Pesticide pollution is a major environmental concern. Biochar adsorption offers a sustainable remediation method, but optimal conditions vary. This study uses ensemble machine learning (CatBoost, LightGBM, RF) on a literature database to predict biochar's pesticide adsorption efficiency. Textural properties of biochar, pesticide concentration, and dosage were significant factors. Data-driven modeling provides an empirical approach to optimizing biochar use for water purification in agriculture.
