Biochar has been explored as a sorbent for contaminants, soil amendment and climate change mitigation tool through carbon sequestration. Through the optimization of the pyrolysis process, biochar can be designed with qualities to suit the intended uses. Biochar samples were prepared from four particle sizes (100–2000 µm) of three different feedstocks (oak acorn shells, jift and deseeded carob pods) at different pyrolysis temperatures (300–600 °C). The effect of these combinations on the properties of the produced biochar was studied. Biochar yield decreased with increasing pyrolysis temperature for all particle sizes of the three feedstocks. Ash content, fixed carbon, thermal stability, pH, electrical conductivity (EC), specific surface area (SSA) of biochar increased with increasing pyrolysis temperature. Volatile matter and pH value at the point of zero charge (pH_pzc) of biochar decreased with increasing pyrolysis temperature. Fourier-transform infrared spectroscopy (FTIR) analysis indicated that the surface of the biochar was rich with hydroxyl, phenolic, carbonyl and aliphatic groups. Methylene blue (MB) adsorption capacity was used as an indicator of the quality of the biochar. Artificial neural networks (ANN) model was developed to predict the quality of the biochar based on operational conditions of biochar production (parent biomass type, particle size, pyrolysis temperature). The model successfully predicted the MB adsorption capacity of the biochar. The model is a very useful tool to predict the performance of biochar for water treatment purposes or assessing the general quality of a design biochar for specific application.

生物炭已被研究出通过碳封存作为污染物，土壤改良剂和减缓气候变化工具的吸附剂。通过热解工艺的优化，可以设计出适合所需用途的生物炭。生物炭样品是在三种不同的热解温度（300–600°C）下，由三种不同原料（橡子橡壳，裂谷和去籽的角豆荚）的四种粒径（100–2000 µm）制备的。研究了这些组合对所生产生物炭的性能的影响。对于三种原料的所有粒径，生物炭产率都随着热解温度的升高而降低。生物炭的灰分含量，固定碳，热稳定性，pH，电导率（EC），比表面积（SSA）随着热解温度的升高而增加。生物炭的_pzc）随着热解温度的升高而降低。傅里叶变换红外光谱（FTIR）分析表明，生物炭的表面富含羟基，酚基，羰基和脂肪族基团。亚甲基蓝（MB）的吸附容量用作生物炭质量的指标。开发了人工神经网络（ANN）模型，以根据生物炭生产的运行条件（母体生物质类型，粒径，热解温度）预测生物炭的质量。该模型成功预测了生物炭的MB吸附能力。该模型是非常有用的工具，可预测用于水处理目的的生物炭的性能或评估特定用途的设计生物炭的总体质量。