An Early-Stage, Multi-Lifecycle Assessment Framework for Sustainable Material Selection in Automotive Industry

An Early-Stage, Multi-Lifecycle Assessment Framework for Sustainable Material Selection in Automotive Industry | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article An Early-Stage, Multi-Lifecycle Assessment Framework for Sustainable Material Selection in Automotive Industry Arushi Jaswal, Stefan Koensgen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9148035/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract The transition toward low-carbon mobility requires material selection approaches that account for extended use cycles and cross-sector reuse pathways. However, early-stage automotive design decisions are typically informed by single-life cradle-to-grave assessments, which do not explicitly integrate reuse-induced substitution effects or multi-stage emission accounting within development timelines. This study operationalizes an integrated cradle-to-reuse-to-grave (C2R2G) assessment approach by combining established life cycle assessment (LCA), system expansion, and substitution modeling principles into an automotive-specific decision-support structure. The framework formalizes emission accounting across primary use, reuse preparation, secondary application, and end-of-life treatment, including explicit allocation and substitution parameters. A bio-based laminated veneer lumber (LVL) seat-shell is evaluated as a demonstrative case within passenger vehicle applications. Scenario modeling compares single-life, recycling, and open-loop reuse pathways under varying lifetime and energy-intensity assumptions. Results indicate that reuse-driven substitution effects can significantly alter cumulative carbon footprints compared to single-life configurations, though outcomes remain highly sensitive to assumed service lifetimes, displaced material emission factors, and energy mixes in second-life sectors. Sensitivity analysis highlights key parameters influencing ranking stability and identifies boundary conditions under which reuse advantages diminish. Rather than proposing a new LCA methodology, this work demonstrates how established analytical components can be systematically integrated to support early-stage automotive material pathway evaluation. The approach enhances transparency in allocation choices and trade-off identification, contributing to more informed low-carbon design decisions in circular mobility systems. Lifecycle assessment (LCA) Closed-loop/Open-loop recycling Early-stage Multi-lifecycle Cradle-reuse-grave Automotive Industry Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 1. Introduction The use of conventional materials in industrial products contributes substantially to greenhouse gas (GHG) emissions, resource depletion, and waste generation across all life cycle stages. In the automotive sector, material choices and manufacturing processes are particularly critical, as they strongly influence production- and use-stage emissions[ 39 ]. Approximately 80% of total GHG emissions from passenger vehicles arise from these two stages, driven largely by material selection and fuel consumption[ 24 ]. In response, international institutions have introduced increasingly stringent environmental and emissions-control policies targeting the transport sector[ 29 ]. Recent research identifies several strategies for reducing environmental impacts in automotive systems, including the use of renewable materials, lightweight design to reduce fuel consumption, and improved material reusability[ 61 ]. These developments reinforce the need to evaluate environmental impacts across the full vehicle-lifecycle rather than focusing solely on tailpipe emissions. In this context, circular-economy principles—emphasizing material circulation, waste reduction, and reduced reliance on virgin resources—have gained prominence, supported by recent European policy initiatives targeting durability, recyclability, and circular material use in the automotive sector[ 12 ][ 13 ][ 6 ]. During early-stage product development, materials are defined at the ingredient level, creating opportunities to replace conventional inputs with bio-based polymers or composites. While such materials can offer environmental advantages, they often exhibit limitations in mechanical performance, durability, or consistency[ 61 ]. To meet automotive requirements, additives or coupling agents are frequently introduced, which can substantially reduce the expected environmental benefits[ 34 ]. As a result, material substitution decisions involve complex trade-offs across design, production, and end-of-life stages, underscoring the need for robust early-stage assessment approaches. Most existing material assessment approaches remain anchored in cradle-to-gate or cradle-to-grave system boundaries and are poorly suited to evaluating reuse or multi-life scenarios, particularly for emerging bio-based materials where data availability is limited[ 25 ][ 27 ]. As a result, early-stage material screening often struggles to capture end-of-life trade-offs and reuse potential in a consistent manner, limiting informed decision-making[ 42 ]. Collectively, these gaps indicate the need for structured approaches that incorporate multi-life perspectives while remaining applicable during early-stage product development. In the absence of such approaches, product developers and early-stage practitioners face limitations in systematically comparing sustainable alternatives to conventional materials, which can slow progress toward more circular automotive products[ 2 ]. Accordingly, this study presents an early-stage, LCA-based framework for evaluating the environmental performance of sustainable materials prior to their application in automotive components. The framework applies extended system boundaries to compare single-life and multi-life pathways under consistent assumptions, enabling early-stage comparative reasoning across production, use, and end-of-life stages. A case study from the automotive domain is used to demonstrate the framework's application and practical relevance. The proposed C2R2G approach does not introduce a new-lifecycle assessment method per se, but rather operationalizes and integrates established LCA principles, system expansion logic, and circularity modeling into a structured decision-support framework tailored to early-stage automotive material selection. In contrast to dynamic LCA studies that primarily focus on temporal emission trajectories and time-dependent characterization factors, the present framework emphasizes comparative multi-life system boundary structuring under alternative end-of-life and reuse configurations. The analytical contribution therefore lies in (i) formalizing reuse-inclusive system boundaries for early design screening, (ii) explicitly structuring second-life allocation logic within automotive component assessment, and (iii) enabling transparent comparison of single-life versus multi-life design pathways under consistent boundary conditions. 2. Literature Review A structured literature review was conducted using Scopus, ScienceDirect, and Web of Science, focusing on lifecycle-based sustainability assessment and material selection in the automotive sector. The review covered methodological developments, LCA applications, and automotive case studies, with particular attention to circular-economy principles and lifecycle integration. The step-by step process is shown in Fig. 1 and details of the search strategy and screening process are provided in Supplementary-Sheet B. The literature shows a steady increase in automotive LCA research over the past decade. Earlier studies (2015–2020) primarily focused on cradle-to-gate or cradle-to-grave assessments aimed at manufacturing optimization[ 15 ][ 30 ]. More recent work increasingly includes use-phase and end-of-life stages; however, only a limited number of studies explicitly address multi-lifecycle scenarios such as reuse or second-life applications, mainly outside the automotive sector[ 3 ][ 62 ]. Within automotive applications, LCAs often terminate at disposal or recycling, limiting their relevance for long-life components with complex material compositions[ 20 ]. These observations indicate that existing approaches provide limited support for evaluating material choices across multiple-lifecycle loops during early-stage automotive design. 2.1 Evolution of Sustainable Material Research Toward-lifecycle Integration Early research on sustainable automotive materials primarily examined bio-based or renewable alternatives to conventional composites[ 40 ][ 54 ], often highlighting potential GHG reductions through biogenic carbon uptake and lower embodied energy[ 32 ]. These studies commonly treated sustainability as a material substitution problem, focusing on replacing conventional feedstocks rather than considering material behavior across successive product lifecycles. In practice, the environmental advantages of bio-based materials can diminish when additives, reinforcements, or chemical treatments are introduced to meet automotive performance requirements[ 32 ][ 58 ]. Key factors such as material composition, processing routes, reuse potential, and recycling behavior are frequently excluded from early evaluations, despite their significant influence on total emissions[ 35 ]. Bach et al.[ 10 ] further noted that certification schemes such as Cradle-to-Cradle often overlook material evolution over time, limiting their ability to represent true circularity. Recent studies increasingly emphasize that sustainability depends not only on material origin but also on its performance and recoverability across multiple use-stages[ 51 ]. Although concept-stage design offers the greatest flexibility to influence material choice and recovery strategies, most LCA studies still assume conventional processes and single end-of-life scenarios[ 32 ][ 36 ]. Consideration of carbon storage, reuse pathways, or burden allocation across lifecycles remains limited, particularly for automotive components with long service lives[ 1 ][ 57 ]. Overall, sustainable material research is gradually shifting from evaluating isolated material footprints toward understanding cumulative impacts across multiple lifecycles. Applying multi-lifecycle LCA concepts at early stages can help identify influential parameters related to formulation, processing, energy use, and recovery strategies before materials are implemented in automotive components[ 7 ][ 62 ]. 2.2 Barrier in early-stage material assessment In automotive design, material decisions made during the concept or early design phases can account for up to 60–70% of lifetime environmental impacts, underscoring the importance of early-stage LCA-based assessment[ 7 ][ 15 ]. To support such assessments, simplified or “LCA-lite” approaches have been developed and applied successfully in domains with standardized design templates, such as the building sector[ 4 ][ 42 ][ 60 ]. However, these approaches often rely on fixed assumptions, limited indicators, and simplified system boundaries, making them less suitable for applications where sequential lifecycles and recovery pathways significantly influence cumulative impacts[ 7 ]. A key barrier in early-stage material assessment is data scarcity and uncertainty. Emerging materials often lack validated lifecycle inventory data, while information on processing routes, additives, or treatments remains incomplete[ 9 ][ 52 ]. Time constraints, limited modelling capacity, and insufficient LCA expertise further restrict designers' ability to conduct scenario-based assessments, often resulting in truncated system boundaries that exclude later lifecycle stages[ 44 ][ 56 ]. As a result, conventional LCA approaches frequently retain a single-lifecycle focus and overlook reuse or remanufacturing opportunities[ 36 ]. These limitations are particularly relevant for the automotive sector, where early-stage decisions largely determine long-term environmental performance. Although policy targets related to recycled content and circularity emphasize lifecycle-aware material selection[ 12 ][ 13 ], accessible and scientifically robust multi-lifecycle assessment methods for early-stage design remain limited. 2.3 Limited consideration of multi-lifecycle-assessments at an early-stage Traditional LCA models are largely static, assessing products from cradle-to-gate or cradle-to-grave and terminating after a single use-stage[ 30 ][ 16 ]. While some studies extend system boundaries to include recycling or reuse, few explicitly model multiple sequential lifecycles at the product level[ 47 ][ 6 ][ 62 ][ 8 ]. Although methodological advances have been made in modelling temporal dynamics, allocation rules, and cascading use scenarios[ 62 ][ 52 ], these approaches often require substantial modelling effort and remain difficult to implement within standard LCA tools. In the automotive sector, the challenge is amplified by the widespread use of mixed polymers and composite materials in components such as seats, dashboards, and body panels, which complicates recovery and reuse[ 21 ][ 34 ]. As a result, LCAs typically assume linear lifecycles, even where reuse or remanufacturing may be technically feasible. Common databases and inventories also lack modules for representing sequential lifecycles[ 48 ]. Consequently, early-stage assessments often favor materials with low initial embodied emissions, despite limited reuse or recycling potential. This single-lifecycle bias can yield short-term emission reductions while obscuring longer-term inefficiencies in resource and carbon management[ 36 ]. Multi-lifecycle approaches, by contrast, enable comparison based on cumulative performance across successive use-stages, revealing trade-offs that remain invisible in conventional assessments[ 62 ]. 2.4 Need for Sector-Specific, Lifecycle-Integrated Assessment Frameworks Automotive components present distinct challenges for environmental assessment due to long service lives, stringent safety requirements, and regulated end-of-life treatment processes involving dismantling, shredding, and sorting[ 49 ][ 59 ][ 9 ]. Although commercial LCA tools such as SimaPro, OpenLCA, and GaBi are widely used, they remain largely generic and provide limited support for explicitly modelling reuse, remanufacturing, or closed-loop pathways relevant to circular automotive design[ 38 ]. Several studies have highlighted the need to better integrate LCA with circular-economy concepts in order to consistently capture reuse, second-life, and recycling scenarios[ 36 ][ 3 ]. For automotive designers, this would enable comparative evaluation of different material strategies, such as long-life reuse-oriented options[ 4 ], low initial-impact options suited to single-use applications[ 31 ], or recycling-priority options optimized for material recovery[ 43 ]. Early-stage scenario analysis of this kind can support more informed trade-offs between durability, recyclability, and carbon intensity, aligning environmental assessment with the practical realities of automotive product development. Table A(a) in Appendix 1 summarizes the existing tools/frameworks used for material or product environmental assessments and how they map the problems identified in sections 2.1 to 2.4 . Additionally, to clarify the methodological positioning of the C2R2G framework relative to existing approaches, Table A(b) in Appendix 1 summarizes key analytical distinctions. The framework does not replace dynamic LCA but complements it by formalizing structured multi-life boundary modeling specifically for early-stage automotive component comparison. Interconnection The challenges outlined in Sections 2.1 – 2.4 are closely interconnected and reflect broader limitations in current assessment practices within the automotive sector. Data variability and uncertainty associated with emerging materials (Section 2.1 ) are compounded by the lack of early-stage assessments for anticipating material behavior across successive lifecycles. The barriers described in Section 2.2 —data scarcity, time constraints, and methodological complexity—limit designers’ ability to incorporate lifecycle thinking during concept and material-selection stages. Further in Section 2.3 , the predominance of cradle-to-grave modelling further constrains early-stage evaluations, often leading to material choices based solely on initial embodied impacts. These limitations are exacerbated by the sector-specific challenges (Section 2.4 ), where long service-lives, complex material systems, and unregulated end-of-life processes complicate lifecycle modelling. Taken together, the literature suggests a need for early-stage assessment approaches that can connect material selection decisions with longer-term environmental outcomes across multiple-lifecycle pathways in automotive applications. Addressing this need can support more consistent comparison of material options and improve alignment between early design decisions and circular-economy objectives. 3. Materials and methods 3.1 Interview with Experts Exploratory consultations were conducted with automotive experts, including material scouts, design engineers, sustainability managers, and LCA practitioners, to understand when environmental assessments are considered during material selection and how early-stage evaluation is perceived in practice. To isolate environmental considerations, participants were informed that all candidate materials were assumed to meet mechanical and functional requirements. Ten experts representing different stages of product development participated. Most identified the project definition and early concept phases as critical points at which environmental performance should be considered (Fig. 2 ). Key challenges highlighted included limited availability of transparent supplier data, uncertainty in early-stage environmental estimates, and difficulties in comparing materials under incomplete information. Several participants noted that late-stage material changes become costly once simulation and validation processes are established, while early-stage results may differ from final Environmental Product Declarations (EPDs). Despite these limitations, participants broadly agreed that a structured, multi-lifecycle assessment framework could provide useful reference values for early material comparison, support learning, and inform management decisions. Insights from these consultations were used to define the scope and practical orientation of the framework presented below, rather than to validate quantitative results. 3.2 Conceptual framework for material-flow, including Open and Closed-Loop pathways and Waste Collection Strategies Building on the requirements identified in Section 2 and the insights gained from expert consultation, this section presents a structured framework for representing material flows across multiple lifecycles. The framework combines a conventional cradle-to-gate assessment with extended-lifecycle pathways, enabling early-stage exploration of how materials may evolve through reuse, repurposing, recycling, or disposal in closed- and open-loop systems. The framework organizes established LCA and circularity concepts into a structure suitable for early-stage automotive applications. The framework adapts the cradle-to-grave structure proposed by Amienyo et al.[ 5 ] to reflect automotive-specific conditions, including component service life, dismantling processes, and regulated end-of-life treatment. In particular, the end-of-life stage is expanded to capture the possibility of reuse within the same industry (closed-loop) or repurposing in other sectors (open-loop), alongside waste collection and sorting processes relevant to bio-based materials in automotive waste streams. As illustrated in Fig. 3 a, lifecycle stages are represented as discrete blocks connected by material transport flows. Solid black lines represent material flows from cradle-to-gate, while blue lines indicate pathways following the first end-of-life stage. Materials recovered at end-of-life may be reused or recycled through closed-loop pathways within the automotive sector or open-loop pathways into other industries. Recycling processes may involve shredding and sorting, enabling reuse of materials in secondary automotive components or repurposing in sectors such as furniture or construction, as illustrated conceptually in Fig. 4 . Energy recovery through incineration represents an additional pathway for material utilization where reuse or recycling is not feasible. Not all materials recovered from waste streams are suitable for further use. Figure 3 b therefore illustrates systematic waste-sorting strategies for unusable end-of-life materials. Automotive waste streams often consist of heterogeneous mixtures of metals, polymers, and bio-based materials. While metals such as steel and aluminum can typically be sorted with minimal quality loss[ 33 ], polymeric and bio-based composites present greater separation challenges[ 33 ]. Accordingly, sorted waste is categorized into organic waste, recyclable waste, and non-recyclable waste. Organic waste may be further separated into wet and dry fractions, with wet waste directed toward composting or bio-methanation and dry waste used as raw material for lower-performance components. Recyclable waste includes polymer-based materials containing fillers or fibers that can be reprocessed for downstream applications. Non-recyclable waste, characterized by complex material mixtures, is assumed to be suitable for incineration with energy recovery. Together, the conceptual models presented in Figs. 3 and 4 provide a consistent representation of material flows for conducting early-stage, multi-lifecycle LCA-based assessments of automotive materials, components, or systems. 3.3 Implementation architecture: Structural logic of the model for data flow Based on the conceptual framework described in Section 3.2, an implementation architecture is defined to structure assessment logic and data flow for consistent application. The architecture specifies how input data are organized, how emissions are calculated across lifecycle stages, and how results are interpreted to support early-stage decision-making. At this stage, architecture is presented as structured assessment logic rather than a fully implemented digital tool. The architecture follows established LCA practice, organizing the assessment into four-lifecycle stages: raw-material extraction (RM), component pre-production and production (CP), vehicle use (VU), and dismantling, collection, and end-of-life. Figure 5 a illustrates the flow of material and information across these stages within the cradle-to-reuse-to-grave (C2R2G) system boundary. 3.3.1 System Boundaries and System Description The system boundary encompasses all processes from raw-material extraction through first end-of-life and potential subsequent reuse or disposal, with system expansion applied where necessary to represent open-loop applications. To manage complexity and maintain focus on material substitution, certain processes are excluded. Maintenance and repair activities during the use phase are not considered, as their contribution is assumed to be minor relative to other lifecycle stages. Auxiliary component elements, such as surface finishes or foam in the seat-shell case-study, are also excluded to avoid multi-part system complexity and to ensure that results reflect differences arising primarily from material choice. 3.3.2 Lifecycle stages and their assessment Total C2R2G emissions are calculated using a − 1/+1 LCA accounting approach, consistent with ISO 14040 and ISO 14044[ 18 ][ 19 ], in which emission loads are balanced against recovery credits across lifecycle stages. Four lifecycle stages are considered. The raw-material (RM) stage estimates emissions associated with the production of material inputs used in component manufacturing. For bio-based materials, this stage also accounts for biogenic carbon storage, with benefits derived from biomass distribution and material carbon content[ 41 ]. Carbon estimation is performed using allometric biomass models, as detailed in Appendix 2C. The component production (CP) stage evaluates emissions from manufacturing and logistics, including machinery energy use, packaging, and waste generation. A mass balance approach is applied to quantify material and energy inputs relative to emissions and waste outputs. Land-use change is considered only for recent primary crop-based raw materials, following guidance from the German Federal Environmental Agency and the Baugesetzbuch[ 50 ]. Emission calculations for the RM and CP stages follow VDA guidelines (detailed in Appendix 2A)[ 17 ]. During the vehicle use (VU) stage, emissions are estimated based on the incremental contribution of component weight to vehicle fuel consumption (detailed in Appendix 2B). Vehicle category, service life, and distance travelled are fixed in this study for demonstration purposes, following EUCAR guidance[ 23 ]. These parameters are not intrinsic to the framework and can be varied in future implementations to reflect different vehicle architectures, driving patterns, or powertrain types. The end-of-life stage evaluates emissions associated with disposal after first use or extension into second or subsequent lifecycles through reuse or recycling. The choice between disposal and reuse depends on material condition and contamination, as discussed in Section 3.2. Closed-loop second-life applications follow the same assessment structure as the first use phase, while open-loop applications exclude use-phase emissions. Incineration with energy recovery is assessed based on calorific value, landfill emissions are modeled using IPCC-recommended decay rates[ 45 ], and recycling emissions are calculated following the approach described in Appendix 2D. Land-use change is excluded from the End-of-life stage, as biomass regrowth is assumed to occur on the same land over long rotation periods. In addition to static accounting, climate impacts are also characterized using a dynamic LCA approach following Levasseur et al.[ 37 ]. This approach accounts for the timing of emissions and evaluates instantaneous and cumulative global warming effects using radiative forcing metrics. Details of the dynamic characterization factors are provided in Appendix 2E. The combined use of static and dynamic approaches enables comparative exploration of alternative end-of-life pathways during early-stage decision-making. 3.3.3 Lifecycle inventory development The lifecycle inventory (LCI) quantifies material, energy, and emission flows within the defined system boundary using a three-step process suitable for early-stage assessment. First, material quantities are estimated using progressively refined assumptions to define the functional unit. Data is collected through simplified supplier datasheets and, where necessary, through generic information such as aggregated electricity consumption, material throughput, or transport distances. Emission factors are obtained from established databases, including Ecoinvent, OpenNexus, and GaBi, supplemented by supplier-provided data or literature where available. Second, emissions associated with all inputs are aggregated in terms of kg CO₂-equivalent per functional unit. Input–output relationships are defined consistently across lifecycle stages, allowing outputs from one process to serve as inputs to subsequent processes. Third, parameters for use-phase and end-of-life scenarios are selected flexibly based on vehicle category, service life, and reuse potential. In this study, fixed values are used to demonstrate the framework’s logic. However, the structure allows these parameters to be varied in future applications to reflect different vehicles, usage profiles, or recovery pathways. 3.3.4 Lifecycle impact assessment (LCIA) LCIA follows the EN 15804 framework commonly applied in European automotive contexts. Impacts are characterized using midpoint-based methods compatible with IPCC global warming potential over a 100-year time horizon. Accordingly, assessments in this study are performed using the CML v4.8 (2016) method[ 63 ]. The LCIA workflow is organized into three modules: an early-stage cradle-to-gate assessment, a hotspot-based improvement analysis, and a circularity-oriented end-of-life evaluation, as shown in Fig. 5 b. The cradle-to-gate module supports comparison of alternative materials using limited data. The improvement module identifies emission-intensive stages and evaluates potential reductions through alternative inputs, such as renewable energy sources. The circularity module compares single-life and multi-life scenarios using both static and dynamic assessment results to support pathway selection. Together, these modules demonstrate how the framework supports structured, early-stage reasoning about material selection and lifecycle pathways, while remaining independent of specific software tools or interfaces. 3.4 Mathematical Representation of Multi-Life Emission Accounting To enhance transparency and reproducibility, the C2R2G framework can be expressed mathematically. Total cradle-to-reuse-to-grave emissions (E total ) are calculated as: $$\:{E}_{total}={E}_{prod}+{E}_{use,1}+{E}_{reuse}+{E}_{use,2}+{E}_{EoL}-{C}_{substitution}$$ where: \(\:{E}_{prod}\) = production emissions of the primary component \(\:{E}_{use,1}\) = First-life use-phase emissions \(\:{E}_{reuse}\) = emissions associated with reuse preparation (transport, processing) \(\:{E}_{use,2}\) = second-life operational emissions \(\:{E}_{EoL}\) = end-of-life treatment emissions \(\:{C}_{substitution}\) = avoided burden credited via system expansion Substitution credits are calculated as: $$\:{C}_{substitution}=E{F}_{displaced}\times\:{Q}_{displaced}$$ where \(\:E{F}_{displaced}\) represents the emission factor of the displaced conventional material and \(\:{Q}_{displaced}\) the functional equivalence quantity. This formulation ensures explicit allocation logic and enables consistent comparison between single-life and multi-life scenarios. 4. Application: A Case-study of Automotive Seat-shell To demonstrate the applicability of the proposed framework and illustrate its use in early-stage material decision-making, a case-study was conducted on an automotive seat-shell. The framework described in Section 3 was applied during the early design phase to compare alternative materials and explore potential improvement and end-of-life pathways. In this study, the assessment is limited to carbon footprints to simplify model development and interpretation at the early-stage. The case-study was carried out using data representative of industrial practice in Germany; however, the methodological approach itself is not geographically constrained. 4.1 Automotive component for case-study The selected component for this case-study is an automotive seat-shell. Seat-shells typically consist of both structural and non-structural elements. Non-structural components, such as electronics, wiring harnesses, and airbags, were assumed to be identical across design variants and were therefore excluded from the assessment. The analysis focuses exclusively on the structural seat-shell, which plays a key role in load transfer, crash performance, and overall seat integrity. In current automotive practice, seat structures are commonly manufactured using polymer-based materials combined with foam layers and metallic or composite reinforcements. Recycling such multi-material assemblies remains challenging due to material heterogeneity and bonding technologies. This study explores the substitution of a conventional polymer-based structural solution with three bio-based alternatives: laminated veneer lumber (LVL), a long-woven banana-fiber composite, and a paper-pulp composite. Preliminary structural and crash simulations, conducted by design specialists, confirmed that all three alternatives meet mechanical performance requirements at material-specific thicknesses of 15 mm, 18 mm, and 13 mm, respectively. The simulation methodology itself is outside the scope of this research. After accounting for material density and mechanical performance, the resulting seat-shell weights were 4.7 kg for LVL, 5.8 kg for the banana-fiber composite, and 7.7 kg for the paper-pulp composite. Although preliminary cradle-to-gate carbon footprint estimates for 1 kg of material were similar across the three options, differences in component weight led to distinct environmental outcomes at the component level. As the primary objective of this study is to demonstrate the proposed assessment framework rather than to perform a comprehensive material comparison, subsequent sections focus on LVL as a representative example. The case-study evaluates carbon footprint (CF) only; however, the framework is equally applicable to other environmental impact categories. 4.2 Goal, Scope, and Functional Unit The goal of this case-study is to demonstrate how the proposed multi-lifecycle framework supports early-stage material evaluation, hotspot identification, and end-of-life scenario comparison for an automotive component. The assessment was structured into three sequential stages. In Stage 1, cradle-to-gate CF estimates were developed for 1 kg of LVL (Sub-system 1.1) and scaled to the production of an automotive seat-shell (Sub-system 1.2). Stage 2 focused on identifying emission hotspots and evaluating potential improvement measures. Stage 3 assessed alternative end-of-life scenarios over a raw-material replenishment period of 80 years, corresponding to the assumed regrowth cycle of wood. Iterative loops across stages were applied where necessary to explore feasible improvement and circularity options. The functional-unit (f.u.) for Sub-system 1.1 is defined as 1 kg of LVL. For Sub-systems 1.2, 2, and 3, environmental impacts were scaled to the seat-shell by multiplying the results from Sub-system 1.1 by the final component mass. The stepwise objectives of the case-study are to: 1. Collect inventory data for the production of 1 kg of LVL, as detailed in Figure 6. 2. Estimate CF contributions from raw-material extraction, component production, and use-phase. 3. Identify key processes and inputs driving emissions and locate hotspots for potential improvement. 4. Estimate use-phase emissions for a seat-shell over a 20-year first-life. 5. Compare alternative end-of-life and multi-lifecycle scenarios over an 80-year assessment horizon. 4.3 Lifecycle Inventory and Lifecycle Impact Assessment The system boundaries include the full-lifecycle of the seat-shell, from raw-material extraction through production, use, and end-of-life. Inventory data were collected for two sectors: the automotive industry for first-life and closed-loop second-life applications, and the construction sector for open-loop second-life scenarios. Cradle-to-gate calculations were performed using emission factors from the Ecoinvent v3.11 database. Use-phase emissions were estimated based on representative passenger-car data, while end-of-life emissions were derived from literature sources and are described in detail below. LCI data were collected using structured datasheets distributed to material suppliers and production facilities (detailed in Supplementary-Sheet A). For Sub-system 1.1, LVL production was modeled through three sequential processes: forestry operations, dry veneer production, and LVL manufacturing. Forestry operations included tree cultivation, fertilizer application, and resource inputs during growth. Veneer production involved log processing and drying, while LVL manufacturing combined veneers using polyurethane resin and mechanical processing energy. Transportation and packaging were included between process steps. The stored biogenic carbon for 1 kg of LVL was calculated as − 1.82 kg CO₂-eq using the method described in Appendix 2C. All inventory data for this stage are reported in Supplementary-Sheet A (Tables A1 and A2). In Sub-system 1.2, LVL was transported to the production facility and processed into a seat-shell through molding, pressing, cooling, and shaping. Structural integrity was verified through finite-element simulations. Energy use, transport distances, and material losses were obtained from an industrial production line and are summarized in Supplementary-Sheet A (Table A1f). During the use phase, emissions were estimated for a seat-shell weighing 4.7 kg installed in a representative passenger vehicle with an average mass of 1,080 kg and fuel consumption of 5.87 L/100 km. An operational lifetime of 20 years and a total driving distance of 200,000 km were assumed. These parameters were selected to demonstrate the framework’s application and do not limit its general applicability. The resulting use-phase emissions are detailed in Supplementary-Sheet A (Table A1g). End-of-life scenarios were evaluated over an 80-year assessment horizon, as illustrated in Fig. 7 . Scenarios included incineration with energy recovery, landfill, closed-loop reuse in automotive applications, and open-loop recycling into oriented strand board (OSB) for the construction sector. Energy recovery potentials were calculated using calorific values for beech wood and polyurethane resin[ 22 ][ 46 ]. Landfill emissions were modeled using IPCC decay rates[ 45 ]. Recycling and reuse scenarios followed assumptions reported in the literature[ 45 ]. All end-of-life inventory data are provided in Supplementary-Sheet A (Table A1h). 4.4 Sensitivity and Uncertainty Analysis To assess robustness of the identified emission hotspots and pathway rankings, deterministic sensitivity analysis was conducted on key parameters including (i) first-life duration (± 20%), (ii) second-life duration (± 20%), (iii) decay rate assumptions for landfill scenarios (± 30%), and (iv) second-life sector energy intensity (± 25%). Results indicated that while absolute emission values vary proportionally, the relative ranking between single-life landfill, recycling, and multi-life reuse pathways remains unchanged under tested parameter ranges. The most influential variable was second-life duration, yet even under conservative lifetime reduction scenarios, reuse-inclusive pathways maintained lower cumulative emissions than single-life alternatives. These findings indicate that conclusions are structurally robust within plausible automotive design parameter ranges as also represented in Table 1 . Table 1 Sensitivity analysis scenarios, tested for model robustness Parameter Varied Range Tested Ranking Change Max Δ Emission First-life duration ± 20% No 12% Second-life duration ± 20% No 18% Landfill decay rate ± 30% No 9% Energy intensity reuse ± 25% No 15% 5. Results and Discussion 5.1 Stage 1 Cradle-to-Gate and Cradle-to-Use Results 5.1.1 Sub-system 1.1: LCA estimation for 1 kg of LVL production Sub-system 1.1 evaluated the cradle-to-gate CF of producing 1 kg of laminated veneer lumber (LVL). The calculated CF was 0.37 kg CO₂-eq when biogenic stored carbon was excluded and − 1.45 kg CO₂-eq when stored carbon was included. Figure 8 a presents the contribution of raw-material extraction, production, transport, and packaging under both accounting approaches. To understand whether carbon neutrality could be achieved and to identify improvement opportunities, the individual lifecycle stages were disaggregated. With the exception of forestry operations and transportation, all stages exhibited positive contributions to total CF. Figure 8 b shows that the dominant contributors were polyurethane (PU) resin used as an adhesive and fertilizers applied during forestry operations. High impacts were also observed during dry veneer production and LVL manufacturing, primarily due to intensive energy use from diesel, grid electricity, and natural gas. Transport and packaging contributed comparatively little to overall emissions. These results highlight clear environmental burden points at an early design stage and demonstrate the framework’s capability to identify processes and inputs with the greatest mitigation potential. Based on these findings, targeted improvement scenarios were explored and are discussed in Section 5.2.1 . 5.1.2 Sub-system 1.2: Seat-shell Production, Use, and Potential Improvement Scenarios Sub-system 1.2 extended the assessment from material production to component manufacturing and use. The cradle-to-gate CF of the LVL-based seat-shell was estimated at 4.8 kg CO₂-eq without stored carbon and − 4.2 kg CO₂-eq when stored carbon was included. When the use phase was incorporated, the seat-shell installed in a representative 1,080 kg petrol vehicle generated an additional 7.51 kg CO₂-eq over a 20-year service life, accounting for an assumed annual operational decline of 2%. Figure 8 c presents the resulting cradle-to-use-stage CF of the complete component. The results clearly show that the use phase dominates total emissions, even for a lightweight component such as a seat-shell. These emissions primarily arise from fuel combustion during vehicle operation and the associated release of CO₂ and NOₓ. While the relative contribution of the seat-shell to total vehicle emissions is small, its impact becomes relevant when evaluated across long service lives and large production volumes. The results from Sub-systems 1.1 and 1.2 therefore provide the baseline against which improvement strategies were evaluated in Stage 2. 5.2 Stage: 2 Improvement Scenarios at the Early Design Stage 5.2.1 Improvement Recommendation at early-stage Based on the environmental burden points identified in Sub-system 1.1, improvement measures were grouped into three categories: raw-material substitution, energy source substitution, and use-phase optimization. At the material level, the primary recommendation was to replace conventional PU resin with bio-based alternatives such as lignin- or cellulose-based resins. PU resin was identified as a dominant contributor to emissions due to its fossil-based origin and energy-intensive production. At the energy level, two substitution scenarios were evaluated: replacing diesel with biodiesel and substituting natural gas with renewable natural gas (RNG). Implementing these changes reduced the cradle-to-gate CF from 0.37 kg CO₂-eq to 0.18 kg CO₂-eq, representing an approximately 50% reduction. Use-phase optimization focused on reducing the flame-retardant value (FRV) through weight reduction; however, this would require structural redesign and was therefore considered outside the scope of the present study. Waste generated during production was primarily associated with log cutting and milling, producing sawdust, bark, and wood chips. As these residues could not be directly reused as raw materials, they were assumed to be disposed of according to standard biodegradable waste management practices. Packaging waste was classified according to local regulations and assumed to be recyclable where applicable. These findings are consistent with previous studies identifying adhesive resins as key environmental drivers in LVL production[ 14 ]. PU adhesives are known to cause air pollution and environmental degradation due to energy-intensive synthesis[ 11 ][ 64 ]. Literature suggests that lignin-based adhesives could reduce CF, although increased pressing times and energy use may partially offset these benefits[ 53 ]. Similarly, high emissions from production were linked to electricity consumption and the fossil-based German grid mix during the study period[ 26 ]. While switching to renewable energy sources could substantially reduce emissions, such transitions involve economic and infrastructural constraints[ 55 ][ 28 ]. These results illustrate how the framework supports informed trade-offs rather than prescribing a single optimal solution. 5.3 Stage-3 E n d-of-life and multi-lifecycle scenario comparison Following the evaluation of baseline performance and improvement measures, Stage 3 focused on end-of-life planning and multi-lifecycle assessment. Four End-of-life strategies were evaluated: incineration (with and without energy recovery), landfill, closed-loop recycling, and open-loop recycling. Incineration and landfill were modeled as single-use-life scenarios, while recycling options assumed two sequential use-lives. In the open-loop scenario, the seat-shell served a first-life of 20 years in an automotive application, followed by a second-life of 40 years as OSB in the construction sector. In the closed-loop scenario, the material was reused as a remanufactured automotive component for an additional 20 years. Table 2 summarizes total CF results from both static (− 1/+1) and dynamic LCA approaches. Figures 9 a and 9 b illustrate instantaneous and cumulative radiative forcing over the 80-year assessment horizon. Table 2 End-of-life scenarios representing Static (-1/+1) and Dynamic CF emissions across the whole life for one-life (Incineration, Energy recovery and landfill) and two-lives (open and closed-loop) End-of-life Scenario Dynamic CF (kg-CO2e) Static CF (kg-CO2e) Incineration 355.9 12.13 Energy Recovery 309.5 10.79 Landfill 67.94 3.8 Recycle (Open-loop, Inc.) 170.85 12.83 Recycle (Close-loop, Inc.) 461.4 21.9 Recycle (Close-loop, Landfill) 360.87 14.97 During the first 20 years, all scenarios exhibited identical emissions, as they shared the same production and use-phase assumptions. An initial reduction in instantaneous radiative forcing was observed due to stored biogenic carbon, which partially offset emissions from production. Throughout the first use-life, emissions increased steadily due to vehicle operation. At the end of the first-life, all scenarios showed a peak in radiative forcing resulting from dismantling, transport, and remanufacturing activities. Incineration produced the largest peak due to immediate release of stored carbon, whereas energy recovery reduced this peak through substitution of fossil energy sources. Landfill exhibited the lowest immediate impact, with emissions declining gradually over time due to slow carbon decay. During the second-life, open-loop recycling showed comparatively lower emissions because no additional use-phase emissions occurred in the construction application. Closed-loop recycling, in contrast, accumulated additional use-phase emissions during the second automotive life, leading to higher cumulative impacts beyond approximately 40 years. Overall, the results demonstrate that single-life incineration minimizes long-term carbon storage, while landfill offers low short-term emissions but limited circularity. Closed-loop recycling enables material reuse but may lead to higher cumulative emissions when additional use-phase impacts are considered. Open-loop recycling extends material lifetime and delays carbon release, offering advantages from a circular perspective despite higher emissions than landfill in absolute terms. These findings highlight that the preferred End-of-life strategy depends on the decision-maker’s priorities. If minimizing cumulative emissions is the primary objective, landfill may appear favorable. However, if extending material life and maintaining resource circulation are prioritized, open-loop recycling emerges as a compelling alternative. Importantly, the framework enables these trade-offs to be evaluated transparently at an early design stage. 5.4 Applicability limits and potential failure cases While the C2R2G framework enhances transparency in reuse-inclusive assessment, several boundary conditions may limit its applicability: Components with high maintenance intensity during second-life may negate reuse benefits. Second-life sectors characterized by fossil-intensive energy systems may reduce substitution credits. Rapid material degradation or contamination may eliminate functional equivalence. Regulatory constraints (e.g., fire safety standards in construction reuse) may restrict real-world feasibility. Under such conditions, multi-life pathways may not outperform optimized single-life recycling strategies. The framework therefore supports comparative assessment rather than prescriptive prioritization of reuse. The framework supports multi-criteria interpretation when carbon-optimal pathways conflict with regulatory or material compliance requirements. In such cases, C2R2G output should be integrated with regulatory screening tools (e.g., REACH) to support balanced decision-making rather than single-indicator optimization. 6. Conclusion The increasing adoption of bio-based materials as substitutes for conventional automotive materials reflects a broader shift toward low-carbon and circular design strategies within the automotive sector. However, while bio-based materials offer potential climate benefits, their environmental performance is highly dependent on formulation choices, processing energy, use-phase behavior, and end-of-life management. These interdependencies make early-stage decision-making particularly challenging, especially when material properties must be enhanced through additives or reinforcements to meet automotive safety and durability requirements. This study addresses this challenge by proposing a structured, early-stage, lifecycle-integrated evaluation framework tailored to automotive material selection. The framework supports environmental assessment at a point in product development where materials, processes, and energy sources can still be adjusted with relatively low cost and high design freedom. By expanding conventional cradle-to-gate and cradle-to-grave assessments toward a cradle-to-reuse-to-grave (C2R2G) perspective, the framework enables comparison of both single-life and multi-life material pathways, including landfill, incineration, closed-loop reuse, and open-loop repurposing. Rather than positioning itself as a new LCA methodology, the framework systematically integrates existing LCA principles, hotspot analysis, and multi-lifecycle scenario modeling into a coherent structure suited for early-stage automotive decision-making. It allows product developers to identify emission-intensive stages, explore improvement options iteratively, and understand how early material choices influence cumulative environmental outcomes across one or more lifecycles. Importantly, the framework does not prescribe optimal material choices but instead supports transparent comparison of trade-offs between short-term emission minimization and long-term circularity objectives. The applicability of the framework was demonstrated through a case-study of an automotive seat-shell using laminated veneer lumber (LVL). While LVL showed favorable mechanical performance and low embodied emissions at the material level, the analysis revealed that conventional resin systems and fossil-based energy sources significantly increased its overall environmental footprint. Through hotspot identification, targeted substitutions of resins and energy sources were shown to substantially reduce emissions at an early design stage. End-of-life scenario analysis highlighted that different sustainability objectives lead to different preferred pathways. Landfill after a single use-life resulted in the lowest cumulative carbon emissions within the modeled assumptions, whereas open-loop reuse extended material service life and delayed carbon release over a longer time horizon. These findings illustrate that environmental ranking of end-of-life strategies is context-dependent and reinforce the importance of evaluating materials across multiple lifecycles rather than relying solely on single-life indicators. Although demonstrated using laminated veneer lumber, the mathematical formulation is material-agnostic and can be applied to metals, hybrid composites, or thermoplastic systems. However, materials with limited reuse feasibility or low substitution potential may exhibit reduced multi-life advantages. Limitations and Future Development Several limitations of the present study should be acknowledged. First, the assessment focused primarily on CF as an exemplary environmental indicator. While this aligns with current climate-driven policy priorities, it does not capture other relevant impact categories such as toxicity, resource depletion, water use, or land-use impacts, which may be particularly important for bio-based and composite materials. Future work should extend the framework to include additional midpoint impact categories to support more comprehensive sustainability assessments. Second, the framework relies on a combination of secondary data, supplier-provided information, and literature-based assumptions, particularly for use-phase behavior, end-of-life processes, decay rates, and second-life scenarios. While these assumptions were chosen to reflect realistic automotive contexts, uncertainties in data quality and variability remain. While deterministic sensitivity analysis was conducted for key parameters, uncertainties related to data quality, regional variability, and long-term assumptions remain and should be addressed through more comprehensive uncertainty analysis in future work. Third, the framework was demonstrated using a single automotive component and material system. Although the structural logic is transferable, direct extrapolation of results to other components, materials, or vehicle types should be undertaken with caution. The framework is intended to support comparative and exploratory early-stage decision-making, not to replace detailed product-specific LCAs conducted at later development stages. Finally, the current implementation of the framework is methodological rather than digital. While the assessment logic and workflows are explicitly defined, calculations were performed manually using established databases. A natural next step is the development of a user-oriented implementation that operationalizes the framework into a configurable assessment environment. Such an implementation could allow users to select parameters such as vehicle type (e.g., internal combustion or electric), service life, distance travel, and reuse scenarios, and to evaluate multiple materials or design iterations consistently. Importantly, such a development would not alter the framework itself but would enhance its accessibility, reproducibility, and practical adoption in industrial contexts. By providing a lifecycle-integrated, automotive-specific structure for early-stage material evaluation, this work contributes to bridging the gap between academic lifecycle assessment methods and practical material-selection challenges faced by automotive product developers. As regulatory pressure and circular-economy ambitions continue to grow, such structured early-stage frameworks can play a key role in enabling informed, transparent, and forward-looking sustainability decisions. Declarations Disclosure statement The authors report no potential conflict of interest. Funding This work was supported by the BMW Group’s research and development department at New Technology House, Garching (Munich). Acknowledgements The authors acknowledge the valuable insights and contributions of Matthias Franz and Thomas Gerstl from BMW Group. BMW Group and New Technology House supported this research. Data availability statement Data supporting the case study are available in the Supplementary Sheet. Other data, if required, can be made available on reasonable request to the authors. References de Araujo JB, Dieterle M, Schell L, Herrmann T, Haug M, Viere T (2024) How do LCA studies support CE? A systematic case-study review. J Circular-Economy, 2(3) Ahmed E, Wiyao A, Ghoniem E, Elmarakbi A (2024) Modelling of hybrid biocomposites for automotive structural applications. Compos Sci Technol, 251(10) Allacker K, Mathieux F, Manfredi S, Pelletier N, Ardente F, Pant R, Suh S (2022) The need for and principles of a lifecycle-based circularity assessment framework: Towards more circular and sustainable products. Int J Lifecycle-assessment 27(2):375–388 Jerome A, Ljunggren M (2025) Product-lifetime in lifecycle-assessments of circular-economy strategies — A review and consolidation of methodology. Int J Lifecycle-assessment 30:2162–2189 Amienyo D (2012) Lifecycle sustainability assessment in the UK beverage-sector (Doctoral-dissertation). University of Manchester, School of Chemical Engineering and Analytical Science Liu Y, Zhang L, Wang Y (2024) Reducing greenhouse gas emissions in China’s automobile manufacturing through circular-economy strategies: A closed-loop recycling perspective. Environmental-impact Assess Rev 94:106758 Bassam H, Luennemann P, Riedelsheimer T, Lndow K (2024) A Model-Based Methodology for Lifecycle-assessment from Cradle-to-Grave Early in Product-Design. Procedia CIRP 128:662–667 Zanghelini GM, Cherubini E, Soares SR (2018) How Multi-Criteria Decision Analysis (MCDA) is aiding Lifecycle-Assessment (LCA) in results interpretation. J Clean Prod 172:609–622 Rognoli V, Pollini B (2021) Early-stage material-selection based on the lifecycle approach, including tools, obstacles, and opportunities for design. Sustainable Prod Consum 28:1130–1139 Bach V, Minkov N, Finkbeiner M (2018) Assessing the ability of the Cradle-to-Cradle Certified™ Products Program to reliably determine the environmental-performance of products. Sustainability 10(5):1562 Ciastowicz Ż, Pamuła R, Białowiec A (2024) Utilization of Plant Oils for Sustainable Polyurethane Adhesives. Rev Mater 17(8):1738 European Parliament & Council of the European Union (2024) Regulation (EU) 2024/1781 of the European Parliament and of the Council of 13 June 2024 establishing a framework for the setting of eco-design requirements for sustainable products, amending Directive (EU) 2020/1828 and Regulation (EU) 2023/1542, and repealing Directive 2009/125/EC. Official J Eur Union 202:1–30 European Commission (2025) The Clean Industrial Deal: A joint roadmap for competitiveness and decarbonization (COM(2025) 85 final). Official Journal of the European Union. European Commission, Brussels, Belgium Piekarski CM, de Francisco AC, da Luz LM, Kovaleski JL, Lopes Silva DA (2017) Lifecycle-assessment of the medium-density fiberboard (MDF) manufacturing process in Brazil. Sci Total Environ 575:103–111 Cojocariu C, Barjoveanu G, Teodosiu C, Robu B (2015) Environmental-impact and risk quantification based on selected water quality indicators. Nat Hazards 75(1):89–105 Ragab A, Ramzy A (2023) Cradle-to-Gate Lifecycle-assessment of Bottle-to-Bottle Recycling Plant: Case-study. In: Wohlgemuth V, Naumann S, Behrens G, Arndt HK, Höb M (eds) Advances and New Trends in Environmental Informatics. ENVIROINFO 2022. Springer, Cham Verband der Automobilindustrie (VDA) (2023) Sustainability in the German automotive industry: A roadmap for the future ISO 14040 (2006a) Environmental Management - Lifecycle-assessment - Principles and Framework. Geneva ISO 14040 (2006b) Environmental Management - Lifecycle-assessment - Requirements and Guidelines. Geneva Soo VK, Doolan M, Compston P, Duflou JR, Peeters J, Umeda Y (2021) The influence of end-of-life regulation on vehicle material circularity: A comparison of Europe, Japan, Australia and the US. Resources, Conservation & Recycling. 168, Article 105294 Sable S, Ikar M, Dudheinamdar P (2024) Exploring the Complexities and Challenges of Plastic Recycling: A Comprehensive Research Review. In: Sumesh, M., R. S. Tavares, J.M., Vettivel, S.C., Oliveira, M.O. (eds) 2nd International Conference on Smart Sustainable Materials and Technologies (ICSSMT 2023). Advances in Science, Technology & Innovation. Springer, Cham Vusić D, Vujanić F, Pešić K, Šafran B, Jurišić V, Zečić Ž (2021) Variability of normative properties of wood chips and implications for quality control. Energies 14(13):3789 EUCAR (1998) Eucar-automotive LCA guidelines- phase 2 (982185). Lynne Ridge, Rover Group Ltd. (Coordinator Bieker G et al (2021) A global comparison of the lifecycle greenhouse gas emissions of combustion engine and electric passenger cars. ICCT – International Council on Clean Transportation Europe Grabowski A, Selke SEM, Auras R (2015) Lifecycle inventory data-quality issues for bioplastics feedstocks. Int J Lifecycle-assessment 20:584–596 Gross electricity production in Germany in (2022) Retrieved from https://www.destatis.de/EN/Themes/Economic-Sectors-Enterprises/Energy/Production/Tables/gross-electricity Shabbir H, Gheewala SH (2023) Lifecycle-assessment for sustainability assessment of biofuels and bioproducts. Biofuel Res J 10(1):1810–1815 U.S. Energy Information Administration. (n.d.). Wind explained: Wind energy and the environment. 1000 Independence Ave., SW Washington, DC Jaśkiewicz A, Kasprzyk J (2023) The right to clean air is a unique form of the right to environmental protection, international and national regulations. Environ Prot 45(2–4):46–60 Buban DJ, Relano R-J, Concepcion R, Culaba A (2023) Cradle-to-Gate Environmental-impact Assessment of a Polylactic Acid Polymer-Based Adjustable Air Stone for Adjustable Microbubbles Generation. 2023 IEEE 15th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), Coron, Palawan, Philippines, 1–6 Grenz J, Ostermann M, Käsewieter K, Cerdas F, Marten T, Herrmann C, Tröster T (2023) Integrating Prospective LCA in the Development of Automotive Components. Sustainability 15(13):10041 Kumar PL, Chaudhary V, Gupta P, Mehta J, Gupta K (2024) Inherent roadmap in the synthesis and applications of sustainable materials using oil-based and microbial polymers. Mater Today Sustain 25:100615 Zuiderveen E, Kuipers JJ, Caldeira C (2023) & others. The potential of emerging bio-based products to reduce environmental-impacts. Nature Communications, 14, 8521 Brunklaus B, Riise E (2018) Bio-based Materials Within the Circular-economy: Opportunities and Challenges. In: Benetto E, Gericke K, Guiton M (eds) Designing Sustainable Technologies, Products and Policies. Springer, Cham, pp 43–47 Korhonen J, Honkasalo A, Seppälä J (2018) Circular-economy: the concept and its limitations. J Clean Prod 175:544–552 Malabi Eberhardt LC, van Stijn A, Nygaard Rasmussen F, Birkved M, Birgisdottir H (2020) Development of a Lifecycle-assessment Allocation Approach for Circular-economy in the Built Environment. Sustainability 12(22):9579 Levasseur A, Lesage P, Margni M, Deschenes L, Samson R (2010) Considering time in LCA: Dynamic LCA and its application to global warming impact assessments. Environ Sci Technol 44:3169–3174 Markatos DN, Pantelakis SG (2022) Assessment of the impact of material-selection on aviation sustainability from a circular-economy perspective. Aerospace 9(2):52 Ghosh A, Roy A (2020) Renewable and Sustainable Materials in the Automotive Industry. Encyclopedia of Renewable and Sustainable Materials, vol 3. Elsevier, pp 162–179 Maiti S, Islam MR, Uddin MA, Afroj S, Eichhorn SJ (2022) Sustainable Fiber-Reinforced Composites: A Review. Adv sustainable Syst 6(11):2200258 Müller LJ, Kätelhön A, Bachmann M, Zimmermann A, Sternberg A, Bardow A (2020) A Guideline for Lifecycle-assessment of Carbon-Capture and Utilization. Front Energy Res 8(15):1–20 Roberts M, Cascione V, Allen S, Dams B, Maskell D, Coley D (2022) Applying lifecycle-assessment with minimal information to support early-stage material-selection. Acta Polytechnica CTU Proceedings, 38, 44–49 He X, Su D, Cai W, Pehlken A, Zhang G, Wang A, Xiao J (2021) Influence of material-selection and product design on automotive vehicle recyclability. Sustainability 13(6):3407 Goucher-Lambert N, Goridkov N, Wang Y (2023) Challenges in extracting insights from lifecycle-assessment documents during early-stage design. Proceedings of the Design Society, 3, 837–846 Nguyen T (2023) Climate effects of post-use wood materials from the building sector in a system perspective. Waste Manag 170:317–328 Zhang L, Na Z (2020) The lignin-based phenolic resin was modified with whisker silicon for its application. J Bioresources Bioprod 5(1):67–77 Paraskevas D, Kellens K, Dewulf W, Duflou JR (2015) Environmental modelling of aluminium recycling: A Lifecycle-assessment tool for sustainable metal management. Resources, Conservation and Recycling, 102, 59–70 Falcone PM, Morone P, Sica E (2021) Greening the construction industry: The role of green public procurement and lifecycle costing in circular-economy transition. J Clean Prod 323:129023 Pihkola H, Pajula T, Tapia C, Smith L (2016) Sustainability assessment methods and tools to support decision-making in the process industries. VTT Technical Research Center of Finland, Tecnalia Research, and Innovation. SAMT Deliverable 3.1 Panda H, Sahu RK, Biswal B, Mahapatra SS (2016) Lifecycle-assessment for cleaner production: A case-study of a woven fabric manufacturing industry. J Clean Prod 112:1233–1241 Rebitzer G, Stepnicka K et al (2021) Advances in Lifecycle-assessment methods and applications. Int J Lifecycle-assessment 26(5):1103–1116 Rocca R, Acerbi F, Fumagalli L (2023) Development of an LCA-based tool to assess the environmental sustainability level of cosmetics products. Int J Lifecycle Assess 28:1261–1285 Soukka R, Järv S, Liikanen M, Grönman K Environmental-impacts of lignin-based resin in plywood production (, Thesis MS (2023) Lappeenranta–Lahti University of Technology LUT, LUT School of Energy Systems Environmental Technology Skosana S, Khoathane C, Malwela T (2025) Driving towards sustainability: A review of natural fiber reinforced polymer composites for eco-friendly automotive light-weighting. J Thermoplast Compos Mater 38(2):754–780 Inalegwu OS, Liu S (2021) Integration of algae cultivation to anaerobic digestion for biofuel and bioenergy production. Adv Bioenergy 6(1):199–300 Winter S, Quernheim N, Arnemann L, Anderl R, Schleich B (2023) Framework for comparison of product carbon footprints of different manufacturing scenarios. Proceedings of the Design Society, 3, 1935–1944 Nordahl SL, Scown CD (2024) Recommendations for life-cycle assessment of recyclable plastics in a circular-economy. Chem Sci 15:9397–9407 Persson A, Ramamoorthy SK, Skrifvars M (2015) A review of natural fibers used in biocomposites: Plant, animal, and regenerated cellulose fibers. Polym Rev 55:107–162 Suh SC, Kim YC (2020) Data needs and challenges for lifecycle-assessment (LCA) of emerging materials. Environ Sci Technol 54:24 abrizi TB, Brambilla A (2019) Toward LCA-lite: A simplified tool to easily apply LCA logic at the early design-stage of building in Australia. Eur J Sustainable Dev 8(5):383–396 IEA (2022) The role of critical minerals in clean energy transitions Suhariyanto TT, Wahab DA, Raham MN (2017) Multi-Lifecycle-assessment for sustainable products: A systematic review. J Clean Prod 165:677–696 Leiden University and CML-IA Characterization Factors (2023) CML-IA characterization factors Ulrich AE (2019) Cadmium governance in Europe’s phosphate fertilizers: Not so fast? Sci Total Environ 650:541–545 Additional Declarations No competing interests reported. Supplementary Files Supplymentdatanew.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 06 May, 2026 Reviewers agreed at journal 22 Apr, 2026 Reviewers agreed at journal 21 Apr, 2026 Reviewers agreed at journal 21 Apr, 2026 Reviewers agreed at journal 20 Apr, 2026 Reviewers invited by journal 19 Apr, 2026 Editor assigned by journal 24 Mar, 2026 Submission checks completed at journal 18 Mar, 2026 First submitted to journal 17 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9148035","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":627550148,"identity":"420b3d12-f7b8-412b-9a8f-b07a54e52015","order_by":0,"name":"Arushi Jaswal","email":"data:image/png;base64,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","orcid":"","institution":"BMW Group (Germany)","correspondingAuthor":true,"prefix":"","firstName":"Arushi","middleName":"","lastName":"Jaswal","suffix":""},{"id":627550149,"identity":"7d02215f-ebcc-4965-baa6-d2edfdc25632","order_by":1,"name":"Stefan Koensgen","email":"","orcid":"","institution":"BMW Group (Germany)","correspondingAuthor":false,"prefix":"","firstName":"Stefan","middleName":"","lastName":"Koensgen","suffix":""}],"badges":[],"createdAt":"2026-03-17 11:09:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9148035/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9148035/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108008731,"identity":"f2cd059a-4c9b-4bd6-8f6a-5dfb017973c3","added_by":"auto","created_at":"2026-04-28 13:08:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":46307,"visible":true,"origin":"","legend":"\u003cp\u003eThe flow shows a step-by-step literature review.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9148035/v1/813bcdb2eb374ae804547142.png"},{"id":108007933,"identity":"e18f4a36-2917-40d0-89ed-adee2dee3949","added_by":"auto","created_at":"2026-04-28 13:04:49","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":114908,"visible":true,"origin":"","legend":"\u003cp\u003eDefinition of early-stage for experts.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-9148035/v1/7d3390f4141e242520d7fc1f.png"},{"id":108007997,"identity":"8460812e-a3bc-4caa-8340-bd16a7c5d232","added_by":"auto","created_at":"2026-04-28 13:05:04","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":842277,"visible":true,"origin":"","legend":"\u003cp\u003eThe framework illustrates flow annotation for (a) the conceptual model of automotive materials in both open (green) and closed-loop (red) approaches. Boxes represent the main-lifestages: raw-material extraction, processing, use-stage, collection and dismantling, and waste collection strategies, connected by a black line. Dark blue lines indicate the end-of-life waste flow from each stage, while light blue shows End-of-life material-flow to recycling centers. Red lines denote the reuse potential of recycled and waste materials in a closed-loop system. Waste can serve as an energy source for production (black dotted lines) within a closed-loop. Green lines illustrate material reuse (repurposing) in other industries, such as construction, in an open-loop. The extension for second-life use, particularly in the automotive sector due to high demands, necessitates recycling or repurposing at end-of-life. (b) Waste collection strategies include organic (bio-based), recyclable (metals and some polymers), and non-recyclable (ASR) materials. Organic and recycled waste can be repurposed for a second-life, while non-recycled waste is directed to incineration for energy generation or landfills.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9148035/v1/25afabba3da6603cd9a9ab40.png"},{"id":108007990,"identity":"7dcf11ba-1eb7-49a8-a786-19dcc3461c54","added_by":"auto","created_at":"2026-04-28 13:04:59","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":288975,"visible":true,"origin":"","legend":"\u003cp\u003eAn exemplary vision for cascading lifecycles for wood-based products in automotive, followed by closed-loop and open-loop utilization in automotive or the furniture industry.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-9148035/v1/f054604f6f4c0156d88c018a.png"},{"id":108008033,"identity":"788bf7d3-30ce-48f4-b560-9e0f716cc37d","added_by":"auto","created_at":"2026-04-28 13:05:15","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":610645,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Illustration of the material and information flow across the product lifecycle within the C2R2G system boundary, (b) Illustrates the structured analytical workflow used to evaluate materials under the C2R2G model.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-9148035/v1/0cf1d5e57b7c740814b9ea0c.png"},{"id":108008655,"identity":"1c3d19b7-7539-4449-89d4-96604bff0c3b","added_by":"auto","created_at":"2026-04-28 13:07:48","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":368260,"visible":true,"origin":"","legend":"\u003cp\u003eThe material and process flow for LVL, starting from Forestry Operation, followed by Veneer Production, and finally, LVL production at the plant.\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-9148035/v1/1fb902fd0bda69e8178fdfdc.png"},{"id":108008721,"identity":"83dd0d79-2aef-4846-8ff6-cd65330bfc5c","added_by":"auto","created_at":"2026-04-28 13:08:10","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":150202,"visible":true,"origin":"","legend":"\u003cp\u003eEnd-of-life scenarios for Open-loop and Closed-loop possibilities for LVL made from beech wood on a time scale of 80.\u003c/p\u003e","description":"","filename":"floatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-9148035/v1/c5e7afc66d446f7203ac34ba.png"},{"id":108007926,"identity":"238a322b-581e-42b2-a727-aa5ee5c41d43","added_by":"auto","created_at":"2026-04-28 13:04:45","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":334478,"visible":true,"origin":"","legend":"\u003cp\u003eThe plots represent: (a) CO\u003csub\u003e2\u003c/sub\u003e footprint per different categories/Stages with and without stored-carbon, (b) the contribution from individual input towards total emissions during Raw-material , production, packaging, and transport stages, aiming \u003cstrong\u003eenvironmental burden points\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e8 \u003c/strong\u003e\u003c/sup\u003eanalysis (c) Total contribution per various stages of a seat-shell as a final product.\u0026nbsp;\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-9148035/v1/5b3129fe494d7dd5cb01efbd.png"},{"id":108007998,"identity":"043425e5-f55c-462d-a44f-271490bf7b2f","added_by":"auto","created_at":"2026-04-28 13:05:04","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":811924,"visible":true,"origin":"","legend":"\u003cp\u003eThe graphical representation of (a) instantaneous radiative forcing for automotive seat-shells according to different End-of-life scenarios, W = watts, (b) cumulative radiative forcing for automotive seat-shells according to different End-of-life scenarios, W = watts, and (c) instantaneous radiative forcing (Zoomed view) for automotive seat-shell according to different End-of-life scenario, W = watt\u003c/p\u003e","description":"","filename":"floatimage12.png","url":"https://assets-eu.researchsquare.com/files/rs-9148035/v1/ee1e7e97f049a266663bf13c.png"},{"id":108011640,"identity":"e42ca463-ef0b-4108-b053-0358fe4d4380","added_by":"auto","created_at":"2026-04-28 13:15:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4100462,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9148035/v1/1d1540e4-6b49-4db0-95ca-39dfb7619aa1.pdf"},{"id":108007994,"identity":"5f3e0596-10e7-41c5-8855-d3fa9d93e13f","added_by":"auto","created_at":"2026-04-28 13:05:02","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":984187,"visible":true,"origin":"","legend":"","description":"","filename":"Supplymentdatanew.docx","url":"https://assets-eu.researchsquare.com/files/rs-9148035/v1/686eb71d29a828ed708bcad5.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"An Early-Stage, Multi-Lifecycle Assessment Framework for Sustainable Material Selection in Automotive Industry","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe use of conventional materials in industrial products contributes substantially to greenhouse gas (GHG) emissions, resource depletion, and waste generation across all life cycle stages. In the automotive sector, material choices and manufacturing processes are particularly critical, as they strongly influence production- and use-stage emissions[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Approximately 80% of total GHG emissions from passenger vehicles arise from these two stages, driven largely by material selection and fuel consumption[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In response, international institutions have introduced increasingly stringent environmental and emissions-control policies targeting the transport sector[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRecent research identifies several strategies for reducing environmental impacts in automotive systems, including the use of renewable materials, lightweight design to reduce fuel consumption, and improved material reusability[\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. These developments reinforce the need to evaluate environmental impacts across the full vehicle-lifecycle rather than focusing solely on tailpipe emissions. In this context, circular-economy principles\u0026mdash;emphasizing material circulation, waste reduction, and reduced reliance on virgin resources\u0026mdash;have gained prominence, supported by recent European policy initiatives targeting durability, recyclability, and circular material use in the automotive sector[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e][\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e][\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDuring early-stage product development, materials are defined at the ingredient level, creating opportunities to replace conventional inputs with bio-based polymers or composites. While such materials can offer environmental advantages, they often exhibit limitations in mechanical performance, durability, or consistency[\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. To meet automotive requirements, additives or coupling agents are frequently introduced, which can substantially reduce the expected environmental benefits[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. As a result, material substitution decisions involve complex trade-offs across design, production, and end-of-life stages, underscoring the need for robust early-stage assessment approaches.\u003c/p\u003e \u003cp\u003eMost existing material assessment approaches remain anchored in cradle-to-gate or cradle-to-grave system boundaries and are poorly suited to evaluating reuse or multi-life scenarios, particularly for emerging bio-based materials where data availability is limited[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e][\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. As a result, early-stage material screening often struggles to capture end-of-life trade-offs and reuse potential in a consistent manner, limiting informed decision-making[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCollectively, these gaps indicate the need for structured approaches that incorporate multi-life perspectives while remaining applicable during early-stage product development. In the absence of such approaches, product developers and early-stage practitioners face limitations in systematically comparing sustainable alternatives to conventional materials, which can slow progress toward more circular automotive products[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAccordingly, this study presents an early-stage, LCA-based framework for evaluating the environmental performance of sustainable materials prior to their application in automotive components. The framework applies extended system boundaries to compare single-life and multi-life pathways under consistent assumptions, enabling early-stage comparative reasoning across production, use, and end-of-life stages. A case study from the automotive domain is used to demonstrate the framework's application and practical relevance.\u003c/p\u003e \u003cp\u003eThe proposed C2R2G approach does not introduce a new-lifecycle assessment method per se, but rather operationalizes and integrates established LCA principles, system expansion logic, and circularity modeling into a structured decision-support framework tailored to early-stage automotive material selection. In contrast to dynamic LCA studies that primarily focus on temporal emission trajectories and time-dependent characterization factors, the present framework emphasizes comparative multi-life system boundary structuring under alternative end-of-life and reuse configurations. The analytical contribution therefore lies in (i) formalizing reuse-inclusive system boundaries for early design screening, (ii) explicitly structuring second-life allocation logic within automotive component assessment, and (iii) enabling transparent comparison of single-life versus multi-life design pathways under consistent boundary conditions.\u003c/p\u003e"},{"header":"2. Literature Review","content":"\u003cp\u003eA structured literature review was conducted using Scopus, ScienceDirect, and Web of Science, focusing on lifecycle-based sustainability assessment and material selection in the automotive sector. The review covered methodological developments, LCA applications, and automotive case studies, with particular attention to circular-economy principles and lifecycle integration. The step-by step process is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and details of the search strategy and screening process are provided in Supplementary-Sheet B.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe literature shows a steady increase in automotive LCA research over the past decade. Earlier studies (2015\u0026ndash;2020) primarily focused on cradle-to-gate or cradle-to-grave assessments aimed at manufacturing optimization[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e][\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. More recent work increasingly includes use-phase and end-of-life stages; however, only a limited number of studies explicitly address multi-lifecycle scenarios such as reuse or second-life applications, mainly outside the automotive sector[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e][\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Within automotive applications, LCAs often terminate at disposal or recycling, limiting their relevance for long-life components with complex material compositions[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThese observations indicate that existing approaches provide limited support for evaluating material choices across multiple-lifecycle loops during early-stage automotive design.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Evolution of Sustainable Material Research Toward-lifecycle Integration\u003c/h2\u003e \u003cp\u003eEarly research on sustainable automotive materials primarily examined bio-based or renewable alternatives to conventional composites[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e][\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e], often highlighting potential GHG reductions through biogenic carbon uptake and lower embodied energy[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. These studies commonly treated sustainability as a material substitution problem, focusing on replacing conventional feedstocks rather than considering material behavior across successive product lifecycles.\u003c/p\u003e \u003cp\u003eIn practice, the environmental advantages of bio-based materials can diminish when additives, reinforcements, or chemical treatments are introduced to meet automotive performance requirements[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e][\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Key factors such as material composition, processing routes, reuse potential, and recycling behavior are frequently excluded from early evaluations, despite their significant influence on total emissions[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Bach et al.[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] further noted that certification schemes such as Cradle-to-Cradle often overlook material evolution over time, limiting their ability to represent true circularity. Recent studies increasingly emphasize that sustainability depends not only on material origin but also on its performance and recoverability across multiple use-stages[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough concept-stage design offers the greatest flexibility to influence material choice and recovery strategies, most LCA studies still assume conventional processes and single end-of-life scenarios[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e][\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Consideration of carbon storage, reuse pathways, or burden allocation across lifecycles remains limited, particularly for automotive components with long service lives[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e][\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOverall, sustainable material research is gradually shifting from evaluating isolated material footprints toward understanding cumulative impacts across multiple lifecycles. Applying multi-lifecycle LCA concepts at early stages can help identify influential parameters related to formulation, processing, energy use, and recovery strategies before materials are implemented in automotive components[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e][\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Barrier in early-stage material assessment\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn automotive design, material decisions made during the concept or early design phases can account for up to 60\u0026ndash;70% of lifetime environmental impacts, underscoring the importance of early-stage LCA-based assessment[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e][\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. To support such assessments, simplified or \u0026ldquo;LCA-lite\u0026rdquo; approaches have been developed and applied successfully in domains with standardized design templates, such as the building sector[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e][\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e][\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. However, these approaches often rely on fixed assumptions, limited indicators, and simplified system boundaries, making them less suitable for applications where sequential lifecycles and recovery pathways significantly influence cumulative impacts[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA key barrier in early-stage material assessment is data scarcity and uncertainty. Emerging materials often lack validated lifecycle inventory data, while information on processing routes, additives, or treatments remains incomplete[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e][\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Time constraints, limited modelling capacity, and insufficient LCA expertise further restrict designers' ability to conduct scenario-based assessments, often resulting in truncated system boundaries that exclude later lifecycle stages[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e][\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. As a result, conventional LCA approaches frequently retain a single-lifecycle focus and overlook reuse or remanufacturing opportunities[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThese limitations are particularly relevant for the automotive sector, where early-stage decisions largely determine long-term environmental performance. Although policy targets related to recycled content and circularity emphasize lifecycle-aware material selection[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e][\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], accessible and scientifically robust multi-lifecycle assessment methods for early-stage design remain limited.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 \u003cb\u003eLimited consideration of multi-lifecycle-assessments at an early-stage\u003c/b\u003e\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTraditional LCA models are largely static, assessing products from cradle-to-gate or cradle-to-grave and terminating after a single use-stage[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e][\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. While some studies extend system boundaries to include recycling or reuse, few explicitly model multiple sequential lifecycles at the product level[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e][\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e][\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e][\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Although methodological advances have been made in modelling temporal dynamics, allocation rules, and cascading use scenarios[\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e][\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e], these approaches often require substantial modelling effort and remain difficult to implement within standard LCA tools.\u003c/p\u003e \u003cp\u003eIn the automotive sector, the challenge is amplified by the widespread use of mixed polymers and composite materials in components such as seats, dashboards, and body panels, which complicates recovery and reuse[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e][\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. As a result, LCAs typically assume linear lifecycles, even where reuse or remanufacturing may be technically feasible. Common databases and inventories also lack modules for representing sequential lifecycles[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Consequently, early-stage assessments often favor materials with low initial embodied emissions, despite limited reuse or recycling potential.\u003c/p\u003e \u003cp\u003eThis single-lifecycle bias can yield short-term emission reductions while obscuring longer-term inefficiencies in resource and carbon management[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Multi-lifecycle approaches, by contrast, enable comparison based on cumulative performance across successive use-stages, revealing trade-offs that remain invisible in conventional assessments[\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Need for Sector-Specific, Lifecycle-Integrated Assessment Frameworks\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAutomotive components present distinct challenges for environmental assessment due to long service lives, stringent safety requirements, and regulated end-of-life treatment processes involving dismantling, shredding, and sorting[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e][\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e][\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Although commercial LCA tools such as SimaPro, OpenLCA, and GaBi are widely used, they remain largely generic and provide limited support for explicitly modelling reuse, remanufacturing, or closed-loop pathways relevant to circular automotive design[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeveral studies have highlighted the need to better integrate LCA with circular-economy concepts in order to consistently capture reuse, second-life, and recycling scenarios[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e][\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. For automotive designers, this would enable comparative evaluation of different material strategies, such as long-life reuse-oriented options[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], low initial-impact options suited to single-use applications[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], or recycling-priority options optimized for material recovery[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Early-stage scenario analysis of this kind can support more informed trade-offs between durability, recyclability, and carbon intensity, aligning environmental assessment with the practical realities of automotive product development.\u003c/p\u003e \u003cp\u003eTable A(a) in Appendix 1 summarizes the existing tools/frameworks used for material or product environmental assessments and how they map the problems identified in sections \u003cspan refid=\"Sec3\" class=\"InternalRef\"\u003e2.1\u003c/span\u003e to \u003cspan refid=\"Sec6\" class=\"InternalRef\"\u003e2.4\u003c/span\u003e. Additionally, to clarify the methodological positioning of the C2R2G framework relative to existing approaches, Table A(b) in Appendix 1 summarizes key analytical distinctions. The framework does not replace dynamic LCA but complements it by formalizing structured multi-life boundary modeling specifically for early-stage automotive component comparison.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eInterconnection\u003c/strong\u003e \u003cp\u003eThe challenges outlined in Sections \u003cspan refid=\"Sec3\" class=\"InternalRef\"\u003e2.1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Sec6\" class=\"InternalRef\"\u003e2.4\u003c/span\u003e are closely interconnected and reflect broader limitations in current assessment practices within the automotive sector. Data variability and uncertainty associated with emerging materials (Section \u003cspan refid=\"Sec3\" class=\"InternalRef\"\u003e2.1\u003c/span\u003e) are compounded by the lack of early-stage assessments for anticipating material behavior across successive lifecycles. The barriers described in Section \u003cspan refid=\"Sec4\" class=\"InternalRef\"\u003e2.2\u003c/span\u003e\u0026mdash;data scarcity, time constraints, and methodological complexity\u0026mdash;limit designers\u0026rsquo; ability to incorporate lifecycle thinking during concept and material-selection stages. Further in Section \u003cspan refid=\"Sec5\" class=\"InternalRef\"\u003e2.3\u003c/span\u003e, the predominance of cradle-to-grave modelling further constrains early-stage evaluations, often leading to material choices based solely on initial embodied impacts. These limitations are exacerbated by the sector-specific challenges (Section \u003cspan refid=\"Sec6\" class=\"InternalRef\"\u003e2.4\u003c/span\u003e), where long service-lives, complex material systems, and unregulated end-of-life processes complicate lifecycle modelling.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eTaken together, the literature suggests a need for early-stage assessment approaches that can connect material selection decisions with longer-term environmental outcomes across multiple-lifecycle pathways in automotive applications. Addressing this need can support more consistent comparison of material options and improve alignment between early design decisions and circular-economy objectives.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Materials and methods","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Interview with Experts\u003c/h2\u003e \u003cp\u003eExploratory consultations were conducted with automotive experts, including material scouts, design engineers, sustainability managers, and LCA practitioners, to understand when environmental assessments are considered during material selection and how early-stage evaluation is perceived in practice. To isolate environmental considerations, participants were informed that all candidate materials were assumed to meet mechanical and functional requirements.\u003c/p\u003e \u003cp\u003eTen experts representing different stages of product development participated. Most identified the project definition and early concept phases as critical points at which environmental performance should be considered (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Key challenges highlighted included limited availability of transparent supplier data, uncertainty in early-stage environmental estimates, and difficulties in comparing materials under incomplete information. Several participants noted that late-stage material changes become costly once simulation and validation processes are established, while early-stage results may differ from final Environmental Product Declarations (EPDs).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDespite these limitations, participants broadly agreed that a structured, multi-lifecycle assessment framework could provide useful reference values for early material comparison, support learning, and inform management decisions. Insights from these consultations were used to define the scope and practical orientation of the framework presented below, rather than to validate quantitative results.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Conceptual framework for material-flow, including Open and Closed-Loop pathways and Waste Collection Strategies\u003c/h2\u003e \u003cp\u003eBuilding on the requirements identified in Section 2 and the insights gained from expert consultation, this section presents a structured framework for representing material flows across multiple lifecycles. The framework combines a conventional cradle-to-gate assessment with extended-lifecycle pathways, enabling early-stage exploration of how materials may evolve through reuse, repurposing, recycling, or disposal in closed- and open-loop systems. The framework organizes established LCA and circularity concepts into a structure suitable for early-stage automotive applications.\u003c/p\u003e \u003cp\u003eThe framework adapts the cradle-to-grave structure proposed by Amienyo et al.[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] to reflect automotive-specific conditions, including component service life, dismantling processes, and regulated end-of-life treatment. In particular, the end-of-life stage is expanded to capture the possibility of reuse within the same industry (closed-loop) or repurposing in other sectors (open-loop), alongside waste collection and sorting processes relevant to bio-based materials in automotive waste streams.\u003c/p\u003e \u003cp\u003eAs illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea, lifecycle stages are represented as discrete blocks connected by material transport flows. Solid black lines represent material flows from cradle-to-gate, while blue lines indicate pathways following the first end-of-life stage. Materials recovered at end-of-life may be reused or recycled through closed-loop pathways within the automotive sector or open-loop pathways into other industries. Recycling processes may involve shredding and sorting, enabling reuse of materials in secondary automotive components or repurposing in sectors such as furniture or construction, as illustrated conceptually in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Energy recovery through incineration represents an additional pathway for material utilization where reuse or recycling is not feasible.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eNot all materials recovered from waste streams are suitable for further use. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb therefore illustrates systematic waste-sorting strategies for unusable end-of-life materials. Automotive waste streams often consist of heterogeneous mixtures of metals, polymers, and bio-based materials. While metals such as steel and aluminum can typically be sorted with minimal quality loss[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], polymeric and bio-based composites present greater separation challenges[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Accordingly, sorted waste is categorized into organic waste, recyclable waste, and non-recyclable waste. Organic waste may be further separated into wet and dry fractions, with wet waste directed toward composting or bio-methanation and dry waste used as raw material for lower-performance components. Recyclable waste includes polymer-based materials containing fillers or fibers that can be reprocessed for downstream applications. Non-recyclable waste, characterized by complex material mixtures, is assumed to be suitable for incineration with energy recovery.\u003c/p\u003e \u003cp\u003eTogether, the conceptual models presented in Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e provide a consistent representation of material flows for conducting early-stage, multi-lifecycle LCA-based assessments of automotive materials, components, or systems.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Implementation architecture: Structural logic of the model for data flow\u003c/h2\u003e \u003cp\u003eBased on the conceptual framework described in Section 3.2, an implementation architecture is defined to structure assessment logic and data flow for consistent application. The architecture specifies how input data are organized, how emissions are calculated across lifecycle stages, and how results are interpreted to support early-stage decision-making. At this stage, architecture is presented as structured assessment logic rather than a fully implemented digital tool. The architecture follows established LCA practice, organizing the assessment into four-lifecycle stages: raw-material extraction (RM), component pre-production and production (CP), vehicle use (VU), and dismantling, collection, and end-of-life. Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea illustrates the flow of material and information across these stages within the cradle-to-reuse-to-grave (C2R2G) system boundary.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e3.3.1 System Boundaries and System Description\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe system boundary encompasses all processes from raw-material extraction through first end-of-life and potential subsequent reuse or disposal, with system expansion applied where necessary to represent open-loop applications.\u003c/p\u003e \u003cp\u003eTo manage complexity and maintain focus on material substitution, certain processes are excluded. Maintenance and repair activities during the use phase are not considered, as their contribution is assumed to be minor relative to other lifecycle stages. Auxiliary component elements, such as surface finishes or foam in the seat-shell case-study, are also excluded to avoid multi-part system complexity and to ensure that results reflect differences arising primarily from material choice.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e3.3.2 Lifecycle stages and their assessment\u003c/h2\u003e \u003cp\u003eTotal C2R2G emissions are calculated using a\u0026thinsp;\u0026minus;\u0026thinsp;1/+1 LCA accounting approach, consistent with ISO 14040 and ISO 14044[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e][\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], in which emission loads are balanced against recovery credits across lifecycle stages. Four lifecycle stages are considered.\u003c/p\u003e \u003cp\u003eThe raw-material (RM) stage estimates emissions associated with the production of material inputs used in component manufacturing. For bio-based materials, this stage also accounts for biogenic carbon storage, with benefits derived from biomass distribution and material carbon content[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Carbon estimation is performed using allometric biomass models, as detailed in Appendix 2C.\u003c/p\u003e \u003cp\u003eThe component production (CP) stage evaluates emissions from manufacturing and logistics, including machinery energy use, packaging, and waste generation. A mass balance approach is applied to quantify material and energy inputs relative to emissions and waste outputs. Land-use change is considered only for recent primary crop-based raw materials, following guidance from the German Federal Environmental Agency and the Baugesetzbuch[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Emission calculations for the RM and CP stages follow VDA guidelines (detailed in Appendix 2A)[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDuring the vehicle use (VU) stage, emissions are estimated based on the incremental contribution of component weight to vehicle fuel consumption (detailed in Appendix 2B). Vehicle category, service life, and distance travelled are fixed in this study for demonstration purposes, following EUCAR guidance[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. These parameters are not intrinsic to the framework and can be varied in future implementations to reflect different vehicle architectures, driving patterns, or powertrain types.\u003c/p\u003e \u003cp\u003eThe end-of-life stage evaluates emissions associated with disposal after first use or extension into second or subsequent lifecycles through reuse or recycling. The choice between disposal and reuse depends on material condition and contamination, as discussed in Section 3.2. Closed-loop second-life applications follow the same assessment structure as the first use phase, while open-loop applications exclude use-phase emissions. Incineration with energy recovery is assessed based on calorific value, landfill emissions are modeled using IPCC-recommended decay rates[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e], and recycling emissions are calculated following the approach described in Appendix 2D. Land-use change is excluded from the End-of-life stage, as biomass regrowth is assumed to occur on the same land over long rotation periods.\u003c/p\u003e \u003cp\u003eIn addition to static accounting, climate impacts are also characterized using a dynamic LCA approach following Levasseur et al.[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. This approach accounts for the timing of emissions and evaluates instantaneous and cumulative global warming effects using radiative forcing metrics. Details of the dynamic characterization factors are provided in Appendix 2E. The combined use of static and dynamic approaches enables comparative exploration of alternative end-of-life pathways during early-stage decision-making.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e3.3.3 \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eLifecycle inventory development\u003c/span\u003e\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe lifecycle inventory (LCI) quantifies material, energy, and emission flows within the defined system boundary using a three-step process suitable for early-stage assessment.\u003c/p\u003e \u003cp\u003eFirst, material quantities are estimated using progressively refined assumptions to define the functional unit. Data is collected through simplified supplier datasheets and, where necessary, through generic information such as aggregated electricity consumption, material throughput, or transport distances. Emission factors are obtained from established databases, including Ecoinvent, OpenNexus, and GaBi, supplemented by supplier-provided data or literature where available.\u003c/p\u003e \u003cp\u003eSecond, emissions associated with all inputs are aggregated in terms of kg CO₂-equivalent per functional unit. Input\u0026ndash;output relationships are defined consistently across lifecycle stages, allowing outputs from one process to serve as inputs to subsequent processes.\u003c/p\u003e \u003cp\u003eThird, parameters for use-phase and end-of-life scenarios are selected flexibly based on vehicle category, service life, and reuse potential. In this study, fixed values are used to demonstrate the framework\u0026rsquo;s logic. However, the structure allows these parameters to be varied in future applications to reflect different vehicles, usage profiles, or recovery pathways.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003e3.3.4 Lifecycle impact assessment (LCIA)\u003c/h2\u003e \u003cp\u003eLCIA follows the EN 15804 framework commonly applied in European automotive contexts. Impacts are characterized using midpoint-based methods compatible with IPCC global warming potential over a 100-year time horizon. Accordingly, assessments in this study are performed using the CML v4.8 (2016) method[\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe LCIA workflow is organized into three modules: an early-stage cradle-to-gate assessment, a hotspot-based improvement analysis, and a circularity-oriented end-of-life evaluation, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb. The cradle-to-gate module supports comparison of alternative materials using limited data. The improvement module identifies emission-intensive stages and evaluates potential reductions through alternative inputs, such as renewable energy sources. The circularity module compares single-life and multi-life scenarios using both static and dynamic assessment results to support pathway selection.\u003c/p\u003e \u003cp\u003eTogether, these modules demonstrate how the framework supports structured, early-stage reasoning about material selection and lifecycle pathways, while remaining independent of specific software tools or interfaces.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.4 \u003cb\u003eMathematical Representation of Multi-Life Emission Accounting\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eTo enhance transparency and reproducibility, the C2R2G framework can be expressed mathematically. Total cradle-to-reuse-to-grave emissions (E\u003csub\u003etotal\u003c/sub\u003e) are calculated as:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:{E}_{total}={E}_{prod}+{E}_{use,1}+{E}_{reuse}+{E}_{use,2}+{E}_{EoL}-{C}_{substitution}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\:{E}_{prod}\\)\u003c/span\u003e \u003c/span\u003e= production emissions of the primary component\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\:{E}_{use,1}\\)\u003c/span\u003e \u003c/span\u003e= First-life use-phase emissions\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\:{E}_{reuse}\\)\u003c/span\u003e \u003c/span\u003e= emissions associated with reuse preparation (transport, processing)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\:{E}_{use,2}\\)\u003c/span\u003e \u003c/span\u003e= second-life operational emissions\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\:{E}_{EoL}\\)\u003c/span\u003e \u003c/span\u003e= end-of-life treatment emissions\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\:{C}_{substitution}\\)\u003c/span\u003e \u003c/span\u003e= avoided burden credited via system expansion\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eSubstitution credits are calculated as:\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:{C}_{substitution}=E{F}_{displaced}\\times\\:{Q}_{displaced}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:E{F}_{displaced}\\)\u003c/span\u003e\u003c/span\u003erepresents the emission factor of the displaced conventional material and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{Q}_{displaced}\\)\u003c/span\u003e\u003c/span\u003ethe functional equivalence quantity. This formulation ensures explicit allocation logic and enables consistent comparison between single-life and multi-life scenarios.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Application: A Case-study of Automotive Seat-shell","content":"\u003cp\u003eTo demonstrate the applicability of the proposed framework and illustrate its use in early-stage material decision-making, a case-study was conducted on an automotive seat-shell. The framework described in Section 3 was applied during the early design phase to compare alternative materials and explore potential improvement and end-of-life pathways. In this study, the assessment is limited to carbon footprints to simplify model development and interpretation at the early-stage. The case-study was carried out using data representative of industrial practice in Germany; however, the methodological approach itself is not geographically constrained.\u003c/p\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Automotive component for case-study\u003c/h2\u003e \u003cp\u003eThe selected component for this case-study is an automotive seat-shell. Seat-shells typically consist of both structural and non-structural elements. Non-structural components, such as electronics, wiring harnesses, and airbags, were assumed to be identical across design variants and were therefore excluded from the assessment. The analysis focuses exclusively on the structural seat-shell, which plays a key role in load transfer, crash performance, and overall seat integrity.\u003c/p\u003e \u003cp\u003eIn current automotive practice, seat structures are commonly manufactured using polymer-based materials combined with foam layers and metallic or composite reinforcements. Recycling such multi-material assemblies remains challenging due to material heterogeneity and bonding technologies.\u003c/p\u003e \u003cp\u003eThis study explores the substitution of a conventional polymer-based structural solution with three bio-based alternatives: laminated veneer lumber (LVL), a long-woven banana-fiber composite, and a paper-pulp composite. Preliminary structural and crash simulations, conducted by design specialists, confirmed that all three alternatives meet mechanical performance requirements at material-specific thicknesses of 15 mm, 18 mm, and 13 mm, respectively. The simulation methodology itself is outside the scope of this research.\u003c/p\u003e \u003cp\u003eAfter accounting for material density and mechanical performance, the resulting seat-shell weights were 4.7 kg for LVL, 5.8 kg for the banana-fiber composite, and 7.7 kg for the paper-pulp composite. Although preliminary cradle-to-gate carbon footprint estimates for 1 kg of material were similar across the three options, differences in component weight led to distinct environmental outcomes at the component level.\u003c/p\u003e \u003cp\u003eAs the primary objective of this study is to demonstrate the proposed assessment framework rather than to perform a comprehensive material comparison, subsequent sections focus on LVL as a representative example. The case-study evaluates carbon footprint (CF) only; however, the framework is equally applicable to other environmental impact categories.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Goal, Scope, and Functional Unit\u003c/h2\u003e \u003cp\u003eThe goal of this case-study is to demonstrate how the proposed multi-lifecycle framework supports early-stage material evaluation, hotspot identification, and end-of-life scenario comparison for an automotive component.\u003c/p\u003e \u003cp\u003eThe assessment was structured into three sequential stages. In Stage 1, cradle-to-gate CF estimates were developed for 1 kg of LVL (Sub-system 1.1) and scaled to the production of an automotive seat-shell (Sub-system 1.2). Stage 2 focused on identifying emission hotspots and evaluating potential improvement measures. Stage 3 assessed alternative end-of-life scenarios over a raw-material replenishment period of 80 years, corresponding to the assumed regrowth cycle of wood. Iterative loops across stages were applied where necessary to explore feasible improvement and circularity options.\u003c/p\u003e \u003cp\u003eThe functional-unit (f.u.) for Sub-system 1.1 is defined as 1 kg of LVL. For Sub-systems 1.2, 2, and 3, environmental impacts were scaled to the seat-shell by multiplying the results from Sub-system 1.1 by the final component mass.\u003c/p\u003e \u003cp\u003eThe stepwise objectives of the case-study are to:\u003c/p\u003e \u003cp\u003e1. Collect inventory data for the production of 1 kg of LVL, as detailed in Figure 6.\u003c/p\u003e\n\u003cp\u003e2. Estimate CF contributions from raw-material extraction, component production, and use-phase.\u003c/p\u003e\n\u003cp\u003e3. Identify key processes and inputs driving emissions and locate hotspots for potential improvement.\u003c/p\u003e\n\u003cp\u003e4. Estimate use-phase emissions for a seat-shell over a 20-year first-life.\u003c/p\u003e\n\u003cp\u003e5. Compare alternative end-of-life and multi-lifecycle scenarios over an 80-year assessment horizon.\u003c/p\u003e\u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Lifecycle Inventory and Lifecycle Impact Assessment\u003c/h2\u003e \u003cp\u003eThe system boundaries include the full-lifecycle of the seat-shell, from raw-material extraction through production, use, and end-of-life. Inventory data were collected for two sectors: the automotive industry for first-life and closed-loop second-life applications, and the construction sector for open-loop second-life scenarios.\u003c/p\u003e \u003cp\u003eCradle-to-gate calculations were performed using emission factors from the Ecoinvent v3.11 database. Use-phase emissions were estimated based on representative passenger-car data, while end-of-life emissions were derived from literature sources and are described in detail below.\u003c/p\u003e \u003cp\u003eLCI data were collected using structured datasheets distributed to material suppliers and production facilities (detailed in Supplementary-Sheet A). For Sub-system 1.1, LVL production was modeled through three sequential processes: forestry operations, dry veneer production, and LVL manufacturing. Forestry operations included tree cultivation, fertilizer application, and resource inputs during growth. Veneer production involved log processing and drying, while LVL manufacturing combined veneers using polyurethane resin and mechanical processing energy. Transportation and packaging were included between process steps.\u003c/p\u003e \u003cp\u003eThe stored biogenic carbon for 1 kg of LVL was calculated as \u0026minus;\u0026thinsp;1.82 kg CO₂-eq using the method described in Appendix 2C. All inventory data for this stage are reported in Supplementary-Sheet A (Tables A1 and A2).\u003c/p\u003e \u003cp\u003eIn Sub-system 1.2, LVL was transported to the production facility and processed into a seat-shell through molding, pressing, cooling, and shaping. Structural integrity was verified through finite-element simulations. Energy use, transport distances, and material losses were obtained from an industrial production line and are summarized in Supplementary-Sheet A (Table A1f).\u003c/p\u003e \u003cp\u003eDuring the use phase, emissions were estimated for a seat-shell weighing 4.7 kg installed in a representative passenger vehicle with an average mass of 1,080 kg and fuel consumption of 5.87 L/100 km. An operational lifetime of 20 years and a total driving distance of 200,000 km were assumed. These parameters were selected to demonstrate the framework\u0026rsquo;s application and do not limit its general applicability. The resulting use-phase emissions are detailed in Supplementary-Sheet A (Table A1g).\u003c/p\u003e \u003cp\u003eEnd-of-life scenarios were evaluated over an 80-year assessment horizon, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. Scenarios included incineration with energy recovery, landfill, closed-loop reuse in automotive applications, and open-loop recycling into oriented strand board (OSB) for the construction sector. Energy recovery potentials were calculated using calorific values for beech wood and polyurethane resin[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e][\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Landfill emissions were modeled using IPCC decay rates[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Recycling and reuse scenarios followed assumptions reported in the literature[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. All end-of-life inventory data are provided in Supplementary-Sheet A (Table A1h).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Sensitivity and Uncertainty Analysis\u003c/h2\u003e \u003cp\u003eTo assess robustness of the identified emission hotspots and pathway rankings, deterministic sensitivity analysis was conducted on key parameters including (i) first-life duration (\u0026plusmn;\u0026thinsp;20%), (ii) second-life duration (\u0026plusmn;\u0026thinsp;20%), (iii) decay rate assumptions for landfill scenarios (\u0026plusmn;\u0026thinsp;30%), and (iv) second-life sector energy intensity (\u0026plusmn;\u0026thinsp;25%). Results indicated that while absolute emission values vary proportionally, the relative ranking between single-life landfill, recycling, and multi-life reuse pathways remains unchanged under tested parameter ranges. The most influential variable was second-life duration, yet even under conservative lifetime reduction scenarios, reuse-inclusive pathways maintained lower cumulative emissions than single-life alternatives.\u003c/p\u003e \u003cp\u003eThese findings indicate that conclusions are structurally robust within plausible automotive design parameter ranges as also represented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSensitivity analysis scenarios, tested for model robustness\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter Varied\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRange Tested\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRanking Change\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMax Δ Emission\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirst-life duration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecond-life duration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLandfill decay rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnergy intensity reuse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;25%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"5. Results and Discussion","content":"\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e5.1 Stage 1 Cradle-to-Gate and Cradle-to-Use Results\u003c/h2\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003e5.1.1 Sub-system 1.1: LCA estimation for 1 kg of LVL production\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eSub-system 1.1 evaluated the cradle-to-gate CF of producing 1 kg of laminated veneer lumber (LVL). The calculated CF was 0.37 kg CO₂-eq when biogenic stored carbon was excluded and \u0026minus;\u0026thinsp;1.45 kg CO₂-eq when stored carbon was included. Figure\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ea presents the contribution of raw-material extraction, production, transport, and packaging under both accounting approaches.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo understand whether carbon neutrality could be achieved and to identify improvement opportunities, the individual lifecycle stages were disaggregated. With the exception of forestry operations and transportation, all stages exhibited positive contributions to total CF. Figure\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eb shows that the dominant contributors were polyurethane (PU) resin used as an adhesive and fertilizers applied during forestry operations. High impacts were also observed during dry veneer production and LVL manufacturing, primarily due to intensive energy use from diesel, grid electricity, and natural gas. Transport and packaging contributed comparatively little to overall emissions.\u003c/p\u003e \u003cp\u003eThese results highlight clear environmental burden points at an early design stage and demonstrate the framework\u0026rsquo;s capability to identify processes and inputs with the greatest mitigation potential. Based on these findings, targeted improvement scenarios were explored and are discussed in Section \u003cspan refid=\"Sec26\" class=\"InternalRef\"\u003e5.2.1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section3\"\u003e \u003ch2\u003e5.1.2 Sub-system 1.2: Seat-shell Production, Use, and Potential Improvement Scenarios\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eSub-system 1.2 extended the assessment from material production to component manufacturing and use. The cradle-to-gate CF of the LVL-based seat-shell was estimated at 4.8 kg CO₂-eq without stored carbon and \u0026minus;\u0026thinsp;4.2 kg CO₂-eq when stored carbon was included.\u003c/p\u003e \u003cp\u003eWhen the use phase was incorporated, the seat-shell installed in a representative 1,080 kg petrol vehicle generated an additional 7.51 kg CO₂-eq over a 20-year service life, accounting for an assumed annual operational decline of 2%. Figure\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ec presents the resulting cradle-to-use-stage CF of the complete component.\u003c/p\u003e \u003cp\u003eThe results clearly show that the use phase dominates total emissions, even for a lightweight component such as a seat-shell. These emissions primarily arise from fuel combustion during vehicle operation and the associated release of CO₂ and NOₓ. While the relative contribution of the seat-shell to total vehicle emissions is small, its impact becomes relevant when evaluated across long service lives and large production volumes. The results from Sub-systems 1.1 and 1.2 therefore provide the baseline against which improvement strategies were evaluated in Stage 2.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e5.2 Stage: 2 Improvement Scenarios at the Early Design Stage\u003c/h2\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003e5.2.1 Improvement Recommendation at early-stage\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eBased on the environmental burden points identified in Sub-system 1.1, improvement measures were grouped into three categories: raw-material substitution, energy source substitution, and use-phase optimization.\u003c/p\u003e \u003cp\u003eAt the material level, the primary recommendation was to replace conventional PU resin with bio-based alternatives such as lignin- or cellulose-based resins. PU resin was identified as a dominant contributor to emissions due to its fossil-based origin and energy-intensive production.\u003c/p\u003e \u003cp\u003eAt the energy level, two substitution scenarios were evaluated: replacing diesel with biodiesel and substituting natural gas with renewable natural gas (RNG). Implementing these changes reduced the cradle-to-gate CF from 0.37 kg CO₂-eq to 0.18 kg CO₂-eq, representing an approximately 50% reduction.\u003c/p\u003e \u003cp\u003eUse-phase optimization focused on reducing the flame-retardant value (FRV) through weight reduction; however, this would require structural redesign and was therefore considered outside the scope of the present study.\u003c/p\u003e \u003cp\u003eWaste generated during production was primarily associated with log cutting and milling, producing sawdust, bark, and wood chips. As these residues could not be directly reused as raw materials, they were assumed to be disposed of according to standard biodegradable waste management practices. Packaging waste was classified according to local regulations and assumed to be recyclable where applicable.\u003c/p\u003e \u003cp\u003eThese findings are consistent with previous studies identifying adhesive resins as key environmental drivers in LVL production[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. PU adhesives are known to cause air pollution and environmental degradation due to energy-intensive synthesis[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e][\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Literature suggests that lignin-based adhesives could reduce CF, although increased pressing times and energy use may partially offset these benefits[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSimilarly, high emissions from production were linked to electricity consumption and the fossil-based German grid mix during the study period[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. While switching to renewable energy sources could substantially reduce emissions, such transitions involve economic and infrastructural constraints[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e][\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. These results illustrate how the framework supports informed trade-offs rather than prescribing a single optimal solution.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003e5.3 \u003cb\u003eStage-3 E\u003c/b\u003en\u003cb\u003ed-of-life and multi-lifecycle scenario comparison\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eFollowing the evaluation of baseline performance and improvement measures, Stage 3 focused on end-of-life planning and multi-lifecycle assessment. Four End-of-life strategies were evaluated: incineration (with and without energy recovery), landfill, closed-loop recycling, and open-loop recycling. Incineration and landfill were modeled as single-use-life scenarios, while recycling options assumed two sequential use-lives.\u003c/p\u003e \u003cp\u003eIn the open-loop scenario, the seat-shell served a first-life of 20 years in an automotive application, followed by a second-life of 40 years as OSB in the construction sector. In the closed-loop scenario, the material was reused as a remanufactured automotive component for an additional 20 years.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarizes total CF results from both static (\u0026minus;\u0026thinsp;1/+1) and dynamic LCA approaches. Figures\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ea and \u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eb illustrate instantaneous and cumulative radiative forcing over the 80-year assessment horizon.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEnd-of-life scenarios representing Static (-1/+1) and Dynamic CF emissions across the whole life for one-life (Incineration, Energy recovery and landfill) and two-lives (open and closed-loop)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnd-of-life Scenario\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eDynamic CF (kg-CO2e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStatic CF (kg-CO2e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncineration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e355.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e12.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnergy Recovery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e309.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e10.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLandfill\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecycle (Open-loop, Inc.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e170.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e12.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecycle (Close-loop, Inc.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e461.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e21.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecycle (Close-loop, Landfill)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e360.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e14.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e\u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDuring the first 20 years, all scenarios exhibited identical emissions, as they shared the same production and use-phase assumptions. An initial reduction in instantaneous radiative forcing was observed due to stored biogenic carbon, which partially offset emissions from production. Throughout the first use-life, emissions increased steadily due to vehicle operation.\u003c/p\u003e \u003cp\u003eAt the end of the first-life, all scenarios showed a peak in radiative forcing resulting from dismantling, transport, and remanufacturing activities. Incineration produced the largest peak due to immediate release of stored carbon, whereas energy recovery reduced this peak through substitution of fossil energy sources. Landfill exhibited the lowest immediate impact, with emissions declining gradually over time due to slow carbon decay.\u003c/p\u003e \u003cp\u003eDuring the second-life, open-loop recycling showed comparatively lower emissions because no additional use-phase emissions occurred in the construction application. Closed-loop recycling, in contrast, accumulated additional use-phase emissions during the second automotive life, leading to higher cumulative impacts beyond approximately 40 years.\u003c/p\u003e \u003cp\u003eOverall, the results demonstrate that single-life incineration minimizes long-term carbon storage, while landfill offers low short-term emissions but limited circularity. Closed-loop recycling enables material reuse but may lead to higher cumulative emissions when additional use-phase impacts are considered. Open-loop recycling extends material lifetime and delays carbon release, offering advantages from a circular perspective despite higher emissions than landfill in absolute terms.\u003c/p\u003e \u003cp\u003eThese findings highlight that the preferred End-of-life strategy depends on the decision-maker\u0026rsquo;s priorities. If minimizing cumulative emissions is the primary objective, landfill may appear favorable. However, if extending material life and maintaining resource circulation are prioritized, open-loop recycling emerges as a compelling alternative. Importantly, the framework enables these trade-offs to be evaluated transparently at an early design stage.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003e5.4 Applicability limits and potential failure cases\u003c/h2\u003e \u003cp\u003eWhile the C2R2G framework enhances transparency in reuse-inclusive assessment, several boundary conditions may limit its applicability:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eComponents with high maintenance intensity during second-life may negate reuse benefits.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eSecond-life sectors characterized by fossil-intensive energy systems may reduce substitution credits.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eRapid material degradation or contamination may eliminate functional equivalence.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eRegulatory constraints (e.g., fire safety standards in construction reuse) may restrict real-world feasibility.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eUnder such conditions, multi-life pathways may not outperform optimized single-life recycling strategies. The framework therefore supports comparative assessment rather than prescriptive prioritization of reuse. The framework supports multi-criteria interpretation when carbon-optimal pathways conflict with regulatory or material compliance requirements. In such cases, C2R2G output should be integrated with regulatory screening tools (e.g., REACH) to support balanced decision-making rather than single-indicator optimization.\u003c/p\u003e \u003c/div\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eThe increasing adoption of bio-based materials as substitutes for conventional automotive materials reflects a broader shift toward low-carbon and circular design strategies within the automotive sector. However, while bio-based materials offer potential climate benefits, their environmental performance is highly dependent on formulation choices, processing energy, use-phase behavior, and end-of-life management. These interdependencies make early-stage decision-making particularly challenging, especially when material properties must be enhanced through additives or reinforcements to meet automotive safety and durability requirements.\u003c/p\u003e \u003cp\u003eThis study addresses this challenge by proposing a structured, early-stage, lifecycle-integrated evaluation framework tailored to automotive material selection. The framework supports environmental assessment at a point in product development where materials, processes, and energy sources can still be adjusted with relatively low cost and high design freedom. By expanding conventional cradle-to-gate and cradle-to-grave assessments toward a cradle-to-reuse-to-grave (C2R2G) perspective, the framework enables comparison of both single-life and multi-life material pathways, including landfill, incineration, closed-loop reuse, and open-loop repurposing.\u003c/p\u003e \u003cp\u003eRather than positioning itself as a new LCA methodology, the framework systematically integrates existing LCA principles, hotspot analysis, and multi-lifecycle scenario modeling into a coherent structure suited for early-stage automotive decision-making. It allows product developers to identify emission-intensive stages, explore improvement options iteratively, and understand how early material choices influence cumulative environmental outcomes across one or more lifecycles. Importantly, the framework does not prescribe optimal material choices but instead supports transparent comparison of trade-offs between short-term emission minimization and long-term circularity objectives.\u003c/p\u003e \u003cp\u003eThe applicability of the framework was demonstrated through a case-study of an automotive seat-shell using laminated veneer lumber (LVL). While LVL showed favorable mechanical performance and low embodied emissions at the material level, the analysis revealed that conventional resin systems and fossil-based energy sources significantly increased its overall environmental footprint. Through hotspot identification, targeted substitutions of resins and energy sources were shown to substantially reduce emissions at an early design stage.\u003c/p\u003e \u003cp\u003eEnd-of-life scenario analysis highlighted that different sustainability objectives lead to different preferred pathways. Landfill after a single use-life resulted in the lowest cumulative carbon emissions within the modeled assumptions, whereas open-loop reuse extended material service life and delayed carbon release over a longer time horizon. These findings illustrate that environmental ranking of end-of-life strategies is context-dependent and reinforce the importance of evaluating materials across multiple lifecycles rather than relying solely on single-life indicators.\u003c/p\u003e \u003cp\u003eAlthough demonstrated using laminated veneer lumber, the mathematical formulation is material-agnostic and can be applied to metals, hybrid composites, or thermoplastic systems. However, materials with limited reuse feasibility or low substitution potential may exhibit reduced multi-life advantages.\u003c/p\u003e \u003cp\u003e \u003cb\u003eLimitations and Future Development\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSeveral limitations of the present study should be acknowledged. First, the assessment focused primarily on CF as an exemplary environmental indicator. While this aligns with current climate-driven policy priorities, it does not capture other relevant impact categories such as toxicity, resource depletion, water use, or land-use impacts, which may be particularly important for bio-based and composite materials. Future work should extend the framework to include additional midpoint impact categories to support more comprehensive sustainability assessments.\u003c/p\u003e \u003cp\u003eSecond, the framework relies on a combination of secondary data, supplier-provided information, and literature-based assumptions, particularly for use-phase behavior, end-of-life processes, decay rates, and second-life scenarios. While these assumptions were chosen to reflect realistic automotive contexts, uncertainties in data quality and variability remain. While deterministic sensitivity analysis was conducted for key parameters, uncertainties related to data quality, regional variability, and long-term assumptions remain and should be addressed through more comprehensive uncertainty analysis in future work.\u003c/p\u003e \u003cp\u003eThird, the framework was demonstrated using a single automotive component and material system. Although the structural logic is transferable, direct extrapolation of results to other components, materials, or vehicle types should be undertaken with caution. The framework is intended to support comparative and exploratory early-stage decision-making, not to replace detailed product-specific LCAs conducted at later development stages.\u003c/p\u003e \u003cp\u003eFinally, the current implementation of the framework is methodological rather than digital. While the assessment logic and workflows are explicitly defined, calculations were performed manually using established databases. A natural next step is the development of a user-oriented implementation that operationalizes the framework into a configurable assessment environment. Such an implementation could allow users to select parameters such as vehicle type (e.g., internal combustion or electric), service life, distance travel, and reuse scenarios, and to evaluate multiple materials or design iterations consistently. Importantly, such a development would not alter the framework itself but would enhance its accessibility, reproducibility, and practical adoption in industrial contexts.\u003c/p\u003e \u003cp\u003eBy providing a lifecycle-integrated, automotive-specific structure for early-stage material evaluation, this work contributes to bridging the gap between academic lifecycle assessment methods and practical material-selection challenges faced by automotive product developers. As regulatory pressure and circular-economy ambitions continue to grow, such structured early-stage frameworks can play a key role in enabling informed, transparent, and forward-looking sustainability decisions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDisclosure statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors report no potential conflict of interest.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the BMW Group\u0026rsquo;s research and development department at New Technology House, Garching (Munich).\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge the valuable insights and contributions of \u003cstrong\u003eMatthias Franz\u003c/strong\u003e and \u003cstrong\u003eThomas Gerstl\u003c/strong\u003e from BMW Group. BMW Group and New Technology House supported this research. \u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData supporting the case study are available in the Supplementary Sheet. Other data, if required, can be made available on reasonable request to the authors.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ede Araujo JB, Dieterle M, Schell L, Herrmann T, Haug M, Viere T (2024) How do LCA studies support CE? A systematic case-study review. J Circular-Economy, 2(3)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAhmed E, Wiyao A, Ghoniem E, Elmarakbi A (2024) Modelling of hybrid biocomposites for automotive structural applications. Compos Sci Technol, 251(10)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAllacker K, Mathieux F, Manfredi S, Pelletier N, Ardente F, Pant R, Suh S (2022) The need for and principles of a lifecycle-based circularity assessment framework: Towards more circular and sustainable products. Int J Lifecycle-assessment 27(2):375\u0026ndash;388\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJerome A, Ljunggren M (2025) Product-lifetime in lifecycle-assessments of circular-economy strategies \u0026mdash; A review and consolidation of methodology. Int J Lifecycle-assessment 30:2162\u0026ndash;2189\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmienyo D (2012) Lifecycle sustainability assessment in the UK beverage-sector (Doctoral-dissertation). University of Manchester, School of Chemical Engineering and Analytical Science\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu Y, Zhang L, Wang Y (2024) Reducing greenhouse gas emissions in China\u0026rsquo;s automobile manufacturing through circular-economy strategies: A closed-loop recycling perspective. Environmental-impact Assess Rev 94:106758\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBassam H, Luennemann P, Riedelsheimer T, Lndow K (2024) A Model-Based Methodology for Lifecycle-assessment from Cradle-to-Grave Early in Product-Design. Procedia CIRP 128:662\u0026ndash;667\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZanghelini GM, Cherubini E, Soares SR (2018) How Multi-Criteria Decision Analysis (MCDA) is aiding Lifecycle-Assessment (LCA) in results interpretation. J Clean Prod 172:609\u0026ndash;622\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRognoli V, Pollini B (2021) Early-stage material-selection based on the lifecycle approach, including tools, obstacles, and opportunities for design. Sustainable Prod Consum 28:1130\u0026ndash;1139\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBach V, Minkov N, Finkbeiner M (2018) Assessing the ability of the Cradle-to-Cradle Certified\u0026trade; Products Program to reliably determine the environmental-performance of products. Sustainability 10(5):1562\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCiastowicz Ż, Pamuła R, Białowiec A (2024) Utilization of Plant Oils for Sustainable Polyurethane Adhesives. Rev Mater 17(8):1738\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEuropean Parliament \u0026amp; Council of the European Union (2024) Regulation (EU) 2024/1781 of the European Parliament and of the Council of 13 June 2024 establishing a framework for the setting of eco-design requirements for sustainable products, amending Directive (EU) 2020/1828 and Regulation (EU) 2023/1542, and repealing Directive 2009/125/EC. Official J Eur Union 202:1\u0026ndash;30\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEuropean Commission (2025) The Clean Industrial Deal: A joint roadmap for competitiveness and decarbonization (COM(2025) 85 final). Official Journal of the European Union. European Commission, Brussels, Belgium\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePiekarski CM, de Francisco AC, da Luz LM, Kovaleski JL, Lopes Silva DA (2017) Lifecycle-assessment of the medium-density fiberboard (MDF) manufacturing process in Brazil. Sci Total Environ 575:103\u0026ndash;111\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCojocariu C, Barjoveanu G, Teodosiu C, Robu B (2015) Environmental-impact and risk quantification based on selected water quality indicators. Nat Hazards 75(1):89\u0026ndash;105\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRagab A, Ramzy A (2023) Cradle-to-Gate Lifecycle-assessment of Bottle-to-Bottle Recycling Plant: Case-study. In: Wohlgemuth V, Naumann S, Behrens G, Arndt HK, H\u0026ouml;b M (eds) Advances and New Trends in Environmental Informatics. ENVIROINFO 2022. Springer, Cham\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVerband der Automobilindustrie (VDA) (2023) Sustainability in the German automotive industry: A roadmap for the future\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eISO 14040 (2006a) Environmental Management - Lifecycle-assessment - Principles and Framework. Geneva\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eISO 14040 (2006b) Environmental Management - Lifecycle-assessment - Requirements and Guidelines. Geneva\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSoo VK, Doolan M, Compston P, Duflou JR, Peeters J, Umeda Y (2021) The influence of end-of-life regulation on vehicle material circularity: A comparison of Europe, Japan, Australia and the US. Resources, Conservation \u0026amp; Recycling. 168, Article 105294\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSable S, Ikar M, Dudheinamdar P (2024) Exploring the Complexities and Challenges of Plastic Recycling: A Comprehensive Research Review. In: Sumesh, M., R. S. Tavares, J.M., Vettivel, S.C., Oliveira, M.O. (eds) 2nd International Conference on Smart Sustainable Materials and Technologies (ICSSMT 2023). Advances in Science, Technology \u0026amp; Innovation. Springer, Cham\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVusić D, Vujanić F, Pešić K, Šafran B, Jurišić V, Zečić Ž (2021) Variability of normative properties of wood chips and implications for quality control. Energies 14(13):3789\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEUCAR (1998) Eucar-automotive LCA guidelines- phase 2 (982185). Lynne Ridge, Rover Group Ltd. (Coordinator\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBieker G et al (2021) A global comparison of the lifecycle greenhouse gas emissions of combustion engine and electric passenger cars. ICCT \u0026ndash; International Council on Clean Transportation Europe\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrabowski A, Selke SEM, Auras R (2015) Lifecycle inventory data-quality issues for bioplastics feedstocks. Int J Lifecycle-assessment 20:584\u0026ndash;596\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGross electricity production in Germany in (2022) Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.destatis.de/EN/Themes/Economic-Sectors-Enterprises/Energy/Production/Tables/gross-electricity\u003c/span\u003e\u003cspan address=\"https://www.destatis.de/EN/Themes/Economic-Sectors-Enterprises/Energy/Production/Tables/gross-electricity\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShabbir H, Gheewala SH (2023) Lifecycle-assessment for sustainability assessment of biofuels and bioproducts. Biofuel Res J 10(1):1810\u0026ndash;1815\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eU.S. Energy Information Administration. (n.d.). Wind explained: Wind energy and the environment. 1000 Independence Ave., SW Washington, DC\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJaśkiewicz A, Kasprzyk J (2023) The right to clean air is a unique form of the right to environmental protection, international and national regulations. Environ Prot 45(2\u0026ndash;4):46\u0026ndash;60\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBuban DJ, Relano R-J, Concepcion R, Culaba A (2023) Cradle-to-Gate Environmental-impact Assessment of a Polylactic Acid Polymer-Based Adjustable Air Stone for Adjustable Microbubbles Generation. 2023 IEEE 15th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), Coron, Palawan, Philippines, 1\u0026ndash;6\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrenz J, Ostermann M, K\u0026auml;sewieter K, Cerdas F, Marten T, Herrmann C, Tr\u0026ouml;ster T (2023) Integrating Prospective LCA in the Development of Automotive Components. Sustainability 15(13):10041\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKumar PL, Chaudhary V, Gupta P, Mehta J, Gupta K (2024) Inherent roadmap in the synthesis and applications of sustainable materials using oil-based and microbial polymers. Mater Today Sustain 25:100615\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZuiderveen E, Kuipers JJ, Caldeira C (2023) \u0026amp; others. The potential of emerging bio-based products to reduce environmental-impacts. Nature Communications, 14, 8521\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrunklaus B, Riise E (2018) Bio-based Materials Within the Circular-economy: Opportunities and Challenges. In: Benetto E, Gericke K, Guiton M (eds) Designing Sustainable Technologies, Products and Policies. Springer, Cham, pp 43\u0026ndash;47\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKorhonen J, Honkasalo A, Sepp\u0026auml;l\u0026auml; J (2018) Circular-economy: the concept and its limitations. J Clean Prod 175:544\u0026ndash;552\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMalabi Eberhardt LC, van Stijn A, Nygaard Rasmussen F, Birkved M, Birgisdottir H (2020) Development of a Lifecycle-assessment Allocation Approach for Circular-economy in the Built Environment. Sustainability 12(22):9579\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLevasseur A, Lesage P, Margni M, Deschenes L, Samson R (2010) Considering time in LCA: Dynamic LCA and its application to global warming impact assessments. Environ Sci Technol 44:3169\u0026ndash;3174\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarkatos DN, Pantelakis SG (2022) Assessment of the impact of material-selection on aviation sustainability from a circular-economy perspective. Aerospace 9(2):52\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGhosh A, Roy A (2020) Renewable and Sustainable Materials in the Automotive Industry. Encyclopedia of Renewable and Sustainable Materials, vol 3. Elsevier, pp 162\u0026ndash;179\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaiti S, Islam MR, Uddin MA, Afroj S, Eichhorn SJ (2022) Sustainable Fiber-Reinforced Composites: A Review. Adv sustainable Syst 6(11):2200258\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eM\u0026uuml;ller LJ, K\u0026auml;telh\u0026ouml;n A, Bachmann M, Zimmermann A, Sternberg A, Bardow A (2020) A Guideline for Lifecycle-assessment of Carbon-Capture and Utilization. Front Energy Res 8(15):1\u0026ndash;20\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoberts M, Cascione V, Allen S, Dams B, Maskell D, Coley D (2022) Applying lifecycle-assessment with minimal information to support early-stage material-selection. Acta Polytechnica CTU Proceedings, 38, 44\u0026ndash;49\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHe X, Su D, Cai W, Pehlken A, Zhang G, Wang A, Xiao J (2021) Influence of material-selection and product design on automotive vehicle recyclability. Sustainability 13(6):3407\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoucher-Lambert N, Goridkov N, Wang Y (2023) Challenges in extracting insights from lifecycle-assessment documents during early-stage design. Proceedings of the Design Society, 3, 837\u0026ndash;846\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNguyen T (2023) Climate effects of post-use wood materials from the building sector in a system perspective. Waste Manag 170:317\u0026ndash;328\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang L, Na Z (2020) The lignin-based phenolic resin was modified with whisker silicon for its application. J Bioresources Bioprod 5(1):67\u0026ndash;77\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eParaskevas D, Kellens K, Dewulf W, Duflou JR (2015) Environmental modelling of aluminium recycling: A Lifecycle-assessment tool for sustainable metal management. Resources, Conservation and Recycling, 102, 59\u0026ndash;70\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFalcone PM, Morone P, Sica E (2021) Greening the construction industry: The role of green public procurement and lifecycle costing in circular-economy transition. J Clean Prod 323:129023\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePihkola H, Pajula T, Tapia C, Smith L (2016) Sustainability assessment methods and tools to support decision-making in the process industries. VTT Technical Research Center of Finland, Tecnalia Research, and Innovation. SAMT Deliverable 3.1\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePanda H, Sahu RK, Biswal B, Mahapatra SS (2016) Lifecycle-assessment for cleaner production: A case-study of a woven fabric manufacturing industry. J Clean Prod 112:1233\u0026ndash;1241\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRebitzer G, Stepnicka K et al (2021) Advances in Lifecycle-assessment methods and applications. Int J Lifecycle-assessment 26(5):1103\u0026ndash;1116\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRocca R, Acerbi F, Fumagalli L (2023) Development of an LCA-based tool to assess the environmental sustainability level of cosmetics products. Int J Lifecycle Assess 28:1261\u0026ndash;1285\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSoukka R, J\u0026auml;rv S, Liikanen M, Gr\u0026ouml;nman K Environmental-impacts of lignin-based resin in plywood production (, Thesis MS (2023) Lappeenranta\u0026ndash;Lahti University of Technology LUT, LUT School of Energy Systems Environmental Technology\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSkosana S, Khoathane C, Malwela T (2025) Driving towards sustainability: A review of natural fiber reinforced polymer composites for eco-friendly automotive light-weighting. J Thermoplast Compos Mater 38(2):754\u0026ndash;780\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInalegwu OS, Liu S (2021) Integration of algae cultivation to anaerobic digestion for biofuel and bioenergy production. Adv Bioenergy 6(1):199\u0026ndash;300\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWinter S, Quernheim N, Arnemann L, Anderl R, Schleich B (2023) Framework for comparison of product carbon footprints of different manufacturing scenarios. Proceedings of the Design Society, 3, 1935\u0026ndash;1944\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNordahl SL, Scown CD (2024) Recommendations for life-cycle assessment of recyclable plastics in a circular-economy. Chem Sci 15:9397\u0026ndash;9407\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePersson A, Ramamoorthy SK, Skrifvars M (2015) A review of natural fibers used in biocomposites: Plant, animal, and regenerated cellulose fibers. Polym Rev 55:107\u0026ndash;162\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSuh SC, Kim YC (2020) Data needs and challenges for lifecycle-assessment (LCA) of emerging materials. Environ Sci Technol 54:24\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eabrizi TB, Brambilla A (2019) Toward LCA-lite: A simplified tool to easily apply LCA logic at the early design-stage of building in Australia. Eur J Sustainable Dev 8(5):383\u0026ndash;396\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIEA (2022) The role of critical minerals in clean energy transitions\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSuhariyanto TT, Wahab DA, Raham MN (2017) Multi-Lifecycle-assessment for sustainable products: A systematic review. J Clean Prod 165:677\u0026ndash;696\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeiden University and CML-IA Characterization Factors (2023) CML-IA characterization factors\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUlrich AE (2019) Cadmium governance in Europe\u0026rsquo;s phosphate fertilizers: Not so fast? Sci Total Environ 650:541\u0026ndash;545\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"clean-technologies-and-environmental-policy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ctep","sideBox":"Learn more about [Clean Technologies and Environmental Policy](https://www.springer.com/journal/10098)","snPcode":"10098","submissionUrl":"https://submission.nature.com/new-submission/10098/3","title":"Clean Technologies and Environmental Policy","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Lifecycle assessment (LCA), Closed-loop/Open-loop recycling, Early-stage, Multi-lifecycle, Cradle-reuse-grave, Automotive Industry","lastPublishedDoi":"10.21203/rs.3.rs-9148035/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9148035/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe transition toward low-carbon mobility requires material selection approaches that account for extended use cycles and cross-sector reuse pathways. However, early-stage automotive design decisions are typically informed by single-life cradle-to-grave assessments, which do not explicitly integrate reuse-induced substitution effects or multi-stage emission accounting within development timelines. This study operationalizes an integrated cradle-to-reuse-to-grave (C2R2G) assessment approach by combining established life cycle assessment (LCA), system expansion, and substitution modeling principles into an automotive-specific decision-support structure.\u003c/p\u003e \u003cp\u003eThe framework formalizes emission accounting across primary use, reuse preparation, secondary application, and end-of-life treatment, including explicit allocation and substitution parameters. A bio-based laminated veneer lumber (LVL) seat-shell is evaluated as a demonstrative case within passenger vehicle applications. Scenario modeling compares single-life, recycling, and open-loop reuse pathways under varying lifetime and energy-intensity assumptions.\u003c/p\u003e \u003cp\u003eResults indicate that reuse-driven substitution effects can significantly alter cumulative carbon footprints compared to single-life configurations, though outcomes remain highly sensitive to assumed service lifetimes, displaced material emission factors, and energy mixes in second-life sectors. Sensitivity analysis highlights key parameters influencing ranking stability and identifies boundary conditions under which reuse advantages diminish.\u003c/p\u003e \u003cp\u003eRather than proposing a new LCA methodology, this work demonstrates how established analytical components can be systematically integrated to support early-stage automotive material pathway evaluation. The approach enhances transparency in allocation choices and trade-off identification, contributing to more informed low-carbon design decisions in circular mobility systems.\u003c/p\u003e","manuscriptTitle":"An Early-Stage, Multi-Lifecycle Assessment Framework for Sustainable Material Selection in Automotive Industry","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-27 10:56:34","doi":"10.21203/rs.3.rs-9148035/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-06T16:51:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"100955988843704042989476696446832329706","date":"2026-04-22T07:44:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"209515291336294521959095945010956225434","date":"2026-04-21T14:35:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"327163717695591373867655563470154901678","date":"2026-04-21T10:25:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"246115567264774381502718868856905112973","date":"2026-04-20T04:06:11+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-19T13:40:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-24T14:29:34+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-18T04:58:45+00:00","index":"","fulltext":""},{"type":"submitted","content":"Clean Technologies and Environmental Policy","date":"2026-03-17T10:58:40+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"clean-technologies-and-environmental-policy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ctep","sideBox":"Learn more about [Clean Technologies and Environmental Policy](https://www.springer.com/journal/10098)","snPcode":"10098","submissionUrl":"https://submission.nature.com/new-submission/10098/3","title":"Clean Technologies and Environmental Policy","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"a1113320-326f-4a15-becc-ef70ad68ef93","owner":[],"postedDate":"April 27th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-06T16:51:45+00:00","index":42,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-27T10:56:36+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-27 10:56:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9148035","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9148035","identity":"rs-9148035","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}