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Response surface methodology-based modeling and optimization of chromium removal using spiral-wound reverse-osmosis membrane setup

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Abstract

Contamination of groundwater sources due to the presence of chromium ions, a heavy metal, and the detrimental impact of it on the health of consumers have become a serious global concern. The present study was designed to understand the effects of three process variables, namely feed chromium concentration, feed pH and pressure, on chromium removal and permeate flux, by employing response surface methodology and central composite design techniques. Spiral-wound reverse-osmosis membrane was used for the removal of chromium from the groundwater samples in this study. Membrane performance, in terms of high permeate quality and flux, was evaluated by optimization of various operating conditions. The obtained experimental results were then matched with the predicted values obtained from the models. The models indicated that the highest chromium removal of 98.38% and permeate flux of 48.73 L/m2 h could be achieved at the optimum feed pH of 3.00, pressure of 4 kg/cm2 and feed chromium concentration of 0.431 ppm. Experimental validation confirmed that the model had higher predictive capabilities. The changes in pressure and the chromium concentration significantly affected the chromium removal and permeate flux, the former being positively correlated and the latter being negative to both the responses. Therefore, small-scale RO membranes can be used to treat aqueous solution with chromium contamination.

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Acknowledgements

This work was supported by Science and Engineering Research Board (SERB), Department of Science and Technology (DST), Government of India, New Delhi, India (Grant No. ECR/2016/001668).

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Correspondence to M. C. Garg.

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Editorial responsibility: Parveen Fatemeh Rupani.

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Karunakaran, A., Chaturvedi, A., Ali, J. et al. Response surface methodology-based modeling and optimization of chromium removal using spiral-wound reverse-osmosis membrane setup. Int. J. Environ. Sci. Technol. 19, 5999–6010 (2022). https://doi.org/10.1007/s13762-021-03422-y

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