Modeling for prediction and optimization of heavymetals removal from water using modified sandfiltration: Response surface methodology (RSM)

Heavy metals removal from polluted water is one of the main environmental concerns.Although modified sand filtration process showed a promising performance in heavymetals removal, the operational conditions play important role in the feasibility of usingthis approach. In this study, we used response surface methodology (RSM) in order todevelop experimental model for prediction and find the optimal conditions for heavymetals removal from water by modified sand filtration with Pistachio hall waste (PHW).According to the results, the maximum removal of ۷۷%, ۶۸%, ۶۱% and ۷۹% wereachieved for Pb, Cu, Co and Ni, respectively under the optimal conditions of flow rate(Q) = ۵ mL/min, fixed-bed column height (H) = ۱۰ cm and adsorbent PHW mas (M) =۷.۴ g/kg. It was observed that, the PHW mass has the highest impact on heavy metalsremoval and then column height, while the flow rate had adverse impact on the finalremoval. Ultimately, four quadratic models were developed by the RSM to predict theremoval efficiency of Pb, Cu, Co and Ni. The results of model evaluation revealed thatthe proposed model could accurately predict the removal efficiency (R۲ > ۰.۹۹۹). Thisstudy provides a useful guideline for the application of modified sand filter in heavymetals removal from contaminated water.

کلیدواژه ها:

RSM ، Heavy metals ، Sand filtration ، Modeling ، optimization ، PHW