Water and sediments have become a major threat. Heavy metals, some of which are potentially toxic, are distributed in different areas by different routes. Tafna river was studied upstream and downstream under contrasting hydrological conditions during the year 2020.The different levels and sources of pollution are assessed by combining geochemical indicators: geoaccumulation index (GI-go), contamination factor (CF), pollutant loading index (PLI) and supplemented by correlation matrix (CM) as statiscal analyses added principal component analysis (PCA). The elements analysed were physical and chemical parameters (pH, DO, electrical conductivity CE and, COD BOD5), and the metallic elements (Fe, Cd, Pb, Cu, Mn and Zn). They were classified based on how contaminated they were: for the water compartment (Fe> Mn>Cu>Pb>Cd>Zn), while for sediments (Zn> Pb>Fe>Cd>Cu >Mn). The results suggest that the chemical composition of the waters of the Tafna river is influenced by the lithology, which contributes to the enrichment of the sediments. All of the indicators suggest an average levels of sediment and water pollution at the Tafna's summit, then decreases towards the bottom due to the geomorphology with multiple sources of pollution. As a result, our study offers the first comprehensive information on the amount of heavy metals present in the riverbed's sediment and water.

The article aims to assess radon concentration in various water samples, revealing levels ranging from 0.53 Bq/L to 4.68 Bq/L. Radon, specifically the isotope 222Rn, is a naturally occurring radioactive gas formed during the decay of the 238U decay series, originating from the breakdown of 226Ra. This gas is commonly found in rocks, soil, natural gas, and groundwater. Exposure to airborne and waterborne radon can increase the risk of certain cancers due to human radiation exposure. The primary Aim of this study was to assess the concentration of radon in water samples collected from diverse regions of Morocco, particularly the Midelt province and the Draa-Tafilalt region located at coordinates 32° 40' 48″ North, 4° 44' 24″ West. For this purpose, Solid State Nuclear Track Detectors of the LR-115 variety were used. The evaluations of annual effective dose equivalents exhibited a range spanning from 11.51 to 1.30 μSv/y, showcasing a consistent pattern of decline. Correspondingly, projections of excess lifetime cancer risk encompassed a spectrum from 4.00 to 1.98. Significantly higher risks were associated with samples S1 and S2, while notably lower risks were tied to S14 and S15. It is worth noting that all the water samples subjected to analysis registered annual effective doses that fell within the global average level recommended for ingestion exposure dose values (0.23 mSv/y) by the United Nations Scientific Committee on the Effects of Atomic Radiation. Given these results, there seem to be no radiation risks from radon gas in the study area.

Most pollutants found in rivers come from the discharge of raw sewage from both point and nonpoint sources. So, monitoring the pollution levels in surface water sources is essential. River pollution monitoring is a real challenge. Using remote sensing, precise outcomes can be achieved with the help of the selection of the right combination of satellite images and algorithms. Generally, established available algorithms are site-specific, indicating that they may not work at all areas on Earth's surface due to differences in altitude, cloud cover, and sun glint. The present work determined Chlorophyll-a concentrations in the Tapi River at various locations using Landsat-8 satellite images and Acolite software from 2017 to 2021 Period. The outcomes reveal that applying the dark spectrum fitting with sun glint correction when processing Landsat-8 satellite images is needed. In the present study, water quality results were obtained very precisely for the months of January, February, November, and December after processing and analysing satellite images. Due to factors such as sun glare, cloud cover, cloud shadow, and haze, the desired effect could not be achieved in the remaining months of the study period. This research provides a solid foundation for estimating the impact of eutrophication in the water body by estimating chlorophyll-a concentration from satellite images.

Phenols have attracted global interest in the sphere of environmental management due to their potential toxicity on human health. This study determined concentrations of three priority phenolic compounds in effluent and water of a local textile industry in Abeokuta, Nigeria.  During tie-dye production, triplicates of effluent, well water, stream and control water were collected three times from five points to give a total of forty-five samples. Physicochemical parameters of samples including temperature, pH, electrical conductivity (EC), total suspended solids (TSS) and total dissolved solids (TDS) were determined according to standard methods while the concentrations of the priority phenolic compounds (4-nitrophenol, 4-chloro-3-methylphenol and 2, 4-dinitrophenol) were determined using High Performance Liquid Chromatography equipped with Ultra-Violet detector (HPLC/UV). Data obtained were subjected to descriptive (mean and standard deviation) and inferential (ANOVA) statistics. pH, EC and TSS of effluent and water samples were higher than the permissible limits of World Health Organization (WHO) and Federal Environmental Protection Agency (FEPA) while temperature of the effluent samples and TDS of the well water samples were within standard values. Higher concentrations of the priority phenolic compounds occurred in effluent than water samples but 4-nitrophenol was below detection limit (DL) in water samples. Concentrations of 4-nitrophenol, 4-chloro-3-methylphenol and 2,4-dinitrophenol in effluent exceeded stipulated standard of WHO (0.01 mg/L) and water samples. High concentrations of phenols in water bodies at the local textile industry suggest uncontrolled discharge of effluent from the industry which could eventually reach surface and ground water with potential significant health implications to the populace.

The landfill leachate contains high concentrations of organic pollutants that can be biological and resistant to it. Therefore, the resulting leachate must be treated from the healthy landfill before disposing of it in the environment. In this research, the technique of improved magnetic therapy was tested to improve some physicochemical properties of landfill leachate. Where a laboratory model was designed to evaluate the performance of the magnetic field with different strengths on the treatment of the leachate field collected from the Wadi al-Hadda landfill in Tartous Governorate-Syria. By the increasing in magnetic field strength from 272 to 678 µT, the removal efficacy of BOD and COD increased from 9 and 19% to 36.7 and 54.7%, respectively, and, the removal efficacy of NO3-N and NO3 increased from 6 and 17% to 24.6 and 46.8%, respectively. Electric conductivity (EC) values also decreased due to the use of magnetic field.

Nuisance dust particles have emerged as a significant environmental concern within the Middle Eastern region. The principal aim of this research was to conduct an extensive investigation into the physical and chemical attributes of dust-fall particles located within the city of Sulaymaniyah, northeastern Iraq. Over a period of six months, a total of 72 dust-fall particle samples were systematically gathered from three distinct stations, with intervals of seven days. In addition to quantitative analysis, this study included detailed morphological examinations and mineralogical composition assessments, facilitated through the application of analytical methodologies, including Scanning Electron Microscopy (SEM) and X-Ray Diffraction (XRD). The outcomes of these analytical procedures revealed predominantly irregular shapes of the dust particles, characterized by the presence of quartz and calcite minerals, confirming their natural origin due to wind-driven erosion originating from the arid desert landscapes of Iraq and its neighboring southern and western countries. Moreover, this investigation extended to encompass a comprehensive evaluation of both water-soluble and insoluble fractions, in addition to the overall concentration levels of alkali and alkaline earth metals including sodium (Na), potassium (K), calcium (Ca), and magnesium (Mg). Furthermore, the levels of heavy metals of manganese (Mn), iron (Fe), copper (Cu), and arsenic (As) were investigated. The extent of pollution associated with these elements was assessed through the application of the Geo-accumulation index (Igeo) which revealed that, during the study, calcium, magnesium, and copper demonstrated noticeable levels of contamination within the dust-fall particles of Sulaymaniyah city.

Artificial neural networks (ANNs) simulate an anaerobic co-digestion process of Organic Fraction of Municipal Solid Waste (OFMSW) and bio-flocculated sludge for a mesophilic lab-scale semi-continuous feed reactor. The operational, substrate quality and process control parameters such as Organic Loading Rate, Hydraulic Retention Time, pH, VFA/Alkalinity ratio and Total Solids are input variables and methane yield and Volatile Solids removal are outputs for ANN modelling. The lab-scale experimental results are used to develop a prediction model using fitting application for ANN. The network architecture was optimized to achieve accurate predictions, resulting in a 5-19-2 architecture for methane yield and a 5-17-2 architecture for %VSremoval. The training was performed using the Bayesian Regularization (trainbr) algorithm, leading to high coefficients of determination (R2) of 0.953 and 0.978 for methane yield and %VSremoval, respectively. The results demonstrate the effectiveness of neural network-based modelling in capturing complex relationships within the methane yield process, facilitating accurate prediction of crucial output parameters.

This study was undertaken to evaluate concentration of Uranium (U) in the drinking water of the Tonk district of Rajasthan (India). The main objective of the study is to determine the distribution of Uranium concentration and the geochemical behavior of Uranium in pre-monsoon (PRM) and post-monsoon (POM) drinking water samples. Uranium was measured by LED fluorimeter. Total 318 drinking water samples were collected for both seasons. It is observed that the water quality of all the samples is within the limits prescribed by WHO (30 µg/L) except a few, and can be used for domestic purposes. The Uranium concentration was found to be in the range 0.21 to 173.72 µg/L with a mean value of 8.58 µg/L in pre-monsoon and 0.21 to 162.34 µg/L with a mean value of 11.22 µg/L in post-monsoon samples. The geochemistry of the study area shows rock-water interaction. The order of average anionic concentration is found to be HCO3 – > Cl – > SO4 2– > NO3 –. Although no definite trend of seasonal variation in the concentration of U was observed, large samples have higher Uranium concentrations in post-monsoon than pre-monsoon.

Cedrus deodara is a coniferous tree native to Himalayan region. Its wood is a valuable resource for the timber industry; however, its bark is typically discarded as a waste material. The present study examines the performance of Cedrus deodara bark powder (CD) as an inexpensive adsorbent for elimination of Pb (II) ions. In addition to this multiple linear regression (MLR) and artificial neural network (ANN) models were developed for modelling the adsorption process and prediction of Pb (II) removal efficiency. The structural and chemical properties of CD were explored using Field Emission Scanning Electron Microscope (FE-SEM), Energy Dispersive Spectrometer (EDS), X-Ray Diffractometer (XRD) and Fourier Transform Infrared Spectroscopy (FTIR). Batch experiments were conducted to investigate the influence of factors including pH, contact time, initial Pb (II) concentration and temperature on Pb (II) adsorption. The adsorption followed pseudo-second-order kinetic and Langmuir isotherm models with maximum monolayer uptake capacity 77.52 mg/g. Based on the thermodynamic criteria, the process was endothermic and spontaneous with enthalpy change (ΔH = 8.08 kJ/mol), free energy change (ΔG = -2.44 kJ/mol) and entropy change (ΔS = 0.03 kJ/K/mol). Statistical comparison of MLR model (R2 = 0.817, RMSE = 8.954, MAPE = 17.379 %) and ANN model (R2 = 0.993, RMSE = 1.777, MAPE = 2.054 %) confirmed that ANN model was far more accurate in predicting removal efficiency.

In this work, it was attempted to evaluate and demonstrate disinfection effectiveness of an electrochemical process to entirely remove coliform from wastewater effluent following secondary treatment. For the tests, an experimental bench-scale batch electrochemical cell was constructed, and aluminum electrodes were employed in the electro-disinfection reactor. In the electric disinfection phase, wastewater samples were put in the reactor/disinfector and a direct current (DC) was applied to it. According to findings, a significant decrease occurred in the total number of coliforms in the treated wastewater, and a high improvement occurred in the effluent properties. At a contact time of 15 min and a current density of 5.5 mA/cm2, led to a bacterial killing effectiveness of 97.7% or above. As the current density and contact time increased, a general increase occurred in the bacterial killing efficiency, and the effect of the two above-mentioned factors was much greater than the effect of salinity. Moreover, according to the experimental data, the removal efficiency of chemical oxygen demand (COD) and total suspended solids (TSS) by the aluminum electrodes were 78.50% and 99.93%, respectively. The findings indicate the applicability of the proposed electrochemical treatment to wastewater effluent. Nevertheless, to be able to apply this system at an industrial scale in the future, it is necessary to conduct more research into the optimum operation conditions and make an in-depth comparison of energy consumptions between the electrochemical treatment and the conventional approaches.