Sequential extraction and risk assessment of pollutants from one major tributary of the Ganga

The geochemical fractionation of toxic heavy metals Cd, Pb, Cr, Co, Mn, Ni, Cu, Fe and Zn was investigated in 10 different sites of river bed sediments (up, mid and downstream) of Gomti River at Lucknow city. Sequential extraction technique was used to identify the distribution of trace elements binding in different fractions i.e., exchangeable, carbonate, Fe and Mn oxide, organic matter and residual. Heavy metal concentrations were least at upstream and significantly higher in mid and downstream. Fractionation indicated that dominant metals were bound in residual fraction to the bed sediments except for Cd and Pb which were bound in an equivalent fraction. Geo-accumulation index factor reveals that the enrichment of heavy metals in the bio-available fraction is contributed anthropogenically. Hierarchical cluster analysis also shows the metal pollution load in the river. Risk assessment code of Cd and Ni showed very high risk (ranged from 54.41 to 85.56 and 20.57 to 44.92 respectively) followed by Pb (high risk), Zn, Co (medium risk), Cr, Mn, Cu, Fe (low risk) in Gomti River water. Further, concentrations of Cd and Pb at mid Lucknow were 31 and 75%, high enough to pose a substantial risk to the environment.

Controls on the Spatial Distribution of Trace Metal Concentrations along the Bedrock-Dominated South Fork New River, North Carolina

In marked contrast to alluvial rivers, few studies have examined the physical and geochemical controls on the spatial distribution of toxic trace metals along bedrock channels. This study examined the factors controlling the geographical pattern of selected trace metal (Cu, Cr, and Zn) concentrations along the bedrock-dominated channel of the South Fork New River (SFNR). The SFNR is located in the Blue Ridge Physiographic Province of North Carolina, and is representative of many rivers in mountainous terrains that are often subjected to the influx of toxic trace metals from historic and contemporary mining operations. The topography of the SFNR’s channel bed is highly variable and can be subdivided into pool and shallow bedrock reaches. The latter contained localized cascades characterized by topographically higher bedrock ribs that are separated by topographic lows, both of which are oriented oblique to flow. Accumulations of bed sediments are predominantly associated with the traverse bedrock ribs that generate high hydraulic roughness. Except for a few localized zones of enrichment, sediment-associated trace metal concentrations tended to vary within a narrow range of background values over the 36 km study reach. Elevated trace metal concentrations were closely linked to zones of high Fe and Mn concentrations, and were associated with pools located within or immediately downstream of bedrock cascades. The elevated concentrations of the metals appear to be derived from the erosion of lithologic units within the cascades that contain sulfidic layers or zones of mafic mineral enrichment, and which are known to occur in the underlying bedrock. Once eroded, these minerals and/or rock fragments were deposited within low-velocity zones created by the transverse ribs or within downstream pools. The enrichment of trace metals downstream of the cascades may also be due to the formation of Fe and Mn oxyhydroxides as turbulent flows aerate river waters as they traverse the cascades. Chemically reactive fine-grained (<63 µm) sediments had a relatively limited influence on the downstream variations in metal concentrations, presumably because the channel bed sediments are composed primarily of sand-sized and larger particles. Although a principal component analysis (PCA) suggested that reach-scale variations in channel and valley morphology may have partly influenced downstream variations in trace metal concentrations, the geographical patterns were primarily controlled by local geological and geomorphic factors associated with the bedrock cascades. The design of future sampling programs along such coarse-grained, bedrock rivers should consider the significance of these local controls on trace metal storage to effectively characterize and interpret downstream patterns in metal concentrations.

Bedform segregation and locking increase storage of natural and synthetic particles in rivers

While the ecological significance of hyporheic exchange and fine particle transport in rivers is well established, these processes are generally considered irrelevant to riverbed morphodynamics. We show that coupling between hyporheic exchange, suspended sediment deposition, and sand bedform motion strongly modulates morphodynamics and sorts bed sediments. Hyporheic exchange focuses fine-particle deposition within and below mobile bedforms, which suppresses bed mobility. However, deposited fines are also remobilized by bedform motion, providing a mechanism for segregating coarse and fine particles in the bed. Surprisingly, two distinct end states emerge from the competing interplay of bed stabilization and remobilization: a locked state in which fine particle deposition completely stabilizes the bed, and a dynamic equilibrium in which frequent remobilization sorts the bed and restores mobility. These findings demonstrate the significance of hyporheic exchange to riverbed morphodynamics and clarify how dynamic interactions between coarse and fine particles produce sedimentary patterns commonly found in rivers.

Toxicity and Risks Assessment of Polycyclic Aromatic Hydrocarbons in River Bed Sediments of an Artisanal Crude Oil Refining Area in the Niger Delta, Nigeria

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous environmental pollutants that possess serious risks to human health and the environment. Forty riverbed sediments samples were collected in mangrove river bed sediments where artisanal refining of crude oil takes place in the Niger Delta of Nigeria. The concentration, occurrence, distribution, toxicity and health risk of sixteen priority PAHs (16PAHs) were analysed in the samples. Apart from Nap, Acy, BkF, InP and DbE, all the other PAHs were present in all the sampled points of the studied area with BbF and BaA recording the highest mean values. The range and mean of the total PAHs (∑16PAHs) of this study are 23.461–89.886 mg/kg and 42.607 ± 14.30 mg/kg dry weight (dw), which is classified as heavily contaminated when compared to the European classification of PAHs pollution in soil (>1.0 mg/kg). The range of the effect range factors used to assess the risk of PAHs in an ecosystem (Effect rang-low (ER-L) and Effect range-median ER-M) of this study is from 0.953 to 8.80 mg/kg. PAHs below ER-L (4.0 mg/kg) indicate no toxic effect, but values above ER-M (44.79 mg/kg) indicate toxic effects to the sediments, its resources and, ultimately, the public that consumes the resources thereof; hence, the study area falls within the contaminated category. The occurrence of the high molecular weight (HMW) PAHs (73.4%) supersedes those of the lower molecular weight (LMW) PAHs (26.6%). The diagnostic ratios and principal component analysis suggest that the main contributors of PAHS into the sediments are the combustion of biomass, fossil fuel (crude oil) and pyrogenic sources. The toxic equivalent quotient (TEQ) and mutagenic equivalent quotient (MEQ) of PAHs ranged from 2.96 to 23.26 mgTEQ/kg dw and 4.47 to 23.52 mgMEQ/kg dw, and the total mean toxic equivalency quotient (∑TEQ) (15.12 ± 8.4 mg/kg) is also greater than the safe level of 0.6 mg/kg, which indicates high toxicity potency. The mean incremental lifetime cancer risks (ILCRs) of human exposure to PAHs shows that both adults TotalILCR adults (6.15 × 10−5) and children TotalILCR children (2.48 × 10−4) can be affected by dermal contact rather than ingestion and inhalation. Based on these findings, the appropriate regulatory bodies and other organs of government in the region should enforce outright stoppage of the activities of these illegal artisans who do not have control mechanisms for loss control at the site and carry out appropriate clean-up of the area.

Effect of cadmium sorption by river sediments on longitudinal dispersion

This paper concerns the cadmium sorptive effects by river bed sediments on longitudinal dispersion coefficient in an open-channel flow via experimental and numerical study. For this purpose, a circular flume was used with mean diameter of 1.6 m and a width of 0.2 m. The adsorbing bed was considered as a thin layer of the sediment particles with mean diameter of 0.53 mm and three sediment concentrations of 3, 12, and 20 gr/lit. To determine the sorption parameters of the sediments, some experiments were conducted with three cadmium concentrations of 150, 460, and 770 ppb. Then, the dispersion experiments were carried out with and without the bed sediments with the same cadmium concentration as the sorption experiments. A numerical model was then developed to solve the advection-dispersion equation with considering the sorption term by river bed sediments. The longitudinal dispersion coefficients were estimated by comparing the experimental and numerical breakthrough curves. The results showed that, with increasing the sediment concentrations, the sediment sorption rate increased and the longitudinal dispersion coefficient decreased by about 38, 36 and 33 percent, respectively, for cadmium concentrations of 150, 460 and 770 ppb. In addition, by increasing the cadmium concentrations, the changes in the longitudinal dispersion coefficient are decreased. Furthermore, a relationship was developed using non-dimensional longitudinal dispersion as a function of the new parameter of sorption ratio. From a practical point of view, the results of this study demonstrated that, at the presence of riverbed sediment, the cadmium is longitudinally dispersed with more delay in comparison with no sediment at the river bed.

Determination of Heavy Metals in Surface Water, Sediments and Planktons at the Junction of Multiple Rivers (Punjnad Headworks) and Their Impact on Human Health

This study was conducted to calculate the burden of heavy metals i.e., aluminium (Al), arsenic (As), barium (Ba) and lead (Pb) in the river water of Punjnad Headworks, Bahawalpur, Pakistan. For this purpose, samples were collected from surface water, bed sediments and planktons during autumn, winter and spring seasons (September 2018 to May 2019). The results showed that in surface water Pb concentration was highest (453.87 mg L-1), while in sediments and plankton, Al concentration was highest (370.24 µg g-1 and 315.05 µg g-1, respectively). A significant difference (p < 0.000) in metal concentrations was found among surface water, bed sediments and plankton at different sampling stations during various seasons. However, findings of this study showed no adverse effects of heavy metal concentrations on human health. This study provided better understanding of various pollutants and their concentrations in water sources at the studied location.

Mapping riverbed sediment size from Sentinel 2 satellite data

A comprehensive understanding of river dynamics requires quantitative knowledge of the grain size distribution of bed sediments and its variation across different temporal and spatial scales. Several techniques are already available for grain size assessment based on field and remotely sensed data. However, the existing methods are only applicable on small spatial scales and on short time scales. Thus, the operational measurement of grain size distribution of river bed sediments at the catchment scale remains an open problem. A solution could be the use of satellite images as the main imaging platform. However, this would entail retrieving information at sub-pixel scales. In this study, we propose a new approach to retrieve sub-pixel scale grain size class information from Copernicus Sentinel-2 imagery building upon a new image-based grain size mapping procedure. Three Italian gravel-bed rivers featuring different morphologies were selected for Unmanned Aerial Vehicle (UAV) acquisitions coupled to field surveys and lab analysis meant to serve as ground truth grain size data. Grain size maps on river bars were generated in each study site by exploiting image texture measurements, upscaled and co-registered with Sentinel-2 data resolution. Relationships between the grain sizes measured and the reflectance values in Sentinel-2 imagery were analyzed by using a machine learning framework. Results show statistically significant predictive models (MAE of ±8.34 mm and R2=0.92). The trained model was applied on 300 km of the Po river in Italy and allows to detect grain size longitudinal variation and to identify the gravel-sand transition occurring along this river length.Our proposed approach based on freely available satellite data calibrated by low-cost automated drone technology can provide reasonably accurate estimates of surface grain size classes, in the range of sand to gravel, for bar sediments in medium to large river channels, over lengths of hundreds of kilometers.