cadmium usually enter the environment and water resources through wastewater, released by various industries, and may have adverse effects. The current study employs surface of bentonite clay available locally in order to remove cadmium In solutions contaminated with this type of ions, in order to research on a surface with a high ability to adsorption of cadmium (II) ions, study Some factors affect the adsorption process on bentonite clay, such as contact time, pH the solution, Adsorbent particle size, Initial concentration of solutions and temperature of the solution were examined in the a batch process mode. The amount of adsorbed Cd (II) increased with height temperature, the optimum adsorption pH was about 6.5. Under this condition, the percent removal was 95.17%. The adsorption  isotherms were studied and  the results of adsorption processes were more fitted with Friendlich model rather than Langmuir adsorption model. Thermodynamic study showed that,  ΔH was endothermic, ΔG is found to be negative That is, the process is automatic and  ΔS was found to be positive. The current study also involves  practical application using bentonite to get rid of Cd(II) ions  to  from wastewater of Hamdan's station of the Basra- iraq, The results indicate high affinity (97.84%) removal of Cd(II) ions.

An important practice in environmental risk management is assessing the consequences of heavy metal concentrations resulting from a mine dam tailing failure on soil, water, and trees. To appraise the extent of pollution, an effective classification is essential. In this study, trace element contamination is handled as a two-group classification problem and examined the performance of supervised regularization algorithms as spatial classifiers using imbalanced uncertain data. In addition to conventional shrinkage algorithms such as Ridge, the Lasso and Elastic-Net, the generalized t-statistic-based U-Lasso classifiers have been introduced and tested for mitigating such imbalances and adjusting weights for class distributions. The feature interpretation studies underlined that the most important indicator of the models is Zinc (Zn). The experimental studies revealed that the Ridge classifier (l2 penalty) outperforms the other models. Statistically, the U-Lasso models exhibited notable explanation capacity and their performances recorded close to the conventional shrinkage algorithms. The use of statistical learning-based classification approach to appraise geo-environmental contamination under the conditions of natural variability and spatial uncertainty provides useful meta-data and reliable classification models.

This scientific article presents the results of studies on the distribution of natural and artificial radionuclides in fish living in the rivers of the northwestern sector of the Arctic zone of the Russian Federation. Fish sampling (about 76 kg in total) was carried out in the White Sea, in the Northern Dvina and Mezen Rivers, and in the Sukhoe Sea Bay of the Arkhangelsk Region, as well as in the rivers of the Nenets Autonomous District: Pesha, Oma, Vizhas, Nes, and Pechora. The results showed the presence of artificial radionuclides Cs-137 and Sr-90 in fish only in the Nes River of the Nenets Autonomous District. The levels of radionuclides in whole bodies perch and pike in the Nes River range from 3.73 to 14.0 Bq/kg wet weight for Cs-137 and less than 3.72 to 23.1 Bq/kg wet weight for Sr-90. In addition to Cs-137 and Sr-90, the presence of the radionuclide K-40, which is the main dose-forming radionuclide, was noted in the fish of all the studied rivers and seas. K-40 activity was in the reached values 138 Bq/kg for whole fish bodies. The only assumption that can explain the presence of artificial radionuclides in the fish of the Nes River is a possible radioactive trace formed as a result of global nuclear tests, including in the Novaya Zemlya archipelago. At the same time, it is noted that the current levels of technogenic radioactivity in fish from the Nes River do not pose a radiological hazard to the local population.

AGIS method based on spatial autocorrelation analysis used to identification and ranking of thoron (220Rn)concentration. Spatial radiation patterns are analyzed using Moran's I statistic. Getis-Ord Gi* is utilized to locate clusters of high and low measurements and create a map of thoron hot spots. One hundred schools in the center of Najaf City were examined for thoron using CR-39 detectors (produced from Track Analysis Systems Ltd., UK)  for this research. Average thoron levels were 2.99 Bq/m3, with a range of 9.00 Bq/m3 to 0.22 Bq/m3. The radiation levels found in this investigation were significantly lower than the UNSCEAR 2000 safety standards of 40 Bq/m3. Moran's, I have used it to analyze the clustering of districts across a research region and to measure the spatial distribution of data. Getis-Ord Gi* statistics were used to identify cold and hot spots within the research area. Thoron concentrations were shown to have insignificant spatially random distribution patterns, as demonstrated by Global Moran's I. (Moran’s I =0.28, p-value=0.24).

Predicting the path of pollution in the marine area is one of the most important concerns for those involved in environmental studies. In this paper, we have discussed the capabilities of using the data assimilation method in the FVCOM numerical model in forecasting the movement path of a surface drifter in the Strait of Hormuz. Initially, the FVCOM model was implemented for particle tracking by using environmental data in the Strait of Hormuz. Then tidal gages data of the Strait of Hormuz were assimilated in the numerical model using the nudging method. The results of the two runs were compared with field measurements data using statistical parameters such as bias and correlation coefficient. Statistical analysis and visual comparisons depicted the ability of data assimilation in optimizing the model water level outputs and reducing the differences between drifter location and model results and also the rate of the distance between them.

Domestic and industrial wastewater contributed to some urban wastewater, which requires specific processing before being disposed into surface waters or reused for irrigation. This paper aimed to employ kaolin as an adsorbent to remove heavy metals from wastewater, as well as aeration and alum to remove nutrients. Experiment were conducted in three parts: first, involved using the aeration method to determine the ideal amount of time to remove or minimize the nutrients. Second, involves treating the solution with potassium alum using various alum doses at the obvious times to eliminate or minimize the nutrients, while third step involves treating the solution with kaolin ore with a size of < 63 µm at various doses, pH, and contact times to remove heavy metals. The findings showed that the aeration method completely removed CO3, OH, PO4, NO3, Ca, and Mn ions after contact time equal 120, 24, 192, 24, 120, and 48 hrs, respectively. Applaying alum treatment method can remove completely CO3, OH, PO4, NO3, and Mn, after contact time 120, 24, 120, 24, and 24 hrs, respectively. When Kaolin ore used as adsorbent, the removal efficiency of  Fe, Cd, Cr, Cu, Sr, Mn, and Zn were; 92, 100, 100, 100, 94, 100, and 88 % ,respectively in 24 hours contact time. The experiment succeeds in treatment of industrial wastewater that was within the range of specified limitations for disposing into surface water or reuse in irrigation field as stated by Egyptian standard code using the three successive treatment techniques.

Petroleum contains carcinogens and toxic substances that can have an unfavorable impact on environmental quality and human health when the soil becomes contaminated with crude oil.  BBiostimulation and bioaugmentation are the main strategies in the bioremediation of oil-contaminated soils. To decompose old-aged petroleum pollution in saline soil, a full factorial experiment was utilized. The experiment was designed using a completely randomized design with four factors: bacterial inoculum, sugarcane bagasse, chemical fertilizer, and molasses. The application of these factors was conducted in four separate experiments: pretreatment of agricultural soil and spent mushroom compost, pretreatment of spent mushroom compost, pretreatment of agricultural soil, and no pretreatment. After a 60-day incubation period at 28 ˚C, the results showed that the organic wastes of molasses and spent mushroom compost in combination with bacterial inoculum reduced total petroleum hydrocarbons 38 and 33.3%, respectively. Molasses had a considerable impact on increasing the efficiency of bacterial inoculum 1 and bacterial inoculum 3. Similarly, spent mushroom compost was found to significantly affect bacterial inoculum 1. In addition, bagasse was observed to accelerate the bioremediation process by improving the physical conditions of the soil. In the pretreatment of agricultural soil, bagasse in combination with bacterial inoculum 1 and chemical fertilizer reduced the total petroleum hydrocarbons significantly (38%) compared to the control treatment. These results highlight the effectiveness of organic wastes as biostimulation agents in promoting the growth and reproduction of the soil microbial community, as well as establishing the bacterial inoculum.

The Huatanay River in Cusco-Peru, is affected by wastewater discharges along its course. In order to evaluate this impact, we evaluate antibiotic residues and their impact on the increase of bacterial resistance in the city of Cusco treatment plant. For this purpose, water samples from the influent and effluent of the treatment plant were analyzed by chromatographic methods; additionally, sensitivity tests were performed with three bacterial strains (Escherichia coli, Salmonella sp., and Klebsiella sp.), which were isolated from the same place. Six antibiotic residues were identified (ceftriaxone, amoxicillin, trimethoprim, sulfamethoxazole, dicloxacillin, and lincomycin). Those found in the highest concentration were: amoxicillin (91495 and 0 µg/L) and lincomycin (33970 and 10800 µg/L) in the influent and effluent, respectively. There is more resistance in the effluent than the influent in the case of E. coli shows resistance in the effluent to cephalexin (30 µg) and azithromycin (15 µg). Salmonella sp. is resistant to amoxicillin (15 µg), dicloxacillin (1 µg), lincomycin (2 µg), ceftriaxone (30 µg), cephalexin (30 µg), and ciprofloxacin (5 µg). Finally, Klebsiella sp. is sensitive to ceftriaxone (30 µg), amoxicillin (15 µg), and cephalexin (30 µg). This confirms that the antibiotic residues contained in the wastewater of Cusco generate resistance in the isolated bacteria.

Elevated level of fluoride (> 1.0 mg/L) in drinking water leads to both dental and skeletal fluorides. Present research is dedicated to check the efficacy of duck shell dust towards removal of fluoride. Various analytical tools (XRF, XRD, SEM-EDAX and zero point charge) were used to characterize the present adsorbent. The entire batch mode study results were further optimized by Response Surface Methodology (RSM). The results revealed that Langmuire isotherm is best fitted (R2 = 0.819) with adsorption capacity 4.894 mg/g. However, kinetic study suggest that the fluoride adsorption followed pseudo-second-order kinetic equation (R2 = 0.956). Similarly, thermodynamic study revealed that the fluoride adsorption by duck shell dust is endothermic and entropy driven process. Finally, optimization study demonstrated the optimized condition such as initial concentration, adsorbent dose, contact time and pH are 89.29 mg/L, 1.112 g/100 mL, 42.5 min and 9.91, respectively. Therefore, it may be concluded that duck shell dust could be a promising adsorbent for decontamination of fluoride from contaminated body.

Clogging of the drainage layer is the main reason for the inefficiency and failure of the leachate collection system in municipal solid waste (MSW) landfills. One of the most important challenges in the design and operation of landfills is to identify the factors affecting the drainage layer clogging and the extent of their influence especially in the real scale. In this study, five experimental columns were designed to investigate the effective factors on the clogging of the drainage system in the MSW landfills, making it possible to measure the effect of different parameters on the drainage layer clogging through simulating the real conditions. The designed columns are capable to apply the boundary conditions of the MSW landfill including temperature, pressure, and leachate recirculation as well as measuring the permeability of drainage layer. High strength real leachate recirculated in the experimental columns to monitor the degree of drainage layer clogging through the regular measurement of permeability in the different columns. The results showed hydraulic conductivity of the drainage layer decreased between 20 to 50 percent in different samples over time. Although the particle size of drainage materials directly influences the reduction of hydraulic conductivity, the common concentration of calcium carbonate in the materials of the drainage layer does not considerably affect this issue. Formation of biofilm in the drainage layer was observed through scanning electron microscope (SEM) and visual inspection in all columns indicating the proper performance of clogging process simulator which is designed and developed in this research.