International Journal of Life Cycle Assessment最新文献

Purpose: Agri-food systems across the globe are faced with the challenge of reducing their supply-chain emissions of greenhouse gases (GHGs) such as nitrous oxide (N₂O), carbon dioxide (CO₂), and methane (CH₄). For instance, 10% of the UK's GHG emissions are generated by agriculture, and ~ 56% of these are generated by livestock production. Numerous mitigation measures are being proposed to reduce GHG emissions from ruminants (representing 70 to 80% of total livestock emissions), particularly from beef cattle (presenting 30-40% of total livestock emissions).

Methods: To explore such potential, first, a business-as-usual (BAU) partial cradle-to-finishing farmgate scale modelling framework was developed. The BAU systems (i.e. steady-state productivity based on primary data from the North Wyke Farm Platform) were built using ensemble modelling wherein the RothC process-based soil organic carbon (SOC) model was integrated into the life cycle assessment (LCA) framework to conduct a trade-off analysis related to mitigation measures applicable to the study system. Potential mitigation measures were applied to the BAU scenario. The interventions assessed included: (i) extensification; (ii) adopting anaerobic digestion technology; and (iii) the use of the nitrification inhibitor DCD and substitution of fertiliser nitrogen with symbiotically fixed nitrogen from legumes.

Results: The partial carbon footprint for 1 kg of beef liveweight gain leaving the farmgate could be reduced by 7.5%, 12%, or 26% by adopting nitrification inhibitors, white clover introduction (pending establishment success), and anaerobic digestion for manure management, respectively.

Conclusions: The findings highlight the importance of including emissions beyond the farmgate level to analyse the carbon footprint of different management scenarios in order to assess the sustainability of agri-food production systems.

Supplementary information: The online version contains supplementary material available at 10.1007/s11367-025-02428-9.

Purpose: This study examines the climate impact of two surgical treatments for knee osteoarthritis, unicompartmental knee replacement (UKR) and high tibial osteotomy (HTO), also comparing conventional manufacturing (CM) with additive manufacturing (AM) for HTO. Factors beyond the implants themselves are considered that depend on the manufacturing method, such as surgical instruments and guides (jig), sterilisation, transport and anesthesia using data obtained first hand from manufacturers and a hospital.

Method: The relevance of the comparative results are maximised beyond a specific manufacturer's product by including uncertainty in the foreground and background life cycle inventories to represent uncertainty and variability of process characteristics, materials, and geographical location. The analysis is carried out in Brightway 2 using Ecoinvent inventory data and impacts are calculated across 18 mid-point categories. To consider possible improvement to the environmental impact of the surgical interventions, alternative electricity and surgical guide (jig) material scenarios are considered.

Results: The climate change impact of UKR, 37.9 (36.8-38.9) kg CO $_{2e}^{}$ , is highly significantly greater than that of the CM HTO, 10.7 (10.0-11.4) kg CO $_{2e}^{}$ , and AM HTO, 13.4 (13.0-13.7) kg CO $_{2e}^{}$ . The custom single-use surgical jig of the AM HTO and the use of potentially higher-carbon electricity leads to the AM HTO having an impact 1.25 (1.17-1.34) times higher than the CM HTO. But when low-carbon electricity is used and the surgical guide is made of stainless steel, this reduces to 0.78 (0.73-0.84). Initial screening of other lifecycle impact categories shows similar trends in most cases.

Conclusions: This study concludes that HTO has highly significantly lower climate change impact than UKR. AM HTO has the potential to further reduce the climate impact compared to CM HTO given low-carbon energy supply and further improvements in material choice and design optimisation. Challenges include limited availability in design skill-set for optimisation and higher cost for healthcare providers compared to CM HTO, although still lower than the cost of UKR. Our study highlights policy implications: along with being a solution for early treatment and yielding improved correction accuracy compared to CM HTO, personalised AM HTO also offers environmental benefits if designed and manufactured well.

Supplementary information: The online version contains supplementary material available at 10.1007/s11367-025-02473-4.

Purpose: The main aim of this study is to identify how evolutions in the electricity mix and climate change affect the LCA results of buildings regarding the multitude of environmental impacts. This is of critical importance now, and one that is likely to receive growing interest in the future. Firstly, because carbon might become a secondary environmental impact to mitigate as economies achieve decarbonisation milestones, and secondly, due to concerns around the trade-offs between the environmental impacts.

Methods: This study evaluates the lifecycle environmental impacts of a case study office building in London by considering climate change in the UK (using CIBSE weather files) and electricity mix evolution in the UK (using National Grid ESO data), EU (using EU commission data) and China that influence operational and embodied modules of LCA. Electrification of transport is also considered, reflecting the forementioned electricity mixes. A dynamic LCA approach was followed in which the inventory was modified to reflect future electricity mixes. The influence of climate evolution was considered through dynamic thermal simulations according to London's future climatic projections provided by CIBSE's weather files that were then translated into lifecycle environmental impacts through the modified inventory.

Results and discussion: Results of applying a dynamic approach in LCA show that there are several co-benefits of grid decarbonisation when it comes to the building's environmental impacts. However, ecotoxicity and land occupation might come to light. Climate change led to minor reductions in the operational electricity needs, indicating that no significant savings are to be expected in the case of actively cooled buildings without free ventilative cooling. Evolving electricity mixes do not significantly reduce material embodied impacts for this case study, showing that the reduction of lifecycle impacts cannot rely only on future electricity mix evolutions. The electrification of transport was found to have an adverse effect on the building's embodied ionising radiation impact, highlighting the importance of sourcing materials locally to avoid long transportation distances. A new type of performance gap is proposed for the building's lifecycle environmental impacts. This can be defined as 'the difference between the predicted and the actual environmental impact resulting from the mismatch between the actual case and the life cycle inventory'.

Conclusions: Future research is needed to investigate how sensitive results are to other assumptions and how improvements in material manufacturing affect the obtained results.

Purpose: A well-known limitation of conventional Life Cycle Assessment (LCA) is the lack of temporal considerations, particularly the temporal distribution and evolution of processes, emissions, and environmental responses. While these aspects have been explored to some extent in dynamic and prospective LCA, a comprehensive approach for considering both temporal distribution and evolution is currently missing. We introduce a novel framework for time-explicit LCA that integrates the temporal distribution and evolution of product systems in the Life Cycle Inventory (LCI) phase and supports dynamic characterization of emissions in the Life Cycle Impact Assessment (LCIA) phase.

Methods: The proposed approach expands the conventional LCA matrices to incorporate timing and time-based changes. We use a best-first graph traversal to derive an absolute timeline of intermediate flows by convolving relative temporal distributions at the process level. These timings are then integrated into the LCA matrices by adding time-specific row-column pairs in the technology matrix. Temporal markets are used to distribute product demands to the most-suitable processes in time-specific background databases. New rows in the biosphere matrix represent time-specific elementary flows. By preserving the timing of elementary flows during inventory calculation, time-explicit LCA enables dynamic alongside conventional LCIA. The proposed framework can be used for assessing any product system and impact category. An implementation of time-explicit LCA is provided in the open-source python package bw_timex, part of the Brightway ecosystem.

Results: We demonstrate the framework with a simplified case study of an electric vehicle (EV). For a Paris-Agreement-compatible scenario, which assumes strong decarbonization over time, time-explicit LCA determines the EV's total Global Warming Impact to be half that of a 2020 conventional LCA and nearly double that of a 2040 prospective LCA. These differences arise because time-explicit LCA uses time-specific inventory data for each timestep, depending on the timing of processes in the supply chain, contrasting the conventional or prospective cases, which rely on a single inventory database. To further demonstrate dynamic characterization, we show the instantaneous and cumulative radiative forcing over the EV life cycle.

Conclusions: Overall, time-explicit LCA can provide more representative results compared to conventional LCA, by considering when processes and emissions occur and what the state of the systems is at these timings. This is particularly valuable for long-lived products in temporally variable or fast-evolving systems. Future research should focus on filling data gaps and connecting time-explicit LCA with spatial LCA or dynamic material flow analysis.

Graphical abstract:

Purpose: We evaluate methodological approaches of different methods that can offer social assessments of product value chains. By analyzing both product-oriented social life cycle assessment (S-LCA) methods and qualitative, organization-, and project-oriented methods, we provide recommendations towards a clearer, harmonized method to better integrate the social dimension into sustainability assessments of products. This could help make S-LCA more analogous to environmental LCA (E-LCA) and more suitable for implementation in frameworks as life cycle sustainability assessment (LCSA).

Methods: We apply two quantitative S-LCA methods side-by-side with three qualitative social assessment methods on the same case-study of a textile's value chain. The two quantitative S-LCA methods adopt a quantitative functional unit (FU) approach, use similar data structures and calculation principles as E-LCA and are based on the product social impact life cycle assessment (PSILCA) database. The three qualitative methods applied include two social due diligence approaches - one based on the OECD Due Diligence and UN Guiding Principles for Business and Human Rights and the other on the IFC Performance Standards - and the Subcategory Assessment Method (SAM), a semi-quantitative performance evaluation assessment method based on the UNEP S-LCA Guidelines.

Results: None of the approaches to S-LCA described in the UNEP S-LCA Guidelines can, at present, fully achieve the equivalent goals and scope of E-LCA, specifically in the social domain. Our evaluation of five social assessment methods, including two S-LCA methods, highlights their significant differences in basic structure and logic. Consequently, results differ considerably in nature, depth, and social aspects covered. Current product-oriented S-LCA approaches encounter important limitations as they require quantifiable aspects, whereas many social impacts are often qualitative in nature. Qualitative, organization-focused methods, conversely, make it difficult to link organizational social performance to specific products. Instead, these methods are typically used for social due diligence on suppliers in the company's supply chain and cover only a small part of the product's life cycle.

Conclusion: For the purpose of computational integration, LCSA frameworks need an S-LCA method with a quantitative FU approach. However, only some S-LCA approaches are able to comply with this requirement, and these will only be able to cover a limited set of scalable quantitative impact indicators. We conclude by emphasizing the equal importance of product-oriented S-LCA and organization-oriented social assessment methods, while appreciating their fundamentally different goals and scopes.

Purpose: The construction sector, and in particular concrete, contributes substantially to global emissions, energy demand, and the extensive use of materials. To address these challenges, it is important to develop and implement strategies that reduce the environmental footprint of concrete supply chains. Understanding such impacts and the ways to mitigate them is essential. Therefore, this study focuses on analysing the impacts of decarbonisation strategies within the construction sector, with a specific focus on concrete.

Methods: A life cycle assessment (LCA) was conducted at different levels of the concrete supply chain, from the production in the United Kingdom (UK) of 1 ton of cement and 1 m³ of concrete to the construction of a building. In addition to the business-as-usual scenario, three alternative scenarios were assessed, namely cleaner electricity, in which the impact of using five different electricity grid mixes was evaluated; cleaner transportation, for which the impact of using battery-powered electric trucks and different transportation distances was assessed; and cleaner fuels, for which the impact of using alternative fuel combinations in the cement kiln was analysed. Multi-objective optimisation was used to find the optimal solution when minimising Global Warming Potential (GWP) and maximising the reduction of all the other impact categories.

Results and discussion: The results show that significant reductions (of 10 to 37%) in CO₂-eq emissions can be achieved when combining different strategies. However, certain strategies could bring an increase in other impact categories, including stratospheric ozone depletion, ionising radiation, freshwater eutrophication, and land use.

Conclusions: Adopting an electricity mix featuring substantial proportions of nuclear and wind energies, coupled with the use of biomass alongside municipal solid waste for kiln fuel, and integrating battery electric trucks, emerges as a promising alternative. However, this optimal scenario for CO₂-eq reduction might not align with the best outcomes across all impact categories. Specific attention is warranted, particularly regarding nuclear sources for electricity and increasing land use due to expanding renewable energy sources.

Supplementary information: The online version contains supplementary material available at 10.1007/s11367-025-02537-5.

Purpose: Marine vertebrate populations have halved in the past decades, and invasive species are a major driver for this loss. While many model the spread of invasive species, a model to assess impacts of marine invasions, after introduction, has hitherto been missing. We present the first regionalized effect factors for marine invasions. These factors gauge differences in biodiversity impacts after invasions, enabling life cycle impact assessments to highlight biodiversity impacts from invasive species.

Methods: Alien species are species that are introduced by humans to ecosystems where they are not native. We combine data from the IUCN red list and the MarINvaders database to identify the potentially disappeared fraction of native species within each marine coastal ecoregion after alien introduction. The effect factors indicate the biodiversity impact from invasions per alien introduction. However, the IUCN red list has a performance bias between taxonomic groups, and both the IUCN and the harmonized citizen science data from MarINvaders have a geographic observer's bias. We address some of this bias by evaluating the number of threatened species per number of assessed species, as well as including machine-learning derived data for data deficient species.

Results and discussion: The resulting regional effect factors demonstrate high effects of invasions at high latitudes, which is in line with other findings. Our approach is founded on continuously growing citizen science data and so reflects the biases and uncertainties that follow with this uneven way of data sampling. On the other hand, the continuous data collection by citizen scientists will improve data coverage and thus improve the model. Vice versa, the model itself may be motivation for citizens scientists to collect more data.

Conclusion: The effect of marine invasions presented herein reflects current global information on the issue viewed in a perspective relevant for life cycle impact assessments. The developed effect factors can be used for further assessments that will aid decision-making for policies, industries, and consumers to work towards minimizing impacts of marine invasions and are developed to be compatible with different relevant fate factors.

Supplementary information: The online version contains supplementary material available at 10.1007/s11367-024-02325-7.