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The cosmetics industry is facing growing pressure to offer more sustainable products, which can be tackled by applying eco-design. This article aims to present the Sustainable Product Optimization Tool (SPOT) methodology developed by L’Oréal to eco-design its cosmetic products and the strategies adopted for its implementation while presenting the challenges encountered along the way. The SPOT methodology is based on the life cycle assessment (LCA) of a finished product and its subsystems (formula, packaging, manufacturing and distribution). Several environmental indicators are assessed, normalized and weighted based on the planetary boundaries concept, and then aggregated into a single footprint. A product sustainability index (a single rating, easy to interpret) is then obtained by merging the environmental product rating derived from the single environmental footprint with the social rating (not covered here). The use of the SPOT method is shown by two case studies. The implementation of SPOT, based on specific strategic and managerial measures (corporate and brand targets, Key Performance Indicators, and financial incentives) is discussed. These measures have enabled L’Oréal to have 97% of their products stated as eco-designed in 2022. SPOT shows how eco-design can be implemented on a large scale without compromising scientific robustness. Eco-design tools must strike the right balance between the complexity of the LCA and the ease of interpretation of the results, and have a robust implementation plan to ensure a successful eco-design strategy.

Hybrid life cycle assessment (HLCA) strives to combine process‐based life cycle assessment (PLCA) and environmentally extended input–output (EEIO) analysis to bridge gaps of both methodologies. The recent development of HLCA databases constitutes a major step forward in achieving complete system coverage. Nevertheless, current applications of HLCA still suffer from issues related to incompleteness of the inventory and data gaps: (1) hybridization without endogenizing the capital inputs of the EEIO database leads to underestimations, (2) the unreliability of price data hinders the application of streamlined HLCA for processes in some sectors, and (3) the sparse coverage of pollutants in multiregional EEIO databases limits the application of HLCA to a handful of impact categories. This paper aims at offering a methodology for tackling these issues in a streamlined manner and visualizing their effects on impact scores across an entire PLCA database and multiple impact categories. Data reconciliation algorithms are demonstrated on the PLCA database ecoinvent3.5 and the multiregional EEIO database EXIOBASE3. Instead of performing hybridization solely with annual product requirements, this hybridization approach incorporates endogenized capital requirements, demonstrates a novel hybridization methodology to bypass issues of price unavailability, estimates new pollutants to EXIOBASE3 environmental extensions, and thus yields improved inventories characterized in terms of 13 impact categories from the IMPACT World+ methodology. The effect of hybridization on the impact score of each process of ecoinvent3.5 varied from a few percentages to three‐fold increases, depending on the impact category and the process studied, displaying in which cases hybridization should be prioritized. This article met the requirements for a Gold—Gold JIE data openness badge described at http://jie.click/badges.

Purpose Regionalized life cycle impact assessment (LCIA) has rapidly developed in the past decade, though its widespread application, robustness, and validity still face multiple challenges. Under the umbrella of UNEP/SETAC Life Cycle Initiative, a dedicated cross-cutting working group on regionalized LCIA aims to provide an overview of the status of regionalization in LCIA methods. We give guidance and recommendations to harmonize and support regionalization in LCIA for developers of LCIA methods, LCI databases, and LCA software. Methods A survey of current practice among regionalized LCIA method developers was conducted. The survey included questions on chosen method’s spatial resolution and scale, the spatial resolution of input parameters, the choice of native spatial resolution and limitations, operationalization and alignment with life cycle inventory data, methods for spatial aggregation, the assessment of uncertainty from input parameters and model structure, and the variability due to spatial aggregation. Recommendations are formulated based on the survey results and extensive discussion by the authors. Results and discussion Survey results indicate that majority of regionalized LCIA models have global coverage. Native spatial resolutions are generally chosen based on the availability of global input data. Annual modeled or measured elementary flow quantities are mostly used for aggregating characterization factors (CFs) to larger spatial scales, although some use proxies, such as population counts. Aggregated CFs are mostly available at the country level. Although uncertainty due to input parameter, model structure, and spatial aggregation are available for some LCIA methods, they are rarely implemented for LCA studies. So far, there is no agreement if a finer native spatial resolution is the best way to reduce overall uncertainty. When spatially differentiated model CFs are not easily available, archetype models are sometimes

The increased demand for food production to nourish the rapidly growing human population raises serious sustainability issues for the food sector. Indeed, conventional food production lines involve processes having a significant environmental burden. Hence, the present study aims to demonstrate an environmentally sustainable process of food production. The milk protein was chosen as a model food ingredient due to its exceptional role in the human diet. The proposed innovative process of milk protein production includes bipolar membrane electrodialysis coupled with ultrafiltration (EDBM-UF). The crucial problem during the EDBM-UF of milk, such as different types of membrane fouling, was successfully solved. Moreover, the life cycle assessment of the novel EDBM-UF protein production process was carried out and compared to a conventional acid/base process. Additionally, a sensitivity test of electricity supply at different geographical locations of the world was performed since electricity is the main energy source for the EDBM-UF process and it could be derived from different sources (renewable and non-renewable). The assessment results demonstrate that the proposed electromembrane process has significant environmental benefits compared to the conventional process using chemicals independently from the electricity supply mix from all considered geographical locations. Thus, EDBM-UF could become a prospective industrial technology taking into account environmental concerns and promoting the development of healthy human society.

The increased demand for food production to nourish the rapidly growing human population raises serious sustainability issues for the food sector. Indeed, conventional food production lines involve processes having a significant environmental burden. Hence, the present study aims to demonstrate an environmentally sustainable process of food production. The milk protein was chosen as a model food ingredient due to its exceptional role in the human diet. The proposed innovative process of milk protein production includes bipolar membrane electrodialysis coupled with ultrafiltration (EDBM-UF). The crucial problem during the EDBM-UF of milk, such as different types of membrane fouling, was successfully solved. Moreover, the life cycle assessment of the novel EDBM-UF protein production process was carried out and compared to a conventional acid/base process. Additionally, a sensitivity test of electricity supply at different geographical locations of the world was performed since electricity is the main energy source for the EDBM-UF process and it could be derived from different sources (renewable and non-renewable). The assessment results demonstrate that the proposed electromembrane process has significant environmental benefits compared to the conventional process using chemicals independently from the electricity supply mix from all considered geographical locations. Thus, EDBM-UF could become a prospective industrial technology taking into account environmental concerns and promoting the development of healthy human society.

Purpose This paper addresses the need for a globally regionalized method for life cycle impact assessment (LCIA), integrating multiple state-of-the-art developments as well as damages on water and carbon areas of concern within a consistent LCIA framework. This method, named IMPACT World+, is the update of the IMPACT 2002+, LUCAS, and EDIP methods. This paper first presents the IMPACT World+ novelties and results and then analyzes the spatial variability for each regionalized impact category. Methods With IMPACT World+, we propose a midpoint-damage framework with four distinct complementary viewpoints to present an LCIA profile: (1) midpoint impacts, (2) damage impacts, (3) damages on human health, ecosystem quality, and resources & ecosystem service areas of protection, and (4) damages on water and carbon areas of concerns. Most of the regional impact categories have been spatially resolved and all the long-term impact categories have been subdivided between shorter-term damages (over the 100 years after the emission) and long-term damages. The IMPACT World+ method integrates developments in the following categories, all structured according to fate (or competition/scarcity), exposure, exposure response, and severity: (a) Complementary to the global warming potential (GWP100), the IPCC Global Temperature Potentials (GTP100) are used as a proxy for climate change long-term impacts at midpoint. At damage level, shorter-term damages (over the first 100 years after emission) are also differentiated from long-term damages. (b) Marine acidification impact is based on the same fate model as climate change, combined with the H+ concentration affecting 50% of the exposed species. (c) For mineral resources depletion impact, the material competition scarcity index is applied as a midpoint indicator. (d) Terrestrial and freshwater acidification impact assessment combines, at a resolution of 2° × 2.5° (latitude × longitude), global atmospheric source-deposition relationships wi

Purpose Regionalization in life cycle assessment (LCA) aims to increase the representativeness of LCA results and reduce the uncertainty due to spatial variability. It may refer to adapting processes to better account for regional technological specificities (inventory regionalization) or adding of spatial information to the elementary flows (inventory spatialization) which allow using more regionalized characterization factors. However, developing and integrating regionalization requires additional efforts for LCA practitioners and database developers that must be prioritized. Methods We propose a stepwise methodology for LCA practitioners to prioritize data collection for regionalization based on global sensitivity analysis (GSA) using Sobol indices. It involves several GSA to select the impact categories (ICs) that require further inventory data collection (IC ranking), prioritize between inventory regionalization and inventory spatialization (LCA phase ranking), and target specific data to collect. Then we propose a method to derive sector-specific recommendations using statistical tests to prioritize inventory regionalization versus spatialization and the ICs on which to focus inventory data collection. These recommendations are meant to help LCA practitioners and database developers define their strategy for regional data collection by focusing on data that have the highest potential to reduce the uncertainty of the results. Results and discussion The applicability of the methodology is illustrated through three case studies using the ecoinvent v3 database and the regionalized impact methodology IMPACT World+: one on prioritizing data collection in a single biofuel product system and two meta-analyses of all product systems in two distinct economic sectors (biofuel production and land passenger transport). Recommendations for regionalization can be derived for an economic sector and appear to be different from one economic sector to another. GSA seems to be mo

Increasing needs for decision support and advances in scientific knowledge within life cycle assessment (LCA) led to substantial efforts to provide global guidance on environmental life cycle impact assessment (LCIA) indicators under the auspices of the UNEP-SETAC Life Cycle Initiative. As part of these efforts, a dedicated task force focused on addressing several LCIA cross-cutting issues as aspects spanning several impact categories, including spatiotemporal aspects, reference states, normalization and weighting, and uncertainty assessment. Here, findings of the cross-cutting issues task force are presented along with an update of the existing UNEP-SETAC LCIA emission-to-damage framework. Specific recommendations are provided with respect to metrics for human health (Disability Adjusted Life Years, DALY) and ecosystem quality (Potentially Disappeared Fraction of species, PDF). Additionally, we stress the importance of transparent reporting of characterization models, reference states, and assumptions, in order to facilitate cross-comparison between chosen methods and indicators. We recommend developing spatially regionalized characterization models, whenever the nature of impacts shows spatial variability and related spatial data are available. Standard formats should be used for reporting spatially differentiated models, and choices regarding spatiotemporal scales should be clearly communicated. For normalization, we recommend using external normalization references. Over the next two years, the task force will continue its effort with a focus on providing guidance for LCA practitioners on how to use the UNEP-SETAC LCIA framework as well as for method developers on how to consistently extend and further improve this framework.

Purpose Consequential life cycle assessment (C-LCA) aims to assess the environmental consequences of a decision. It differs from traditional LCA because its inventory includes all the processes affected by the decision which are identified by accounting for causal links (physical, economic, etc.). However, C-LCA results could be quite uncertain which makes the interpretation phase harder. Therefore, strategies to assess and reduce uncertainty in C-LCA are needed. Part of uncertainty in C-LCA is due to spatial variability that can be reduced using regionalization. However, regionalization can be complex and time-consuming if straightforwardly applied to an entire LCA model. Methods The main purpose of this article is to prioritize regionalization efforts to enhance interpretation in C-LCA by assessing the spatial uncertainty of a case study building on a partial equilibrium economic model. Three specific objectives are derived: (1) perform a C-LCA case study of alternative transportation scenarios to investigate the benefits of implementing a public policy for energy transition in France by 2050 with an uncertainty analysis to explore the strength of our conclusions, (2) perform global sensitivity analyses to identify and quantify the main sources of spatial uncertainty between foreground inventory model from partial equilibrium economic modeling, background inventory model and characterization factors, (3) propose a strategy to reduce the spatial uncertainty for our C-LCA case study by prioritizing regionalization. Results and discussion Results show that the implementation of alternative transport scenarios in compliance with public policy for the energy transition in France is beneficial for some impact categories (ICs) (global warming, marine acidification, marine eutrophication, terrestrial acidification, thermally polluted water, photochemical oxidant formation, and particulate matter formation), with a confidence level of 95%. For other ICs, uncertainty reduct