Nonlinear kinetic analysis of phenol adsorption onto peat soil

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• 作者：Supriya Pal (1)
  Somnath Mukherjee (2)
  Sudipta Ghosh (2)
  
• 关键词：Peat soil ; Adsorption ; Phenol ; Batch kinetics ; Column experiment ; Nonlinear regression analysis
• 刊名：Environmental Earth Sciences
• 出版年：2014
• 出版时间：February 2014
• 年：2014
• 卷：71
• 期：4
• 页码：1593-1603
• 全文大小：540 KB
• 作者单位：Supriya Pal (1)
  Somnath Mukherjee (2)
  Sudipta Ghosh (2)
  
  1. Civil Engineering Department, National Institute of Technology (NIT), Durgapur, 713209, West Bengal, India
  2. Civil Engineering Department, Jadavpur University (JU), Kolkata, 700032, West Bengal, India
  
• ISSN：1866-6299

文摘

Phenolic compounds are considered as a serious organic pollutant containing in many industrial effluents particularly vulnerable when the plant discharge is disposed on land. In the present study, the phenol removal potential of peat soil as adsorption media was investigated as the adsorption process are gaining popular for polishing treatment of toxic materials in industrial wastewater. Batch experiments were performed in the laboratory to determine the adsorption isotherms of initial concentrations for 5, 8, 10, 15, and 20?mg/L and predetermined quantity of peat soil with size ranges between 425 and 200?μm poured into different containers. The effects of various parameters like initial phenol concentration, adsorbent quantity, pH, and contact time were also investigated. From experimental results, it was found that 42?% of phenol removal took place with optimized initial phenol concentration of 10?mg/L, adsorbent dose of 200?g/L, solution pH 6.0 for the equilibrium contact time of 6?h. The result exhibits that pseudo-first-order (R 2?=?0.99) and Langmuir isotherm models are fitted reasonably (R 2?=?0.91). Adams–Bohart, Thomas, Yoon–Nelson, and Wolborska models were also investigated to the column experimental data of different bed heights to predict the breakthrough curves and to determine the kinetic coefficient of the models using nonlinear regression analysis. It was found that the Thomas model is the best fitted model to predict the experimental breakthrough curves with the highest coefficient of determination, R 2?=?0.99 and lowest root mean square error and mean absolute performance error values.