Decarbonizing steel production requires adopting low-carbon technologies and the efficient use of available resources, yet the effects of such a transition on the metabolism of the plant remain underexplored. This study applies a prospective plant-level Material Flow Analysis (MFA) to assess the transition from the conventional blast furnace–basic oxygen furnace route to hydrogen (H2)-based Direct Reduced Iron (DRI), Electric Arc Furnace (EAF) steelmaking, and hydrogen combustion in the rolling mill, in combination with resource efficiency interventions. Using a Swedish case study, we quantify material, energy, and carbon flows across the production chain under different decarbonization strategies. The results show up to 89
The steel industry is fundamental to global infrastructure but faces pressure to reduce its resource consumption and environmental footprint, particularly regarding climate change. This study proposes a multi-objective, multi-level cleaner production (CP) evaluation framework that integrates a full life-cycle perspective with a dedicated carbon reduction dimension. Grounded in industrial ecology, the framework uses life-cycle assessment to define the system boundary and screen indicators, and multi-criteria decision analysis for scoring. We operationalize the framework and demonstrate its practical application through a case study of China’s steel industry, the world’s largest producer. The framework moves beyond traditional pollution-and resource-focused metrics by integrating life-cycle thinking and carbon reduction as a core criterion. We constructed the system through a policy review, life-cycle inventory analysis and expert consultation, and used an improved analytic hierarchy process to determine weights and fuzzy comprehensive evaluation for scoring. A case study at Baosteel showed that the framework is practical and revealed a significant improvement in CP performance: the score rose from 62.68 (Domestic Poor) in 2014 to 86.39 (Domestic Advanced) in 2021. The evaluation identified critical shortcomings in carbon reduction and product life-cycle management, leading to specific, actionable recommendations. This work demonstrates the framework’s potential and usefulness as a proof-of-concept, offering a preliminary tool that could, with further contextualization and testing, help the steel industry to move toward sustainable production under carbon constraints. The findings are based on a single Chinese case and thus require cautious interpretation until validated across broader industrial and geographical contexts.
The photovoltaic supply chain is complex and geographically concentrated. Assessing the impacts of policies targeting it requires models that explicitly represent supply-chain structure. While process-based life-cycle assessment truncates economy-wide effects and top-down input–output models are too aggregated to resolve individual manufacturing stages, our study develops a hybrid framework integrating a process-based PV supply chain model into the multi-regional input–output accounting structure of EXIOBASE. The model is first verified against reference literature ranges of solar electricity carbon footprints and producer prices, showing literature-consistent results that purely top-down models miss by omitting productive capital. The framework is applied to the Net Zero Industry Act, a major European Union (EU) reshoring policy, under a scenario where 40
Promoting regional sustainable development requires improving both ecological efficiency and resilience of critical resource systems. Among these, the energy system plays a central role due to its dominant contribution to resource consumption and carbon emissions. However, there remains a lack of integrated research on network ecological efficiency (NEE) and network ecological resilience (NER) of energy systems in China. To address this gap, this study adopts a regional metabolism perspective to conceptualize regions as interconnected nodes linked through energy and carbon flows. This perspective is operationalized using environmentally extended multi-regional input–output (EE-MRIO) tables for 2010, 2012, 2015, and 2017 to quantify interregional energy consumption and carbon emission flows. Based on this, an NEE measurement model is developed to evaluate the relative efficiency performance of energy networks, while social network analysis (SNA) is employed to characterize network structure and assess NER. The results show a wide variation in NEE values across regions in 2017, with the Sichuan-Jiangsu path demonstrating the highest resource flow efficiency. Over time, NEE shows a trend toward regional differentiation, with some regions showing higher efficiency than others. The study also reveals that China’s energy network is organized hierarchically, with significant variation in regional connections and accessibility. Most adjacent areas are more interconnected, while the number of nodes in isolated areas is low. The results reveal significant spatial externalities in both regional NEE and NER throughout China. Based on these findings, policy recommendations are made to improve regional ecological efficiency and resilience of energy networks, focusing on enhancing cross-regional collaboration, optimizing ecological governance, and strengthening resilience in vulnerable areas.
The fashion industry, a leading contributor to carbon emissions, faces sustainability challenges despite extensive adoption of circular economy (CE) principles in the literature. While cradle-to-cradle (C2C) and closed-loop systems (CLS) are also corresponding pillars for sustainability, their integration with CE to reflect their systematic impact remains underexplored. This study extracted 110 peer-reviewed studies to examine how CE, C2C, and CLS are applied across fashion supply chains. Moving beyond descriptive mapping, this study integrates an industrial ecological framework with technological readiness level (TRL) to assess where and why circular interventions succeed or face barriers across the product lifecycle. The findings show that current policy environments fail to connect early-stage CE concepts at TRL 1–4, with the technical realities of material and operational closure in C2C and CLS at TRL 4–6. The misalignment, compounded by regulatory inertia, inhibits progression towards large-scale applications. This study directly addresses a critical mid-TRL bottleneck caused by regulatory and infrastructure inertia, along with fragmented implementation across the supply chain actors. By mapping circular strategies to TRLs and lifecycle stages, this study provides actionable pathways for policymakers and industry stakeholders to accelerate system-level, scalable circular transitions in the fashion sector.
Plastic packaging is a critical component of contemporary production and consumption systems, but it also represents a major challenge for circular economy implementation. Although prior studies have examined practices such as redesign, recycling, and material substitution, less attention has been given to the system-level conditions that enable or constrain circularity across value chains. Drawing on Global Value Chain and Global Production Network perspectives, we analyze how transaction complexity, codification requirements, capability gaps, and extra-firm institutional conditions shape circular upgrading pathways in the Brazilian plastic packaging industry. Empirically, the study is based on an in-depth qualitative case study using semi-structured interviews with actors across the value chain, supported by secondary data. The findings identify three uneven pathways: design and material upgrading led by focal firms, process upgrading associated with internal efficiency and loop control, and network-dependent recovery and recirculation. While firm-controlled pathways are more readily implemented, network-dependent pathways remain constrained by infrastructural deficiencies, informality, and regulatory limitations. The study shows that circularity depends not only on firm-level initiatives, but also on broader technical, organizational, and institutional arrangements.
Substitution can help avoid environmental impacts when preferring low impact technologies and feedstocks. The substitution benefit is typically assessed using life cycle assessment (LCA). However, LCA only quantifies the environmental impacts of product systems, while approaches from the field of economics are required to quantify the displacement rate (DR)—the market response that a change in the production of one product has on the production of alternative products. Substitution only occurs in comparison to a counterfactual and therefore remains essentially unobservable. This study introduces a novel approach with the aim of radically reducing the uncertainty of DR estimates. System dynamics modeling is adopted allowing the DRs to be quantified by recreating alternative histories in addition to future shocks. The approach is applied to the global textile fiber market. While the backward- and forward-looking scenarios yielded similar results, the former were essential in relieving the uncertainty associated with the latter. The results show that substitution occurs mainly between regenerated cellulosic fibers (RCFs) and cotton, whereas RCFs and cotton are mostly unaffected by changes in the production and price of synthetic fibers. Overall, a one-unit increase in the production of one fiber leads to a 0–32
Circular economy (CE) strategies are increasingly expected to enhance resilience under geopolitical volatility, supply disruption, and critical-material insecurity. Yet CE–resilience research reports heterogeneous findings: circularity may reduce vulnerability, create brittleness, or do both under different conditions. This article argues that these findings become intelligible once specified resilience is distinguished from general resilience. CE strategies can strengthen specified resilience by reducing exposure to identifiable disruptions such as material scarcity, import dependence, or supply-chain interruption. At the same time, efficiency-oriented circularity may weaken general resilience when it narrows response diversity, reduces slack, increases coupling, or creates dependence on specialized recovery infrastructures. We explain this ambiguity by conceptualizing Circular Resilience as the governance of system options: collectively valuable capacities that preserve alternative courses of action under disturbance. Using ordonomics as an analytical lens, the framework connects operational circularity, governance, and legitimation. The article contributes to CE–resilience scholarship by showing how circularity can simultaneously enhance specified resilience and threaten general resilience, and why preserving system options depends on governance and legitimation.
A systems-level understanding of livestock production and its environmental consequences is essential for informing sustainability transitions and evidence-based policy in Europe. While life cycle assessment (LCA) is widely applied in this context, the use of consequential LCA (CLCA), which aims to capture market-mediated and structural system responses, remains comparatively limited. This study provides a critical synthesis of CLCA applications in European livestock systems through a PRISMA-guided systematic literature review complemented by an expert workshop. Twenty-three studies met the inclusion criteria, spanning multiple livestock groups, regions, and modelling approaches. Scenario development was dominated by technical or management-oriented adjustments, with limited use of optimisation-based, narrative, or policy-driven frameworks capable of exploring transformative system changes. Inventory construction typically relied on Ecoinvent, supplemented where necessary by experimental datasets, expert elicitation, survey data, or outputs from economic models. Most studies focused on midpoint indicators, and although uncertainty analysis was commonly included, its implementation was inconsistent across studies. Overall, most of the reviewed CLCA applications remain focused on incremental improvements within existing systems, limiting their ability to assess the consequences of more profound system transitions. Key limitations include both methodological challenges (particularly in scenario formulation and the representation of system-wide responses) and data gaps, notably the limited availability of regionally specific inventory data for marginal processes and endpoint characterisation factors. We recommend that future CLCAs adopt more structured and forward-looking scenario development approaches, strengthen inventory construction through updated and localised datasets, and consider the incorporation of both midpoint and endpoint indicators, while clearly acknowledging the limitations of both approaches. In addition, the systematic application of sensitivity and scenario-based uncertainty analysis is essential for assessing robustness. Addressing these practical and methodological dimensions will enhance the contribution of CLCA to analysing sustainability transitions of European livestock systems.
The five-node resource nexus is a recognized framework covering energy, minerals, land, water, and food concurrently. However, most current models lack the scope to cover all the nodes. Furthermore, the absence of a long-term global perspective limits our understanding of future resource interrelations. The current study introduces an integrated assessment model (IAM) designed to fill these resource coverage and temporal gaps. By integrating a water resource model and human health impacts via water supply shortages into our IAM, we successfully capture the interrelations across all five nodes. The model comprehensively covers consequential impacts by resource use, such as climate change, local air pollution, land use and its change, mineral resources, and so forth. The framework utilizes a hybrid approach, integrating four resource-balance models and a Life Cycle Impact Assessment (LCIA) model into a macro-economic structure with social welfare maximization. The study results clarified causal chains that start from a carbon budget, which does not appear in the five-node nexus, to reach land and energy resources. Each chain arrives not only through food but also through bio-resources (biodiversity) and minerals. The chain from food to water resources causes the most significant changes in water. The lifecycle impact assessment model enables us to clarify impacts on human health. We conclude that our modeling approach can address interrelations in all the five-node nexus.
Life cycle assessment (LCA) is increasingly used to evaluate the environmental performance of buildings under climate-related hazards. However, current approaches assume constant service delivery over time and represent disturbances primarily through additional environmental burdens (e.g., repair and replacement), limiting their ability to capture resilience. This study aims to examine how resilience dimensions are currently operationalized in building LCA and to propose a methodological framework that enables their full integration. A systematic review of 40 original LCA studies spanning four hazard types (heat, flood, wind, and seismic) reveals that while resilience is commonly defined in terms of functionality loss and recovery, LCA studies largely neglect variations in service delivery over time and concentrate on robustness, particularly in preparation and recovery phases. Other dimensions (rapidity, redundancy, and resourcefulness) remain systematically unrepresented due to static functional units and constrained system boundaries. To address this limitation, this paper introduces a resilience-extended LCA (RES-LCA) that redefines the functional unit as time-integrated functionality, representing the cumulative service actually delivered over the building life cycle under disturbance. This reformulation captures both the magnitude and duration of performance loss and establishes a logical basis for extending the LCA inventory to include compensatory service flows during periods of impaired function, post-event improvement works, and avoided environmental burdens attributable to resilience investments. This paper demonstrates that the commonly assumed trade-off between resilience and sustainability is, in part, an artifact of conventional LCA formulations that undercount the environmental costs of service disruption.
The aim of this study is to contribute to the methodological development of social life cycle assessment (S-LCA) by using controversy mapping (CM), a qualitative social science method. CM is applied with life cycle thinking (LCT) to gain an understanding of what CM can add to S-LCA. The limitations of traditional S-LCA are that it rarely includes actors or social impacts that are not directly part of any product life cycle stage. Both methods can be used to study aspects of social acceptance, but social acceptance as an impact subcategory has not been widely applied in S-LCA case studies. To achieve this goal, a case study of the Finnish battery material industry was conducted using CM. Data were collected from local and national online news media and analyzed using qualitative coding. Currently, S-LCA often excludes important aspects such as local history-related social constructions and diverse actors focusing only on a narrow part of the product value chain. These aspects can be recognized with CM, which can be used as a complementary approach with S-LCA. The results indicate that social acceptance can be linked to multiple S-LCA impact subcategories and can be affected by the fairness experienced in social procedures. Thus, a separate social acceptance S-LCA subcategory is proposed. This study focused on social acceptance, but the social sciences also offer other opportunities for S-LCA development that could be studied in the future.
The prime objective of this study is to develop a cost-based sensitivity analysis of recycling perovskite solar module glass and to project future glass availability for recycling in Europe. To do this, we use global average prices data and an extended bottom-up cost model, with modifications to account for the recycling of perovskite photovoltaic glass. We conduct sensitivity analyses with 0, 2, and 5
The carbon footprint of electricity is a critical metric for climate policy and corporate sustainability reporting, yet its quantification is hampered by a lack of methodological consensus and a fragmented evidence base. This fragmentation reflects a central debate in industrial ecology regarding the consistency and comparability of life-cycle-based emission factors across different modelling paradigms. This study addresses this gap by performing a systematic, quantitative comparison of electricity emission factors from a wide range of authoritative sources, including process-LCA databases (Ecoinvent), environmentally extended input–output tables (EXIOBASE, EMERGING, EORA, GLORIA, GTAP), primary agency data (IEA), and others. We harmonize technology taxonomies and GHG characterization factors to compare technology-level and national-level emission factors for the EU and the US. Our findings indicate that, for technology-specific emission factors, there is a moderate level of agreement regarding direct operational emissions (direct carbon intensity). However, we observe substantial and systematic variation when it comes to full life-cycle carbon intensity. These discrepancies propagate to national-level estimates, where a country’s calculated carbon intensity can significantly vary, solely based on the data source chosen. This paper provides a useful reference to deconstruct and understand such divergences. We operationalize these findings into a set of practical selection criteria that enable analysts and decision-makers to make transparent and context-appropriate choices. We conclude that a more transparent and critical approach to sourcing emission data is fundamental to the credibility of carbon accounting and the broader energy transition.
This study investigates Türkiye’s export-embodied CO2 emissions and efficiency using an environmentally extended input–output framework and the Multi-Stage Hypothetical Extraction Method. The analysis focuses on major partners: France, Germany, Iraq, Italy, the UK, and the US. By decomposing exports into intermediate and final goods and disaggregating final demand into household, government, and investment channels, the research traces emissions along domestic production stages. The results reveal a systemic deterioration in CO2 efficiency across most destinations. While intermediate goods typically dominate the emissions profile, the UK exhibits a broad reliance on both intermediate and final goods. Furthermore, efficiency responses are partner-specific; state-procured government expenditures drive intense liabilities in France and Italy via petroleum and chemical sectors, while acting as deep systemic dependencies in Iraq and the US within utility and heavy manufacturing sectors. Findings document a highly concentrated structure where textiles, transport equipment, petroleum-chemical products, and electricity and gas provisions account for the dominant shares of efficiency effects. This evidence underscores the necessity for targeted, partner-specific industrial policies and technological investments to mitigate carbon leakage and enhance environmental performance in these key economic sectors.
Accurate estimates of building material stocks (BMS) are critical for advancing circular economy strategies. The widely used material intensity (MI) method applies fixed values per square meter and therefore overlooks variations introduced by architectural design. To assess the sensitivity of MI-based estimates to design parameters—a question difficult to address with real-world data—we developed an automated workflow that combines parametric modeling and deep learning to generate synthetic building datasets and calculate their component-based material stocks. We generated 48,600 residential buildings, all with a constant gross floor area (GFA) of 2,400 m^2 , while systematically varying footprint shape, corridor type, number of units, room layout, number of floors, and structural system configuration. Statistical analysis reveals that within this controlled design space, even under identical GFA, total material stock ranges from 758 to 2,888 m^3 . Multiple regression analysis shows that number of floors and structural system configuration exert the strongest influence, followed by footprint shape and number of units, while corridor type and room layout contribute only marginally. These results demonstrate how component-based approaches can be used to assess design-induced variability in MI-based estimates. The findings also provide guidance on when MI values may require design-specific refinement by considering dominant design parameters.
This paper applies a spatial lens to conceptualise circular economy (CE) transition within the framework of urban green infrastructure (UGI) in the global South, where this interplay remains underexplored. Extending the CE transition thinking beyond the Global North, the paper argues that current conceptualisations of CE transition in the Global South cannot be separated from the UGI politics. This article advocates looking beyond a generic conception of CE transition towards a spatialised approach, where UGI is central to CE transition in the global South. Drawing on an extensive literature review, the paper utilises empirical cases from the global South to initiate spatial discussions and establish a guiding framework for integrating the urban greenery agenda into cities’ circular economy transitions. Using the concept of CE transition landscapes, the article proposes an alternative approach to understanding CE transitions and the conceptualisations of the UGI-CE transition nexus in Global South settings.
The study examines how strategic considerations influence green relocation decisions for value chain steps in energy-intensive industries located in renewable energy resource-scarce regions. The empirical analysis draws on 66 semi-structured interviews with experienced managers and experts from steel, chemical, and renewable energy sectors worldwide, but from a European perspective. The results reveal three recent global tendencies: a slowed yet ongoing sustainable transition, increasing cost pressures, and growing national ambitions to achieve energy and resource independence. In this context, both local green hydrogen production and large-scale hydrogen imports ultimately prove unfeasible in the long term for energy-intensive industries located in renewable energy resource-scarce regions in Europe. Instead, importing intermediates and semi-finished products like hot-briquetted iron and green urea from renewable energy resource-rich regions emerges as strategically favorable. This leads to a policy-supported tripartite strategy for European energy-intensive industries: consolidating high-quality downstream production, maintaining minimal full value chain capacity in renewable energy resource-rich European regions (e.g., Nordics, Iberia), and globally diversifying upstream imports through green relocation. Canada, the Middle East, and leading African/South American countries emerge as prime targets via a novel value chain positioning model derived from existing literature. The study contributes to the literature by enhancing understanding of an evolving industrial ecology characterized by reconfigured value chains and material flows, highlighting strategic considerations that extend beyond the research’s empirical scope. It offers directions for future research and provides actionable guidance for policymakers and firms navigating green industrial transitions.
Operational life cycle assessments (LCAs) of campus buildings often use static electricity backgrounds, under-specified scenarios, and limited uncertainty treatment, reducing their usefulness for routine decarbonisation decisions. This study presents a prospective, attributional, location-based workflow for annual building operations. The case study is the Advanced Engineering Building at the University of Queensland, and the functional unit is one building-year. A 2 × 2 scenario design compares two factors: the electricity background (current Queensland mix versus Queensland-2050) and municipal solid-waste diversion (approximately 64
