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The current study was to examine the reliability and effectiveness of using most abundant, inexpensive waste in the form of scrap raw zero valent aluminum ZVAI and zero valent iron ZVI for the capture, retard, and removal of one of the most serious and hazardous heavy metals cadmium dissolved in water. Batch tests were conducted to examine contact time (0-250) min, sorbent dose (0.25-1 g ZVAI/100 mL and 2-8 g ZVI/100 mL), initial pH (3-6), pollutant concentration of 50mg/L initially, and speed of agitation (0-250) rpm. Maximum contaminant removal efficiency corresponding to (90 %) for cadmium at 250 min contact time, 1g ZVAI/ 6g ZVI sorbent mass ratio, pH 5.5, pollutant concentration of 50 mg/L initially, and 250 rpm agitation speed were obtained. Langmuir and Freundlich isotherms were presumed to fit the batch kinetics data for the sorption of Cd(II) onto ZVAI and/or ZVI and found that Langmuir (I) was the most representative model type with coefficient of determination R 2 greater than 0.9115. Kinetics data for the sorption of Cd(II) onto ZVAI/ZVI mixture and due to the good agreement between the fitted and the experimental results; the data was found to obey the pseudo second order model. The scanning electron microscopy (SEM) for the ZVI and ZVAI was conducted before and after the sorbent-liquid reaction and revealed distinct morphological changes in the sorbent surface due to the contaminant saturation and pore channel blockages that ceased the sorption process.

The current theoretical and experimental study was to thoroughly examine the capability of date stones for scavenging cadmium and lead ions from simulated wastewater. Three layers-artificial neural network (ANN) with 115 batch tests proved that the best conditions achieved the highest sorption efficiency (>63% for Cd(II) and > 91% for Pb(II)) where time 1 h, pH 5–6, dosage 5 g/100 mL, speed 100 rpm and temperature 25 °C. A satisfactory matching between the measurements and the ANN outputs was recognized with coefficient of determination greater than 99%. The ANN has also revealed throughout the sensitivity analysis that the initial pH and contact time with importance of 25 and 39% for cadmium and lead ions respectively were considered to be the most influential parameters in the removal process. Among Langmuir, Freundlich, and ANN models, the latter one was well fitted the sorption data. This model was substituted in solute transport equation to describe the spatial and temporal distribution of metal ions through the packed column. From the breakthrough curves, the well agreement between the theoretical and measurements (Willmott’s index almost greater less than 0.97), the date stones sorbent have had greater tendency to sorb lead ions than that of cadmium ones.

The present study is to investigate the possibility of using wastes in the form of scrap iron (ZVI) and/ or aluminum ZVAI for the detention and immobilization of the chromium ions in simulated wastewater. Different batch equilibrium parameters such as contact time (0-250) min, sorbent dose (2-8 g ZVI/100 mL and 0.2-1 g ZVAI/100 mL), initial pH (3-6), initial pollutant concentration of 50 mg/L, and speed of agitation (0-250) rpm were investigated. Maximum contaminant removal efficiency corresponding to (96 %) at 250 min contact time, 1g ZVAI/ 6g ZVI sorbent mass ratio, pH 5.5, pollutant concentration of 50 mg/L initially, and 250 rpm agitation speed were obtained. The best isotherm model for the batch single Cr(III) uptake by ZVI and / or ZVAI sorbent was found to follow Langmuir (I) with corresponding R2greater than 0.9115. Kinetics data for the sorption of Cr(III) onto ZVAI/ZVI mixture and due to the good agreement between the fitted and the experimental results; the data was found to obey the pseudo second order model at which the chemisorptions mechanism was the most dominant in the sorption process. Scanning electron microscopy (SEM) for the ZVI and ZVAI has revealed highly surface changes and saturation by contaminant and apparent pores blockage that hindered and ceased the sorption process.

Polluted water may cause a variety of diseases in humans and animals, affecting the ecosystem's life cycle. Owing to the great worldwide demand for water, the examination of water quality must be put into consideration. To ensure a constant supply of fresh water, this quality must be checked regularly. With an up-to-date advancement in communications, sensors, and IoT technologies, the whole problems accompanied by monitoring water deterioration have already been tackled. In the present work, a proposed smart and low-cost, high-efficiency IoT appliance water quality detected device that continuously checks for pH, TDS, temperature, and turbidity water quality parameters. Forty tests of water samples were collected from four groups of different sources were used to evaluate the created model for water sample that is safe for drinking and Water Quality Index classified as drinking purpose. The framework's Wi-Fi module sends data from the sensors to the Arduino, which then sends the data to the cloud and displays it on a mobile/webpage application. This framework can maintain a close eye on water asset pollution and can provide a successful scenario for suitable drinking water or not using a WQI analysis of the water sample. In contrast, this allows for a water quality standard that is well regulated.

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