Optimization of Strontium Removal Process From Contaminated Water Using Zeolite Nanocomposites

Abstract The effective removal of strontium from polluted water is an emerging issue worldwide, especially in Japan, after the destruction of Fukushima’s Daiichi Nuclear Power Plant. In the strontium removal process, statistical optimization of associated factors is needed to reduce the quantity of chemicals and the number of experimental trials. In this study, response surface methodology based on the central composite design was employed for assessing the influence of different factors and their interaction effects on the efficiency of strontium removal. We have considered nanoscale zero-valent iron-zeolite (nZVI-Z) and nano-Fe/Cu zeolite (nFe/Cu-Z) as adsorbents for the effective removal of strontium. The present study showed that the most statistically significant potential contributor was initial concentration, followed by contact time in the removal process. The study indicated that the interaction effect between contact time and initial concentration was statistically important, suggesting the need for a multi-mechanism technique in the removal phase of strontium. Tόth, Langmuir, Dubinin-Astakhov (D-A), Freundlich, and Hill isotherm models were also fitted with the experimental strontium adsorption data, in which the Tόth model fitted best compared to the other models based on the RMSD.