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Desorption kinetics and isotherms of phenanthrene from contaminated soil
Farzaneh Gharibzadeh1,2, Roshanak Rezaei Kalantary3,4, Ali Esrafili3,4
11Students' Scientific Research Center (SSRC), Tehran University of Medical Sciences, Tehran, Iran.
Background:
Prediction of polycyclic aromatic hydrocarbons (PAHs) desorption from soil to estimate available fraction regarding to initial concentration of the contaminant is of great important in soil pollution management, which has poorly been understood until now. In the present study estimation of fast desorption fraction which is considered as available fraction was conducted by evaluating desorption kinetics of phenanthrene (a three ring PAH) from artificially contaminated soils through the mathematical models.
Methods:
Desorption rate of phenanthrene (PHE) was investigated by using the nonionic surfactant Tween80 in a series of batch experiments. The effects of reaction time from 5 to 1440 min and initial PHE concentration in the range of 100-1600 mg/kg were studied.
Results:
Available fractions of the contaminant were achieved within the first hour of desorption process as the system reached to equilibrium conditions. Experimental data were examined by using kinetic models including pseudo-first-order, pseudo-second-order in four linearized forms, and fractional power. Among the models tested, experimental data were well described by pseudo-second-order model type (III) and (IV) and fractional power equation. Fast desorption rates, as Available fractions were determined 79%, 46%, 40%, 39%, and 35% for initial PHE concentrations of 100, 400, 800, 1200, and 1600 mg/kg respectively. Among the evaluated isotherm models, including Freundlich, Langmuir in four linearized forms, and Temkin, the equilibrium data were well fitted by the first one.
Conclusion:
Applying the nonionic surfactant Tween80 is a useful method to determine available fraction of the contaminant. This method will provide the management of contaminated sites by choosing a proper technique for remediation and predicting achievable treatment efficiency.
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