Electro-kinetic remediation technology is one of the developing technologies that offer great promise for the cleanup of soils contaminated with heavy metals. A numerical model was formulated to simulate copper (Cu) transport under an electric field using one-dimensional diffusion-advection equations describing the contaminant transport driven by chemical and electrical gradients in soil during the electro-kinetic remediation as a function of time and space. This model included complex physicochemical factors affecting the transport phenomena, such as soil pH value, aqueous phase reaction, adsorption, and precipitation. One-dimensional finitedifference computer program successfully predicted meaningful values for soil pH profiles and Cu

     The presence of heavy metal in environment associated with several health problems. The clean up environment from lead (Pb) and Nickel (Ni) represent major challenges. In his study, planktonic and immobilized bacteria were used to purify the water from Pb and Ni in Lab. In the present study, three bacterial isolates of Staphylococcus aureus (isolated from wound swaps), Pseudomonas aeruginosa (isolated from wound swaps) and Pantoea (isolated from urine samples) and identified using biochemical methods to check their ability to biosorb Pb and Ni. Ten PPM of Pb and Ni were added to the deionized distilled water and 107 c.f.u. of planktonic bacteria were used to biosorpe Pb and Ni. Similar experiment was repeated but

Simple method has been used to determine the absence of heavy metals in an aqueous solution. Fluorescein was used as the base colorimetric materialThis was doped with CuCl2 and the final solution showeda clear change in color. This change was correlated with the change in both pH and electrical conductivity of the solution. The optical property as an obvious change of the spectra was observed. Therefore, this simple method could be proposed as a method to detectheavy metals in any solution.

Titanium oxide nanoparticles-modified smectite (SMC-nTiO2) as a low-cost adsorbent was investigated for the removal of Rhodamine B (RhB) from aqueous solutions. The adsorbents (SMC and SMC-nTiO2) were characterized by scanning electron microscopy, Fourier transforms infrared spectroscopy, and energy-dispersive X-ray spectroscopy. The effects of various parameters like contact time, adsorbent weight, pH, and temperatures were examined. Three kinetic equations (pseudo-first-order (PFO), pseudo-second-order (PSO), and intra-particle diffusion) were used to evaluate the experimental kinetic of the data and the results showed that the adsorption process is in line with the PSO kinetic model. Adsorption equilibrium isotherms were modeled using La

In the present study, activated carbon supported metal oxides was prepared for thiophene removal from model fuel (Thiophene in n-hexane) using adsorptive desulfurization technique. Commercial activated carbon was loaded individually with copper oxide in the form of Cu₂O/AC. A comparison of the kinetic and isotherm models of the sorption of thiophene from model fuel was made at different operating conditions including adsorbent dose, initial thiophene concentration and contact time. Various adsorption rate constants and isotherm parameters were calculated. Results indicated that the desulfurization was enhanced when copper was loaded onto activated carbon surface. The highest desulfurization percent for Cu₂O/AC and o

The object of this study was to evaluate the efficiency of safranin O (SFO), dye removal with application of Thuja orientalis as a low-cost biosorbent. The biosorption equilibrium level was determined as a function of pH, adsorbent dose, contact time and temperature. Surface area and pore size distribution were measured for the adsorbent. Thuja has a good removal effeciency for SFO dye. The adsorption kinetics data were best fit for the pseudo-second order kinetic (the regression coefficient = 0.999). The experimental equilibrium adsorption data are tested for the Langmuir, freundlich,Temkin and Dubinin-Radushkevich isotherm modles. From the values of the regression coefficient the results indicate the following order to fit the isotherm