Cloud Point Extraction for the Preconcentration of Silver and Palladium in Real Samples and Determination by Atomic Absorption Spectrometry

A cloud point extraction procedure is presented for the preconcentration and simultaneous determination of Ag⁺ and Pd²⁺ in various samples. After complexation with 2‐((2‐((1H‐benzo[d]imidazole‐2‐yl)methoxy)phenoxy)methyl)‐1H‐benzo[d]imidazol (BIMPI), which was used as a new chelating agent, analyte ions were quantitatively extracted to a phase rich in Triton X‐114 following centrifugation, and determination was carried out by flame atomic absorption spectrometry (FAAS). Under the optimum experimental conditions (i. e., pH = 7.0, 15.0·10^–5 mol/L BIMPI and 0.036% (w/v) Triton X‐114), calibration graphs were linear in the range of 28.0–430.0 μg/L and 57.0–720.0 μg/L with detection limits of 10.0 and 25.0 μg/L for Ag⁺ and Pd²⁺, respectively. The enrichment factors were 35.0 and 28.0 for Ag⁺ and Pd²⁺, respectively. The method has been successfully applied to evaluate these metals in some real samples, including waste water, soil and hydrogenation catalyst samples.     

Sedimentological and geoenvironmental evaluation of the coastal area between Al-Khowkhah and Al-Mokha,southeastern Red Sea,Republic of Yemen

The increasing anthropogenic activities (e.g., constructing touristic resorts) have led to notable changes in the Yemeni Red Sea coastal regions. In this context, recent sediments have been investigated to infer possible natural and man-induced processes on these coastal areas. The target area lies between longitudes 43°13′–43°30′E and latitudes 13°15′–13°55′N. It extends about 90 km along the coastline as a part of the Tihama plain. Geomorphologically, it forms a long-curved stretch with pronounced headlands, embayments and bays. Generally, it is covered by recent sediments (wadi, lagoon, beach and spit deposits along with sabkha, coastal dunes and mangrove). Textural studies reveal that most of the studied sediments are mainly poorly to moderately sorted and are composed mainly of sandy fractions with few gravel and mud, mostly bimodal with minor unimodal patterns. The igneous (granites) as well as basic (basalt, andesite and andesitic pyroclastics) and acidic (dacite and rhyolite) volcanic rocks of Tertiary age, which are exposed to the east of the study area, are believed to be the source of pyroxenes, amphiboles, epidotes, biotite, sphene, zircon, tourmaline and rutile, in a decreasing order of abundance. Moreover, smectite, kaolinite, chlorite, illite and palygorskite are the predominant clay minerals, mainly of detrital origin. The total carbonate content fluctuates from 37.41% (lagoon sediments) to 53.74% (sabkha sediments). The high amount of sea grasses, which covers the tidal flat zone and relates to the fine-grained sediments, accounts for the high organic matter content. The mineralogy of the source rocks has controlled the general distribution of major elements (Fe, Mg, Na, K and Mn) in the beach sediments. In such sediments, the concentrations of the heavy metals (Cu, Zn, Cd, Ni, Pb and Co) may reflect the sediment pollution using different approaches. The enrichment factors (EFs) of the trace metals for most samples reveal values that are greater than 1, referring to three groupings, which are: moderate to moderately severe (Zn, Cu and Mn), minor to moderate (Pb and Co) and zero to minor (Cd and Ni) enrichment. The EFs for Pb, Cd, Ni and Co metals (<5) may be attributed to the crustal materials and/or natural weathering processes. But, those for Zn, Cu and Mn (>5), especially in Al-Khowkhah–Abu-Zahr, Moushij–Zahari–Ruays, Yokhtol and Mokha localities, are possible of anthropogenic contributions.     

Spectroscopic-based assessment of the content and geochemical behaviour of arsenic in a highly heterogeneous sulphide-rich mine waste dump

Soil pollution by arsenic is a serious environmental problem in many mining areas. Quick identification of the amount and extent of the pollution is an important basis for developing appropriate remediation strategies. In a case study, 55 soil samples were collected from a highly heterogeneous waste dump around the Sarcheshmeh copper mine, south east Iran. Samples’ visible and near-infrared (VNIR) reflectance spectra were measured, transformed to absorbance and then pre-processed using Savitzky–Golay first-derivative (FD) and Savitzky–Golay second-derivative (SD) transformation methods. The obtained spectra were then subjected to three regression models including principal component regression (PCR), partial least squares regression (PLSR) and support vector regression (SVR) for predicting arsenic concentration. The best prediction accuracies were obtained by SVR and PLSR methods applied on first-derivative pre-processed spectra with R ² values of 0.81 and 0.69, respectively. It was found that VNIR spectroscopy is a successful method for predicting As concentration in contaminated soils of the dumpsites. Study of the prediction mechanism showed that the intercorrelation between arsenic and spectral features of soil including iron oxy/hydroxides and clay minerals was the major mechanism enabling the prediction of arsenic concentration. However, higher values of correlation coefficients at ~460, ~560 and ~590 nm suggested the internal association between arsenic and iron minerals as the more important mechanism for prediction. This conclusion supported previous speciation studies conducted in the same waste dump using improved correlation analysis and chemical sequential extraction method.