Regenerative agriculture, or “carbon farming,” is the use of agricultural practices and crops that draw down excess atmospheric carbon through photosynthesis, and store it in biomass and soils over the course of decades. Though carbon constantly cycles through the soil due to active nutrient processes, regenerative agriculture seeks to deliver additional carbon inputs to the soil, which can result in the net accumulation and storage of carbon in soil. Practically, this net accumulation can be achieved through agricultural practices like cover cropping, no-till farming, and agroforestry.
Studies have estimated that, at scale, carbon farming could pull enough carbon out of the atmosphere to offset 10% of annual anthropogenic carbon emissions. Given broad recognition of the need for significant atmospheric carbon removal in addition to aggressive emissions reductions, carbon farming is seen as a promising climate response. Furthermore, carbon farming can result in significant agricultural and ecological co-benefits, like improved soil structure, a robust soil microbiome, and better water retention, all of which bolster agriculture’s climate change resilience.
Economic, policy-based, and social programs can provide the financial incentives to motivate widespread implementation of carbon farming practices. Farmers could participate in voluntary carbon markets, selling carbon credits that represent the soil carbon accumulated through regenerative farming practices. Government policy initiatives could reward carbon farming through subsidy or grant programs. Consumers could reward “low-carbon” or “carbon-neutral” products through their purchasing decisions.
However, the difficulty of getting standardized, comprehensive, and accurate soil carbon measurements is a major impediment to the wider development of these programs. Traditional soil carbon monitoring techniques are slow and invasive: they require extracting soil cores that are shipped to a lab, and analyzed using expensive analytical chemistry methods. This sensing pipeline can take days or weeks and currently makes it impractical to run soil carbon incentives initiatives at scale.
Thus, our group is starting to investigate sensing techniques and systems to address the challenge of scalable soil carbon sensing. We are looking systems that use data fusion to integrate farm-based sensor data, satellite imagery, and environmental modeling in order to provide fast, cheap, and accurate carbon estimation at scale.