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ABSTRACT
This study aimed to optimize the treatment of pharmaceutical wastewater using a photocatalytic reactor by investigating the effects of Adsorbent Dosage, Contact Time, and pH levels on Nitrite Reduction %. Coconut shell were collected, washed, dried, and carbonized. After this was done, optimization was carried out using Central Composite Design (CCD) of the Response Surface Methodology (RSM) to determine the optimal nitrite reduction yield. A sample of the adsorbent dosage was sent for characterization and a predictive model was developed to understand the complex relationships between the factors and the response variable. Valuable insights were gained from adsorbent characterization methods concerning specific surface area, pore size distribution, and adsorption capability. Elemental analysis provided information on the adsorbent's composition. The adsorbent has a specific surface area of 471.544 m2/g, a micropore volume of 0.415 cc/g, and a pore diameter mode of 3.020 nm, with a pore volume of 0.244 cc/g, and a pore diameter (Dv(d)) of 2.131 nm. These results indicate exceptional adsorption properties for wastewater treatment due to the high surface area and pore volume, with the presence of micropores enhancing the removal of pollutants. Analysis of the experimental design revealed significant interactions among Adsorbent Dosage, Contact Time, and pH levels, which influenced Nitrite Reduction %. The fit statistics of the linear model displayed a high level of predictive accuracy, with an R2 value of 0.9544. The optimal conditions revealed through 3D surface analysis resulted in a significant Nitrite Reduction of 83.37%, emphasizing the effectiveness of the treatment process in addressing environmental pollution.
