Life cycle thinking is increasingly seen as a key concept for ensuring a transition towards more sustainable production and consumption patterns. As food production systems and consumption patterns ...are among the leading drivers of impacts on the environment, it is important to assess and improve food-related supply chains as much as possible. Over the years, life cycle assessment has been used extensively to assess agricultural systems and food processing and manufacturing activities, and compare alternatives “from field to fork” and through to food waste management. Notwithstanding the efforts, several methodological aspects of life cycle assessment still need further improvement in order to ensure adequate and robust support for decision making in both business and policy development contexts. This paper discusses the challenges for life cycle assessment arising from the complexity of food systems, and recommends research priorities for both scientific development and improvements in practical implementation. In summary, the intrinsic variability of food production systems requires dedicated modelling approaches, including addressing issues related to: the distinction between technosphere and ecosphere; the most appropriate functional unit; the multi-functionality of biological systems; and the modelling of the emissions and how this links with life cycle impact assessment. Also, data availability and interpretation of the results are two issues requiring further attention, including how to account for consumer behaviour.
•Life cycle thinking is needed for more sustainable food supply chains.•An overview of challenges for improving the robustness of LCA results is provided.•Research needs at the modelling, inventory and impact assessment level are identified.•Complexity of food systems and supply chains requires food-tailored methods in LCA.•Capitalisation of knowledge from different disciplines is key for future development.
In recent literature, prospective application of life cycle assessment (LCA) at low technology readiness levels (TRL) has gained immense interest for its potential to enable development of emerging ...technologies with improved environmental performances. However, limited data, uncertain functionality, scale up issues and uncertainties make it very challenging for the standard LCA guidelines to evaluate emerging technologies and requires methodological advances in the current LCA framework. In this paper, we review published literature to identify major methodological challenges and key research efforts to resolve these issues with a focus on recent developments in five major areas: cross‐study comparability, data availability and quality, scale‐up issues, uncertainty and uncertainty communication, and assessment time. We also provide a number of recommendations for future research to support the evaluation of emerging technologies at low technology readiness levels: (a) the development of a consistent framework and reporting methods for LCA of emerging technologies; (b) the integration of other tools with LCA, such as multicriteria decision analysis, risk analysis, technoeconomic analysis; and (c) the development of a data repository for emerging materials, processes, and technologies.
Purpose
In addition to the Guidelines for the social life-cycle assessment of products (S-LCA) (Benoît and Mazijn
2009
), there are several other methodological frameworks in this field. In recent ...S-LCA literature reviews, much attention has been paid to how performances or impacts should be or are measured (i.e., life-cycle impact assessment) in existing S-LCA studies. In this review, we focus on what is measured (i.e., assessment criteria and indicators C&I) and on the definition and selection of these C&I.
Methods
We conduct a review of existing S-LCA frameworks in order to understand (i) the origin, selection, and applicability of C (ii) the purpose of the assessment and the assessed phenomena as reflected in the indicators; and (iii) the scope of C&I of the topics, life-cycle stages, and stakeholders.
Results and discussion
Based on our review, we identify 14 distinct S-LCA frameworks, for which we propose a classification according to the rationale behind the definition and selection of C&I: value-based, context-oriented, theory-structured, impact-based, and applicability-oriented. While authors of the frameworks agree with the purpose of supporting decision-making, the assessed phenomena are quite diverse among the frameworks. However, given the mixed character of the indicators, we cannot draw a clear line between frameworks assessing practices or performances and frameworks assessing effects or impacts. Lastly, our review highlights the uneven coverage of the stakeholder, life-cycle stages and topics in the S-LCA frameworks and confirms that the use stage and the relations between value chain actors receive less attention than the production stage.
Conclusions
Our comparative review not only confirms the diverse nature of S-LCA frameworks but also highlights their specificities, common features, and potential areas for improvement. We encourage the use of assessment criteria that are legitimate and meaningful for stakeholders. In addition, given the S-LCA promise to provide a holistic assessment, the variables included should be envisaged as elements of a product system and that must be branded according to their position in relation to other elements. In addition, we recommend for LCIA the combination of type I and type II assessment, including further research on impact pathways, that could link these meaningful and legitimate criteria with further impacts and related stressors in order to strengthen the capacity of S-LCA to contribute to sustainability management.
Purpose
Weighting in life cycle assessment (LCA) incorporates stakeholder preferences in the decision-making process of comparative LCAs. Research efforts on this topic are concerned with deriving ...weights according to different principles, but few studies have evaluated the relationship between normalization and weights and their effect on single scores. We evaluate the sensitivity of aggregation methods to weights in different life cycle impact assessment (LCIA) methods to provide insight on the receptiveness of single score results to value systems.
Methods
Sensitivity to weights in two LCIA methods is assessed by exploring weight spaces stochastically and evaluating the rank of alternatives via the Rank Acceptability Index (RAI). We assess two aggregation methods: a weighted sum based on externally normalized scores and a method of internal normalization based on outranking across CML-IA and ReCipE midpoint impact assessment. The RAI represents the likelihood that an alternative occupies a certain rank given all possible weight spaces, and it can be used to compare the sensitivity of final ranks to weight values in each aggregation method and LCIA. Evaluation is based on a case study of a comparative LCA of five PV technologies whose inventory is readily available in Ecoinvent.
Results and discussion
Influence of weights in single scores depend on the scaling/normalization step more than the value of the weight itself. In each LCIA, aggregated results from a weighted sum with external normalization references show a higher weight insensitivity in RAI than outranking-based aggregation because in the former, results are driven by a few dominant impact categories due to the normalization procedure. Differences in sensitivity are caused by the notable variety (up two orders of magnitude) in the scales of normalized values for the weighted sum with external normalization and intrinsic properties of the methods including compensation and a lack of accounting for mutual differences.
Conclusions
Contrary to the belief that the choice of weights is decisive in aggregation of LCIA results, in this case study, it is shown that the normalization step has the greatest influence in the results. This point holds for EU and World references in ReCiPe and CML-IA alike. Aggregation consisting of outranking generates rank orderings with a more balanced contribution of impact categories and sensitivity to weights’ values as opposed to weighted sum approaches that rely on external normalization references.
Recommendations
Practitioners aiming to include stakeholder values in single scores for LCIA should be aware of how the weights are treated in the aggregation method as to ensure proper representation of values.
The production of resources e.g., copper (Cu) has induced many environmental issues worldwide, due to the growing demand to satisfy the world growing population. China, as the largest Cu production ...country in the world, deserves a special attention. However, the Life Cycle Assessment (LCA)-based environmental profile of Cu produced in China remains unclear due to insufficient representativeness, inconsistency of methodologies applied, and absence of reliable upstream datasets. In the present study, this critical gap was filled using globally harmonized LCA methodologies and facility-level data, technologically representing 77% of China's total Cu production capacity, with consideration of environmental burden embedded in upstream raw materials. Environmental issues were prioritized using LCA weighting and normalization method, while key contributing factors were identified via Life Cycle Impact Assessment (LCIA). Weighted and normalized results showed that Global Warming Potential (GWP) was found to be the priority issue whose contribution to the overall environmental impact reached up to 47%. LCIA results demonstrated that the environmental impacts of China Cu production were primarily caused by production process of raw materials (51%–66%), followed by fuels used for transport by sea and land (11%–22%) and electricity consumption (5%–12%), depending on impact categories. Based on the study results and the importance of GWP, special attention was given to energy systems and direct GWP relevant emissions, by investigating smelting technologies. Five ways towards a more environmentally improved Cu industry associated with the challenges to be addressed were put forward in the outlook (e.g., the use of green electricity can effectively reduce CO2 emission by 14%–29%).
Sustainable crop production is critical to address the grand challenges of climate change and food security, and eco-efficiency is increasingly used to assess systems sustainability. Sugarcane is a ...major high biomass, high input sugar and bioenergy crop but with a relatively large carbon footprint. China is the third largest sugarcane producing country. However, its production eco-efficiency remains unclear. A reliable assessment of sugarcane crop production eco-efficiency is necessary to identify the most important targets and effective strategies to improve its economic and environmental outputs.
This study aimed to i) establish an eco-efficiency assessment model framework suitable for sugarcane crop production system in general, ii) quantify the eco-efficiency of sugarcane production in China, and iii) propose strategies to improve sugarcane crop productivity, sustainability and economic profit, while reducing its environmental cost.
Here, based on farmer survey data, we combined life cycle assessment (LCA) and data envelopment analysis (DEA) to determine eco-efficiency and sustainability of small-holder sugarcane farm production system in southern China. Six modelling approaches, including both input- and output-oriented, were used to assess sugarcane agriculture eco-efficiency.
An output-oriented DEA model with yield and profit as desirable and carbon footprint as undesirable outputs proved to be superior to the other approaches for sugarcane production eco-efficiency assessment. The estimated average eco-efficiency of plant (first year) and ratoon (second year) crops were 0.803 and 0.869, respectively. Under this model, yield and profit were increased by 16.6% and 180% for plant crop, and 9.62% and 38.2% for ratoon crop, respectively, with a substantial reduction, up to 28%, in carbon footprint. The farm performance analysis indicated that the most eco-efficient farmers had large farms with crop rotation systems, lower fertiliser input, a relatively higher education, more acceptance of new farming practices and products, and better access to agriculture resources, compared with eco-inefficient farmers.
Adopting the model outputs reported here will help eco-inefficient farmers to narrow their productivity gap, increase profit and make Chinese sugarcane farming more eco-efficient. This is the first report of eco-efficiency and sustainability assessment in sugarcane production using LCA + DEA framework, with potential for adopting it to other agricultural systems.
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•This is the first report of eco-efficiency and sustainability assessment of sugarcane production using LCA + DEA framework.•Farm survey data from southern China were used to determine efficient strategies for sustainable sugarcane production.•A output-oriented four-step LCA + DEA model is the best among six models tested.•Implementing model-predicted efficient system changes will increase profit by 90% and reduce carbon footprint by 26%.•Higher farmer education, better access to agri-resources, larger farms, crop rotation and low nitrogen input mostly account for eco-efficiency.
•Life cycle assessment based on feeding experiments of black soldier flies.•Soybean meal and fishmeal less harmful than insect-derived protein in most cases.•Energy and non-residue insect diets ...contribute greatly to environmental impacts.•Alternative energy and residue-feed sources only part of the solution.
Life cycle assessment (LCA) was applied to evaluate black soldier fly production using different diets, including typical Belgian agro-residues (Brussels sprout stems, endive roots and solid fraction pig manure). The LCA compared insect-based feed with soybean meal and fishmeal, and composting through insects versus conventional treatments. Underlying LCA data were derived through feeding experiments. To determine the sensitivity of the results, we tested the effect of alternative energy sources and dietary components.
Non-residue insect feed and energy use contributed greatly to overall environmental impacts. Insect protein had greater impacts than protein from soybean meal or fishmeal due to the high energy consumption and, in some cases, agro-product demands. These should be areas of focus to make European insect production more sustainable. In the case of Brussels sprout stems and endive roots, conventional treatments outperformed composting by insects. Between industrial versus insect pig manure composting, the results varied greatly by energy source and impact category.
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This work has calculated the organisational environmental and social footprint of the University of the Basque Country (UPV/EHU) in 2016. First, input and output data flows of the UPV/EHU activity ...were collected. Next, the environmental and social impacts of the academic activity were modelled, using the Ecoinvent 3.3 database with the PSILCA-based Soca v1 module in openLCA software. In order to evaluate the environmental impacts, CML and ReCiPe LCIA methods were used. The Social Impact Weighting Method was adjusted for the assessment of specific social impacts.
The modelling has identified some hotspots in the organisation. The contribution of transport (8,900 km per user, annually) is close to 60% in most of the environmental impacts considered. The life cycle of computers stands out among the impacts derived from the consumption of material products. More than half of environmental impacts are located outside the Basque Country. This work has also made it possible to estimate some of the impacts of the organisational social footprint, such as accidents at work, only some of which occur at the UPV/EHU. Traces of child labour and illiteracy have also been detected in the social footprint that supports the activity of the UPV/EHU. Some of the social and environmental impacts analysed are not directly generated by the UPV/EHU, but they all demand attention and co-responsibility.
Based on the modelling performed, this work explores alternative scenarios and recommends some improvement actions which may reduce (in some cases over 30%) the environmental and social impacts of the UPV/EHU's activity. These scenarios and improvement actions will feed a process with stakeholders in the UPV/EHU based on the Multi-criteria Decision Analysis (MCDA) methodology.
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•The environmental and social footprint of the UPV/EHU was calculated.•Three campuses, with different transport needs, and around 47,000 users in the year 2016.•Impacts were modelled using Ecoinvent 3.3 and Soca (PSILCA) databases in openLCA software.•More than half of the environmental impacts derive from transport needs.•Most of the environmental impacts are located outside the Basque Country.
•Life cycle assessment of a new nuclear power plant in Europe.•Three methods used: process-based, input-output, and hybrid life cycle assessment.•Results range from 8 to 64 gCO2e/kWhe.•Averages for ...the three methods are 16.97, 24.89 and 27.63 gCO2e/kWhe.•Results are higher than generally accepted figures for nuclear energy.
Nuclear energy contributes ~10% of the global electricity generation and different views exist on its carbon-intensity and sustainability. Context is crucial to determine the sustainability of new nuclear power generators, making the existence of a global answer to the unresolved question unlikely. This study aims to establish the life-cycle greenhouse gas emissions associated with nuclear energy in Europe given ongoing construction of nuclear generators. Due to the high uncertainty and complexity that characterise construction and operation of nuclear generators, we adopt a multi-method, scenario-based approach. The three methods used are: process-based, input-output, and hybrid life cycle assessment. Scenarios account for different total energy outputs over the life cycle of the nuclear generator, different end of life options, and different sectoral allocations of costs in the input-output calculus. Results for the process-based, input-output, and hybrid methods range between 16.55–17.69, 18.82–35.15, and 24.61–32.74 gCO2e/kWh, respectively. These are either well above or at the upper end of the range of possibilities (5 to 22 gCO2e/kWh) stated in a report for the UK’s Committee on Climate Change, and significantly higher than the median value of 12 gCO2e/kWh presented by the Intergovernmental Panel on Climate Change. They are also higher than the values acknowledged by the nuclear industry. Given the severe potential lock-in effects of today’s energy choices for future generations, this research questions the role of nuclear energy to meet the UN Sustainable Development Goals and calls for further scrutiny on its sustainability and environmental viability.
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