Isotherm modelling and optimization of oil layer removal from surface water by organic acid activated plantain peels fiber

Abstract

This research aimed to optimize and model the adsorption process of oil layer removal using activated plantain peels fiber (PPF), a biomass-based material. The adsorbent was activated by thermal and esterification methods using human and environmentally friendly organic acid. Effects of process parameters were examined by one factor at a time (OFAT) batch adsorption studies, revealing optimal conditions for oil removal. Also, RSM, ANN and ANFIS were used to adequately predict the oil removal with correlation coefficient > 0.98. RSM modelling revealed the best conditions as 90 °C, 0.2 mg/l, 1.5 g, 6 and 75 mins, for temperature, oil–water ratio, adsorbent dosage, pH and contact time respectively. Under these simulated conditions, the predicted oil removal was 96.88 %, which was experimentally validated as 97.44 %. Thermodynamic studies revealed the activation energy, change in enthalpy and change in entropy for irreversible pseudo-first order and pseudo-second order model as (15.82, 24.17, −0.614 KJ/mols) and (33.21,40.31, −0.106 KJ/mols) respectively, indicating non-spontaneous process; while modeling studies revealed that the adsorption process was highly matched to Langmuir’s isotherm, with maximum adsorption capacity of 50.34 mg/g. At the end of the overall statistical modelling, ANFIS performed marginally better than the ANN and RSM. It can be concluded from these results that our biomass-based material is an efficient, economically viable and sustainable adsorbent for oil removal, and has potentials for commercialization since the process of adsorption highly matched with standard models, and its capacity or percentage oil removal also compares favorably to that of commercially available adsorbents.

Keywords

• Esterification
• Thermodynamics
• Response surface methodology
• Artificial neural network
• Langmuir’ isotherm