(680f) Spatial Life Cycle Analysis of Soybean-Based Biodiesel Production in Indiana Using Process Modeling

Spatial Life Cycle Analysis (LCA) studies are vital for decision making as conventional LCAs utilize data that is representative of an average system with regards to life cycle stages, thus providing only an aggregate picture. For example, all regions may not use the same level of energy efficient production technology to produce a product and/or may use different raw materials to produce the same product. Such variations can lead to significant changes in the net impacts of different life cycle stages of a product. Therefore, it is important to account for the differences in impacts due to spatial variations in LCA studies. However, it is challenging to find spatial/ regional level life cycle inventory (LCI) data in the excising LCA databases. The more spatial desegregation desired, the more challenging it is to find data. To overcome this challenge, in this study, process modeling techniques were used to fill in the regional life cycle inventory data for performing a spatial LCA of biodiesel production from soybean in both north and central Indiana. Process models were developed for all the life cycle stages in the production process of soybean oil and soybean-based biodiesel for both central and northern regions of Indiana. The spatial LCI data for the soybean farming was available from the United States Department of Agriculture’s (USDA) regional datasets.

Once all the LCI data was acquired, the data was fed to SimaPro to integrate with upstream processes to perform a full scale LCA of producing a liter of biodiesel from both north and central Indiana biodiesel producers. The impact categories studied were global warming potential (kg CO2 eq) and freshwater eutrophication (kg P eq) using the 2008 US TRACI impact assessment method. The spatial LCA study made it possible to compare two different spatial scenarios of biodiesel production in two different regions of Indiana. With the analysis performed, it is possible to build a county level environmental impact distribution maps for soybean farming in Indiana. The results in the study show that the spatial distribution of environmental impacts of biodiesel production is sensitive to at least four factors: (1) fertilizer and water application rates for feedstock, (2) land usage, (3) distance to the processing plant, and (4) the available options for soybean farmers to sell their harvested soybeans. While the technology for biobased processing can be same, it can have different spatial impacts based on these factors.