Biosorptive uptake of ibuprofen by chemically modified Parthenium hysterophorus derived biochar: Equilibrium, kinetics, thermodynamics and modeling

•N-biochar (CMNB) from Parthenium hysterophorus was prepared and characterized.•Use of N-biochar as adsorbent for removal of ibuprofen (more than 99%) from simulated water.•Equilibrium, kinetics and thermodynamics study of ibuprofen sorption was performed.•ANN (R2 = 0.9933) showed better optimization predictive capability over RSM (R2 = 0.877).•Cost estimation for preparation of adsorbent material was done.

The present investigation emphasizes the feasibility of chemically modified N-biochar (CMNB) as a potential sorbent for the removal of a non-steroidal and anti-inflammatory drug ibuprofen from contaminated water. N-biochar engineered from precursor Parthenium hysterophorus was treated with NaOH for surface modification. The biosorptive uptake of ibuprofen onto CMNB was studied for the solid–liquid phase characteristics of ibuprofen–water system by a series of batch sorption experiments over the influence of different process parameters viz. adsorbent dose (0.05 g–3 g), speed of agitation (80–240 rpm), contact time (15 min–240 min), pH (2–10), initial ibuprofen concentration (5–100 ppm) and temperature (293–308 K). The maximum adsorptive removal percentage of ibuprofen onto CMNB was found to be more than 99% at adsorbent dose of 20 g L−1, agitation speed 160 rpm, pH 2, initial ibuprofen concentration 20 mg L−1, equilibrium time 120 min and temperature 20°C. The equilibrium adsorption data was well fitted into the Langmuir isotherm model. Kinetic data suggested that the adsorption of ibuprofen onto CMNB follows the pseudo second order kinetics. The probable mechanistic adsorptive behavior of CMNB was well supported by different analytical techniques viz. SEM, FTIR, BET, pHPZC, XRD. Out of six process parameters studied in batch process, three parameters such as dose, agitation speed and pH were chosen for optimization of ibuprofen removal employing central composite design (CCD) approach of response surface methodology (RSM). The same experimental matrix was used in artificial neural network (ANN) for the comparative analysis of ibuprofen removal. Results of this study revealed that CMNB could be a cost-effective and efficient adsorbent for the removal of ibuprofen from aqueous solution.