Comparative multifactor optimization of biochar from pyrolysis and gasification: A Taguchi – ANOVA - RSM framework for climate-resilient soil applications

Biochar is recognized as a multifunctional material for soil remediation, nutrient retention, and carbon sequestration, yet its performance depends on coupled effects between biomass composition and thermochemical processing conditions. Most studies optimize biochar using one-factor-at-a-time approaches or focus on a single feedstock–process combination, limiting the ability to identify robust production windows for targeted soil applications. This study emphasizes a statistically driven multi-factor optimization framework, integrating a Taguchi L36 orthogonal array with ANOVA and Response Surface Methodology to tailor biochars produced from energy-crop residues cultivated on degraded land. Corn, sorghum, and soybean were converted through pyrolysis, air gasification, and CO2 gasification at 700–1000°C. Four functional responses were evaluated: specific surface area, total pore volume, pH, and aromatic ordering. ANOVA identified the thermochemical conversion pathway as the dominant factor controlling the specific surface area and the pore volume, with CO2 gasification producing the highest textural development. Biomass type was the primary driver of alkalinity, while aromatic ordering showed only modest variation and no statistically significant main effects. Taguchi signal to noise ratio analysis and Response Surface Methodology further highlighted interaction-driven sensitivity regions and practical optimal windows, particularly under CO2 at 800°C and 900°C. Overall, this work provides a scalable decision framework for engineering biochars with tailored structural and chemical functionality for soil remediation.