There is an increasing need for life cycle data for bio-based products, which becomes particularly evident with the recent drive for greenhouse gas reporting and carbon footprinting studies. Meeting this need is challenging given that many bio-products have not yet been studied by life cycle assessment (LCA), and those that have are specific and limited to certain geographic regions.
In an attempt to bridge data gaps for bio-based products, LCA practitioners can use either proxy data sets (e.g., use existing environmental data for apples to represent pears) or extrapolated data (e.g., derive new data for pears by modifying data for apples considering pear-specific production characteristics). This article explores the challenges and consequences of using these two approaches. Several case studies are used to illustrate the trade-offs between uncertainty and the ease of application, with carbon footprinting as an example. As shown, the use of proxy data sets is the quickest and easiest solution for bridging data gaps but also has the highest uncertainty. In contrast, data extrapolation methods may require extensive expert knowledge and are thus harder to use but give more robust results in bridging data gaps. They can also provide a sound basis for understanding variability in bio-based product data. If resources (time, budget, and expertise) are limited, the use of averaged proxy data may be an acceptable compromise for initial or screening assessments. Overall, the article highlights the need for further research on the development and validation of different approaches to bridging data gaps for bio-based products.