Client case study · Renewable fuels

Making Renewable Fuel Carbon Scores More Accurate with Field-Level Data

How Corvian helped a leading Canadian renewable fuel provider connect corn production practices to carbon intensity calculations and build the foundation for scalable, field-based reporting.

9,000+Acres of Ontario corn represented in field-level CI analysis
16Participating growers contributing detailed farm data
77%Average CI score attributed to fertilizer-related field and manufacturing emissions
The business challenge

Average crop scores miss what happens on individual farms.

Renewable fuel producers need credible agricultural carbon intensity data. But a single average score for a crop cannot capture how practices vary across farms.

Limited field-level visibility

Crop averages did not reflect differences in fertilizer use and other on-farm practices that affect carbon intensity.

Grower participation at scale

Collecting reliable, recurring farm data had to be practical for growers and respectful of sensitive information.

Evidence for regulatory discussions

The client needed a credible proof of concept to demonstrate how field-specific scoring could inform Canada’s Clean Fuel Regulations.

Project scale

More than 9,000 acres of corn. One connected view of field-level carbon intensity.

Corvian worked with 16 participating Ontario growers to capture detailed cornfield practices, convert agricultural activity into usable data, and calculate field-specific CI scores. The project demonstrated a more precise alternative to relying solely on provincial or crop-wide averages—without requiring the renewable fuel provider to build its own grower data infrastructure.

The Corvian solution

From farm practices to defensible carbon intensity analysis.

Corvian combined grower engagement, agricultural data collection, lifecycle analysis and secure information access into a single delivery approach.

01 / ENGAGE

Work with growers

Engaged 16 Ontario farmers and gathered detailed information about practices across more than 9,000 acres of corn.

02 / STRUCTURE

Collect field data

Used Corvian’s FarmCommand® platform to organize field-level information while restricting access to the client and regulators.

03 / CALCULATE

Model carbon intensity

Processed farm-specific inputs using OpenLCA lifecycle analysis to calculate CI scores reflecting actual agricultural practices.

04 / DEMONSTRATE

Support regulatory dialogue

Worked with the client to present findings to Canadian regulators and show the feasibility of field-based scoring.

Why fertilizer data matters

Fertilizer-related field emissions and upstream fertilizer manufacturing emissions represented an average of 77% of the calculated CI score in this project—highlighting a major area where better field data can inform improvement opportunities.

Project outcomes

A proof of concept with enterprise relevance.

The work established a practical basis for incorporating farm-level agricultural data into renewable fuel carbon intensity strategies, should the regulatory framework formally accommodate these methodologies.

More precise scoring

Demonstrated CI calculations informed by individual farm practices rather than a single crop average.

Controlled data access

Created a digital approach designed to protect grower information and build confidence in participation.

Path to wider adoption

Provided evidence to support future discussions about scaling field-based CI scoring across Canada.

Why this matters

Better agricultural data can change how renewable fuel performance is measured.

When field practices become part of the calculation, renewable fuel organizations gain a clearer understanding of the agricultural inputs behind carbon intensity. Corvian connects the growers, data infrastructure and analysis needed to make that possible.

Frequently asked questions

Field-based carbon intensity explained.

What is field-based carbon intensity scoring?

It calculates carbon intensity using data about practices on individual farms rather than relying only on a single average for an agricultural crop. The project applied this approach to Ontario corn production.

How can agricultural data help renewable fuel producers?

Field-level information can provide a more detailed picture of the agricultural emissions associated with feedstocks, helping producers evaluate CI assumptions and inform long-term strategy.

What was the scale of Corvian’s renewable fuels project?

The project involved 16 Ontario growers farming more than 9,000 acres of corn.

What role did fertilizer emissions play?

In the project’s calculations, fertilizer-related field and upstream manufacturing emissions accounted for 77% of the CI score on average.

Does this case study establish regulatory approval for field-level scoring?

No. It describes a proof of concept and discussions with Canadian regulators. The case study does not state that field-based scoring was formally approved for compliance use.

Connect with our team

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