Abstract
Biosorption is a sort of sorption technology in which the sorbent is a substance that is biologically sourced. In today's world, biosorption is seen as a simple, inexpensive, and ecologically friendly way for removing pollutants from the environment. One of the branches of bioremediation that is utilised to decrease environmental pollution in the context of minimising improper textile waste disposal is this method. The sorption isotherm of Cibacron Blue onto bean peel were analyzed using ten models—Henry, Langmuir, Dubinin-Radushkevich, Freundlich, BET, Toth, Sips, Fritz-Schlunder IV, Baudu and Fritz-Schlunder V, and fitted using non-linear regression. Statistical analysis based on root-mean-square error (RMSE), adjusted coefficient of determination (adjR2), bias factor (BF), accuracy factor (AF), corrected AICc (Akaike Information Criterion), BIC and HQC showed that the Freundlich model was the best model in terms of overall best criteria. The calculated evidence ratio was 8 with an AICc probability value of 0.89 indicating that the best model was at least 8 times better than the nearest best model, which was Sips. The calculated Freundlich parameters KF (Freundlich isotherm constant) and nF (Freundlich exponent) were 5.369 (L/g) (95% confidence interval from 4.359 to 6.379) and 3.125 (95% confidence interval from 2.717 to 3.533). The Langmuir constant was utilized to calculate the maximum adsorption capacity QmL (mg/g) which gave a value of 27.83 mg/g (95% confidence interval from 23.69 to 31.98). The nonlinear regression method allows for the parameter values to be represented in the 95% confidence interval range which can better allow comparison with published results.
Highlights
Humans have been fascinated by colour for centuries, whether from an aesthetic or a social one
The root-mean-square error (RMSE) was calculated according to Eq (1), [1], and smaller number of parameters is expected to give a smaller RMSE values. n is the number of experimental data, Obi and Pdi are the experimental and predicted data while p is the number of parameters
The equilibrium data from [12] was analyzed using ten models— Henry, Langmuir, Dubinin-Radushkevich, Freundlich, BET, Toth, Sips, Fritz-Schlunder IV, Baudu and Fritz-Schlunder V, and fitted using non-linear regression (Figs. 1-8) Statistical analysis based on root-mean-square error (RMSE), adjusted coefficient of determination, bias factor (BF), accuracy factor (AF), corrected AICc (Akaike Information Criterion), Bayesian Information Criterion (BIC) and Hannan–Quinn information criterion (HQC) showed that the Freundlich model was the best model in terms of overall best criteria (Table 2)
Summary
Humans have been fascinated by colour for centuries, whether from an aesthetic or a social one. A significant growth in the dyeing industry's need for synthetic pigments has occurred in recent decades, owing to the cheap cost of synthetic pigments, their availability in a wide range of colours, and the simplicity with which they may be manufactured. It is textile waste that is the most serious polluter of clean water, and it is dyeing and finishing methods that are to fault (Kant, 2011). A key resource for aquatic life, has been reduced in the water as a result of excessive dye discharge. According to Kant (2012), in order to keep pollutants under control throughout the dyeing and finishing process, an environmentally friendly method must be implemented to replace the hazardous steps that are used (Wong et al, 2020)
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