Solutions and insights for agricultural monitoring, reporting, and verification (MRV) from three consecutive issuances of soil carbon credits

Regenerative agricultural practice adoption on conventionally managed fields has gained momentum as a climate mitigation strategy, given the ability of these practices to sequester carbon or reduce greenhouse gas emissions. However, the geospatial and temporal variability of the impact of specific practices, such as cover cropping or no-till, pose challenges for scalable quantification of emissions reduction and deploying incentives to drive increased adoption. To quantify impact while accounting for variability and uncertainty at scale, Indigo Ag created a monitoring, reporting, and verification (MRV) pipeline to produce agricultural soil carbon credits produced at large scales (hundreds of thousands of hectares). The pipeline ingests field data from enrolled farmers, checks data quality, uses hybrid soil sampling and biogeochemical modeling to produce estimates of emissions reduction and uncertainty, and then applies deductions based on calculated uncertainty and leakage to quantify total project-wide carbon credits and monitor for durability of carbon. The implementation of a carbon project (CAR1459) from 2018 to 2022 on 553,743 ha of U.S. cropland utilizing the pipeline is estimated to have reduced emissions by 398,408.5 tCO₂e, amounting to 296,662 tCO2e of soil carbon credits after uncertainty deductions. This paper explores the effect sizes associated with specific regenerative practice changes across the project domain. Cover cropping consistently resulted in a net positive climate impact and reduced emissions by 1.29 tCO₂e per hectare per year, on average. Introduction of no-till was more common in the project, but it had a lower average emissions reduction of 0.38 tCO₂e per hectare per year. Effect sizes for no-till vary spatiotemporally and are typically low in the first several years after adoption but increase in subsequent years. Agricultural carbon programs that capture and incentivize the nuance of outcomes of practices rather than the implementation of practices, can promote adoption of the right management practice to be deployed on the right field for maximum environmental benefit.