Estimating the Carbon Footprint: Biodiesel and Soy-Based Products in Minnesota

Background

Minnesota has one of the highest biofuels use rates in the US. The Minnesota B20 mandate places both a floor and ceiling on biofuel mixing levels at 5% and 20%, respectively, and affects most diesel within the state. The Minnesota Soybean Research and Promotion Council (MSR&PC) hired HEI to identify the greenhouse gas (GHG) emission differences between regular diesel and biodiesel at various mixing rates in Minnesota. We also looked at how soybean use in consumer products affects their life cycle emissions.

The Project

This project had two parts. First, we investigated the net difference between mixing rates of biofuel into diesel compared to conventional diesel. Secondly, we looked at how the use of soy-based products (such as car tires and animal feed) affect carbon emissions of consumer products created from Minnesota soybeans.

Our scientists completed a life cycle analysis for biodiesel, which took into consideration all aspects of soybean production, processing, land use change, biodiesel production, and consumption. After the emission factor for creating soy-based biofuel in Minnesota was known, it could be directly compared to the production of conventional diesel.

To determine the actual real life reduction potential of biodiesel compared to that of conventional diesel, we used the mixing schedule for biodiesel to create a monthly consumption rate where the biodiesel was apportioned out accurately. This project looked at mixing rates ranging from 5-20% to show the positive impact that using sustainably grown soybeans in Minnesota can have a role in reducing carbon emissions.

We completed a life cycle review on two consumer products (car tire, glycerin) and one soybean coproduct (animal feed, soybean meal) and compared it to their non-soy-based product. The three products received a modeled carbon intensity value to show their impact within the supply chain. In the case of soy-based tires, a comparison to a traditional rubber-based tire was shown.

We used the GREET model to develop the biodiesel carbon intensity (CI) score, and literature reviews supported the findings and methodology of the life cycle analysis for consumer products and biodiesel.

This project provided CI scores for biodiesel for Minnesota and a valuable comparison with traditional fuels. Additionally, the report provided valuable information about how CI scores vary by management practice and region. Finally, the study demonstrated how reduction in soybean feedstock CI could result in a reduction of CI scores for biofuels. These results provided valuable information on how soybeans and biofuels can be a carbon asset to the biodiesel plant, which could be managed as a credit within the biodiesel supply chain (i.e., insets) or exchange outside of the supply chain (i.e., offsets).