ARPA-E funds 6 projects supporting the biofuels supply chain

By Erin Voegele | September 08, 2020

The U.S. Department of Energy’s Advanced Research Projects Agency-Energy on Sept. 1 announced the award of $16.5 million for six projects that aim to bridge the data gap in the in the biofuel supply chain by quantifying feedstock-related greenhouse gas (GHG) emissions and soil carbon dynamics at the field-level.

The selected projects were awarded funding as part of the Systems for Monitoring and Analytics for Renewable Transportation Fuels from Agricultural Resources Management (SMARTFARM) program.

According to ARPA-D, the funded projects will allow for improved efficiency in feedstock production and enable new ag-sector carbon removal and management opportunities, and are capable of delivering a positive return on investment when field-level carbon emissions reductions are connected to associated biofuel carbon markets. The agency noted the SMARTFARM program also focuses on potential economic benefits to feedstock producers and future carbon management markets. As a result yield-based revenues could potentially be complemented with incentives for input efficiency and restorative practices.

 “Biofuel production is a growing asset to many aspects of the American energy generation landscape,” said ARPA-E Director Lane Genatowski. “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.”

Projects selected for SMARTFARM awards include:

University of Illinois, $4.5 million: The University of Illinois will develop a commercial solution, known as SYMFONI to estimate soil organic carbon and the dynamics of nitrous oxide emissions at an individual field level. SYMFONI is a “system of system” solution that integrates airborne-satellite remote sensing, process-based modeling, deep learning, atmospheric inversion, field-level sensing and high-performance computing.  The solution can be scaled up to perform per-field estimates for an entire region.

University of Utah, $1.9 million: The University of Utah aims to develop and deploy a distributed carbon sensor system that is buried in the soil, capable of locally stimulating a surrounding volume of soils at multiple depths, and sensing carbon and carbon influx at ultra-low operational cost. The senor will enable high-accuracy and real-time decision data for cost-effective carbon removal, storage and management.

Soil Health Institute, $3.25 million: The Soil Health Institute aims to develop an integrated soil carbon measurement and monitoring system that meets current and future needs for carbon markets in agriculture. The system, known as the DeepC System, includes in-field hardware, an optimized special sampling algorithm to select measurement sites, and machine learning calibrations that level the current infrastructure of national soil spectroscopy libraries to allow users to obtain rapid, non-destructive measurements of soil carbon stock.

Princeton University, $3 million: Princeton University Is developing NitroNet, an autonomous sensing system designed to monitor nitrous oxide over an entire growing season at high spatial and temporal resolutions. The system casts a virtual net over an entire field using atmospheric laser imaging to monitor the non-uniform nitrous oxide emissions within the field. Total nitrogen loss over a growing season through nitrous oxide emissions will be quantified to inform practices that minimize the climate change impacts and environmental harms of agricultural crop production.

Michigan Aerospace Corp., 1.97 million: Michigan Aerospace Corp. aims to develop a drone-based system to sense nitrous oxide emissions from agricultural fields using laser-based sensors that include an optical adsorption cell, a short-range miniature wind LiDAR, and a camera for plant health and ground assessment. The measurements from the sensors will be combined and processed with artificial intelligence-enabled software to accurately measure nitrous oxide emissions from a given farm field during the entire growing season. The resulting data will provide farmers with tangible incentives to alter farming practices in ways that reduce GHG emissions.

Dagan Inc., 1.84 million: Dagan proposes to build, validate and demonstrate an integrated system for reliable and cost-effective measurement of field-level soil carbon and nitrous oxide emissions that consists of a field sampling and measurement system, subfield scale process modeling to improve the quantification of soil carbon and GHG emissions, a detailed model validation system for quantification of model uncertainty, and an operational platform for implementing the system at scale.

Additional information is available on the ARPA-E website



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