Assessment Of Sediment Contamination Research Articles

Accumulation Patterns of Polychlorinated Dibenzo-p-Dioxins, Dibenzofurans and Dioxin-like Polychlorinated Biphenyls in Sediments of the South-Eastern Baltic Sea

The current research paper presents the results of the first regional assessment of sediment contamination by dioxins (polychlorinated dibenzo-p-dioxins (PCDDs), dibenzofurans (PCDFs) and dioxin-like polychlorinated biphenyls (dl-PCBs)) in the south-eastern part of the Baltic Sea (Lithuanian and Polish marine areas) during the periods of 2014 and 2019–2020. In total, 143 surface and core sediment samples were taken of existing offshore dredged-soil-disposal sites in the area of the former shipyard in the Port of Gdynia (Poland), as well as in a profile from the nearshore to the deeps of the Gdansk basin, following the natural pattern of sediment migration in the region. The obtained results indicated wide variation in both the total content of the investigated compounds as well as the profiles of congeners, indicating the likely sources of their origin. Based on the obtained concentration characteristic profiles of the congeners, we determined the amount of dioxins and the likely sources of their origin in the Gdansk Basin. The profiles showed elevated contents of octa- and hepta-chlorodibenzodioxins (OCDD and HpCDD) in the sediments, while the fractions of most other toxic congeners were considerably lower. The domination of OCDF in the spectrum of the studied PCDFs suggests the possible contribution of industrial processes. The obtained results have filled the gaps in our knowledge while providing a perfect background for more detailed discussions concerning the accumulation of dioxins in surface sediments from the south-eastern part of the Baltic Sea.

Historical construction, quantitative source identification and risk assessment of heavy metals contamination in sediments from the Pearl River Estuary, South China

Historical reconstruction of heavy metals (HMs) contamination in sediments is a key for understanding the effects of anthropogenic stresses on water bodies and predicting the variation trends of environmental state. In this work, eighteen sediment cores from the Pearl River Estuary (PRE) were collected to determine concentrations and geochemical fractions of HMs. Then, their potential sources and the relative contributions during different time periods were quantitatively identified by integrating lead-210 (210Pb) radioisotope dating technique into positive matrix factorisation (PMF) method. Pollution levels and potential ecological risks (PERs) caused by HMs were accurately assessed by enrichment factors (EF) based on establishment of their geochemical baselines (GCBs) and multiparameter evaluation index (MPE). HMs concentrations generally showed a particle size- and organic matter-dependent distribution pattern. During the period of 1958–1978, HMs concentrations remained at low levels with agricultural activities and natural processes being identified as the predominant sources and averagely contributing >60%. Since the reform and opening-up in 1978, industrial and traffic factors become the primary anthropogenic sources of HMs (such as Cu, Zn, Cd, Pb, Cr, and Ni), averagely increasing from 22.1% to 28.1% and from 11.6% to 23.4%, respectively. Conversely, the contributions of agricultural and natural factors decreased from 37.0% to 28.5% and from 29.3% to 20.0%, respectively. Subsequently, implementation of environmental preservation policies was mainly responsible for the declining trend of HMs after 2010. Little enrichment of sediment Cu, Zn, Pb, Cr and Ni with EFs (0.15–1.43) was found in the PRE, whereas EFs of Cd (1.16–2.70) demonstrated a slight to moderate enrichment. MPE indices of Cu (50.7–252), Pb (52.0–147), Zn (35.5–130), Ni (19.6–71.5), Cr (14.2–68.8) and Cd (0–9.90) highlighted their potential ecological hazards due to their non-residual fractions and anthropogenic sources.

Assessment of Selenium Contamination in Sediments of the Aby and Tendo Lagoons in Côte d’Ivoire

Assessment of Selenium Contamination in Sediments of the Aby and Tendo Lagoons in Côte d’Ivoire

Assessment of sediments contamination by potential toxic elements, in relationships with the physicochemical characteristics of Moroccan Oued Fez river

The Oued Fez river has long been significantly impacted by various sources of pollution, including industrial activities. However, there is limited available data concerning the presence of potentially harmful toxic elements that could affect human health in this area. The primary aim of this study was to evaluate the spatial and temporal distribution of nine Potential Toxic Elements (PTEs) Aluminum (Al), Cadmium (Cd), Chromium (Cr), Copper (Cu), Iron (Fe), Lead (Pb), Nickel (Ni), Arsenic (As), and Zinc (Zn) in the sediment of the Oued Fez river. In both February and August, we collected four sediment samples at six different locations along the Oued Fez. To ensure sample consistency at each station, we mixed the sediment samples, dried them, and finely ground them into a powder. We then used acid etching to dissolve the samples, and the concentrations of these PTEs were determined using the ICP-AES method. The findings revealed that heavy metal concentrations were higher in February compared to August, with a gradual increase observed from upstream to downstream areas of the river. Specifically, in February, site six (S6) exhibited the highest values for Fe at 27,749.6 mg.kg−1 and Al at 13,967.2 mg.kg−1. Additionally, the PCA analysis and assessment of sediment contamination indicated that the sediment was more contaminated with Fe, Al, and Zn, especially at upstream stations (S5 and S6). This contamination can be attributed to their proximity to the industrial area. These results clearly demonstrate that anthropogenic factors, particularly industrial activities, are contributing to increased sediment contamination by PTEs. This contamination not only jeopardizes the environmental integrity of this site but also poses a significant threat to human health.

Integrated assessment of trace elements contamination in sediments of a typical aquaculture bay in China: Ecological toxicity, sources and spatiotemporal variation

Trace elements contamination in estuarine and bay ecosystems has become a serious problem, especially in bays with frequent aquaculture activities. To explore the pollution risk, sources and trends of pollution trace elements in Dongshan Bay, a typical aquaculture bay in China, the concentration and spatial distribution of seven trace elements in surface sediments were investigated. In this study, Zn was the element with the highest content in surface sediments, followed by Pb and Cr, while Cd was the lowest, but the average concentrations of Cd and Hg exceeded the regional background values. High levels of trace elements were distributed in estuaries and aquaculture areas, which were illustrated also by the SOM model. An evaluation of the pollution load index (PLI), geo-accumulation index (Igeo) and potential ecological risk index (PERI) demonstrated that Cd and Hg were the principal pollution elements and ecological risk factors in the surface sediments of the Bay. A positive matrix factorization model (PMF) revealed that the main sources of trace elements were natural sources, petrochemical industry and fossil fuel combination emissions, use of agricultural fertilizer, and industrial and agricultural sewage discharge. Comparative analysis found that since 2008, the mean content of Cu, Pb, Zn, and As have decreased significantly, while the content of Cd, Hg, and Cr have increased significantly. This information will help marine management efforts in taking effective measures to prevent environmental risks caused by trace elements pollution, especially related to aquaculture.

Phthalates contamination in the coastal and marine sediments of Rio de Janeiro, Brazil

Coastal and marine environments have been strongly influenced by anthropogenic activities, which may lead to high concentrations of different pollutants in sediments. Our study aimed to assess sediment contamination by polycyclic aromatic hydrocarbons (PAHs), phthalates (PAEs) and bisphenol A (BPA) in nine coastal and marine environments at Rio de Janeiro-Brazil. Physical and chemical water variables, grain-size parameters, moisture, and organic-matter content in sediments were assessed by sampling station. Multivariate analysis evidenced environmental differences between coastal lagoon and oceanic beaches, mostly influenced by marine waters. Differences among bay's beaches were mostly evidenced by sediment characteristics. PAHs and BPA were not detected in samples. For the first time, PAEs were found in sediments at Rio de Janeiro coast (South Atlantic). DEHP was detected in all coastal and marine environments, DBP was found in coastal lagoon and three marine environments. DnOP and DINP were solely found in the coastal lagoon.

Pollution status and ecological risk assessment of metal(loid)s in the sediments of the world's largest mangrove forest: A data synthesis in the Sundarbans

The Sundarbans is the largest single-mass mangrove forest in the world, experiencing environmental and anthropogenic stress from metal(loid) inputs. We undertook a comprehensive assessment of sediment contamination and ecological risks posed by metal(loid)s in the Sundarbans using previously published data. There was a distinct difference in metal(loid) content, pollution level and ecological risk in Bangladeshi and Indian parts of the Sundarbans, with the Indian counterpart experiencing relatively higher metal(loid) pollution. The higher pollution level in India might be attributed to its vicinity to municipal and industrial areas that act the primary source of metal(loid)s in the Sundarbans. The cumulative ecological risks of metal(loid)s pointed out that the south-eastern part of Bangladeshi Sundarbans and north-eastern Indian part are at moderate ecological risk. This research will provide valuable data to inform the responsible authorities and will underpin future policies and management to reduce future metal(loid) inputs in the Sundarbans.

Assessment of heavy metals pollution in the sediments of Haditha reservior and Eupheates River, within Anbar Governorate/Iraq

10 sediment samples were obtained from Haditha reservoir and Anah city in Al-Anbar governorate for this study during (October, 2021). to assess sediment contamination in trace metals like (Cd, Fe, Pb, Zn, Cu, and Ni), from applying geochemical contamination coefficients such as Geo - Accumulation variable I-Geo, Contamination Factor CF, as well as Pollution loud Index PLI. The research area is found in the northwestern region of Al-Anbar governorate, between the longitudes (42º23'.13'' - 42º01'.10'' E). and latitudes (34º10'.22'' - 34º22'.7'' N), The area which is located between Haditha Dam and Anah city. The results of geochemical analyzes showed that it soil sediment has a high value of the elements (Ni, Fe and Cd), which exceeds the limits of local studies, this can be affected by Anthropogenic activities like urbanization, industrialization, agricultural runoff, fertilizers, and also the Haditha dam's electrical station, but the elements (Zn, Pb and Cu), Within the permissible limits of local studies.The results of the I-geo shows that the elements (Ni, Zn, Pb, Fe and Cu), has unpolluted (class- 0). While Cd is (class- 1), slightly polluted.

Heavy Metals in River Sediments: Contamination, Toxicity, and Source Identification-A Case Study from Poland.

This study investigated the spatial distribution, contamination, potential ecological risks and quantities of pollutant sources of six heavy metals (HMs) in sediments of 47 rivers. The catchments of the investigated rivers are situated in Poland, but some of them are located in Slovakia, the Czech Republic, and Germany. Cluster analysis was applied to analyze the spatial distribution of Cd, Cr, Cu, Ni, Pb, and Zn in river sediments. Moran I and Getis-Ord statistics were calculated to reveal the distribution pattern and hotspot values. Principal component analysis (PCA) and positive matrix factorization (PMF) were used to identify pollution sources. Furthermore, geochemical indices and sediment quality guidelines allowed us to assess sediment contamination and potential toxic effects on aquatic biota. The results showed that in 1/3rd of the rivers, the HM pattern and concentrations indicate sediment contamination. The EF, PLI, and MPI indices indicate that concentrations were at a rather low level in 2/3rd of the analyzed rivers. Only in individual rivers may the HMs have toxic effects on aquatic biota. Spatial autocorrelation analysis using the Moran I statistic revealed a random and dispersed pattern of HMs in river sediments. PCA analysis identified two sources of HMs’ delivery to the aquatic environment. Cr, Cu, Ni, Pb, and Zn originate from point and non-point sources, while Cd concentrations have a dominant natural origin. The PMF identified three sources of pollution. Among them, urban pollution sources are responsible for Cu delivery, agricultural pollution for Zn, and industrial pollution for Ni and Cr. Moreover, the analysis showed no relationship between catchment land-use patterns and HM content in river sediments.

Spatio-temporal variation and assessment of trace metal contamination in sediments along the Lom River in the gold mining site of Gankombol (Adamawa Cameroon)

Spatio-temporal variation and assessment of trace metal contamination in sediments along the Lom River in the gold mining site of Gankombol (Adamawa Cameroon)

Genotoxicity Set Up in Artemia franciscana Nauplii and Adults Exposed to Phenanthrene, Naphthalene, Fluoranthene, and Benzo(k)fluoranthene

Polycyclic aromatic hydrocarbons (PAHs) consist of a group of over 100 different organic compounds mainly generated by anthropogenic activities. Because of their low water solubility, they tend to be accumulated in sediment, where their degradation rate is very low. Few studies have been carried out so far to investigate the effects of PAHs on Artemia franciscana. Artemia is easy to manage at laboratory scale, but it is not a sensitive biological model considering the traditional endpoints (i.e., mortality). In addition to evaluating the lethality on nauplii and adults of A. franciscana after 24 and 48 h, we focused on the genotoxicity to investigate the potential effects of phenanthrene (PHE), naphthalene (NAP), fluoranthene (FLT), and benzo(k)fluoranthene (BkF). Results showed that FLT was the most toxic both for nauplii and adults after 48 h of exposure. Real-time qPCR showed that all toxicants, including BkF, which had no negative effects on the survival of the crustacean, were able to switch the gene expression of all nine genes. This work has important ecological implications, especially on contaminated sediment assessment considering that PAHs represent the most abundant organic group of compounds in marine environment, opening new perspectives in understanding the molecular pathways activated by crustaceans.

Human-induced arsenic pollution modeling in surface waters - An integrated approach using machine learning algorithms and environmental factors

In recent years, assessment of sediment contamination by heavy metals, i.e., arsenic, has attracted the interest of scientists worldwide. The present study provides a new methodology to better understand the factors influencing surface water vulnerability to arsenic pollution by two advanced machine learning algorithms including boosted regression trees (BRT) and random forest (RF). Based on the sediment quality guidelines (Effects range low) polluted and non-polluted arsenic sediment samples were defined with concentrations >8 ppm and <8 ppm, respectively. Different conditioning factors such as topographical, lithology, erosion, hydrological, and anthropogenic factors were acquired to model surface waters' vulnerability to arsenic. We trained and validated the models using 70 and 30% of both polluted and non-polluted samples, respectively, and generated surface vulnerability maps. To verify the maps to arsenic pollution, the receiver operating characteristics (ROC) curve was implemented. The results approved the acceptable performance of the RF and BRT algorithms with an area under ROC values of 85% and 75.6%, respectively. Further, the findings showed higher importance of precipitation, slope aspect, distance from residential areas, and slope length in arsenic pollution in the modeling process. Erosion, lithology, and land use maps were introduced as the least important factors. The introduced methodology can be used to define the most vulnerable areas to arsenic pollution in advance and implement proper remediation actions to reduce the damages.

Assessment of metal contamination in sediments of a perennial river in India using pollution indices and multivariate statistics

Assessment of metal contamination in sediments of a perennial river in India using pollution indices and multivariate statistics

Trace metals in surface sediments from the Laptev and East Siberian Seas: Levels, enrichment, contamination assessment, and sources

Trace metals in Laptev and East Siberian Sea sediments were analyzed to examine the element distribution pattern and to assess sediment contamination using contamination indices. The maximum Cr, Zn, Ni, Cu, and As concentrations occurred in the deeper parts of the East Siberian and Laptev Seas and the estuarine shelves of the Lena and Yana Rivers, and a high Cd content was observed in the sediment of the eastern part of the East Siberian Sea. The increased Cd concentration could be a result of the large number of phytoplankton supplied by the highly productive waters of the Bering Sea and the sorption capacity of Cd precipitation on Fe and Mn oxyhydroxides in seawater. The mean enrichment factors and geoaccumulation index values for Cr, Ni, Cu, Zn, Pb, and Cd showed no contamination by these metals at any sampling locations; however, slight As enrichment was found, possibly originating from natural sources.

Assessment of metal contamination in sediments induced by small ships around lighters wharf in Southwest Korea

Assessment of metal contamination in sediments induced by small ships around lighters wharf in Southwest Korea

Distribution and assessment of cadmium contamination in sediments from the Four River inlets to Dongting Lake, China.

The total concentrations of Cd in bulk sediments and those of the BCR sequential extraction fractions of sediments from inlets of the Four Rivers that feed Dongting Lake were determined using ICP-MS techniques. The results suggested that Cd was heterogeneously distributed in the inlet sediments of the rivers, with the highest degree of enrichment in sediments from the Xiangjiang River. The Cd anomaly was defined as Cd enrichment in sediments with an EF (enrichment factor) > 10.0, and it was identified in the inlet sediments of the Xiangjiang River. Cd in the sediments was dominated by acid-soluble Cd at a proportion of 23.9-69.8 (%) compared to its total concentrations in the sediments. The inlet sediments of the Four Rivers were contaminated with Cd, with the highest degree of contamination in the inlet sediments of the Xiangjiang River. The Cd contamination as well as the Cd anomaly in the sediments were closely related to the industrial activities (e.g. smelting and refining for ore minerals) in the areas, and Cd contamination at high levels may represent an ecological risk for the lake watershed. Cd contamination of the inlet sediments may also impact the lake basin sediments and is harmful to the lake ecological system, particularly for sediments of the Xiangjiang River. Therefore, it is essential to control and treat Cd contamination in the inlet sediments for ecological environmental protection of lake watersheds.

Stochastic Framework for Addressing Chemical Partitioning and Bioavailability in Contaminated Sediment Assessment and Management.

Passive sampling to quantify net partitioning of hydrophobic organic contaminants between the porewater and solid phase has advanced risk management for contaminated sediments. Direct porewater (Cfree) measures represent the best way to predict adverse effects to biota. However, when the need arises to convert between solid-phase concentration (Ctotal) and Cfree, a wide variation in observed sediment-porewater partition coefficients (KTOC) is observed due to intractable complexities in binding phases. We propose a stochastic framework in which a given Ctotal is mapped to an estimated range of Cfree through variability in passive sampling-derived KTOC relationships. This mapping can be used to pair estimated Cfree with biological effects data or inversely to translate a measured or assumed Cfree to an estimated Ctotal. We apply the framework to both an effects threshold for polycyclic aromatic hydrocarbon (PAH) toxicity and an aggregate adverse impact on an assemblage of species. The stochastic framework is based on a "bioavailability ratio" (BR), which reflects the extent to which potency-weighted, aggregate PAH partitioning to the solid-phase is greater than that predicted by default, KOW-based KTOC values. Along a continuum of Ctotal, we use the BR to derive an estimate for the probability that Cfree will exceed a threshold. By explicitly describing the variability of KTOC and BR, estimates of risk posed by sediment-associated contaminants can be more transparent and nuanced.

Assessment of Heavy Metal Contamination in Sediments of the Shitalakhya River, Bangladesh

Sediment samples collected from the river Shitalakhya, Bangladesh, were analyzed using atomic absorption spectroscopy (AAS) to investigate site-to-site (spatial) and seasonal (i.e., dry, premonsoon, post-monsoon) variation of Cr, Mn, Ni, Cu and Zn. The mean concentrations of Cr, Mn, Ni, Cu and Zn were 22.37 ± 6.09, 612.59 ± 160.08, 54.11 ± 11.21, 50.36 ± 9.40 and 103.62 ± 62.74 mg/kg in the dry, 31.58 ± 5.22, 569.71 ± 112.16, 58.35 ± 7.82, 49.93 ± 17.36 and 110.88 ± 95.83 mg/kg in the pre-monsoon and 18.09± 6.32, 567.02 ± 115.55, 50.89 ± 6.58, 39.75 ± 4.56 and 55.22 ± 11.33 mg/kg in the post-monsoon, respectively. Based on the metals’ concentrations, no considerable difference was observed among the three seasons, but the concentrations were slightly elevated in the dry and pre-monsoon compared to that in the post-monsoon with respect to site-to-site variation. Among the metals examined, concentrations of Ni and Cu were elevated because of the use of oxides of these heavy metals as catalysts in the ammonia plant. The following statistical indices i.e., Pearson correlation matrix, geo-accumulation index (Igeo), contamination factor (Cf), degree of contamination (Cd), pollution load index (PLI) and ecological risk potential (RI) factors were taken into account to assess the heavy metals contamination of the sediments. According to the values of the statistical indices for Cr, Mn, Ni, Cu and Zn, it is concluded that the study area was with low contamination while concentrations of Ni and Cu were higher than the Threshold Effect Level (TEL) and Toxicity Reference Value (TRV) values suggesting unsafe to use the sediments for vegetation and other uses.

Distribution and Assessment of Trace Elements Contamination in Sediments of Conceição River Basin, Brazil

The Conceição river basin, in Quadrilátero Ferrífero (Iron Quadrangle), Brazil, has a long mining history which dates back to the late 17th century, with large gold and iron mines. These activities may be associated with river sediment contamination by trace elements, which were evaluated in this paper by the enrichment factor (EF) and contamination factor (CF). Potential ecological risks, assessed by combining sediment quality control guidelines (SQCG) and potential ecological risk indexes (Er and RI), are presented. Anomalous values for As (92.5 mg·kg−1), Cd (22.49 mg·kg−1), Cr (2582 mg·kg−1), Cu (65.9 mg·kg−1), Pb (58.6 mg·kg−1) and Zn (133.4 mg·kg−1) are observed. The EF and CF indexes indicate contamination by Cd, Cr, Fe, Mn, Ni and Zn in at least one site, with the highest values for Fe and Mn downstream of the iron mines, and Cr and Ni close to the gold mines. According to the SQGC and Er, As, Cd, Cr, and Ni are the most probable to result in adverse effects on sediment-dwelling organisms in this study. The results of principal component analysis (PCA) indicate distinct lithological units as sources of the analyzed elements, which, associated with the indexes, made it possible for the first time to delimit and classify the high concentrations of some analyzed elements as contamination in the Conceição river basin.

Health risk assessment of heavy metals contamination in sediments of the River Nile, Damietta Branch using Mathematical Models

This study was conducted to evaluate heavy metals pollution in sediments of the Nile River- Damietta Branch using mathematical models of heavy metal indices (enrichment factor (EF), contamination factor (CF), pollution load index (PLI), degree of contamination (DC) and geo-accumulation index (Igeo)). The results showed that the concentrations of heavy metals in sediment samples, followed the order of Fe> Zn> Pb> Co> Ni> Cu> Mg. The EF for each heavy metal element was calculated relative to the background values after normalization with the Fe element. According to the mean values of EFs, the descending order of heavy metals enrichment in the sediments was: Cd >Fe> Pb > Co > Zn > Ni > Cu (greater to lower). Cd was considered to poses significant to very high enrichment along with the different stations along the study area. In addition, it recorded very high contamination (7.41±0.71) and Igeo mean value (6.50 ± 1.32) along the study area. PLI values varied between 0.813 and 2.331 along the study area with a mean value of 1.338 ± 0.477. This result showed a considerable degree of contamination (mean value =16.442 ± 7.136) along the branch. However, stations 3, 5, 9 and 10 recorded a very high degree of contamination with values (30.901, 33.867, 56.932 and 48.536), respectively. HI values of heavy metal order was: Cd (239.63) > Pb (72.65) > Co (34.732) > Ni (14.457) > Zn (5.952) > Cu (4.719) > Fe (2.896). With respect to human health, Ni, Pb, Cd, Fe, Zn, Cu, and Co were identified as potential contaminants. whereas, Pb, Cd and Cu are classified as non-carcinogenic by Agency for Toxic Substances and Disease Registry.