Research could simplify process for calculating soil carbon credits
Study led by the University of Illinois Agroecosystem Sustainability Center provides new insights for quantifying cropland carbon budgets and credits, two important metrics for mitigating climate change
Peer-Reviewed PublicationIMAGE: ILLUSTRATION OF SOIL CARBON CREDITS CALCULATION BASED ON PROCESS-BASED MODELS. THE UNCERTAINTY IN THE CALCULATED CARBON CREDITS IS MUCH SMALLER THAN THE UNCERTAINTY IN THE INITIAL SOIL CARBON STOCK. SOURCE: GEODERMA view more
CREDIT: GEODERMA
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, two important metrics for mitigating climate change.
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. The project was funded by the U.S. Department of Energy’s Advanced Research Projects Agency-Energy (ARPA-E).
Agricultural activity causes a significant amount of soil organic carbon (SOC) to be released into the atmosphere as carbon dioxide, a greenhouse gas that contributes to climate change. Several conservation practices have been suggested to help sequester that carbon in the soil, but their potential to enhance the total SOC in a soil profile, known as SOC stock, needs to be assessed locally. Such assessments are key to the emerging agricultural carbon credit market.
Accurately calculating cropland carbon budgets and soil carbon credits 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 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 to accurately calculate carbon credits with low uncertainty.
“This is a very important study that reveals counter-intuitive findings. Initial soil carbon data is very important for all the downstream carbon budget calculation. However, carbon credit measures the relative soil carbon difference between a new practice and a business-as-usual scenario. We find that the uncertainty of initial soil carbon data has limited impacts on the final calculated soil carbon credit,” said ASC Founding Director Kaiyu Guan, Blue Waters Professor in NRES and the National Center for Supercomputing Applications (NCSA) at Illinois and lead of the DOE-funded SMARTFARM project at iSEE, which featured several co-authors on this paper.
The results indicate that expensive in-field soil sampling may not be required when focusing only on quantifying soil carbon credits from farm conservation practices – a major benefit for the agricultural carbon credit market.
“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 soil carbon credit calculation, 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.
The ASC was jointly established by the Institute for Sustainability, Energy and Environment (iSEE), the College of Agricultural, Consumer and Environmental Sciences (ACES), and the Office of the Vice Chancellor for Research and Innovation at Illinois.
Co-authors on the study included ASC Associate Director Andrew Margenot, Assistant Professor of Crop Sciences; DoKyoung Lee, Professor of Crop Sciences and ASC founding faculty member; Even DeLucia, Professor Emeritus of Plant Biology and ASC founding faculty member; Sheng Wang of ASC and NRES Research Assistant Professor; Ziqi Qin of ASC and graduate student in NRES; NRES Professor Michelle Wander; Jinyun Tang, Staff Scientist of the Earth and Environmental Sciences Area, Lawrence Berkeley National Laboratory; Zhenong Jin, Assistant Professor in the Department of Bioproducts and Biosystems Engineering, University of Minnesota; and Robert Grant, Professor in the Department of Renewable Resources, University of Alberta, Edmonton, Canada.
JOURNAL
Geoderma
METHOD OF RESEARCH
Computational simulation/modeling
SUBJECT OF RESEARCH
Not applicable
ARTICLE TITLE
How does uncertainty of soil organic carbon stock affect the calculation of carbon budgets and soil carbon credits for croplands in the U.S. Midwest?
ARTICLE PUBLICATION DATE
1-Jan-2023
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