three independent factors. As a whole, PCA resolved high and moderate loading factors with positive and negative values showing the anthropogenic and natural sources of pollution [75,81]. Table 5.…”

Section: Multivariate Analysismentioning

confidence: 99%

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Heavy Metals Contamination and Ecological Risk Assessment in Surface Sediments of Namal Lake, Pakistan

Javed¹,

Ahmad²,

Mashiatullah³

2018

Pol. J. Environ. Stud.

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Heavy metals pollution is a worldwide problem that has grown during the past few decades because of their toxicity, extensive sources, non-biodegradable characteristics, and accumulative behaviors in aquatic environments [1][2][3]. These metals are identified as a significant indicator for degradation of aquatic environments. Enormous quantities of metals are being released into the environment both from anthropogenicrelated processes and natural sources through direct discharge into water or indirectly through stormwater runoff, domestic effluents, fossil fuel combustion, and atmospheric depositions [4]. Heavy metals ultimately Pol. J. Environ. Stud. Vol. 27, No. 2 (2018), 675-688 Original Research Heavy Metals Contamination and Ecological Risk AbstractHeavy metal concentrations were determined using inductively coupled plasma-optical emission spectrometry (ICP-OES) in surface sediments of Namal Lake, Pakistan. The metals content in sediment varied significantly and were in the order of Al>Fe>Mn>V>Zn>Cr>Ni>Cu>As>Co>Pb>Cd. Except for Al, the average concentrations of metals were higher than the average value of the upper continental crust (UCC). The significant positive correlations among heavy metals (p<0.01) suggested that these metals originated from the same sources. The pollution indices indicated severe contamination of sediments with As, Cd, and Ni. The sediment quality guidelines (SQGs) revealed that 19.2% of As, 11.5% of Cr, and 88.5% of Ni from all the sampling sites exceeded the probable effect level (PEL). The computed average risk index (RI) of single elements were in the following order Cd(411.9)>As(69.0)>Ni(15.4)>Cu(10.0)>Cr(4.3)> Pb(3.66)>Zn(1.7). Principle component analysis (PCA) extracted three components explaining (76.136%) of total variance of chemical data and were highly to moderately loaded with Fe, Mn, Co, Cu, Zn, Al, As, Cd, Ni, V, Cr, TOC, pH, CaCO 3 , and Pb in three principal components (PCs). The results obtained from cluster analysis, correlation of heavy metals, and principal component analysis suggested the origin of metals from both anthropogenic and natural sources.

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Section: Multivariate Analysismentioning

confidence: 99%

“…squared Euclidean distance, which provides the extent of association of metals on their similarity between chemical properties [74][75]. Fig.…”

Section: Cluster Analysismentioning

confidence: 99%

Heavy Metals Contamination and Ecological Risk Assessment in Surface Sediments of Namal Lake, Pakistan

Javed¹,

Ahmad²,

Mashiatullah³

2018

Pol. J. Environ. Stud.

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“…The source of high metal concentrations in the water could be natural (sediments in the case of environmental change) or from effluents of anthropogenic activities [21]. The water column and sediment layer are in direct contact, leading to an exchange of constituents, including metals [22]. In the Steelpoort, the high mean concentrations of Cr and Fe could be from Ferrochrome mining discharge, while the relatively higher As concentration in the Blyde could have come from fertilizers and pesticides due to the intensive agricultural activities in some parts of the catchment [23].…”

Section: Resultsmentioning

confidence: 99%

Assessment of Heavy Metal Pollution in the Blyde and Steelpoort Rivers of the Olifants River System, South Africa

Addo‐Bediako

2020

Pol. J. Environ. Stud.

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“…The presence of elements such as iron, manganese, zinc, lead, cobalt, copper, and nickel was found in the tested samples. High variability of heavy metal contents in stormwater sediments from catchments that differ in land use indicates the complex nature and dynamics of pollutants washing-off and also the diverse sources of pollution [34,35]. Iron had the largest share in the total content of heavy metals.…”

Section: Contamination Of Stormwater Sedimentsmentioning

confidence: 99%

Modeling of Heavy Metal (Ni, Mn, Co, Zn, Cu, Pb, and Fe) and PAH Content in Stormwater Sediments Based on Weather and Physico-Geographical Characteristics of the Catchment-Data-Mining Approach

Bąk

Szeląg

Sałata

et al. 2019

Water

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The processes that affect sediment quality in drainage systems show high dynamics and complexity. However, relatively little information is available on the influence of both catchment characteristics and meteorological conditions on sediment chemical properties, as those issues have not been widely explored in research studies. This paper reports the results of investigations into the content of selected heavy metals (Ni, Mn, Co, Zn, Cu, Pb, and Fe) and polycyclic aromatic hydrocarbons (PAHs) in sediments from the stormwater drainage systems of four catchments located in the city of Kielce, Poland. The influence of selected physico-geographical catchment characteristics and atmospheric conditions on pollutant concentrations in the sediments was also analyzed. Based on the results obtained, statistical models for forecasting the quality of stormwater sediments were developed using artificial neural networks (multilayer perceptron neural networks). The analyses showed varied impacts of catchment characteristics and atmospheric conditions on the chemical composition of sediments. The concentration of heavy metals in sediments was far more affected by catchment characteristics (land use, length of the drainage system) than atmospheric conditions. Conversely, the content of PAHs in sediments was predominantly affected by atmospheric conditions prevailing in the catchment. The multilayer perceptron models developed for this study had satisfactory predictive abilities; the mean absolute error of the forecast (Ni, Mn, Zn, Cu, and Pb) did not exceed 21%. Hence, the models show great potential, as they could be applied to, for example, spatial planning for which environmental aspects (i.e., sediment quality in the stormwater drainage systems) are accounted.

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Heavy metal contamination in surface runoff sediments of the urban area of Vilnius, Lithuania

Cited by 18 publications

References 0 publications

Heavy Metals Contamination and Ecological Risk Assessment in Surface Sediments of Namal Lake, Pakistan

Heavy Metals Contamination and Ecological Risk Assessment in Surface Sediments of Namal Lake, Pakistan

Assessment of Heavy Metal Pollution in the Blyde and Steelpoort Rivers of the Olifants River System, South Africa

Modeling of Heavy Metal (Ni, Mn, Co, Zn, Cu, Pb, and Fe) and PAH Content in Stormwater Sediments Based on Weather and Physico-Geographical Characteristics of the Catchment-Data-Mining Approach

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