Oil-contaminated water is among the most significant environmental challenges from various industries and manufacturing processes. Oily water poses a severe environmental threat and is toxic to many forms of life. This study aims to investigate the potential of natural adsorbents, namely animal bones (ABs) and anise residues (ARs), for removing oil from water using a batch adsorption process. The effects of adsorbent dosage (0.2–2 g), oil concentration (200–1000 mg/L), and contact time (30–120 min) on the adsorption process were evaluated. This study is the first to employ ABs and ARs as adsorbents for oil removal, and their efficacy for this purpose has not been previously reported. The results indicate that ABs exhibit superior oil removal capacity compared to ARs. Specifically, ABs removed 45 mg/g of oil from water, while ARs removed only 30 mg/g of oil. Furthermore, ABs achieved a percentage removal rate of 94%, whereas ARs had a percentage removal rate of 70%. The adsorbents were characterised using Fourier transform infrared (FTIR) spectrometry, contact angle measurements before and after adsorption, and thermogravimetric analysis (TGA). In addition to the experimental analysis, several kinetic and adsorption models were employed to investigate the adsorption process. The pseudo-first-order and pseudo-second-order models were used to represent the kinetics of the reaction, while the Langmuir and Freundlich isotherm models were used to represent the adsorption isotherm. Marquardt’s percent standard deviation (MPSD) error function was used to confirm the fit of the experimental data with the isotherm model, in addition to the correlation coefficient R². The isotherm studies indicated that the experimental data of the two adsorbents used with the Langmuir isotherm model were consistent with one another. The kinetics study demonstrated that the adsorption process using the two adsorbents adheres to a pseudo-second-order kinetics model.

Paracetamol is one of the most anthropogenic micropollutants, and their removal from the environment often requires a specialized method of remediation. In this study, a photocatalyst technique aided with air bubbles was used to degrade the pharmaceutical pollutant paracetamol (PCT) from the water via the COD test and HPLC analysis under different operating conditions. The experiments were carried out in a semi-batch rectangular bubble column with dimensions of 1500 mm height, 30 mm depth, and 200 mm width under UV light. Titanium oxide (TiO2) was used as a source of catalyst. The effect of operating conditions of pH (3-10), air flow rate (0-2) L/min, salinity of solution represented by NaCl concentration (0-1000) mg/L, and 240 min irradiation time on the paracetamol removal were studied. The Box–Behnken design was adopted to study the individual effects of pH (A), air flow rate (B), and salinity (C) and their interactive effects. From the experimental and regression data, a second-order polynomial regression model is predicted, and the variance analysis of the regressions shows that the linear terms (A and B), and all quadratic terms (A, B, and C) have significant effects on the removal percentage of COD. According to numerical optimization, the greatest %COD removal is 76.7 in the process conditions of 5.3 pH, 1L/min, and 269 mg/L of NaCl. The experimental results show that the maximum %COD removal was 78% at pH=7, 1L/min, and 0mg/L of NaCl. HPLC analysis shows 91.2% of paracetamol degradation.