New biochar model could help farmers and policymakers make climate-smart agriculture more site-specific

A global study across 48 field sites shows that a new process-based model can predict how biochar affects crop yields, soil carbon, and greenhouse gas emissions under diverse real-world conditions.

Biochar, a carbon-rich material made by heating biomass in limited oxygen, has gained attention as a promising tool for climate-smart agriculture. It can help soils store carbon, retain nutrients and water, support crop production, and reduce greenhouse gas emissions. Yet one major question has remained difficult to answer: where, when, and how much biochar should be applied to achieve the best results?

A new study published in Biochar offers a step toward answering that question. Researchers developed and evaluated a process-based model called DLEM-Ag-Biochar, designed to simulate how biochar interacts with crops, soils, water, nitrogen, soil organic carbon, and greenhouse gas emissions. The model was tested using data from 48 globally distributed field experiment sites across 12 countries, covering four climate zones, 10 soil texture classes, six cropping systems, and 11 biochar feedstocks.

“Biochar is not a one-size-fits-all solution,” said corresponding author Dr. Wei Ren. “Its benefits depend strongly on local climate, soil texture, crop type, and application rate. Our goal was to develop a modeling tool that can help translate scattered field observations into practical, site-specific guidance.”

The model focused on three widely grown crops, maize, wheat, and soybean, which are central to global food production and well represented in existing biochar field datasets. It evaluated three key indicators of climate-smart agriculture: crop yield, soil organic carbon, and carbon dioxide emissions.

Overall, the model performed well against field observations. For crop yield, it achieved an R² of 0.78 across 418 observations. For soil organic carbon, it achieved an R² of 0.72 across 228 observations. For CO2 emissions, the model showed the strongest performance, with an R² of 0.91 across 88 observations. These results suggest that DLEM-Ag-Biochar can capture important patterns in how biochar affects agricultural systems under different environmental and management conditions.

The study also found that model accuracy varied by setting. Yield predictions were strongest in tropical and temperate climate zones, but less accurate in arid regions. The model also performed best on medium-textured soils, while predictions were less reliable on coarse soils. Crop type mattered as well, with model performance differing among maize, wheat, and soybean systems.

Application rate was another important factor. Medium biochar application rates produced the best yield simulations, while higher rates performed better for predicting soil organic carbon and CO2 emissions. This finding highlights the need to balance productivity, carbon storage, and emissions goals when planning biochar use.

“Farmers, land managers, and policymakers need tools that can compare outcomes before decisions are made in the field,” Dr. Ren said. “A model like DLEM-Ag-Biochar can help identify where biochar is most likely to improve yields, increase soil carbon, and contribute to climate mitigation.”

The researchers note that biochar affects agriculture through many linked pathways, including decomposition, priming effects on native soil organic matter, nitrogen mineralization and immobilization, soil pH, cation exchange capacity, ammonia adsorption, and soil water retention. By integrating these processes into one framework, the model provides a more comprehensive way to evaluate biochar as a climate-smart practice.

The study also underscores the importance of continued field monitoring. Long-term biochar experiments remain limited, especially across diverse climates, soils, and management systems. More field data will allow models to become more accurate and more useful for real-world decisions.

As agriculture faces growing pressure to produce more food while reducing climate impacts, site-specific biochar modeling could become an important tool for sustainable intensification and net-zero agricultural systems.

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Journal Reference: Ren, W., Kumar, Y. & Huang, Y. Global evaluation of a new biochar model for supporting climate-smart agriculture. Biochar 8, 95 (2026).   

https://doi.org/10.1007/s42773-026-00609-9   

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About Biochar

Biochar (e-ISSN: 2524-7867) is the first journal dedicated exclusively to biochar research, spanning agronomy, environmental science, and materials science. It publishes original studies on biochar production, processing, and applications—such as bioenergy, environmental remediation, soil enhancement, climate mitigation, water treatment, and sustainability analysis. The journal serves as an innovative and professional platform for global researchers to share advances in this rapidly expanding field. 

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