University of Utah

The University of Utah aims to develop and deploy a distributed carbon sensor system that is buried into the soil, capable of locally stimulating a surrounding volume of soils at multiple depths, and sensing carbon and carbon flux at ultra-low operational cost. The sensors will enable high-accuracy and real-time decision data for cost-effective carbon removal, storage, and management to promote climate change mitigation via agriculture and managed land systems. The team aims to develop (1) a UV-based non-destructive CO2 sampling technique, (2) low-cost, wideband, and high-selectivity CO2 sensors, enabling accurate quantification of CO2 among gas mixtures (3) an artificial intelligence-based auto-calibration technique by combining environmental information and infrared spectra to quantify the sensor data, (4) machine learning-based geo-statistical mapping of CO2 distribution and flux over time, with an operational cost of <$10/acre/year on a commercial scale.

Reducing the uncertainty of emissions quantification is critical to realizing the revenue potential of carbon management markets.