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The concentrations of As, Cd, Cr, Co, Cu, Ni, Pb, and Zn in water and sediment samples from Trepça and Sitnica rivers were determined to assess the level of contamination. Six water and sediment samples were collected during the period from April to July 2014. Most of the water samples was found within the European and Kosovo permissible limits. The highest concentration of As, Cd, Pb, and Zn originates primarily from anthropogenic sources such discharge of industrial water from mining flotation and from the mine waste eroded from the river banks. Sediment contamination assessment was carried out using the pollution indicators such as contamination factor ( CF ), degree of contamination ( Cd ), modified degree of contamination ( mCd ), pollution load index ( PLI ), and geo-accumulation index (I geo ). The CF values for the investigated metals indicated a high contaminated nature of sediments, while the Cd values indicated a very high contamination degree of sediments. The mCd values indicate a high degree of contamination of Sitnica river sediment to ultrahigh degree of contamination of Trepça river sediment. The PLI values ranged from 1.89 to 14.1 which indicate that the heavy metal concentration levels in all investigated sites exceeded the background values and sediment quality guidelines. The average values of Igeo revealed the following ranking of intensity of heavy metal contamination of the Trepça and Sitnica river sediments: Cd > As > Pb > Zn > Cu > Co > Cr > Ni. Cluster analysis suggests that As, Cd, Cr, Co, Cu, Ni, Pb, and Zn are derived from anthropogenic sources, particularly discharges from mining flotation and erosion form waste from a zinc mine plant. In order to protect the sediments from further contamination, the designing of a monitoring network and reducing the anthropogenic discharges are suggested.

This detailed study assessed heavy metal contamination of sediments/soil near central India’s largest copper mining area using 38 sampling sites within 10 km of the mine using atomic absorption spectroscopy. This study utilized multivariate pattern recognition methods, namely hierarchical clustering analysis (HCA) and principal component analysis (PCA), for source identification. Twelve parameters, i.e., copper (Cu), manganese (Mn), cobalt (Co), zinc (Zn), nickel (Ni), lead (Pb), organic matter (OM), cation exchange capacity (CEC), soil pH, distance (D), and elevation (E) were analyzed. The hierarchical cluster analysis (HCA) was used to analyze the sample sites with similar metal contamination and principal component analysis (PCA) was used to analyze the relationship between the parameters as well as to identify sources of heavy metal pollution. Three major pollution hotspots were detected by AHC and were classified as unpolluted/low pollution sites (UPS: mean concentration factor of 1.35 for Cu), highly polluted sites (HPS: mean concentration factor of 22 for Cu), and extremely polluted sites (EPS: mean concentration factor of 74 for Cu). PCA revealed three hidden factors/components, namely PC1 (explaining 38% of the variability), PC2 (18% of the variability), and PC3 (14% of the variability). Metals showed strong positive loading in PC1, explaining the highest variability. The mean content of Cu in soil/sediment samples was 502.526 mg/kg. The mean copper content was 10 times higher than the natural crustal value of 45mg/kg, indicating severe pollution in several sites around the study area. Mapping of copper contamination was conducted to reveal the spatial distribution of copper contamination using QGIS. This study exposes the heavy metal contamination level in surface sediments/soil and the effectiveness of pattern recognition techniques for the assessment of multivariate datasets in discerning spatial disparities and identifying the contamination causes.

Investigations on asymmetries showed that deviations from perfect bilateral symmetry are interpreted as environmental changes inducing developmental instability. Since morphological abnormalities increase with pollution, deformations may be considered indicators of the organism exposition to pollution. Therefore, the onset of asymmetry in otherwise normally symmetrical traits has been used as a measure of some stresses as well. In this context, we studied how marine pollution affects the valve morphological alterations in the mussel Mytilus galloprovincialis . We used 180 specimens (30 per site) from the aquaculture area of Goro (River Po delta, northern Adriatic Sea), translocated, and released within 50 × 50 × 50 cm cages in five sites: two disturbed and one undisturbed near Naples (eastern Tyrrhenian Sea), and one disturbed and one undisturbed near Siracusa (western Ionian Sea). Disturbed sites were stressed by heavy industrialization and heavy tankers traffic of crude and refined oil, and were defined basing on sediment contamination. In particular, by the cone-beam computed tomography we obtained 3D virtual valve surfaces to be analyzed by the geometric morphometric techniques. Specifically, we focused the levels of the shell shape fluctuating asymmetry in relation to the degrees of marine pollution in different sites of the Tyrrhenian Sea. The Mahalanobis distances (interpreted as proxy of the individual shape asymmetry deviation from the mean asymmetry) significantly regressed with the sediment contamination gradient. Indeed, although the left–right differences were normally distributed in each studied site, the individual asymmetry scores (IAS) significantly varied amongst the investigated sites. IAS showed higher values in disturbed areas than those of undisturbed ones in both Tyrrhenian and Ionian Sea. Our results are consistent with past studies on molluscans and other taxa, demonstrating some detrimental effects of chemicals on organisms, although the investigated morphological marker did not discriminate the real disturbance source. Our findings indicate that the mussels act as a prognostic tool for sea pollution levels driving detrimental effects on benthic community.

The heavy metal speciation analysis in sediments helps us understand and evaluate essential and unavoidable issues in terms of both health and environmental hazards imposed by these metals in our lives. Analyzing the total content of heavy metals enables us to understand only the quantity of the contaminants. To understand the different species or the chemical forms of heavy metals available in the sediments, we must study their speciation. Speciation studies help us determine their possible sources as well as their environmental stability in terms of availability to plants and other organisms. The heavy metals in this study were specified using four-stage sequential extraction, also known as the BCR technique. This study mainly highlights the quantification of metal contamination of Cu, Zn, Pb, Ni, Cd & Cr, and chemical forms as species in sediment samples collected from different Pune District, Maharashtra sites. Heavy metal contamination from the collected samples was analyzed with the use of flame atomic absorption spectrometry. This study indicated that Zn and Ni are among the most abundant metals in the sediment samples; however, Cu and Cd belong to the least abundant category. The oxidizable and residual forms (immobile and cannot be used by the organisms readily) appeared dominant for most heavy metals. Very significant differences were observed in the speciation of heavy metals from sample to sample, which was probably due to differences in water/soil composition and the agrochemicals like pesticides, weedicides, and fertilizers used in agricultural practices; the wastewater generated from different pharmaceuticals, chemical processing and manufacturing industries as well as the improper wastewater treatment methods.

A bleached kraft pulp mill in Nova Scotia has discharged effluent wastewater into Boat Harbour, a former tidal estuary within Pictou Landing First Nation since 1967. Fifty years of effluent discharge into Boat Harbour has created >170,000 m 3 of unconsolidated sediment, impacted by inorganic and organic contaminants, including metal[loid]s, polycyclic aromatic hydrocarbons (PAHs), dioxins, and furans. This study aimed to characterize metal(loid)-impacted sediments to inform decisions for a $89 million CAD sediment remediation program. The remediation goals are to return this impacted aquatic site to pre-mill tidal conditions. To understand historical sediment characteristics, spatiotemporal variation covering ~quarter century, of metal(loid) sediment concentrations across 103 Boat Harbour samples from 81 stations and four reference locations, were assessed by reviewing secondary data from 1992 to 2015. Metal(loid) sediment concentrations were compared to current Canadian freshwater and marine sediment quality guidelines (SQGs). Seven metal(loid)s, As, Cd, Cr, Cu, Pb, Hg, and Zn, exceeded low effect freshwater and marine SQGs; six, As, Cd, Cr, Pb, Hg, and Zn, exceeded severe effect freshwater SQGs; and four, Cd, Cu, Hg, and Zn, exceeded severe effect marine SQGs. Metal(loid) concentrations varied widely across three distinct temporal periods. Significantly higher Cd, Cu, Pb, Hg, and Zn concentrations were measured between 1998 and 2000, compared to earlier, 1992–1996 and more recent 2003–2015 data. Most samples, 69%, were shallow (0–15 cm), leaving deeper horizons under-characterized. Geographic information system (GIS) techniques also revealed inadequate spatial coverage, presenting challenges for remedy decisions regarding vertical and horizontal delineation of contaminants. Review of historical monitoring data revealed that gaps still exist in our understanding of sediment characteristics in Boat Harbour, including spatial, vertical and horizontal, and temporal variation of sediment contamination. To help return Boat Harbour to a tidal estuary, more detailed sampling is required to better characterize these sediments and to establish appropriate reference (background) concentrations to help develop cost-effective remediation approaches for this decades-old problem.

The effect of metals on environmental health is well documented and monitoring these and other pollutants is considered an important part of environmental management. Developing countries are yet to fully appreciate the direct impacts of pollution on aquatic ecosystems and as such, information on pollution dynamics is scant. Here, we assessed the temporal and spatial dynamics of stream sediment metal and nutrient concentrations using contaminant indices (e.g. enrichment factors, pollution load and toxic risk indices) in an arid temperate environment over the wet and dry seasons. The mean sediment nutrient, organic matter and metal concentration were highest during the dry season, with high values being observed for the urban environment. Sediment contaminant assessment scores indicated that during the wet season, the sediment quality was acceptable, but not so during the dry season. The dry season had low to moderate levels of enrichment for metals B, Cu, Cr, Fe, Mg, K and Zn. Overall, applying the sediment pollution load index highlighted poor quality river sediment along the length of the river. Toxic risk index indicated that most sites posed no toxic risk. The results of this study highlighted that river discharge plays a major role in structuring temporal differences in sediment quality. It was also evident that infrastructure degradation was likely contributing to the observed state of the river quality. The study contributes to our understanding of pollution dynamics in arid temperate landscapes where vast temporal differences in base flow characterise the riverscape. Such information is further useful for contrasting sediment pollution dynamics in aquatic environments with other climatic regions.

Chemical contaminants were assessed in Sydney Harbour, Nova Scotia during pre-remediation (baseline) and 3 years of remediation of a former coking and steel facility after nearly a century of operation and historical pollution into the Sydney Tar Ponds (STP). Concentrations of polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls, metals, and inorganic parameters measured in sediments and total suspended solids in seawater indicate that the overall spatial distribution pattern of historical contaminants remains unchanged, although at much lower concentrations than previously reported due to natural sediment recovery, despite remediation activities. Measured sediment deposition rates in bottom-moored traps during baseline were low (0.4–0.8 cm year −1 ), but during dredging operations required for construction of new port facilities in the inner Sydney Harbour, sedimentation rates were equivalent to 26–128 cm year −1 . Measurements of sediment chemical contaminants confirmed that natural recovery rates of Sydney Harbour sediments were in broad agreement with predicted concentrations, or in some cases, lower than originally predicted despite remediation activities at the STP site. Overall, most measured contaminants in sediments showed little temporal variability (4 years), except for the detection of significant increases in total PAH concentrations during the onset of remediation monitoring compared to baseline. This slight increase represents only a short-term interruption in the overall natural recovery of sediments in Sydney Harbour, which were enhanced due to the positive impacts of large-scale dredging of less contaminated outer harbor sediments which were discharged into a confined disposal area located in the inner harbor.

Increased intensity and frequency of floods raise concerns about the release and transport of contaminated soil and sediment to and from rivers and streams. To model these processes during flooding events, we developed an External Coupler in Python to link the Hydrologic Engineering Center‐River Analysis System (HEC‐RAS) 2D hydrodynamic model to the Water Quality Analysis Simulation Program (WASP). Accurate data transfer from a hydrodynamic model to a water quality model is critical. Our test results showed the External Coupler successfully linked HEC‐RAS and WASP and addressed technical challenges in aggregating flow data and conserving mass during the flood event. We ran the coupled models for a 100‐year flood event to calculate flood‐induced transport of sediment‐associated arsenic in Woodbridge Creek, NJ. Change in surface sediment and arsenic at the end of 48‐h flood simulation ranged from a net loss of 13.5 cm to a net gain of 11.6 cm, and 16.2 to 2.9 mg/kg, respectively, per model segment, which demonstrates the capability of the coupled model for simulating sediment and contaminant transport in flood.

PurposeContamination of sediments with heavy metals (HMs) is a worldwide environmental issue, due to the negative ecological effects of HMs. Sediments are an important component of aquatic ecosystems, impacting the transformation and transfer of HMs in the environment. Thus, remediating sediments polluted by HMs is a crucial activity within the full aquatic ecosystem remediation process, and economical, effective, and environmentally friendly remediation techniques are urgently needed.Materials and methodsWe reviewed the existing literature on sediment remediation techniques and developments in the fields of environmental science and engineering, attempting to provide a better understanding of the advances of remediation techniques and new research directions for sediments contaminated by HMs.Results and discussionThis review summarized remediation methods (e.g., physical–chemical strategies, biological strategies, and combined techniques) used to treat sediments contaminated with HMs. This included analyzing the mechanisms associated with biological remediation technologies and their combination with other methods. Then, the review summarized the factors influencing the selection of remediation methods and evaluated the prospects of new emerging remediation methods.ConclusionsBioimmobilization techniques (e.g., phytostabilization and microorganism immobilization) have received increased attention because of their low remediation cost and environmental compatibility. Furthermore, particular attention has been paid to explore the role of sulfate-reducing bacteria in decreasing heavy metal mobility. The review provides a useful theoretical foundation and technology reference for the remediation of sediment polluted by HMs.

The present study includes a systematic analysis of sediment contamination by heavy metals of the River Ghaghara flowing through the Uttar Pradesh and Bihar in Indian Territory. To estimate the geochemical environment of the river, seven heavy metals, namely Co, Cu, Cr, Ni, Cd, Zn, and Pb were examined from the freshly deposited river bed sediment. All the sediment samples were collected on a seasonal basis for the assessment of fluctuation in 2014–2015 and after preparation samples were analyzed using standard procedure. Result showed that heavy metal concentration ranged between 11.37 and 18.42 mg/kg for Co, 2.76 and 11.74 mg/kg for Cu, 61.25 and 87.68 mg/kg for Cr, 15.29 and 25.59 mg/kg for Ni, 0.21 and 0.28 mg/kg for Cd, 13.26 and 17.59 mg/kg for Zn, 10.71 and 14.26 mg/kg for Pb in different season. Metal contamination factor indicates the anthropogenic input in the river sediment was in the range of (0.62–0.97) for Co, (0.04–0.26) for Cu, (0.68–0.97) for Cr, (0.22–0.38) for Ni, (0.70–0.93) for Cd, (0.14–0.19) for Zn, and (0.54–0.71) for Pb. The highest contamination degree of the sediment was noticed as 4.01 at Ayodhya and lowest as 3.16 at Katerniaghat. Geo-accumulation index was noted between (0 and 1) which showed that sediment was uncontaminated to moderately contaminated and may have adverse affects on freshwater ecology of the river. Pollution load index (PLI) was found highest at Chhapra which was 0.45 and lowest at Katerniaghat which was 0.35 and it indicates that the river sediment has a low level of contamination. Significant high correlation was observed between Co, Cu, and Zn, it suggests same source of contamination input is mainly due to human settlement and agriculture activity. Positive correlation between Zn, Co, Cu, Cr, and Ni indicated a natural origin of these elements in the river sediment. Cluster analysis suggests grouping of similar polluted sites. The strong similarity between Co, Zn, Pb, Ni, Cu, and Cd showed relationship of these metals come from the same origin, which is possibly from natural and anthropogenic input which was also confirmed by correlation analysis. Using the various pollution indicators it was found that the river bed sediment is less contaminated by toxic metals during the study but the sediment quality may degrade in the near future due to increasing anthropogenic inputs in the river basin, hence proper management strategies are required to control the direct dumping of wastewater in the river.