Use of LCA as a development tool within early research: challenges and issues across different sectors

The aim of this paper is to highlight the challenges that face the use of life cycle assessment (LCA) for the development of emerging technologies. LCA has great potential for driving the development of products and processes with improved environmental credentials when used at the early research stage, not only to compare novel processing with existing commercial alternatives but to help identify environmental hotspots. Its use in this way does however provide methodological and practical difficulties, often exacerbated by the speed of analysis required to enable development decisions to be made. Awareness and understanding of the difficulties in such cases is vital for all involved with the development cycle. This paper employs three case studies across the diverse sectors of nanotechnology, lignocellulosic ethanol (biofuel), and novel food processes demonstrating both the synergy of issues across different sectors and highlighting the challenges when applying LCA for early research. Whilst several researchers have previously highlighted some of the issues with use of LCA techniques at an early stage, most have focused on a specific product, process development, or sector. The use of the three case studies here is specifically designed to highlight conclusively that such issues are prevalent to use of LCA in early research irrespective of the technology being assessed. The four focus areas for the paper are system boundaries, scaling issues, data availability, and uncertainty. Whilst some of the issues identified will be familiar to all LCA practitioners as problems shared with standard LCAs, their importance and difficulty is compounded by factors distinct to novel processes as emerging technology is often associated with unknown future applications, unknown industrial scales, and wider data gaps that contribute to the level of LCA uncertainty. These issues, in addition with others that are distinct to novel applications, such as the challenges of comparing laboratory scale data with well-established commercial processing, are exacerbated by the requirement for rapid analysis to enable development decisions to be made. Based on the challenges and issues highlighted via illustration through the three case studies, it is clear that whilst transparency of information is paramount for standard LCAs, the sensitivities, complexities, and uncertainties surrounding LCAs for early research are critical. Full reporting and understanding of these must be established prior to utilising such data as part of the development cycle.