Horsemeat is consumed in several world regions, including Asia and Europe. Belgium has reported high horsemeat consumption per capita in Europe, while also acting as a major importer and re-exporter. Horsemeat is a lean, protein-rich meat type, often described as environmentally sustainable. Nonetheless, evidence on its environmental impacts remains scarce. This study addressed this gap through a cradle-to-retail-shelf attributional life cycle assessment of horsemeat. The assessment quantified the environmental impacts of horsemeat sourced from end-of-life horses that performed non-food functions (e.g., leisure and draft), entering the food chain burden-free under a cut-off approach. Environmental accounting commenced at the mandatory six-month quarantine for drug clearance. Six supply chains were modelled for fresh and frozen horsemeat from Canada, Argentina, and Uruguay. Primary data from collection centres and slaughterhouses were combined with Agribalyse and ecoinvent databases in SimaPro. Impacts were calculated in mass and protein terms for 1 kg of horsemeat and 100 g of horsemeat protein at the Belgian retail shelf using the Environmental Footprint 3.1 method and economic allocation between horsemeat and co-products. Sea-freighted frozen horsemeat showed a more favourable environmental profile than fresh horsemeat, which relies partly on carbon and resource-intensive air transport. The production stage, dominated by the quarantine period, was the most impactful, followed by distribution. Lower-input systems in Argentina and Uruguay - characterised by grass-feeding, shorter accumulation times and wind-powered water pumps - result in lower impacts. Climate change and marine eutrophication were significant impact categories (≈ 40
With the rapid growth of the global population and rising food demand, aquaculture plays a key role in meeting protein demand while facing pressure to become more efficient and sustainable. Polyculture, where multiple species are farmed together, is often regarded as a Nature-based Solution (NbS). The study assessed and compared the environmental performances and economic feasibility of two different tilapia production systems: (1) tilapia monoculture and (2) tilapia-whiteleg shrimp polyculture. Life Cycle Assessment (LCA) was used to assess the environmental impacts of both systems. The scope of the study is cradle-to-farm gate, covering the nursery, grow-out, and harvesting stages. An uncertainty analysis was also performed to assess the robustness of the results. Economic feasibility was evaluated using Net Present Value (NPV) and the Benefit-Cost Ratio (BCR). The study further examined the influence of feed type and production intensity on overall system performance. The findings revealed that tilapia-whiteleg shrimp polyculture is generally more environmentally and economically favorable. However, these systems often require larger pond areas and longer production cycles, resulting in higher water consumption compared to tilapia monoculture. Environmental impacts can be further reduced by using alternative or homemade feed, as feed is the largest contributor to most impact categories. Economically, polyculture improved farm profitability by diversifying outputs and eliminating additional shrimp feed costs, while alternative feeds further lowered input costs and financial risks. Production intensity also affected environmental performance; extensive systems are not always better than intensive ones, as efficiency (e.g., feed conversion ratio) determines the impacts per tonne. In summary, tilapia-whiteleg shrimp polyculture, which use the benefits from natural processes and functions, can enhance resource efficiency, reduce environmental impacts, and lower risks of crop failure and financial loss, showing its feasibility as an NbS. However, further research is needed to assess additional dimensions, such as ecosystem services and biodiversity outcomes.
The valorization of herbal residue (HR) through biochar production and return-to-field application represents a promising pathway for sustainable biomass waste management. Biochar can be applied as a soil amendment and compost additive, both showing significant environmental potential. However, systematic comparisons of the ecological, environmental, and economic (3E) performance of these strategies still remains insufficient. Therefore, this study developed a thermodynamic-ecological life cycle assessment framework to compare return-to-field strategies and support sustainable HR management. A comprehensive assessment framework was developed to compare four return-to-field strategies: direct application of biochar, compost product, biochar-modified compost product, and their combined application. Based on industrial data and literature sources, the life cycle system boundary covered upstream Chinese patent medicine production, HR collection, treatment, and return-to-field application. The functional unit was defined as 1 ton of HR treated. The framework integrates life cycle assessment (LCA), entropy increase analysis, and ecological cumulative exergy consumption (ECEC) to evaluate environmental impacts, system irreversibility, and resource-use efficiency. Among the four scenarios, direct application of biochar demonstrated the best environmental performance, achieving a net-negative carbon emissions of -14.80 kg CO2 eq/t HR, mainly attributed to reduced process emissions and enhanced soil carbon sequestration. It also showed the lowest acidification (1.54 kg SO2 eq/t HR) and eutrophication potentials (0.24 kg Phosphate eq/t HR). In contrast, compost product application resulted in the highest environmental burdens due to associated biogenic gas releases. From a system sustainability perspective, the combined application strategy exhibited the optimal overall performance, with the lowest ECEC (2.85E + 15 sej/t), negative entropy generation (-8.46 MJ/K), and superior integrated 3E performance. Sensitivity analysis further revealed that improving biochar yield and carbon stability were among the most influential parameters affecting greenhouse gas mitigation performance. This study established a quantitative, system-level framework for evaluating HR management strategies. Results showed that biochar-based pathways significantly improved environmental performance through emissions reduction and enhanced carbon sequestration, while the co-application of biochar and compost product achieved the most balanced overall performance. More broadly, the framework provides a transferable approach for assessing circular economy strategies across environmental, economic, energy, and ecological dimensions, supporting system-oriented circular economy development.
Racial discrimination remains a pervasive social issue but is not systematically addressed in current social life cycle assessment (S-LCA) frameworks. Existing guidelines cover general discrimination only under the subcategory equal opportunities/discrimination for the stakeholder group worker, which is insufficient, as racial discrimination can occur across supply chains and affect multiple stakeholder groups. This study reviewed S-LCA guiding documents and databases to assess current coverage and to identify gaps. Based on these findings and incorporation of interdisciplinary evidence on racial discrimination from e.g., labour psychology and healthcare, indicators were developed for workers, value chain actors, local communities, and children. They were then reviewed by international racism experts and adapted based on their feedback. 38 expert-reviewed indicators assessing racial discrimination in S-LCA were proposed and grouped into two sets: a core set representing minimum compliance with anti-racist practices and an advanced set incorporating aspirational measures aimed at addressing systemic racism. A set of reference scales was developed to facilitate implementation for practitioners. The set can be adapted to specific systems under study and local contexts. Methodological and practical challenges remain, including survey design, site-specific data availability, and risks of underreporting. This work provides the first comprehensive framework for integrating racial discrimination into S-LCA using the reference scale approach and highlights the central role of organisations in addressing racial inequities across supply chains. Next steps include the testing and optimisation of the reference scales in practical application across various sectors and geographical contexts. Future work should expand this foundational work and cover racial discrimination within the impact pathway approach.
Food waste management remains a major challenge in developing countries, while Black Soldier Fly (BSF) farming offers a promising valorization pathway despite persistent constraints in specialised systems. This study compares the environmental, social, and economic performance of integrated and specialised BSF farming systems using a Life Cycle Sustainability Assessment (LCSA) framework and examines how increasing levels of system integration through aquaculture, vegetable cultivation, and agritourism affect sustainability performance and associated trade-offs across production scenarios. A comprehensive LCSA was conducted by integrating Life Cycle Assessment (LCA), Social Life Cycle Assessment (S-LCA), and Life Cycle Costing (LCC). Five production scenarios, ranging from fully integrated BSF systems (combining BSF farming, catfish aquaculture, vegetable cultivation, and agritourism) to specialised BSF farming, were assessed under a cradle-to-gate system boundary. Environmental impacts were quantified using the CML-IA Baseline method, social performance was evaluated using reference-scale S-LCIA across multiple stakeholder groups, and economic performance was analysed through engineering-based life cycle costing with a ten-year analysis period. The results indicate that greater system integration does not consistently reduce environmental impacts, as the specialised BSF system records the lowest burden with the fewest processes and least electricity demand. Eutrophication remains a critical hotspot in integrated configurations, although vegetable cultivation reduces it by reusing aquaculture sludge. Social performance improves markedly with system integration, especially when agritourism is included, as it enhances knowledge transfer, community engagement, and benefit sharing. Economic results reveal increasing total costs with greater integration, with labour as the dominant cost driver. No single configuration performed best on all three pillars. The specialised BSF system had the lowest environmental impacts and costs but the weakest social performance, and the fully integrated configuration showed the reverse pattern. Reading the three pillars together, rather than separately, is therefore essential for judging these systems. Given contextual adaptation and policy support, integrated BSF farming is a workable circular-economy route for handling food waste while generating environmental and social value.
This study examines how Life Cycle Assessment (LCA) has been integrated into urban planning and applied across different urban development domains. It also explores the decision-support potential of LCA in promoting sustainability-oriented urban planning and investigates the tools, databases, and methodological approaches used in urban-scale applications. An integrative literature review was conducted following the PRISMA framework. A total of 56 peer-reviewed journal articles were systematically selected and analysed using an author-developed data extraction and coding framework. The review focused on urban application domains, planning strategies, LCA methods, software tools, database usage, and decision-support functions in urban planning processes. The findings show increasing use of LCA in urban planning, particularly in building construction, transportation, waste management, water systems, green spaces, agriculture, and environmental management. Analysis of these functional goals revealed common patterns across different domains, which were then grouped into three broad strategic approaches: Optimization, Assessment, and Prediction. The results identified three major LCA methodological approaches: commercial LCA software with built-in databases, self-built LCA evaluation processes using customized methods and datasets, and hybrid approaches integrating self-developed processes with existing LCA tools and databases, providing a comparative overview of their flexibility, usability, adoption, and practical applicability. The review also highlights the growing role of LCA as a decision-support tool for comparing planning scenarios and evaluating long-term environmental impacts. However, current applications remain constrained by inconsistent data quality, limited spatial and temporal resolution, and insufficient integration of socio-economic dimensions. Most studies continue to prioritize environmental indicators, while social and economic considerations are less systematically incorporated. LCA is becoming an important decision-support tool for sustainable urban planning, but methodological and data-related limitations continue to restrict its broader application. Improving data accessibility, methodological consistency, and the integration of socio-economic dimensions is essential to strengthen the robustness and practical relevance of urban LCA for evidence-based and sustainability-oriented planning decisions.
The use of diesel fuel in global agriculture causes over 40 megatonnes of carbon dioxide equivalents every year, highlighting the need for more sustainable alternatives. While electrification and automation of agricultural machinery represent promising pathways for sustainable farming, their environmental performance remains underrepresented. This study investigates whether electrification and automation of large agricultural machinery, both individually and in combination, can reduce the environmental footprint of agriculture. A cradle-to-grave life cycle assessment evaluates four tractor configurations: diesel and electric tractors, each with manual and autonomous operation. The analysis covers the manufacturing, maintenance, use, and end-of-life (EoL) phases over a 15-year lifetime and applies the Environmental Footprint 3.1. method, assessing 16 impact categories. In the use phase, different farm sizes and operating speed scenarios are analysed across the field activities of ploughing, sowing, and spraying. The analysis focuses on the 100-year global warming potential (GWP) to assess the effects on climate change. Electric tractors can reduce GWP by 56–57
This study presents a technical and environmental assessment of decentralized green hydrogen production for blending into existing natural gas networks to meet residential heating demand in cold-climate regions. The proposed system integrates photovoltaic (PV) energy, a proton exchange membrane electrolyzer (PEMEL), reverse osmosis water purification, multi-stage compression, and seasonal hydrogen storage. A dynamic model of the system is developed in MATLAB/Simulink using Simscape, enabling high-resolution simulations of hydrogen production, buffering, compression, and distribution processes over one year. Real thermal demand data from Ronzo-Chienis, a municipality in the Autonomous Province of Trento (Italy), are used as the primary case study. The hydrogen production plant is modelled using site-specific solar irradiance data and local thermal demand profiles, accounting for both daily and seasonal variability. Two hydrogen-blending scenarios (S1: 10
Public transportation plays a crucial role in reducing traffic congestion, greenhouse gas emissions, and social inequalities in urban systems. However, selecting the most sustainable transit bus technologies remains challenging because socio-economic conditions, geographic characteristics, and energy infrastructures vary across regions. This study aims to develop an integrated sustainability-based decision-making framework to evaluate and optimize alternative-fuel bus technologies across different urban contexts. The study proposes a novel sustainability-integrated multi-objective decision-making (SI-MODM) framework that uniquely combines three integrated components: 1) an activity-based life-cycle sustainability assessment model incorporating a battery upscale cost model for an emerging and understudied advanced solid-state battery technology, 2) systematic embedding of region-specific operational and socio-economic context across different dimensions (e.g. driving cycles, urban geography, etc.), and a multi-objective optimization model for strategic fleet planning. This integrated approach enables the first comprehensive evaluation of advanced solid-state lithium sulfur (ASSLiS) batteries for urban transit applications alongside conventional alternatives (diesel, hybrid, compressed natural gas (CNG), and battery electric buses (BEBs) powered by ASSLiS and lithium-ion nickel manganese cobalt oxide (NMC-LIB) batteries). Real-world driving cycles from four major U.S. cities, such as Atlanta, Chicago, Denver, and New York, were incorporated to capture region-specific operational conditions. The results indicate that BEBs powered by ASSLiS batteries demonstrate the lowest life-cycle carbon emission intensity among all alternatives. In addition, ASSLiS-powered BEBs achieve, on average, 2.5
Given the urgency of the cement and concrete industry to decarbonise by 2050, circular economy (CE) strategies are becoming more eminent. This study aims to identify how CE practices can contribute to lowering environmental impacts and in particular greenhouse gas (GHG) emissions in the European Union. As future developments of our socio-economic systems are inherently uncertain, the analysis also considers the effectiveness of CE measures in different types of decarbonised futures. As part of a prospective LCA (pLCA), the study defines a status quo, a future baseline scenario with a decarbonised energy system and an ambitious circular economy scenario. These are then assessed using the Environmental Footprint (EF 3.1) method for the years 2030 and 2050. To account for the inherently higher epistemic uncertainty in 2050, the ambitious CE scenario is subjected to a sensitivity analysis consisting of four normative socio-economic scenarios on the green transition. The quantification of these alternative future narratives is achieved by means of a stakeholder workshop and sensemaking session. In a final step, the results of the pLCA following the historical trajectory and the ones of the alternative futures are compared and contextualised with the agency of the involved actors. Results indicate that the ambitious CE scenario saves up to 43 Mt CO2-eq. compared to the decarbonised baseline scenario, underlining the substantial contribution of CE to decarbonisation. These savings are mainly due to CE practices related to reduce (33
Life cycle assessment (LCA) is increasingly applied to evaluate emerging biobased materials; however, its use is often constrained by fragmented, inconsistent, and incomplete life cycle inventory (LCI) data. Industrial hemp is representative of such materials, as historical regulatory barriers and heterogeneous study assumptions have resulted in sparse and poorly harmonized product and process data, limiting the reuse and comparability of existing LCAs. This study addresses these challenges by developing harmonized datasets and LCIs. A structured literature synthesis was conducted to systematically screen and extract quantitative parameters from published studies describing upstream and midstream stages of industrial hemp production. Data were compiled for pre-harvest operations, including fertilizer use (nitrogen, phosphorus, and potassium), seeding density, harvest yield, hemp type, and geographic context. Additional data cover emissions from fertilizers to air, soil, and water, as well as water use (irrigation), agricultural machinery, diesel use, and electricity use. Post-harvest data included decortication process energy use, extraction yields for fiber and hurd, and carbon storage potential. To address data sparsity and missing parameter combinations commonly encountered during LCI development, machine learning (ML) is demonstrated as a supporting data-augmentation and gap-filling approach, using hemp yield as an illustrative case. The datasets compiled for the upstream and midstream stages consolidate the key material and energy flows required to build screening-level LCIs for industrial hemp. Reported cultivation inputs and yields exhibited substantial variability across studies, with nitrogen application ranging from 37 to 300 kg/ha and biomass yields from 2,200 to 31,300 kg/ha. Decortication energy demand ranged from 1.21 to 9.63 MJ/kg of fiber, reflecting differences in agronomic practices and processing configurations. Extraction yields ranged from 20
Artificial intelligence (AI), and particularly generative AI (GenAI), has expanded rapidly in recent years. Although its environmental impacts might be significant, they remain poorly understood and the application of life cycle assessment (LCA) to AI technologies remains in its early stages. The aim of this study is to quantify the life cycle climate impact of an AI-generated radio station named KSPR, marking the first LCA of a system composed of a variety of AI models. In this study, LCA is applied to assess the climate impact of KSPR, which is a research prototype of an AI-generated autonomous radio application developed at KTH Royal Institute of Technology in Stockholm. The functional unit was defined as one hour of generating, broadcasting and streaming radio content. Data was obtained from real-time energy measurements, publications by AI model developers and scientific literature. Sensitivity and scenario analyses were applied to test the reliability of the results and to assess parameter as well as model uncertainties. In the baseline scenario, computer hardware production is identified as the main contributor to KSPR’s life cycle climate change impact (at about 70
This paper presents a component-based methodology for integrated eco-efficiency assessment of buildings in early design phases, when intervention potential is highest but conventional LCA and LCC require unavailable detail. Unlike simplified LCA, which approximates detailed results from reduced inputs, it operates on early-phase information and integrates economic performance into a single eco-efficiency indicator. The research question is: how can environmental and economic performance be assessed at the component level with limited early-phase information? The methodology integrates life cycle assessment (LCA) and life cycle costing (LCC) at the building component level (foundations, external walls, internal walls, floors, roof) within the ISO 14045 eco-efficiency framework. To accommodate limited information availability in early design phases, the approach employs simplified geometry determination based on building typology parameters and utilizes standardized component catalogs containing pre-calculated environmental and cost indicators. Assessment is performed for two system boundaries: modules A1–3, B4, B6, C3–C4 (without recycling potential) and the extended boundary including module D (with recycling potential), revealing sensitivity to end-of-life assumptions. A proof-of-concept application demonstrates the methodology using a hypothetical multi-family residential building with four construction variants: masonry, concrete, solid timber, and timber frame. The proof-of-concept application demonstrates the methodology’s capability to differentiate between construction alternatives, yielding eco-efficiency values ranging from − 24
Database-driven social life cycle assessment (S-LCA), supported by PSILCA and the Social Hotspots Database, distills complex social risks in global value chains into a uniform metric expressed in medium-risk hours equivalent (mrh-eq). This commentary argues that such aggregated scores should be treated strictly as screening tools to flag potential issues, not as definitive quantifications of realized social harm, and examines the methodological and policy consequences of taking the metric at face value. We pose six guiding questions that challenge recurring practices in recent applications of database-driven S-LCA, organized under four methodological themes: the weighting dilemma of using worker hours as the activity variable (Q1 and Q2), methodological vulnerability arising from data gap treatment and indicator aggregation (Q3 and Q4), the dimensional mismatch of applying labor-based weighting to non-worker stakeholders (Q5), and the macro-consequence of mrh-eq-driven decision-making (Q6). Each question is illustrated with published case studies, chiefly on battery raw material supply chains. Worker-hour weighting is functionally necessary to prevent low-value but high-risk upstream activities, such as cobalt mining, from being averaged out, yet it conflates social harm with low industrial productivity and thereby penalizes less automated economies. Treating missing data as low risk rewards opaque supply chains, and summing correlated indicators can generate artificial hotspots such as fair salary. Weighting community and societal issues by worker hours distorts risks unrelated to labor intensity. Finally, minimizing mrh-eq encourages divestment from high-risk regions, depriving vulnerable communities of development opportunities. The mrh-eq metric should serve as a screening indicator and industry baseline rather than an endpoint-like measure of social impact, with disaggregated data reported alongside any aggregated score. S-LCA practice should shift the paradigm from risk avoidance toward corporate engagement that improves local conditions and generates a positive social handprint, substantiated by primary, site-specific evidence rather than generic database data.
Emissions and resource use are influenced by soil and climate as well as by farm management. In addition, characterisation factors (CFs) used in life cycle assessment (LCA) to translate emissions and resource use into environmental impacts also depend on the location. The purpose of this study was to evaluate how regional differences in emissions, resource use, and CFs influence the variability of the environmental impacts of agricultural products from the perspective of an LCA practitioner. We examined four databases—AGRIBALYSE®, SALCA, WFLDB, and Agri-footprint®—differentiating both emissions/resource uses and their environmental impacts at the country level. Only the Agri-footprint® database had data from at least ten different countries considered sufficient for a statistical analysis. The country-specific environmental impacts of the products in Agri-footprint® were calculated according to the Swiss Agricultural Life Cycle Assessment (SALCA) method using Brightway and analysed for seven spatially explicit impact categories: water use, land occupation, terrestrial acidification, eutrophication, water scarcity, soil quality, and biodiversity. Spatial differences in emissions, resources, and CFs contributed to the spatial variability of environmental impacts at the product level. For nutrient-related impacts, such as eutrophication and acidification, the spatial variability of the contributing emissions had a stronger influence than the variability of the CFs. This is evident for marine and freshwater eutrophication, where characterisation is assumed to be uniform across all countries. For biodiversity the variability in CFs was more dominant. Most of the impact categories showed more significant positive than significant negative correlations between agricultural land occupation and the impact score. A higher yield per area thus generally leads to lower impacts per product unit. In summary, a spatial differentiation is needed if the parameters driving the impacts show high spatial variability or have a strong influence on the emission, and this emission has an important contribution to the impact. Our analysis highlighted that emission fluxes and CFs significantly influence the spatial variability of midpoint-level environmental impacts. Inventory flows exhibited greater variability than CFs, except for the land-use-related impact categories. Most impacts correlated positively with agricultural land occupation, showing a strong effect on yield levels. Our results underlined the importance of accounting for the spatial variability of emissions and CFs to adequately reflect the environmental impacts of agricultural products. The results are primarily representative of European conditions and temperate regions, as Agri-footprint® mainly includes products cultivated in Europe.
The allocation of environmental burdens in multifunctional systems remains one of the most debated methodological challenges in Life Cycle Assessment (LCA). In most applications, allocation is implemented or reported using aggregated allocation rules, which can make burden propagation less explicit and reduce result transparency. This study proposes a generalizable stage-wise bookkeeping and reporting approach that attributes burdens locally at each transformation stage, enabling traceable burden propagation and system-wide reconciliation, while supporting transparent implementation and documentation of allocation choices made under ISO 14044. The approach operates on a subdivided process model represented as discrete transformation stages (unit processes) linked by material and energy flows. For each stage, gate-to-gate impacts are calculated and normalized per unit reference flow, and stream burdens are propagated through the network and allocated at multifunctional nodes according to an explicit allocation profile. Single-rationale profiles yield footprints under that rationale, whereas mixed-rationale profiles are reported as allocation-sensitivity scenarios. Accounting closure is checked by reconciling the total system impact with the sum of product burdens. The approach is demonstrated through a sugarcane biorefinery producing sugar, ethanol, and electricity. Results show that the level of system disaggregation, internal-flow representation, and allocation strongly affect the distribution of environmental burdens among co-products. The stage-wise approach enables transparent tracing of burdens through internal flows such as steam and electricity recycling, which are often neglected in conventional LCA models. Compared with global allocation methods, the proposed approach makes the allocation profile explicit and supports traceable burden propagation and system-wide reconciliation (accounting closure) between product-level results and total system impacts. This transparency also facilitates identification of stage-level hotspots and supports more robust sensitivity analyses of allocation factors. The proposed approach supports the implementation of ISO-aligned operational modelling choices, offering a transparent, algebraic, and scalable approach for multifunctional systems. By integrating burden propagation, allocation, and accounting closure explicitly at the stage level, it enhances the interpretability and reproducibility of LCA studies. Although illustrated through a sugarcane biorefinery, the procedure is broadly transferable and applicable to other complex systems such as energy networks, food processing, and chemical production chains. The procedure is well suited to studies requiring stage-level transparency, especially when a process has shared utilities or recycled streams. The stage-wise representation can be embedded in process-systems analyses (e.g., optimization), and future work should extend it to additional impact categories, uncertainty analysis, and implementation within LCA software environments.
Carbon-footprint (CF) evidence for vineyards under warm-temperate humid climates is limited, despite strong interannual climate variability (“vintage effect”) that can reshape field operations and emissions. This study provides the first systematic CF baseline for Uruguayan vineyards and evaluates how variety, site and growing season conditions influence hotspots and mitigation priorities. We applied Life Cycle Assessment (LCA) to the agricultural phase of grape production using the LIFE-ADVICLIM methodology aligned with OIV guidance. The functional unit was one ha of productive vineyard per growing season (cradle-to-gate; for the vineyard stage) and one kg of grape. Eighteen commercial cases were compiled from three vineyards, two varieties (Tannat, Albariño) and four consecutive growing seasons (2020–2021 to 2023–2024). System boundaries included direct emissions (diesel combustion in machinery; N2O and urea-related emissions from nitrogen inputs) and indirect emissions (upstream production of inputs, machinery, irrigation components and trellis materials). Modelling used SimaPro with Ecoinvent and Agribalyse databases and the 100-year Global Warming Potential (GWP100). Emissions were separated into 10 activity groups in the grape production process. Mean CF was 1707 kg CO2 eq ha− 1 yr− 1(range 1178–2273), positioning the analyzed cases at the lower threshold of internationally reported values for the sector. Direct emissions contributed 61
Tandem photovoltaic (PV) devices such as Si/Copper Indium Gallium Selenide (CIGS) tandem architectures have the potential for higher conversion efficiency compared to single-junction silicon modules. This study evaluates the environmental performance of two emerging two-terminal (2T) Si/CIGS tandem architectures: circuitry 2T (C2T) and bonded 2T (B2T). The goal is to quantify their environmental impacts during manufacturing and identify key drivers and improvement opportunities through prospective life cycle assessment. An innovative concept designed for tandem solar cells with a 2T approach based on two technologies: Silicon Heterojunction (SHJ) and high bandgap Cu(In, Ga)(Se, S)2 (CIGS). A cradle-to-gate life cycle assessment was conducted for both C2T and B2T configurations. The study quantified the impacts per 1 kWh of generated electricity and conducted a life cycle impact assessment (LCIA) to identify the environmental hotspots of introduced technologies. The LCIA showed GWP values of 0.2203 and 0.1056 kg CO₂-eq/kWh for B2T and C2T, respectively. C2T demonstrated lower environmental impacts due to reduced energy requirements. Silicon solar cell production had the largest contribution across most impact categories. Replacing selenium with sulphur improved the results but the effect was small. Replacing ethyl-vinyl acetate with polyolefins also led to a minor improvement. The prospective analysis shows that under SSP2_RCP1.9 (targeting climate policy for carbon emissions reduction) and strong technological development, emissions fall to 0.014 kg CO₂ eq/kWh for B2T and 0.013 kg for C2T in 2050, representing a 94
Premise has been quickly adopted as a major tool for performing prospective LCAs (pLCA). Premise databases are generated by combining the ecoinvent database and data from climate change (CC) scenarios implemented in Integrated Assessment Models (IAMs). Both the extent of changes made with Premise and the focus on CC raise a question on how they affect LCA results. We aim to give practitioners better insight into how changes may affect results when using Premise databases. Our analysis of Premise consists of several steps. We begin by generating three Premise databases, one for 2020, and two for 2050 assuming different future changes: one that represents a continuation of current trajectories and policies (Base) and one that represents assuming ambitious decarbonization strategies (RCP 2.6). We analyze these databases based on 9 industrial products: Electricity, Heat, Road Transport, Steel, Aluminium, Copper, Concrete, Organic Chemical and Inorganic Chemical. We calculate results for each of them for 16 impact categories, although we focus on CC as the main driver of changes in these databases. We then assess impact change the different databases for each product. We do a contribution analysis where we analyze the contribution of 15 large groups of processes to these products. For CC, we find that impact changes for most products are related to impact reductions in electricity production and increased use of biomass and Carbon Capture and Storage. We find that Electricity, Heat, Road Transport, Steel and Concrete are primary contributors to their own respective impacts. Other products are instead mainly affected by these groups. Furthermore, the contribution from the Ore Minerals, Energy resources, Chemicals and Transport product groups is much higher when we include Indirect contributions (contributions ‘connected through’ another group, e.g. production of fuel for Transport), these product groups connect to impacts elsewhere in the system. In other impact categories we find much more varied results, though the uncertainty around these results is high, specifically ‘land use’ shows large changes in impact. Our approach can highlight products or product groups of interest in large databases like Premise, which can aid in modeling and finding errors. We suggest Premise to be used primarily for assessments of climate change impacts and practitioners clearly communicate versions and settings to make their work reproduceable. Despite us taking a critical stance toward some aspects of Premise, we still recommend using it for pLCA.
