The Advanced Research Projects Agency-Energy (APRA-E) will award $16.5 million in funding for six projects as part of the Systems for Monitoring and Analytics for Renewable Transportation Fuels from Agricultural Resources and Management (SMARTFARM) program.

These projects will develop technologies that bridge the data gap in the biofuel supply chain by quantifying feedstock-related GHG emissions and soil carbon dynamics at the field-level. These technologies will allow for improved efficiency in feedstock production and enable new ag-sector carbon removal and management opportunities.

SMARTFARM teams will work to further develop the core technologies for our nation’s agricultural community to more efficiently support the biofuels supply chain, while enabling carbon markets to incentivize greater feedstock production efficiency and carbon management opportunities for producers.

—ARPA-E Director Lane Genatowski

SMARTFARM teams will work to design and develop systems to quantify feedstock production life cycle GHG emissions at the field level reliably, accurately, and cost-effectively. Selected projects are capable of delivering a positive return on investment when field-level carbon emissions reductions are connected to associated biofuel carbon markets.

The program also focuses on potential economic benefits to feedstock producers and future carbon management markets, potentially complementing yield-based revenues with incentives for input efficiency and restorative practices. This focus will also help to lay the groundwork for market structures to shift away from national averages and toward lower uncertainty field-based estimates for incentivizing efficiency and other services.

Working to make the biofuel supply chain carbon-negative through the removal or sequestration of carbon would greatly improve biofuel’s economic and environmental benefits. Achieving reductions in carbon emissions also encourages feedstock producers to adopt new technologies and practices to quantify their impact. SMARTFARM teams are working to develop robust quantification methods through these awards so that management practices can be linked to environmental and economic outcomes simultaneously.

Project descriptions:

• University of Illinois – Urbana. The “System of Systems” Solutions for Commercial Field-Level Quantification of Soil Organic Carbon and Nitrous Oxide Emission for Scalable Applications (SYMFONI) - $4,500,000
  Accurate and rapid field-level quantification of carbon intensity at a regional scale is critical to facilitate adoption of new technologies to increase the bioeconomy’s feedstock productivity and reduce its carbon footprint. The University of Illinois will develop a commercial solution, SYMFONI, to estimate soil organic carbon and the dynamics of nitrous oxide emissions at an individual field level. The solution can be scaled up to perform per-field estimates for an entire region. SYMFONI is a “system of systems” solution that integrates airborne-satellite remote sensing, process-based modeling, deep learning, atmospheric inversion, field-level sensing, and high-performance computing.

• University of Utah. Soil Organic Carbon Networked Measurement System (SOCNET) - $1,899,317
  The inability to measure on-the-spot underground carbon flux and storage within an economically sensible operation cost limits the accurate quantification of carbon sequestration, capture, loss, and storage necessary to achieve a carbon negative bioeconomy and biofuel supply chain. 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 sensor will enable high-accuracy and real-time decision data for cost-effective carbon removal, storage, and management.

• Soil Health Institute. A Rapid In-Field System to Measure Deep Soil C Stock and Flux - $3,250,609
  The Soil Health Institute aims to develop an integrated soil carbon measurement and monitoring system—the DeepC System—that meets current and future needs for carbon markets in agriculture. The system comprises three main components: in-field measurement hardware, an optimized spatial sampling algorithm to select measurement sites, and machine learning calibrations that leverage the current infrastructure of national soil spectroscopy libraries. As a system, these components synergistically allow a user to obtain rapid, non- destructive measurements of soil carbon stock.

• Princeton University. NitroNet: Smart System to Quantify Nitrous Oxide Emissions - $3,004,563
  Nitrogen management for agricultural production of crops, the primary source of nitrous oxide (N₂O), contributes approximately 4% of all greenhouse gases from the US annually. Quantifying these emissions, which are non-uniform in space and time, is a significant challenge at the field and farm scales. NitroNet is an autonomous sensing system designed to monitor N₂O emissions over an entire growing season at high spatial and temporal resolutions. By casting a virtual “net” over an entire field, NitroNet will monitor the non-uniform N₂O emissions within the field using atmospheric laser imaging. The total nitrogen loss over a growing season through N2O emissions will be quantified to inform practices that minimize the climate change impacts and environmental harms of agricultural crop production.

• Michigan Aerospace Corporation. DroN₂O: A Drone-Based System for Measuring Nitrous Oxide Emissions from Agricultural Fields - $1,967,446
  Michigan Aerospace Corporation proposes to develop an inexpensive system to sense nitrous oxide (N₂O) emissions from agricultural fields using laser-based sensors mounted on drones. These sensors include an optical absorption cell, a short-range miniature wind LiDAR, and a camera for plant health and ground assessment. The measurements from these sensors will be combined and processed with artificial intelligence-enabled software to accurately measure N₂O emissions from a given farm field during the entire growing season. The resulting data will provide farmers of bioeconomy feedstock crops with tangible incentives to alter farming practices in ways that reduce greenhouse gas emissions.

• Dagan, Inc. Integrating Sensors, Remote Sensing and DNDC Model for Quantifying GHG Emissions - $1,840,203
  Spatial and temporal variability of soil carbon stocks and environmental drivers that cause the production and flux of nitrous oxide (N₂O) across agricultural systems create challenges for cost effective quantification of N₂O emissions and soil carbon stock changes at scale. Dagan proposes to build, validate, and demonstrate an integrated system for reliable and cost-effective measurement of field-level soil carbon and N₂O emissions. This system will consist of the following four components: a field sampling and measurement system; subfield scale process modeling to improve the quantification of soil carbon and greenhouse gas emissions; a detailed model validation system for quantification of model uncertainty; and an operational platform for implementing the system at scale.