A Consequential Comparative Life Cycle Assessment of Seitan and Beef

Meaningful sustainable consumption patterns require informed consumers who understand the actual impact of their actions on a quantitative and tangible basis. Life cycle assessment (LCA) is a tool well suited to achieving this goal, but has only been superficially applied to the analysis of plant-based diets. This analysis looks at a common component of plant-based meat alternatives: a wheat-based protein known as seitan, which is a common substitute for beef. A comparative consequential analysis shows the overall change in environmental impact when 1000 servings of seitan displace 1000 servings of beef. The functional unit for comparison is one serving of seitan or one serving of beef and the system boundaries include production but not distribution, consumption or disposal. Life cycles are created for seitan and beef in the LCA modeling software SimaPro and an analysis is run using the Eco-indicator 99 methodology. The beef life cycle is created using complete existing LCA data, while the seitan life cycle is created using LCA data for constituent materials and processes.

Findings indicate that beef is much more environmentally impactful than seitan, but the largest difference is found in land use change. Significant data quality and uncertainty issues exist due to the data being incomplete or not representative for US processes and the use of proxy processes to estimate industrial processing. This analysis is still useful as a screening tool to show rough differences in impact. It is noted that despite seitan having a lower environmental impact than beef, increasing seitan production will probably have the effect of increasing overall environmental impacts, as beef production is not likely to decrease as a result. Massive changes in consumer purchase patterns are required before reductions in impact can be expected. Recommendations for future work include expanding system boundaries and obtaining industry specific data for seitan production.