dc.description.abstract |
One of the main environmental problems is the contamination of water by heavy metals.
Cadmium is important industrial heavy metals used in various production industries.
Remediation of cadmium poisoned areas have both economic and technological challenges,
as conventional and techniques are very expensive to apply for wastewater treatment and
its operation is difficult. Nevertheless, based on environmentally friendly, easy to operate
and cost-effectiveness adsorption technique is very important as it compared to other
technique according to different studies. Adsorption method could solve the problem using
sol-gel based synthesized adsorbent since it is environmentally friendly with high quality
product produced. The moisture content, ash content, specific surface area, volatile matter
and carbon content are characterized by different physical and chemical properties.
Characterization of Fourier transform infrared radiation spectroscope, X-ray diffraction,
specific surface area and thermal gravimetric analysis was done before batch adsorption
experiments. X-ray diffraction revealed that the size of synthesized calcium oxide
nanoparticles was 24.34nm and the specific surface area was 77.4m2/g. The removal of
Cadmium from aqueous solutions was optimized by using response surface methodology.
The influences of different process parameters, by varying dosages of calcium
Nanoparticles, initial Cd (II) concentrations, pH values, and contact times. The optimum
percent removal of cadmium (99.108) has resulted at initial concentration 55ppm, PH 7,
adsorbent dose 0.75g, and contact time 50. The experimental removal efficiency (99.108%)
agreed very well with the predicted one (99.0%), showing the suitability of the model used
and the success of response surface methodology in optimizing of removal of Cd (II) ions
from aqueous solutions. The cadmium removal was well fitted into the Langmuir isotherm
model with correlation coefficients of 0.9854. The adsorption kinetic data were well fitted
with the pseudo-second-order model with a correlation coefficient of 0.9982. |
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