A new study indicates that expensive in-field soil sampling may not be required when focusing only on calculating soil carbon credits from farm conservation practices. This could be a major benefit for the agricultural carbon credit market.
A study led by researchers at the Agroecosystem Sustainability Center (ASC) at the University of Illinois Urbana-Champaign provides new insights for quantifying cropland carbon budgets and soil carbon credits.
The results, outlined in a paper published in the soil science journal Geoderma, could simplify the process for calculating soil carbon credits, which reward farmers for conserving soil carbon through crop rotation, no-tillage, cover crops, and other conservation practices that improve soil health.
Accurately calculating soil carbon credits and cropland carbon budgets is critical to assessing the climate change mitigation potential of agriculture as well as conservation practices. Those calculations are sensitive to local soil and climatic conditions, especially the initial soil organic carbon (SOC) stock used to initialize the calculation models.
However, various uncertainties exist in SOC stock datasets, and it’s unclear how that can affect cropland carbon budget and soil carbon credit calculations, according to lead author Wang Zhou, Research Scientist at the ASC and the Department of Natural Resources and Environmental Sciences (NRES) at Illinois.
In this study, researchers used an advanced and well-validated agroecosystem model, known as ecosys, to assess the impact of SOC stock uncertainty on cropland carbon budget and soil carbon credit calculation in corn-soybean rotation systems in the U.S. Midwest.
They found that high-accuracy SOC concentration measurements are needed to quantify a cropland carbon budget, but the current publicly available soil dataset is sufficient for accurately calculating carbon credits with low uncertainty.
“Uncertainty in SOC concentration measurements has a large impact on cropland carbon budget calculation, indicating novel approaches such as hyperspectral remote sensing are needed to estimate topsoil SOC concentration at large scale to reduce the uncertainty from interpolation. However, uncertainty in SOC concentration only has a slight impact on calculating soil carbon credits, suggesting solely focusing on quantifying soil carbon credit from additional management practices may not require extensive in-field soil sampling – an advantage considering its high cost,” Zhou said.
“The approach in this study can be applied to other models and used to assess important uncertainties of the carbon sequestration potential of various conservative land management practices,” said Bin Peng, the other primary author of the study and Senior Research Scientist at ASC and NRES.