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1. Introduction Life cycle assessment is a powerful tool for quantifying the environmental impacts of products and services and is an essential part of product development. It can, for example, be used to identify hotspots to find ways to keep environmental impacts as small as possible. Assessing a product or service under development requires a prospective approach. A problem in prospective life cycle assessment (pLCA) is, however, the lack of data, which can lead to inconclusive results. The prospective context, however, also implies that there is still room for process changes and improvements [1]. This paper will present a work procedure for pLCA that grew out of a multi-year project aimed at developing lignin-based carbon fibres for composites (see LIBRE [2]). The intention with this contribution is to provide practitioners guidance on how LCAs in early stages of material development can be handled. 2. Method:The development ofa work procedure for pLCA When starting the LIBRE project, there were no data available for the production of the fibres, and efforts needed to be made to: 1) identify hotspots in the life cycle of carbon fibre composites to show the possible influence of transitioning to a lignin-based fibre, and 2) identify other important routes for decreasing the environmental impact of the composite. This was then done by developing a meta-analysis framework for using results found in available literature on LCAs of carbon fibre reinforced polymers (CFRP) and of lignin production. The results found in the literature were carefully extracted and recalculated to the same functional unit to enable comparisons between studies. The meta-analysis found that a shift to lignin could decrease the environmental impact of carbon fibre composites, but that this is heavily dependent on the allocation approach used to allocate the impacts between co-products at a mill where the lignin is produced. The meta-analysis also identified recycling and recovery of fibres as promising, but that this also is very dependent on how allocation is handled, in this case allocation between life cycles [3]. To explore the influence of the allocation approach for lignin production, allocation approaches found in literature were applied to a case study of the climate impact of lignin extracted from a Kraft pulp mill (see Hermansson et al. [4] for details). In addition, two new allocation approaches were developed: 1) considering the impacts from the lignin extraction process in a subdivision style approach, and 2) partitioning the impacts of the system between energy streams and material streams based on mass conversion, followed by either energy allocation (for energy streams) or mass allocation (for material streams). Results showed that the climate impact of the lignin is highly sensitive to the choice of allocation approach. As the intention was to apply the allocation approaches in a pLCA, they were assessed based on sensitivity to changes in demand for lignin, as this is an aspect of this specific system that could change much over time. The outcome was that many allocation approaches are sensitive to the temporal settings of the study, in particular with regard to prices and/or what is considered the main reason for lignin being extracted from the mill. The influence of allocation approaches in recycling of CFRP was also assessed in a case study. Different allocation approaches were redefined to handle the multiple outputs of both polymer and fibre from composite recycling. The redefined allocation approaches were applied to different fictitious recycling systems that employed different recycling methods. Results showed that the outcome of the assessment is highly dependent on the inherent incentives for recycling in the allocation approaches. For example: The cut- off approach provides no incentive to recycle the product, whereas the end-of-life recycling approach and the circular footprint formula (CFF) do. Recommendations were to, if possible, include both the end-of-life recycling approach and the cut-off approach as two extremes in pLCAs, as the result of the case study showed a large sensitivity to quality and demand for recycled carbon fibres. The CFF, which can be seen as a compromise between the two other allocation approaches but that is dependent on information on the supply and demand for secondary material and therefore challenging to apply in a prospective context, can then be avoided [5]. When different technology routes and allocation approaches had been identified, the findings were applied in a case study of carbon fibre composites in road vehicles (see Hermansson et al. [6]). The technology routes were assessed both separately and grouped into coherent scenarios, as it is likely that some technology development routes will happen simultaneously [7]. By assessing them separately, the individual routes that are most promising for decreasing the environmental impact of the system could be identified. By assessing them together, it was possible to assess under which overarching conditions in society, for example due to aspects related to legislation or R&D funding, the environmental impact would be reduced the most. The end-result, where carbon fibre composites reduced the vehicles’ environmental impact in almost all futures [6], should be seen as an indication of the possible future environmental impacts of the system under study and can provide guidance to technology development. 3. Results,Discussion, and Conclusions The work procedure that grew out of the work in the LIBRE project is visualized in Figure 1. The procedure proved useful for tackling the issue of lack of data in early stages of materials development and helped identifying key parameters in both the technical development and in the surrounding world that would have a large influence on the end result. Figure 1: The procedure for prospective life cycle assessment in materials development, which grew out of the context of assessing carbon-fibre composites Key findings include the usefulness of mining and extracting LCA results from available literature to identify the most important parameters in early stages of materials developments. They also include recommendations on how allocation should be handled for both multi-output processes and recycling systems in pLCAs, also including some new options for multi-output processes. While the procedure was initially used and developed for assessing CFRP, we argue that it is likely applicable to many emerging technologies, especially when the assessment of these face the same types of difficulties in terms of data availability and uncertainties regarding changes to, for example, market demand and prices. 4. References [1] Arvidsson, R., et al., Environmental Assessment of Emerging Technologies: Recommendations for Prospective LCA. Journal of Industrial Ecology, 2018. 22(6): p. 1286-1294. [2] LIBRE. LIBRE-Lignin Based Carbon Fibres for Composites. 2016 [cited 2018 9:th of november]; Available from: http://libre2020.eu. [3] Hermansson, F., M. Janssen, and M. Svanström, Prospective study of lignin-based and recycled carbon fibers in composites through meta-analysis of life cycle assessments. Journal of Cleaner Production, 2019. 223: p. 946-956. [4] Hermansson, F., M. Janssen, and M. Svanström, Allocation in life cycle assessment of lignin. The International Journal of Life Cycle Assessment, 2020. [5] Hermansson, F., et al., Allocation in recycling of composites - the case of life cycle assessment of products from carbon fiber composites. The International Journal of Life Cycle Assessment, 2022. 27(3): p. 419-432. [6] Hermansson, F., et al., Can carbon fiber composites have a lower environmental impact than fiberglass? Resources, Conservation and Recycling, 2022. 181: p. 106234. [7] Langkau, S. and M. Erdmann, Environmental impacts of the future supply of rare earths for magnet applications. Journal of Industrial Ecology, 2021. 25(4): p. 1034-1050. Acknowledgement - This project has received funding from the Bio Based Industries Joint Undertaking under the European Union’s Horizon 2020 research and innovation programme under grant agreement No 720707 and Chalmers University of Technology - Energy Area of Advance (ECE profile) Transport Area of Advance.

Towards a bio-economy: the role of the forest Biomass has an increasingly important role in replacing fossil and mineral resources, and it is central in environmental impact-reduction strategies in companies and governments, locally, nationally and internationally. The European Union (EU) has recently taken action to strengthen the bio-economy, defined as “…the sustainable production and conversion of biomass into a range of food, health, fibre and industrial products and energy”. Two thirds of the land area in Sweden is covered by forests, and forestry has been an important industry for centuries. Increased and/or more efficient use of forest biomass thus has a great potential for replacing the use of fossil and mineral resources in Sweden. There are two main reasons for why forest- and other bio-based products are seen as environmentally beneficial. Biomass is (most often) a renewable resource, in contrast to finite fossil and mineral resources, and there is often a balance between CO2 captured when the biomass grows, and CO2 released when the bio-based product is incinerated. The challenge: calculate carbon footprints Moving towards a bio-economy means replacing non-renewable fuels and materials with bio-based fuels and materials. This is a transition on many levels: technology, business models, infrastructure, political priorities, etc. To guide such a grand transition, there is a need to understand the environmental implications of new bio-based products. This includes assessing their climate impact, so-called carbon footprinting. Carbon footprinting of forest products is not as simple as saying that forest products are carbon and climate neutral by definition. Fossil energy used for producing and transporting the products has a carbon footprint. Also, the carbon balance can differ between forest products, which can influence their carbon footprint. For example, carbon stored in products, while CO2 is captured in the re-growing forest, can mitigate climate change. The modelling of the carbon balance is influenced by the study’s geographical system boundaries – national, regional, landscape and single-stand perspectives often yield different results. Forestry can also lead to positive or negative changes in the levels of carbon stored in the soil, the levels of aerosols emitted by the trees (influencing cloud formation), and the albedo (surface reflectivity) of the forest land. An indirect effect of forestry can be increased competition for land, with expanding or intensified land use elsewhere, with positive or negative climate effects. All these factors are potentially important when calculating carbon footprints. There is limited knowledge about how and to which extent the aforementioned factors influence the carbon footprint of forest products. Also, there is a lack of methods for assessing some of these factors. In light of this, can the carbon footprints of today be trusted? And can we ensure that they provide relevant and robust decision support? Our approach: testing three different carbon footprint methods in five case studies In this study, we have: Identified different carbon footprint methods. Used the identified methods to calculate the carbon footprint of different forest products and non-forest benchmarks (using life cycle assessment, LCA). Compared the results to find out how and why they differ. We identified three main categories of carbon footprint methods: (i) the common practice in LCA, (ii) recommendations in standards and directives (we tested the EU sustainability criteria for biofuels and bioliquids and the Product Environmental Footprint (PEF) guide), and (iii) more advanced methods proposed in the scientific literature (we tested dynamic LCA). For dynamic LCA, we tested different time horizons (20 and 100 years) and different geographical system boundaries, based on (a) the national level, assuming a net annual growth of biomass (which is the case in Sweden); (b) the landscape level, assuming a balance between the annual harvesting and growth (the level at which forests are often managed); and (c) the stand level, assuming regrowth during a time period of 80 years (a stand is the part of a landscape that is harvested in one year, a level often used by researchers developing new methods for modelling the dynamics of forest carbon flows). These methods were applied to five forest products: two automotive fuels (a lignin-based fuel produced from black liquor and butanol), a textile fibre (viscose), a timber structure building, and a chemical (methanol, used for different end products). Our findings We found that different carbon footprint methods can give different results. The common practice is close to the recommendation in the EU sustainability criteria and the PEF guide. Results from dynamic LCA differ considerably, as it accounts for the timing of (fossil and biogenic) greenhouse gas (GHG) emissions and CO2 capture, which is ignored by the other methods. The results of dynamic LCA depend primarily on the geographical system boundaries, but also on the time horizon. When applying dynamic LCA with a stand perspective, we assumed that the CO2 uptake occurs after harvest. Alternatively, one could assume that the CO2 uptake occurs before harvest, which would give different (lower) results. When comparing the carbon footprints of the forest products with products they could be expected to replace, we see that the results for the forest products could range from being definitely favourable to worse. More results can be found in the full report. Results were produced to answer the research questions of this study, and should not be used out of context. Conclusions and recommendations Because there is (still) limited knowledge about how forest products influence the climate, and as carbon footprints will always depend on value-based assumptions (e.g. regarding geographical system boundaries), it is not possible to recommend one specific method which is suitable regardless of context. As different carbon footprint methods can give very different results, our key message is that we need to increase consciousness on these matters. It is important to be aware of the assumptions made in the study, the effects of those assumptions on results, and how results can and cannot be used for decision support in a certain context. More specific recommendations for decision makers are listed below. Further details and results can be found in the main report, along with recommendations for LCA practitioners and researchers. Decision makers must be aware that the main methodological choices influencing carbon footprints of Swedish forest products are the choice of geographical system boundaries (e.g. national-, landscape- or stand-level system boundaries) and whether the timing of CO2 capture and GHG emissions is accounted for. This is because Swedish forests are, in general, slow growing. If the aim of the decision is to obtain short-term climate impact reduction – for example, the urgent reduction that is possibly needed for preventing the world average temperature to rise with more than 2°C – the timing of CO2 capture and GHG emissions should be taken into account. Decision makers must be aware that a particular method for capturing timing (such as dynamic LCA) can be combined with different system boundaries, which can yield different results. When conclusions from existing LCA studies are synthesized for decision support, the decision maker must be aware that most existing studies do not account for the timing of CO2 capture and GHG emissions. This is particularly important when the decision concerns the prioritization of forest products with different service lives (e.g., fuels versus buildings). When timing is considered, decision makers must be aware that there are different views on when the CO2 capture occurs, which will influence the carbon footprint. One could either consider the CO2 captured before the harvest (i.e., the capture of the carbon that goes into the product system), or the CO2 captured after the harvest (i.e., the consequence of the harvest operation). In this study, we tested the second alternative when we applied dynamic LCA with a stand perspective – this does not mean we advocate the use of the second alternative over the first alternative. Decision makers must be aware that the location and management practices of the forestry influence the climate impact of a forest product. For example, growth rates, changes in soil carbon storages and fertilisers (a source of GHGs) differ between locations. Based on our results, we cannot say that the carbon footprints of some product categories are more robust than for others, i.e. less influenced by choice of methodology. However, the more forest biomass use in the product system, the higher the influence of the choice of method. As many interactions between the forest and the climate are still not fully understood, it is important to be open to new knowledge gained in methodology development work. Regarding how to use Swedish forests for the most efficient climate impact reduction, it is impossible to draw a general conclusion on the basis of our results. Factors that influence the “optimal” use are:Which fraction of forest biomass that is used. Various products use different fractions (as was the case in our case studies) and do not necessarily compete for the same biomass. However, a production system may be more or less optimised for a specific output. So there may be situations of competition also when feedstocks are not directly interchangeable. Which non-forest product that is assumed to be replaced by the forest product (if any). The carbon footprint of the non-forest product matters, but also how large the substitution effect is (i.e., does the forest product actually replace the non-forest alternative, or merely add products to the market, and what are the rebound effects from increased production?). If all other factors are identical: the longer the service life of the forest product the better, due to the climate benefit of storing carbon and thereby delaying CO2 emissions. This effect is particularly strong if the aim is to obtain short-term climate impact reduction. Moreover, the effect supports so-called cascade use of forest biomass, e.g. first using wood in a building structure, then reusing the wood in a commodity, and at end-of-life, as late as possible, recovering the energy content of the wood for heat or fuel production. Traditional LCA practice and methods required by the EU sustainability criteria and PEF have limitations in the support they can provide for the transition to a bio-economy, as they cannot capture the variations of different forest products in terms of rotation periods and service lives. Thus, decision makers need to consider studies using more advanced methods to be able to distinguish better or worse uses of forest biomass. We have tested one such advanced method (dynamic LCA), that proved applicable in combination with several different geographical perspectives, but also other methods exist (e.g. GWPbio). Climate change is not the only environmental impact category which is relevant in decision making concerned with how to use forests. Other environmental issues, such as loss of biodiversity and ecosystem services, are also important. There are also non-environmental sustainability issues of potential importance, e.g. related to indigenous rights and job creation. The method’s influence on climate impact assessment of biofuels and other uses of forest biomass