Accurate measurement of soil organic carbon (SOC) is a major bottleneck for results-based payments in smallholder carbon projects. Measurement error can distort carbon estimates and undermine fair and credible payments, making smart combinations of measurement, aggregation, and payment mechanisms essential.

In a newly published study, Schlling et al. (2026) analyze how different SOC measurement approaches perform in practice, using data from 151 smallholder plots in Western Kenya. The authors find substantial inconsistencies between portable soil scanners and laboratory analyses, as well as only moderate agreement across laboratories. These measurement errors can lead to large distortions in estimated carbon stock changes and, in smallholder settings, may render individual-level results-based payments unfeasible. Simulations, however, indicate that aggregating farmers into larger groups can substantially reduce random measurement error, while targeted improvements in measurement accuracy are needed to address systematic biases.

Key implications for carbon project design: viable and scalable soil carbon projects for smallholders require improved SOC measurement accuracy, explicit consideration of measurement uncertainty, and MRV systems that combine group-level soil sampling with activity-based monitoring at the individual level. Carbon markets can support food systems transformation, but only if MRV systems are designed to reflect the realities of measurement uncertainty.

Journal of Environmental Management 398 (2026): Reliability of approaches for measuring soil organic carbon and implications for results-based payments for smallholder carbon farming – ScienceDirect