Applying an iterative prospective LCA approach to emerging wood-based technologies: three German case studies

Abstract

AbstractPurposeThe innovative utilization of hardwood as a future material resource can contribute to a wood-based bioeconomy. Many hardwood-based products are still at the developmental stage, so it is crucial to assess and improve their environmental performance now. Given the lack of knowledge about future conditions, and accounting for potential changes in emerging technologies at an industrial scale, mean that many parameters must be considered.MethodsA stepwise approach for prospective LCA has been refined, resulting in two LCA iterations. In the first iteration, a preliminary prospective LCA was conducted to understand the emerging technology, using an uncertainty analysis to identify the most influential parameters. The results were incorporated in the second LCA iteration, the final prospective LCA, to develop future scenarios based on the identified parameters. The approach is applied to three case studies that cover the range of technological readiness levels (TRL) from laboratory to pilot and industrial scale. The first case study is a lignin-based phenol–formaldehyde (LPF) adhesive (TRL 4). The second case study is a hardwood glued-laminated (glulam) load-bearing beam (TRL 7). The third case study is a cellulose-based viscose fiber for clothing (TRL 9).Results and discussionNumerous parameters were narrowed down to a few parameters important for the scenarios; from 25 to 4 in the LPF adhesive case study, from 5 to 2 in the glulam case study, and from 24 parameters to 3 in the viscose fiber case study. The LCIA scenario results for climate change showed differences based on the effects of the important scenario-related parameters, such as the total energy demand or the renewable energy share in foreground and background systems. The LCIA scenario results for land use depend on the amount of wood input and the size of the allocation factor, which was also shown in the local sensitivity analyses. Their variation significantly affected the land use, while having a negligible effect on the other impact categories.Conclusions and recommendationsThe prospective LCIA results for climate change depend mostly on the energy demand for the manufacture of emerging hardwood-based products. The effects of a high energy demand cannot be compensated for by inputting a higher share of renewable energy production, neither for on-site production nor in the electricity mix. To reduce the climate change impacts, it is crucial to reduce the overall energy demand of the product system. The results for land use are not robust against variations of the allocation factors. Local sensitivity analyses of different allocation methods are recommended. Overall, the inclusion of an uncertainty analysis in the first iteration of the prospective LCA can reduce complexity for the scenario development, especially when the emerging technology to be evaluated presents with a high number of uncertain parameters.