The presence of heavy metals in the environment is major concern due to their toxicity. In the present study a strong acid cation exchange resin, Amberlite IR 120 was used for the removal of lead, zinc and copper from simulated wastewater. The optimum conditions were determined in a batch system of concentration 100 mg/L, pH range between 1 and 8, contact time between 5 and 120 minutes, and amount of adsorbent was from 0.05 to 0.45 g/100 ml. A constant stirring speed, 180 rpm, was chosen during all of the experiments. The optimum conditions were found to be pH of 4 for copper and lead and pH 6 for zinc, contact time of 60 min and 0.35 g of adsorbent. Three different temperatures (25, 40 and 60°C) were selected to investigate the effect

Pilot-scale dead end microfiltration membranes were carried out to determine the feasibility of the process for treating the oily wastewater which discharge from some Iraqi factories such as power station of south of Baghdad and the general company of petrochemical industries. Polypropylene membranes (cylindrical shape) with different pore diameters (1 and 5 micron) were used to conduct the study on micromembrane process. The variables studied are oil concentration (100 – 1000 ppm), feed flow rate (20 – 40 l/h), operating temperature (31 – 50°C) and time (0 – 3 h). It was found that the flux increases with increasing feed flow rate, temperature and pore size of membrane, and decreases with increasing oil concentration and operating

   It is challenging to remove antibiotics from water bodies, as they are among the most widespread contaminants in the environment, particularly with conventional wastewater treatment methods, due to their persistence and low biodegradability. The current study examined the use of nanoscale zero-valent iron to remove antibiotics. Conocarpus leaf extract, which is primarily composed of polyphenols like flavonoids and tannins, was employed as a green source to prepare Fe/Cu nanoparticles, which can act as an eco-friendly reducing agent. The nanoparticles were immobilized onto silica sand (SS), forming SS-Fe/Cu nanocomposite to remove tetracycline (TC) and ciprofloxacin (CIP) from aqueous solutions. The structural characteristics

The current study investigated the stability and the extraction efficiency of emulsion liquid membrane (ELM) for Abamectin pesticide removal from aqueous solution. The stability was investigated in terms of droplet emulsion size distribution and emulsion breakage percent. The proposed ELM included a mixture of corn oil and kerosene (1:1) as a diluent, Span 80 (sorbitan monooleate) as a surfactant and hydrochloric acid (HCl) as a stripping agent without utilizing a carrier agent. Parameters such as homogenizer speed, surfactant concentration, emulsification time and internal to organic volume ratio (I/O) were evaluated. Results show that the lower droplet size of 0.9 µm and higher stable emulsion in terms of breakage percent of 1.12 % we

The current study investigated the stability and the extraction efficiency of emulsion liquid membrane (ELM) for Abamectin pesticide removal from aqueous solution. The stability was investigated in terms of droplet emulsion size distribution and emulsion breakage percent. The proposed ELM included a mixture of corn oil and kerosene (1:1) as a diluent, Span 80 (sorbitan monooleate) as a surfactant and hydrochloric acid (HCl) as a stripping agent without utilizing a carrier agent. Parameters such as homogenizer speed, surfactant concentration, emulsification time and internal to organic volume ratio (I/O) were evaluated. Results show that the lower droplet size of 0.9 µm and higher stable emulsion in terms of breakage percent of 1.12 % were

This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce