Abstract
In the present work, spent tea leaves were modified with Ca(OH)2 and used as a new, non-conventional and low-cost biosorbent for the removal of Cu(II) from aqueous solution. Response surface methodology (RSM) and artificial neural network (ANN) were used to develop predictive models for simulation and optimization of the biosorption process. The influence of process parameters (pH, biosorbent dose and reaction time) on the biosorption efficiency was investigated through a two-level three-factor (23) full factorial central composite design with the help of Design Expert. The same design was also used to obtain a training set for ANN. Finally, both modeling methodologies were statistically compared by the root mean square error and absolute average deviation based on the validation data set. Results suggest that RSM has better prediction performance as compared to ANN. The biosorption followed Langmuir adsorption isotherm and it followed pseudo-second-order kinetic. The optimum removal efficiency of the adsorbent was found as 96.12 %.
Highlights
Over the past several decades, the exponential population and social civilization expansion, sharp modernization and metropolitan growth, and continuing progress of the industrial and technologies has largely contributed to the contamination of groundwater and other water resources by toxic heavy metals (Foo and Hameed 2010a, b)
The same design was used to obtain a training set for artificial neural network (ANN). Both modeling methodologies were statistically compared by the root mean square error and absolute average deviation based on the validation data set
Using modified spent tea leaves (MSTL) it was observed that adsorption capacity of copper increased 20 times more than using untreated tea leaves (UTL)
Summary
Over the past several decades, the exponential population and social civilization expansion, sharp modernization and metropolitan growth, and continuing progress of the industrial and technologies has largely contributed to the contamination of groundwater and other water resources by toxic heavy metals (Foo and Hameed 2010a, b). Copper is one of the most widely used heavy metals. Copper and its compounds are extensively used in various important industrial applications such as electrical wiring, plumbing, gear wheel, air conditioning tubing, and roofing (Chowdhury and Saha 2011). Intake of excessively large doses of copper by human beings leads to severe mucosal irritation and corrosion, stomach upset and ulcer, wide spread capillary damage, hepatic and renal damage, central nervous system irritation followed by depression, gastrointestinal irritation, and possible necrotic changes in the liver and kidney (Yao et al 2010). Removal of copper from effluents is essential to protect the water sources and for the protection of human health
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