Sediment Contamination by Heavy Metals and PAH in the Piombino Channel (Tyrrhenian Sea)

Sediment contamination is of major concern in areas affected by heavy maritime traffic. The spatial variation and contamination of 11 trace elements and 17 PAHs in surface sediments were studied along a 31 km transect along the seaway from the port of Piombino (Tuscany) to the port of Portoferraio (Elba Island) in the Northern Tyrrhenian Sea. Heavy metal contamination was detected at sites near Piombino (Ni, Pb, Hg, Cu and Zn) and at sites near Portoferraio (Pb, Zn, Hg, Cr and Cd). Each of the 35 sampled sites showed PAH contamination, with the highest concentrations at sites near Portoferraio. The most abundant isomers detected were 2- and 4-ring PAHs. PAH ratio analysis showed a prevalence of PAHs of pyrolytic origin. High values of PAHs and heavy metals were related to high sediment water content, TOC, silt, and clay content. Arsenic increased with increasing depth. The correlation between concentrations of metals and PAHs suggests common anthropogenic sources and is of concern for possible synergistic adverse effects on the biota.

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Heavy metal pollution status in surface sediments of the Khajeh Kory River, north Iran

Water Science & Technology ◽

10.2166/wst.2020.202 ◽

2020 ◽

Vol 81 (6) ◽

pp. 1148-1158

Author(s):

Maryam Zare Khosheghbal ◽

Marjan Esmaeilzadeh ◽

Fereydoun Ghazban ◽

Mohammad Ebrahim Charmsazi

Keyword(s):

Heavy Metals ◽

Heavy Metal ◽

Metal Pollution ◽

Heavy Metal Pollution ◽

Metal Contamination ◽

Surface Sediments ◽

Heavy Metal Contamination ◽

Principal Component ◽

Anthropogenic Sources ◽

Riverbed Sediments

Abstract This study aimed at exploring the extent of likely sources of heavy metal pollution in sediments of the Khajeh Kory riverbed in the north of Iran. In order to assess the heavy metal contamination, samples from surface sediments in 10 stations covering the river were collected and analysed to determine heavy metal contents including Cd, Cu, Ni, Pb, Zn, Mn, Co, Al, and Fe. Three guidelines were applied to assess the heavy metal contamination. Compared with the global average values, the calculated enrichment factors indicated high values for Fe, Mn, Cd, Co, and Cu, and very high values for Pb and Zn. The results obtained from principal component analysis revealed that the geogenic and anthropogenic sources were the main causes of the widespread enrichment of heavy metals in the riverbed sediments. The results suggested that the riverbed sediments were contaminated with heavy metals, which contribute to the freshwater toxicity in the ecosystem of the Khajeh Kory River.

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Environmental Risk Assessment of Petroleum Activities in Surface Sediments, Suez Gulf, Egypt

Journal of Marine Science and Engineering ◽

10.3390/jmse9050473 ◽

2021 ◽

Vol 9 (5) ◽

pp. 473

Author(s):

Magda M. Abou El-Safa ◽

Mohamed Gad ◽

Ebrahem M. Eid ◽

Ashwaq M. Alnemari ◽

Mohammed H. Almarshadi ◽

...

Keyword(s):

Heavy Metals ◽

Risk Assessment ◽

Heavy Metal ◽

Surface Sediment ◽

Surface Sediments ◽

Surf Zone ◽

Risk Index ◽

Negative Relationship ◽

Anthropogenic Sources ◽

Suez Gulf

The present study focuses on the risk assessment of heavy metal contamination in aquatic ecosystems by evaluating the current situation of heavy metals in seven locations (North Amer El Bahry, Amer, Bakr, Ras Gharib, July Water Floud, Ras Shokeir, and El Marageen) along the Suez Gulf coast that are well-known representative sites for petroleum activities in Egypt. One hundred and forty-six samples of surface sediments were carefully collected from twenty-seven profiles in the intertidal and surf zone. The hydrochemical parameters, such as pH and salinity (S‰), were measured during sample collection. The mineralogy study was carried out by an X-ray diffractometer (XRD), and the concentrations of Al, Mn, Fe, Cr, Cu, Co, Zn, Cd, and Pb were determined using inductively coupled plasma mass spectra (ICP-MS). The ecological risks of heavy metals were assessed by applying the contamination factor (CF), enrichment factor (EF), geoaccumulation index (Igeo), pollution load index (PLI), and potential ecological risk index (RI). The mineralogical composition mainly comprised quartz, dolomites, calcite, and feldspars. The average concentrations of the detected heavy metals, in descending order, were Al > Fe > Mn > Cr > Pb > Cu > Zn > Ni > Co > Cd. A non-significant or negative relationship between the heavy metal concentration in the samples and their textural grain size characteristics was observed. The coastal surface sediment samples of the Suez Gulf contained lower concentrations of heavy metals than those published for other regions in the world with petroleum activities, except for Al, Mn, and Cr. The results for the CF, EF, and Igeo showed that Cd and Pb have severe enrichment in surface sediment and are derived from anthropogenic sources, while Al, Mn, Fe, Cr, Co, Ni, Cu, and Zn originate from natural sources. By comparison, the PLI and RI results indicate that the North Amer El Bahry and July Water Floud are considered polluted areas due to their petroleum activities. The continuous monitoring and assessment of pollutants in the Suez Gulf will aid in the protection of the environment and the sustainability of resources.

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Assessment of the metal pollution in surface sediments of coastal Tasaul Lake (Romania)

Environmental Monitoring and Assessment ◽

10.1007/s10661-020-08698-0 ◽

2020 ◽

Vol 192 (12) ◽

Author(s):

Dan Vasiliu ◽

Andra Bucse ◽

Naliana Lupascu ◽

Bogdan Ispas ◽

Catalin Gheablau ◽

...

Keyword(s):

Metal Contamination ◽

Surface Sediments ◽

Heavy Metal Contamination ◽

Contamination Factor ◽

Distribution Patterns ◽

Agricultural Runoff ◽

Pollution Load Index ◽

Anthropogenic Sources ◽

Pollution Indices ◽

Metal Concentrations

AbstractForty-three surface sediment samples were collected in September 2019 from Tasaul Lake (Black Sea coast, Romania) to examine the metal distribution patterns, assess the level of metal contamination, and identify the pollutant sources. The determined mean metal concentrations were as follows: Al 49,772 mg/kg, Zn 84.40 mg/kg, Cr 83.70 mg/kg, V 76.45 mg/kg, Ni 42.53 mg/kg, Cu 34.27 mg/kg, Pb 26.30 mg/kg, As 12.49 mg/kg, and Hg 0.06 mg/kg. The metals in the surface sediments of Tasaul Lake displayed moderate spatial variation, with higher metal concentrations mainly occurring in the south and southeast (As, Pb, and Hg), southwest (Cu and Zn), and west of the lake (Cr, Ni, and V). Heavy metal contamination in sediments is assessed using pollution indices such as enrichment factor, contamination factor, and pollution load index. The highest CFs and EFs were determined for As (moderate to high pollution), followed by Pb (low to moderate pollution). The Cu, Zn, and Hg pollution indices showed values corresponding to low pollution levels, while Ni, Cr, and V presented the lowest indices, suggesting unpolluted sediments. Multivariate statistical analyses were performed to identify the origin of the analyzed heavy metals. Cr was predominantly sourced from lithogenic components, Ni and V originated from both natural and anthropogenic sources, and As, Cu, Zn, Pb, and Hg showed mainly anthropogenic sources such as agricultural runoff, domestic and industrial wastewater discharges, and quarrying activities.

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Heavy Metal Contamination and Ecological Risk Assessment of Overlying Water and Sediments of Nkozoa Lake (Southern Cameroon)

Annual Research & Review in Biology ◽

10.9734/arrb/2021/v36i430366 ◽

2021 ◽

pp. 92-109

Author(s):

Noa Tang Sylvie Désirée ◽

Ekoa Bessa Armel Zacharie ◽

Tchakam Kamtchueng Brice ◽

Wongan Kouonchie Sorel Ange ◽

Etame Jacques ◽

...

Keyword(s):

Heavy Metals ◽

Heavy Metal ◽

Ecological Risk ◽

Metal Contamination ◽

Heavy Metal Contamination ◽

Anthropogenic Sources ◽

Overlying Water ◽

Sediment Samples ◽

Contamination Degree ◽

Effect Level

Examination of heavy metals (Cr, Cu, Zn, Pb, Hg, Cd and Ni) in overlying water and sediments was conducted in Lake Nkozoa, in a peripheral area of Yaoundé characterized by a high population density and rapid economic development in Cameroon. Sediment samples were collected at the entrance and near the center of the lake, using a raft and polyvinyl chloride (PVC) pipes. They were subjected to water quality parameters, heavy metals comparisons and calculations of pollution indices and ecological risks followed by statistical analysis in order to identify and estimate the sources of metal contamination in overlying water and sediments of the Nkozoa Lake. The physico-chemical parameters of water show that the pH (5 < pH < 6), total dissolved solids (TDS~130 g/L) and conductivity (EC~194.8 µs/cm) are below the recommendations of the WHO. The average heavy metal concentrations in sediments, except Cd, are lower than the upper continental crust (UCC) and several environmental contamination monitoring parameters, such as threshold effect level (TEL), probable effect level (PEL), and severe effect level (SEL). The sediment samples show a low heavy metal contamination degree (class 0) and low potential ecological risk (PER) level, except for Cd and Hg which have high contamination degree (class 1 to 6) and moderate PER. Matrix correlation shows that some parameters like pH, EC, Cr and TDS, Cu, Hg in water have perfect positive correlations (r = 1.00) suggesting common sources of contamination. Cluster analyses coupled with matrix data for sediments revealed that Cd is the most contaminant elements derived from anthropogenic sources.

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Heavy Metal Contamination in Oryza sativa L. at the Eastern Region of Malaysia and Its Risk Assessment

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph19020739 ◽

2022 ◽

Vol 19 (2) ◽

pp. 739

Author(s):

Nur Syahirah Zulkafflee ◽

Nurul Adillah Mohd Redzuan ◽

Sara Nematbakhsh ◽

Jinap Selamat ◽

Mohd Razi Ismail ◽

...

Keyword(s):

Heavy Metals ◽

Risk Assessment ◽

Heavy Metal ◽

Cancer Risk ◽

Health Risk ◽

Health Risk Assessment ◽

Metal Contamination ◽

Heavy Metal Contamination ◽

Anthropogenic Sources ◽

Acceptable Limit

Paddy plants tend to accumulate heavy metals from both natural and anthropogenic sources, and this poses adverse risks to human health. The objective of this study was to investigate heavy metal contamination in paddy plants in Kelantan, Malaysia, and its health risk assessment. The bioaccumulation of heavy metals was studied by means of enrichment (EF) and translocation factors (TF). The health risk assessment was performed based on USEPA guidelines. The EF for heavy metals in the studied areas was in the descending order of Cu > As > Cr > Cd > Pb. Meanwhile, Cr and Pb exhibited higher TF values from stem to grain compared with the others. The combined hazard index (HI) resulting from five heavy metals exceeded the acceptable limit (HI >1). The lifetime cancer risk, in both adult and children, was beyond the acceptable limit (10−4) and mainly resulted from exposure. The total cancer risk (CRt) due to simultaneous exposures to multiple carcinogenic elements also exceeded 10−4. In conclusion, intake of heavy metal through rice ingestion is likely to cause both non-carcinogenic and carcinogenic health risks. Further research is required to investigate the extent of heavy metal contamination in agricultural soils and, moreover, to establish human exposure as a result of rice consumption.

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Bioavailability and Assessment of Metal Contamination in Surface Sediments of Rades-Hamam Lif Coast, around Meliane River (Gulf of Tunis, Tunisia, Mediterranean Sea)

Journal of Chemistry ◽

10.1155/2019/4284987 ◽

2019 ◽

Vol 2019 ◽

pp. 1-11 ◽

Cited By ~ 2

Author(s):

Rim Ben Amor ◽

Asma Yahyaoui ◽

Myriam Abidi ◽

Lasaad Chouba ◽

Moncef Gueddari

Keyword(s):

Heavy Metals ◽

Mediterranean Sea ◽

Surface Sediments ◽

Total Concentration ◽

Anthropogenic Sources ◽

Residual Fraction ◽

Gulf Of Tunis ◽

Exchangeable Fraction ◽

Geochemical Indices ◽

Low Toxicity

The total concentration and the speciation of heavy metals (Pb, Cd, Cu, Zn, Ni, and Cr) in surface sediments of Rades-Hamam Lif coast were determined, with particular focus on the effect that urban and industrial waste in the Meliane river has on the estuary and coastal surface sediments of the Rades-Hamam Lif coast, off the Mediterranean Sea. Several geochemical indices were applied to assess the risk of contamination and the environmental risks of heavy metals on surface sediments. The total concentrations of these heavy metals are influenced by runoff, industrial, and urban wastewater. The Cd, Pb, Zn, and Ni are affected by anthropogenic sources, especially at the mouth of the Meliane river. The sequential extraction of Cd was presented dominantly in the exchangeable fraction and thus the high potential bioavailability. In contrast, Cr and Cu were mostly bound to the residual fraction indicating their low toxicity and bioavailability. The order of migration and transformation sequence was Cd > Pb > Ni > Zn > Cr > Cu, and the degree of pollution was Cd > Pb > Ni > Zn > Cr > Cu.

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Assessment of Heavy Metal Contamination in Soil in and around Sohar Industrial Port Area, Oman

Sultan Qaboos University Journal for Science [SQUJS] ◽

10.24200/squjs.vol24iss1pp1-10 ◽

2019 ◽

Vol 24 (1) ◽

pp. 1 ◽

Cited By ~ 1

Author(s):

Maha Al-Jabri ◽

Daniel Moraetis ◽

Reginald Victor

Keyword(s):

Heavy Metals ◽

Heavy Metal ◽

Inductively Coupled Plasma ◽

Heavy Metal Contamination ◽

Anthropogenic Impacts ◽

International Standards ◽

Anthropogenic Sources ◽

Emission Spectrometry ◽

High Background ◽

Port Area

The increase in the number of heavy metal emitting sources in industrial areas is a serious issue in pollution science. Sohar Industrial Port (SIP) area is located in the northern part of Oman where different industrial activities like petrochemical production, metal processing, and waste disposal are prevalent. This study comprehensively identified the presence and quantities of heavy metals in the soils of Sohar Industrial Port area and traced their origin to geogenic or anthropogenic sources. Bulk geochemical and mineralogical analyses were carried out on all samples. Environmentally available and bioavailable heavy metals were extracted by diethylenetriaminepentaacetic acid (DTPA) and were finally analyzed using Inductively Coupled Plasma-Optical Emission spectrometry (ICP-OES). The environmentally available metals that showed higher concentrations when compared to international standards were Ni and Cd. The geochemical evidence showed a strong geochemical signature of the ophiolite rocks in the soils as indicated by the significant correlation between Cr and Ni (P< 0.05). In addition, the Cd content showed significant correlations with Ni and Cr (P< 0.05). Other metals like Pb and Zn, possibly also were geogenic in origin, but with significantly elevated concentrations in samples close to a national highway (P< 0.05). The present study demonstrated the significance of understanding the geological framework of an industrial area, which is already imposing high background concentrations of Cr, Ni and Cd, and also the possible anthropogenic impacts in the cases of Pb and Cd that exceeded internationally permissible limits.

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Heavy Metal Contamination in the Floodplains Along Mula River, Pune District, Maharashtra State, India

Hydrospatial Analysis ◽

10.21523/gcj3.19030102 ◽

2019 ◽

Vol 3 (1) ◽

pp. 12-21

Author(s):

Ashwini Supekar ◽

Ashok Issac ◽

Ashwini Rane

Keyword(s):

Heavy Metals ◽

Heavy Metal ◽

Metal Contamination ◽

Surface Sediments ◽

Heavy Metal Contamination ◽

Contamination Factor ◽

Pollution Load Index ◽

Pollution Load ◽

Urban Sites

Pre-urban, urban and post-urban stretch of the Mula River in Pune District of Maharashtra (India) is examined for quantification of heavy metals (Cr, Co, Ni, Cu, Zn and Cd), calculation of the Pollution Load Index (PLI) and Contamination Factor (CF). They were estimated from the surface sediments (0-5 cm) at 10 sampling sites along the Mula river. High Cr anomaly (Max. 388.20 ppm) followed by Co (Max. 104.91 ppm), Ni (Max. 167.44 ppm), Cu (Max. 391.35 ppm), Zn (Max. 507.91 ppm) and Cd (Max. 2.38 ppm) is seen at various locations mostly encompassing the urban stretch. PLI is found to be high i.e., >1 in urban sites like Khadki, Kalyaninagar and Kharadi than the rural downstream sites. There is negligible mobility of the heavy metals and the urban floodplains are increasingly accumulating the heavy metals to a highly hazardous level.

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Assessment of metal contamination in coastal marine sediments of Makadi Bay on the Red Sea, Egypt

Marine and Freshwater Research ◽

10.1071/mf19306 ◽

2020 ◽

Vol 71 (10) ◽

pp. 1241

Author(s):

Mohamed Youssef ◽

Hashem Madkour ◽

Raafat El Attar ◽

Abbas Mansour ◽

Amani Badawi

Keyword(s):

Heavy Metals ◽

Metal Contamination ◽

Heavy Metal Contamination ◽

Atomic Absorption Spectrophotometry ◽

Enrichment Factors ◽

Anthropogenic Sources ◽

Pollution Indices ◽

Trace Metal Concentration ◽

Coastal Marine ◽

Cd Contamination

To assess the heavy metal contamination in the sediments of Makadi Bay (Hurghada, Egypt), surface samples were collected from 32 locations. Six heavy metals (Fe, Mn, Zn, Cu, Pb and Cd) were analysed using atomic absorption spectrophotometry. The order of trace metal concentration in the samples was Mn>Zn>Pb>Cu>Cd. The analytical results were subjected to univariate statistical analyses to evaluate the distribution and abundance of the metals in the area. The degree of pollution of the sediments by these metals was evaluated by calculating enrichment factors and the geoaccumulation, pollution load and soil pollution indices. The results indicated that all marine sediment locations are practically unpolluted by metals. The high metal concentrations of Pb and Cd due to anthropogenic sources (mean 38.76 and 2.43μgg–1 respectively) recorded in most samples are essentially attributable to the anomalous concentrations of Pb and Cd in these samples. Both natural and anthropogenic sources of Pb and Cd contamination around Makadi Bay are possible. Generally, the levels of heavy metals in the study area do not constitute any serious environmental risk, except in the case of Pb and Cd.

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Feasibility of using environmental covariates and machine learning to predict the spatial variability of selected heavy metals in soils

10.5194/egusphere-egu2020-12378 ◽

2020 ◽

Author(s):

Mojtaba Zeraatpisheh ◽

Rouhollah Mirzaei ◽

Younes Garosi ◽

Ming Xu ◽

Gerard B.M. Heuvelink ◽

...

Keyword(s):

Machine Learning ◽

Heavy Metals ◽

Heavy Metal ◽

Spatial Distribution ◽

Random Forest ◽

Metal Contamination ◽

Heavy Metal Contamination ◽

Prediction Performance ◽

Anthropogenic Sources ◽

Environmental Covariates

Heavy metal contamination in soil is a major environmental issue intensified by rapid industrial and population growth. Understanding the spatial distribution of soil contamination by heavy metals in the ecosystem is a necessary precondition to monitor soil health and to assess the ecological risks. The main sources of heavy metals in soil are natural and anthropogenic sources. Natural sources are typically released of heavy metals from rock by weathering and atmospheric precipitation. Anthropogenic sources are related to industrialization, rapid urbanization, agricultural practices, and military activities. We analyzed a total of 358 topsoil samples (0&#8211;30 cm) collected in Golestan province in the northeast of Iran based on a regular square grid networks with 1,700 squares each sized 2.5 km&#178;(random sampling within the grid). From these samples, we determined the spatial distribution of Cd, Cu, Ni, Zn, and Pb using random forest (RF). A multi-spectral image (Landsat 8), and environmental derivatives calculated from terrain attributes, climatic parameters, parent material, land use maps, distances to mine sectors, main roads, industrial sites, and rivers were used as covariates to predict the spatial distribution of concentrations of heavy metals. The multi-collinearity of the predictors was examined by the variance inflation factor (VIF), and a feature selection process (genetic algorithm) was applied to avoid noise and optimize the selected input variables for the final model. The predictive accuracy of RF model was assessed by the mean prediction error (ME), root mean squared error (RMSE), and coefficient of determination (R2) using 5-fold cross-validation technique. The results showed that the concentration levels (mg kg-1) of Cd, Cu, Pb, Ni, and Zn varied from 0.02 to 2.75, 9.70 to 93.70, 6.80 to 114.20, 9.50 to 93.20, and 25.10 to 417.4, respectively. The best prediction performance was for Ni (RMSE=9.9 mg kg-1 and R2=56.6%), and the lowest prediction performance for Cd (RMSE=0.4 mg kg-1 and R2=28.0%). Environmental covariates that control soil moisture and water flow along with climatic factors were the most important variables to define the spatial distribution of soil heavy metals. We conclude that the RF model using easily accessible environmental covariates is a promising, cost-effective and fast approach to monitor the spatial distribution of heavy metal contamination in soils.Keywords: Heavy metals; digital soil mapping; machine learning; random forest; spatial variation; soil pollution.

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