COMET-farm use cases: GHG emission estimates from climate- smart practices and platform enhancement opportunities

To appropriately value climate change impacts caused by management practices in their business operations, agricultural land and supply chain managers need to understand how previous and future crop management choices affect GHG (greenhouse gas) balances at the field level. The USDA has recommended the COMET-Farm model for measuring, reporting, and verifying GHGs from farm activities. We posited that COMET-Farm could estimate the GHG changes expected from implementing climate-smart practices at the University of Illinois Urbana-Champaign’s research farm, South Farm, and provide estimates from practices already implemented at a private commercial farm in Alabama, Martin Farms. To achieve our objectives, we gathered 20 years of management data from both South Farms and Martin Farms and used COMET-Farm to simulate four alternative cropland management scenarios alongside the BAU (business-as-usual) scenario: switching from synthetic N fertilizer to manure, adding cover crops between regular cropping periods, transitioning from conventional tillage to no-till, and converting from a corn/soy rotation to perennial switchgrass. Results showed that converting from conventional systems to diversified systems had the potential to reduce GHG emissions by a maximum of 4.15 Mg CO2e ha-1yr-1 in UIUC’s evaluated scenarios and by 8.03 Mg CO2e ha-1yr-1 in Martin’s evaluated scenarios. UIUC’s South Farms BAU was calculated to be a net source of 0.29 Mg CO2e ha-1yr-1 by COMET-Farm, with evaluated scenarios ranging from a maximum net source of 3.4 Mg CO2e ha-1yr-1 for cover crops and a maximum net sink of -3.9 Mg CO2e ha-1yr-1 for switchgrass. Larkin’s Martin Farms BAU was calculated as a net sink of -0.81 Mg CO2e ha-1yr-1, with evaluated scenarios estimates ranging from a maximum net source of 0.88 Mg CO2e ha-1yr-1 for cover crops and a maximum net sink of -8.85 Mg CO2e ha-1yr-1 for the switchgrass scenario. Our study identified several major opportunities to improve the COMET-Farm platform and predictive ability, including a lack of clear model guidance and code errors, highlighting areas of opportunity for improved predictions with site specific data. Our assessment suggests that while existing evaluations are directionally valid, future work should consider these improvement areas to enhance the tool’s reliability and usability.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Crop Sciences

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2024

Author dc:creator

• Delaney, Killian

Contributors dc:contributor

• Heaton, Emily
• Davis, Adam
• Martin, Nicolas
• Becker, Talon
• Dokoohaki, Hamze

• Greenhouse Gases
• Comet-farm
• Carbon
• Models
• Opportunities
• Climate.

Statement dc:rights

• Copyright 2024 Killian Delaney

Language dc:language

eng, en

Handle dc:identifier

https://hdl.handle.net/2142/127336

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/127336