Statistical modeling the effect of sediment physicochemical properties on the concentration of heavy metal (case study: Musa Creek, SW Iran)

Shabankareh, Maryam Ghazanfari; Amanipoor, Hakimeh; Battaleb-Looie, Sedigheh; Khatooni, Javad Dravishi

doi:10.1007/s12665-018-7289-6

Cited by 4 publications

(5 citation statements)

References 40 publications

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“…The Pearson correlation coefficient (r) analysis of various parameters of the sediments and heavy metals revealed that Cr was positively correlated (p ≤ 0.05) with silt, Cd and clay (r = 0.94, 0.89 and 0.83, respectively), while it was negatively correlated with EC, sand, OM, Cu and Ni, with r values of −0.95, −0.93, −0.83, −0.71 and −0.71, respectively (Table S1). The positive correlation of Cr with clay and silt contents was reported by Shabankareh et al [34]. In contrast with our result, Kierczak et al [38] and Shabankareh et al [34] showed that Cr is positively correlated with OM.…”

Section: Correlation Between Sediment Parameters and Heavy Metalscontrasting

confidence: 92%

“…The positive correlation of Cr with clay and silt contents was reported by Shabankareh et al [34]. In contrast with our result, Kierczak et al [38] and Shabankareh et al [34] showed that Cr is positively correlated with OM.…”

Section: Correlation Between Sediment Parameters and Heavy Metalscontrasting

confidence: 92%

“…The environmental mobility and availability of heavy metals in sediments are controlled by their physicochemical properties, including the total metal content, pH, Electrical conductivity (EC), organic matter (OM), grain size, and calcium carbonate and oxides contents [10,[32][33][34]. The present data show a significant difference (p ≤ 0.05) in the EC, OM, sand and silt values between the positions (upstream, middlestream and downstream) of the three studied drains (Table 1).…”

Section: Physiochemical Parametersmentioning

confidence: 99%

“…On the other hand, the OM in the present study ranged from 1.40% in the upstream to 2.59% in the downstream. The role of OM in metal availability has been extensively investigated [33,34,38]. It was found that increasing the content of OM led to an increased mobility and availability of heavy metals to plant roots.…”

Section: Physiochemical Parametersmentioning

confidence: 99%

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Ecological Risk Assessment of Heavy Metals along Three Main Drains in Nile Delta and Potential Phytoremediation by Macrophyte Plants

El‐Amier

Bonanomi

Al‐Rowaily

et al. 2020

Plants

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The use of drainage water in the irrigation of agroecosystem is associated with environmental hazards, and can pose threats to human health. Nine heavy metals (Fe, Mn, Zn, Cu, Co, Cr, Ni, Cd and Pb) along three main drains in the middle Nile Delta were measures in the sediments, roots and shoots of three common macrophytes (Echinochloa stagnina, Phragmites australis and Typha domingensis). The physicochemical characteristics, as well as the enrichment factor (Ef), contamination factor (Cf), geoaccumulation index (Igeo), ecological risk factor (Er), degree of contamination (Dc) and potential ecological risk index (PERI), were determined for sediment. The metal bioaccumulation factor (BAF) and translocation factor (TF) were assessed for plants. Data revealed high contents of Cr, Zn and Cd in the upstream of the drains, while Mn, Cu and Ni were recorded in high concentrations in the downstream. Mn, Cr, Co, Cu, Ni and Zn were recorded to be within EU (2002), CSQGD (2007) and US EPA (1999) limits, while Cd and Pb showed high a ecological risk index. This high concentration of pollutants could be attributed to unremitting industrial activities, which can bioaccumulate in the food chains and cause serious problems for humans. The root of P. australis showed the effective accumulation of most of the elements, while T. domingensis revealed the highest accumulation of Pb. However, the highest BAF shoot value was found in T. domingensis for most of the heavy metals, except for Fe and Zn in P. australis and Mn in E. stagnina. Thus, P. australis could be used as a potential phytoextractor of these hazardous metals, as an eco-friendly and cost-efficient method for remediation of the polluted drains. Further, T. domingensis could be integrated as a hyperaccumulator of Pb. Strict laws and regulations must be taken into consideration by the policymaker against unmanaged industrial activities, particularly near the water streams in the Nile Delta.

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Section: Correlation Between Sediment Parameters and Heavy Metalscontrasting

confidence: 92%

Section: Correlation Between Sediment Parameters and Heavy Metalscontrasting

confidence: 92%

Section: Physiochemical Parametersmentioning

confidence: 99%

Section: Physiochemical Parametersmentioning

confidence: 99%

See 2 more Smart Citations

Ecological Risk Assessment of Heavy Metals along Three Main Drains in Nile Delta and Potential Phytoremediation by Macrophyte Plants

El‐Amier

Bonanomi

Al‐Rowaily

et al. 2020

Plants

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“…On the other hand, index calculations and statistical analyses were used in the study on Gabes Coast (Tunisia) beach sands, and it was revealed that Cu, Cd, and Zn were enriched and posed ecological risks [32]. Multivariate statistical methods were conducted on the data to examine heavy metal distribution in the coastal sands of Shenzhen (China); later, the risk indices were calculated for these heavy metals, as a result, Cd, and Hg became prominent based on their ecological risk index values [42]. The potential ecological risk indices of Cu, Pb, Ni, Zn, and Hg elements were found to be high in the study conducted on the beach sands of Laizhou Bay (China); moreover, it was revealed that their distribution was compatible with industrial areas [43].…”

Section: Introductionmentioning

confidence: 99%

Data Analysis of Beach Sands’ Chemical Analysis Using Multivariate Statistical Methods and Heavy Metal Distribution Maps: The Case of Moonlight Beach Sands, Kemer, Antalya, Turkey

Yalçın

2020

Symmetry

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Multivariate statistical methods are widely used in several disciplines of fundamental sciences. In the present study, the data analysis of the chemical analysis of the sands of Moonlight Beach in the Kemer region was examined using multivariate statistical methods. This study consists of three parts. The multivariate statistical analysis tests were described in the first part, then the pollution indexes were studied in the second part. Finally, the distribution maps of the chemical analyses and pollution indexes were generated using the obtained data. The heavy metals were mostly observed in location K1, while they were sorted as follows based on their concentrations: Mg > Fe > Al > Ti > Sr > Mn > Cr > Ni > Zn > Zr > Cu > Rb. Also, strong positive correlations were found between Si, Fe, Al, K, Ti, P. According to the results of factor analysis, it was found that four factors explained 83.5% of the total variance. On the other hand, the coefficient of determination (R2) was calculated as 63.6% in the regression model. Each unit increase in the value of Ti leads to an increase of 0.022 units in the value of Si. Potential Ecological Risk Index analysis results (RI < 150) revealed that the study area had no risk. However, the locations around Moonlight Beach are under risk in terms of Enrichment Factor and Contamination Factor values. The index values of heavy metals in the anomaly maps and their densities were found to be successful; and higher densities were observed based on heavy metal anomalies.

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Evaluation of Lead and Cadmium Contamination in the Zayandeh Rud River

Chamani

2020

Standing Up to Climate Change

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Statistical modeling the effect of sediment physicochemical properties on the concentration of heavy metal (case study: Musa Creek, SW Iran)

Cited by 4 publications

References 40 publications

Ecological Risk Assessment of Heavy Metals along Three Main Drains in Nile Delta and Potential Phytoremediation by Macrophyte Plants

Ecological Risk Assessment of Heavy Metals along Three Main Drains in Nile Delta and Potential Phytoremediation by Macrophyte Plants

Data Analysis of Beach Sands’ Chemical Analysis Using Multivariate Statistical Methods and Heavy Metal Distribution Maps: The Case of Moonlight Beach Sands, Kemer, Antalya, Turkey

Evaluation of Lead and Cadmium Contamination in the Zayandeh Rud River

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