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Application of response surface methodology for optimization of an onsite electro-chlorinator for drinking water treatment

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Abstract

The potential of the novel electro-chlorination system assembled with graphite anodes for its application in drinking water supply was explored. The process parameter optimization was carried out using response surface methodology (RSM) approach and the optimal conditions for highest yield of active chlorine were arrived. The effect of the process variables were investigated using Box-Behnken design. The experimentally observed results were correlated and integrated to derive a mathematical model. The derived RSM model predicted active chlorine production was validated using various statistical parameters i.e., coefficient of determination (R2), adjusted R2 (R2adj), and predicted R2 (R2pred). The experimental results were fitted well with the quadratic model suggested by the software and the R2 value obtained was 0.9828. The study concluded that active chlorine formation can be optimized and modeled using RSM approach and can be effectively implemented.

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Acknowledgements

The authors thank the financial support from Indian Institute of Technology (ISM), Dhanbad, funded by the Ministry of Human Resource Development (MHRD), Government of India, New Delhi, for carrying out this study.

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Authors and Affiliations

  1. Department of Environmental Science and Engineering, Indian Institute of Technology (ISM), Dhanbad, Jharkhand, 826004, India

    Jayeeta Saha & Sunil Kumar Gupta

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  1. Jayeeta Saha
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  2. Sunil Kumar Gupta
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Correspondence to Jayeeta Saha.

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Highlights

• Study on a novel electro-chlorination reactor using low-cost graphite anodes and stainless steel cathodes for drinking water treatment.

• The study was conducted with electrolytes at low chloride concentration occurring naturally in the surface water.

• The optimization process was carried out using designs of experiment-based response surface methodology (RSM).

• Box-Behnken design was used for evaluating the impacts of the process factors on the response.

• The experimentally determined response levels conformed satisfactorily with the model assumed theoretical values at an R2 value of 0.98.

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Saha, J., Gupta, S.K. Application of response surface methodology for optimization of an onsite electro-chlorinator for drinking water treatment. Ionics 24, 3237–3248 (2018). https://doi.org/10.1007/s11581-017-2430-1

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