Global NEST Journal

Presence of antibiotics in the environment specially in aqueous environments is considered a major warning about health and environment. Thus, this study aims the efficiency of coupled process of Activated Carbon (AC) prepared from mango seed+ZnO under UV irradiation as an advanced oxidation process in removing cefazolin antibiotic from aqueous solutions. This experimental study was carried out in a discontinuous reaction chamber with volume of one liter. In this process, the effect of initial pH parameters of the environment (3– 9), initial concentration of cefazolin (20 – 200 mg/L), concentration of modified, photocatalyzer (20 – 100 mg/L) and reaction time (10 – 60 min) were studied. The pilot used consisted of a low pressure mercury lamp with a 55-watt beam radiation power inside the steel chamber. The kinetic of the process was studied based on pseudo first order kinetics. Results showed that the highest removal efficiency of cefazolin antibiotics in the reaction of UV/AC + ZnO, at optimal conditions of pH= 3, contact time of 60 min, initial concentration of 100 mg/L and modified photocatalyzer of 0.1 g/L was equal to 96%. The kinetic model determined for the process followed kinetic model of pseudo- first order kinetics with high correlation of (R2 = 0.99). Results of present study revealed that photocatalyzer process of nanoparticles oxidation on synthetic activated carbon can be effectively used as an advanced oxidation reaction to remove cefazolin and similar pollutants.

The removal of Lead (II) from aqueous solutions using Fagopyrum esculentum Moench (Buckwheat) and Bambusa vulgaris (common bamboo) as adsorbents was investigated. The effects of various experimental parameters such as initial concentration, contact time and pH have been studied using batch adsorption technique. All the Adsorption isotherm models fitted well with the adsorption data. However, Freundlich isotherm displayed a better fitting model than the other two isotherm models due to high correlation coefficient (R2). This indicates the applicability of multilayer coverage of the Pb (II) on the surface of adsorbent. The adsorption kinetics was studied using four simplified models and it was found to follow the pseudo-second-order kinetic model which confirmed the applicability of the model. The adsorption mechanism was found to be chemisorption and the rate-limiting step was mainly surface adsorption.

This study presents the evaluation of a strong base (Purolite A200) and weak base (Purolite PFA847) polymeric anion exchange resins for nitrite removal. The different parameters on the removal of NO2– were investigated in batch sorption mode. Common isotherm models; Langmuir and Freundlich, were used in order to present a description of the equilibrium data. Experimental results showed that the equilibrium data tend to follow Freundlich isotherm model for weak base resin and Langmuir model for strong base resin. The sorption of NO2– on anion exchange resins was found to follow the pseudo-second order kinetic model. The values of thermodynamic parameters proved that ion exchange reaction of NO2– onto such resins are endothermic (ΔH > 0).

Multivariate statistical analysis including cluster analysis, factor analysis and correlation coefficient was applied to the groundwater samples to understand the groundwater condition in Wadi Bani Malik area. Water samples collected from the study area were analysed for physical parameters, major cations and major anions. The groundwater quality is not good in this area and the physicochemical parameters go beyond the acceptable limits of the Kingdom of Saudi Arabia and WHO drinking water standards. The water type in the study area was primarily NaCl. Correlation coefficients were determined among different parameters and then regression analysis was performed to realize the linear relationship between the best correlated parameters. Results of factor analysis specify that factor 1 is dominant and is responsible for 45.5% of the total variance and is dominated by Cl-, Na+, Mg++ and K+. Ground water samples can be divided into four clusters.