• FD-CIC Tool 2021 - Spreadsheet (4.6 MB xlsx)
• User Guide for FD-CIC Tool 2021 (975 KB pdf)



Note: If experiencing any issues when loading the stochastic module, please follow the instruction below:
Open FD-CIC tool -> Go to File -> Go to Options -> Go to Add-ins -> Scroll down to Bottom section “Manage: Excel Add-ins” and click “Go…” -> Click “Browse” and select the “STOCHASTIC.xla” file in your local GREET folder -> Click “OK”-> Save the new version on your local drive

Technical contact: Xinyu Liu ([email protected])

• FD-CIC Tool 2020 rev.1 - Spreadsheet (Standalone version) (12.6 MB xlsx)
• FD-CIC Tool 2020 - Spreadsheet (Standalone version) (12.6 MB xlsx)

U.S. Department of Energy’s Advanced Research Projects Agency–Energy (ARPA-E) has supported the Systems Assessment Center of the Energy Systems Division at Argonne National Laboratory to examine carbon intensity (CI) variations of different farming practices to grow agricultural crops for biofuel production and further develop a transparent and easy-to-use tool to calculate feedstock-specific, farm-level CI of biofuel feedstock. The tool uses life cycle inventory (LCI) data of key farming inputs from the Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET) fuel-cycle model. The system boundary of FD-CIC covers the cradle-to-farm-gate activities, including upstream emissions related to farming input manufacturing and feedstock production.

• Expanded the tool’s capabilities by including additional feedstocks such as soybeans, sorghum, and rice, besides corn
• Updated N2O emission factors for corn farming considering different climate zones and novel nitrogen management practices
• Updated soil organic carbon (SOC) look-up table by attributing the total SOC changes estimated from corn-soybean rotation to corn and soybean, separately, and generating feedstock-specific and county-level SOC changes for the United States
• Levelized the stochastic modelling capacity of the GREET model to perform uncertainty analysis in FD-CIC tool
• Incorporated CH4 emission factors derived from the IPCC 2019 report for rice cultivation under various water management regime

• Dynamic version: The dynamic version interacts with the GREET fuel cycle model by directly reading the LCI data of key farming inputs from the model. The dynamic version suits well when users want to change the default settings of the GREET model as related to farming inputs. The dynamic version is included in the GREET Excel release package.
• Standalone version: The standalone version suits well for users who are not familiar with the GREET model and contains the default LCI data for key farming inputs from the GREET model.

• X. Liu, H. Kwon, D. Northrup, M. Wang. Sustainable farming practices to potentially lower carbon intensity of feedstock production for biofuels. Environmental Research Letters. DOI: https://doi.org/10.1088/1748-9326/ab794e
• X. Liu, H. Kwon, M. Wang. Varied farm-level carbon intensities of corn feedstock help reduce corn ethanol greenhouse gas emissions. Environmental Research Letters. DOI: https://doi.org/10.1088/1748-9326/ac018f