Biochar, a carbon-rich material made from organic waste, is gaining attention for its ability to improve soils, clean water, and capture carbon. A new review in Biochar X highlights how machine learning (ML) is reshaping biochar research, making it faster, smarter, and more effective in tackling climate change.
By analyzing large datasets, ML models such as random forests and deep neural networks can predict biochar yield, surface area, and pollutant removal efficiency with over 90% accuracy. This reduces costly trial-and-error experiments and allows scientists to design biochars with tailored properties for environmental applications.
“Biochar has enormous potential as both a waste-to-resource pathway and a climate solution,” said corresponding author Tao Zhang of China Agricultural University. “Machine learning gives us powerful tools to accelerate its development and maximize its environmental benefits.”
The review finds that biochar use can cut greenhouse gas emissions by 20%–70% and sequester up to 90% of carbon , depending on production conditions. Beyond climate mitigation, engineered biochars are being applied to clean polluted water, remove heavy metals and organic contaminants, capture microplastics, and even strengthen construction and energy storage materials.
The authors note that challenges remain, including the need for better data sharing, standardized reporting, and closer collaboration between environmental scientists and AI experts. Emerging techniques such as deep learning, self-supervised learning, and life cycle assessment are expected to further enhance the role of biochar in achieving global carbon neutrality and supporting a circular economy.
“This integration of machine learning and biochar is a clear example of how digital technologies can drive green innovation,” Zhang said.
===
Journal reference: iang Y, Xie S, Abou-Elwafa SF, Mukherjee S, Singh RK, et al. 2025. Machine learning-enabled optimization of biochar resource utilization and carbon mitigation pathways: mechanisms and challenges. Biochar X 1: e002
https://www.maxapress.com/article/doi/10.48130/bchax-0025-0003
About the Journal:
Biochar X is an open access, online-only journal aims to transcend traditional disciplinary boundaries by providing a multidisciplinary platform for the exchange of cutting-edge research in both fundamental and applied aspects of biochar. The journal is dedicated to supporting the global biochar research community by offering an innovative, efficient, and professional outlet for sharing new findings and perspectives. Its core focus lies in the discovery of novel insights and the development of emerging applications in the rapidly growing field of biochar science.
Follow us on Facebook , X , and Bluesky .
Literature review
Not applicable
Machine learning-enabled optimization of biochar resource utilization and carbon mitigation pathways: mechanisms and challenges
11-Sep-2025