Midwest Bioenergy Crop Landscape Laboratory (MBC-Lab): Capturing Spatio-temporal and Managerial Variations to Provide a Gold Standard Data and Platform for Validating Field-level Emission from Bioenergy Crops
This topic works to establish validation sites for field-level emissions quantification of agricultural bioenergy feedstock production. These teams will work towards the development of “ground truth” solutions to establish measurements and protocols for emissions monitoring at the field level to create publically available, open-source, high-resolution datasets to support testing and validation of emerging biofuel production monitoring technologies. The projects will also compliment selections in ARPA-E’s full SMARTFARM program, further supporting and validating the selections made through this full funding opportunity. Ethanol production is one of the largest consumers of domestic grain in the U.S., and developing sustainable production methods for ethanol and bio-based fuels has great potential to both reduce emissions and potentially provide a net emissions-free source of energy. While the economic and emissions impacts of ethanol production nationally are clear, field-level contributions remain unclear. The lack of understanding of field-level feedstock emissions, combined with the absence of economic incentives beyond yield, leaves feedstock producers to estimate and assume risks to their primary revenue stream by new management practices. By establishing sites and protocols for measuring the impact on yield increasing and emissions reducing technologies, these teams will bridge the technology gap between feedstock producers and existing market incentives to de-risk sustainable management practices, defray the cost of monitoring their impact, reduce biofuel feedstock production emissions, and broadly enable a future carbon farming industry.
Project Innovation + Advantages:
The University of Illinois will produce field-level emissions data from commercial bioenergy crops managed by Illinois farmers. The project team will 1) collect emissions data from three commercial bioenergy feedstock sites, using ground and remote sensing measurements, 2) develop protocols for data processing and storage, and an online portal for users to access emissions datasets, 3) develop cyberinfrastructure to enable emissions data visualization, including real-time eddy covariance data, in a timely manner, and 4) actively engage stakeholders regarding emissions data usage. The project will reduce energy-related emissions by enabling technology development for managing bioenergy crops, improving yield, reducing over-fertilization, and designing and validating remote sensors and decision support tools for smart farms.