Rsm-optimized biochar production from young coconut waste (Cocos nucifera): multivariate analysis of non-linear interactions between temperature, time, and activator concentration

Organic waste, particularly from young coconut husks, comprises over 60 % of landfill material, presenting significant environmental challenges. This study presents a biochar production method that integrates Response Surface Methodology (RSM) to optimize the carbonization process. The optimization framework uncovers non-linear interactions between carbonization temperature, duration, and KOH concentration, improving prediction accuracy. Carbonization temperature emerged as the most influential factor, with the optimal conditions, 400°C, 165.8 min, and 4.07 M KOH, yielding biochar with an iodine number of 1398.2 mg/g and an MB adsorption efficiency of 93.9 %. The enhanced model achieved an attractiveness index of 90.2 %, a significant improvement compared to conventional methods (84.5 %). Validation experiments confirmed the model's precision, with actual results closely matching predictions: a biochar yield of 25.7 %, an iodine number of 1395.7 mg/g, and MB adsorption of 94.3 %, all within a variance of less than 2 %. This represents a nearly identical iodine number, with only a 0.2 % difference, and a 6.3 % improvement in MB adsorption capacity compared to commercial biochar. This approach significantly advances biochar production from young coconut waste and expands its applications in sustainable waste management.

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