Driven by individualisation as a trend and enabled by new production technologies and increasing digitalisation, mass customisation (MC) and mass personalisation (MP) open up new possibilities to address user demands much better. However, the sustainability achievements of current manufacturing technology could be compromised by this trend as variability in environmental impacts increases. Small lot sizes are likely to increase per piece manufacturing efforts, and reusability and recyclability might be limited. Nevertheless, personalised products can address user demands much better and hold great sustainability potential as well. In order to manage these risks and potentials, sustainability assessments are necessary. This paper first provides a short overview of the current state of sustainability assessment in the field based on existing literature and the current discussion in the scientific community. To contribute to filling the existing gap in the application of sustainability assessments by providing further quantitative results, Life Cycle Assessment (LCA) is applied to two conceptual MC/MP examples. Operationalised by the carbon footprint, the environmental impacts of customer choices are quantified for the analysed scenarios. The examples are within the field of mobility, one examining return logistics of personalised consumer products, the other analysing lowcarbon vehicle choices based on individual driving behaviour. The aim of this paper is to contribute to embedding LCA as a methodology for the assessment of environmental sustainability in the area of MC and MP and add qualitative assessment to support existing sustainability frameworks in the field.

A material flow model for the production of Bifacial Selective Emitter 60-cell p-type Cz PERC (Passivated Emitter and Rear Contacted) glass-backsheet modules with aluminium frame was built. The selected module represents mature technologies in the PV industry and their manufacturing is considered to take place in China in a production cluster with an annual module capacity of 5 GWp. In a first step, data acquisition and validation for wafer, cell and module fabs took place. The data were used to generate the reference system lifecycle inventories (LCI) and extended waste databases for the reference wafers, cells and modules. A set of potential circularity actions, such as the vertical integration of the operations and waste revalorisation strategies, had been proposed and their environmental performance and cost assessed by means of a life cycle assessment (LCA) and a total cost of ownership (TCO). Our results show that 87% of the waste can be reduced and revalorised, this represents a circular flow of raw materials of 18,756 Mg per year from a 5GWp PV module production cluster. Environmental impact reductions of 0.6–2.3% are estimated for different impact categories. We also estimate a cost reduction potential of 2.59% from total module costs.

Growing environmental awareness in society increasingly influences individual everyday decisions, such as which product to buy or how to sustainably use it. Yet, available information to support these decisions is often limited, or difficult to understand particularly regarding sustainability. Effective ways of communicating environmental impacts of individual decisions are required to close this gap. While Life Cycle Assessment (LCA) is an established tool to evaluate environmental impacts of products and services and support environmental decision-making, the results are typically standardized and based on statistical or averaged data. However, for individuals, this information might be irrelevant, as it neglects personal situation, behavior, information need, or individual level of expertise. In tackling those central issues of personalization in LCA, this article focuses on two main questions: How can individual aspects be addressed in LCA and at which stages of the methodology can LCA be personalized? For this purpose, the ISO 14040/44 standards are analyzed regarding individuality, and current approaches in literature are presented. In an explorative approach, this research identifies two general approaches of personalizing LCA. A personalized Life Cycle Inventory (LCI) enables evaluating the environmental impacts of personal(ized) products and conditions. A broader personalization approach based on the flexibility of the methodological framework of LCA aims at providing understandable and relevant results for individual stakeholders. This article provides an overview, outlines key aspects of this vision, and points out further research needs to bring the concept into application.

Life Cycle Assessment (LCA) is a powerful and sophisticated tool to gain deep understanding of the environmental hotspots and optimization potentials of products. Yet, its cost-intensive manual data engineering and analysis workflows restrain its wider application in eco-design, green procurement, supply chain management, sustainable investment or other relevant business processes. Especially for large product portfolios and increasing reporting requirements, traditional LCA workflows and tools often fail to provide the necessary scalability. The Sustainability Data Science Life Cycle (S-DSLC) is a concept for workflow automation for multi-purpose LCA of large product portfolios. The concept integrates the frameworks of LCA, the cross-industry standard process for data mining (CRISP-DM), and the Data Science Life Cycle (DSLC). Key aspects of the concept are deep business-, stakeholder and user-understanding, deployment of LCA results in interactive browser tools (i.e. LCA-dashboards and Guided Analytics) tailored to the needs of individual roles and business processes, as well as the automation of data preparation, model generation and Life Cycle Impact Assessment based on modern data analytic tools. The demonstration of the concept shows substantial scalability improvements for dealing with large product portfolios and broad application of LCA results in various business processes.

Biosurfactants are considered as an environmentally friendly and sustainable alternative to conventional fossil-derived and chemically produced surfactants. Their production pathways, physicochemical properties, and applications are widely researched and discussed in literature. In this context, investigating the different impacts from the entire life cycle of biosurfactants is important to understand and mitigate potential environmental hotspots. Life Cycle Assessment (LCA) is an internationally accepted and standardized methodology to analyze the environmental impacts of products from a holistic view. Therefore, this study provides a detailed overview of existing LCA studies of biosurfactants by means of a systematic literature research. The focus specifically lies on articles that investigated microbial biosurfactants. However, the systematic approach used ensured a broader overview related to bio-based surfactants as well. Furthermore, two related topics, ecotoxicity and biodegradability of biosurfactants, were identified and discussed based on the search findings. After screening over 2,500 documents using Scopus and Google Scholar, six relevant LCA articles of biosurfactants could be identified. The identified articles are divided into LCA studies of alkyl polyglycosides, chemically produced bio-based surfactants, and LCA studies of microbial biosurfactants, their content analyzed and discussed in context. In conclusion, the number of available LCA studies is very limited and their results are often not comparable. To the best of the authors’ knowledge, this review is the first of its kind to provide a detailed overview of LCA studies of biosurfactants. Consequently, the need for implementing more LCA studies becomes clear. Graphical Abstract