Phenolic pollution is very common, and toxic and water-soluble compounds and their derivatives can have significant harmful effects on humans, aquatic life, and the environment. The adsorption method is the most efficient way of handling, but the high cost of biosorbents obstructs the feasibility of this approach. In this study, biomass waste derived from Palm-oil shells is synthesized as an eco-friendly biosorbent for phenol adsorption. A novel inverse modelling method based on differential evolution optimization (DEO) is used to estimate the isotherm and kinetic model parameters, which facilitates to identify the inherent mechanisms in the adsorption process for removing phenol from wastewater. The DEO based model parameters provides an accurate prediction that is very close to experimental data, thus resulting in higher regression coefficient, R^2, and relatively low Pearson’s Chi-square, χ²& root mean square error (RMSE). Phenol adsorption found to be following Langmuir isotherm (R² = 0.995; χ² = 0.429; RMSE = 4.420) and Pseudo 2nd order kinetic model (R² = 0.992; χ² = 0.346; RMSE = 15.58). With a biosorbent size of 0.85 mm resulted in phenol removal efficiency of 98 %. For large scale industrial process, a design methodology is developed to estimate the amount of biosorbent (Palm-oil shell-based GAC) required to meet the desired phenol removal concentration.

酚类污染非常普遍，有毒和水溶性化合物及其衍生物可能对人类，水生生物和环境产生重大危害。吸附法是最有效的处理方法，但是生物吸附剂的高成本阻碍了这种方法的可行性。在这项研究中，从棕榈油壳中提取的生物质废物被合成为一种用于苯酚吸附的生态友好型生物吸附剂。提出了一种基于微分进化优化（DEO）的逆建模方法来估计等温线和动力学模型参数，这有助于确定吸附过程中从废水中去除苯酚的内在机理。基于DEO的模型参数可提供与实验数据非常接近的准确预测，从而导致较高的回归系数，[R ^2，和相对低的Pearson卡方，χ ²＆根均方误差（RMSE）。苯酚吸附发现以下Langmuir等温（- [R ² = 0.995;χ ² = 0.429; RMSE = 4.420）和伪第二阶动力学模型（- [R ² = 0.992;χ ² = 0.346; RMSE = 15.58）。生物吸附剂尺寸为0.85毫米，苯酚去除效率为98％。对于大规模工业过程，开发了一种设计方法来估算满足所需的苯酚去除浓度所需的生物吸附剂（基于棕榈油壳的GAC）的量。