Assessment of sediment quality using different pollution indicators and statistical analyses, Hurghada area, Red Sea coast, Egypt

Nour, Hamdy E.; El‐Sorogy, Abdelbaset S.; Abdelwahab, Mohamed A.; Almadani, Sattam; Alfaifi, Hussain J.; Youssef, Mohamed

doi:10.1016/j.marpolbul.2018.06.046

Cited by 40 publications

(16 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…One important yet relatively seldom studied means of metals transferring to sediments is storm water run-off. Contemporary studies [2,[5][6][7][8][9][10] revealed that storm water run-off carried metals originating from a variety of everyday activities associated with tire wear, corrosion, roof run-off and fuel combustion products. It is well established that run-off from urbanized catchment is abundant in HMs [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Heavy Metals in Sediments of Urban Streams: Contamination and Health Risk Assessment of Influencing Factors

et al. 2019

View full text Add to dashboard Cite

Sediments of two urban streams in northern Poland outflowing to the Baltic Sea were assessed to explain the spatial variation in relation to urbanization level of the catchment, the role of retention tanks (RTs) and identification of pollution level. During the 3 month period of investigation sediment samples were collected from the inflow (IN) and outflow (OUT) of six RTs located on streams for flood protection. Six heavy metals (HMs) were investigated: Cu, Pb, Zn, Cd, Ni, Cr. The assessment of four geochemical enrichment indices used to quantify contamination of HMs in the sediments at IN and OUT samples was carried out. Contamination factor (CF), pollution load index (PLI), geoaccumulation index (Igeo) and potential ecological risk (RI) were calculated and the indices usefulness was assessed. Also, the hazard quotient (HQ) was calculated to assess health risk associated with dredging works. In sediments from RTs where paved surfaces constituted more than 70% of the catchment the HMs concentrations were from one to three times higher for Ni and from two to 143 times higher for Cu in comparison to soft catchment results. The extremely high Cu concentration (1114 mg/kg d.w.) found in sediments at RT Orłowska IN was most likely associated with large area of roofs covered with copper sheet. Calculation of CF, PLI, Igeo, RI, HQ indicators allows for a complex and multi-dimensional assessment of sediment status. Among these, CF and PLI classified the analyzed sediments as most polluted. Basing on the sedimentary HMs concentrations the health risk level via dermal exposure pathway was assessed as low.

show abstract

Section: Introductionmentioning

confidence: 99%

Heavy Metals in Sediments of Urban Streams: Contamination and Health Risk Assessment of Influencing Factors

et al. 2019

View full text Add to dashboard Cite

show abstract

Section: Metal Concentrations and Distribution In Baechmentioning

confidence: 99%

“…Depending on the characteristics of the locations, some heavy metals may accumulate at the locations [6,7,19,21,34,[52][53][54][55]61]. The distribution maps of these deposits are important in terms of showing the differences and similarities of the elements and heavy metals' general distribution on the site [11,34]. In this context, distribution maps of the heavy metal concentrations of Al, Fe, P, Ti, which were the metals representing the first factor, in the beach sand samples from Moonlight Beach were prepared (Figure 3).…”

Section: Metal Concentrations and Distribution In Baechmentioning

confidence: 99%

“…The following indexes were used in the studies: Geo-accumulation index (I-geo) and Enrichment Factor (EF), Contamination Factor (CF), Contamination Degree (CD), Pollution Load Index (PLI), Ecological Risk Index (ERI), Potential Risk Factor (PRF), Potential Ecological Risk Index (PERI), and Potential Contamination Index (PCI). Also, there are several studies on metal accumulation indices and heavy metal accumulations in beach sands [27][28][29][30][31][32][33][34][35][36][37].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

View full text Add to dashboard Cite

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.

show abstract

“…Carbon (C), nitrogen (N), and phosphorus (P) in plants are the basic nutrient elements required by plants; meanwhile, these elements are important for cell metabolism, protein and genetic materials [2]. The stoichiometry of elements is a hotspot in the current research on ecological field, which is aim to probe into the important role of physiological and biochemical processes of C, N, P and other elements in the biogeochemical cycle and energy sources [3][4][5]. As one of the universal characteristics of the measurement of C, N and P in high terrestrial plants, it is reported that the significant negative correlation of the leaf C and N: P is an equilibrium strategy for nutrient use efficiency of green plants during the fixed carbon process [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Eco Stoichiometric Characteristics of Soil Plant System of <i>Taxus wallichiana</i> under Multi factor Driving

Zhang¹,

Wu²,

Zhang³

et al. 2021

Pol. J. Environ. Stud.

View full text Add to dashboard Cite

To investigate the soil fertility of the rare plant, Taxus wallichiana var. mairei, the distribution characteristics and corresponding influencing factors of carbon (C), nitrogen (N), and phosphorus (P) in Taxus wallichiana and its surrounding soil were determined in this study. Redundancy analysis was used to evaluate the relationship among different indicators of soil surrounding Taxus wallichiana trees. The results exhibited that the contents of organic matters, Total-N, Total-P, Hydrolyzable-N, and Valid-P in soils surrounding the Taxus wallichiana trees was 44.24±5.04 g/kg, 3.81±0.53 g/kg, 2.02±2.80 g/kg, 679.73±27.61 mg/kg and 248.95±45.15 mg/kg, respectively. The contents of C, N and P in Taxus wallichiana leaves was 46.03±1.10%, 1.89±0.43% and 11.49±3.32%, respectively; and in Taxus wallichiana stem was 45.83±0.33%, 0.71±0.19% and 9.96±3.10%, respectively. Concerned nutrients in the soils surrounding Taxus wallichiana trees were abundant. The soil fertility index was 4.94 according to the improved Nemerow index method with the weighted average, which suggested that the soil surrounding Taxus wallichiana trees was fertile in Mount Fanjing. The contents of C, N and P in the leaf of Taxus wallichiana were greater than that in its stems. The soil C was the major factor impacting the distribution of N in the stem of Taxus wallichiana. The soil vaild-P was the critical factor influencing the distribution of P in the stem of Taxus wallichiana. The soil bulk density was the highest influencing factor of the C content in the leaf of Taxus wallichiana. The total-P in the soil has the dominant governance on the P content in the plant.

show abstract

Assessment of sediment quality using different pollution indicators and statistical analyses, Hurghada area, Red Sea coast, Egypt

Cited by 40 publications

References 20 publications

Heavy Metals in Sediments of Urban Streams: Contamination and Health Risk Assessment of Influencing Factors

Heavy Metals in Sediments of Urban Streams: Contamination and Health Risk Assessment of Influencing Factors

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

Eco Stoichiometric Characteristics of Soil Plant System of <i>Taxus wallichiana</i> under Multi factor Driving

Contact Info

Product

Resources

About