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Comparison of Response Surface Methodology and Artificial Neural Network in Optimization and Prediction of Acid Activation of Bauxsol for Phosphorus Adsorption

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Abstract

Bauxsol is a chemico-physically modified product of red mud and is a promising material for the removal and recovery of phosphorus from wastewater. In this study, response surface methodology (RSM) and artificial neural network (ANN) were employed to develop prediction models and also to investigate the interactions of independent experimental factors for phosphorus adsorption onto acid-activated Bauxsol. The experimental results indicated that HCl activation was effective to improve the adsorption capacity of Bauxsol. The maximum adsorption capacity of acid-activated Bauxsol was 55.72 mg/g (as P) with HCl concentration of 10.20 mol/L, temperature of 41.00 °C, and time of 5.60 h, which increased by 10.53 and 6.62 times compared with the raw red mud and Bauxsol before acid activation, respectively. The relative importance of HCl concentration in RSM and ANN models was 51.78 and 54.25 %, respectively, which illustrated that HCl concentration played the predominant role on improving the adsorption capacity of Bauxsol. The predictive capability of RSM and ANN models was compared, and the results showed that both models provided excellent predictions with R 2 > 0.93. However, the ANN model showed the superiority over RSM for estimation capability.

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Acknowledgments

The authors are thankful to the China Scholarship Council (CSC), the National Natural Science Foundation of China (51178047, 51378190, 51039001), and Furong Scholar of Hunan Province for supporting.

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Authors and Affiliations

  1. College of Environmental Science and Engineering, Hunan University, Changsha, 410082, China

    Jie Ye, Panyue Zhang, Guangming Zeng & Yang Liu

  2. Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha, 410082, China

    Jie Ye, Panyue Zhang, Guangming Zeng & Yang Liu

  3. Department of Aquatic Environmental Engineering, Karlsruhe Institute of Technology, Karlsruhe, D-76131, Germany

    Jie Ye, Erhard Hoffmann, Yinan Tang & Johanna Dresely

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  1. Jie Ye
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  2. Panyue Zhang
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  4. Guangming Zeng
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  7. Yang Liu
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Correspondence to Panyue Zhang or Erhard Hoffmann.

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Ye, J., Zhang, P., Hoffmann, E. et al. Comparison of Response Surface Methodology and Artificial Neural Network in Optimization and Prediction of Acid Activation of Bauxsol for Phosphorus Adsorption. Water Air Soil Pollut 225, 2225 (2014). https://doi.org/10.1007/s11270-014-2225-1

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